WorldWideScience

Sample records for neighbor embedding t-sne

  1. The Galah Survey: Classification and Diagnostics with t-SNE Reduction of Spectral Information

    Energy Technology Data Exchange (ETDEWEB)

    Traven, G.; Zwitter, T.; Žerjal, M. [Faculty of Mathematics and Physics, University of Ljubljana, Jadranska 19, 1000 Ljubljana (Slovenia); Matijevič, G. [Leibniz-Institut für Astrophysik Potsdam (AIP), An der Sternwarte 16, D-14482 Potsdam (Germany); Kos, J.; Bland-Hawthorn, J.; De Silva, G.; Sharma, S. [Sydney Institute for Astronomy, School of Physics, A28, The University of Sydney, NSW 2006 (Australia); Asplund, M.; Freeman, K.; Lin, J.; Da Costa, G.; Duong, L. [Research School of Astronomy and Astrophysics, Australian National University, Canberra, ACT 2611 (Australia); Casey, A. R. [Institute of Astronomy, University of Cambridge, Madingley Road, Cambridge CB3 0HA (United Kingdom); Martell, S. L. [School of Physics, University of New South Wales, Sydney, NSW 2052 (Australia); Schlesinger, K. J. [Research School of Astronomy and Astrophysics, Mount Stromlo Observatory, Cotter Road, Weston Creek, ACT 2611 (Australia); Simpson, J. D. [Australian Astronomical Observatory, North Ryde, NSW 2113 (Australia); Zucker, D. B. [Australian Astronomical Observatory, P.O. Box 915, North Ryde, NSW 1670 (Australia); Anguiano, B. [Department of Physics and Astronomy, Macquarie University, North Ryde, NSW 2109 (Australia); Horner, J., E-mail: gregor.traven@fmf.uni-lj.si [Computational Engineering and Science Research Centre, University of Southern Queensland, Towoomba QLD 4350 (Australia); and others

    2017-02-01

    Galah is an ongoing high-resolution spectroscopic survey with the goal of disentangling the formation history of the Milky Way using the fossil remnants of disrupted star formation sites that are now dispersed around the Galaxy. It is targeting a randomly selected magnitude-limited ( V ≤ 14) sample of stars, with the goal of observing one million objects. To date, 300,000 spectra have been obtained. Not all of them are correctly processed by parameter estimation pipelines, and we need to know about them. We present a semi-automated classification scheme that identifies different types of peculiar spectral morphologies in an effort to discover and flag potentially problematic spectra and thus help to preserve the integrity of the survey results. To this end, we employ the recently developed dimensionality reduction technique t-SNE ( t -distributed stochastic neighbor embedding), which enables us to represent the complex spectral morphology in a two-dimensional projection map while still preserving the properties of the local neighborhoods of spectra. We find that the majority (178,483) of the 209,533 Galah spectra considered in this study represents normal single stars, whereas 31,050 peculiar and problematic spectra with very diverse spectral features pertaining to 28,579 stars are distributed into 10 classification categories: hot stars, cool metal-poor giants, molecular absorption bands, binary stars, H α /H β emission, H α /H β emission superimposed on absorption, H α /H β P-Cygni, H α /H β inverted P-Cygni, lithium absorption, and problematic. Classified spectra with supplementary information are presented in the catalog, indicating candidates for follow-up observations and population studies of the short-lived phases of stellar evolution.

  2. Applications and Benefits for Big Data Sets Using Tree Distances and The T-SNE Algorithm

    Science.gov (United States)

    2016-03-01

    BENEFITS FOR BIG DATA SETS USING TREE DISTANCES AND THE T-SNE ALGORITHM by Suyoung Lee March 2016 Thesis Advisor: Samuel E. Buttrey...REPORT TYPE AND DATES COVERED Master’s thesis 4. TITLE AND SUBTITLE APPLICATIONS AND BENEFITS FOR BIG DATA SETS USING TREE DISTANCES AND THE T-SNE...public release; distribution is unlimited 12b. DISTRIBUTION CODE 13. ABSTRACT (maximum 200 words ) Modern data sets often consist of unstructured data

  3. Approximated and User Steerable tSNE for Progressive Visual Analytics

    NARCIS (Netherlands)

    Pezzotti, N.; Lelieveldt, B.P.F.; van der Maaten, L.J.P.; Hollt, T.; Eisemann, E.; Vilanova Bartroli, A.

    2016-01-01

    Progressive Visual Analytics aims at improving the interactivity in existing analytics techniques by means of visualization as well as interaction with intermediate results. One key method for data analysis is dimensionality reduction, for example, to produce 2D embeddings that can be visualized and

  4. High-Dimensional Modeling for Cytometry: Building Rock Solid Models Using GemStone™ and Verity Cen-se'™ High-Definition t-SNE Mapping.

    Science.gov (United States)

    Bruce Bagwell, C

    2018-01-01

    This chapter outlines how to approach the complex tasks associated with designing models for high-dimensional cytometry data. Unlike gating approaches, modeling lends itself to automation and accounts for measurement overlap among cellular populations. Designing these models is now easier because of a new technique called high-definition t-SNE mapping. Nontrivial examples are provided that serve as a guide to create models that are consistent with data.

  5. A YOUNG ECLIPSING BINARY AND ITS LUMINOUS NEIGHBORS IN THE EMBEDDED STAR CLUSTER Sh 2-252E

    Energy Technology Data Exchange (ETDEWEB)

    Lester, Kathryn V.; Gies, Douglas R.; Guo, Zhao, E-mail: lester@chara.gsu.edu, E-mail: gies@chara.gsu.edu, E-mail: guo@chara.gsu.edu [Center for High Angular Resolution Astronomy and Department of Physics and Astronomy, Georgia State University, P.O. Box 5060, Atlanta, GA 30302-5060 (United States)

    2016-12-01

    We present a photometric and light curve analysis of an eccentric eclipsing binary in the K2 Campaign 0 field, which resides in Sh 2-252E, a young star cluster embedded in an H ii region. We describe a spectroscopic investigation of the three brightest stars in the crowded aperture to identify which is the binary system. We find that none of these stars are components of the eclipsing binary system, which must be one of the fainter nearby stars. These bright cluster members all have remarkable spectra: Sh 2-252a (EPIC 202062176) is a B0.5 V star with razor sharp absorption lines, Sh 2-252b is a Herbig A0 star with disk-like emission lines, and Sh 2-252c is a pre-main-sequence star with very red color.

  6. Spherical stochastic neighbor embedding of hyperspectral data

    CSIR Research Space (South Africa)

    Lunga, D

    2012-07-01

    Full Text Available and manifold learning in Euclidean spaces, very few attempts have focused on non-Euclidean spaces. Here, we propose a novel approach that embeds hyperspectral data, transformed into bilateral probability similarities, onto a nonlinear unit norm coordinate...

  7. NeighborHood

    OpenAIRE

    Corominola Ocaña, Víctor

    2015-01-01

    NeighborHood és una aplicació basada en el núvol, adaptable a qualsevol dispositiu (mòbil, tablet, desktop). L'objectiu d'aquesta aplicació és poder permetre als usuaris introduir a les persones del seu entorn més immediat i que aquestes persones siguin visibles per a la resta d'usuaris. NeighborHood es una aplicación basada en la nube, adaptable a cualquier dispositivo (móvil, tablet, desktop). El objetivo de esta aplicación es poder permitir a los usuarios introducir a las personas de su...

  8. Neighbors United for Health

    Science.gov (United States)

    Westhoff, Wayne W.; Corvin, Jaime; Virella, Irmarie

    2009-01-01

    Modeled upon the ecclesiastic community group concept of Latin America to unite and strengthen the bond between the Church and neighborhoods, a community-based organization created Vecinos Unidos por la Salud (Neighbors United for Health) to bring health messages into urban Latino neighborhoods. The model is based on five tenants, and incorporates…

  9. Dimensionality reduction with unsupervised nearest neighbors

    CERN Document Server

    Kramer, Oliver

    2013-01-01

    This book is devoted to a novel approach for dimensionality reduction based on the famous nearest neighbor method that is a powerful classification and regression approach. It starts with an introduction to machine learning concepts and a real-world application from the energy domain. Then, unsupervised nearest neighbors (UNN) is introduced as efficient iterative method for dimensionality reduction. Various UNN models are developed step by step, reaching from a simple iterative strategy for discrete latent spaces to a stochastic kernel-based algorithm for learning submanifolds with independent parameterizations. Extensions that allow the embedding of incomplete and noisy patterns are introduced. Various optimization approaches are compared, from evolutionary to swarm-based heuristics. Experimental comparisons to related methodologies taking into account artificial test data sets and also real-world data demonstrate the behavior of UNN in practical scenarios. The book contains numerous color figures to illustr...

  10. Embedded Systems

    Indian Academy of Sciences (India)

    Embedded system, micro-con- troller ... Embedded systems differ from general purpose computers in many ... Low cost: As embedded systems are extensively used in con- .... operating systems for the desktop computers where scheduling.

  11. Embedded Leverage

    DEFF Research Database (Denmark)

    Frazzini, Andrea; Heje Pedersen, Lasse

    find that asset classes with embedded leverage offer low risk-adjusted returns and, in the cross-section, higher embedded leverage is associated with lower returns. A portfolio which is long low-embedded-leverage securities and short high-embedded-leverage securities earns large abnormal returns...

  12. Neighboring and Urbanism: Commonality versus Friendship.

    Science.gov (United States)

    Silverman, Carol J.

    1986-01-01

    Examines a dimension of neighboring that need not assume friendship as the role model. When the model assumes only a sense of connectedness as defining neighboring, then the residential correlation, shown in many studies between urbanism and neighboring, disappears. Theories of neighboring, study variables, methods, and analysis are discussed.…

  13. Nearest neighbors by neighborhood counting.

    Science.gov (United States)

    Wang, Hui

    2006-06-01

    Finding nearest neighbors is a general idea that underlies many artificial intelligence tasks, including machine learning, data mining, natural language understanding, and information retrieval. This idea is explicitly used in the k-nearest neighbors algorithm (kNN), a popular classification method. In this paper, this idea is adopted in the development of a general methodology, neighborhood counting, for devising similarity functions. We turn our focus from neighbors to neighborhoods, a region in the data space covering the data point in question. To measure the similarity between two data points, we consider all neighborhoods that cover both data points. We propose to use the number of such neighborhoods as a measure of similarity. Neighborhood can be defined for different types of data in different ways. Here, we consider one definition of neighborhood for multivariate data and derive a formula for such similarity, called neighborhood counting measure or NCM. NCM was tested experimentally in the framework of kNN. Experiments show that NCM is generally comparable to VDM and its variants, the state-of-the-art distance functions for multivariate data, and, at the same time, is consistently better for relatively large k values. Additionally, NCM consistently outperforms HEOM (a mixture of Euclidean and Hamming distances), the "standard" and most widely used distance function for multivariate data. NCM has a computational complexity in the same order as the standard Euclidean distance function and NCM is task independent and works for numerical and categorical data in a conceptually uniform way. The neighborhood counting methodology is proven sound for multivariate data experimentally. We hope it will work for other types of data.

  14. Embedded defects

    International Nuclear Information System (INIS)

    Barriola, M.; Vachaspati, T.; Bucher, M.

    1994-01-01

    We give a prescription for embedding classical solutions and, in particular, topological defects in field theories which are invariant under symmetry groups that are not necessarily simple. After providing examples of embedded defects in field theories based on simple groups, we consider the electroweak model and show that it contains the Z string and a one-parameter family of strings called the W(α) string. It is argued that although the members of this family are gauge equivalent when considered in isolation, each member becomes physically distinct when multistring configurations are considered. We then turn to the issue of stability of embedded defects and demonstrate the instability of a large class of such solutions in the absence of bound states or condensates. The Z string is shown to be unstable for all values of the Higgs boson mass when θ W =π/4. W strings are also shown to be unstable for a large range of parameters. Embedded monopoles suffer from the Brandt-Neri-Coleman instability. Finally, we connect the electroweak string solutions to the sphaleron

  15. Identifying influential neighbors in animal flocking.

    Directory of Open Access Journals (Sweden)

    Li Jiang

    2017-11-01

    Full Text Available Schools of fish and flocks of birds can move together in synchrony and decide on new directions of movement in a seamless way. This is possible because group members constantly share directional information with their neighbors. Although detecting the directionality of other group members is known to be important to maintain cohesion, it is not clear how many neighbors each individual can simultaneously track and pay attention to, and what the spatial distribution of these influential neighbors is. Here, we address these questions on shoals of Hemigrammus rhodostomus, a species of fish exhibiting strong schooling behavior. We adopt a data-driven analysis technique based on the study of short-term directional correlations to identify which neighbors have the strongest influence over the participation of an individual in a collective U-turn event. We find that fish mainly react to one or two neighbors at a time. Moreover, we find no correlation between the distance rank of a neighbor and its likelihood to be influential. We interpret our results in terms of fish allocating sequential and selective attention to their neighbors.

  16. Identifying influential neighbors in animal flocking.

    Science.gov (United States)

    Jiang, Li; Giuggioli, Luca; Perna, Andrea; Escobedo, Ramón; Lecheval, Valentin; Sire, Clément; Han, Zhangang; Theraulaz, Guy

    2017-11-01

    Schools of fish and flocks of birds can move together in synchrony and decide on new directions of movement in a seamless way. This is possible because group members constantly share directional information with their neighbors. Although detecting the directionality of other group members is known to be important to maintain cohesion, it is not clear how many neighbors each individual can simultaneously track and pay attention to, and what the spatial distribution of these influential neighbors is. Here, we address these questions on shoals of Hemigrammus rhodostomus, a species of fish exhibiting strong schooling behavior. We adopt a data-driven analysis technique based on the study of short-term directional correlations to identify which neighbors have the strongest influence over the participation of an individual in a collective U-turn event. We find that fish mainly react to one or two neighbors at a time. Moreover, we find no correlation between the distance rank of a neighbor and its likelihood to be influential. We interpret our results in terms of fish allocating sequential and selective attention to their neighbors.

  17. Clustering Professional Basketball Players by Performance

    OpenAIRE

    Patel, Riki

    2017-01-01

    Basketball players are traditionally grouped into five distinct positions, but these designationsare quickly becoming outdated. We attempt to reclassify players into new groupsbased on personal performance in the 2016-2017 NBA regular season. Two dimensionalityreduction techniques, t-Distributed Stochastic Neighbor Embedding (t-SNE) and principalcomponent analysis (PCA), were employed to reduce 18 classic metrics down to two dimensionsfor visualization. k-means clustering discovered four grou...

  18. Embedded Hardware

    CERN Document Server

    Ganssle, Jack G; Eady, Fred; Edwards, Lewin; Katz, David J; Gentile, Rick

    2007-01-01

    The Newnes Know It All Series takes the best of what our authors have written to create hard-working desk references that will be an engineer's first port of call for key information, design techniques and rules of thumb. Guaranteed not to gather dust on a shelf!. Circuit design using microcontrollers is both a science and an art. This book covers it all. It details all of the essential theory and facts to help an engineer design a robust embedded system. Processors, memory, and the hot topic of interconnects (I/O) are completely covered. Our authors bring a wealth of experience and ideas; thi

  19. A Novel AMR-WB Speech Steganography Based on Diameter-Neighbor Codebook Partition

    Directory of Open Access Journals (Sweden)

    Junhui He

    2018-01-01

    Full Text Available Steganography is a means of covert communication without revealing the occurrence and the real purpose of communication. The adaptive multirate wideband (AMR-WB is a widely adapted format in mobile handsets and is also the recommended speech codec for VoLTE. In this paper, a novel AMR-WB speech steganography is proposed based on diameter-neighbor codebook partition algorithm. Different embedding capacity may be achieved by adjusting the iterative parameters during codebook division. The experimental results prove that the presented AMR-WB steganography may provide higher and flexible embedding capacity without inducing perceptible distortion compared with the state-of-the-art methods. With 48 iterations of cluster merging, twice the embedding capacity of complementary-neighbor-vertices-based embedding method may be obtained with a decrease of only around 2% in speech quality and much the same undetectability. Moreover, both the quality of stego speech and the security regarding statistical steganalysis are better than the recent speech steganography based on neighbor-index-division codebook partition.

  20. False-nearest-neighbors algorithm and noise-corrupted time series

    International Nuclear Information System (INIS)

    Rhodes, C.; Morari, M.

    1997-01-01

    The false-nearest-neighbors (FNN) algorithm was originally developed to determine the embedding dimension for autonomous time series. For noise-free computer-generated time series, the algorithm does a good job in predicting the embedding dimension. However, the problem of predicting the embedding dimension when the time-series data are corrupted by noise was not fully examined in the original studies of the FNN algorithm. Here it is shown that with large data sets, even small amounts of noise can lead to incorrect prediction of the embedding dimension. Surprisingly, as the length of the time series analyzed by FNN grows larger, the cause of incorrect prediction becomes more pronounced. An analysis of the effect of noise on the FNN algorithm and a solution for dealing with the effects of noise are given here. Some results on the theoretically correct choice of the FNN threshold are also presented. copyright 1997 The American Physical Society

  1. Electronic transport of molecular nanowires by considering of electron hopping energy between the second neighbors

    Directory of Open Access Journals (Sweden)

    H Rabani

    2015-07-01

    Full Text Available In this paper, we study the electronic conductance of molecular nanowires by considering the electron hopping between the first and second neighbors with the help Green’s function method at the tight-binding approach. We investigate three types of structures including linear uniform and periodic chains as well as poly(p-phenylene molecule which are embedded between two semi-infinite metallic leads. The results show that in the second neighbor approximation, the resonance, anti-resonance and Fano phenomena occur in the conductance spectra of these structures. Moreover, a new gap is observed at edge of the lead energy band wich its width depends on the value of the electron hopping energy between the second neighbors. In the systems including intrinsic gap, this hopping energy shifts the gap in the energy spectra.

  2. Recrafting the Neighbor-Joining Method

    DEFF Research Database (Denmark)

    Mailund; Brodal, Gerth Stølting; Fagerberg, Rolf

    2006-01-01

    Background: The neighbor-joining method by Saitou and Nei is a widely used method for constructing phylogenetic trees. The formulation of the method gives rise to a canonical Θ(n3) algorithm upon which all existing implementations are based. Methods: In this paper we present techniques for speeding...... up the canonical neighbor-joining method. Our algorithms construct the same phylogenetic trees as the canonical neighbor-joining method. The best-case running time of our algorithms are O(n2) but the worst-case remains O(n3). We empirically evaluate the performance of our algoritms on distance...... matrices obtained from the Pfam collection of alignments. Results: The experiments indicate that the running time of our algorithms evolve as Θ(n2) on the examined instance collection. We also compare the running time with that of the QuickTree tool, a widely used efficient implementation of the canonical...

  3. The clinic as a good corporate neighbor.

    Science.gov (United States)

    Sass, Hans-Martin

    2013-02-01

    Clinics today specialize in health repair services similar to car repair shops; procedures and prices are standardized, regulated, and inflexibly uniform. Clinics of the future have to become Health Care Centers in order to be more respected and more effective corporate neighbors in offering outreach services in health education and preventive health care. The traditional concept of care for health is much broader than repair management and includes the promotion of lay health competence and responsibility in healthy social and natural environments. The corporate profile and ethics of the clinic as a good and competitive local neighbor will have to focus on [a] better personalized care, [b] education and services in preventive care, [c] direct or web-based information and advice for general, seasonal, or age related health risks, and on developing and improving trustworthy character traits of the clinic as a corporate person and a good neighbor.

  4. Lectures on the nearest neighbor method

    CERN Document Server

    Biau, Gérard

    2015-01-01

    This text presents a wide-ranging and rigorous overview of nearest neighbor methods, one of the most important paradigms in machine learning. Now in one self-contained volume, this book systematically covers key statistical, probabilistic, combinatorial and geometric ideas for understanding, analyzing and developing nearest neighbor methods. Gérard Biau is a professor at Université Pierre et Marie Curie (Paris). Luc Devroye is a professor at the School of Computer Science at McGill University (Montreal).   .

  5. New Sliding Puzzle with Neighbors Swap Motion

    OpenAIRE

    Prihardono, Ariyanto; Kawagoe, Kenichi

    2015-01-01

    The sliding puzzles (15-puzzle, 8-puzzle, 5-puzzle) are known to have 2 kind of puz-zle: solvable puzzle and unsolvable puzzle. In this thesis, we make a new puzzle with only 1 kind of it, solvable puzzle. This new puzzle is made by adopting sliding puzzle with several additional rules from M13 puzzle; the puzzle that is formed form The Mathieu group M13. This puzzle has a movement that called a neighbors swap motion, a rule of movement that enables every neighboring points to swap. This extr...

  6. An enhanced data visualization method for diesel engine malfunction classification using multi-sensor signals.

    Science.gov (United States)

    Li, Yiqing; Wang, Yu; Zi, Yanyang; Zhang, Mingquan

    2015-10-21

    The various multi-sensor signal features from a diesel engine constitute a complex high-dimensional dataset. The non-linear dimensionality reduction method, t-distributed stochastic neighbor embedding (t-SNE), provides an effective way to implement data visualization for complex high-dimensional data. However, irrelevant features can deteriorate the performance of data visualization, and thus, should be eliminated a priori. This paper proposes a feature subset score based t-SNE (FSS-t-SNE) data visualization method to deal with the high-dimensional data that are collected from multi-sensor signals. In this method, the optimal feature subset is constructed by a feature subset score criterion. Then the high-dimensional data are visualized in 2-dimension space. According to the UCI dataset test, FSS-t-SNE can effectively improve the classification accuracy. An experiment was performed with a large power marine diesel engine to validate the proposed method for diesel engine malfunction classification. Multi-sensor signals were collected by a cylinder vibration sensor and a cylinder pressure sensor. Compared with other conventional data visualization methods, the proposed method shows good visualization performance and high classification accuracy in multi-malfunction classification of a diesel engine.

  7. Embedded Processor Laboratory

    Data.gov (United States)

    Federal Laboratory Consortium — The Embedded Processor Laboratory provides the means to design, develop, fabricate, and test embedded computers for missile guidance electronics systems in support...

  8. Recrafting the neighbor-joining method

    Directory of Open Access Journals (Sweden)

    Pedersen Christian NS

    2006-01-01

    Full Text Available Abstract Background The neighbor-joining method by Saitou and Nei is a widely used method for constructing phylogenetic trees. The formulation of the method gives rise to a canonical Θ(n3 algorithm upon which all existing implementations are based. Results In this paper we present techniques for speeding up the canonical neighbor-joining method. Our algorithms construct the same phylogenetic trees as the canonical neighbor-joining method. The best-case running time of our algorithms are O(n2 but the worst-case remains O(n3. We empirically evaluate the performance of our algoritms on distance matrices obtained from the Pfam collection of alignments. The experiments indicate that the running time of our algorithms evolve as Θ(n2 on the examined instance collection. We also compare the running time with that of the QuickTree tool, a widely used efficient implementation of the canonical neighbor-joining method. Conclusion The experiments show that our algorithms also yield a significant speed-up, already for medium sized instances.

  9. Conceptualizing Embedded Configuration

    DEFF Research Database (Denmark)

    Oddsson, Gudmundur Valur; Hvam, Lars; Lysgaard, Ole

    2006-01-01

    and services. The general idea can be named embedded configuration. In this article we intend to conceptualize embedded configuration, what it is and is not. The difference between embedded configuration, sales configuration and embedded software is explained. We will look at what is needed to make embedded...... configuration systems. That will include requirements to product modelling techniques. An example with consumer electronics will illuminate the elements of embedded configuration in settings that most can relate to. The question of where embedded configuration would be relevant is discussed, and the current...

  10. Neighbor Rupture Degree of Some Middle Graphs

    Directory of Open Access Journals (Sweden)

    Gökşen BACAK-TURAN

    2017-12-01

    Full Text Available Networks have an important place in our daily lives. Internet networks, electricity networks, water networks, transportation networks, social networks and biological networks are some of the networks we run into every aspects of our lives. A network consists of centers connected by links. A network is represented when centers and connections modelled by vertices and edges, respectively. In consequence of the failure of some centers or connection lines, measurement of the resistance of the network until the communication interrupted is called vulnerability of the network. In this study, neighbor rupture degree which is a parameter that explores the vulnerability values of the resulting graphs due to the failure of some centers of a communication network and its neighboring centers becoming nonfunctional were applied to some middle graphs and neighbor rupture degree of the $M(C_{n},$ $M(P_{n},$ $M(K_{1,n},$ $M(W_{n},$ $M(P_{n}\\times K_{2}$ and $M(C_{n}\\times K_{2}$ have been found.

  11. ACTION RECOGNITION USING SALIENT NEIGHBORING HISTOGRAMS

    DEFF Research Database (Denmark)

    Ren, Huamin; Moeslund, Thomas B.

    2013-01-01

    Combining spatio-temporal interest points with Bag-of-Words models achieves state-of-the-art performance in action recognition. However, existing methods based on “bag-ofwords” models either are too local to capture the variance in space/time or fail to solve the ambiguity problem in spatial...... and temporal dimensions. Instead, we propose a salient vocabulary construction algorithm to select visual words from a global point of view, and form compact descriptors to represent discriminative histograms in the neighborhoods. Those salient neighboring histograms are then trained to model different actions...

  12. A dumbed-down approach to unite Fermilab, its neighbors

    CERN Multimedia

    Constable, B

    2004-01-01

    "...Fermilab is reaching out to its suburban neighbors...With the nation on orange alert, Fermilab scientists no longer can sit on the front porch and invite neighbors in for coffee and quasars" (1 page).

  13. Polymorphic Embedding of DSLs

    DEFF Research Database (Denmark)

    Hofer, Christian; Ostermann, Klaus; Rendel, Tillmann

    2008-01-01

    propose polymorphic embedding of DSLs, where many different interpretations of a DSL can be provided as reusable components, and show how polymorphic embedding can be realized in the programming language Scala. With polymorphic embedding, the static type-safety, modularity, composability and rapid...

  14. Cryptosporidiosis in Saudi Arabia and neighboring countries

    International Nuclear Information System (INIS)

    Areeshi, Mohammed Y.; Hart, C.A.; Beeching, N.J.

    2007-01-01

    Cryptosporidium is a coccidian protozoan parasite of the intestinal tract that causes severe and sometimes fatal watery diarrhea in immunocompromised patients and self-limiting but prolonged diarrheal disease in immunocompetent individuals. It exists naturally in animals and can be zoonotic. Although cryptosporidiosis is a significant cause of diarrheal disease in both developing and developed countries, it is more prevalent in developing countries and in tropical environments. We examined the epidemiology and disease burden of Cryptosporidium in Saudi Arabia and neighboring countries by reviewing 23 published studies of Cryptosporidium and etiology of diarrhea in between 1986 and 2006. The prevalence of Cryptosporidium infection in human's ranged from 1% to 37% with a median of 4%, while in animals it was for different species of animals and geographic locations of the studies. Most cases of cryptosporidiosis occurred among children less than 7 years of age and particularly in the first two years of life. The seasonality of Cryptosporidium varied depending on the geographic locations of the studies but it generally most prevalent in the rainy season. The most commonly identified species was Cryptosporidium parvum while C.hominis was detected only in one study from Kuwait. The cumulative experience from Saudi Arabia and four neighboring countries (Kuwait, Oman, Jordan and Iraq) suggest that Cryptosporidium is an important cause of diarrhea in human and cattle. However, the findings of this review also demonstrate the limitations of the available data regarding Cryptosporidium species and strains in circulation in these countries. (author)

  15. Model of directed lines for square ice with second-neighbor and third-neighbor interactions

    Science.gov (United States)

    Kirov, Mikhail V.

    2018-02-01

    The investigation of the properties of nanoconfined systems is one of the most rapidly developing scientific fields. Recently it has been established that water monolayer between two graphene sheets forms square ice. Because of the energetic disadvantage, in the structure of the square ice there are no longitudinally arranged molecules. The result is that the structure is formed by unidirectional straight-lines of hydrogen bonds only. A simple but accurate discrete model of square ice with second-neighbor and third-neighbor interactions is proposed. According to this model, the ground state includes all configurations which do not contain three neighboring unidirectional chains of hydrogen bonds. Each triplet increases the energy by the same value. This new model differs from an analogous model with long-range interactions where in the ground state all neighboring chains are antiparallel. The new model is suitable for the corresponding system of point electric (and magnetic) dipoles on the square lattice. It allows separately estimating the different contributions to the total binding energy and helps to understand the properties of infinite monolayers and finite nanostructures. Calculations of the binding energy for square ice and for point dipole system are performed using the packages TINKER and LAMMPS.

  16. The surprising power of neighborly advice.

    Science.gov (United States)

    Gilbert, Daniel T; Killingsworth, Matthew A; Eyre, Rebecca N; Wilson, Timothy D

    2009-03-20

    Two experiments revealed that (i) people can more accurately predict their affective reactions to a future event when they know how a neighbor in their social network reacted to the event than when they know about the event itself and (ii) people do not believe this. Undergraduates made more accurate predictions about their affective reactions to a 5-minute speed date (n = 25) and to a peer evaluation (n = 88) when they knew only how another undergraduate had reacted to these events than when they had information about the events themselves. Both participants and independent judges mistakenly believed that predictions based on information about the event would be more accurate than predictions based on information about how another person had reacted to it.

  17. Observing Literacy Practices in Neighbor Institutions

    DEFF Research Database (Denmark)

    Reusch, Charlotte

    ’procedures on language and literacy. Based on this material, we developed an observation scheme and a guide for preschool teachers to follow, inspired by an action learning concept.During fall 2015, a pilot project is carried out. Preschool teachers from one institution visit a neighbor institution one by one during...... work hours, in order to observe and register how language and literacy events look like there. Afterwards, they share their registrations at a team meeting, and discuss and decide which procedures to test in their own institution. Thus, they form a professional learning network. In the pilot project......The Danish National Centre for Reading and a municipality in southern Denmark cooperate to develop a program to improve preschool children’s early literacy skills. The project aims to support preschool teachers’ ability to create a rich literacy environment for children age 3‒6. Recent research...

  18. Giant Planets: Good Neighbors for Habitable Worlds?

    Science.gov (United States)

    Georgakarakos, Nikolaos; Eggl, Siegfried; Dobbs-Dixon, Ian

    2018-04-01

    The presence of giant planets influences potentially habitable worlds in numerous ways. Massive celestial neighbors can facilitate the formation of planetary cores and modify the influx of asteroids and comets toward Earth analogs later on. Furthermore, giant planets can indirectly change the climate of terrestrial worlds by gravitationally altering their orbits. Investigating 147 well-characterized exoplanetary systems known to date that host a main-sequence star and a giant planet, we show that the presence of “giant neighbors” can reduce a terrestrial planet’s chances to remain habitable, even if both planets have stable orbits. In a small fraction of systems, however, giant planets slightly increase the extent of habitable zones provided that the terrestrial world has a high climate inertia. In providing constraints on where giant planets cease to affect the habitable zone size in a detrimental fashion, we identify prime targets in the search for habitable worlds.

  19. Raman scattering mediated by neighboring molecules

    Science.gov (United States)

    Williams, Mathew D.; Bradshaw, David S.; Andrews, David L.

    2016-05-01

    Raman scattering is most commonly associated with a change in vibrational state within individual molecules, the corresponding frequency shift in the scattered light affording a key way of identifying material structures. In theories where both matter and light are treated quantum mechanically, the fundamental scattering process is represented as the concurrent annihilation of a photon from one radiation mode and creation of another in a different mode. Developing this quantum electrodynamical formulation, the focus of the present work is on the spectroscopic consequences of electrodynamic coupling between neighboring molecules or other kinds of optical center. To encompass these nanoscale interactions, through which the molecular states evolve under the dual influence of the input light and local fields, this work identifies and determines two major mechanisms for each of which different selection rules apply. The constituent optical centers are considered to be chemically different and held in a fixed orientation with respect to each other, either as two components of a larger molecule or a molecular assembly that can undergo free rotation in a fluid medium or as parts of a larger, solid material. The two centers are considered to be separated beyond wavefunction overlap but close enough together to fall within an optical near-field limit, which leads to high inverse power dependences on their local separation. In this investigation, individual centers undergo a Stokes transition, whilst each neighbor of a different species remains in its original electronic and vibrational state. Analogous principles are applicable for the anti-Stokes case. The analysis concludes by considering the experimental consequences of applying this spectroscopic interpretation to fluid media; explicitly, the selection rules and the impact of pressure on the radiant intensity of this process.

  20. Raman scattering mediated by neighboring molecules

    Energy Technology Data Exchange (ETDEWEB)

    Williams, Mathew D.; Bradshaw, David S.; Andrews, David L., E-mail: david.andrews@physics.org [School of Chemistry, University of East Anglia, Norwich NR4 7TJ (United Kingdom)

    2016-05-07

    Raman scattering is most commonly associated with a change in vibrational state within individual molecules, the corresponding frequency shift in the scattered light affording a key way of identifying material structures. In theories where both matter and light are treated quantum mechanically, the fundamental scattering process is represented as the concurrent annihilation of a photon from one radiation mode and creation of another in a different mode. Developing this quantum electrodynamical formulation, the focus of the present work is on the spectroscopic consequences of electrodynamic coupling between neighboring molecules or other kinds of optical center. To encompass these nanoscale interactions, through which the molecular states evolve under the dual influence of the input light and local fields, this work identifies and determines two major mechanisms for each of which different selection rules apply. The constituent optical centers are considered to be chemically different and held in a fixed orientation with respect to each other, either as two components of a larger molecule or a molecular assembly that can undergo free rotation in a fluid medium or as parts of a larger, solid material. The two centers are considered to be separated beyond wavefunction overlap but close enough together to fall within an optical near-field limit, which leads to high inverse power dependences on their local separation. In this investigation, individual centers undergo a Stokes transition, whilst each neighbor of a different species remains in its original electronic and vibrational state. Analogous principles are applicable for the anti-Stokes case. The analysis concludes by considering the experimental consequences of applying this spectroscopic interpretation to fluid media; explicitly, the selection rules and the impact of pressure on the radiant intensity of this process.

  1. Embedding beyond electrostatics

    DEFF Research Database (Denmark)

    Nåbo, Lina J.; Olsen, Jógvan Magnus Haugaard; Holmgaard List, Nanna

    2016-01-01

    We study excited states of cholesterol in solution and show that, in this specific case, solute wave-function confinement is the main effect of the solvent. This is rationalized on the basis of the polarizable density embedding scheme, which in addition to polarizable embedding includes non-electrostatic...... repulsion that effectively confines the solute wave function to its cavity. We illustrate how the inclusion of non-electrostatic repulsion results in a successful identification of the intense π → π∗ transition, which was not possible using an embedding method that only includes electrostatics....... This underlines the importance of non-electrostatic repulsion in quantum-mechanical embedding-based methods....

  2. Embedded systems handbook

    CERN Document Server

    Zurawski, Richard

    2005-01-01

    Embedded systems are nearly ubiquitous, and books on individual topics or components of embedded systems are equally abundant. Unfortunately, for those designers who thirst for knowledge of the big picture of embedded systems there is not a drop to drink. Until now. The Embedded Systems Handbook is an oasis of information, offering a mix of basic and advanced topics, new solutions and technologies arising from the most recent research efforts, and emerging trends to help you stay current in this ever-changing field.With preeminent contributors from leading industrial and academic institutions

  3. Web Server Embedded System

    Directory of Open Access Journals (Sweden)

    Adharul Muttaqin

    2014-07-01

    Full Text Available Abstrak Embedded sistem saat ini menjadi perhatian khusus pada teknologi komputer, beberapa sistem operasi linux dan web server yang beraneka ragam juga sudah dipersiapkan untuk mendukung sistem embedded, salah satu aplikasi yang dapat digunakan dalam operasi pada sistem embedded adalah web server. Pemilihan web server pada lingkungan embedded saat ini masih jarang dilakukan, oleh karena itu penelitian ini dilakukan dengan menitik beratkan pada dua buah aplikasi web server yang tergolong memiliki fitur utama yang menawarkan “keringanan” pada konsumsi CPU maupun memori seperti Light HTTPD dan Tiny HTTPD. Dengan menggunakan parameter thread (users, ramp-up periods, dan loop count pada stress test embedded system, penelitian ini menawarkan solusi web server manakah diantara Light HTTPD dan Tiny HTTPD yang memiliki kecocokan fitur dalam penggunaan embedded sistem menggunakan beagleboard ditinjau dari konsumsi CPU dan memori. Hasil penelitian menunjukkan bahwa dalam hal konsumsi CPU pada beagleboard embedded system lebih disarankan penggunaan Light HTTPD dibandingkan dengan tiny HTTPD dikarenakan terdapat perbedaan CPU load yang sangat signifikan antar kedua layanan web tersebut Kata kunci: embedded system, web server Abstract Embedded systems are currently of particular concern in computer technology, some of the linux operating system and web server variegated also prepared to support the embedded system, one of the applications that can be used in embedded systems are operating on the web server. Selection of embedded web server on the environment is still rarely done, therefore this study was conducted with a focus on two web application servers belonging to the main features that offer a "lightness" to the CPU and memory consumption as Light HTTPD and Tiny HTTPD. By using the parameters of the thread (users, ramp-up periods, and loop count on a stress test embedded systems, this study offers a solution of web server which between the Light

  4. Embedded systems handbook networked embedded systems

    CERN Document Server

    Zurawski, Richard

    2009-01-01

    Considered a standard industry resource, the Embedded Systems Handbook provided researchers and technicians with the authoritative information needed to launch a wealth of diverse applications, including those in automotive electronics, industrial automated systems, and building automation and control. Now a new resource is required to report on current developments and provide a technical reference for those looking to move the field forward yet again. Divided into two volumes to accommodate this growth, the Embedded Systems Handbook, Second Edition presents a comprehensive view on this area

  5. The data embedding method

    Energy Technology Data Exchange (ETDEWEB)

    Sandford, M.T. II; Bradley, J.N.; Handel, T.G.

    1996-06-01

    Data embedding is a new steganographic method for combining digital information sets. This paper describes the data embedding method and gives examples of its application using software written in the C-programming language. Sandford and Handel produced a computer program (BMPEMBED, Ver. 1.51 written for IBM PC/AT or compatible, MS/DOS Ver. 3.3 or later) that implements data embedding in an application for digital imagery. Information is embedded into, and extracted from, Truecolor or color-pallet images in Microsoft{reg_sign} bitmap (.BMP) format. Hiding data in the noise component of a host, by means of an algorithm that modifies or replaces the noise bits, is termed {open_quote}steganography.{close_quote} Data embedding differs markedly from conventional steganography, because it uses the noise component of the host to insert information with few or no modifications to the host data values or their statistical properties. Consequently, the entropy of the host data is affected little by using data embedding to add information. The data embedding method applies to host data compressed with transform, or {open_quote}lossy{close_quote} compression algorithms, as for example ones based on discrete cosine transform and wavelet functions. Analysis of the host noise generates a key required for embedding and extracting the auxiliary data from the combined data. The key is stored easily in the combined data. Images without the key cannot be processed to extract the embedded information. To provide security for the embedded data, one can remove the key from the combined data and manage it separately. The image key can be encrypted and stored in the combined data or transmitted separately as a ciphertext much smaller in size than the embedded data. The key size is typically ten to one-hundred bytes, and it is in data an analysis algorithm.

  6. Text Categorization Using Weight Adjusted k-Nearest Neighbor Classification

    National Research Council Canada - National Science Library

    Han, Euihong; Karypis, George; Kumar, Vipin

    1999-01-01

    .... The authors present a nearest neighbor classification scheme for text categorization in which the importance of discriminating words is learned using mutual information and weight adjustment techniques...

  7. Smart Multicore Embedded Systems

    DEFF Research Database (Denmark)

    This book provides a single-source reference to the state-of-the-art of high-level programming models and compilation tool-chains for embedded system platforms. The authors address challenges faced by programmers developing software to implement parallel applications in embedded systems, where ve...

  8. Embedded engineering education

    CERN Document Server

    Kaštelan, Ivan; Temerinac, Miodrag; Barak, Moshe; Sruk, Vlado

    2016-01-01

    This book focuses on the outcome of the European research project “FP7-ICT-2011-8 / 317882: Embedded Engineering Learning Platform” E2LP. Additionally, some experiences and researches outside this project have been included. This book provides information about the achieved results of the E2LP project as well as some broader views about the embedded engineering education. It captures project results and applications, methodologies, and evaluations. It leads to the history of computer architectures, brings a touch of the future in education tools and provides a valuable resource for anyone interested in embedded engineering education concepts, experiences and material. The book contents 12 original contributions and will open a broader discussion about the necessary knowledge and appropriate learning methods for the new profile of embedded engineers. As a result, the proposed Embedded Computer Engineering Learning Platform will help to educate a sufficient number of future engineers in Europe, capable of d...

  9. Common Nearest Neighbor Clustering—A Benchmark

    Directory of Open Access Journals (Sweden)

    Oliver Lemke

    2018-02-01

    Full Text Available Cluster analyses are often conducted with the goal to characterize an underlying probability density, for which the data-point density serves as an estimate for this probability density. We here test and benchmark the common nearest neighbor (CNN cluster algorithm. This algorithm assigns a spherical neighborhood R to each data point and estimates the data-point density between two data points as the number of data points N in the overlapping region of their neighborhoods (step 1. The main principle in the CNN cluster algorithm is cluster growing. This grows the clusters by sequentially adding data points and thereby effectively positions the border of the clusters along an iso-surface of the underlying probability density. This yields a strict partitioning with outliers, for which the cluster represents peaks in the underlying probability density—termed core sets (step 2. The removal of the outliers on the basis of a threshold criterion is optional (step 3. The benchmark datasets address a series of typical challenges, including datasets with a very high dimensional state space and datasets in which the cluster centroids are aligned along an underlying structure (Birch sets. The performance of the CNN algorithm is evaluated with respect to these challenges. The results indicate that the CNN cluster algorithm can be useful in a wide range of settings. Cluster algorithms are particularly important for the analysis of molecular dynamics (MD simulations. We demonstrate how the CNN cluster results can be used as a discretization of the molecular state space for the construction of a core-set model of the MD improving the accuracy compared to conventional full-partitioning models. The software for the CNN clustering is available on GitHub.

  10. ALIGNMENTS OF GROUP GALAXIES WITH NEIGHBORING GROUPS

    International Nuclear Information System (INIS)

    Wang Yougang; Chen Xuelei; Park, Changbom; Yang Xiaohu; Choi, Yun-Young

    2009-01-01

    Using a sample of galaxy groups found in the Sloan Digital Sky Survey Data Release 4, we measure the following four types of alignment signals: (1) the alignment between the distributions of the satellites of each group relative to the direction of the nearest neighbor group (NNG); (2) the alignment between the major axis direction of the central galaxy of the host group (HG) and the direction of the NNG; (3) the alignment between the major axes of the central galaxies of the HG and the NNG; and (4) the alignment between the major axes of the satellites of the HG and the direction of the NNG. We find strong signal of alignment between the satellite distribution and the orientation of central galaxy relative to the direction of the NNG, even when the NNG is located beyond 3r vir of the host group. The major axis of the central galaxy of the HG is aligned with the direction of the NNG. The alignment signals are more prominent for groups that are more massive and with early-type central galaxies. We also find that there is a preference for the two major axes of the central galaxies of the HG and NNG to be parallel for the system with both early central galaxies, however, not for the systems with both late-type central galaxies. For the orientation of satellite galaxies, we do not find any significant alignment signals relative to the direction of the NNG. From these four types of alignment measurements, we conclude that the large-scale environment traced by the nearby group affects primarily the shape of the host dark matter halo, and hence also affects the distribution of satellite galaxies and the orientation of central galaxies. In addition, the NNG directly affects the distribution of the satellite galaxies by inducing asymmetric alignment signals, and the NNG at very small separation may also contribute a second-order impact on the orientation of the central galaxy in the HG.

  11. Embedded Linux in het onderwijs

    NARCIS (Netherlands)

    Dr Ruud Ermers

    2008-01-01

    Embedded Linux wordt bij steeds meer grote bedrijven ingevoerd als embedded operating system. Binnen de opleiding Technische Informatica van Fontys Hogeschool ICT is Embedded Linux geïntroduceerd in samenwerking met het lectoraat Architectuur van Embedded Systemen. Embedded Linux is als vakgebied

  12. Frog sound identification using extended k-nearest neighbor classifier

    Science.gov (United States)

    Mukahar, Nordiana; Affendi Rosdi, Bakhtiar; Athiar Ramli, Dzati; Jaafar, Haryati

    2017-09-01

    Frog sound identification based on the vocalization becomes important for biological research and environmental monitoring. As a result, different types of feature extractions and classifiers have been employed to evaluate the accuracy of frog sound identification. This paper presents a frog sound identification with Extended k-Nearest Neighbor (EKNN) classifier. The EKNN classifier integrates the nearest neighbors and mutual sharing of neighborhood concepts, with the aims of improving the classification performance. It makes a prediction based on who are the nearest neighbors of the testing sample and who consider the testing sample as their nearest neighbors. In order to evaluate the classification performance in frog sound identification, the EKNN classifier is compared with competing classifier, k -Nearest Neighbor (KNN), Fuzzy k -Nearest Neighbor (FKNN) k - General Nearest Neighbor (KGNN)and Mutual k -Nearest Neighbor (MKNN) on the recorded sounds of 15 frog species obtained in Malaysia forest. The recorded sounds have been segmented using Short Time Energy and Short Time Average Zero Crossing Rate (STE+STAZCR), sinusoidal modeling (SM), manual and the combination of Energy (E) and Zero Crossing Rate (ZCR) (E+ZCR) while the features are extracted by Mel Frequency Cepstrum Coefficient (MFCC). The experimental results have shown that the EKNCN classifier exhibits the best performance in terms of accuracy compared to the competing classifiers, KNN, FKNN, GKNN and MKNN for all cases.

  13. The Islands Approach to Nearest Neighbor Querying in Spatial Networks

    DEFF Research Database (Denmark)

    Huang, Xuegang; Jensen, Christian Søndergaard; Saltenis, Simonas

    2005-01-01

    , and versatile approach to k nearest neighbor computation that obviates the need for using several k nearest neighbor approaches for supporting a single service scenario. The experimental comparison with the existing techniques uses real-world road network data and considers both I/O and CPU performance...

  14. Performance modeling of neighbor discovery in proactive routing protocols

    Directory of Open Access Journals (Sweden)

    Andres Medina

    2011-07-01

    Full Text Available It is well known that neighbor discovery is a critical component of proactive routing protocols in wireless ad hoc networks. However there is no formal study on the performance of proposed neighbor discovery mechanisms. This paper provides a detailed model of key performance metrics of neighbor discovery algorithms, such as node degree and the distribution of the distance to symmetric neighbors. The model accounts for the dynamics of neighbor discovery as well as node density, mobility, radio and interference. The paper demonstrates a method for applying these models to the evaluation of global network metrics. In particular, it describes a model of network connectivity. Validation of the models shows that the degree estimate agrees, within 5% error, with simulations for the considered scenarios. The work presented in this paper serves as a basis for the performance evaluation of remaining performance metrics of routing protocols, vital for large scale deployment of ad hoc networks.

  15. Brauer type embedding problems

    CERN Document Server

    Ledet, Arne

    2005-01-01

    This monograph is concerned with Galois theoretical embedding problems of so-called Brauer type with a focus on 2-groups and on finding explicit criteria for solvability and explicit constructions of the solutions. The advantage of considering Brauer type embedding problems is their comparatively simple condition for solvability in the form of an obstruction in the Brauer group of the ground field. This book presupposes knowledge of classical Galois theory and the attendant algebra. Before considering questions of reducing the embedding problems and reformulating the solvability criteria, the

  16. Time-dependent embedding

    OpenAIRE

    Inglesfield, J. E.

    2007-01-01

    A method of solving the time-dependent Schr\\"odinger equation is presented, in which a finite region of space is treated explicitly, with the boundary conditions for matching the wave-functions on to the rest of the system replaced by an embedding term added on to the Hamiltonian. This time-dependent embedding term is derived from the Fourier transform of the energy-dependent embedding potential, which embeds the time-independent Schr\\"odinger equation. Results are presented for a one-dimensi...

  17. Electronics for embedded systems

    CERN Document Server

    Bindal, Ahmet

    2017-01-01

    This book provides semester-length coverage of electronics for embedded systems, covering most common analog and digital circuit-related issues encountered while designing embedded system hardware. It is written for students and young professionals who have basic circuit theory background and want to learn more about passive circuits, diode and bipolar transistor circuits, the state-of-the-art CMOS logic family and its interface with older logic families such as TTL, sensors and sensor physics, operational amplifier circuits to condition sensor signals, data converters and various circuits used in electro-mechanical device control in embedded systems. The book also provides numerous hardware design examples by integrating the topics learned in earlier chapters. The last chapter extensively reviews the combinational and sequential logic design principles to be able to design the digital part of embedded system hardware.

  18. Embedded Fragments Registry (EFR)

    Data.gov (United States)

    Department of Veterans Affairs — In 2009, the Department of Defense estimated that approximately 40,000 service members who served in OEF/OIF may have embedded fragment wounds as the result of small...

  19. Smart Multicore Embedded Systems

    DEFF Research Database (Denmark)

    This book provides a single-source reference to the state-of-the-art of high-level programming models and compilation tool-chains for embedded system platforms. The authors address challenges faced by programmers developing software to implement parallel applications in embedded systems, where very...... specificities of various embedded systems from different industries. Parallel programming tool-chains are described that take as input parameters both the application and the platform model, then determine relevant transformations and mapping decisions on the concrete platform, minimizing user intervention...... and hiding the difficulties related to the correct and efficient use of memory hierarchy and low level code generation. Describes tools and programming models for multicore embedded systems Emphasizes throughout performance per watt scalability Discusses realistic limits of software parallelization Enables...

  20. Our Galactic Neighbor Hosts Complex Organic Molecules

    Science.gov (United States)

    Hensley, Kerry

    2018-03-01

    For the first time, data from the Atacama Large Millimeter/submillimeter Array (ALMA) reveal the presence of methyl formate and dimethyl ether in a star-forming region outside our galaxy. This discovery has important implications for the formation and survival of complex organic compounds importantfor the formation of life in low-metallicity galaxies bothyoung and old.No Simple Picture of Complex Molecule FormationALMA, pictured here with the Magellanic Clouds above, has observed organic molecules in our Milky Way Galaxy and beyond. [ESO/C. Malin]Complex organic molecules (those with at least six atoms, one or more of which must be carbon) are the precursors to the building blocks of life. Knowing how and where complex organic molecules can form is a key part of understanding how life came to be on Earth and how it might arise elsewhere in the universe. From exoplanet atmospheres to interstellar space, complex organic molecules are ubiquitous in the Milky Way.In our galaxy, complex organic molecules are often found in the intense environments of hot cores clumps of dense molecular gas surrounding the sites of star formation. However, its not yet fully understood how the complex organic molecules found in hot cores come to be. One possibility is that the compounds condense onto cold dust grains long before the young stars begin heating their natal shrouds. Alternatively, they might assemble themselves from the hot, dense gas surrounding the blazing protostars.Composite infrared and optical image of the N 113 star-forming region in the LMC. The ALMA coverage is indicated by the gray line. Click to enlarge. [Sewio et al. 2018]Detecting Complexity, a Galaxy AwayUsing ALMA, a team of researchers led by Marta Sewio (NASA Goddard Space Flight Center) recently detected two complex organic molecules methyl formate and dimethyl ether for the first time in our neighboring galaxy, the Large Magellanic Cloud (LMC). Previous searches for organic molecules in the LMC detected

  1. Dimensional testing for reverse k-nearest neighbor search

    DEFF Research Database (Denmark)

    Casanova, Guillaume; Englmeier, Elias; Houle, Michael E.

    2017-01-01

    Given a query object q, reverse k-nearest neighbor (RkNN) search aims to locate those objects of the database that have q among their k-nearest neighbors. In this paper, we propose an approximation method for solving RkNN queries, where the pruning operations and termination tests are guided...... by a characterization of the intrinsic dimensionality of the data. The method can accommodate any index structure supporting incremental (forward) nearest-neighbor search for the generation and verification of candidates, while avoiding impractically-high preprocessing costs. We also provide experimental evidence...

  2. Color and neighbor edge directional difference feature for image retrieval

    Institute of Scientific and Technical Information of China (English)

    Chaobing Huang; Shengsheng Yu; Jingli Zhou; Hongwei Lu

    2005-01-01

    @@ A novel image feature termed neighbor edge directional difference unit histogram is proposed, in which the neighbor edge directional difference unit is defined and computed for every pixel in the image, and is used to generate the neighbor edge directional difference unit histogram. This histogram and color histogram are used as feature indexes to retrieve color image. The feature is invariant to image scaling and translation and has more powerful descriptive for the natural color images. Experimental results show that the feature can achieve better retrieval performance than other color-spatial features.

  3. Unsupervised machine learning account of magnetic transitions in the Hubbard model

    Science.gov (United States)

    Ch'ng, Kelvin; Vazquez, Nick; Khatami, Ehsan

    2018-01-01

    We employ several unsupervised machine learning techniques, including autoencoders, random trees embedding, and t -distributed stochastic neighboring ensemble (t -SNE), to reduce the dimensionality of, and therefore classify, raw (auxiliary) spin configurations generated, through Monte Carlo simulations of small clusters, for the Ising and Fermi-Hubbard models at finite temperatures. Results from a convolutional autoencoder for the three-dimensional Ising model can be shown to produce the magnetization and the susceptibility as a function of temperature with a high degree of accuracy. Quantum fluctuations distort this picture and prevent us from making such connections between the output of the autoencoder and physical observables for the Hubbard model. However, we are able to define an indicator based on the output of the t -SNE algorithm that shows a near perfect agreement with the antiferromagnetic structure factor of the model in two and three spatial dimensions in the weak-coupling regime. t -SNE also predicts a transition to the canted antiferromagnetic phase for the three-dimensional model when a strong magnetic field is present. We show that these techniques cannot be expected to work away from half filling when the "sign problem" in quantum Monte Carlo simulations is present.

  4. Embedded Systems Design: Optimization Challenges

    DEFF Research Database (Denmark)

    Pop, Paul

    2005-01-01

    Summary form only given. Embedded systems are everywhere: from alarm clocks to PDAs, from mobile phones to cars, almost all the devices we use are controlled by embedded systems. Over 99% of the microprocessors produced today are used in embedded systems, and recently the number of embedded systems...

  5. Scalable Nearest Neighbor Algorithms for High Dimensional Data.

    Science.gov (United States)

    Muja, Marius; Lowe, David G

    2014-11-01

    For many computer vision and machine learning problems, large training sets are key for good performance. However, the most computationally expensive part of many computer vision and machine learning algorithms consists of finding nearest neighbor matches to high dimensional vectors that represent the training data. We propose new algorithms for approximate nearest neighbor matching and evaluate and compare them with previous algorithms. For matching high dimensional features, we find two algorithms to be the most efficient: the randomized k-d forest and a new algorithm proposed in this paper, the priority search k-means tree. We also propose a new algorithm for matching binary features by searching multiple hierarchical clustering trees and show it outperforms methods typically used in the literature. We show that the optimal nearest neighbor algorithm and its parameters depend on the data set characteristics and describe an automated configuration procedure for finding the best algorithm to search a particular data set. In order to scale to very large data sets that would otherwise not fit in the memory of a single machine, we propose a distributed nearest neighbor matching framework that can be used with any of the algorithms described in the paper. All this research has been released as an open source library called fast library for approximate nearest neighbors (FLANN), which has been incorporated into OpenCV and is now one of the most popular libraries for nearest neighbor matching.

  6. The role of orthography in the semantic activation of neighbors.

    Science.gov (United States)

    Hino, Yasushi; Lupker, Stephen J; Taylor, Tamsen E

    2012-09-01

    There is now considerable evidence that a letter string can activate semantic information appropriate to its orthographic neighbors (e.g., Forster & Hector's, 2002, TURPLE effect). This phenomenon is the focus of the present research. Using Japanese words, we examined whether semantic activation of neighbors is driven directly by orthographic similarity alone or whether there is also a role for phonological similarity. In Experiment 1, using a relatedness judgment task in which a Kanji word-Katakana word pair was presented on each trial, an inhibitory effect was observed when the initial Kanji word was related to an orthographic and phonological neighbor of the Katakana word target but not when the initial Kanji word was related to a phonological but not orthographic neighbor of the Katakana word target. This result suggests that phonology plays little, if any, role in the activation of neighbors' semantics when reading familiar words. In Experiment 2, the targets were transcribed into Hiragana, a script they are typically not written in, requiring readers to engage in phonological coding. In that experiment, inhibitory effects were observed in both conditions. This result indicates that phonologically mediated semantic activation of neighbors will emerge when phonological processing is necessary in order to understand a written word (e.g., when that word is transcribed into an unfamiliar script). PsycINFO Database Record (c) 2012 APA, all rights reserved.

  7. Smart multicore embedded systems

    CERN Document Server

    Bertels, Koen; Karlsson, Sven; Pacull, François

    2014-01-01

    This book provides a single-source reference to the state-of-the-art of high-level programming models and compilation tool-chains for embedded system platforms. The authors address challenges faced by programmers developing software to implement parallel applications in embedded systems, where very often they are forced to rewrite sequential programs into parallel software, taking into account all the low level features and peculiarities of the underlying platforms. Readers will benefit from these authors’ approach, which takes into account both the application requirements and the platform specificities of various embedded systems from different industries. Parallel programming tool-chains are described that take as input parameters both the application and the platform model, then determine relevant transformations and mapping decisions on the concrete platform, minimizing user intervention and hiding the difficulties related to the correct and efficient use of memory hierarchy and low level code generati...

  8. Polarizable Density Embedding

    DEFF Research Database (Denmark)

    Olsen, Jógvan Magnus Haugaard; Steinmann, Casper; Ruud, Kenneth

    2015-01-01

    We present a new QM/QM/MM-based model for calculating molecular properties and excited states of solute-solvent systems. We denote this new approach the polarizable density embedding (PDE) model and it represents an extension of our previously developed polarizable embedding (PE) strategy. The PDE...... model is a focused computational approach in which a core region of the system studied is represented by a quantum-chemical method, whereas the environment is divided into two other regions: an inner and an outer region. Molecules belonging to the inner region are described by their exact densities...

  9. Algoritma Interpolasi Nearest-Neighbor untuk Pendeteksian Sampul Pulsa Oscilometri Menggunakan Mikrokontroler Berbiaya Rendah

    Directory of Open Access Journals (Sweden)

    Firdaus Firdaus

    2017-12-01

    Full Text Available Non-invasive blood pressure measurement devices are widely available in the marketplace. Most of these devices use the oscillometric principle that store and analyze oscillometric waveforms during cuff deflation to obtain mean arterial pressure, systolic blood pressure and diastolic blood pressure. Those pressure values are determined from the oscillometric waveform envelope. Several methods to detect the envelope of oscillometric pulses utilize a complex algorithm that requires a large capacity memory and certainly difficult to process by a low memory capacity embedded system. A simple nearest-neighbor interpolation method is applied for oscillometric pulse envelope detection in non-invasive blood pressure measurement using microcontroller such ATmega328. The experiment yields 59 seconds average time to process the computation with 3.6% average percent error in blood pressure measurement.

  10. The patient-centered medical home neighbor: A primary care physician's view.

    Science.gov (United States)

    Sinsky, Christine A

    2011-01-04

    The American College of Physicians' position paper on the patient-centered medical home neighbor (PCMH-N) extends the work of the patient-centered medical home (PCMH) as a means of improving the delivery of health care. Recognizing that the PCMH does not exist in isolation, the PCMH-N concept outlines expectations for comanagement, communication, and care coordination and broadens responsibility for safe, effective, and efficient care beyond primary care to include physicians of all specialties. As such, it is a fitting follow-up to the PCMH and moves further down the road toward improved care for complex patients. Yet, there is more work to be done. Truly transforming the U.S. health care system around personalized medical homes embedded in highly functional medical neighborhoods will require better staffing models; more robust electronic information tools; aligned incentives for quality and efficiency within payment and regulatory policies; and a culture of greater engagement of patients, their families, and communities.

  11. Haldane to Dimer Phase Transition in the Spin-1 Haldane System with Bond-Alternating Nearest-Neighbor and Uniform Next-Nearest-Neighbor Exchange Interactions

    OpenAIRE

    Takashi, Tonegawa; Makoto, Kaburagi; Takeshi, Nakao; Department of Physics, Faculty of Science, Kobe University; Faculty of Cross-Cultural Studies, Kobe University; Department of Physics, Faculty of Science, Kobe University

    1995-01-01

    The Haldane to dimer phase transition is studied in the spin-1 Haldane system with bond-alternating nearest-neighbor and uniform next-nearest-neighbor exchange interactions, where both interactions are antiferromagnetic and thus compete with each other. By using a method of exact diagonalization, the ground-state phase diagram on the ratio of the next-nearest-neighbor interaction constant to the nearest-neighbor one versus the bond-alternation parameter of the nearest-neighbor interactions is...

  12. Embedding JIT into MRP

    NARCIS (Netherlands)

    Flapper, S.D.P.; Miltenburg, G.J.; Wijngaard, J.

    1991-01-01

    Today many companies who are using MRP production control systems are investigating how they can produce some or all of their products using just-in time (JIT) principles. They wonder to what extent MRP can provide support for JIT production. This paper describes how JIT can be embedded into MRP. A

  13. Embedded Multimaterial Extrusion Bioprinting

    NARCIS (Netherlands)

    Rocca, Marco; Fragasso, Alessio; Liu, Wanjun; Heinrich, Marcel A.; Zhang, Yu Shrike

    Embedded extrusion bioprinting allows for the generation of complex structures that otherwise cannot be achieved with conventional layer-by-layer deposition from the bottom, by overcoming the limits imposed by gravitational force. By taking advantage of a hydrogel bath, serving as a sacrificial

  14. Embedded data representations

    DEFF Research Database (Denmark)

    Willett, Wesley; Jansen, Yvonne; Dragicevic, Pierre

    2017-01-01

    We introduce embedded data representations, the use of visual and physical representations of data that are deeply integrated with the physical spaces, objects, and entities to which the data refers. Technologies like lightweight wireless displays, mixed reality hardware, and autonomous vehicles...

  15. Polarizable Density Embedding

    DEFF Research Database (Denmark)

    Reinholdt, Peter; Kongsted, Jacob; Olsen, Jógvan Magnus Haugaard

    2017-01-01

    We analyze the performance of the polarizable density embedding (PDE) model-a new multiscale computational approach designed for prediction and rationalization of general molecular properties of large and complex systems. We showcase how the PDE model very effectively handles the use of large...

  16. Embedded enzymes catalyse capture

    Science.gov (United States)

    Kentish, Sandra

    2018-05-01

    Membrane technologies for carbon capture can offer economic and environmental advantages over conventional amine-based absorption, but can suffer from limited gas flux and selectivity to CO2. Now, a membrane based on enzymes embedded in hydrophilic pores is shown to exhibit combined flux and selectivity that challenges the state of the art.

  17. Beyond formal groups: neighboring acts and watershed protection in Appalachia

    Directory of Open Access Journals (Sweden)

    Heather Lukacs

    2016-09-01

    Full Text Available This paper explores how watershed organizations in Appalachia have persisted in addressing water quality issues in areas with a history of coal mining. We identified two watershed groups that have taken responsibility for restoring local creeks that were previously highly degraded and sporadically managed. These watershed groups represent cases of self-organized commons governance in resource-rich, economically poor Appalachian communities. We describe the extent and characteristics of links between watershed group volunteers and watershed residents who are not group members. Through surveys, participant observation, and key-informant consultation, we found that neighbors – group members as well as non-group-members – supported the group's function through informal neighboring acts. Past research has shown that local commons governance institutions benefit from being nested in supportive external structures. We found that the persistence and success of community watershed organizations depends on the informal participation of local residents, affirming the necessity of looking beyond formal, organized groups to understand the resources, expertise, and information needed to address complex water pollution at the watershed level. Our findings augment the concept of nestedness in commons governance to include that of a formal organization acting as a neighbor that exchanges informal neighboring acts with local residents. In this way, we extend the concept of neighboring to include interactions between individuals and a group operating in the same geographic area.

  18. Multiple k Nearest Neighbor Query Processing in Spatial Network Databases

    DEFF Research Database (Denmark)

    Xuegang, Huang; Jensen, Christian Søndergaard; Saltenis, Simonas

    2006-01-01

    This paper concerns the efficient processing of multiple k nearest neighbor queries in a road-network setting. The assumed setting covers a range of scenarios such as the one where a large population of mobile service users that are constrained to a road network issue nearest-neighbor queries...... for points of interest that are accessible via the road network. Given multiple k nearest neighbor queries, the paper proposes progressive techniques that selectively cache query results in main memory and subsequently reuse these for query processing. The paper initially proposes techniques for the case...... where an upper bound on k is known a priori and then extends the techniques to the case where this is not so. Based on empirical studies with real-world data, the paper offers insight into the circumstances under which the different proposed techniques can be used with advantage for multiple k nearest...

  19. Embedding in thermosetting resins

    International Nuclear Information System (INIS)

    Buzonniere, A. de

    1985-01-01

    Medium activity waste coming either from nuclear power plants in operation such as evaporator concentrates, spent resins, filter cartridges or the dismantling of installations are embedded in order to obtain a product suitable for long term disposal. Embedding in thermosetting resins (polyester or epoxy) is one among currently used techniques; it is being developed by the CEA (Commissariat a l'Energie Atomique) and Technicatome (subsidiary of CEA and EDF). The process is easy to operate and yields excellent results particularly as far as volume reduction and radioelement containment (cesium particularly) are concerned. The process has already been in operation in four stationary plants for several years. Extension of the process to mobile units has been completed by Technicatome in collaboration with the CEA [fr

  20. Nearest unlike neighbor (NUN): an aid to decision confidence estimation

    Science.gov (United States)

    Dasarathy, Belur V.

    1995-09-01

    The concept of nearest unlike neighbor (NUN), proposed and explored previously in the design of nearest neighbor (NN) based decision systems, is further exploited in this study to develop a measure of confidence in the decisions made by NN-based decision systems. This measure of confidence, on the basis of comparison with a user-defined threshold, may be used to determine the acceptability of the decision provided by the NN-based decision system. The concepts, associated methodology, and some illustrative numerical examples using the now classical Iris data to bring out the ease of implementation and effectiveness of the proposed innovations are presented.

  1. Contrasting demographic histories of the neighboring bonobo and chimpanzee

    DEFF Research Database (Denmark)

    Hvilsom, Christina; Carlsen, Frands; Heller, Rasmus

    2014-01-01

    of the neighboring bonobo remained constant. The changes in population size are likely linked to changes in habitat area due to climate oscillations during the late Pleistocene. Furthermore, the timing of population expansion for the rainforest-adapted chimpanzee is concurrent with the expansion of the savanna...

  2. Local randomization in neighbor selection improves PRM roadmap quality

    KAUST Repository

    McMahon, Troy

    2012-10-01

    Probabilistic Roadmap Methods (PRMs) are one of the most used classes of motion planning methods. These sampling-based methods generate robot configurations (nodes) and then connect them to form a graph (roadmap) containing representative feasible pathways. A key step in PRM roadmap construction involves identifying a set of candidate neighbors for each node. Traditionally, these candidates are chosen to be the k-closest nodes based on a given distance metric. In this paper, we propose a new neighbor selection policy called LocalRand(k,K\\'), that first computes the K\\' closest nodes to a specified node and then selects k of those nodes at random. Intuitively, LocalRand attempts to benefit from random sampling while maintaining the higher levels of local planner success inherent to selecting more local neighbors. We provide a methodology for selecting the parameters k and K\\'. We perform an experimental comparison which shows that for both rigid and articulated robots, LocalRand results in roadmaps that are better connected than the traditional k-closest policy or a purely random neighbor selection policy. The cost required to achieve these results is shown to be comparable to k-closest. © 2012 IEEE.

  3. Local randomization in neighbor selection improves PRM roadmap quality

    KAUST Repository

    McMahon, Troy; Jacobs, Sam; Boyd, Bryan; Tapia, Lydia; Amato, Nancy M.

    2012-01-01

    Probabilistic Roadmap Methods (PRMs) are one of the most used classes of motion planning methods. These sampling-based methods generate robot configurations (nodes) and then connect them to form a graph (roadmap) containing representative feasible pathways. A key step in PRM roadmap construction involves identifying a set of candidate neighbors for each node. Traditionally, these candidates are chosen to be the k-closest nodes based on a given distance metric. In this paper, we propose a new neighbor selection policy called LocalRand(k,K'), that first computes the K' closest nodes to a specified node and then selects k of those nodes at random. Intuitively, LocalRand attempts to benefit from random sampling while maintaining the higher levels of local planner success inherent to selecting more local neighbors. We provide a methodology for selecting the parameters k and K'. We perform an experimental comparison which shows that for both rigid and articulated robots, LocalRand results in roadmaps that are better connected than the traditional k-closest policy or a purely random neighbor selection policy. The cost required to achieve these results is shown to be comparable to k-closest. © 2012 IEEE.

  4. Clustered K nearest neighbor algorithm for daily inflow forecasting

    NARCIS (Netherlands)

    Akbari, M.; Van Overloop, P.J.A.T.M.; Afshar, A.

    2010-01-01

    Instance based learning (IBL) algorithms are a common choice among data driven algorithms for inflow forecasting. They are based on the similarity principle and prediction is made by the finite number of similar neighbors. In this sense, the similarity of a query instance is estimated according to

  5. Near Neighbor Distribution in Sets of Fractal Nature

    Czech Academy of Sciences Publication Activity Database

    Jiřina, Marcel

    2013-01-01

    Roč. 5, č. 1 (2013), s. 159-166 ISSN 2150-7988 R&D Projects: GA MŠk(CZ) LG12020 Institutional support: RVO:67985807 Keywords : nearest neighbor * fractal set * multifractal * Erlang distribution Subject RIV: BB - Applied Statistics, Operational Research http://www.mirlabs.org/ijcisim/regular_papers_2013/Paper91.pdf

  6. Neighboring Genes Show Correlated Evolution in Gene Expression

    Science.gov (United States)

    Ghanbarian, Avazeh T.; Hurst, Laurence D.

    2015-01-01

    When considering the evolution of a gene’s expression profile, we commonly assume that this is unaffected by its genomic neighborhood. This is, however, in contrast to what we know about the lack of autonomy between neighboring genes in gene expression profiles in extant taxa. Indeed, in all eukaryotic genomes genes of similar expression-profile tend to cluster, reflecting chromatin level dynamics. Does it follow that if a gene increases expression in a particular lineage then the genomic neighbors will also increase in their expression or is gene expression evolution autonomous? To address this here we consider evolution of human gene expression since the human-chimp common ancestor, allowing for both variation in estimation of current expression level and error in Bayesian estimation of the ancestral state. We find that in all tissues and both sexes, the change in gene expression of a focal gene on average predicts the change in gene expression of neighbors. The effect is highly pronounced in the immediate vicinity (genes increasing their expression in humans tend to avoid nuclear lamina domains and be enriched for the gene activator 5-hydroxymethylcytosine, we conclude that, most probably owing to chromatin level control of gene expression, a change in gene expression of one gene likely affects the expression evolution of neighbors, what we term expression piggybacking, an analog of hitchhiking. PMID:25743543

  7. Secure Nearest Neighbor Query on Crowd-Sensing Data

    Directory of Open Access Journals (Sweden)

    Ke Cheng

    2016-09-01

    Full Text Available Nearest neighbor queries are fundamental in location-based services, and secure nearest neighbor queries mainly focus on how to securely and quickly retrieve the nearest neighbor in the outsourced cloud server. However, the previous big data system structure has changed because of the crowd-sensing data. On the one hand, sensing data terminals as the data owner are numerous and mistrustful, while, on the other hand, in most cases, the terminals find it difficult to finish many safety operation due to computation and storage capability constraints. In light of they Multi Owners and Multi Users (MOMU situation in the crowd-sensing data cloud environment, this paper presents a secure nearest neighbor query scheme based on the proxy server architecture, which is constructed by protocols of secure two-party computation and secure Voronoi diagram algorithm. It not only preserves the data confidentiality and query privacy but also effectively resists the collusion between the cloud server and the data owners or users. Finally, extensive theoretical and experimental evaluations are presented to show that our proposed scheme achieves a superior balance between the security and query performance compared to other schemes.

  8. Thermodynamic systematics of oxides of americium, curium, and neighboring elements

    International Nuclear Information System (INIS)

    Morss, L.R.

    1984-01-01

    Recently-obtained calorimetric data on the sesquioxides and dioxides of americium and curium are summarized. These data are combined with other properties of the actinide elements to elucidate the stability relationships among these oxides and to predict the behavior of neighboring actinide oxides. 45 references, 4 figures, 5 tables

  9. Embedded software verification and debugging

    CERN Document Server

    Winterholer, Markus

    2017-01-01

    This book provides comprehensive coverage of verification and debugging techniques for embedded software, which is frequently used in safety critical applications (e.g., automotive), where failures are unacceptable. Since the verification of complex systems needs to encompass the verification of both hardware and embedded software modules, this book focuses on verification and debugging approaches for embedded software with hardware dependencies. Coverage includes the entire flow of design, verification and debugging of embedded software and all key approaches to debugging, dynamic, static, and hybrid verification. This book discusses the current, industrial embedded software verification flow, as well as emerging trends with focus on formal and hybrid verification and debugging approaches. Includes in a single source the entire flow of design, verification and debugging of embedded software; Addresses the main techniques that are currently being used in the industry for assuring the quality of embedded softw...

  10. Incidence and Prevalence of Tuberculosis in Iran and Neighboring Countries

    Directory of Open Access Journals (Sweden)

    Arezoo Tavakoli

    2017-07-01

    Full Text Available Background Tuberculosis is one of the major public health concerns in many countries, however the available and effective treatment is known. Tuberculosis typically determined with socio-economic problems such as war, malnutrition and HIV prevalence. In Iran, many progresses are carried to control tuberculosis but, different factors such as immigration from neighboring countries are affective to tuberculosis infection. Objectives In this paper, the incidence and prevalence of tuberculosis is evaluated in different regions of Iran and neighboring countries. Methods The data are collected from different and valid sources such as Scopus, Pubmed and also many reports from world health organization (WHO and center of disease control and prevention (CDC for a period of 25 years (1990 - 2015 evaluated for Iran and neighboring countries. Results This study as a descriptive- analytical research is conducted cross- sectional among Iran and neighboring countries since 1990. The information is obtained from exact and valid informative data from web of sciences. The east and west border countries of Iran which are faced with war and immigration in Afghanistan, Pakistan and Iraq are source of tuberculosis infection that effect on tuberculosis prevalence in Iran. The data were analyzed by SPSS 22 and Excel 2013. Conclusions The incidence of tuberculosis in Iran has been decreased because of many controlling actions such as BCG vaccination, electronic reporting system for tuberculosis and free access to tuberculosis medication. Some of Iran neighboring countries such as Tajikistan and Pakistan have the highest incidence of tuberculosis which known as a challenge for tuberculosis control in Iran while Saudi Arabia and Turkey have the lowest incidence.

  11. Local biotic adaptation of trees and shrubs to plant neighbors

    Science.gov (United States)

    Grady, Kevin C.; Wood, Troy E.; Kolb, Thomas E.; Hersch-Green, Erika; Shuster, Stephen M.; Gehring, Catherine A.; Hart, Stephen C.; Allan, Gerard J.; Whitham, Thomas G.

    2017-01-01

    Natural selection as a result of plant–plant interactions can lead to local biotic adaptation. This may occur where species frequently interact and compete intensely for resources limiting growth, survival, and reproduction. Selection is demonstrated by comparing a genotype interacting with con- or hetero-specific sympatric neighbor genotypes with a shared site-level history (derived from the same source location), to the same genotype interacting with foreign neighbor genotypes (from different sources). Better genotype performance in sympatric than allopatric neighborhoods provides evidence of local biotic adaptation. This pattern might be explained by selection to avoid competition by shifting resource niches (differentiation) or by interactions benefitting one or more members (facilitation). We tested for local biotic adaptation among two riparian trees, Populus fremontii and Salix gooddingii, and the shrub Salix exigua by transplanting replicated genotypes from multiple source locations to a 17 000 tree common garden with sympatric and allopatric treatments along the Colorado River in California. Three major patterns were observed: 1) across species, 62 of 88 genotypes grew faster with sympatric neighbors than allopatric neighbors; 2) these growth rates, on an individual tree basis, were 44, 15 and 33% higher in sympatric than allopatric treatments for P. fremontii, S. exigua and S. gooddingii, respectively, and; 3) survivorship was higher in sympatric treatments for P. fremontiiand S. exigua. These results support the view that fitness of foundation species supporting diverse communities and dominating ecosystem processes is determined by adaptive interactions among multiple plant species with the outcome that performance depends on the genetic identity of plant neighbors. The occurrence of evolution in a plant-community context for trees and shrubs builds on ecological evolutionary research that has demonstrated co-evolution among herbaceous taxa, and

  12. Unsteady Flame Embedding

    KAUST Repository

    El-Asrag, Hossam A.

    2011-01-01

    Direct simulation of all the length and time scales relevant to practical combustion processes is computationally prohibitive. When combustion processes are driven by reaction and transport phenomena occurring at the unresolved scales of a numerical simulation, one must introduce a dynamic subgrid model that accounts for the multiscale nature of the problem using information available on a resolvable grid. Here, we discuss a model that captures unsteady flow-flame interactions- including extinction, re-ignition, and history effects-via embedded simulations at the subgrid level. The model efficiently accounts for subgrid flame structure and incorporates detailed chemistry and transport, allowing more accurate prediction of the stretch effect and the heat release. In this chapter we first review the work done in the past thirty years to develop the flame embedding concept. Next we present a formulation for the same concept that is compatible with Large Eddy Simulation in the flamelet regimes. The unsteady flame embedding approach (UFE) treats the flame as an ensemble of locally one-dimensional flames, similar to the flamelet approach. However, a set of elemental one-dimensional flames is used to describe the turbulent flame structure directly at the subgrid level. The calculations employ a one-dimensional unsteady flame model that incorporates unsteady strain rate, curvature, and mixture boundary conditions imposed by the resolved scales. The model is used for closure of the subgrid terms in the context of large eddy simulation. Direct numerical simulation (DNS) data from a flame-vortex interaction problem is used for comparison. © Springer Science+Business Media B.V. 2011.

  13. Embedded microcontroller interfacing

    CERN Document Server

    Gupta, Gourab Sen

    2010-01-01

    Mixed-Signal Embedded Microcontrollers are commonly used in integrating analog components needed to control non-digital electronic systems. They are used in automatically controlled devices and products, such as automobile engine control systems, wireless remote controllers, office machines, home appliances, power tools, and toys. Microcontrollers make it economical to digitally control even more devices and processes by reducing the size and cost, compared to a design that uses a separate microprocessor, memory, and input/output devices. In many undergraduate and post-graduate courses, teachi

  14. Embedded Multimaterial Extrusion Bioprinting.

    Science.gov (United States)

    Rocca, Marco; Fragasso, Alessio; Liu, Wanjun; Heinrich, Marcel A; Zhang, Yu Shrike

    2018-04-01

    Embedded extrusion bioprinting allows for the generation of complex structures that otherwise cannot be achieved with conventional layer-by-layer deposition from the bottom, by overcoming the limits imposed by gravitational force. By taking advantage of a hydrogel bath, serving as a sacrificial printing environment, it is feasible to extrude a bioink in freeform until the entire structure is deposited and crosslinked. The bioprinted structure can be subsequently released from the supporting hydrogel and used for further applications. Combining this advanced three-dimensional (3D) bioprinting technique with a multimaterial extrusion printhead setup enables the fabrication of complex volumetric structures built from multiple bioinks. The work described in this paper focuses on the optimization of the experimental setup and proposes a workflow to automate the bioprinting process, resulting in a fast and efficient conversion of a virtual 3D model into a physical, extruded structure in freeform using the multimaterial embedded bioprinting system. It is anticipated that further development of this technology will likely lead to widespread applications in areas such as tissue engineering, pharmaceutical testing, and organs-on-chips.

  15. Learning optimal embedded cascades.

    Science.gov (United States)

    Saberian, Mohammad Javad; Vasconcelos, Nuno

    2012-10-01

    The problem of automatic and optimal design of embedded object detector cascades is considered. Two main challenges are identified: optimization of the cascade configuration and optimization of individual cascade stages, so as to achieve the best tradeoff between classification accuracy and speed, under a detection rate constraint. Two novel boosting algorithms are proposed to address these problems. The first, RCBoost, formulates boosting as a constrained optimization problem which is solved with a barrier penalty method. The constraint is the target detection rate, which is met at all iterations of the boosting process. This enables the design of embedded cascades of known configuration without extensive cross validation or heuristics. The second, ECBoost, searches over cascade configurations to achieve the optimal tradeoff between classification risk and speed. The two algorithms are combined into an overall boosting procedure, RCECBoost, which optimizes both the cascade configuration and its stages under a detection rate constraint, in a fully automated manner. Extensive experiments in face, car, pedestrian, and panda detection show that the resulting detectors achieve an accuracy versus speed tradeoff superior to those of previous methods.

  16. Social dilemma alleviated by sharing the gains with immediate neighbors

    Science.gov (United States)

    Wu, Zhi-Xi; Yang, Han-Xin

    2014-01-01

    We study the evolution of cooperation in the evolutionary spatial prisoner's dilemma game (PDG) and snowdrift game (SG), within which a fraction α of the payoffs of each player gained from direct game interactions is shared equally by the immediate neighbors. The magnitude of the parameter α therefore characterizes the degree of the relatedness among the neighboring players. By means of extensive Monte Carlo simulations as well as an extended mean-field approximation method, we trace the frequency of cooperation in the stationary state. We find that plugging into relatedness can significantly promote the evolution of cooperation in the context of both studied games. Unexpectedly, cooperation can be more readily established in the spatial PDG than that in the spatial SG, given that the degree of relatedness and the cost-to-benefit ratio of mutual cooperation are properly formulated. The relevance of our model with the stakeholder theory is also briefly discussed.

  17. Grain price spikes and beggar-thy-neighbor policy responses

    DEFF Research Database (Denmark)

    Boysen, Ole; Jensen, Hans Grinsted

    on the agenda of various international policy fora, including the annual meetings of G20 countries in recent years. For that reason, recent studies have attempted to quantify the extent to which such policy actions contributed to the rise in food prices. A study by Jensen & Anderson (2014) uses the global AGE...... model GTAP and the corresponding database to quantify the global policy actions contributions to the raise in food prices by modeling the changes in distortions to agricultural incentives in the period 2006 to 2008. We link the results from this global model into a national AGE model, highlighting how...... global "Beggar-thy-Neighbor Policy Responses" impacted on poor households in Uganda. More specifically we examine the following research questions: What were the Ugandan economy-wide and poverty impacts of the price spikes? What was the impact of other countries "Beggar-thy-Neighbor Policy Responses...

  18. Nearest Neighbor Networks: clustering expression data based on gene neighborhoods

    Directory of Open Access Journals (Sweden)

    Olszewski Kellen L

    2007-07-01

    Full Text Available Abstract Background The availability of microarrays measuring thousands of genes simultaneously across hundreds of biological conditions represents an opportunity to understand both individual biological pathways and the integrated workings of the cell. However, translating this amount of data into biological insight remains a daunting task. An important initial step in the analysis of microarray data is clustering of genes with similar behavior. A number of classical techniques are commonly used to perform this task, particularly hierarchical and K-means clustering, and many novel approaches have been suggested recently. While these approaches are useful, they are not without drawbacks; these methods can find clusters in purely random data, and even clusters enriched for biological functions can be skewed towards a small number of processes (e.g. ribosomes. Results We developed Nearest Neighbor Networks (NNN, a graph-based algorithm to generate clusters of genes with similar expression profiles. This method produces clusters based on overlapping cliques within an interaction network generated from mutual nearest neighborhoods. This focus on nearest neighbors rather than on absolute distance measures allows us to capture clusters with high connectivity even when they are spatially separated, and requiring mutual nearest neighbors allows genes with no sufficiently similar partners to remain unclustered. We compared the clusters generated by NNN with those generated by eight other clustering methods. NNN was particularly successful at generating functionally coherent clusters with high precision, and these clusters generally represented a much broader selection of biological processes than those recovered by other methods. Conclusion The Nearest Neighbor Networks algorithm is a valuable clustering method that effectively groups genes that are likely to be functionally related. It is particularly attractive due to its simplicity, its success in the

  19. Crimean-Congo hemorrhagic fever in Iran and neighboring countries

    DEFF Research Database (Denmark)

    Chinikar, S; Ghiasi, Seyed Mojtaba; Hewson, R

    2010-01-01

    Crimean-Congo hemorrhagic fever (CCHF) is a zoonotic viral disease that is asymptomatic in infected livestock, but a serious threat to humans. Human infections begin with nonspecific febrile symptoms, but progress to a serious hemorrhagic syndrome with a case fatality rate of 2-50%. Although the ...... in Iran and neighboring countries and provide evidence of over 5000 confirmed cases of CCHF in a single period/season....

  20. Fast Most Similar Neighbor (MSN) classifiers for Mixed Data

    OpenAIRE

    Hernández Rodríguez, Selene

    2010-01-01

    The k nearest neighbor (k-NN) classifier has been extensively used in Pattern Recognition because of its simplicity and its good performance. However, in large datasets applications, the exhaustive k-NN classifier becomes impractical. Therefore, many fast k-NN classifiers have been developed; most of them rely on metric properties (usually the triangle inequality) to reduce the number of prototype comparisons. Hence, the existing fast k-NN classifiers are applicable only when the comparison f...

  1. ENTROPY CHARACTERISTICS IN MODELS FOR COORDINATION OF NEIGHBORING ROAD SECTIONS

    Directory of Open Access Journals (Sweden)

    N. I. Kulbashnaya

    2016-01-01

    Full Text Available The paper considers an application of entropy characteristics as criteria to coordinate traffic conditions at neighboring road sections. It has been proved that the entropy characteristics are widely used in the methods that take into account information influence of the environment on drivers and in the mechanisms that create such traffic conditions which ensure preservation of the optimal level of driver’s emotional tension during the drive. Solution of such problem is considered in the aspect of coordination of traffic conditions at neighboring road sections that, in its turn, is directed on exclusion of any driver’s transitional processes. Methodology for coordination of traffic conditions at neighboring road sections is based on the E. V. Gavrilov’s concept on coordination of some parameters of road sections which can be expressed in the entropy characteristics. The paper proposes to execute selection of coordination criteria according to accident rates because while moving along neighboring road sections traffic conditions change drastically that can result in creation of an accident situation. Relative organization of a driver’s perception field and driver’s interaction with the traffic environment has been selected as entropy characteristics. Therefore, the given characteristics are made conditional to the road accidents rate. The investigation results have revealed a strong correlation between the relative organization of the driver’s perception field and the relative organization of the driver’s interaction with the traffic environment and the accident rate. Results of the executed experiment have proved an influence of the accident rate on the investigated entropy characteristics.

  2. Do alcohol compliance checks decrease underage sales at neighboring establishments?

    Science.gov (United States)

    Erickson, Darin J; Smolenski, Derek J; Toomey, Traci L; Carlin, Bradley P; Wagenaar, Alexander C

    2013-11-01

    Underage alcohol compliance checks conducted by law enforcement agencies can reduce the likelihood of illegal alcohol sales at checked alcohol establishments, and theory suggests that an alcohol establishment that is checked may warn nearby establishments that compliance checks are being conducted in the area. In this study, we examined whether the effects of compliance checks diffuse to neighboring establishments. We used data from the Complying with the Minimum Drinking Age trial, which included more than 2,000 compliance checks conducted at more than 900 alcohol establishments. The primary outcome was the sale of alcohol to a pseudo-underage buyer without the need for age identification. A multilevel logistic regression was used to model the effect of a compliance check at each establishment as well as the effect of compliance checks at neighboring establishments within 500 m (stratified into four equal-radius concentric rings), after buyer, license, establishment, and community-level variables were controlled for. We observed a decrease in the likelihood of establishments selling alcohol to underage youth after they had been checked by law enforcement, but these effects quickly decayed over time. Establishments that had a close neighbor (within 125 m) checked in the past 90 days were also less likely to sell alcohol to young-appearing buyers. The spatial effect of compliance checks on other establishments decayed rapidly with increasing distance. Results confirm the hypothesis that the effects of police compliance checks do spill over to neighboring establishments. These findings have implications for the development of an optimal schedule of police compliance checks.

  3. Single cell transcriptomics of neighboring hyphae of Aspergillus niger

    Science.gov (United States)

    2011-01-01

    Single cell profiling was performed to assess differences in RNA accumulation in neighboring hyphae of the fungus Aspergillus niger. A protocol was developed to isolate and amplify RNA from single hyphae or parts thereof. Microarray analysis resulted in a present call for 4 to 7% of the A. niger genes, of which 12% showed heterogeneous RNA levels. These genes belonged to a wide range of gene categories. PMID:21816052

  4. [Galaxy/quasar classification based on nearest neighbor method].

    Science.gov (United States)

    Li, Xiang-Ru; Lu, Yu; Zhou, Jian-Ming; Wang, Yong-Jun

    2011-09-01

    With the wide application of high-quality CCD in celestial spectrum imagery and the implementation of many large sky survey programs (e. g., Sloan Digital Sky Survey (SDSS), Two-degree-Field Galaxy Redshift Survey (2dF), Spectroscopic Survey Telescope (SST), Large Sky Area Multi-Object Fiber Spectroscopic Telescope (LAMOST) program and Large Synoptic Survey Telescope (LSST) program, etc.), celestial observational data are coming into the world like torrential rain. Therefore, to utilize them effectively and fully, research on automated processing methods for celestial data is imperative. In the present work, we investigated how to recognizing galaxies and quasars from spectra based on nearest neighbor method. Galaxies and quasars are extragalactic objects, they are far away from earth, and their spectra are usually contaminated by various noise. Therefore, it is a typical problem to recognize these two types of spectra in automatic spectra classification. Furthermore, the utilized method, nearest neighbor, is one of the most typical, classic, mature algorithms in pattern recognition and data mining, and often is used as a benchmark in developing novel algorithm. For applicability in practice, it is shown that the recognition ratio of nearest neighbor method (NN) is comparable to the best results reported in the literature based on more complicated methods, and the superiority of NN is that this method does not need to be trained, which is useful in incremental learning and parallel computation in mass spectral data processing. In conclusion, the results in this work are helpful for studying galaxies and quasars spectra classification.

  5. Evidence for cultural differences between neighboring chimpanzee communities.

    Science.gov (United States)

    Luncz, Lydia V; Mundry, Roger; Boesch, Christophe

    2012-05-22

    The majority of evidence for cultural behavior in animals has come from comparisons between populations separated by large geographical distances that often inhabit different environments. The difficulty of excluding ecological and genetic variation as potential explanations for observed behaviors has led some researchers to challenge the idea of animal culture. Chimpanzees (Pan troglodytes verus) in the Taï National Park, Côte d'Ivoire, crack Coula edulis nuts using stone and wooden hammers and tree root anvils. In this study, we compare for the first time hammer selection for nut cracking across three neighboring chimpanzee communities that live in the same forest habitat, which reduces the likelihood of ecological variation. Furthermore, the study communities experience frequent dispersal of females at maturity, which eliminates significant genetic variation. We compared key ecological factors, such as hammer availability and nut hardness, between the three neighboring communities and found striking differences in group-specific hammer selection among communities despite similar ecological conditions. Differences were found in the selection of hammer material and hammer size in response to changes in nut resistance over time. Our findings highlight the subtleties of cultural differences in wild chimpanzees and illustrate how cultural knowledge is able to shape behavior, creating differences among neighboring social groups. Copyright © 2012 Elsevier Ltd. All rights reserved.

  6. Spatially Embedded Inequality

    DEFF Research Database (Denmark)

    Holck, Lotte

    2016-01-01

    /methodology/approach: – The (re)production of inequality is explored by linking research on organizational space with HRM diversity management. Data from an ethnographic study undertaken in a Danish municipal center illustrates how a substructure of inequality is spatially upheld alongside a formal diversity policy. Archer...... and ethnification of job categories. However, the same spatial structures allows for a variety of opposition and conciliation strategies among minority employees, even though the latter tend to prevail in a reproduction rather than a transformation of the organizational opportunity structures. Research limitations...... the more subtle, spatially embedded forms of inequality. Originality/value: – Theoretical and empirical connections between research on organizational space and HRM diversity management have thus far not been systematically studied. This combination might advance knowledge on the persistence of micro...

  7. Embedded sensor systems

    CERN Document Server

    Agrawal, Dharma Prakash

    2017-01-01

    This inspiring textbook provides an introduction to wireless technologies for sensors, explores potential use of sensors for numerous applications, and utilizes probability theory and mathematical methods as a means of embedding sensors in system design. It discusses the need for synchronization and underlying limitations, inter-relation between given coverage and connectivity to number of sensors needed, and the use of geometrical distance to determine location of the base station for data collection and explore use of anchor nodes for relative position determination of sensors. The book explores energy conservation, communication using TCP, the need for clustering and data aggregation, and residual energy determination and energy harvesting. It covers key topics of sensor communication like mobile base stations and relay nodes, delay-tolerant sensor networks, and remote sensing and possible applications. The book defines routing methods and do performance evaluation for random and regular sensor topology an...

  8. Communicating embedded systems networks applications

    CERN Document Server

    Krief, Francine

    2013-01-01

    Embedded systems become more and more complex and require having some knowledge in various disciplines such as electronics, data processing, telecommunications and networks. Without detailing all the aspects related to the design of embedded systems, this book, which was written by specialists in electronics, data processing and telecommunications and networks, gives an interesting point of view of communication techniques and problems in embedded systems. This choice is easily justified by the fact that embedded systems are today massively communicating and that telecommunications and network

  9. Advances in embedded computer vision

    CERN Document Server

    Kisacanin, Branislav

    2014-01-01

    This illuminating collection offers a fresh look at the very latest advances in the field of embedded computer vision. Emerging areas covered by this comprehensive text/reference include the embedded realization of 3D vision technologies for a variety of applications, such as stereo cameras on mobile devices. Recent trends towards the development of small unmanned aerial vehicles (UAVs) with embedded image and video processing algorithms are also examined. The authoritative insights range from historical perspectives to future developments, reviewing embedded implementation, tools, technolog

  10. Embedded Systems Design with FPGAs

    CERN Document Server

    Pnevmatikatos, Dionisios; Sklavos, Nicolas

    2013-01-01

    This book presents methodologies for modern applications of embedded systems design, using field programmable gate array (FPGA) devices.  Coverage includes state-of-the-art research from academia and industry on a wide range of topics, including advanced electronic design automation (EDA), novel system architectures, embedded processors, arithmetic, dynamic reconfiguration and applications. Describes a variety of methodologies for modern embedded systems design;  Implements methodologies presented on FPGAs; Covers a wide variety of applications for reconfigurable embedded systems, including Bioinformatics, Communications and networking, Application acceleration, Medical solutions, Experiments for high energy physics, Astronomy, Aerospace, Biologically inspired systems and Computational fluid dynamics (CFD).

  11. Embedding Complementarity in HCI Methods

    DEFF Research Database (Denmark)

    Nielsen, Janni; Yssing, Carsten; Tweddell Levinsen, Karin

    2007-01-01

    Differences in cultural contexts constitute differences in cognition, and research has shown that different cultures may use different cognitive tools for perception and reasoning. The cultural embeddings are significant in relation to HCI, because the cultural context is also embedded in the tec......Differences in cultural contexts constitute differences in cognition, and research has shown that different cultures may use different cognitive tools for perception and reasoning. The cultural embeddings are significant in relation to HCI, because the cultural context is also embedded...

  12. Embedding potentials for excited states of embedded species

    International Nuclear Information System (INIS)

    Wesolowski, Tomasz A.

    2014-01-01

    Frozen-Density-Embedding Theory (FDET) is a formalism to obtain the upper bound of the ground-state energy of the total system and the corresponding embedded wavefunction by means of Euler-Lagrange equations [T. A. Wesolowski, Phys. Rev. A 77(1), 012504 (2008)]. FDET provides the expression for the embedding potential as a functional of the electron density of the embedded species, electron density of the environment, and the field generated by other charges in the environment. Under certain conditions, FDET leads to the exact ground-state energy and density of the whole system. Following Perdew-Levy theorem on stationary states of the ground-state energy functional, the other-than-ground-state stationary states of the FDET energy functional correspond to excited states. In the present work, we analyze such use of other-than-ground-state embedded wavefunctions obtained in practical calculations, i.e., when the FDET embedding potential is approximated. Three computational approaches based on FDET, that assure self-consistent excitation energy and embedded wavefunction dealing with the issue of orthogonality of embedded wavefunctions for different states in a different manner, are proposed and discussed

  13. Modeling of Embedded Human Systems

    Science.gov (United States)

    2013-07-01

    ISAT study [7] for DARPA in 20051 concretized the notion of an embedded human, who is a necessary component of the system. The proposed work integrates...Technology, IEEE Transactions on, vol. 16, no. 2, pp. 229–244, March 2008. [7] C. J. Tomlin and S. S. Sastry, “Embedded humans,” tech. rep., DARPA ISAT

  14. Embedded palmprint recognition system using OMAP 3530.

    Science.gov (United States)

    Shen, Linlin; Wu, Shipei; Zheng, Songhao; Ji, Zhen

    2012-01-01

    We have proposed in this paper an embedded palmprint recognition system using the dual-core OMAP 3530 platform. An improved algorithm based on palm code was proposed first. In this method, a Gabor wavelet is first convolved with the palmprint image to produce a response image, where local binary patterns are then applied to code the relation among the magnitude of wavelet response at the central pixel with that of its neighbors. The method is fully tested using the public PolyU palmprint database. While palm code achieves only about 89% accuracy, over 96% accuracy is achieved by the proposed G-LBP approach. The proposed algorithm was then deployed to the DSP processor of OMAP 3530 and work together with the ARM processor for feature extraction. When complicated algorithms run on the DSP processor, the ARM processor can focus on image capture, user interface and peripheral control. Integrated with an image sensing module and central processing board, the designed device can achieve accurate and real time performance.

  15. Quality and efficiency in high dimensional Nearest neighbor search

    KAUST Repository

    Tao, Yufei; Yi, Ke; Sheng, Cheng; Kalnis, Panos

    2009-01-01

    Nearest neighbor (NN) search in high dimensional space is an important problem in many applications. Ideally, a practical solution (i) should be implementable in a relational database, and (ii) its query cost should grow sub-linearly with the dataset size, regardless of the data and query distributions. Despite the bulk of NN literature, no solution fulfills both requirements, except locality sensitive hashing (LSH). The existing LSH implementations are either rigorous or adhoc. Rigorous-LSH ensures good quality of query results, but requires expensive space and query cost. Although adhoc-LSH is more efficient, it abandons quality control, i.e., the neighbor it outputs can be arbitrarily bad. As a result, currently no method is able to ensure both quality and efficiency simultaneously in practice. Motivated by this, we propose a new access method called the locality sensitive B-tree (LSB-tree) that enables fast highdimensional NN search with excellent quality. The combination of several LSB-trees leads to a structure called the LSB-forest that ensures the same result quality as rigorous-LSH, but reduces its space and query cost dramatically. The LSB-forest also outperforms adhoc-LSH, even though the latter has no quality guarantee. Besides its appealing theoretical properties, the LSB-tree itself also serves as an effective index that consumes linear space, and supports efficient updates. Our extensive experiments confirm that the LSB-tree is faster than (i) the state of the art of exact NN search by two orders of magnitude, and (ii) the best (linear-space) method of approximate retrieval by an order of magnitude, and at the same time, returns neighbors with much better quality. © 2009 ACM.

  16. Mountain tourism development in Serbia and neighboring countries

    Directory of Open Access Journals (Sweden)

    Krunić Nikola

    2010-01-01

    Full Text Available Mountain areas with their surroundings are important parts of tourism regions with potentials for all-season tourism development and complementary activities. Development possibilities are based on size of high mountain territory, nature protection regimes, infrastructural equipment, provided conditions for leisure and recreation as well as involvement of local population in processes of development and protection. This paper analyses the key aspects of tourism development, winter tourism in high-mountain areas of Serbia and some neighboring countries (Slovakia, Romania, Bulgaria, and Greece. Common determinants of cohesion between nature protection and mountain tourism development, national development policies, applied models and concepts and importance of trans-border cooperation are indicated.

  17. Neighboring Structure Visualization on a Grid-based Layout.

    Science.gov (United States)

    Marcou, G; Horvath, D; Varnek, A

    2017-10-01

    Here, we describe an algorithm to visualize chemical structures on a grid-based layout in such a way that similar structures are neighboring. It is based on structure reordering with the help of the Hilbert Schmidt Independence Criterion, representing an empirical estimate of the Hilbert-Schmidt norm of the cross-covariance operator. The method can be applied to any layout of bi- or three-dimensional shape. The approach is demonstrated on a set of dopamine D5 ligands visualized on squared, disk and spherical layouts. © 2017 Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim.

  18. The nearest neighbor and the bayes error rates.

    Science.gov (United States)

    Loizou, G; Maybank, S J

    1987-02-01

    The (k, l) nearest neighbor method of pattern classification is compared to the Bayes method. If the two acceptance rates are equal then the asymptotic error rates satisfy the inequalities Ek,l + 1 ¿ E*(¿) ¿ Ek,l dE*(¿), where d is a function of k, l, and the number of pattern classes, and ¿ is the reject threshold for the Bayes method. An explicit expression for d is given which is optimal in the sense that for some probability distributions Ek,l and dE* (¿) are equal.

  19. Fault Diagnosis of Supervision and Homogenization Distance Based on Local Linear Embedding Algorithm

    Directory of Open Access Journals (Sweden)

    Guangbin Wang

    2015-01-01

    Full Text Available In view of the problems of uneven distribution of reality fault samples and dimension reduction effect of locally linear embedding (LLE algorithm which is easily affected by neighboring points, an improved local linear embedding algorithm of homogenization distance (HLLE is developed. The method makes the overall distribution of sample points tend to be homogenization and reduces the influence of neighboring points using homogenization distance instead of the traditional Euclidean distance. It is helpful to choose effective neighboring points to construct weight matrix for dimension reduction. Because the fault recognition performance improvement of HLLE is limited and unstable, the paper further proposes a new local linear embedding algorithm of supervision and homogenization distance (SHLLE by adding the supervised learning mechanism. On the basis of homogenization distance, supervised learning increases the category information of sample points so that the same category of sample points will be gathered and the heterogeneous category of sample points will be scattered. It effectively improves the performance of fault diagnosis and maintains stability at the same time. A comparison of the methods mentioned above was made by simulation experiment with rotor system fault diagnosis, and the results show that SHLLE algorithm has superior fault recognition performance.

  20. Diagnostic tools for nearest neighbors techniques when used with satellite imagery

    Science.gov (United States)

    Ronald E. McRoberts

    2009-01-01

    Nearest neighbors techniques are non-parametric approaches to multivariate prediction that are useful for predicting both continuous and categorical forest attribute variables. Although some assumptions underlying nearest neighbor techniques are common to other prediction techniques such as regression, other assumptions are unique to nearest neighbor techniques....

  1. Using K-Nearest Neighbor in Optical Character Recognition

    Directory of Open Access Journals (Sweden)

    Veronica Ong

    2016-03-01

    Full Text Available The growth in computer vision technology has aided society with various kinds of tasks. One of these tasks is the ability of recognizing text contained in an image, or usually referred to as Optical Character Recognition (OCR. There are many kinds of algorithms that can be implemented into an OCR. The K-Nearest Neighbor is one such algorithm. This research aims to find out the process behind the OCR mechanism by using K-Nearest Neighbor algorithm; one of the most influential machine learning algorithms. It also aims to find out how precise the algorithm is in an OCR program. To do that, a simple OCR program to classify alphabets of capital letters is made to produce and compare real results. The result of this research yielded a maximum of 76.9% accuracy with 200 training samples per alphabet. A set of reasons are also given as to why the program is able to reach said level of accuracy.

  2. Kinetic Models for Topological Nearest-Neighbor Interactions

    Science.gov (United States)

    Blanchet, Adrien; Degond, Pierre

    2017-12-01

    We consider systems of agents interacting through topological interactions. These have been shown to play an important part in animal and human behavior. Precisely, the system consists of a finite number of particles characterized by their positions and velocities. At random times a randomly chosen particle, the follower, adopts the velocity of its closest neighbor, the leader. We study the limit of a system size going to infinity and, under the assumption of propagation of chaos, show that the limit kinetic equation is a non-standard spatial diffusion equation for the particle distribution function. We also study the case wherein the particles interact with their K closest neighbors and show that the corresponding kinetic equation is the same. Finally, we prove that these models can be seen as a singular limit of the smooth rank-based model previously studied in Blanchet and Degond (J Stat Phys 163:41-60, 2016). The proofs are based on a combinatorial interpretation of the rank as well as some concentration of measure arguments.

  3. Attribute Weighting Based K-Nearest Neighbor Using Gain Ratio

    Science.gov (United States)

    Nababan, A. A.; Sitompul, O. S.; Tulus

    2018-04-01

    K- Nearest Neighbor (KNN) is a good classifier, but from several studies, the result performance accuracy of KNN still lower than other methods. One of the causes of the low accuracy produced, because each attribute has the same effect on the classification process, while some less relevant characteristics lead to miss-classification of the class assignment for new data. In this research, we proposed Attribute Weighting Based K-Nearest Neighbor Using Gain Ratio as a parameter to see the correlation between each attribute in the data and the Gain Ratio also will be used as the basis for weighting each attribute of the dataset. The accuracy of results is compared to the accuracy acquired from the original KNN method using 10-fold Cross-Validation with several datasets from the UCI Machine Learning repository and KEEL-Dataset Repository, such as abalone, glass identification, haberman, hayes-roth and water quality status. Based on the result of the test, the proposed method was able to increase the classification accuracy of KNN, where the highest difference of accuracy obtained hayes-roth dataset is worth 12.73%, and the lowest difference of accuracy obtained in the abalone dataset of 0.07%. The average result of the accuracy of all dataset increases the accuracy by 5.33%.

  4. Phylogenetic trees and Euclidean embeddings.

    Science.gov (United States)

    Layer, Mark; Rhodes, John A

    2017-01-01

    It was recently observed by de Vienne et al. (Syst Biol 60(6):826-832, 2011) that a simple square root transformation of distances between taxa on a phylogenetic tree allowed for an embedding of the taxa into Euclidean space. While the justification for this was based on a diffusion model of continuous character evolution along the tree, here we give a direct and elementary explanation for it that provides substantial additional insight. We use this embedding to reinterpret the differences between the NJ and BIONJ tree building algorithms, providing one illustration of how this embedding reflects tree structures in data.

  5. Tensor Train Neighborhood Preserving Embedding

    Science.gov (United States)

    Wang, Wenqi; Aggarwal, Vaneet; Aeron, Shuchin

    2018-05-01

    In this paper, we propose a Tensor Train Neighborhood Preserving Embedding (TTNPE) to embed multi-dimensional tensor data into low dimensional tensor subspace. Novel approaches to solve the optimization problem in TTNPE are proposed. For this embedding, we evaluate novel trade-off gain among classification, computation, and dimensionality reduction (storage) for supervised learning. It is shown that compared to the state-of-the-arts tensor embedding methods, TTNPE achieves superior trade-off in classification, computation, and dimensionality reduction in MNIST handwritten digits and Weizmann face datasets.

  6. Parametric embedding for class visualization.

    Science.gov (United States)

    Iwata, Tomoharu; Saito, Kazumi; Ueda, Naonori; Stromsten, Sean; Griffiths, Thomas L; Tenenbaum, Joshua B

    2007-09-01

    We propose a new method, parametric embedding (PE), that embeds objects with the class structure into a low-dimensional visualization space. PE takes as input a set of class conditional probabilities for given data points and tries to preserve the structure in an embedding space by minimizing a sum of Kullback-Leibler divergences, under the assumption that samples are generated by a gaussian mixture with equal covariances in the embedding space. PE has many potential uses depending on the source of the input data, providing insight into the classifier's behavior in supervised, semisupervised, and unsupervised settings. The PE algorithm has a computational advantage over conventional embedding methods based on pairwise object relations since its complexity scales with the product of the number of objects and the number of classes. We demonstrate PE by visualizing supervised categorization of Web pages, semisupervised categorization of digits, and the relations of words and latent topics found by an unsupervised algorithm, latent Dirichlet allocation.

  7. Embedded System for Biometric Identification

    OpenAIRE

    Rosli, Ahmad Nasir Che

    2010-01-01

    This chapter describes the design and implementation of an Embedded System for Biometric Identification from hardware and software perspectives. The first part of the chapter describes the idea of biometric identification. This includes the definition of

  8. Hardware Support for Embedded Java

    DEFF Research Database (Denmark)

    Schoeberl, Martin

    2012-01-01

    The general Java runtime environment is resource hungry and unfriendly for real-time systems. To reduce the resource consumption of Java in embedded systems, direct hardware support of the language is a valuable option. Furthermore, an implementation of the Java virtual machine in hardware enables...... worst-case execution time analysis of Java programs. This chapter gives an overview of current approaches to hardware support for embedded and real-time Java....

  9. Molecular Properties through Polarizable Embedding

    DEFF Research Database (Denmark)

    Olsen, Jógvan Magnus Haugaard; Kongsted, Jacob

    2011-01-01

    We review the theory related to the calculation of electric and magnetic molecular properties through polarizable embedding. In particular, we derive the expressions for the response functions up to the level of cubic response within the density functional theory-based polarizable embedding (PE......-DFT) formalism. In addition, we discuss some illustrative applications related to the calculation of nuclear magnetic resonance parameters, nonlinear optical properties, and electronic excited states in solution....

  10. A Foundation for Embedded Languages

    DEFF Research Database (Denmark)

    Rhiger, Morten

    2003-01-01

    Recent work on embedding object languages into Haskell use "phantom types" (i.e., parameterized types whose parameter does not occur on the right-hand side of the type definition) to ensure that the embedded object-language terms are simply typed. But is it a safe assumption that only simply...... be answered affirmatively for an idealized Haskell-like language and discuss to which extent Haskell can be used as a meta-language....

  11. Unsupervised Document Embedding With CNNs

    OpenAIRE

    Liu, Chundi; Zhao, Shunan; Volkovs, Maksims

    2017-01-01

    We propose a new model for unsupervised document embedding. Leading existing approaches either require complex inference or use recurrent neural networks (RNN) that are difficult to parallelize. We take a different route and develop a convolutional neural network (CNN) embedding model. Our CNN architecture is fully parallelizable resulting in over 10x speedup in inference time over RNN models. Parallelizable architecture enables to train deeper models where each successive layer has increasin...

  12. Enhanced Approximate Nearest Neighbor via Local Area Focused Search.

    Energy Technology Data Exchange (ETDEWEB)

    Gonzales, Antonio [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Blazier, Nicholas Paul [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States)

    2017-02-01

    Approximate Nearest Neighbor (ANN) algorithms are increasingly important in machine learning, data mining, and image processing applications. There is a large family of space- partitioning ANN algorithms, such as randomized KD-Trees, that work well in practice but are limited by an exponential increase in similarity comparisons required to optimize recall. Additionally, they only support a small set of similarity metrics. We present Local Area Fo- cused Search (LAFS), a method that enhances the way queries are performed using an existing ANN index. Instead of a single query, LAFS performs a number of smaller (fewer similarity comparisons) queries and focuses on a local neighborhood which is refined as candidates are identified. We show that our technique improves performance on several well known datasets and is easily extended to general similarity metrics using kernel projection techniques.

  13. Nearest Neighbor Estimates of Entropy for Multivariate Circular Distributions

    Directory of Open Access Journals (Sweden)

    Neeraj Misra

    2010-05-01

    Full Text Available In molecular sciences, the estimation of entropies of molecules is important for the understanding of many chemical and biological processes. Motivated by these applications, we consider the problem of estimating the entropies of circular random vectors and introduce non-parametric estimators based on circular distances between n sample points and their k th nearest neighbors (NN, where k (≤ n – 1 is a fixed positive integer. The proposed NN estimators are based on two different circular distances, and are proven to be asymptotically unbiased and consistent. The performance of one of the circular-distance estimators is investigated and compared with that of the already established Euclidean-distance NN estimator using Monte Carlo samples from an analytic distribution of six circular variables of an exactly known entropy and a large sample of seven internal-rotation angles in the molecule of tartaric acid, obtained by a realistic molecular-dynamics simulation.

  14. Introduction to machine learning: k-nearest neighbors.

    Science.gov (United States)

    Zhang, Zhongheng

    2016-06-01

    Machine learning techniques have been widely used in many scientific fields, but its use in medical literature is limited partly because of technical difficulties. k-nearest neighbors (kNN) is a simple method of machine learning. The article introduces some basic ideas underlying the kNN algorithm, and then focuses on how to perform kNN modeling with R. The dataset should be prepared before running the knn() function in R. After prediction of outcome with kNN algorithm, the diagnostic performance of the model should be checked. Average accuracy is the mostly widely used statistic to reflect the kNN algorithm. Factors such as k value, distance calculation and choice of appropriate predictors all have significant impact on the model performance.

  15. Measurement of near neighbor separations of surface atoms

    International Nuclear Information System (INIS)

    Cohen, P.I.

    Two techniques are being developed to measure the nearest neighbor distances of atoms at the surfaces of solids. Both measures extended fine structure in the excitation probability of core level electrons which are excited by an incident electron beam. This is an important problem because the structures of most surface systems are as yet unknown, even though the location of surface atoms is the basis for any quantitative understanding of the chemistry and physics of surfaces and interfaces. These methods would allow any laboratory to make in situ determinations of surface structure in conjunction with most other laboratory probes of surfaces. Each of these two techniques has different advantages; further, the combination of the two will increase confidence in the results by reducing systematic error in the data analysis

  16. Radionuclide content of an exhumed canyon vessel and neighboring soil

    International Nuclear Information System (INIS)

    Holcomb, H.P.

    1976-11-01

    The long-term hazard potential associated with burial of process equipment from radiochemical separations plants is being evaluated. As part of this evaluation, a feed adjustment tank was exhumed eighteen years after burial. The tank had been in service in the fuel reprocessing plant for twenty-nine months before it was retired. Assay of the exhumed tank indicated that 7 mg (0.4 mCi) of 239 Pu and 1 mCi of 137 Cs remained on its surfaces; 1.1 mg (0.07 mCi) 239 Pu, 0.4 mCi 137 Cs, and 3.5 mCi 90 Sr were found in neighboring soil. The vessel and surrounding soil have met the present guidelines (less than or equal to 10 nCi/g) of the U. S. Energy Research and Development Administration (ERDA) for nonretrievable waste

  17. Reduction of Conflicts in Mining Development Using "Good Neighbor Agreements"

    Science.gov (United States)

    Masaitis, A.

    2013-05-01

    New environmental and social challenges for the mining industry in both developed and developing countries show the obvious need to implement "responsible" mining practices that include improved community involvement. Good Neighbor Agreements (GNA's) are a relatively new mechanism for improving communication and trust between a mining company and the community. The focus of a GNA will be to provide a written and enforceable agreement, negotiated between the concerned public and the respective mining company to respond to concerns from the public, and also provide a mechanism for conflict resolution, when there is mutual benefit to maintain a working relationship. Development of GNA's, a recently evolving process that promotes environmentally sound relationships between mines and the surrounding communities. Modify and apply the resulting GNA formulas to the developing countries and countries with transitional economies. This is particularly important for countries that have poorly functioning regulatory systems that cannot guarantee a healthy and safe environment for the communities. The fundamental questions addressed by this research. 1. This is a three-year research project started in August 2012 at the University of Nevada, Reno (UNR) to develop a Good Neighbor Agreements standards as well as to investigate the details of mine development. 2. Identify spheres of possible cooperation between mining companies, government organizations, and the Non-Governmental Organizations (NGO's). Use this cooperation to develop international standards for the GNA, to promote exchange of environmental information, and exchange of successful environmental, health, and safety practices between mining operations from different countries. Discussion: The Good Neighbor Agreement currently evolving will address the following: 1. Provide an economically viable mechanism for developing a partnership between mining operations and the local communities that will increase mining industry

  18. Building good relationships with neighbors of Japan's oldest plant, Tsuruga

    International Nuclear Information System (INIS)

    Hata, Emi

    1992-01-01

    Since its establishment in 1957 as a pioneer company of nuclear power development in Japan, the Japan Atomic Power Company (JAPC) has gained a great deal of experience with construction and operation of four nuclear power plants - one gas-cooled reactor, two boiling water reactors (BWRs), and one pressurized water reactor (PWR) - at two sites, Tsuruga and Tokai. To gain the understanding and cooperation of the local community, the Tsuruga station must keep running. Each employee is encouraged to make every possible effort not only to ensure the safe and reliable operation of the two units, but also to ensure conscientious coexistence and coprosperity within the local community. The Tsuruga office in the city and the Public Relations (PR) Pavilion (visitor's center) at the site work together as an open window of communication with the local community. Under these basic philosophies, various good neighbor activities are developed and carried out

  19. Implementation of Nearest Neighbor using HSV to Identify Skin Disease

    Science.gov (United States)

    Gerhana, Y. A.; Zulfikar, W. B.; Ramdani, A. H.; Ramdhani, M. A.

    2018-01-01

    Today, Android is one of the most widely used operating system in the world. Most of android device has a camera that could capture an image, this feature could be optimized to identify skin disease. The disease is one of health problem caused by bacterium, fungi, and virus. The symptoms of skin disease usually visible. In this work, the symptoms that captured as image contains HSV in every pixel of the image. HSV can extracted and then calculate to earn euclidean value. The value compared using nearest neighbor algorithm to discover closer value between image testing and image training to get highest value that decide class label or type of skin disease. The testing result show that 166 of 200 or about 80% is accurate. There are some reasons that influence the result of classification model like number of image training and quality of android device’s camera.

  20. Neighboring Optimal Aircraft Guidance in a General Wind Environment

    Science.gov (United States)

    Jardin, Matthew R. (Inventor)

    2003-01-01

    Method and system for determining an optimal route for an aircraft moving between first and second waypoints in a general wind environment. A selected first wind environment is analyzed for which a nominal solution can be determined. A second wind environment is then incorporated; and a neighboring optimal control (NOC) analysis is performed to estimate an optimal route for the second wind environment. In particular examples with flight distances of 2500 and 6000 nautical miles in the presence of constant or piecewise linearly varying winds, the difference in flight time between a nominal solution and an optimal solution is 3.4 to 5 percent. Constant or variable winds and aircraft speeds can be used. Updated second wind environment information can be provided and used to obtain an updated optimal route.

  1. Morphological type correlation between nearest neighbor pairs of galaxies

    Science.gov (United States)

    Yamagata, Tomohiko

    1990-01-01

    Although the morphological type of galaxies is one of the most fundamental properties of galaxies, its origin and evolutionary processes, if any, are not yet fully understood. It has been established that the galaxy morphology strongly depends on the environment in which the galaxy resides (e.g., Dressler 1980). Galaxy pairs correspond to the smallest scales of galaxy clustering and may provide important clues to how the environment influences the formation and evolution of galaxies. Several investigators pointed out that there is a tendency for pair galaxies to have similar morphological types (Karachentsev and Karachentseva 1974, Page 1975, Noerdlinger 1979). Here, researchers analyze morphological type correlation for 18,364 nearest neighbor pairs of galaxies identified in the magnetic tape version of the Center for Astrophysics Redshift Catalogue.

  2. Designing lattice structures with maximal nearest-neighbor entanglement

    Energy Technology Data Exchange (ETDEWEB)

    Navarro-Munoz, J C; Lopez-Sandoval, R [Instituto Potosino de Investigacion CientIfica y Tecnologica, Camino a la presa San Jose 2055, 78216 San Luis Potosi (Mexico); Garcia, M E [Theoretische Physik, FB 18, Universitaet Kassel and Center for Interdisciplinary Nanostructure Science and Technology (CINSaT), Heinrich-Plett-Str.40, 34132 Kassel (Germany)

    2009-08-07

    In this paper, we study the numerical optimization of nearest-neighbor concurrence of bipartite one- and two-dimensional lattices, as well as non-bipartite two-dimensional lattices. These systems are described in the framework of a tight-binding Hamiltonian while the optimization of concurrence was performed using genetic algorithms. Our results show that the concurrence of the optimized lattice structures is considerably higher than that of non-optimized systems. In the case of one-dimensional chains, the concurrence increases dramatically when the system begins to dimerize, i.e., it undergoes a structural phase transition (Peierls distortion). This result is consistent with the idea that entanglement is maximal or shows a singularity near quantum phase transitions. Moreover, the optimization of concurrence in two-dimensional bipartite and non-bipartite lattices is achieved when the structures break into smaller subsystems, which are arranged in geometrically distinguishable configurations.

  3. Credit scoring analysis using weighted k nearest neighbor

    Science.gov (United States)

    Mukid, M. A.; Widiharih, T.; Rusgiyono, A.; Prahutama, A.

    2018-05-01

    Credit scoring is a quatitative method to evaluate the credit risk of loan applications. Both statistical methods and artificial intelligence are often used by credit analysts to help them decide whether the applicants are worthy of credit. These methods aim to predict future behavior in terms of credit risk based on past experience of customers with similar characteristics. This paper reviews the weighted k nearest neighbor (WKNN) method for credit assessment by considering the use of some kernels. We use credit data from a private bank in Indonesia. The result shows that the Gaussian kernel and rectangular kernel have a better performance based on the value of percentage corrected classified whose value is 82.4% respectively.

  4. Radiative energy loss of neighboring subjets arXiv

    CERN Document Server

    Mehtar-Tani, Yacine

    We compute the in-medium energy loss probability distribution of two neighboring subjets at leading order, in the large-$N_c$ approximation. Our result exhibits a gradual onset of color decoherence of the system and accounts for two expected limiting cases. When the angular separation is smaller than the characteristic angle for medium-induced radiation, the two-pronged substructure lose energy coherently as a single color charge, namely that of the parent parton. At large angular separation the two subjets lose energy independently. Our result is a first step towards quantifying effects of energy loss as a result of the fluctuation of the multi-parton jet substructure and therefore goes beyond the standard approach to jet quenching based on single parton energy loss. We briefly discuss applications to jet observables in heavy-ion collisions.

  5. An interactive cooperation model for neighboring virtual power plants

    International Nuclear Information System (INIS)

    Shabanzadeh, Morteza; Sheikh-El-Eslami, Mohammad-Kazem; Haghifam, Mahmoud-Reza

    2017-01-01

    Highlights: •The trading strategies of a VPP in cooperation with its neighboring VPPs are addressed. •A portfolio of inter-regional contracts is considered to model this cooperation scheme. •A novel mathematical formulation for possible inadvertent transactions is provided. •A two-stage stochastic programming approach is applied to characterize the uncertainty. •Two efficient risk measures, SSD and CVaR, are implemented in the VPP decision-making problem. -- Abstract: Future distribution systems will accommodate an increasing share of distributed energy resources (DERs). Facing with this new reality, virtual power plants (VPPs) play a key role to aggregate DERs with the aim of facilitating their involvement in wholesale electricity markets. In this paper, the trading strategies of a VPP in cooperation with its neighboring VPPs are addressed. Toward this aim, a portfolio of inter-regional contracts is considered to model this cooperation and maximize the energy trade opportunities of the VPP within a medium-term horizon. To hedge against profit variability caused by market price uncertainties, two efficient risk management approaches are also implemented in the VPP decision-making problem based on the concepts of conditional value at risk (CVaR) and second-order stochastic dominance constraints (SSD). The resulting models are formulated as mixed-integer linear programming (MILP) problems that can be solved using off-the-shelf software packages. The efficiency of the proposed risk-hedging models is analyzed through a detailed case study, and thereby relevant conclusions are drawn.

  6. Embedded Linux projects using Yocto project cookbook

    CERN Document Server

    González, Alex

    2015-01-01

    If you are an embedded developer learning about embedded Linux with some experience with the Yocto project, this book is the ideal way to become proficient and broaden your knowledge with examples that are immediately applicable to your embedded developments. Experienced embedded Yocto developers will find new insight into working methodologies and ARM specific development competence.

  7. Trusted computing for embedded systems

    CERN Document Server

    Soudris, Dimitrios; Anagnostopoulos, Iraklis

    2015-01-01

    This book describes the state-of-the-art in trusted computing for embedded systems. It shows how a variety of security and trusted computing problems are addressed currently and what solutions are expected to emerge in the coming years. The discussion focuses on attacks aimed at hardware and software for embedded systems, and the authors describe specific solutions to create security features. Case studies are used to present new techniques designed as industrial security solutions. Coverage includes development of tamper resistant hardware and firmware mechanisms for lightweight embedded devices, as well as those serving as security anchors for embedded platforms required by applications such as smart power grids, smart networked and home appliances, environmental and infrastructure sensor networks, etc. ·         Enables readers to address a variety of security threats to embedded hardware and software; ·         Describes design of secure wireless sensor networks, to address secure authen...

  8. Unwanted Behaviors and Nuisance Behaviors Among Neighbors in a Belgian Community Sample.

    Science.gov (United States)

    Michaux, Emilie; Groenen, Anne; Uzieblo, Katarzyna

    2015-06-30

    Unwanted behaviors between (ex-)intimates have been extensively studied, while those behaviors within other contexts such as neighbors have received much less scientific consideration. Research indicates that residents are likely to encounter problem behaviors from their neighbors. Besides the lack of clarity in the conceptualization of problem behaviors among neighbors, little is known on which types of behaviors characterize neighbor problems. In this study, the occurrence of two types of problem behaviors encountered by neighbors was explored within a Belgian community sample: unwanted behaviors such as threats and neighbor nuisance issues such as noise nuisance. By clearly distinguishing those two types of behaviors, this study aimed at contributing to the conceptualization of neighbor problems. Next, the coping strategies used to deal with the neighbor problems were investigated. Our results indicated that unwanted behaviors were more frequently encountered by residents compared with nuisance problems. Four out of 10 respondents reported both unwanted pursuit behavior and nuisance problems. It was especially unlikely to encounter nuisance problems in isolation of unwanted pursuit behaviors. While different coping styles (avoiding the neighbor, confronting the neighbor, and enlisting help from others) were equally used by the stalked participants, none of them was perceived as being more effective in reducing the stalking behaviors. Strikingly, despite being aware of specialized help services such as community mediation services, only a very small subgroup enlisted this kind of professional help. © The Author(s) 2015.

  9. Design Methodologies for Secure Embedded Systems

    CERN Document Server

    Biedermann, Alexander

    2011-01-01

    Embedded systems have been almost invisibly pervading our daily lives for several decades. They facilitate smooth operations in avionics, automotive electronics, or telecommunication. New problems arise by the increasing employment, interconnection, and communication of embedded systems in heterogeneous environments: How secure are these embedded systems against attacks or breakdowns? Therefore, how can embedded systems be designed to be more secure? And how can embedded systems autonomically react to threats? Facing these questions, Sorin A. Huss is significantly involved in the exploration o

  10. Certifiable Java for Embedded Systems

    DEFF Research Database (Denmark)

    Schoeberl, Martin; Dalsgaard, Andreas Engelbredt; Hansen, Rene Rydhof

    2014-01-01

    The Certifiable Java for Embedded Systems (CJ4ES) project aimed to develop a prototype development environment and platform for safety-critical software for embedded applications. There are three core constituents: A profile of the Java programming language that is tailored for safety......-critical applications, a predictable Java processor built with FPGA technology, and an Eclipse based application development environment that binds the profile and the platform together and provides analyses that help to provide evidence that can be used as part of a safety case. This paper summarizes key contributions...

  11. Morphware - Fremtidens Embedded System Platform

    DEFF Research Database (Denmark)

    Madsen, Jan

    2006-01-01

    FPGA'er bliver i stigende grad brugt som komponenter i embedded systemer. Faldende priser, større kapacitet og en større felksibilitet har gjort FPGA'en til en attraktiv og konkurrencedygtig teknologi der tillader en stadig stigende grad af system integration, hvor traditionel hardware og software...... kombineres og rekonfigureres. Muligheden for at rekonfigurere systemet, og specielt rekonfigurerer det medens det kører, giver nogle helt nye muligheder for at designe og programmere embedded systemer. Dette foredrag vil give et indblik i disse nye og fremtidige muligheder....

  12. Implementation of an embedded computer

    OpenAIRE

    Pikl, Bojan

    2011-01-01

    The goal of this thesis is to describe a production of an embedded computer. The thesis describes development and production of an embedded computer for the medical diode laser DL30 that is being developed in Robomed d.o.o.. The first part of the thesis describes the choice of hardware devices. I mostly describe the technologies that one can buy on the market. Moreover for every part of the computer installed and developed there is an argument why we selected that exact part. The second part ...

  13. Homogeneous Spaces and Equivariant Embeddings

    CERN Document Server

    Timashev, DA

    2011-01-01

    Homogeneous spaces of linear algebraic groups lie at the crossroads of algebraic geometry, theory of algebraic groups, classical projective and enumerative geometry, harmonic analysis, and representation theory. By standard reasons of algebraic geometry, in order to solve various problems on a homogeneous space it is natural and helpful to compactify it keeping track of the group action, i.e. to consider equivariant completions or, more generally, open embeddings of a given homogeneous space. Such equivariant embeddings are the subject of this book. We focus on classification of equivariant em

  14. A Foundation for Embedded Languages

    DEFF Research Database (Denmark)

    Rhiger, Morten

    2003-01-01

    Recent work on embedding object languages into Haskell use "phantom types" (i.e., parameterized types whose parameter does not occur on the right-hand side of the type definition) to ensure that the embedded object-language terms are simply typed. But is it a safe assumption that only simply......-typed terms can be represented in Haskell using phantom types? And conversely, can all simply-typed terms be represented in Haskell under the restrictions imposed by phantom types? In this article we investigate the conditions under which these assumptions are true: We show that these questions can...

  15. A Foundation for Embedded Languages

    DEFF Research Database (Denmark)

    Rhiger, Morten

    2002-01-01

    Recent work on embedding object languages into Haskell use "phantom types" (i.e., parameterized types whose parameter does not occur on the right-hand side of the type definition) to ensure that the embedded object-language terms are simply typed. But is it a safe assumption that only simply......-typed terms can be represented in Haskell using phantom types? And conversely, can all simply-typed terms be represented in Haskell under the restrictions imposed by phantom types? In this article we investigate the conditions under which these assumptions are true: We show that these questions can...

  16. Unsynchronized influenza epidemics in two neighboring subtropical cities

    Directory of Open Access Journals (Sweden)

    Xiujuan Tang

    2018-04-01

    Full Text Available Objective: The aim of this study was to examine the synchrony of influenza epidemics between Hong Kong and Shenzhen, two neighboring subtropical cities in South China. Methods: Laboratory-confirmed influenza data for the period January 2006 to December 2016 were obtained from the Shenzhen Center for Disease Control and Prevention and the Department of Health in Hong Kong. The population data were retrieved from the 2011 population censuses. The weekly rates of laboratory-confirmed influenza cases were compared between Shenzhen and Hong Kong. Results: Unsynchronized influenza epidemics between Hong Kong and Shenzhen were frequently observed during the study period. Influenza A/H1N1 caused a more severe pandemic in Hong Kong in 2009, but the subsequent seasonal epidemics showed similar magnitudes in both cities. Two influenza A/H3N2 dominant epidemic waves were seen in Hong Kong in 2015, but these epidemics were very minor in Shenzhen. More influenza B epidemics occurred in Shenzhen than in Hong Kong. Conclusions: Influenza epidemics appeared to be unsynchronized between Hong Kong and Shenzhen most of the time. Given the close geographical locations of these two cities, this could be due to the strikingly different age structures of their populations. Keywords: Influenza epidemics, Synchrony, Shenzhen, Hong Kong

  17. Forecasting of steel consumption with use of nearest neighbors method

    Directory of Open Access Journals (Sweden)

    Rogalewicz Michał

    2017-01-01

    Full Text Available In the process of building a steel construction, its design is usually commissioned to the design office. Then a quotation is made and the finished offer is delivered to the customer. Its final shape is influenced by steel consumption to a great extent. Correct determination of the potential consumption of this material most often determines the profitability of the project. Because of a long waiting time for a final project from the design office, it is worthwhile to pre-analyze the project’s profitability and feasibility using historical data on already realized orders. The paper presents an innovative approach to decision-making support in one of the Polish construction companies. The authors have defined and prioritized the most important factors that differentiate the executed orders and have the greatest impact on steel consumption. These are, among others: height and width of steel structure, number of aisles, type of roof, etc. Then they applied and adapted the method of k-nearest neighbors to the specificity of the discussed problem. The goal was to search a set of historical orders and find the most similar to the analyzed one. On this basis, consumption of steel can be estimated. The method was programmed within the EXPLOR application.

  18. Identification of influential users by neighbors in online social networks

    Science.gov (United States)

    Sheikhahmadi, Amir; Nematbakhsh, Mohammad Ali; Zareie, Ahmad

    2017-11-01

    Identification and ranking of influential users in social networks for the sake of news spreading and advertising has recently become an attractive field of research. Given the large number of users in social networks and also the various relations that exist among them, providing an effective method to identify influential users has been gradually considered as an essential factor. In most of the already-provided methods, those users who are located in an appropriate structural position of the network are regarded as influential users. These methods do not usually pay attention to the interactions among users, and also consider those relations as being binary in nature. This paper, therefore, proposes a new method to identify influential users in a social network by considering those interactions that exist among the users. Since users tend to act within the frame of communities, the network is initially divided into different communities. Then the amount of interaction among users is used as a parameter to set the weight of relations existing within the network. Afterward, by determining the neighbors' role for each user, a two-level method is proposed for both detecting users' influence and also ranking them. Simulation and experimental results on twitter data shows that those users who are selected by the proposed method, comparing to other existing ones, are distributed in a more appropriate distance. Moreover, the proposed method outperforms the other ones in terms of both the influential speed and capacity of the users it selects.

  19. k-Nearest Neighbors Algorithm in Profiling Power Analysis Attacks

    Directory of Open Access Journals (Sweden)

    Z. Martinasek

    2016-06-01

    Full Text Available Power analysis presents the typical example of successful attacks against trusted cryptographic devices such as RFID (Radio-Frequency IDentifications and contact smart cards. In recent years, the cryptographic community has explored new approaches in power analysis based on machine learning models such as Support Vector Machine (SVM, RF (Random Forest and Multi-Layer Perceptron (MLP. In this paper, we made an extensive comparison of machine learning algorithms in the power analysis. For this purpose, we implemented a verification program that always chooses the optimal settings of individual machine learning models in order to obtain the best classification accuracy. In our research, we used three datasets, the first containing the power traces of an unprotected AES (Advanced Encryption Standard implementation. The second and third datasets are created independently from public available power traces corresponding to a masked AES implementation (DPA Contest v4. The obtained results revealed some interesting facts, namely, an elementary k-NN (k-Nearest Neighbors algorithm, which has not been commonly used in power analysis yet, shows great application potential in practice.

  20. River Flow Prediction Using the Nearest Neighbor Probabilistic Ensemble Method

    Directory of Open Access Journals (Sweden)

    H. Sanikhani

    2016-02-01

    Full Text Available Introduction: In the recent years, researchers interested on probabilistic forecasting of hydrologic variables such river flow.A probabilistic approach aims at quantifying the prediction reliability through a probability distribution function or a prediction interval for the unknown future value. The evaluation of the uncertainty associated to the forecast is seen as a fundamental information, not only to correctly assess the prediction, but also to compare forecasts from different methods and to evaluate actions and decisions conditionally on the expected values. Several probabilistic approaches have been proposed in the literature, including (1 methods that use resampling techniques to assess parameter and model uncertainty, such as the Metropolis algorithm or the Generalized Likelihood Uncertainty Estimation (GLUE methodology for an application to runoff prediction, (2 methods based on processing the forecast errors of past data to produce the probability distributions of future values and (3 methods that evaluate how the uncertainty propagates from the rainfall forecast to the river discharge prediction, as the Bayesian forecasting system. Materials and Methods: In this study, two different probabilistic methods are used for river flow prediction.Then the uncertainty related to the forecast is quantified. One approach is based on linear predictors and in the other, nearest neighbor was used. The nonlinear probabilistic ensemble can be used for nonlinear time series analysis using locally linear predictors, while NNPE utilize a method adapted for one step ahead nearest neighbor methods. In this regard, daily river discharge (twelve years of Dizaj and Mashin Stations on Baranduz-Chay basin in west Azerbijan and Zard-River basin in Khouzestan provinces were used, respectively. The first six years of data was applied for fitting the model. The next three years was used to calibration and the remained three yeas utilized for testing the models

  1. Nearest neighbor 3D segmentation with context features

    Science.gov (United States)

    Hristova, Evelin; Schulz, Heinrich; Brosch, Tom; Heinrich, Mattias P.; Nickisch, Hannes

    2018-03-01

    Automated and fast multi-label segmentation of medical images is challenging and clinically important. This paper builds upon a supervised machine learning framework that uses training data sets with dense organ annotations and vantage point trees to classify voxels in unseen images based on similarity of binary feature vectors extracted from the data. Without explicit model knowledge, the algorithm is applicable to different modalities and organs, and achieves high accuracy. The method is successfully tested on 70 abdominal CT and 42 pelvic MR images. With respect to ground truth, an average Dice overlap score of 0.76 for the CT segmentation of liver, spleen and kidneys is achieved. The mean score for the MR delineation of bladder, bones, prostate and rectum is 0.65. Additionally, we benchmark several variations of the main components of the method and reduce the computation time by up to 47% without significant loss of accuracy. The segmentation results are - for a nearest neighbor method - surprisingly accurate, robust as well as data and time efficient.

  2. Embedding Sensors During Additive Manufacturing

    Energy Technology Data Exchange (ETDEWEB)

    Sbriglia, Lexey Raylene [Los Alamos National Lab. (LANL), Los Alamos, NM (United States)

    2015-08-10

    This PowerPoint presentation had the following headings: Fused deposition modeling (FDM); Open source 3D printing; Objectives; Vibration analysis; Equipment; Design; Material choices; Failure causes, such as tension, bubbling; Potential solutions; Simulations; Embedding the sensors; LabView programming; Alternate data acquisition; Problem and proposed solution; and, Conclusions

  3. Embedded EZ-Source Inverters

    DEFF Research Database (Denmark)

    Blaabjerg, Frede; Loh, Poh Chiang; Gao, F.

    2008-01-01

    -voltage oscillations to the system. Therefore, Z-source inverters are in effect safer and less complex, and can be implemented using only passive elements with no additional active semiconductor needed. Believing in the prospects of Z-source inverters, this paper contributes by introducing a new family of embedded EZ...

  4. Software for Embedded Control Systems

    NARCIS (Netherlands)

    Broenink, Johannes F.; Hilderink, G.H.; Jovanovic, D.S.

    2001-01-01

    The research of our team deals with the realization of control schemes on digital computers. As such the emphasis is on embedded control software implementation. Applications are in the field of mechatronic devices, using a mechatronic design approach (the integrated and optimal design of a

  5. Embedded, everywhere: a research agenda for networked systems of embedded computers

    National Research Council Canada - National Science Library

    Committee on Networked Systems of Embedded Computers; National Research Council Staff; Division on Engineering and Physical Sciences; Computer Science and Telecommunications Board; National Academy of Sciences

    2001-01-01

    .... Embedded, Everywhere explores the potential of networked systems of embedded computers and the research challenges arising from embedding computation and communications technology into a wide variety of applicationsâ...

  6. A Tool for Interactive Data Visualization: Application to Over 10,000 Brain Imaging and Phantom MRI Data Sets

    Directory of Open Access Journals (Sweden)

    Sandeep R Panta

    2016-03-01

    Full Text Available In this paper we propose a web-based approach for quick visualization of big data from brain magnetic resonance imaging (MRI scans using a combination of an automated image capture and processing system, nonlinear embedding, and interactive data visualization tools. We draw upon thousands of MRI scans captured via the COllaborative Imaging and Neuroinformatics Suite (COINS. We then interface the output of several analysis pipelines based on structural and functional data to a t-distributed stochastic neighbor embedding (t-SNE algorithm which reduces the number of dimensions for each scan in the input data set to two dimensions while preserving the local structure of data sets. Finally, we interactively display the output of this approach via a web-page, based on data driven documents (D3 JavaScript library. Two distinct approaches were used to visualize the data. In the first approach, we computed multiple quality control (QC values from pre-processed data, which were used as inputs to the t-SNE algorithm. This approach helps in assessing the quality of each data set relative to others. In the second case, computed variables of interest (e.g. brain volume or voxel values from segmented gray matter images were used as inputs to the t-SNE algorithm. This approach helps in identifying interesting patterns in the data sets. We demonstrate these approaches using multiple examples including 1 quality control measures calculated from phantom data over time, 2 quality control data from human functional MRI data across various studies, scanners, sites, 3 volumetric and density measures from human structural MRI data across various studies, scanners and sites. Results from (1 and (2 show the potential of our approach to combine t-SNE data reduction with interactive color coding of variables of interest to quickly identify visually unique clusters of data (i.e. data sets with poor QC, clustering of data by site quickly. Results from (3 demonstrate

  7. Phagocytic response of astrocytes to damaged neighboring cells.

    Directory of Open Access Journals (Sweden)

    Nicole M Wakida

    Full Text Available This study aims to understand the phagocytic response of astrocytes to the injury of neurons or other astrocytes at the single cell level. Laser nanosurgery was used to damage individual cells in both primary mouse cortical astrocytes and an established astrocyte cell line. In both cases, the release of material/substances from laser-irradiated astrocytes or neurons induced a phagocytic response in near-by astrocytes. Propidium iodide stained DNA originating from irradiated cells was visible in vesicles of neighboring cells, confirming phagocytosis of material from damaged cortical cells. In the presence of an intracellular pH indicator dye, newly formed vesicles correspond to acidic pH fluorescence, thus suggesting lysosome bound degradation of cellular debris. Cells with shared membrane connections prior to laser damage had a significantly higher frequency of induced phagocytosis compared to isolated cells with no shared membrane. The increase in phagocytic response of cells with a shared membrane occurred regardless of the extent of shared membrane (a thin filopodial connection vs. a cell cluster with significant shared membrane. In addition to the presence (or lack of a membrane connection, variation in phagocytic ability was also observed with differences in injury location within the cell and distance separating isolated astrocytes. These results demonstrate the ability of an astrocyte to respond to the damage of a single cell, be it another astrocyte, or a neuron. This single-cell level of analysis results in a better understanding of the role of astrocytes to maintain homeostasis in the CNS, particularly in the sensing and removal of debris in damaged or pathologic nervous tissue.

  8. Visual words assignment via information-theoretic manifold embedding.

    Science.gov (United States)

    Deng, Yue; Li, Yipeng; Qian, Yanjun; Ji, Xiangyang; Dai, Qionghai

    2014-10-01

    Codebook-based learning provides a flexible way to extract the contents of an image in a data-driven manner for visual recognition. One central task in such frameworks is codeword assignment, which allocates local image descriptors to the most similar codewords in the dictionary to generate histogram for categorization. Nevertheless, existing assignment approaches, e.g., nearest neighbors strategy (hard assignment) and Gaussian similarity (soft assignment), suffer from two problems: 1) too strong Euclidean assumption and 2) neglecting the label information of the local descriptors. To address the aforementioned two challenges, we propose a graph assignment method with maximal mutual information (GAMI) regularization. GAMI takes the power of manifold structure to better reveal the relationship of massive number of local features by nonlinear graph metric. Meanwhile, the mutual information of descriptor-label pairs is ultimately optimized in the embedding space for the sake of enhancing the discriminant property of the selected codewords. According to such objective, two optimization models, i.e., inexact-GAMI and exact-GAMI, are respectively proposed in this paper. The inexact model can be efficiently solved with a closed-from solution. The stricter exact-GAMI nonparametrically estimates the entropy of descriptor-label pairs in the embedding space and thus leads to a relatively complicated but still trackable optimization. The effectiveness of GAMI models are verified on both the public and our own datasets.

  9. Detect thy neighbor: Identity recognition at the root level in plants

    NARCIS (Netherlands)

    Chen, B.J.W.; During, H.J.; Anten, N.P.R.

    2012-01-01

    Some plant species increase root allocation at the expense of reproduction in the presence of non-self and non-kin neighbors, indicating the capacity of neighbor-identityrecognition at the rootlevel. Yet in spite of the potential consequences of rootidentityrecognition for the relationship between

  10. Working with Family, Friend, and Neighbor Caregivers: Lessons from Four Diverse Communities

    Science.gov (United States)

    Powell, Douglas R.

    2011-01-01

    This article is excerpted from "Who's Watching the Babies? Improving the Quality of Family, Friend, and Neighbor Care" by Douglas R. Powell ("ZERO TO THREE," 2008). The article explores questions about program development and implementation strategies for supporting Family, Friend, and Neighbor (FFN) caregivers: How do programs and their host…

  11. Isometric embeddings in cosmology and astrophysics

    Indian Academy of Sciences (India)

    embedding theory, a given spacetime (or 'brane') is embedded in a higher- ..... If one recalls that the motivation (at least in part) for non-compact extra ... to successfully embed (apparently perfect fluid) astrophysical models, we typically need to.

  12. Poincare ball embeddings of the optical geometry

    International Nuclear Information System (INIS)

    Abramowicz, M A; Bengtsson, I; Karas, V; Rosquist, K

    2002-01-01

    It is shown that the optical geometry of the Reissner-Nordstroem exterior metric can be embedded in a hyperbolic space all the way down to its outer horizon. The adopted embedding procedure removes a breakdown of flat-space embeddings which occurs outside the horizon, at and below the Buchdahl-Bondi limit (R/M=9/4 in the Schwarzschild case). In particular, the horizon can be captured in the optical geometry embedding diagram. Moreover, by using the compact Poincare ball representation of the hyperbolic space, the embedding diagram can cover the whole extent of radius from spatial infinity down to the horizon. Attention is drawn to the advantages of such embeddings in an appropriately curved space: this approach gives compact embeddings and it clearly distinguishes the case of an extremal black hole from a non-extremal one in terms of the topology of the embedded horizon

  13. The embedded operating system project

    Science.gov (United States)

    Campbell, R. H.

    1984-01-01

    This progress report describes research towards the design and construction of embedded operating systems for real-time advanced aerospace applications. The applications concerned require reliable operating system support that must accommodate networks of computers. The report addresses the problems of constructing such operating systems, the communications media, reconfiguration, consistency and recovery in a distributed system, and the issues of realtime processing. A discussion is included on suitable theoretical foundations for the use of atomic actions to support fault tolerance and data consistency in real-time object-based systems. In particular, this report addresses: atomic actions, fault tolerance, operating system structure, program development, reliability and availability, and networking issues. This document reports the status of various experiments designed and conducted to investigate embedded operating system design issues.

  14. Perturbation Theory of Embedded Eigenvalues

    DEFF Research Database (Denmark)

    Engelmann, Matthias

    project gives a general and systematic approach to analytic perturbation theory of embedded eigenvalues. The spectral deformation technique originally developed in the theory of dilation analytic potentials in the context of Schrödinger operators is systematized by the use of Mourre theory. The group...... of dilations is thereby replaced by the unitary group generated y the conjugate operator. This then allows to treat the perturbation problem with the usual Kato theory.......We study problems connected to perturbation theory of embedded eigenvalues in two different setups. The first part deals with second order perturbation theory of mass shells in massive translation invariant Nelson type models. To this end an expansion of the eigenvalues w.r.t. fiber parameter up...

  15. An Embedded Reconfigurable Logic Module

    Science.gov (United States)

    Tucker, Jerry H.; Klenke, Robert H.; Shams, Qamar A. (Technical Monitor)

    2002-01-01

    A Miniature Embedded Reconfigurable Computer and Logic (MERCAL) module has been developed and verified. MERCAL was designed to be a general-purpose, universal module that that can provide significant hardware and software resources to meet the requirements of many of today's complex embedded applications. This is accomplished in the MERCAL module by combining a sub credit card size PC in a DIMM form factor with a XILINX Spartan I1 FPGA. The PC has the ability to download program files to the FPGA to configure it for different hardware functions and to transfer data to and from the FPGA via the PC's ISA bus during run time. The MERCAL module combines, in a compact package, the computational power of a 133 MHz PC with up to 150,000 gate equivalents of digital logic that can be reconfigured by software. The general architecture and functionality of the MERCAL hardware and system software are described.

  16. The Modified Embedded Atom Method

    Energy Technology Data Exchange (ETDEWEB)

    Baskes, M.I.

    1994-08-01

    Recent modifications have been made to generalize the Embedded Atom Method (EAM) to describe bonding in diverse materials. By including angular dependence of the electron density in an empirical way, the Modified Embedded Atom Method (MEAM) has been able to reproduce the basic energetic and structural properties of 45 elements. This method is ideal for examining interfacial behavior of dissimilar materials. This paper explains in detail the derivation of the method, shows how parameters of MEAM are determined directly from experiment or first principles calculations, and examine the quality of the reproduction of the database. Materials with fcc, bcc, hcp, and diamond cubic crystal structure are discussed. A few simple examples of the application of the MEAM to surfaces and interfaces are presented. Calculations of pullout of a SiC fiber in a diamond matrix as a function of applied stress show nonuniform deformation of the fiber.

  17. Embedding

    DEFF Research Database (Denmark)

    Høyrup, Jens

    2016-01-01

    systems, in particular place-value and quasi place-value systems. 2. The development of algebraic symbolisms. 3. The discussion whether “scientific revolutions” ever take place in mathematics, or new conceptualizations always include what preceded them. A final section investigates the relation between...

  18. Characteristics of Broadband Seismic Noise in Taiwan and Neighboring Islands

    Science.gov (United States)

    Chen, Ching-Wei; Rau, Ruey-Juin

    2017-04-01

    We used seismic waveform data from 115 broad-band stations of BATS (Institute of Earth Science, Academia Sinica) and Central Weather Bureau Seismic Network from 2012 to 2016 for noise-level mapping in Taiwan and neighboring islands. We computed Power Spectral Density (PSD) for each station and analyzed long-term variance of microseism energy and polarizations of noise for severe weather events. The island of Taiwan is surrounded by ocean and the Central Range which has the highest peak Jade Mountain at 3,952 meters height occupies more than 66% of the island and departs it into the east and west coasts. The geographic settings then result in the high population density in the western plain and northern Taiwan. The dominant noise source in the microseism band (periods from 4-20 seconds) is the coupling between the near-coast ocean and sea floor which produces the high noise of averaging -130 dB along the west coastal area. In the eastern volcanic-arc coastal areas, the noise level is about 7% smaller than the west coast due to its deeper offshore water depth. As for the shorter periods (0.1-0.25 seconds) band, the so-called culture noise, an anthropic activity variance with the highest -103 dB can be identified in the metropolitan areas, such as the Taipei city and the noise level in the Central Range area is averaging -138 dB. Moreover, the noise also shows a daily and temporal evolution mainly related to the traffic effect. Furthermore, we determined the noise level for the entire island of Taiwan during 26-28 September, 2016, when the typhoon Megi hit the island and retrieved the enhancement of secondary microseism energy for each stations. Typhoon Megi landed in eastern and central Taiwan and reached the maximum wind speed of 45m/s in the surrounded eyewall. The Central Range, as a barrier, decreased the wind speed in southern Taiwan making an enhancement less than 10 dB, while in northern Taiwan where the direction the typhoon headed to, can reach more than 35

  19. Sustainable embedded software lifecycle planning

    OpenAIRE

    Lee, Dong-Hyun; In, Hoh Peter; Lee, Keun; Park, Sooyong; Hinchey, Mike

    2012-01-01

    peer-reviewed Time-to-market is a crucial factor in increasing market share in the consumer electronics (CE) market. Furthermore, fierce competition in the market tends to sharply lower the prices of brand-new CE products as soon as they are released. Software-intensive embedded system design methods such as hardware/software co-design have been studied with the goal of reducing development lead-time by designing hardware and software simultaneously. Many researchers, however, concentra...

  20. Embedded multiprocessors scheduling and synchronization

    CERN Document Server

    Sriram, Sundararajan

    2009-01-01

    Techniques for Optimizing Multiprocessor Implementations of Signal Processing ApplicationsAn indispensable component of the information age, signal processing is embedded in a variety of consumer devices, including cell phones and digital television, as well as in communication infrastructure, such as media servers and cellular base stations. Multiple programmable processors, along with custom hardware running in parallel, are needed to achieve the computation throughput required of such applications. Reviews important research in key areas related to the multiprocessor implementation of multi

  1. Bilipschitz embedding of homogeneous fractals

    OpenAIRE

    Lü, Fan; Lou, Man-Li; Wen, Zhi-Ying; Xi, Li-Feng

    2014-01-01

    In this paper, we introduce a class of fractals named homogeneous sets based on some measure versions of homogeneity, uniform perfectness and doubling. This fractal class includes all Ahlfors-David regular sets, but most of them are irregular in the sense that they may have different Hausdorff dimensions and packing dimensions. Using Moran sets as main tool, we study the dimensions, bilipschitz embedding and quasi-Lipschitz equivalence of homogeneous fractals.

  2. Corrosion Monitors for Embedded Evaluation

    Energy Technology Data Exchange (ETDEWEB)

    Robinson, Alex L. [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Pfeifer, Kent B. [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Casias, Adrian L. [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Howell, Stephen W. [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Sorensen, Neil R. [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Missert, Nancy A. [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States)

    2017-05-01

    We have developed and characterized novel in-situ corrosion sensors to monitor and quantify the corrosive potential and history of localized environments. Embedded corrosion sensors can provide information to aid health assessments of internal electrical components including connectors, microelectronics, wires, and other susceptible parts. When combined with other data (e.g. temperature and humidity), theory, and computational simulation, the reliability of monitored systems can be predicted with higher fidelity.

  3. Characterization of Embedded BPM Collimators

    CERN Document Server

    VALENTINO, Gianluca

    2015-01-01

    During LS1, 16 tertiary collimators (TCTs) and 2 secondary collimators (TCSGs) in IR6 were replaced by new embedded BPM collimators. The BPM functionality allows the possibility to align the collimators more quickly and therefore be able to respond faster to machine configuration changes, as well as a direct monitoring of the beam orbit at the collimators. Following an initial commissioning phase, an MD was carried out to test the new collimators and acquisition electronics with beam in the LHC.

  4. Accelerating distributed average consensus by exploring the information of second-order neighbors

    Energy Technology Data Exchange (ETDEWEB)

    Yuan Deming [School of Automation, Nanjing University of Science and Technology, Nanjing 210094, Jiangsu (China); Xu Shengyuan, E-mail: syxu02@yahoo.com.c [School of Automation, Nanjing University of Science and Technology, Nanjing 210094, Jiangsu (China); Zhao Huanyu [School of Automation, Nanjing University of Science and Technology, Nanjing 210094, Jiangsu (China); Chu Yuming [Department of Mathematics, Huzhou Teacher' s College, Huzhou 313000, Zhejiang (China)

    2010-05-17

    The problem of accelerating distributed average consensus by using the information of second-order neighbors in both the discrete- and continuous-time cases is addressed in this Letter. In both two cases, when the information of second-order neighbors is used in each iteration, the network will converge with a speed faster than the algorithm only using the information of first-order neighbors. Moreover, the problem of using partial information of second-order neighbors is considered, and the edges are not chosen randomly from second-order neighbors. In the continuous-time case, the edges are chosen by solving a convex optimization problem which is formed by using the convex relaxation method. In the discrete-time case, for small network the edges are chosen optimally via the brute force method. Finally, simulation examples are provided to demonstrate the effectiveness of the proposed algorithm.

  5. Liquid-Embedded Elastomer Electronics

    Science.gov (United States)

    Kramer, Rebecca; Majidi, Carmel; Park, Yong-Lae; Paik, Jamie; Wood, Robert

    2012-02-01

    Hyperelastic sensors are fabricated by embedding a silicone rubber film with microchannels of conductive liquid. In the case of soft tactile sensors, pressing the surface of the elastomer will deform the cross-section of underlying channels and change their electrical resistance. Soft pressure sensors may be employed in a variety of applications. For example, a network of pressure sensors can serve as artificial skin by yielding detailed information about contact pressures. This concept was demonstrated in a hyperelastic keypad, where perpendicular conductive channels form a quasi-planar network within an elastomeric matrix that registers the location, intensity and duration of applied pressure. In a second demonstration, soft curvature sensors were used for joint angle proprioception. Because the sensors are soft and stretchable, they conform to the host without interfering with the natural mechanics of motion. This marked the first use of liquid-embedded elastomer electronics to monitor human or robotic motion. Finally, liquid-embedded elastomers may be implemented as conductors in applications that call for flexible or stretchable circuitry, such as robotic origami.

  6. Embedding of the radiation cosmos

    International Nuclear Information System (INIS)

    Wang, J.Z.

    1986-01-01

    The embedding of the Friedmann manifold into a higher dimensional Minkowski space is investigated. As solutions of the Friedmann equation with vanishing cosmological term, Friedmann models describe a first expanding, then contracting universe and predict a big bang singularity. For cosmic time t → 0, R(t) → 0, there is an infinite scalar, curvature in the matter cosmos, and an infinite eigenvalue corresponding to the unique timelike eigenvector of the energy-momentum tensor in the radiation cosmos. The big bang, therefore, is an intrinsic singularity of the space time. To investigate the singularity one resorts to the embedding of the Friedmann manifold into a higher dimensional Minkowski space. For the matter cosmos such an investigation has already been done (Lauro and Schucking, 1984). However, the matter cosmos is not a suitable model to discuss the very early universe where the radiation dominates. Geometric properties, such as the Riemann tensor, the Guassian curvature and the global behavior of the geodesics of the embedded manifold, are discussed in detail

  7. Embedding initial data for black hole collisions

    OpenAIRE

    Romano, Joseph D.; Price, Richard H.

    1994-01-01

    We discuss isometric embedding diagrams for the visualization of initial data for the problem of the head-on collision of two black holes. The problem of constructing the embedding diagrams is explicitly presented for the best studied initial data, the Misner geometry. We present a partial solution of the embedding diagrams and discuss issues related to completing the solution.

  8. Visualizing histopathologic deep learning classification and anomaly detection using nonlinear feature space dimensionality reduction.

    Science.gov (United States)

    Faust, Kevin; Xie, Quin; Han, Dominick; Goyle, Kartikay; Volynskaya, Zoya; Djuric, Ugljesa; Diamandis, Phedias

    2018-05-16

    There is growing interest in utilizing artificial intelligence, and particularly deep learning, for computer vision in histopathology. While accumulating studies highlight expert-level performance of convolutional neural networks (CNNs) on focused classification tasks, most studies rely on probability distribution scores with empirically defined cutoff values based on post-hoc analysis. More generalizable tools that allow humans to visualize histology-based deep learning inferences and decision making are scarce. Here, we leverage t-distributed Stochastic Neighbor Embedding (t-SNE) to reduce dimensionality and depict how CNNs organize histomorphologic information. Unique to our workflow, we develop a quantitative and transparent approach to visualizing classification decisions prior to softmax compression. By discretizing the relationships between classes on the t-SNE plot, we show we can super-impose randomly sampled regions of test images and use their distribution to render statistically-driven classifications. Therefore, in addition to providing intuitive outputs for human review, this visual approach can carry out automated and objective multi-class classifications similar to more traditional and less-transparent categorical probability distribution scores. Importantly, this novel classification approach is driven by a priori statistically defined cutoffs. It therefore serves as a generalizable classification and anomaly detection tool less reliant on post-hoc tuning. Routine incorporation of this convenient approach for quantitative visualization and error reduction in histopathology aims to accelerate early adoption of CNNs into generalized real-world applications where unanticipated and previously untrained classes are often encountered.

  9. Nearest Neighbor Search in the Metric Space of a Complex Network for Community Detection

    Directory of Open Access Journals (Sweden)

    Suman Saha

    2016-03-01

    Full Text Available The objective of this article is to bridge the gap between two important research directions: (1 nearest neighbor search, which is a fundamental computational tool for large data analysis; and (2 complex network analysis, which deals with large real graphs but is generally studied via graph theoretic analysis or spectral analysis. In this article, we have studied the nearest neighbor search problem in a complex network by the development of a suitable notion of nearness. The computation of efficient nearest neighbor search among the nodes of a complex network using the metric tree and locality sensitive hashing (LSH are also studied and experimented. For evaluation of the proposed nearest neighbor search in a complex network, we applied it to a network community detection problem. Experiments are performed to verify the usefulness of nearness measures for the complex networks, the role of metric tree and LSH to compute fast and approximate node nearness and the the efficiency of community detection using nearest neighbor search. We observed that nearest neighbor between network nodes is a very efficient tool to explore better the community structure of the real networks. Several efficient approximation schemes are very useful for large networks, which hardly made any degradation of results, whereas they save lot of computational times, and nearest neighbor based community detection approach is very competitive in terms of efficiency and time.

  10. Neighboring trees affect ectomycorrhizal fungal community composition in a woodland-forest ecotone.

    Science.gov (United States)

    Hubert, Nathaniel A; Gehring, Catherine A

    2008-09-01

    Ectomycorrhizal fungi (EMF) are frequently species rich and functionally diverse; yet, our knowledge of the environmental factors that influence local EMF diversity and species composition remains poor. In particular, little is known about the influence of neighboring plants on EMF community structure. We tested the hypothesis that the EMF of plants with heterospecific neighbors would differ in species richness and community composition from the EMF of plants with conspecific neighbors. We conducted our study at the ecotone between pinyon (Pinus edulis)-juniper (Juniperus monosperma) woodland and ponderosa pine (Pinus ponderosa) forest in northern Arizona, USA where the dominant trees formed associations with either EMF (P. edulis and P. ponderosa) or arbuscular mycorrhizal fungi (AMF; J. monosperma). We also compared the EMF communities of pinyon and ponderosa pines where their rhizospheres overlapped. The EMF community composition, but not species richness of pinyon pines was significantly influenced by neighboring AM juniper, but not by neighboring EM ponderosa pine. Ponderosa pine EMF communities were different in species composition when growing in association with pinyon pine than when growing in association with a conspecific. The EMF communities of pinyon and ponderosa pines were similar where their rhizospheres overlapped consisting of primarily the same species in similar relative abundance. Our findings suggest that neighboring tree species identity shaped EMF community structure, but that these effects were specific to host-neighbor combinations. The overlap in community composition between pinyon pine and ponderosa pine suggests that these tree species may serve as reservoirs of EMF inoculum for one another.

  11. Permutation entropy with vector embedding delays

    Science.gov (United States)

    Little, Douglas J.; Kane, Deb M.

    2017-12-01

    Permutation entropy (PE) is a statistic used widely for the detection of structure within a time series. Embedding delay times at which the PE is reduced are characteristic timescales for which such structure exists. Here, a generalized scheme is investigated where embedding delays are represented by vectors rather than scalars, permitting PE to be calculated over a (D -1 ) -dimensional space, where D is the embedding dimension. This scheme is applied to numerically generated noise, sine wave and logistic map series, and experimental data sets taken from a vertical-cavity surface emitting laser exhibiting temporally localized pulse structures within the round-trip time of the laser cavity. Results are visualized as PE maps as a function of embedding delay, with low PE values indicating combinations of embedding delays where correlation structure is present. It is demonstrated that vector embedding delays enable identification of structure that is ambiguous or masked, when the embedding delay is constrained to scalar form.

  12. Reduction in predator defense in the presence of neighbors in a colonial fish.

    Directory of Open Access Journals (Sweden)

    Franziska C Schädelin

    Full Text Available Predation pressure has long been considered a leading explanation of colonies, where close neighbors may reduce predation via dilution, alarming or group predator attacks. Attacking predators may be costly in terms of energy and survival, leading to the question of how neighbors contribute to predator deterrence in relationship to each other. Two hypotheses explaining the relative efforts made by neighbors are byproduct-mutualism, which occurs when breeders inadvertently attack predators by defending their nests, and reciprocity, which occurs when breeders deliberately exchange predator defense efforts with neighbors. Most studies investigating group nest defense have been performed with birds. However, colonial fish may constitute a more practical model system for an experimental approach because of the greater ability of researchers to manipulate their environment. We investigated in the colonial fish, Neolamprologus caudopunctatus, whether prospecting pairs preferred to breed near conspecifics or solitarily, and how breeders invested in anti-predator defense in relation to neighbors. In a simple choice test, prospecting pairs selected breeding sites close to neighbors versus a solitary site. Predators were then sequentially presented to the newly established test pairs, the previously established stimulus pairs or in between the two pairs. Test pairs attacked the predator eight times more frequently when they were presented on their non-neighbor side compared to between the two breeding sites, where stimulus pairs maintained high attack rates. Thus, by joining an established pair, test pairs were able to reduce their anti-predator efforts near neighbors, at no apparent cost to the stimulus pairs. These findings are unlikely to be explained by reciprocity or byproduct-mutualism. Our results instead suggest a commensal relationship in which new pairs exploit the high anti-predator efforts of established pairs, which invest similarly with or

  13. The Application of Determining Students’ Graduation Status of STMIK Palangkaraya Using K-Nearest Neighbors Method

    Science.gov (United States)

    Rusdiana, Lili; Marfuah

    2017-12-01

    K-Nearest Neighbors method is one of methods used for classification which calculate a value to find out the closest in distance. It is used to group a set of data such as students’ graduation status that are got from the amount of course credits taken by them, the grade point average (AVG), and the mini-thesis grade. The study is conducted to know the results of using K-Nearest Neighbors method on the application of determining students’ graduation status, so it can be analyzed from the method used, the data, and the application constructed. The aim of this study is to find out the application results by using K-Nearest Neighbors concept to determine students’ graduation status using the data of STMIK Palangkaraya students. The development of the software used Extreme Programming, since it was appropriate and precise for this study which was to quickly finish the project. The application was created using Microsoft Office Excel 2007 for the training data and Matlab 7 to implement the application. The result of K-Nearest Neighbors method on the application of determining students’ graduation status was 92.5%. It could determine the predicate graduation of 94 data used from the initial data before the processing as many as 136 data which the maximal training data was 50data. The K-Nearest Neighbors method is one of methods used to group a set of data based on the closest value, so that using K-Nearest Neighbors method agreed with this study. The results of K-Nearest Neighbors method on the application of determining students’ graduation status was 92.5% could determine the predicate graduation which is the maximal training data. The K-Nearest Neighbors method is one of methods used to group a set of data based on the closest value, so that using K-Nearest Neighbors method agreed with this study.

  14. Habitual Tastes and Embedded Taste

    DEFF Research Database (Denmark)

    Hedegaard, Liselotte

    2016-01-01

    The interest of this paper is to position taste within the framework of time. This might seem peculiar given that taste, in its physical sense, is referred to as an ephemeral experience taking place in the mouth. Taste, however, is more than that. It is the transient experience that infiltrates...... may be bridged by story-telling or other ways of handing over historically embedded practices, but this leaves a more fundamental question unanswered. Namely, that given that all remembrance has individual recollection as the point of departure, then how does individual recollection of tastes...

  15. Professional Windows Embedded Compact 7

    CERN Document Server

    Phung, Samuel; Joubert, Thierry; Hall, Mike

    2011-01-01

    Learn to program an array of customized devices and solutions As a compact, highly efficient, scalable operating system, Windows Embedded Compact 7 (WEC7) is one of the best options for developing a new generation of network-enabled, media-rich, and service-oriented devices. This in-depth resource takes you through the benefits and capabilities of WEC7 so that you can start using this performance development platform today. Divided into several major sections, the book begins with an introduction and then moves on to coverage of OS design, application development, advanced application developm

  16. Simulation and Embedded Smart Control

    DEFF Research Database (Denmark)

    Conrad, Finn; Fan, Zhun; Sørensen, Torben

    2006-01-01

    The paper presents results obtained from a Danish mechatronic research program focusing on intelligent motion control, simulation and embedded smart controllers for hydraulic actuators and robots as well as results from the EU projects. A mechatronic test facility with digital controllers...... for a hydraulic robot was implemented. The controllers apply digital signal processors (DSPs), and Field Programmable Gate Array, short named as FPGA, respectively. The DSP controller utilizes the dSPACE System that is suitable for real-time experimentation, evaluation and validation of control laws...... and algorithms. Furthermore, a developed IT-tool concept for controller and system design utilizing the ISO 10303 STEP Standard is proposed....

  17. Effects of second neighbor interactions on skyrmion lattices in chiral magnets

    International Nuclear Information System (INIS)

    Oliveira, E A S; Silva, R L; Silva, R C; Pereira, A R

    2017-01-01

    In this paper we investigate the influences of the second neighbor interactions on a skyrmion lattice in two-dimensional chiral magnets. Such a system contains the exchange and the Dzyaloshinskii–Moriya for the spin interactions and therefore, we analyse three situations: firstly, the second neighbor interaction is present only in the exchange coupling; secondly, it is present only in the Dzyaloshinskii–Moriya coupling. Finally, the second neighbor interactions are present in both exchange and Dzyaloshinskii–Moriya couplings. We show that such effects cause important modifications to the helical and skyrmion phases when an external magnetic field is applied. (paper)

  18. Improving Recommendations in Tag-based Systems with Spectral Clustering of Tag Neighbors

    DEFF Research Database (Denmark)

    Pan, Rong; Xu, Guandong; Dolog, Peter

    2012-01-01

    Tag as a useful metadata reflects the collaborative and conceptual features of documents in social collaborative annotation systems. In this paper, we propose a collaborative approach for expanding tag neighbors and investigate the spectral clustering algorithm to filter out noisy tag neighbors...... in order to get appropriate recommendation for users. The preliminary experiments have been conducted on MovieLens dataset to compare our proposed approach with the traditional collaborative filtering recommendation approach and naive tag neighbors expansion approach in terms of precision, and the result...... demonstrates that our approach could considerably improve the performance of recommendations....

  19. Learning Euclidean Embeddings for Indexing and Classification

    National Research Council Canada - National Science Library

    Athitsos, Vassilis; Alon, Joni; Sclaroff, Stan; Kollios, George

    2004-01-01

    BoostMap is a recently proposed method for efficient approximate nearest neighbor retrieval in arbitrary non-Euclidean spaces with computationally expensive and possibly non-metric distance measures...

  20. Testing framework for embedded languages

    Science.gov (United States)

    Leskó, Dániel; Tejfel, Máté

    2012-09-01

    Embedding a new programming language into an existing one is a widely used technique, because it fastens the development process and gives a part of a language infrastructure for free (e.g. lexical, syntactical analyzers). In this paper we are presenting a new advantage of this development approach regarding to adding testing support for these new languages. Tool support for testing is a crucial point for a newly designed programming language. It could be done in the hard way by creating a testing tool from scratch, or we could try to reuse existing testing tools by extending them with an interface to our new language. The second approach requires less work, and also it fits very well for the embedded approach. The problem is that the creation of such interfaces is not straightforward at all, because the existing testing tools were mostly not designed to be extendable and to be able to deal with new languages. This paper presents an extendable and modular model of a testing framework, in which the most basic design decision was to keep the - previously mentioned - interface creation simple and straightforward. Other important aspects of our model are the test data generation, the oracle problem and the customizability of the whole testing phase.

  1. Drilling azimuth gamma embedded design

    Directory of Open Access Journals (Sweden)

    Zhou Yi Ren

    2016-01-01

    Full Text Available Embedded drilling azimuth gamma design, the use of radioactive measuring principle embedded gamma measurement while drilling a short section analysis. Monte Carlo method, in response to the density of horizontal well logging numerical simulation of 16 orientation, the orientation of horizontal well analysed, calliper, bed boundary location, space, different formation density, formation thickness, and other factors inclined strata dip the impact by simulating 137Cs sources under different formation conditions of the gamma distribution, to determine the orientation of drilling density tool can detect window size and space, draw depth of the logging methods. The data 360° azimuth imaging, image processing method to obtain graph, display density of the formation, dip and strata thickness and other parameters, the logging methods obtain real-time geo-steering. To establish a theoretical basis for the orientation density logging while drilling method implementation and application of numerical simulation in-depth study of the MWD azimuth and density log response factors of horizontal wells.

  2. Nanofluidic Device with Embedded Nanopore

    Science.gov (United States)

    Zhang, Yuning; Reisner, Walter

    2014-03-01

    Nanofluidic based devices are robust methods for biomolecular sensing and single DNA manipulation. Nanopore-based DNA sensing has attractive features that make it a leading candidate as a single-molecule DNA sequencing technology. Nanochannel based extension of DNA, combined with enzymatic or denaturation-based barcoding schemes, is already a powerful approach for genome analysis. We believe that there is revolutionary potential in devices that combine nanochannels with nanpore detectors. In particular, due to the fast translocation of a DNA molecule through a standard nanopore configuration, there is an unfavorable trade-off between signal and sequence resolution. With a combined nanochannel-nanopore device, based on embedding a nanopore inside a nanochannel, we can in principle gain independent control over both DNA translocation speed and sensing signal, solving the key draw-back of the standard nanopore configuration. We demonstrate that we can detect - using fluorescent microscopy - successful translocation of DNA from the nanochannel out through the nanopore, a possible method to 'select' a given barcode for further analysis. We also show that in equilibrium DNA will not escape through an embedded sub-persistence length nanopore until a certain voltage bias is added.

  3. Embedded pitch adapters: A high-yield interconnection solution for strip sensors

    Energy Technology Data Exchange (ETDEWEB)

    Ullán, M., E-mail: miguel.ullan@imb-cnm.csic.es [Centro Nacional de Microelectronica (IMB-CNM, CSIC), Campus UAB-Bellaterra, 08193 Barcelona (Spain); Allport, P.P.; Baca, M.; Broughton, J.; Chisholm, A.; Nikolopoulos, K.; Pyatt, S.; Thomas, J.P.; Wilson, J.A. [School of Physics and Astronomy, University of Birmingham, Birmingham B15 2TT (United Kingdom); Kierstead, J.; Kuczewski, P.; Lynn, D. [Brookhaven National Laboratory, Physics Department and Instrumentation Division, Upton, NY 11973-5000 (United States); Hommels, L.B.A. [Cavendish Laboratory, University of Cambridge, JJ Thomson Avenue, Cambridge CB3 0HE (United Kingdom); Fleta, C.; Fernandez-Tejero, J.; Quirion, D. [Centro Nacional de Microelectronica (IMB-CNM, CSIC), Campus UAB-Bellaterra, 08193 Barcelona (Spain); Bloch, I.; Díez, S.; Gregor, I.M.; Lohwasser, K. [DESY, Notkestrasse 85, 22607 Hamburg (Germany); and others

    2016-09-21

    A proposal to fabricate large area strip sensors with integrated, or embedded, pitch adapters is presented for the End-cap part of the Inner Tracker in the ATLAS experiment. To implement the embedded pitch adapters, a second metal layer is used in the sensor fabrication, for signal routing to the ASICs. Sensors with different embedded pitch adapters have been fabricated in order to optimize the design and technology. Inter-strip capacitance, noise, pick-up, cross-talk, signal efficiency, and fabrication yield have been taken into account in their design and fabrication. Inter-strip capacitance tests taking into account all channel neighbors reveal the important differences between the various designs considered. These tests have been correlated with noise figures obtained in full assembled modules, showing that the tests performed on the bare sensors are a valid tool to estimate the final noise in the full module. The full modules have been subjected to test beam experiments in order to evaluate the incidence of cross-talk, pick-up, and signal loss. The detailed analysis shows no indication of cross-talk or pick-up as no additional hits can be observed in any channel not being hit by the beam above 170 mV threshold, and the signal in those channels is always below 1% of the signal recorded in the channel being hit, above 100 mV threshold. First results on irradiated mini-sensors with embedded pitch adapters do not show any change in the interstrip capacitance measurements with only the first neighbors connected.

  4. Does a pear growl? Interference from semantic properties of orthographic neighbors.

    Science.gov (United States)

    Pecher, Diane; de Rooij, Jimmy; Zeelenberg, René

    2009-07-01

    In this study, we investigated whether semantic properties of a word's orthographic neighbors are activated during visual word recognition. In two experiments, words were presented with a property that was not true for the word itself. We manipulated whether the property was true for an orthographic neighbor of the word. Our results showed that rejection of the property was slower and less accurate when the property was true for a neighbor than when the property was not true for a neighbor. These findings indicate that semantic information is activated before orthographic processing is finished. The present results are problematic for the links model (Forster, 2006; Forster & Hector, 2002) that was recently proposed in order to bring form-first models of visual word recognition into line with previously reported findings (Forster & Hector, 2002; Pecher, Zeelenberg, & Wagenmakers, 2005; Rodd, 2004).

  5. Nearest neighbors EPR superhyperfine interaction in divalent iridium complexes in alkali halide host lattice

    International Nuclear Information System (INIS)

    Pinhal, N.M.; Vugman, N.V.

    1983-01-01

    Further splitting of chlorine superhyperfine lines on the EPR spectrum of the [Ir (CN) 4 Cl 2 ] 4 - molecular species in NaCl latice indicates a super-superhyperfine interaction with the nearest neighbors sodium atoms. (Author) [pt

  6. The influence of neighbors' family size preference on progression to high parity births in rural Nepal.

    Science.gov (United States)

    Jennings, Elyse A; Barber, Jennifer S

    2013-03-01

    Large families can have a negative impact on the health and well-being of women, children, and their communities. Seventy-three percent of the individuals in our rural Nepalese sample report that two children is their ideal number, yet about half of the married women continue childbearing after their second child. Using longitudinal data from the Chitwan Valley Family Study, we explore the influence of women's and neighbors' family size preferences on women's progression to high parity births, comparing this influence across two cohorts. We find that neighbors' family size preferences influence women's fertility, that older cohorts of women are more influenced by their neighbors' preferences than are younger cohorts of women, and that the influence of neighbors' preferences is independent of women's own preferences. © 2013 The Population Council, Inc.

  7. On Competitiveness of Nearest-Neighbor-Based Music Classification: A Methodological Critique

    DEFF Research Database (Denmark)

    Pálmason, Haukur; Jónsson, Björn Thór; Amsaleg, Laurent

    2017-01-01

    The traditional role of nearest-neighbor classification in music classification research is that of a straw man opponent for the learning approach of the hour. Recent work in high-dimensional indexing has shown that approximate nearest-neighbor algorithms are extremely scalable, yielding results...... of reasonable quality from billions of high-dimensional features. With such efficient large-scale classifiers, the traditional music classification methodology of aggregating and compressing the audio features is incorrect; instead the approximate nearest-neighbor classifier should be given an extensive data...... collection to work with. We present a case study, using a well-known MIR classification benchmark with well-known music features, which shows that a simple nearest-neighbor classifier performs very competitively when given ample data. In this position paper, we therefore argue that nearest...

  8. Efficient and accurate nearest neighbor and closest pair search in high-dimensional space

    KAUST Repository

    Tao, Yufei; Yi, Ke; Sheng, Cheng; Kalnis, Panos

    2010-01-01

    Nearest Neighbor (NN) search in high-dimensional space is an important problem in many applications. From the database perspective, a good solution needs to have two properties: (i) it can be easily incorporated in a relational database, and (ii

  9. Mixed random walks with a trap in scale-free networks including nearest-neighbor and next-nearest-neighbor jumps

    Science.gov (United States)

    Zhang, Zhongzhi; Dong, Yuze; Sheng, Yibin

    2015-10-01

    Random walks including non-nearest-neighbor jumps appear in many real situations such as the diffusion of adatoms and have found numerous applications including PageRank search algorithm; however, related theoretical results are much less for this dynamical process. In this paper, we present a study of mixed random walks in a family of fractal scale-free networks, where both nearest-neighbor and next-nearest-neighbor jumps are included. We focus on trapping problem in the network family, which is a particular case of random walks with a perfect trap fixed at the central high-degree node. We derive analytical expressions for the average trapping time (ATT), a quantitative indicator measuring the efficiency of the trapping process, by using two different methods, the results of which are consistent with each other. Furthermore, we analytically determine all the eigenvalues and their multiplicities for the fundamental matrix characterizing the dynamical process. Our results show that although next-nearest-neighbor jumps have no effect on the leading scaling of the trapping efficiency, they can strongly affect the prefactor of ATT, providing insight into better understanding of random-walk process in complex systems.

  10. Symmetric Link Key Management for Secure Neighbor Discovery in a Decentralized Wireless Sensor Network

    Science.gov (United States)

    2017-09-01

    KEY MANAGEMENT FOR SECURE NEIGHBOR DISCOVERY IN A DECENTRALIZED WIRELESS SENSOR NETWORK by Kelvin T. Chew September 2017 Thesis Advisor...and to the Office of Management and Budget, Paperwork Reduction Project (0704-0188) Washington, DC 20503. 1. AGENCY USE ONLY (Leave blank) 2. REPORT...DATE September 2017 3. REPORT TYPE AND DATES COVERED Master’s thesis 4. TITLE AND SUBTITLE SYMMETRIC LINK KEY MANAGEMENT FOR SECURE NEIGHBOR

  11. SibRank: Signed bipartite network analysis for neighbor-based collaborative ranking

    Science.gov (United States)

    Shams, Bita; Haratizadeh, Saman

    2016-09-01

    Collaborative ranking is an emerging field of recommender systems that utilizes users' preference data rather than rating values. Unfortunately, neighbor-based collaborative ranking has gained little attention despite its more flexibility and justifiability. This paper proposes a novel framework, called SibRank that seeks to improve the state of the art neighbor-based collaborative ranking methods. SibRank represents users' preferences as a signed bipartite network, and finds similar users, through a novel personalized ranking algorithm in signed networks.

  12. The impact of vacant, tax-delinquent, and foreclosed property on sales prices of neighboring homes

    OpenAIRE

    Stephan Whitaker; Thomas J. Fitzpatrick

    2012-01-01

    In this empirical analysis, we estimate the impact of vacancy, neglect associated with property-tax delinquency, and foreclosures on the value of neighboring homes using parcel-level observations. Numerous studies have estimated the impact of foreclosures on neighboring properties, and these papers theorize that the foreclosure impact works partially through creating vacant and neglected homes. To our knowledge, this is only the second attempt to estimate the impact of vacancy itself and the ...

  13. The Patient-Centered Medical Home Neighbor: A Critical Concept for a Redesigned Healthcare Delivery System

    Science.gov (United States)

    2011-01-25

    Sharing Knowledge: Achieving Breakthrough Performance 2010 Military Health System Conference The Patient -Centered Medical Home Neighbor: A Critical...DATE 25 JAN 2011 2. REPORT TYPE 3. DATES COVERED 00-00-2011 to 00-00-2011 4. TITLE AND SUBTITLE The Patient -Centered Medical Home Neighbor: A...Conference What is the Patient -Centered Medical Home?  …a vision of health care as it should be  …a framework for organizing systems of care at both the

  14. An adaptive deep convolutional neural network for rolling bearing fault diagnosis

    International Nuclear Information System (INIS)

    Fuan, Wang; Hongkai, Jiang; Haidong, Shao; Wenjing, Duan; Shuaipeng, Wu

    2017-01-01

    The working conditions of rolling bearings usually is very complex, which makes it difficult to diagnose rolling bearing faults. In this paper, a novel method called the adaptive deep convolutional neural network (CNN) is proposed for rolling bearing fault diagnosis. Firstly, to get rid of manual feature extraction, the deep CNN model is initialized for automatic feature learning. Secondly, to adapt to different signal characteristics, the main parameters of the deep CNN model are determined with a particle swarm optimization method. Thirdly, to evaluate the feature learning ability of the proposed method, t-distributed stochastic neighbor embedding (t-SNE) is further adopted to visualize the hierarchical feature learning process. The proposed method is applied to diagnose rolling bearing faults, and the results confirm that the proposed method is more effective and robust than other intelligent methods. (paper)

  15. Co-Expression of Neighboring Genes in the Zebrafish (Danio rerio Genome

    Directory of Open Access Journals (Sweden)

    Daryi Wang

    2009-08-01

    Full Text Available Neighboring genes in the eukaryotic genome have a tendency to express concurrently, and the proximity of two adjacent genes is often considered a possible explanation for their co-expression behavior. However, the actual contribution of the physical distance between two genes to their co-expression behavior has yet to be defined. To further investigate this issue, we studied the co-expression of neighboring genes in zebrafish, which has a compact genome and has experienced a whole genome duplication event. Our analysis shows that the proportion of highly co-expressed neighboring pairs (Pearson’s correlation coefficient R>0.7 is low (0.24% ~ 0.67%; however, it is still significantly higher than that of random pairs. In particular, the statistical result implies that the co-expression tendency of neighboring pairs is negatively correlated with their physical distance. Our findings therefore suggest that physical distance may play an important role in the co-expression of neighboring genes. Possible mechanisms related to the neighboring genes’ co-expression are also discussed.

  16. Finger vein identification using fuzzy-based k-nearest centroid neighbor classifier

    Science.gov (United States)

    Rosdi, Bakhtiar Affendi; Jaafar, Haryati; Ramli, Dzati Athiar

    2015-02-01

    In this paper, a new approach for personal identification using finger vein image is presented. Finger vein is an emerging type of biometrics that attracts attention of researchers in biometrics area. As compared to other biometric traits such as face, fingerprint and iris, finger vein is more secured and hard to counterfeit since the features are inside the human body. So far, most of the researchers focus on how to extract robust features from the captured vein images. Not much research was conducted on the classification of the extracted features. In this paper, a new classifier called fuzzy-based k-nearest centroid neighbor (FkNCN) is applied to classify the finger vein image. The proposed FkNCN employs a surrounding rule to obtain the k-nearest centroid neighbors based on the spatial distributions of the training images and their distance to the test image. Then, the fuzzy membership function is utilized to assign the test image to the class which is frequently represented by the k-nearest centroid neighbors. Experimental evaluation using our own database which was collected from 492 fingers shows that the proposed FkNCN has better performance than the k-nearest neighbor, k-nearest-centroid neighbor and fuzzy-based-k-nearest neighbor classifiers. This shows that the proposed classifier is able to identify the finger vein image effectively.

  17. Plant neighbor identity influences plant biochemistry and physiology related to defense.

    Science.gov (United States)

    Broz, Amanda K; Broeckling, Corey D; De-la-Peña, Clelia; Lewis, Matthew R; Greene, Erick; Callaway, Ragan M; Sumner, Lloyd W; Vivanco, Jorge M

    2010-06-17

    Chemical and biological processes dictate an individual organism's ability to recognize and respond to other organisms. A small but growing body of evidence suggests that plants may be capable of recognizing and responding to neighboring plants in a species specific fashion. Here we tested whether or not individuals of the invasive exotic weed, Centaurea maculosa, would modulate their defensive strategy in response to different plant neighbors. In the greenhouse, C. maculosa individuals were paired with either conspecific (C. maculosa) or heterospecific (Festuca idahoensis) plant neighbors and elicited with the plant defense signaling molecule methyl jasmonate to mimic insect herbivory. We found that elicited C. maculosa plants grown with conspecific neighbors exhibited increased levels of total phenolics, whereas those grown with heterospecific neighbors allocated more resources towards growth. To further investigate these results in the field, we conducted a metabolomics analysis to explore chemical differences between individuals of C. maculosa growing in naturally occurring conspecific and heterospecific field stands. Similar to the greenhouse results, C. maculosa individuals accumulated higher levels of defense-related secondary metabolites and lower levels of primary metabolites when growing in conspecific versus heterospecific field stands. Leaf herbivory was similar in both stand types; however, a separate field study positively correlated specialist herbivore load with higher densities of C. maculosa conspecifics. Our results suggest that an individual C. maculosa plant can change its defensive strategy based on the identity of its plant neighbors. This is likely to have important consequences for individual and community success.

  18. Plant neighbor identity influences plant biochemistry and physiology related to defense

    Directory of Open Access Journals (Sweden)

    Callaway Ragan M

    2010-06-01

    Full Text Available Abstract Background Chemical and biological processes dictate an individual organism's ability to recognize and respond to other organisms. A small but growing body of evidence suggests that plants may be capable of recognizing and responding to neighboring plants in a species specific fashion. Here we tested whether or not individuals of the invasive exotic weed, Centaurea maculosa, would modulate their defensive strategy in response to different plant neighbors. Results In the greenhouse, C. maculosa individuals were paired with either conspecific (C. maculosa or heterospecific (Festuca idahoensis plant neighbors and elicited with the plant defense signaling molecule methyl jasmonate to mimic insect herbivory. We found that elicited C. maculosa plants grown with conspecific neighbors exhibited increased levels of total phenolics, whereas those grown with heterospecific neighbors allocated more resources towards growth. To further investigate these results in the field, we conducted a metabolomics analysis to explore chemical differences between individuals of C. maculosa growing in naturally occurring conspecific and heterospecific field stands. Similar to the greenhouse results, C. maculosa individuals accumulated higher levels of defense-related secondary metabolites and lower levels of primary metabolites when growing in conspecific versus heterospecific field stands. Leaf herbivory was similar in both stand types; however, a separate field study positively correlated specialist herbivore load with higher densities of C. maculosa conspecifics. Conclusions Our results suggest that an individual C. maculosa plant can change its defensive strategy based on the identity of its plant neighbors. This is likely to have important consequences for individual and community success.

  19. Pollinator-mediated interactions in experimental arrays vary with neighbor identity.

    Science.gov (United States)

    Ha, Melissa K; Ivey, Christopher T

    2017-02-01

    Local ecological conditions influence the impact of species interactions on evolution and community structure. We investigated whether pollinator-mediated interactions between coflowering plants vary with plant density, coflowering neighbor identity, and flowering season. We conducted a field experiment in which flowering time and floral neighborhood were manipulated in a factorial design. Early- and late-flowering Clarkia unguiculata plants were placed into arrays with C. biloba neighbors, noncongeneric neighbors, additional conspecific plants, or no additional plants as a density control. We compared whole-plant pollen limitation of seed set, pollinator behavior, and pollen deposition among treatments. Interactions mediated by shared pollinators depended on the identity of the neighbor and possibly changed through time, although flowering-season comparisons were compromised by low early-season plant survival. Interactions with conspecific neighbors were likely competitive late in the season. Interactions with C. biloba appeared to involve facilitation or neutral interactions. Interactions with noncongeners were more consistently competitive. The community composition of pollinators varied among treatment combinations. Pollinator-mediated interactions involved competition and likely facilitation, depending on coflowering neighbor. Experimental manipulation helped to reveal context-dependent variation in indirect biotic interactions. © 2017 Botanical Society of America.

  20. ESTEEM: A Novel Framework for Qualitatively Evaluating and Visualizing Spatiotemporal Embeddings in Social Media

    Energy Technology Data Exchange (ETDEWEB)

    Arendt, Dustin L.; Volkova, Svitlana

    2017-07-30

    Analyzing and visualizing large amounts of social media communications and contrasting short-term conversation changes over time and geo-locations is extremely important for commercial and government applications. Earlier approaches for large-scale text stream summarization used dynamic topic models and trending words. Instead, we rely on text embeddings – low-dimensional word representations in a continuous vector space where similar words are embedded nearby each other. This paper presents ESTEEM,1 a novel tool for visualizing and evaluating spatiotemporal embeddings learned from streaming social media texts. Our tool allows users to monitor and analyze query words and their closest neighbors with an interactive interface. We used state-of- the-art techniques to learn embeddings and developed a visualization to represent dynamically changing relations between words in social media over time and other dimensions. This is the first interactive visualization of streaming text representations learned from social media texts that also allows users to contrast differences across multiple dimensions of the data.

  1. Cross functional organisational embedded system development

    OpenAIRE

    Lennon, Sophie

    2015-01-01

    peer-reviewed Embedded system development is continuing to grow. Medical, automotive and Internet of Things are just some of the market segments. There is a tight coupling between hardware and software when developing an embedded system, often needing to meet strict performance targets, standards requirements and aggressive schedules. Embedded software developers need to consider hardware requirements in far greater detail as they can have a significant impact on the quality and value of t...

  2. Homomorphic embeddings in n-groups

    Directory of Open Access Journals (Sweden)

    Mona Cristescu

    2013-06-01

    Full Text Available We prove that an cancellative n-groupoid A can be homotopic embedded in an n-group if and only if in A are satisfied all n-ary Malcev conditions. Now we shall prove that in the presence of associative law we obtain homomorphic embeddings. Furthermore, if A has a lateral identity a such embeddings is assured by a subset of n-ary Malcev conditions - unary Malcev conditions.

  3. Knowledge Engineering for Embedded Configuration

    DEFF Research Database (Denmark)

    Oddsson, Gudmundur Valur

    2008-01-01

    into the system the knowledge needed to achieve them. In order to understand the system, one draws simplified functional streams and identifies archetypes from the product assortment, and then one maps the two together into a system breakdown model. The system model indicates how many encapsulation models (EMs......This thesis presents a way to simplify setup of complex product systems with the help of embedded configuration. To achieve this, one has to focus on what subsystems need to communicate between themselves. The required internal knowledge is then structured at three abstraction levels......, and predefined relation types are suggested. The models are stringent and thought out so they can be implemented in software. They should allow both import and export of product knowledge from the knowledge-based system. The purpose of this work is to simplify the installation process of product systems...

  4. The embedded operating system project

    Science.gov (United States)

    Campbell, R. H.

    1985-01-01

    The design and construction of embedded operating systems for real-time advanced aerospace applications was investigated. The applications require reliable operating system support that must accommodate computer networks. Problems that arise in the construction of such operating systems, reconfiguration, consistency and recovery in a distributed system, and the issues of real-time processing are reported. A thesis that provides theoretical foundations for the use of atomic actions to support fault tolerance and data consistency in real-time object-based system is included. The following items are addressed: (1) atomic actions and fault-tolerance issues; (2) operating system structure; (3) program development; (4) a reliable compiler for path Pascal; and (5) mediators, a mechanism for scheduling distributed system processes.

  5. Embedding knowledge in a workstation

    Energy Technology Data Exchange (ETDEWEB)

    Barber, G

    1982-01-01

    This paper describes an approach to supporting work in the office. Using and extending ideas from the field of artificial intelligence (AI) it describes office work as a problem solving activity. A knowledge embedding language called OMEGA is used to embed knowledge of the organization into an office worker's workstation in order to support the office worker in his or her problem solving. A particular approach to reasoning about change and contradiction is discussed. This approach uses OMEGA's viewpoint mechanism. OMEGA's viewpoint mechanism is a general contradiction handling facility. Unlike other knowledge representation systems, when a contradiction is reached the reasons for the contradiction can be analyzed by the reduction mechanism without having to resort to a backtracking mechanism. The viewpoint mechanism is the heart of the problem solving support paradigm. This paradigm is an alternative to the classical view of problem solving in AI. Office workers are supported using the problem solving support paradigm. 16 references.

  6. Embedding Complementarity in HCI Methods and Techniques

    DEFF Research Database (Denmark)

    Nielsen, Janni; Yssing, Carsten; Tweddell Levinsen, Karin

    Differences in cultural contexts constitute differences in cognition, and research has shown that different cultures may use different cognitive tools for perception and reasoning. The cultural embeddings are significant in relation to HCI, because the cultural context is also embedded in the tec......Differences in cultural contexts constitute differences in cognition, and research has shown that different cultures may use different cognitive tools for perception and reasoning. The cultural embeddings are significant in relation to HCI, because the cultural context is also embedded...... the HCI paradigm in system development....

  7. Embedded Fiber Optic Sensors for Integral Armor

    National Research Council Canada - National Science Library

    Fink, Bruce

    2000-01-01

    This report describes the work performed with Production Products Manufacturing & Sales (PPMS), Inc., under the "Liquid Molded Composite Armor Smart Structures Using Embedded Sensors" Small Business Innovative Research...

  8. Graphical Model Debugger Framework for Embedded Systems

    DEFF Research Database (Denmark)

    Zeng, Kebin

    2010-01-01

    Model Driven Software Development has offered a faster way to design and implement embedded real-time software by moving the design to a model level, and by transforming models to code. However, the testing of embedded systems has remained at the code level. This paper presents a Graphical Model...... Debugger Framework, providing an auxiliary avenue of analysis of system models at runtime by executing generated code and updating models synchronously, which allows embedded developers to focus on the model level. With the model debugger, embedded developers can graphically test their design model...

  9. Multichannel analyzer embedded in FPGA

    International Nuclear Information System (INIS)

    Garcia D, A.; Hernandez D, V. M.; Vega C, H. R.; Ordaz G, O. O.; Bravo M, I.

    2017-10-01

    Ionizing radiation has different applications, so it is a very significant and useful tool, which in turn can be dangerous for living beings if they are exposed to uncontrolled doses. However, due to its characteristics, it cannot be perceived by any of the senses of the human being, so that in order to know the presence of it, radiation detectors and additional devices are required to quantify and classify it. A multichannel analyzer is responsible for separating the different pulse heights that are generated in the detectors, in a certain number of channels; according to the number of bits of the analog to digital converter. The objective of the work was to design and implement a multichannel analyzer and its associated virtual instrument, for nuclear spectrometry. The components of the multichannel analyzer were created in VHDL hardware description language and packaged in the Xilinx Vivado design suite, making use of resources such as the ARM processing core that the System on Chip Zynq contains and the virtual instrument was developed on the LabView programming graphics platform. The first phase was to design the hardware architecture to be embedded in the FPGA and for the internal control of the multichannel analyzer the application was generated for the ARM processor in C language. For the second phase, the virtual instrument was developed for the management, control and visualization of the results. The data obtained as a result of the development of the system were observed graphically in a histogram showing the spectrum measured. The design of the multichannel analyzer embedded in FPGA was tested with two different radiation detection systems (hyper-pure germanium and scintillation) which allowed determining that the spectra obtained are similar in comparison with the commercial multichannel analyzers. (Author)

  10. Multithreading for Embedded Reconfigurable Multicore Systems

    NARCIS (Netherlands)

    Zaykov, P.G.

    2014-01-01

    In this dissertation, we address the problem of performance efficient multithreading execution on heterogeneous multicore embedded systems. By heterogeneous multicore embedded systems we refer to those, which have real-time requirements and consist of processor tiles with General Purpose Processor

  11. Multithreading for embedded reconfigurable multicore systems

    NARCIS (Netherlands)

    Zaykov, P.G.

    2014-01-01

    In this dissertation, we address the problem of performance efficient multithreading execution on heterogeneous multicore embedded systems. By heterogeneous multicore embedded systems we refer to those, which have real-time requirements and consist of processor tiles with General Purpose Processor

  12. TTCN-3 for distributed testing embedded systems

    NARCIS (Netherlands)

    Blom, S.C.C.; Deiß, T.; Ioustinova, N.; Kontio, A.; Pol, van de J.C.; Rennoch, A.; Sidorova, N.; Virbitskaite, I.; Voronkov, A.

    2007-01-01

    Abstract. TTCN-3 is a standardized language for specifying and executing test suites that is particularly popular for testing embedded systems. Prior to testing embedded software in a target environment, the software is usually tested in the host environment. Executing in the host environment often

  13. Verification and Performance Analysis for Embedded Systems

    DEFF Research Database (Denmark)

    Larsen, Kim Guldstrand

    2009-01-01

    This talk provides a thorough tutorial of the UPPAAL tool suite for, modeling, simulation, verification, optimal scheduling, synthesis, testing and performance analysis of embedded and real-time systems.......This talk provides a thorough tutorial of the UPPAAL tool suite for, modeling, simulation, verification, optimal scheduling, synthesis, testing and performance analysis of embedded and real-time systems....

  14. Teaching Embedded System Concepts for Technological Literacy

    Science.gov (United States)

    Winzker, M.; Schwandt, A.

    2011-01-01

    A basic understanding of technology is recognized as important knowledge even for students not connected with engineering and computer science. This paper shows that embedded system concepts can be taught in a technological literacy course. An embedded system teaching block that has been used in an electronics module for non-engineers is…

  15. Embedding methods for phi4-interaction

    International Nuclear Information System (INIS)

    Hanckowiak, J.

    1985-01-01

    The idea of embedding a given theory in a class of similar theories is applied to quantum field theory in the case of phi 4 -interaction to derive different equations for the generating functional. The number of possible embeddings has been restricted by demanding that for the defined projections of the generating functional a closed system of equations be obtained

  16. Embedded Java security security for mobile devices

    CERN Document Server

    Debbabi, Mourad; Talhi, Chamseddine

    2007-01-01

    Java brings more functionality and versatility to the world of mobile devices, but it also introduces new security threats. This book contains a presentation of embedded Java security and presents the main components of embedded Java. It gives an idea of the platform architecture and is useful for researchers and practitioners.

  17. Heterogeneous Embedded Real-Time Systems Environment

    Science.gov (United States)

    2003-12-01

    AFRL-IF-RS-TR-2003-290 Final Technical Report December 2003 HETEROGENEOUS EMBEDDED REAL - TIME SYSTEMS ENVIRONMENT Integrated...HETEROGENEOUS EMBEDDED REAL - TIME SYSTEMS ENVIRONMENT 6. AUTHOR(S) Cosmo Castellano and James Graham 5. FUNDING NUMBERS C - F30602-97-C-0259

  18. Embedded Systems Design with 8051 Microcontrollers

    DEFF Research Database (Denmark)

    Karakahayov, Zdravko; Winther, Ole; Christensen, Knud Smed

    Textbook on embedded microcontrollers. Example microcontroller family: Intel 8051 with special emphasis on Philips 80C552. Structure, design examples and programming in C and assembler. Hardware - software codesign. EProm emulator.......Textbook on embedded microcontrollers. Example microcontroller family: Intel 8051 with special emphasis on Philips 80C552. Structure, design examples and programming in C and assembler. Hardware - software codesign. EProm emulator....

  19. Handling Neighbor Discovery and Rendezvous Consistency with Weighted Quorum-Based Approach.

    Science.gov (United States)

    Own, Chung-Ming; Meng, Zhaopeng; Liu, Kehan

    2015-09-03

    Neighbor discovery and the power of sensors play an important role in the formation of Wireless Sensor Networks (WSNs) and mobile networks. Many asynchronous protocols based on wake-up time scheduling have been proposed to enable neighbor discovery among neighboring nodes for the energy saving, especially in the difficulty of clock synchronization. However, existing researches are divided two parts with the neighbor-discovery methods, one is the quorum-based protocols and the other is co-primality based protocols. Their distinction is on the arrangements of time slots, the former uses the quorums in the matrix, the latter adopts the numerical analysis. In our study, we propose the weighted heuristic quorum system (WQS), which is based on the quorum algorithm to eliminate redundant paths of active slots. We demonstrate the specification of our system: fewer active slots are required, the referring rate is balanced, and remaining power is considered particularly when a device maintains rendezvous with discovered neighbors. The evaluation results showed that our proposed method can effectively reschedule the active slots and save the computing time of the network system.

  20. Handling Neighbor Discovery and Rendezvous Consistency with Weighted Quorum-Based Approach

    Directory of Open Access Journals (Sweden)

    Chung-Ming Own

    2015-09-01

    Full Text Available Neighbor discovery and the power of sensors play an important role in the formation of Wireless Sensor Networks (WSNs and mobile networks. Many asynchronous protocols based on wake-up time scheduling have been proposed to enable neighbor discovery among neighboring nodes for the energy saving, especially in the difficulty of clock synchronization. However, existing researches are divided two parts with the neighbor-discovery methods, one is the quorum-based protocols and the other is co-primality based protocols. Their distinction is on the arrangements of time slots, the former uses the quorums in the matrix, the latter adopts the numerical analysis. In our study, we propose the weighted heuristic quorum system (WQS, which is based on the quorum algorithm to eliminate redundant paths of active slots. We demonstrate the specification of our system: fewer active slots are required, the referring rate is balanced, and remaining power is considered particularly when a device maintains rendezvous with discovered neighbors. The evaluation results showed that our proposed method can effectively reschedule the active slots and save the computing time of the network system.

  1. Plant Clonal Integration Mediates the Horizontal Redistribution of Soil Resources, Benefiting Neighboring Plants.

    Science.gov (United States)

    Ye, Xue-Hua; Zhang, Ya-Lin; Liu, Zhi-Lan; Gao, Shu-Qin; Song, Yao-Bin; Liu, Feng-Hong; Dong, Ming

    2016-01-01

    Resources such as water taken up by plants can be released into soils through hydraulic redistribution and can also be translocated by clonal integration within a plant clonal network. We hypothesized that the resources from one (donor) microsite could be translocated within a clonal network, released into different (recipient) microsites and subsequently used by neighbor plants in the recipient microsite. To test these hypotheses, we conducted two experiments in which connected and disconnected ramet pairs of Potentilla anserina were grown under both homogeneous and heterogeneous water regimes, with seedlings of Artemisia ordosica as neighbors. The isotopes [(15)N] and deuterium were used to trace the translocation of nitrogen and water, respectively, within the clonal network. The water and nitrogen taken up by P. anserina ramets in the donor microsite were translocated into the connected ramets in the recipient microsites. Most notably, portions of the translocated water and nitrogen were released into the recipient microsite and were used by the neighboring A. ordosica, which increased growth of the neighboring A. ordosica significantly. Therefore, our hypotheses were supported, and plant clonal integration mediated the horizontal hydraulic redistribution of resources, thus benefiting neighboring plants. Such a plant clonal integration-mediated resource redistribution in horizontal space may have substantial effects on the interspecific relations and composition of the community and consequently on ecosystem processes.

  2. Error Analysis for RADAR Neighbor Matching Localization in Linear Logarithmic Strength Varying Wi-Fi Environment

    Directory of Open Access Journals (Sweden)

    Mu Zhou

    2014-01-01

    Full Text Available This paper studies the statistical errors for the fingerprint-based RADAR neighbor matching localization with the linearly calibrated reference points (RPs in logarithmic received signal strength (RSS varying Wi-Fi environment. To the best of our knowledge, little comprehensive analysis work has appeared on the error performance of neighbor matching localization with respect to the deployment of RPs. However, in order to achieve the efficient and reliable location-based services (LBSs as well as the ubiquitous context-awareness in Wi-Fi environment, much attention has to be paid to the highly accurate and cost-efficient localization systems. To this end, the statistical errors by the widely used neighbor matching localization are significantly discussed in this paper to examine the inherent mathematical relations between the localization errors and the locations of RPs by using a basic linear logarithmic strength varying model. Furthermore, based on the mathematical demonstrations and some testing results, the closed-form solutions to the statistical errors by RADAR neighbor matching localization can be an effective tool to explore alternative deployment of fingerprint-based neighbor matching localization systems in the future.

  3. Error Analysis for RADAR Neighbor Matching Localization in Linear Logarithmic Strength Varying Wi-Fi Environment

    Science.gov (United States)

    Tian, Zengshan; Xu, Kunjie; Yu, Xiang

    2014-01-01

    This paper studies the statistical errors for the fingerprint-based RADAR neighbor matching localization with the linearly calibrated reference points (RPs) in logarithmic received signal strength (RSS) varying Wi-Fi environment. To the best of our knowledge, little comprehensive analysis work has appeared on the error performance of neighbor matching localization with respect to the deployment of RPs. However, in order to achieve the efficient and reliable location-based services (LBSs) as well as the ubiquitous context-awareness in Wi-Fi environment, much attention has to be paid to the highly accurate and cost-efficient localization systems. To this end, the statistical errors by the widely used neighbor matching localization are significantly discussed in this paper to examine the inherent mathematical relations between the localization errors and the locations of RPs by using a basic linear logarithmic strength varying model. Furthermore, based on the mathematical demonstrations and some testing results, the closed-form solutions to the statistical errors by RADAR neighbor matching localization can be an effective tool to explore alternative deployment of fingerprint-based neighbor matching localization systems in the future. PMID:24683349

  4. Improving Fraudster Detection in Online Auctions by Using Neighbor-Driven Attributes

    Directory of Open Access Journals (Sweden)

    Jun-Lin Lin

    2015-12-01

    Full Text Available Online auction websites use a simple reputation system to help their users to evaluate the trustworthiness of sellers and buyers. However, to improve their reputation in the reputation system, fraudulent users can easily deceive the reputation system by creating fake transactions. This inflated-reputation fraud poses a major problem for online auction websites because it can lead legitimate users into scams. Numerous approaches have been proposed in the literature to address this problem, most of which involve using social network analysis (SNA to derive critical features (e.g., k-core, center weight, and neighbor diversity for distinguishing fraudsters from legitimate users. This paper discusses the limitations of these SNA features and proposes a class of SNA features referred to as neighbor-driven attributes (NDAs. The NDAs of users are calculated from the features of their neighbors. Because fraudsters require collusive neighbors to provide them with positive ratings in the reputation system, using NDAs can be helpful for detecting fraudsters. Although the idea of NDAs is not entirely new, experimental results on a real-world dataset showed that using NDAs improves classification accuracy compared with state-of-the-art methods that use the k-core, center weight, and neighbor diversity.

  5. Velocity correlations and spatial dependencies between neighbors in a unidirectional flow of pedestrians

    Science.gov (United States)

    Porzycki, Jakub; WÄ s, Jarosław; Hedayatifar, Leila; Hassanibesheli, Forough; Kułakowski, Krzysztof

    2017-08-01

    The aim of the paper is an analysis of self-organization patterns observed in the unidirectional flow of pedestrians. On the basis of experimental data from Zhang et al. [J. Zhang et al., J. Stat. Mech. (2011) P06004, 10.1088/1742-5468/2011/06/P06004], we analyze the mutual positions and velocity correlations between pedestrians when walking along a corridor. The angular and spatial dependencies of the mutual positions reveal a spatial structure that remains stable during the crowd motion. This structure differs depending on the value of n , for the consecutive n th -nearest-neighbor position set. The preferred position for the first-nearest neighbor is on the side of the pedestrian, while for further neighbors, this preference shifts to the axis of movement. The velocity correlations vary with the angle formed by the pair of neighboring pedestrians and the direction of motion and with the time delay between pedestrians' movements. The delay dependence of the correlations shows characteristic oscillations, produced by the velocity oscillations when striding; however, a filtering of the main frequency of individual striding out reduces the oscillations only partially. We conclude that pedestrians select their path directions so as to evade the necessity of continuously adjusting their speed to their neighbors'. They try to keep a given distance, but follow the person in front of them, as well as accepting and observing pedestrians on their sides. Additionally, we show an empirical example that illustrates the shape of a pedestrian's personal space during movement.

  6. Hardware standardization for embedded systems

    International Nuclear Information System (INIS)

    Sharma, M.K.; Kalra, Mohit; Patil, M.B.; Mohanty, Ashutos; Ganesh, G.; Biswas, B.B.

    2010-01-01

    Reactor Control Division (RCnD) has been one of the main designers of safety and safety related systems for power reactors. These systems have been built using in-house developed hardware. Since the present set of hardware was designed long ago, a need was felt to design a new family of hardware boards. A Working Group on Electronics Hardware Standardization (WG-EHS) was formed with an objective to develop a family of boards, which is general purpose enough to meet the requirements of the system designers/end users. RCnD undertook the responsibility of design, fabrication and testing of boards for embedded systems. VME and a proprietary I/O bus were selected as the two system buses. The boards have been designed based on present day technology and components. The intelligence of these boards has been implemented on FPGA/CPLD using VHDL. This paper outlines the various boards that have been developed with a brief description. (author)

  7. Field tests on partial embedment effects (embedment effect tests on soil-structure interaction)

    International Nuclear Information System (INIS)

    Kurimoto, O.; Tsunoda, T.; Inoue, T.; Izumi, M.; Kusakabe, K.; Akino, K.

    1993-01-01

    A series of Model Tests of Embedment Effect on Reactor Buildings has been carried out by the Nuclear Power Engineering Corporation (NUPEC), under the sponsorship of the Ministry of International Trade and lndustry (MITI) of Japan. The nuclear reactor buildings are partially embedded due to conditions for the construction or building arrangement in Japan. It is necessary to verify the partial embedment effects by experiments and analytical studies in order to incorporate the effects in the seismic design. Forced vibration tests, therefore, were performed using a model with several types of embedment. Correlated simulation analyses were also performed and the characteristics of partial embedment effects on soil-structure interaction were evaluated. (author)

  8. What Will the Neighbors Think? Building Large-Scale Science Projects Around the World

    International Nuclear Information System (INIS)

    Jones, Craig; Mrotzek, Christian; Toge, Nobu; Sarno, Doug

    2007-01-01

    Public participation is an essential ingredient for turning the International Linear Collider into a reality. Wherever the proposed particle accelerator is sited in the world, its neighbors -- in any country -- will have something to say about hosting a 35-kilometer-long collider in their backyards. When it comes to building large-scale physics projects, almost every laboratory has a story to tell. Three case studies from Japan, Germany and the US will be presented to examine how community relations are handled in different parts of the world. How do particle physics laboratories interact with their local communities? How do neighbors react to building large-scale projects in each region? How can the lessons learned from past experiences help in building the next big project? These and other questions will be discussed to engage the audience in an active dialogue about how a large-scale project like the ILC can be a good neighbor.

  9. A Novel Preferential Diffusion Recommendation Algorithm Based on User’s Nearest Neighbors

    Directory of Open Access Journals (Sweden)

    Fuguo Zhang

    2017-01-01

    Full Text Available Recommender system is a very efficient way to deal with the problem of information overload for online users. In recent years, network based recommendation algorithms have demonstrated much better performance than the standard collaborative filtering methods. However, most of network based algorithms do not give a high enough weight to the influence of the target user’s nearest neighbors in the resource diffusion process, while a user or an object with high degree will obtain larger influence in the standard mass diffusion algorithm. In this paper, we propose a novel preferential diffusion recommendation algorithm considering the significance of the target user’s nearest neighbors and evaluate it in the three real-world data sets: MovieLens 100k, MovieLens 1M, and Epinions. Experiments results demonstrate that the novel preferential diffusion recommendation algorithm based on user’s nearest neighbors can significantly improve the recommendation accuracy and diversity.

  10. A multilevel-skin neighbor list algorithm for molecular dynamics simulation

    Science.gov (United States)

    Zhang, Chenglong; Zhao, Mingcan; Hou, Chaofeng; Ge, Wei

    2018-01-01

    Searching of the interaction pairs and organization of the interaction processes are important steps in molecular dynamics (MD) algorithms and are critical to the overall efficiency of the simulation. Neighbor lists are widely used for these steps, where thicker skin can reduce the frequency of list updating but is discounted by more computation in distance check for the particle pairs. In this paper, we propose a new neighbor-list-based algorithm with a precisely designed multilevel skin which can reduce unnecessary computation on inter-particle distances. The performance advantages over traditional methods are then analyzed against the main simulation parameters on Intel CPUs and MICs (many integrated cores), and are clearly demonstrated. The algorithm can be generalized for various discrete simulations using neighbor lists.

  11. Learn good from bad: Effects of good and bad neighbors in spatial prisoners' dilemma games

    Science.gov (United States)

    Lu, Peng

    2015-10-01

    Cooperation is vital for the human society and this study focuses on how to promote cooperation. In our stratification model, there exist three classes: two minorities are elites who are prone to cooperate and scoundrels who are born to defect; one majority is the class of common people. Agents of these three classes interact with each other on a square lattice. Commons' cooperation and its factors are investigated. Contradicting our common sense, it indicates that elites play a negative role while scoundrels play a positive one in promoting commons' cooperation. Besides, effects of good and bad neighbors vary with temptation. When the temptation is smaller the positive effect is able to overcome the negative effect, but the later prevails when the temptation is larger. It concludes that common people are more prone to cooperate in harsh environment with bad neighbors, and a better environment with good neighbors merely leads to laziness and free riding of commons.

  12. Neighbor-dependent Ramachandran probability distributions of amino acids developed from a hierarchical Dirichlet process model.

    Directory of Open Access Journals (Sweden)

    Daniel Ting

    2010-04-01

    Full Text Available Distributions of the backbone dihedral angles of proteins have been studied for over 40 years. While many statistical analyses have been presented, only a handful of probability densities are publicly available for use in structure validation and structure prediction methods. The available distributions differ in a number of important ways, which determine their usefulness for various purposes. These include: 1 input data size and criteria for structure inclusion (resolution, R-factor, etc.; 2 filtering of suspect conformations and outliers using B-factors or other features; 3 secondary structure of input data (e.g., whether helix and sheet are included; whether beta turns are included; 4 the method used for determining probability densities ranging from simple histograms to modern nonparametric density estimation; and 5 whether they include nearest neighbor effects on the distribution of conformations in different regions of the Ramachandran map. In this work, Ramachandran probability distributions are presented for residues in protein loops from a high-resolution data set with filtering based on calculated electron densities. Distributions for all 20 amino acids (with cis and trans proline treated separately have been determined, as well as 420 left-neighbor and 420 right-neighbor dependent distributions. The neighbor-independent and neighbor-dependent probability densities have been accurately estimated using Bayesian nonparametric statistical analysis based on the Dirichlet process. In particular, we used hierarchical Dirichlet process priors, which allow sharing of information between densities for a particular residue type and different neighbor residue types. The resulting distributions are tested in a loop modeling benchmark with the program Rosetta, and are shown to improve protein loop conformation prediction significantly. The distributions are available at http://dunbrack.fccc.edu/hdp.

  13. Optimizing Neighbor Discovery for Ad hoc Networks based on the Bluetooth PAN Profile

    DEFF Research Database (Denmark)

    Kuijpers, Gerben; Nielsen, Thomas Toftegaard; Prasad, Ramjee

    2002-01-01

    IP layer neighbor discovery mechanisms rely highly on broadcast/multicast capabilities of the underlying link layer. The Bluetooth personal area network (PAN) profile has no native link layer broadcast/multicast capabilities and can only emulate this by repeatedly unicast link layer frames....... This paper introduces a neighbor discovery mechanism that utilizes the resources in the Bluetooth PAN profile more efficient. The performance of the new mechanism is investigated using a IPv6 network simulator and compared with emulated broadcasting. It is shown that the signaling overhead can...

  14. Long-term effect of September 11 on the political behavior of victims' families and neighbors.

    Science.gov (United States)

    Hersh, Eitan D

    2013-12-24

    This article investigates the long-term effect of September 11, 2001 on the political behaviors of victims' families and neighbors. Relative to comparable individuals, family members and residential neighbors of victims have become--and have stayed--significantly more active in politics in the last 12 years, and they have become more Republican on account of the terrorist attacks. The method used to demonstrate these findings leverages the random nature of the terrorist attack to estimate a causal effect and exploits new techniques to link multiple, individual-level, governmental databases to measure behavioral change without relying on surveys or aggregate analysis.

  15. Long-term effect of September 11 on the political behavior of victims’ families and neighbors

    Science.gov (United States)

    Hersh, Eitan D.

    2013-01-01

    This article investigates the long-term effect of September 11, 2001 on the political behaviors of victims’ families and neighbors. Relative to comparable individuals, family members and residential neighbors of victims have become—and have stayed—significantly more active in politics in the last 12 years, and they have become more Republican on account of the terrorist attacks. The method used to demonstrate these findings leverages the random nature of the terrorist attack to estimate a causal effect and exploits new techniques to link multiple, individual-level, governmental databases to measure behavioral change without relying on surveys or aggregate analysis. PMID:24324145

  16. Effect of Floquet engineering on the p-wave superconductor with second-neighbor couplings

    Science.gov (United States)

    Li, X. P.; Li, C. F.; Wang, L. C.; Zhou, L.

    2018-06-01

    The influence of the Floquet engineering on a particular one-dimensional p-wave superconductor, Kitaev model, with second-neighbor couplings is investigated in this paper. The effective Hamiltonians in the rotated reference frames have been obtained, and the convergent regions of the approximated Hamiltonian as well as the topological phase diagrams have been analyzed and discussed. We show that by modulating the external driving field amplitude, frequency as well as the second-neighbor hopping amplitude, the rich phase diagrams and transitions between different topological phases can be obtained.

  17. Secure smart embedded devices, platforms and applications

    CERN Document Server

    Markantonakis, Konstantinos

    2013-01-01

    New generations of IT users are increasingly abstracted from the underlying devices and platforms that provide and safeguard their services. As a result they may have little awareness that they are critically dependent on the embedded security devices that are becoming pervasive in daily modern life. Secure Smart Embedded Devices, Platforms and Applications provides a broad overview of the many security and practical issues of embedded devices, tokens, and their operation systems, platforms and main applications. It also addresses a diverse range of industry/government initiatives and consider

  18. Two diverse models of embedding class one

    Science.gov (United States)

    Kuhfittig, Peter K. F.

    2018-05-01

    Embedding theorems have continued to be a topic of interest in the general theory of relativity since these help connect the classical theory to higher-dimensional manifolds. This paper deals with spacetimes of embedding class one, i.e., spacetimes that can be embedded in a five-dimensional flat spacetime. These ideas are applied to two diverse models, a complete solution for a charged wormhole admitting a one-parameter group of conformal motions and a new model to explain the flat rotation curves in spiral galaxies without the need for dark matter.

  19. The art of designing embedded systems

    CERN Document Server

    Ganssle, Jack G

    2000-01-01

    Art of Designing Embedded Systems is apart primer and part reference, aimed at practicing embedded engineers, whether working on the code or the hardware design. Embedded systems suffer from a chaotic, ad hoc development process. This books lays out a very simple seven-step plan to get firmware development under control. There are no formal methodologies to master; the ideas are immediately useful. Most designers are unaware that code complexity grows faster than code size. This book shows a number of ways to linearize the complexity/size curve and get products out faster

  20. Embedded Solenoid Transformer for Power Conversion

    DEFF Research Database (Denmark)

    2015-01-01

    A resonant power converter for operation in the radio frequency range, preferably in the VHF, comprises at least one PCB-embedded transformer. The transformer is configured for radio frequency operation and comprises a printed circuit board defining a horizontal plane, the printed circuit board...... comprising at least two horizontal conductive layers separated by an isolating layer, a first embedded solenoid forming a primary winding of the transformer and a second embedded solenoid being arranged parallel to the first solenoid and forming a secondary winding of the transformer, wherein the first...

  1. AdS2 models in an embedding superspace

    International Nuclear Information System (INIS)

    McKeon, D.G.C.; Sherry, T.N.

    2003-01-01

    An embedding superspace, whose bosonic part is the flat (2+1)-dimensional embedding space for AdS 2 , is introduced. Superfields and several supersymmetric models are examined in the embedded AdS 2 superspace

  2. Embedded Face Detection and Recognition

    Directory of Open Access Journals (Sweden)

    Göksel Günlü

    2012-10-01

    Full Text Available The need to increase security in open or public spaces has in turn given rise to the requirement to monitor these spaces and analyse those images on-site and on-time. At this point, the use of smart cameras – of which the popularity has been increasing – is one step ahead. With sensors and Digital Signal Processors (DSPs, smart cameras generate ad hoc results by analysing the numeric images transmitted from the sensor by means of a variety of image-processing algorithms. Since the images are not transmitted to a distance processing unit but rather are processed inside the camera, it does not necessitate high-bandwidth networks or high processor powered systems; it can instantaneously decide on the required access. Nonetheless, on account of restricted memory, processing power and overall power, image processing algorithms need to be developed and optimized for embedded processors. Among these algorithms, one of the most important is for face detection and recognition. A number of face detection and recognition methods have been proposed recently and many of these methods have been tested on general-purpose processors. In smart cameras – which are real-life applications of such methods – the widest use is on DSPs. In the present study, the Viola-Jones face detection method – which was reported to run faster on PCs – was optimized for DSPs; the face recognition method was combined with the developed sub-region and mask-based DCT (Discrete Cosine Transform. As the employed DSP is a fixed-point processor, the processes were performed with integers insofar as it was possible. To enable face recognition, the image was divided into sub-regions and from each sub-region the robust coefficients against disruptive elements – like face expression, illumination, etc. – were selected as the features. The discrimination of the selected features was enhanced via LDA (Linear Discriminant Analysis and then employed for recognition. Thanks to its

  3. Multidimensional artificial field embedding with spatial sensitivity

    CSIR Research Space (South Africa)

    Lunga, D

    2013-06-01

    Full Text Available Multidimensional embedding is a technique useful for characterizing spectral signature relations in hyperspectral images. However, such images consist of disjoint similar spectral classes that are spatially sensitive, thus presenting challenges...

  4. Costs and benefits of embedded generation

    International Nuclear Information System (INIS)

    1999-11-01

    This project sought to evaluate the costs and benefits of embedded generation in the light of the UK government's consultation paper on the future of green generation, the government's aim to increase the levels of generation from renewable energy sources and cogeneration, the current Review of the Electricity Trading Arrangements, and the form of the Distribution Price Control. Definitions are given for embedded, centrally dispatched, and pooled generation, and licensed suppliers, and commercial and economic values. The commercial and economic value of embedded generation is examined in terms of generation prices, costs to electrical suppliers, losses (electrical, transmission, distribution), and effects on the national grid and distribution network. Diagrams showing the cost elements of trading through the Pool and the elements that are avoided by non-Pool embedded generator trading are presented

  5. Time-Scale Invariant Audio Data Embedding

    Directory of Open Access Journals (Sweden)

    Mansour Mohamed F

    2003-01-01

    Full Text Available We propose a novel algorithm for high-quality data embedding in audio. The algorithm is based on changing the relative length of the middle segment between two successive maximum and minimum peaks to embed data. Spline interpolation is used to change the lengths. To ensure smooth monotonic behavior between peaks, a hybrid orthogonal and nonorthogonal wavelet decomposition is used prior to data embedding. The possible data embedding rates are between 20 and 30 bps. However, for practical purposes, we use repetition codes, and the effective embedding data rate is around 5 bps. The algorithm is invariant after time-scale modification, time shift, and time cropping. It gives high-quality output and is robust to mp3 compression.

  6. Embedding Moodle into Ubiquitous Computing Environments

    NARCIS (Netherlands)

    Glahn, Christian; Specht, Marcus

    2010-01-01

    Glahn, C., & Specht, M. (2010). Embedding Moodle into Ubiquitous Computing Environments. In M. Montebello, et al. (Eds.), 9th World Conference on Mobile and Contextual Learning (MLearn2010) (pp. 100-107). October, 19-22, 2010, Valletta, Malta.

  7. Apparatuses And Systems For Embedded Thermoelectric Generators

    KAUST Repository

    Hussain, Muhammad M.

    2013-08-08

    An apparatus and a system for embedded thermoelectric generators are disclosed. In one embodiment, the apparatus is embedded in an interface where the ambient temperatures on two sides of the interface are different. In one embodiment, the apparatus is fabricated with the interface in integrity as a unitary piece. In one embodiment, the apparatus includes a first thermoelectric material embedded through the interface. The apparatus further includes a second thermoelectric material embedded through the interface. The first thermoelectric material is electrically coupled to the second thermoelectric material. In one embodiment, the apparatus further includes an output structure coupled to the first thermoelectric material and the second thermoelectric material and configured to output a voltage.

  8. Apparatuses And Systems For Embedded Thermoelectric Generators

    KAUST Repository

    Hussain, Muhammad M.; Inayat, Salman Bin; Smith, Casey Eben

    2013-01-01

    An apparatus and a system for embedded thermoelectric generators are disclosed. In one embodiment, the apparatus is embedded in an interface where the ambient temperatures on two sides of the interface are different. In one embodiment, the apparatus is fabricated with the interface in integrity as a unitary piece. In one embodiment, the apparatus includes a first thermoelectric material embedded through the interface. The apparatus further includes a second thermoelectric material embedded through the interface. The first thermoelectric material is electrically coupled to the second thermoelectric material. In one embodiment, the apparatus further includes an output structure coupled to the first thermoelectric material and the second thermoelectric material and configured to output a voltage.

  9. Embedded High Performance Scalable Computing Systems

    National Research Council Canada - National Science Library

    Ngo, David

    2003-01-01

    The Embedded High Performance Scalable Computing Systems (EHPSCS) program is a cooperative agreement between Sanders, A Lockheed Martin Company and DARPA that ran for three years, from Apr 1995 - Apr 1998...

  10. The Influence of Neighbor Effect and Urbanization Toward Organ Donation in Thailand.

    Science.gov (United States)

    Wongboonsin, Kua; Jindahra, Pavitra; Teerakapibal, Surat

    2018-03-01

    Toward population wellness, an extreme scarcity of organ supply is proven to be an enormous hindrance. Preferences toward organ donation are vital to raise the organ donation rate. Notably, the area people live in can address the social influence on individual preference toward organ donation. This article studies the impact of the neighbor effect on organ donation decisions, addressing the social influence of urbanization on preferences. How neighborhood-specific variables, population density, and socioeconomic status drive the neighbor effect is investigated. The pursuit of organ donor traits is to be answered. The study uses organ donation interview survey data and neighborhood-specific data from Thailand to estimate a series of logistic regression models. Individuals residing in urban areas exhibit a greater likelihood to sign the donor card than those in rural areas. The neighborhood socioeconomic status is the key driver. An individual is more willing to be an organ donor when having neighbors with higher socioeconomic statuses. Results also reveal positive influences of males and education on the organ donation rate. This article documents the "neighbor effect" on the organ donation decision via living area type, offering an alternative exposition in raising the organ donation rate. In shifting the society norm toward organ donation consent, policy-makers should acknowledge the benefit of urbanization on organ donation decision derived from resourceful urban areas. Moreover, raising education levels does improve not only citizens' well-being but also their tendency to exhibit an altruistic act toward others.

  11. Applying an efficient K-nearest neighbor search to forest attribute imputation

    Science.gov (United States)

    Andrew O. Finley; Ronald E. McRoberts; Alan R. Ek

    2006-01-01

    This paper explores the utility of an efficient nearest neighbor (NN) search algorithm for applications in multi-source kNN forest attribute imputation. The search algorithm reduces the number of distance calculations between a given target vector and each reference vector, thereby, decreasing the time needed to discover the NN subset. Results of five trials show gains...

  12. Neighbor discovery in multi-hop wireless networks: evaluation and dimensioning with interferences considerations

    Directory of Open Access Journals (Sweden)

    Elyes Ben Hamida

    2008-04-01

    Full Text Available In this paper, we study the impact of collisions and interferences on a neighbor discovery process in the context of multi-hop wireless networks. We consider three models in which interferences and collisions are handled in very different ways. From an ideal channel where simultaneous transmissions do not interfere, we derive an alternate channel where simultaneous transmissions are considered two-by-two under the form of collisions, to finally reach a more realistic channel where simultaneous transmissions are handled under the form of shot-noise interferences. In these models, we analytically compute the link probability success between two neighbors as well as the expected number of nodes that correctly receive a Hello packet. Using this analysis, we show that if the neighbor discovery process is asymptotically equivalent in the three models, it offers very different behaviors locally in time. In particular, the scalability of the process is not the same depending on the way interferences are handled. Finally, we apply our results to the dimensioning of a Hello protocol parameters. We propose a method to adapt the protocol parameters to meet application constraints on the neighbor discovery process and to minimize the protocol energy consumption.

  13. Loving All Your Neighbors: Why Community Colleges Need the Academic Study of Religion

    Science.gov (United States)

    Maley, Melissa

    2013-01-01

    This chapter explains how the study of world religions prepares the community college student to become a better citizen, worker, and neighbor. The effective middle between the pitfalls of religious relativism and religious dominance in a world religions classroom is central to this discussion of teaching critical thinking, empathy, and…

  14. Stuttering Attitudes among Turkish Family Generations and Neighbors from Representative Samples

    Science.gov (United States)

    Ozdemir, R. Sertan; St. Louis, Kenneth O.; Topbas, Seyhun

    2011-01-01

    Purpose: Attitudes toward stuttering, measured by the "Public Opinion Survey of Human Attributes-Stuttering" ("POSHA-S"), are compared among (a) two different representative samples; (b) family generations (children, parents, and either grandparents or uncles and aunts) and neighbors; (c) children, parents, grandparents/adult…

  15. Estimating forest attribute parameters for small areas using nearest neighbors techniques

    Science.gov (United States)

    Ronald E. McRoberts

    2012-01-01

    Nearest neighbors techniques have become extremely popular, particularly for use with forest inventory data. With these techniques, a population unit prediction is calculated as a linear combination of observations for a selected number of population units in a sample that are most similar, or nearest, in a space of ancillary variables to the population unit requiring...

  16. Estimating cavity tree and snag abundance using negative binomial regression models and nearest neighbor imputation methods

    Science.gov (United States)

    Bianca N.I. Eskelson; Hailemariam Temesgen; Tara M. Barrett

    2009-01-01

    Cavity tree and snag abundance data are highly variable and contain many zero observations. We predict cavity tree and snag abundance from variables that are readily available from forest cover maps or remotely sensed data using negative binomial (NB), zero-inflated NB, and zero-altered NB (ZANB) regression models as well as nearest neighbor (NN) imputation methods....

  17. The indirect effects of cheatgrass invasion: Grasshopper herbivory on native grasses determined by neighboring cheatgrass abundance

    Science.gov (United States)

    Julie Beckstead; Susan E. Meyer; Carol K. Augsperger

    2008-01-01

    Invasion biology has focused on the direct effects of plant invasion and has generally overlooked indirect interactions. Here we link theories of invasion biology and herbivory to explore an indirect effect of one invading species on associational herbivory (the effect of neighboring plants on herbivory) of native species. We studied a Great Basin shadscale (...

  18. Mapping change of older forest with nearest-neighbor imputation and Landsat time-series

    Science.gov (United States)

    Janet L. Ohmann; Matthew J. Gregory; Heather M. Roberts; Warren B. Cohen; Robert E. Kennedy; Zhiqiang. Yang

    2012-01-01

    The Northwest Forest Plan (NWFP), which aims to conserve late-successional and old-growth forests (older forests) and associated species, established new policies on federal lands in the Pacific Northwest USA. As part of monitoring for the NWFP, we tested nearest-neighbor imputation for mapping change in older forest, defined by threshold values for forest attributes...

  19. Numerical Simulation of the Diffusion Processes in Nanoelectrode Arrays Using an Axial Neighbor Symmetry Approximation.

    Science.gov (United States)

    Peinetti, Ana Sol; Gilardoni, Rodrigo S; Mizrahi, Martín; Requejo, Felix G; González, Graciela A; Battaglini, Fernando

    2016-06-07

    Nanoelectrode arrays have introduced a complete new battery of devices with fascinating electrocatalytic, sensitivity, and selectivity properties. To understand and predict the electrochemical response of these arrays, a theoretical framework is needed. Cyclic voltammetry is a well-fitted experimental technique to understand the undergoing diffusion and kinetics processes. Previous works describing microelectrode arrays have exploited the interelectrode distance to simulate its behavior as the summation of individual electrodes. This approach becomes limited when the size of the electrodes decreases to the nanometer scale due to their strong radial effect with the consequent overlapping of the diffusional fields. In this work, we present a computational model able to simulate the electrochemical behavior of arrays working either as the summation of individual electrodes or being affected by the overlapping of the diffusional fields without previous considerations. Our computational model relays in dividing a regular electrode array in cells. In each of them, there is a central electrode surrounded by neighbor electrodes; these neighbor electrodes are transformed in a ring maintaining the same active electrode area than the summation of the closest neighbor electrodes. Using this axial neighbor symmetry approximation, the problem acquires a cylindrical symmetry, being applicable to any diffusion pattern. The model is validated against micro- and nanoelectrode arrays showing its ability to predict their behavior and therefore to be used as a designing tool.

  20. Impact of Training Bolivian Farmers on Integrated Pest Management and Diffusion of Knowledge to Neighboring Farmers

    DEFF Research Database (Denmark)

    Jørs, Erik; Konradsen, Flemming; Huici, Omar

    2016-01-01

    of importance to justify training costs and to promote a healthy and sustainable agriculture. Training on IPM of farmers took place from 2002 to 2004 in their villages in La Paz County, Bolivia, while dissemination of knowledge from trained farmer to neighboring farmer took place until 2009. To evaluate...

  1. Moderate-resolution data and gradient nearest neighbor imputation for regional-national risk assessment

    Science.gov (United States)

    Kenneth B. Jr. Pierce; C. Kenneth Brewer; Janet L. Ohmann

    2010-01-01

    This study was designed to test the feasibility of combining a method designed to populate pixels with inventory plot data at the 30-m scale with a new national predictor data set. The new national predictor data set was developed by the USDA Forest Service Remote Sensing Applications Center (hereafter RSAC) at the 250-m scale. Gradient Nearest Neighbor (GNN)...

  2. Integration and analysis of neighbor discovery and link quality estimation in wireless sensor networks.

    Science.gov (United States)

    Radi, Marjan; Dezfouli, Behnam; Abu Bakar, Kamalrulnizam; Abd Razak, Shukor

    2014-01-01

    Network connectivity and link quality information are the fundamental requirements of wireless sensor network protocols to perform their desired functionality. Most of the existing discovery protocols have only focused on the neighbor discovery problem, while a few number of them provide an integrated neighbor search and link estimation. As these protocols require a careful parameter adjustment before network deployment, they cannot provide scalable and accurate network initialization in large-scale dense wireless sensor networks with random topology. Furthermore, performance of these protocols has not entirely been evaluated yet. In this paper, we perform a comprehensive simulation study on the efficiency of employing adaptive protocols compared to the existing nonadaptive protocols for initializing sensor networks with random topology. In this regard, we propose adaptive network initialization protocols which integrate the initial neighbor discovery with link quality estimation process to initialize large-scale dense wireless sensor networks without requiring any parameter adjustment before network deployment. To the best of our knowledge, this work is the first attempt to provide a detailed simulation study on the performance of integrated neighbor discovery and link quality estimation protocols for initializing sensor networks. This study can help system designers to determine the most appropriate approach for different applications.

  3. 77 FR 50504 - Good Neighbor Environmental Board Notification of Public Advisory Committee Teleconference

    Science.gov (United States)

    2012-08-21

    ... recommendations to the President and Congress on environmental and infrastructure issues along the U.S. border with Mexico. Purpose of Meeting: The purpose of this teleconference is to discuss the Good Neighbor Environmental Board's Fifteenth Report. The report will focus on water infrastructure issues in the U.S.-Mexico...

  4. 77 FR 13599 - Good Neighbor Environmental Board; Notification of Public Advisory Committee Teleconference

    Science.gov (United States)

    2012-03-07

    ... recommendations to the President and Congress on environmental and infrastructure issues along the U.S. border with Mexico. Purpose of Meeting: The purpose of this teleconference is to discuss the Good Neighbor Environmental Board's Fifteenth Report. The report will focus on water infrastructure issues in the U.S.-Mexico...

  5. Probability distributions for first neighbor distances between resonances that belong to two different families

    International Nuclear Information System (INIS)

    Difilippo, F.C.

    1994-01-01

    For a mixture of two families of resonances, we found the probability distribution for the distance, as first neighbors, between resonances that belong to different families. Integration of this distribution gives the probability of accidental overlapping of resonances of one isotope by resonances of the other, provided that the resonances of each isotope belong to a single family. (author)

  6. Neighbor Discovery Algorithm in Wireless Local Area Networks Using Multi-beam Directional Antennas

    Science.gov (United States)

    Wang, Jin; Peng, Wei; Liu, Song

    2017-10-01

    Neighbor discovery is an important step for Wireless Local Area Networks (WLAN) and the use of multi-beam directional antennas can greatly improve the network performance. However, most neighbor discovery algorithms in WLAN, based on multi-beam directional antennas, can only work effectively in synchronous system but not in asynchro-nous system. And collisions at AP remain a bottleneck for neighbor discovery. In this paper, we propose two asynchrono-us neighbor discovery algorithms: asynchronous hierarchical scanning (AHS) and asynchronous directional scanning (ADS) algorithm. Both of them are based on three-way handshaking mechanism. AHS and ADS reduce collisions at AP to have a good performance in a hierarchical way and directional way respectively. In the end, the performance of the AHS and ADS are tested on OMNeT++. Moreover, it is analyzed that different application scenarios and the factors how to affect the performance of these algorithms. The simulation results show that AHS is suitable for the densely populated scenes around AP while ADS is suitable for that most of the neighborhood nodes are far from AP.

  7. Integration and Analysis of Neighbor Discovery and Link Quality Estimation in Wireless Sensor Networks

    Directory of Open Access Journals (Sweden)

    Marjan Radi

    2014-01-01

    Full Text Available Network connectivity and link quality information are the fundamental requirements of wireless sensor network protocols to perform their desired functionality. Most of the existing discovery protocols have only focused on the neighbor discovery problem, while a few number of them provide an integrated neighbor search and link estimation. As these protocols require a careful parameter adjustment before network deployment, they cannot provide scalable and accurate network initialization in large-scale dense wireless sensor networks with random topology. Furthermore, performance of these protocols has not entirely been evaluated yet. In this paper, we perform a comprehensive simulation study on the efficiency of employing adaptive protocols compared to the existing nonadaptive protocols for initializing sensor networks with random topology. In this regard, we propose adaptive network initialization protocols which integrate the initial neighbor discovery with link quality estimation process to initialize large-scale dense wireless sensor networks without requiring any parameter adjustment before network deployment. To the best of our knowledge, this work is the first attempt to provide a detailed simulation study on the performance of integrated neighbor discovery and link quality estimation protocols for initializing sensor networks. This study can help system designers to determine the most appropriate approach for different applications.

  8. Dose distribution in the thyroid and neighboring regions in therapy with 131I

    International Nuclear Information System (INIS)

    Monteiro, Rommel Barbosa; Bonifacio, Daniel Alexandre Baptista; Sa, Lidia Vasconcellos de

    2013-01-01

    In this work, simulations were performed with two types of computer simulators: the MIRD phantom and voxel phantom MASH, both of type adult male and in the standing position, coupled to the computational tool GATE (Geant4 Application for Tomographic Emission), to obtain the dose deposited in thyroid and neighboring regions

  9. Modeling the effect of neighboring grains on twin growth in HCP polycrystals

    Science.gov (United States)

    Kumar, M. Arul; Beyerlein, I. J.; Lebensohn, R. A.; Tomé, C. N.

    2017-09-01

    In this paper, we study the dependence of neighboring grain orientation on the local stress state around a deformation twin in a hexagonal close packed (HCP) crystal and its effects on the resistance against twin thickening. We use a recently developed, full-field elasto-visco-plastic formulation based on fast Fourier transforms that account for the twinning shear transformation imposed by the twin lamella. The study is applied to Mg, Zr and Ti, since these HCP metals tend to deform by activation of different types of slip modes. The analysis shows that the local stress along the twin boundary are strongly controlled by the relative orientation of the easiest deformation modes in the neighboring grain with respect to the twin lamella in the parent grain. A geometric expression that captures this parent-neighbor relationship is proposed and incorporated into a larger scale, mean-field visco-plastic self-consistent model to simulate the role of neighboring grain orientation on twin thickening. We demonstrate that the approach improves the prediction of twin area fraction distribution when compared with experimental observations.

  10. Recursive nearest neighbor search in a sparse and multiscale domain for comparing audio signals

    DEFF Research Database (Denmark)

    Sturm, Bob L.; Daudet, Laurent

    2011-01-01

    We investigate recursive nearest neighbor search in a sparse domain at the scale of audio signals. Essentially, to approximate the cosine distance between the signals we make pairwise comparisons between the elements of localized sparse models built from large and redundant multiscale dictionaries...

  11. Collective Behaviors of Mobile Robots Beyond the Nearest Neighbor Rules With Switching Topology.

    Science.gov (United States)

    Ning, Boda; Han, Qing-Long; Zuo, Zongyu; Jin, Jiong; Zheng, Jinchuan

    2018-05-01

    This paper is concerned with the collective behaviors of robots beyond the nearest neighbor rules, i.e., dispersion and flocking, when robots interact with others by applying an acute angle test (AAT)-based interaction rule. Different from a conventional nearest neighbor rule or its variations, the AAT-based interaction rule allows interactions with some far-neighbors and excludes unnecessary nearest neighbors. The resulting dispersion and flocking hold the advantages of scalability, connectivity, robustness, and effective area coverage. For the dispersion, a spring-like controller is proposed to achieve collision-free coordination. With switching topology, a new fixed-time consensus-based energy function is developed to guarantee the system stability. An upper bound of settling time for energy consensus is obtained, and a uniform time interval is accordingly set so that energy distribution is conducted in a fair manner. For the flocking, based on a class of generalized potential functions taking nonsmooth switching into account, a new controller is proposed to ensure that the same velocity for all robots is eventually reached. A co-optimizing problem is further investigated to accomplish additional tasks, such as enhancing communication performance, while maintaining the collective behaviors of mobile robots. Simulation results are presented to show the effectiveness of the theoretical results.

  12. Who's Watching the Babies? Improving the Quality of Family, Friend, and Neighbor Child Care

    Science.gov (United States)

    Powell, Douglas R.

    2008-01-01

    One of the important influences on a child's development is the quality of his or her early care and education experiences. It is estimated that more than 1 million children in the U.S. are cared for while their parents are at work by nonlicensed caregivers who are family, friends, or neighbors - and these caregivers can be difficult to reach…

  13. Transfer-Efficient Face Routing Using the Planar Graphs of Neighbors in High Density WSNs

    Directory of Open Access Journals (Sweden)

    Eun-Seok Cho

    2017-10-01

    Full Text Available Face routing has been adopted in wireless sensor networks (WSNs where topological changes occur frequently or maintaining full network information is difficult. For message forwarding in networks, a planar graph is used to prevent looping, and because long edges are removed by planarization and the resulting planar graph is composed of short edges, and messages are forwarded along multiple nodes connected by them even though they can be forwarded directly. To solve this, face routing using information on all nodes within 2-hop range was adopted to forward messages directly to the farthest node within radio range. However, as the density of the nodes increases, network performance plunges because message transfer nodes receive and process increased node information. To deal with this problem, we propose a new face routing using the planar graphs of neighboring nodes to improve transfer efficiency. It forwards a message directly to the farthest neighbor and reduces loads and processing time by distributing network graph construction and planarization to the neighbors. It also decreases the amount of location information to be transmitted by sending information on the planar graph nodes rather than on all neighboring nodes. Simulation results show that it significantly improves transfer efficiency.

  14. Embedded Lattice and Properties of Gram Matrix

    Directory of Open Access Journals (Sweden)

    Futa Yuichi

    2017-03-01

    Full Text Available In this article, we formalize in Mizar [14] the definition of embedding of lattice and its properties. We formally define an inner product on an embedded module. We also formalize properties of Gram matrix. We formally prove that an inverse of Gram matrix for a rational lattice exists. Lattice of Z-module is necessary for lattice problems, LLL (Lenstra, Lenstra and Lov´asz base reduction algorithm [16] and cryptographic systems with lattice [17].

  15. Embedded adhesive connection for laminated glass plates

    DEFF Research Database (Denmark)

    Hansen, Jens Zangenberg; Poulsen, S.H.; Bagger, A.

    2012-01-01

    The structural behavior of a new connection design, the embedded adhesive connection, used for laminated glass plates is investigated. The connection consists of an aluminum plate encapsulated in-between two adjacent triple layered laminated glass plates. Fastening between glass and aluminum...... usage in a design situation. The embedded connection shows promising potential as a future fastening system for load-carrying laminated glass plates....

  16. Operating system concepts for embedded multicores

    OpenAIRE

    Horst, Oliver; Schmidt, Adriaan

    2014-01-01

    Currently we can see an increasing adoption of multi-core platforms in the area of embedded systems. While these new hardware platforms offer the potential to satisfy the ever increasing demand for computational power, they pose considerable challenges with regard to software development. This affects the application software itself, but also the system design and architecture. Here, we address the consequences for operating system architecture in embedded systems. After dis-cussing current a...

  17. The distribution of the number of node neighbors in random hypergraphs

    International Nuclear Information System (INIS)

    López, Eduardo

    2013-01-01

    Hypergraphs, the generalization of graphs in which edges become conglomerates of r nodes called hyperedges of rank r ⩾ 2, are excellent models to study systems with interactions that are beyond the pairwise level. For hypergraphs, the node degree ℓ (number of hyperedges connected to a node) and the number of neighbors k of a node differ from each other in contrast to the case of graphs, where counting the number of edges is equivalent to counting the number of neighbors. In this paper, I calculate the distribution of the number of node neighbors in random hypergraphs in which hyperedges of uniform rank r have a homogeneous (equal for all hyperedges) probability p to appear. This distribution is equivalent to the degree distribution of ensembles of graphs created as projections of hypergraph or bipartite network ensembles, where the projection connects any two nodes in the projected graph when they are also connected in the hypergraph or bipartite network. The calculation is non-trivial due to the possibility that neighbor nodes belong simultaneously to multiple hyperedges (node overlaps). From the exact results, the traditional asymptotic approximation to the distribution in the sparse regime (small p) where overlaps are ignored is rederived and improved; the approximation exhibits Poisson-like behavior accompanied by strong fluctuations modulated by power-law decays in the system size N with decay exponents equal to the minimum number of overlapping nodes possible for a given number of neighbors. It is shown that the dense limit cannot be explained if overlaps are ignored, and the correct asymptotic distribution is provided. The neighbor distribution requires the calculation of a new combinatorial coefficient Q r−1 (k, ℓ), which counts the number of distinct labeled hypergraphs of k nodes, ℓ hyperedges of rank r − 1, and where every node is connected to at least one hyperedge. Some identities of Q r−1 (k, ℓ) are derived and applied to the

  18. Impact of Training Bolivian Farmers on Integrated Pest Management and Diffusion of Knowledge to Neighboring Farmers.

    Science.gov (United States)

    Jørs, Erik; Konradsen, Flemming; Huici, Omar; Morant, Rafael C; Volk, Julie; Lander, Flemming

    2016-01-01

    Teaching farmers integrated pest management (IPM) in farmer field schools (FFS) has led to reduced pesticide use and safer handling. This article evaluates the long-term impact of training farmers on IPM and the diffusion of knowledge from trained farmers to neighboring farmers, a subject of importance to justify training costs and to promote a healthy and sustainable agriculture. Training on IPM of farmers took place from 2002 to 2004 in their villages in La Paz County, Bolivia, whereas dissemination of knowledge from trained farmer to neighboring farmer took place until 2009. To evaluate the impact of the intervention, self-reported knowledge and practice on pesticide handling and IPM among trained farmers (n = 23) and their neighboring farmers (n = 47) were analyzed in a follow-up study and compared in a cross-sectional analysis with a control group of farmers (n = 138) introduced in 2009. Variables were analyzed using χ2 test and analysis of variance (ANOVA). Trained farmers improved and performed significantly better in all tested variables than their neighboring farmers, although the latter also improved their performance from 2002 to 2009. Including a control group showed an increasing trend in all variables, with the control farmers having the poorest performance and trained farmers the best. The same was seen in an aggregated variable where trained farmers had a mean score of 16.55 (95% confidence interval [CI]: 15.45-17.65), neighboring farmers a mean score of 11.97 (95% CI: 10.56-13.38), and control farmers a mean score of 9.18 (95% CI: 8.55-9.80). Controlling for age and living altitude did not change these results. Trained farmers and their neighboring farmers improved and maintained knowledge and practice on IPM and pesticide handling. Diffusion of knowledge from trained farmers might explain the better performance of the neighboring farmers compared with the control farmers. Dissemination of knowledge can contribute to justify the cost and convince

  19. The neighbor enclosed area tracking algorithm and its application to cyclone merger in the midlatitudes

    Science.gov (United States)

    Inatsu, Masaru; Amada, Shotarou; Satake, Yuya

    2010-05-01

    The neighbor enclosed area tracking (NEAT) algorithm is proposed as an alternative method to conventional point-to-point cyclone tracking approaches. Most automated Lagrangian tracking algorithms contain three procedures: cyclone identification, cyclone tracking, and quantification of cyclone intensity and activity. The cyclone identification was simply based on a comparison of neighboring grid points; cyclone tracking mainly employed a near-neighbor point search to neighbor-time cyclone-center datasets; and cyclone intensity and activity are mainly quantified as cyclone track density, and other accompanying products such as genesis and lysis densities, mean lifetime, average moving vector, and mean growth rate can also be obtained in the final procedure. But a crucial problem in the above technique is its requirement of some complicated connecting conditions for near-neighbor tracking. To overcome the problem, NEAT completes cyclone identification and cyclone tracking in a single process of equivalent labeling for spatiotemporally connected domains, i.e., if two spatially enclosed areas in a neighboring time frame overlap, they should be connected. NEAT enables us to count the genesis and tracks of individual cyclones as the conventional tracking. Moreover, NEAT has the ability to produce fruitful information on cyclone mergers and separations, cyclone shape, and material transport by individual eddies (the latter two features will be reported elsewhere). There are many possible applications of NEAT to meteorology and oceanography, but now we focus on the situation, well-known by Japanese synopticians, that two cyclones pass respectively over the north and south of Japan and then they frequently merge and are rapidly deepened in the western Pacific. For the case, the southern cyclones tend to be stimulated just above the sea surface temperature front to the north of oceanic western boundary currents, while the northern cyclones, moving eastward along the polar

  20. Classification of molecular structure images by using ANN, RF, LBP, HOG, and size reduction methods for early stomach cancer detection

    Science.gov (United States)

    Aytaç Korkmaz, Sevcan; Binol, Hamidullah

    2018-03-01

    Patients who die from stomach cancer are still present. Early diagnosis is crucial in reducing the mortality rate of cancer patients. Therefore, computer aided methods have been developed for early detection in this article. Stomach cancer images were obtained from Fırat University Medical Faculty Pathology Department. The Local Binary Patterns (LBP) and Histogram of Oriented Gradients (HOG) features of these images are calculated. At the same time, Sammon mapping, Stochastic Neighbor Embedding (SNE), Isomap, Classical multidimensional scaling (MDS), Local Linear Embedding (LLE), Linear Discriminant Analysis (LDA), t-Distributed Stochastic Neighbor Embedding (t-SNE), and Laplacian Eigenmaps methods are used for dimensional the reduction of the features. The high dimension of these features has been reduced to lower dimensions using dimensional reduction methods. Artificial neural networks (ANN) and Random Forest (RF) classifiers were used to classify stomach cancer images with these new lower feature sizes. New medical systems have developed to measure the effects of these dimensions by obtaining features in different dimensional with dimensional reduction methods. When all the methods developed are compared, it has been found that the best accuracy results are obtained with LBP_MDS_ANN and LBP_LLE_ANN methods.

  1. Embedded computer systems for control applications in EBR-II

    International Nuclear Information System (INIS)

    Carlson, R.B.; Start, S.E.

    1993-01-01

    The purpose of this paper is to describe the embedded computer systems approach taken at Experimental Breeder Reactor II (EBR-II) for non-safety related systems. The hardware and software structures for typical embedded systems are presented The embedded systems development process is described. Three examples are given which illustrate typical embedded computer applications in EBR-II

  2. 75 FR 62412 - Notice of Proposed Information Collection: Comment Request; HUD-Owned Real Estate-Good Neighbor...

    Science.gov (United States)

    2010-10-08

    ... DEPARTMENT OF HOUSING AND URBAN DEVELOPMENT [Docket No. FR-5380-N-36] Notice of Proposed Information Collection: Comment Request; HUD- Owned Real Estate-Good Neighbor Next Door Program AGENCY: Office... information: Title of Proposal: HUD-Owned Real Estate-Good Neighbor Next Door Program. OMB Control Number, if...

  3. A two-step nearest neighbors algorithm using satellite imagery for predicting forest structure within species composition classes

    Science.gov (United States)

    Ronald E. McRoberts

    2009-01-01

    Nearest neighbors techniques have been shown to be useful for predicting multiple forest attributes from forest inventory and Landsat satellite image data. However, in regions lacking good digital land cover information, nearest neighbors selected to predict continuous variables such as tree volume must be selected without regard to relevant categorical variables such...

  4. IDE Support of String-Embedded Languages

    Directory of Open Access Journals (Sweden)

    S. Grigorev

    2014-01-01

    Full Text Available Complex information systems are often implemented by using more than one programming language. Sometimes this variety takes a form of one host and one or few string-embedded languages. Textual representation of clauses in a string-embedded language is built at run time by a host program and then analyzed, compiled or interpreted by a dedicated runtime component (database, web browser etc. Most general-purpose programming languages may play the role of the host; one of the most evident examples of the string-embedded language is the dynamic SQL which was specified in ISO SQL standard and is supported by the majority of DBMS. Standard IDE functionality such as code completion or syntax highlighting can really helps the developers who use this technique. There are several tools providing this functionality, but they all process only one concrete string-embedded language and cannot be easily extended for supporting another language. We present a platform which allows to easily create tools for string-embedded language processing.

  5. Diverse Power Iteration Embeddings and Its Applications

    Energy Technology Data Exchange (ETDEWEB)

    Huang H.; Yoo S.; Yu, D.; Qin, H.

    2014-12-14

    Abstract—Spectral Embedding is one of the most effective dimension reduction algorithms in data mining. However, its computation complexity has to be mitigated in order to apply it for real-world large scale data analysis. Many researches have been focusing on developing approximate spectral embeddings which are more efficient, but meanwhile far less effective. This paper proposes Diverse Power Iteration Embeddings (DPIE), which not only retains the similar efficiency of power iteration methods but also produces a series of diverse and more effective embedding vectors. We test this novel method by applying it to various data mining applications (e.g. clustering, anomaly detection and feature selection) and evaluating their performance improvements. The experimental results show our proposed DPIE is more effective than popular spectral approximation methods, and obtains the similar quality of classic spectral embedding derived from eigen-decompositions. Moreover it is extremely fast on big data applications. For example in terms of clustering result, DPIE achieves as good as 95% of classic spectral clustering on the complex datasets but 4000+ times faster in limited memory environment.

  6. Technical solutions to enable embedded generation growth

    Energy Technology Data Exchange (ETDEWEB)

    Lynch, C.A.; Todd, S.; Millar, W.; Wood, H.S.

    2003-07-01

    This report describes the results of one of a series of studies commissioned by the UK Department of Trade and Industry into various aspects of embedded generation with the aim of supporting the development and deployment of electrical sources (particularly their ease of connection to the network) to deliver power to consumers. The first phase of the project involved a literature review and meetings with embedded generation developers and planning engineers from distribution network operators (DNOs). The second phase investigated embedded generation at different levels of the distribution network and included modelling a representative network. Technologies that could facilitate a significant increase in embedded generation were identified and estimates made of when and where significant development would be needed. Technical problems identified by DNOs were concerned with thermal loading, voltage regulation, fault levels, protection and network operation. A number of non-technical (commercial and regulatory) problems were also identified. The report describes the UK regulatory framework, the present situation, the British power system, the accommodation of embedded generation by established means, the representative model and technical innovations.

  7. Autonomous Multicamera Tracking on Embedded Smart Cameras

    Directory of Open Access Journals (Sweden)

    Bischof Horst

    2007-01-01

    Full Text Available There is currently a strong trend towards the deployment of advanced computer vision methods on embedded systems. This deployment is very challenging since embedded platforms often provide limited resources such as computing performance, memory, and power. In this paper we present a multicamera tracking method on distributed, embedded smart cameras. Smart cameras combine video sensing, processing, and communication on a single embedded device which is equipped with a multiprocessor computation and communication infrastructure. Our multicamera tracking approach focuses on a fully decentralized handover procedure between adjacent cameras. The basic idea is to initiate a single tracking instance in the multicamera system for each object of interest. The tracker follows the supervised object over the camera network, migrating to the camera which observes the object. Thus, no central coordination is required resulting in an autonomous and scalable tracking approach. We have fully implemented this novel multicamera tracking approach on our embedded smart cameras. Tracking is achieved by the well-known CamShift algorithm; the handover procedure is realized using a mobile agent system available on the smart camera network. Our approach has been successfully evaluated on tracking persons at our campus.

  8. Embedded Hyperchaotic Generators: A Comparative Analysis

    Science.gov (United States)

    Sadoudi, Said; Tanougast, Camel; Azzaz, Mohamad Salah; Dandache, Abbas

    In this paper, we present a comparative analysis of FPGA implementation performances, in terms of throughput and resources cost, of five well known autonomous continuous hyperchaotic systems. The goal of this analysis is to identify the embedded hyperchaotic generator which leads to designs with small logic area cost, satisfactory throughput rates, low power consumption and low latency required for embedded applications such as secure digital communications between embedded systems. To implement the four-dimensional (4D) chaotic systems, we use a new structural hardware architecture based on direct VHDL description of the forth order Runge-Kutta method (RK-4). The comparative analysis shows that the hyperchaotic Lorenz generator provides attractive performances compared to that of others. In fact, its hardware implementation requires only 2067 CLB-slices, 36 multipliers and no block RAMs, and achieves a throughput rate of 101.6 Mbps, at the output of the FPGA circuit, at a clock frequency of 25.315 MHz with a low latency time of 316 ns. Consequently, these good implementation performances offer to the embedded hyperchaotic Lorenz generator the advantage of being the best candidate for embedded communications applications.

  9. Embedded Web Technology: Applying World Wide Web Standards to Embedded Systems

    Science.gov (United States)

    Ponyik, Joseph G.; York, David W.

    2002-01-01

    Embedded Systems have traditionally been developed in a highly customized manner. The user interface hardware and software along with the interface to the embedded system are typically unique to the system for which they are built, resulting in extra cost to the system in terms of development time and maintenance effort. World Wide Web standards have been developed in the passed ten years with the goal of allowing servers and clients to intemperate seamlessly. The client and server systems can consist of differing hardware and software platforms but the World Wide Web standards allow them to interface without knowing about the details of system at the other end of the interface. Embedded Web Technology is the merging of Embedded Systems with the World Wide Web. Embedded Web Technology decreases the cost of developing and maintaining the user interface by allowing the user to interface to the embedded system through a web browser running on a standard personal computer. Embedded Web Technology can also be used to simplify an Embedded System's internal network.

  10. Multi-strategy based quantum cost reduction of linear nearest-neighbor quantum circuit

    Science.gov (United States)

    Tan, Ying-ying; Cheng, Xue-yun; Guan, Zhi-jin; Liu, Yang; Ma, Haiying

    2018-03-01

    With the development of reversible and quantum computing, study of reversible and quantum circuits has also developed rapidly. Due to physical constraints, most quantum circuits require quantum gates to interact on adjacent quantum bits. However, many existing quantum circuits nearest-neighbor have large quantum cost. Therefore, how to effectively reduce quantum cost is becoming a popular research topic. In this paper, we proposed multiple optimization strategies to reduce the quantum cost of the circuit, that is, we reduce quantum cost from MCT gates decomposition, nearest neighbor and circuit simplification, respectively. The experimental results show that the proposed strategies can effectively reduce the quantum cost, and the maximum optimization rate is 30.61% compared to the corresponding results.

  11. A dynamic evolutionary clustering perspective: Community detection in signed networks by reconstructing neighbor sets

    Science.gov (United States)

    Chen, Jianrui; Wang, Hua; Wang, Lina; Liu, Weiwei

    2016-04-01

    Community detection in social networks has been intensively studied in recent years. In this paper, a novel similarity measurement is defined according to social balance theory for signed networks. Inter-community positive links are found and deleted due to their low similarity. The positive neighbor sets are reconstructed by this method. Then, differential equations are proposed to imitate the constantly changing states of nodes. Each node will update its state based on the difference between its state and average state of its positive neighbors. Nodes in the same community will evolve together with time and nodes in the different communities will evolve far away. Communities are detected ultimately when states of nodes are stable. Experiments on real world and synthetic networks are implemented to verify detection performance. The thorough comparisons demonstrate the presented method is more efficient than two acknowledged better algorithms.

  12. Fusion yield rate recovery by escaping hot-spot fast ions in the neighboring fuel layer

    Science.gov (United States)

    Tang, Xian-Zhu; McDevitt, C. J.; Guo, Zehua; Berk, H. L.

    2014-02-01

    Free-streaming loss by fast ions can deplete the tail population in the hot spot of an inertial confinement fusion (ICF) target. Escaping fast ions in the neighboring fuel layer of a cryogenic target can produce a surplus of fast ions locally. In contrast to the Knudsen layer effect that reduces hot-spot fusion reactivity due to tail ion depletion, the inverse Knudsen layer effect increases fusion reactivity in the neighboring fuel layer. In the case of a burning ICF target in the presence of significant hydrodynamic mix which aggravates the Knudsen layer effect, the yield recovery largely compensates for the yield reduction. For mix-dominated sub-ignition targets, the yield reduction is the dominant process.

  13. Knowledgeable Neighbors: a mobile clinic model for disease prevention and screening in underserved communities.

    Science.gov (United States)

    Hill, Caterina; Zurakowski, David; Bennet, Jennifer; Walker-White, Rainelle; Osman, Jamie L; Quarles, Aaron; Oriol, Nancy

    2012-03-01

    The Family Van mobile health clinic uses a "Knowledgeable Neighbor" model to deliver cost-effective screening and prevention activities in underserved neighborhoods in Boston, MA. We have described the Knowledgeable Neighbor model and used operational data collected from 2006 to 2009 to evaluate the service. The Family Van successfully reached mainly minority low-income men and women. Of the clients screened, 60% had previously undetected elevated blood pressure, 14% had previously undetected elevated blood glucose, and 38% had previously undetected elevated total cholesterol. This represents an important model for reaching underserved communities to deliver proven cost-effective prevention activities, both to help control health care costs and to reduce health disparities.

  14. ANN-Benchmarks: A Benchmarking Tool for Approximate Nearest Neighbor Algorithms

    DEFF Research Database (Denmark)

    Aumüller, Martin; Bernhardsson, Erik; Faithfull, Alexander

    2017-01-01

    This paper describes ANN-Benchmarks, a tool for evaluating the performance of in-memory approximate nearest neighbor algorithms. It provides a standard interface for measuring the performance and quality achieved by nearest neighbor algorithms on different standard data sets. It supports several...... visualise these as images, Open image in new window plots, and websites with interactive plots. ANN-Benchmarks aims to provide a constantly updated overview of the current state of the art of k-NN algorithms. In the short term, this overview allows users to choose the correct k-NN algorithm and parameters...... for their similarity search task; in the longer term, algorithm designers will be able to use this overview to test and refine automatic parameter tuning. The paper gives an overview of the system, evaluates the results of the benchmark, and points out directions for future work. Interestingly, very different...

  15. Use of the neighboring orbital model for analysis of electronic coupling in Class III intervalence compounds

    International Nuclear Information System (INIS)

    Nelsen, Stephen F.; Weaver, Michael N.; Luo Yun; Lockard, Jenny V.; Zink, Jeffrey I.

    2006-01-01

    Symmetrical charge-delocalized intervalence radical ions should not be described by the traditional two-state model that has been so successful for their localized counterparts. If they lack direct overlap between their charge-bearing units (M), their diabatic orbitals have an equal energy pair of symmetrized M-centered combination orbitals that are symmetric (S) or antisymmetric (A) with respect to a symmetry element at the center of the molecule. The M combination orbitals will mix separately with bridge orbitals of the same symmetry. We call the simplest useful model for this situation the neighboring orbital model, which uses the S and A bridge orbitals of high overlap that lie closest in energy to the M orbital pair, resulting in two two-state models that have a common energy for one pair. This model is developed quantitatively, and examples having 1, 3, 5, and 7 electrons in the neighboring orbitals are illustrated

  16. Quantum Algorithm for K-Nearest Neighbors Classification Based on the Metric of Hamming Distance

    Science.gov (United States)

    Ruan, Yue; Xue, Xiling; Liu, Heng; Tan, Jianing; Li, Xi

    2017-11-01

    K-nearest neighbors (KNN) algorithm is a common algorithm used for classification, and also a sub-routine in various complicated machine learning tasks. In this paper, we presented a quantum algorithm (QKNN) for implementing this algorithm based on the metric of Hamming distance. We put forward a quantum circuit for computing Hamming distance between testing sample and each feature vector in the training set. Taking advantage of this method, we realized a good analog for classical KNN algorithm by setting a distance threshold value t to select k - n e a r e s t neighbors. As a result, QKNN achieves O( n 3) performance which is only relevant to the dimension of feature vectors and high classification accuracy, outperforms Llyod's algorithm (Lloyd et al. 2013) and Wiebe's algorithm (Wiebe et al. 2014).

  17. Isometric embeddings of 2-spheres by embedding flow for applications in numerical relativity

    International Nuclear Information System (INIS)

    Jasiulek, Michael; Korzyński, Mikołaj

    2012-01-01

    We present a numerical method for solving Weyl's embedding problem which consists in finding a global isometric embedding of a positively curved and positive-definite spherical 2-metric into the Euclidean 3-space. The method is based on a construction introduced by Weingarten and was used in Nirenberg's proof of Weyl's conjecture. The target embedding results as the endpoint of an embedding flow in R 3 beginning at the unit sphere's embedding. We employ spectral methods to handle functions on the surface and to solve various (non)linear elliptic PDEs. The code requires no additional input or steering from the operator and its convergence is guaranteed by the Nirenberg arguments. Possible applications in 3 + 1 numerical relativity range from quasi-local mass and momentum measures to coarse-graining in inhomogeneous cosmological models. (paper)

  18. Chaotic Synchronization in Nearest-Neighbor Coupled Networks of 3D CNNs

    OpenAIRE

    Serrano-Guerrero, H.; Cruz-Hernández, C.; López-Gutiérrez, R.M.; Cardoza-Avendaño, L.; Chávez-Pérez, R.A.

    2013-01-01

    In this paper, a synchronization of Cellular Neural Networks (CNNs) in nearest-neighbor coupled arrays, is numerically studied. Synchronization of multiple chaotic CNNs is achieved by appealing to complex systems theory. In particular, we consider dynamical networks composed by 3D CNNs, as interconnected nodes, where the interactions in the networks are defined by coupling the first state of each node. Four cases of interest are considered: i) synchronization without chaotic master, ii) maste...

  19. FCNN-MR: A Parallel Instance Selection Method Based on Fast Condensed Nearest Neighbor Rule

    OpenAIRE

    Lu Si; Jie Yu; Shasha Li; Jun Ma; Lei Luo; Qingbo Wu; Yongqi Ma; Zhengji Liu

    2017-01-01

    Instance selection (IS) technique is used to reduce the data size to improve the performance of data mining methods. Recently, to process very large data set, several proposed methods divide the training set into some disjoint subsets and apply IS algorithms independently to each subset. In this paper, we analyze the limitation of these methods and give our viewpoint about how to divide and conquer in IS procedure. Then, based on fast condensed nearest neighbor (FCNN) rul...

  20. Keeping up With The Neighbors: Nonproliferation and Implementation of UNSCR 1540

    Science.gov (United States)

    2016-02-15

    be respectful of the rule of law and a competitive participatory democracy , yet fail to implement UNSCR 1540, just like its neighbors. Discussion...risk-taking between 1816 and 1992. They found a strong association between conservative governmental decision-making and not only democracies , but...specifically those democracies with highly competitive political systems.46 In addition, Bruce Bueno de Mesquita, et.al. found a significant

  1. An Improvement To The k-Nearest Neighbor Classifier For ECG Database

    Science.gov (United States)

    Jaafar, Haryati; Hidayah Ramli, Nur; Nasir, Aimi Salihah Abdul

    2018-03-01

    The k nearest neighbor (kNN) is a non-parametric classifier and has been widely used for pattern classification. However, in practice, the performance of kNN often tends to fail due to the lack of information on how the samples are distributed among them. Moreover, kNN is no longer optimal when the training samples are limited. Another problem observed in kNN is regarding the weighting issues in assigning the class label before classification. Thus, to solve these limitations, a new classifier called Mahalanobis fuzzy k-nearest centroid neighbor (MFkNCN) is proposed in this study. Here, a Mahalanobis distance is applied to avoid the imbalance of samples distribition. Then, a surrounding rule is employed to obtain the nearest centroid neighbor based on the distributions of training samples and its distance to the query point. Consequently, the fuzzy membership function is employed to assign the query point to the class label which is frequently represented by the nearest centroid neighbor Experimental studies from electrocardiogram (ECG) signal is applied in this study. The classification performances are evaluated in two experimental steps i.e. different values of k and different sizes of feature dimensions. Subsequently, a comparative study of kNN, kNCN, FkNN and MFkCNN classifier is conducted to evaluate the performances of the proposed classifier. The results show that the performance of MFkNCN consistently exceeds the kNN, kNCN and FkNN with the best classification rates of 96.5%.

  2. Investment Incentives and Effective Tax Rates in the Philippines; A Comparison With Neighboring Countries

    OpenAIRE

    Alexander D Klemm; Dennis P Botman; Reza Baqir

    2008-01-01

    We compare the general tax provisions and investment incentives in the Philippines to six other east-Asian economies-Malaysia, Indonesia, Lao, Vietnam, Cambodia, and Thailand. We calculate effective tax rates and find that general effective tax rates are relatively high in the Philippines, while investment incentives are comparable to those in neighboring countries. Tax holidays are most attractive for very profitable firms, creating redundancy, and for investment in short-lived assets. We al...

  3. The Tragedy of Your Upstairs Neighbors: Is the Airbnb Negative Externality Internalized?

    OpenAIRE

    Horton, John J.

    2015-01-01

    A commonly expressed concern about the rise of the peer-to-peer rental market Airbnb is that hosts---those renting out their properties---impose costs on their unwitting neighbors. I consider the question of whether apartment building owners will, in a competitive rental market, set a building-specific Airbnb hosting policy that is socially efficient. I find that if tenants can sort across apartments based on the owners policy then the equilibrium fraction of buildings allowing Airbnb listing...

  4. Specific Protein Markers for Stem Cell Cross-Talk with Neighboring Cells in the Environment

    OpenAIRE

    Park, Kyung Soo; Shin, Seung Won; Choi, Jeong-Woo; Um, Soong Ho

    2013-01-01

    A stem cell interacts with the neighboring cells in its environment. To maintain a living organism’s metabolism, either cell-cell or cell-environment interactions may be significant. Usually, these cells communicate with each other through biological signaling by interactive behaviors of primary proteins or complementary chemicals. The signaling intermediates offer the stem cell’s functionality on its metabolism. With the rapid advent of omics technologies, various specific markers by which s...

  5. Spatially Partitioned Embedded Runge--Kutta Methods

    KAUST Repository

    Ketcheson, David I.; MacDonald, Colin B.; Ruuth, Steven J.

    2013-01-01

    We study spatially partitioned embedded Runge--Kutta (SPERK) schemes for partial differential equations (PDEs), in which each of the component schemes is applied over a different part of the spatial domain. Such methods may be convenient for problems in which the smoothness of the solution or the magnitudes of the PDE coefficients vary strongly in space. We focus on embedded partitioned methods as they offer greater efficiency and avoid the order reduction that may occur in nonembedded schemes. We demonstrate that the lack of conservation in partitioned schemes can lead to nonphysical effects and propose conservative additive schemes based on partitioning the fluxes rather than the ordinary differential equations. A variety of SPERK schemes are presented, including an embedded pair suitable for the time evolution of fifth-order weighted nonoscillatory spatial discretizations. Numerical experiments are provided to support the theory.

  6. Embedded Thermal Control for Spacecraft Subsystems Miniaturization

    Science.gov (United States)

    Didion, Jeffrey R.

    2014-01-01

    Optimization of spacecraft size, weight and power (SWaP) resources is an explicit technical priority at Goddard Space Flight Center. Embedded Thermal Control Subsystems are a promising technology with many cross cutting NSAA, DoD and commercial applications: 1.) CubeSatSmallSat spacecraft architecture, 2.) high performance computing, 3.) On-board spacecraft electronics, 4.) Power electronics and RF arrays. The Embedded Thermal Control Subsystem technology development efforts focus on component, board and enclosure level devices that will ultimately include intelligent capabilities. The presentation will discuss electric, capillary and hybrid based hardware research and development efforts at Goddard Space Flight Center. The Embedded Thermal Control Subsystem development program consists of interrelated sub-initiatives, e.g., chip component level thermal control devices, self-sensing thermal management, advanced manufactured structures. This presentation includes technical status and progress on each of these investigations. Future sub-initiatives, technical milestones and program goals will be presented.

  7. Steganographic embedding in containers-images

    Science.gov (United States)

    Nikishova, A. V.; Omelchenko, T. A.; Makedonskij, S. A.

    2018-05-01

    Steganography is one of the approaches to ensuring the protection of information transmitted over the network. But a steganographic method should vary depending on a used container. According to statistics, the most widely used containers are images and the most common image format is JPEG. Authors propose a method of data embedding into a frequency area of images in format JPEG 2000. It is proposed to use the method of Benham-Memon- Yeo-Yeung, in which instead of discrete cosine transform, discrete wavelet transform is used. Two requirements for images are formulated. Structure similarity is chosen to obtain quality assessment of data embedding. Experiments confirm that requirements satisfaction allows achieving high quality assessment of data embedding.

  8. Spatially Partitioned Embedded Runge--Kutta Methods

    KAUST Repository

    Ketcheson, David I.

    2013-10-30

    We study spatially partitioned embedded Runge--Kutta (SPERK) schemes for partial differential equations (PDEs), in which each of the component schemes is applied over a different part of the spatial domain. Such methods may be convenient for problems in which the smoothness of the solution or the magnitudes of the PDE coefficients vary strongly in space. We focus on embedded partitioned methods as they offer greater efficiency and avoid the order reduction that may occur in nonembedded schemes. We demonstrate that the lack of conservation in partitioned schemes can lead to nonphysical effects and propose conservative additive schemes based on partitioning the fluxes rather than the ordinary differential equations. A variety of SPERK schemes are presented, including an embedded pair suitable for the time evolution of fifth-order weighted nonoscillatory spatial discretizations. Numerical experiments are provided to support the theory.

  9. Embedded fiber optic ultrasonic sensors and generators

    Science.gov (United States)

    Dorighi, John F.; Krishnaswamy, Sridhar; Achenbach, Jan D.

    1995-04-01

    Ultrasonic sensors and generators based on fiber-optic systems are described. It is shown that intrinsic fiber optic Fabry-Perot ultrasound sensors that are embedded in a structure can be stabilized by actively tuning the laser frequency. The need for this method of stabilization is demonstrated by detecting piezoelectric transducer-generated ultrasonic pulses in the presence of low frequency dynamic strains that are intentionally induced to cause sensor drift. The actively stabilized embedded fiber optic Fabry-Perot sensor is also shown to have sufficient sensitivity to detect ultrasound that is generated in the interior of a structure by means of a high-power optical fiber that pipes energy from a pulsed laser to an embedded generator of ultrasound.

  10. Embedded and real-time operating systems

    CERN Document Server

    Wang, K C

    2017-01-01

    This book covers the basic concepts and principles of operating systems, showing how to apply them to the design and implementation of complete operating systems for embedded and real-time systems. It includes all the foundational and background information on ARM architecture, ARM instructions and programming, toolchain for developing programs, virtual machines for software implementation and testing, program execution image, function call conventions, run-time stack usage and link C programs with assembly code. It describes the design and implementation of a complete OS for embedded systems in incremental steps, explaining the design principles and implementation techniques. For Symmetric Multiprocessing (SMP) embedded systems, the author examines the ARM MPcore processors, which include the SCU and GIC for interrupts routing and interprocessor communication and synchronization by Software Generated Interrupts (SGIs). Throughout the book, complete working sample systems demonstrate the design principles and...

  11. Design Technology for Heterogeneous Embedded Systems

    CERN Document Server

    O'Connor, Ian; Piguet, Christian

    2012-01-01

    Designing technology to address the problem of heterogeneous embedded systems, while remaining compatible with standard “More Moore” flows, i.e. capable of handling simultaneously both silicon complexity and system complexity, represents one of the most important challenges facing the semiconductor industry today. While the micro-electronics industry has built its own specific design methods to focus mainly on the management of complexity through the establishment of abstraction levels, the emergence of device heterogeneity requires new approaches enabling the satisfactory design of physically heterogeneous embedded systems for the widespread deployment of such systems. This book, compiled largely from a set of contributions from participants of past editions of the Winter School on Heterogeneous Embedded Systems Design Technology (FETCH), proposes a broad and holistic overview of design techniques used to tackle the various facets of heterogeneity in terms of technology and opportunities at the physical ...

  12. Dynamic memory management for embedded systems

    CERN Document Server

    Atienza Alonso, David; Poucet, Christophe; Peón-Quirós, Miguel; Bartzas, Alexandros; Catthoor, Francky; Soudris, Dimitrios

    2015-01-01

    This book provides a systematic and unified methodology, including basic principles and reusable processes, for dynamic memory management (DMM) in embedded systems.  The authors describe in detail how to design and optimize the use of dynamic memory in modern, multimedia and network applications, targeting the latest generation of portable embedded systems, such as smartphones. Coverage includes a variety of design and optimization topics in electronic design automation of DMM, from high-level software optimization to microarchitecture-level hardware support. The authors describe the design of multi-layer dynamic data structures for the final memory hierarchy layers of the target portable embedded systems and how to create a low-fragmentation, cost-efficient, dynamic memory management subsystem out of configurable components for the particular memory allocation and de-allocation patterns for each type of application.  The design methodology described in this book is based on propagating constraints among de...

  13. Laser assisted embedding of nanoparticles into metallic materials

    International Nuclear Information System (INIS)

    Lin Dong; Suslov, Sergey; Ye Chang; Liao Yiliang; Liu, C. Richard; Cheng, Gary J.

    2012-01-01

    This paper reports a methodology of half-embedding nanoparticles into metallic materials. Transparent and opaque nanoparticles are chosen to demonstrate the process of laser assisted nanoparticle embedding. Dip coating method is used to coat transparent or opaque nanoparticle on the surface of metallic material. Nanoparticles are embedded into substrate by laser irradiation. In this study, the mechanism and process of nanoparticle embedding are investigated. It is found both transparent and opaque nanoparticles embedding are with high densities and good uniformities.

  14. A Hybrid Instance Selection Using Nearest-Neighbor for Cross-Project Defect Prediction

    Institute of Scientific and Technical Information of China (English)

    Duksan Ryu; Jong-In Jang; Jongmoon Baik; Member; ACM; IEEE

    2015-01-01

    Software defect prediction (SDP) is an active research field in software engineering to identify defect-prone modules. Thanks to SDP, limited testing resources can be effectively allocated to defect-prone modules. Although SDP requires suffcient local data within a company, there are cases where local data are not available, e.g., pilot projects. Companies without local data can employ cross-project defect prediction (CPDP) using external data to build classifiers. The major challenge of CPDP is different distributions between training and test data. To tackle this, instances of source data similar to target data are selected to build classifiers. Software datasets have a class imbalance problem meaning the ratio of defective class to clean class is far low. It usually lowers the performance of classifiers. We propose a Hybrid Instance Selection Using Nearest-Neighbor (HISNN) method that performs a hybrid classification selectively learning local knowledge (via k-nearest neighbor) and global knowledge (via na¨ıve Bayes). Instances having strong local knowledge are identified via nearest-neighbors with the same class label. Previous studies showed low PD (probability of detection) or high PF (probability of false alarm) which is impractical to use. The experimental results show that HISNN produces high overall performance as well as high PD and low PF.

  15. Who's your neighbor? Acoustic cues to individual identity in red squirrel Tamiasciurus hudsonicus rattle calls

    Directory of Open Access Journals (Sweden)

    Shannon M. DIGWEED, Drew RENDALL, Teana IMBEAU

    2012-10-01

    Full Text Available North American red squirrels Tamiasciurus hudsonicus often produce a loud territorial rattle call when conspecifics enter or invade a territory. Previous playback experiments suggest that the territorial rattle call may indicate an invader's identity as squirrels responded more intensely to calls played from strangers than to calls played from neighbors. This dear-enemy effect is well known in a variety of bird and mammal species and functions to reduce aggressive interactions between known neighbors. However, although previous experiments on red squirrels suggest some form of individual differentiation and thus recognition, detailed acoustic analysis of potential acoustic cues in rattle calls have not been conducted. If calls function to aid in conspecific identification in order to mitigate aggressive territorial interactions, we would expect that individual recognition cues would be acoustically represented. Our work provides a detailed analysis of acoustic cues to identity within rattle calls. A total of 225 calls across 32 individual squirrels from Sheep River Provincial Park, Kananaskis, AB, Canada, were analyzed with discriminant function analysis for potential acoustic cues to individual identity. Initial analysis of all individuals revealed a reliable acoustic differentiation across individuals. A more detailed analysis of clusters of neighboring squirrels was performed and results again indicated a statistically significant likelihood that calls were assigned correctly to specific squirrels (55%-75% correctly assigned; in other words squirrels have distinct voices that should allow for individual identification and discrimination by conspecifics [Current Zoology 58 (5: 758–764, 2012].

  16. Multidimensional k-nearest neighbor model based on EEMD for financial time series forecasting

    Science.gov (United States)

    Zhang, Ningning; Lin, Aijing; Shang, Pengjian

    2017-07-01

    In this paper, we propose a new two-stage methodology that combines the ensemble empirical mode decomposition (EEMD) with multidimensional k-nearest neighbor model (MKNN) in order to forecast the closing price and high price of the stocks simultaneously. The modified algorithm of k-nearest neighbors (KNN) has an increasingly wide application in the prediction of all fields. Empirical mode decomposition (EMD) decomposes a nonlinear and non-stationary signal into a series of intrinsic mode functions (IMFs), however, it cannot reveal characteristic information of the signal with much accuracy as a result of mode mixing. So ensemble empirical mode decomposition (EEMD), an improved method of EMD, is presented to resolve the weaknesses of EMD by adding white noise to the original data. With EEMD, the components with true physical meaning can be extracted from the time series. Utilizing the advantage of EEMD and MKNN, the new proposed ensemble empirical mode decomposition combined with multidimensional k-nearest neighbor model (EEMD-MKNN) has high predictive precision for short-term forecasting. Moreover, we extend this methodology to the case of two-dimensions to forecast the closing price and high price of the four stocks (NAS, S&P500, DJI and STI stock indices) at the same time. The results indicate that the proposed EEMD-MKNN model has a higher forecast precision than EMD-KNN, KNN method and ARIMA.

  17. Resampling nucleotide sequences with closest-neighbor trimming and its comparison to other methods.

    Directory of Open Access Journals (Sweden)

    Kouki Yonezawa

    Full Text Available A large number of nucleotide sequences of various pathogens are available in public databases. The growth of the datasets has resulted in an enormous increase in computational costs. Moreover, due to differences in surveillance activities, the number of sequences found in databases varies from one country to another and from year to year. Therefore, it is important to study resampling methods to reduce the sampling bias. A novel algorithm-called the closest-neighbor trimming method-that resamples a given number of sequences from a large nucleotide sequence dataset was proposed. The performance of the proposed algorithm was compared with other algorithms by using the nucleotide sequences of human H3N2 influenza viruses. We compared the closest-neighbor trimming method with the naive hierarchical clustering algorithm and [Formula: see text]-medoids clustering algorithm. Genetic information accumulated in public databases contains sampling bias. The closest-neighbor trimming method can thin out densely sampled sequences from a given dataset. Since nucleotide sequences are among the most widely used materials for life sciences, we anticipate that our algorithm to various datasets will result in reducing sampling bias.

  18. Equivalent charge source model based iterative maximum neighbor weight for sparse EEG source localization.

    Science.gov (United States)

    Xu, Peng; Tian, Yin; Lei, Xu; Hu, Xiao; Yao, Dezhong

    2008-12-01

    How to localize the neural electric activities within brain effectively and precisely from the scalp electroencephalogram (EEG) recordings is a critical issue for current study in clinical neurology and cognitive neuroscience. In this paper, based on the charge source model and the iterative re-weighted strategy, proposed is a new maximum neighbor weight based iterative sparse source imaging method, termed as CMOSS (Charge source model based Maximum neighbOr weight Sparse Solution). Different from the weight used in focal underdetermined system solver (FOCUSS) where the weight for each point in the discrete solution space is independently updated in iterations, the new designed weight for each point in each iteration is determined by the source solution of the last iteration at both the point and its neighbors. Using such a new weight, the next iteration may have a bigger chance to rectify the local source location bias existed in the previous iteration solution. The simulation studies with comparison to FOCUSS and LORETA for various source configurations were conducted on a realistic 3-shell head model, and the results confirmed the validation of CMOSS for sparse EEG source localization. Finally, CMOSS was applied to localize sources elicited in a visual stimuli experiment, and the result was consistent with those source areas involved in visual processing reported in previous studies.

  19. Classification of EEG Signals using adaptive weighted distance nearest neighbor algorithm

    Directory of Open Access Journals (Sweden)

    E. Parvinnia

    2014-01-01

    Full Text Available Electroencephalogram (EEG signals are often used to diagnose diseases such as seizure, alzheimer, and schizophrenia. One main problem with the recorded EEG samples is that they are not equally reliable due to the artifacts at the time of recording. EEG signal classification algorithms should have a mechanism to handle this issue. It seems that using adaptive classifiers can be useful for the biological signals such as EEG. In this paper, a general adaptive method named weighted distance nearest neighbor (WDNN is applied for EEG signal classification to tackle this problem. This classification algorithm assigns a weight to each training sample to control its influence in classifying test samples. The weights of training samples are used to find the nearest neighbor of an input query pattern. To assess the performance of this scheme, EEG signals of thirteen schizophrenic patients and eighteen normal subjects are analyzed for the classification of these two groups. Several features including, fractal dimension, band power and autoregressive (AR model are extracted from EEG signals. The classification results are evaluated using Leave one (subject out cross validation for reliable estimation. The results indicate that combination of WDNN and selected features can significantly outperform the basic nearest-neighbor and the other methods proposed in the past for the classification of these two groups. Therefore, this method can be a complementary tool for specialists to distinguish schizophrenia disorder.

  20. Local and neighboring patch conditions alter sex-specific movement in banana weevils.

    Science.gov (United States)

    Carval, Dominique; Perrin, Benjamin; Duyck, Pierre-François; Tixier, Philippe

    2015-12-01

    Understanding the mechanisms underlying the movements and spread of a species over time and space is a major concern of ecology. Here, we assessed the effects of an individual's sex and the density and sex ratio of conspecifics in the local and neighboring environment on the movement probability of the banana weevil, Cosmopolites sordidus. In a "two patches" experiment, we used radiofrequency identification tags to study the C. sordidus movement response to patch conditions. We showed that local and neighboring densities of conspecifics affect the movement rates of individuals but that the density-dependent effect can be either positive or negative depending on the relative densities of conspecifics in local and neighboring patches. We demonstrated that sex ratio also influences the movement of C. sordidus, that is, the weevil exhibits nonfixed sex-biased movement strategies. Sex-biased movement may be the consequence of intrasexual competition for resources (i.e., oviposition sites) in females and for mates in males. We also detected a high individual variability in the propensity to move. Finally, we discuss the role of demographic stochasticity, sex-biased movement, and individual heterogeneity in movement on the colonization process.

  1. Cultural macroevolution on neighbor graphs : vertical and horizontal transmission among Western North American Indian societies.

    Science.gov (United States)

    Towner, Mary C; Grote, Mark N; Venti, Jay; Borgerhoff Mulder, Monique

    2012-09-01

    What are the driving forces of cultural macroevolution, the evolution of cultural traits that characterize societies or populations? This question has engaged anthropologists for more than a century, with little consensus regarding the answer. We develop and fit autologistic models, built upon both spatial and linguistic neighbor graphs, for 44 cultural traits of 172 societies in the Western North American Indian (WNAI) database. For each trait, we compare models including or excluding one or both neighbor graphs, and for the majority of traits we find strong evidence in favor of a model which uses both spatial and linguistic neighbors to predict a trait's distribution. Our results run counter to the assertion that cultural trait distributions can be explained largely by the transmission of traits from parent to daughter populations and are thus best analyzed with phylogenies. In contrast, we show that vertical and horizontal transmission pathways can be incorporated in a single model, that both transmission modes may indeed operate on the same trait, and that for most traits in the WNAI database, accounting for only one mode of transmission would result in a loss of information.

  2. Protein function prediction using neighbor relativity in protein-protein interaction network.

    Science.gov (United States)

    Moosavi, Sobhan; Rahgozar, Masoud; Rahimi, Amir

    2013-04-01

    There is a large gap between the number of discovered proteins and the number of functionally annotated ones. Due to the high cost of determining protein function by wet-lab research, function prediction has become a major task for computational biology and bioinformatics. Some researches utilize the proteins interaction information to predict function for un-annotated proteins. In this paper, we propose a novel approach called "Neighbor Relativity Coefficient" (NRC) based on interaction network topology which estimates the functional similarity between two proteins. NRC is calculated for each pair of proteins based on their graph-based features including distance, common neighbors and the number of paths between them. In order to ascribe function to an un-annotated protein, NRC estimates a weight for each neighbor to transfer its annotation to the unknown protein. Finally, the unknown protein will be annotated by the top score transferred functions. We also investigate the effect of using different coefficients for various types of functions. The proposed method has been evaluated on Saccharomyces cerevisiae and Homo sapiens interaction networks. The performance analysis demonstrates that NRC yields better results in comparison with previous protein function prediction approaches that utilize interaction network. Copyright © 2012 Elsevier Ltd. All rights reserved.

  3. A new approach to very short term wind speed prediction using k-nearest neighbor classification

    International Nuclear Information System (INIS)

    Yesilbudak, Mehmet; Sagiroglu, Seref; Colak, Ilhami

    2013-01-01

    Highlights: ► Wind speed parameter was predicted in an n-tupled inputs using k-NN classification. ► The effects of input parameters, nearest neighbors and distance metrics were analyzed. ► Many useful and reasonable inferences were uncovered using the developed model. - Abstract: Wind energy is an inexhaustible energy source and wind power production has been growing rapidly in recent years. However, wind power has a non-schedulable nature due to wind speed variations. Hence, wind speed prediction is an indispensable requirement for power system operators. This paper predicts wind speed parameter in an n-tupled inputs using k-nearest neighbor (k-NN) classification and analyzes the effects of input parameters, nearest neighbors and distance metrics on wind speed prediction. The k-NN classification model was developed using the object oriented programming techniques and includes Manhattan and Minkowski distance metrics except from Euclidean distance metric on the contrary of literature. The k-NN classification model which uses wind direction, air temperature, atmospheric pressure and relative humidity parameters in a 4-tupled space achieved the best wind speed prediction for k = 5 in the Manhattan distance metric. Differently, the k-NN classification model which uses wind direction, air temperature and atmospheric pressure parameters in a 3-tupled inputs gave the worst wind speed prediction for k = 1 in the Minkowski distance metric

  4. Feasibility study on embedded transport core calculations

    International Nuclear Information System (INIS)

    Ivanov, B.; Zikatanov, L.; Ivanov, K.

    2007-01-01

    The main objective of this study is to develop an advanced core calculation methodology based on embedded diffusion and transport calculations. The scheme proposed in this work is based on embedded diffusion or SP 3 pin-by-pin local fuel assembly calculation within the framework of the Nodal Expansion Method (NEM) diffusion core calculation. The SP 3 method has gained popularity in the last 10 years as an advanced method for neutronics calculation. NEM is a multi-group nodal diffusion code developed, maintained and continuously improved at the Pennsylvania State University. The developed calculation scheme is a non-linear iteration process, which involves cross-section homogenization, on-line discontinuity factors generation, and boundary conditions evaluation by the global solution passed to the local calculation. In order to accomplish the local calculation, a new code has been developed based on the Finite Elements Method (FEM), which is capable of performing both diffusion and SP 3 calculations. The new code will be used in the framework of the NEM code in order to perform embedded pin-by-pin diffusion and SP 3 calculations on fuel assembly basis. The development of the diffusion and SP 3 FEM code is presented first following by its application to several problems. Description of the proposed embedded scheme is provided next as well as the obtained preliminary results of the C3 MOX benchmark. The results from the embedded calculations are compared with direct pin-by-pin whole core calculations in terms of accuracy and efficiency followed by conclusions made about the feasibility of the proposed embedded approach. (authors)

  5. The art of programming embedded systems

    CERN Document Server

    Ganssle, Jack

    1992-01-01

    Embedded systems are products such as microwave ovens, cars, and toys that rely on an internal microprocessor. This book is oriented toward the design engineer or programmer who writes the computer code for such a system. There are a number of problems specific to the embedded systems designer, and this book addresses them and offers practical solutions.Key Features* Offers cookbook routines, algorithms, and design techniques* Includes tips for handling debugging management and testing* Explores the philosophy of tightly coupling software and hardware in programming and dev

  6. Tools for Embedded Computing Systems Software

    Science.gov (United States)

    1978-01-01

    A workshop was held to assess the state of tools for embedded systems software and to determine directions for tool development. A synopsis of the talk and the key figures of each workshop presentation, together with chairmen summaries, are presented. The presentations covered four major areas: (1) tools and the software environment (development and testing); (2) tools and software requirements, design, and specification; (3) tools and language processors; and (4) tools and verification and validation (analysis and testing). The utility and contribution of existing tools and research results for the development and testing of embedded computing systems software are described and assessed.

  7. Modern system architectures in embedded systems

    International Nuclear Information System (INIS)

    Korhonen, T.

    2012-01-01

    Several new technologies are making their way also in embedded systems. In addition to the FPGA technology which has become commonplace, multi-core CPUs and I/O virtualization (the implementation of the tasks of a software hyper-visor in hardware to improve the efficiency) are being introduced to the embedded systems. In this paper we review the trends and discuss how to take advantage of these features in control systems. Some potential application examples like parallelization, data streaming, high-speed data acquisition and virtualization are discussed

  8. Model-based testing for embedded systems

    CERN Document Server

    Zander, Justyna; Mosterman, Pieter J

    2011-01-01

    What the experts have to say about Model-Based Testing for Embedded Systems: "This book is exactly what is needed at the exact right time in this fast-growing area. From its beginnings over 10 years ago of deriving tests from UML statecharts, model-based testing has matured into a topic with both breadth and depth. Testing embedded systems is a natural application of MBT, and this book hits the nail exactly on the head. Numerous topics are presented clearly, thoroughly, and concisely in this cutting-edge book. The authors are world-class leading experts in this area and teach us well-used

  9. Communicating embedded systems software and design

    CERN Document Server

    Jard, Claude

    2013-01-01

    The increased complexity of embedded systems coupled with quick design cycles to accommodate faster time-to-market requires increased system design productivity that involves both model-based design and tool-supported methodologies. Formal methods are mathematically-based techniques and provide a clean framework in which to express requirements and models of the systems, taking into account discrete, stochastic and continuous (timed or hybrid) parameters with increasingly efficient tools. This book deals with these formal methods applied to communicating embedded systems by presenting the

  10. Microring embedded hollow polymer fiber laser

    Energy Technology Data Exchange (ETDEWEB)

    Linslal, C. L., E-mail: linslal@gmail.com; Sebastian, S.; Mathew, S.; Radhakrishnan, P.; Nampoori, V. P. N.; Girijavallabhan, C. P.; Kailasnath, M. [International School of Photonics, Cochin University of Science and Technology, Cochin 22 (India)

    2015-03-30

    Strongly modulated laser emission has been observed from rhodamine B doped microring resonator embedded in a hollow polymer optical fiber by transverse optical pumping. The microring resonator is fabricated on the inner wall of a hollow polymer fiber. Highly sharp lasing lines, strong mode selection, and a collimated laser beam are observed from the fiber. Nearly single mode lasing with a side mode suppression ratio of up to 11.8 dB is obtained from the strongly modulated lasing spectrum. The microring embedded hollow polymer fiber laser has shown efficient lasing characteristics even at a propagation length of 1.5 m.

  11. Belowground neighbor perception in Arabidopsis thaliana studied by transcriptome analysis: roots of Hieracium pilosella cause biotic stress

    Directory of Open Access Journals (Sweden)

    Christoph eSchmid

    2013-08-01

    Full Text Available Root-root interactions are much more sophisticated than previously thought, yet the mechanisms of belowground neighbor perception remain largely obscure. Genome-wide transcriptome analyses allow detailed insight into plant reactions to environmental cues.A root interaction trial was set up to explore both morphological and whole genome transcriptional responses in roots of Arabidopsis thaliana in the presence or absence of an inferior competitor, Hieracium pilosella.Neighbor perception was indicated by Arabidopsis roots predominantly growing away from the neighbor (segregation, while solitary plants placed more roots towards the middle of the pot. Total biomass remained unaffected. Database comparisons in transcriptome analysis revealed considerable similarity between Arabidopsis root reactions to neighbors and reactions to pathogens. Detailed analyses of the functional category ‘biotic stress’ using MapMan tools found the sub-category ‘pathogenesis-related proteins’ highly significantly induced. A comparison to a study on intraspecific competition brought forward a core of genes consistently involved in reactions to neighbor roots.We conclude that beyond resource depletion roots perceive neighboring roots or their associated microorganisms by a relatively uniform mechanism that involves the strong induction of pathogenesis-related proteins. In an ecological context the findings reveal that belowground neighbor detection may occur independently of resource depletion, allowing for a time advantage for the root to prepare for potential interactions.

  12. Views on Evolvability of Embedded Systems

    NARCIS (Netherlands)

    Laar, P. van de; Punter, T.

    2011-01-01

    Evolvability, the ability to respond effectively to change, represents a major challenge to today's high-end embedded systems, such as those developed in the medical domain by Philips Healthcare. These systems are typically developed by multi-disciplinary teams, located around the world, and are in

  13. Views on evolvability of embedded systems

    NARCIS (Netherlands)

    Laar, van de P.J.L.J.; Punter, H.T.

    2011-01-01

    Evolvability, the ability to respond effectively to change, represents a major challenge to today's high-end embedded systems, such as those developed in the medical domain by Philips Healthcare. These systems are typically developed by multi-disciplinary teams, located around the world, and are in

  14. Embedded high-contrast distributed grating structures

    Science.gov (United States)

    Zubrzycki, Walter J.; Vawter, Gregory A.; Allerman, Andrew A.

    2002-01-01

    A new class of fabrication methods for embedded distributed grating structures is claimed, together with optical devices which include such structures. These new methods are the only known approach to making defect-free high-dielectric contrast grating structures, which are smaller and more efficient than are conventional grating structures.

  15. Carcinogenicity of Embedded Tungsten Alloys in Mice

    Science.gov (United States)

    2011-03-01

    formation as a result of embedded metal from a lawn mower blade (Saruwatari et al. 2009) and a chain saw blade (Osawa et al. 2006), respectively. In both...granuloma attributable to a piece of lawn - mower blade. Clin Exp Dermatol 34:e268–e269 Schins RP, Borm PJ (1999) Mechanisms and mediators in coal dust induced

  16. The polarizable embedding coupled cluster method

    DEFF Research Database (Denmark)

    Sneskov, Kristian; Schwabe, Tobias; Kongsted, Jacob

    2011-01-01

    We formulate a new combined quantum mechanics/molecular mechanics (QM/MM) method based on a self-consistent polarizable embedding (PE) scheme. For the description of the QM region, we apply the popular coupled cluster (CC) method detailing the inclusion of electrostatic and polarization effects...

  17. Flash memory in embedded Java programs

    DEFF Research Database (Denmark)

    Korsholm, Stephan Erbs

    This paper introduces a Java execution environment with the capability for storing constant heap data in Flash, thus saving valuable RAM. The extension is motivated by the structure of three industrial applications which demonstrate the need for storing constant data in Flash on small embedded...

  18. Are Central European countries’ financial institutions embedded?

    NARCIS (Netherlands)

    Jong, E. de; Hooijdonk, C.J.J. van

    2010-01-01

    The fall of the Iron Curtain in 1989 was one of the causes of an increased interest in the relation between economics and culture. An important idea of this literature is that social and economic systems will function properly if they are embedded in a corresponding value system. Although some

  19. Embedding complex objects with 3d printing

    KAUST Repository

    Hussain, Muhammad Mustafa; Diaz, Cordero Marlon Steven

    2017-01-01

    A CMOS technology-compatible fabrication process for flexible CMOS electronics embedded during additive manufacturing (i.e. 3D printing). A method for such a process may include printing a first portion of a 3D structure; pausing the step

  20. Embedded Critique in a Tensed World

    DEFF Research Database (Denmark)

    Hansen, Ejvind

    2006-01-01

    , it is probably best not to criticize at all. I argue that this reaction is wrong. Descriptivism does on the one hand not solve the problem from which it originates: the description is itself embedded in a contingent validity. The postmodern insight does on the other hand not necessarily lead to absolute...

  1. Web Service Architecture Framework for Embedded Devices

    Science.gov (United States)

    Yanzick, Paul David

    2009-01-01

    The use of Service Oriented Architectures, namely web services, has become a widely adopted method for transfer of data between systems across the Internet as well as the Enterprise. Adopting a similar approach to embedded devices is also starting to emerge as personal devices and sensor networks are becoming more common in the industry. This…

  2. The Embedding Theorems of Whitney and Nash

    Indian Academy of Sciences (India)

    IAS Admin

    We begin by briefly motivating the idea of a manifold and then discuss the embedding the- orems of Whitney and Nash that allow us to view these objects inside appropriately large Eu- clidean spaces. 1. Introduction. Let us begin by motivating the concept of a manifold. Start with the unit circle C in the plane given by x2.

  3. The Embedded Character of Workplace Relations.

    Science.gov (United States)

    Frenkel, Stephen J.

    2003-01-01

    The workplace is embedded in three force fields: the macro field of globalization/technology, the meso field of transnational production networks, and the micro field of local labor markets and organizations. Each field influences the way flexibility and cost reduction are prioritized and has consequences for workplace structures and relations.…

  4. Dealing with dynamism in embedded system design

    NARCIS (Netherlands)

    Gheorghita, S.V.

    2007-01-01

    In the past decade, real-time embedded systems became more and more complex and pervasive. From the user perspective, these systems have stringent requirements regarding size, performance and energy consumption, and due to business competition, their time-to-market is a crucial factor. Besides these

  5. Structure Map for Embedded Binary Alloy Nanocrystals

    Energy Technology Data Exchange (ETDEWEB)

    Yuan, C.W.; Shin, S.J.; Liao, C.Y.; Guzman, J.; Stone, P.R.; Watanabe, M.; Ager III, J.W.; Haller, E.E.; Chrzan, D.C.

    2008-09-20

    The equilibrium structure of embedded nanocrystals formed from strongly segregating binary-alloys is considered within a simple thermodynamic model. The model identifies two dimensionlessinterface energies that dictate the structure, and allows prediction of the stable structure for anychoice of these parameters. The resulting structure map includes three distinct nanocrystal mor-phologies: core/shell, lobe/lobe, and completely separated spheres.

  6. EMBEDDED MARKETING AND THE QUALITY-QUANTITY ...

    African Journals Online (AJOL)

    NGOZI

    This paper discusses how embedded marketing can be harnessed to yield additional .... to the school of thought that look at film as nothing short of a lucrative ..... Awaeze, C.C.& Nworgu, K.O. “History of Motion Pictures and. Film Criticism “ In ...

  7. Singular interactions supported by embedded curves

    International Nuclear Information System (INIS)

    Kaynak, Burak Tevfik; Turgut, O Teoman

    2012-01-01

    In this work, singular interactions supported by embedded curves on Riemannian manifolds are discussed from a more direct and physical perspective, via the heat kernel approach. We show that the renormalized problem is well defined, the ground state is finite and the corresponding wavefunction is positive. The renormalization group invariance of the model is also discussed. (paper)

  8. The Embedding Theorems of Whitney and Nash

    Indian Academy of Sciences (India)

    We begin by briefly motivating the idea of amanifold and then discuss the embedding theorems of Whitney and Nash that allow us toview these objects inside appropriately large Euclidean spaces. Resonance – Journal of Science Education. Current Issue : Vol. 23, Issue 4. Current Issue Volume 23 | Issue 4. April 2018.

  9. Embedding Multiple Literacies into STEM Curricula

    Science.gov (United States)

    Soules, Aline; Nielsen, Sarah; LeDuc, Danika; Inouye, Caron; Singley, Jason; Wildy, Erica; Seitz, Jeff

    2014-01-01

    In fall 2012, an interdisciplinary team of science, English, and library faculty embedded reading, writing, and information literacy strategies in Science, Technology, Engineering, and Mathematics (STEM) curricula as a first step in improving student learning and retention in science courses and aligning them with the Next Generation Science and…

  10. Concurrent Design of Embedded Control Software

    NARCIS (Netherlands)

    Groothuis, M.A.; Frijns, Raymond; Voeten, Jeroen; Broenink, Johannes F.; Margaria, T.; Padberg, J.; Taentzer, G.; Levendovszky, T.; Lengyel, L.; Karsai, G.; Hardebolle, C.

    2009-01-01

    Embedded software design for mechatronic systems is becoming an increasingly time-consuming and error-prone task. In order to cope with the heterogeneity and complexity, a systematic model-driven design approach is needed, where several parts of the system can be designed concurrently. There is

  11. Integrated Design Tools for Embedded Control Systems

    NARCIS (Netherlands)

    Jovanovic, D.S.; Hilderink, G.H.; Broenink, Johannes F.; Karelse, F.

    2001-01-01

    Currently, computer-based control systems are still being implemented using the same techniques as 10 years ago. The purpose of this project is the development of a design framework, consisting of tools and libraries, which allows the designer to build high reliable heterogeneous real-time embedded

  12. Reusing knowledge in embedded system modelling

    NARCIS (Netherlands)

    Marincic, J.; Mader, Angelika H.; Wieringa, Roelf J.; Lucas, Yan

    Model-based design is a promising technique to improve the quality of software and the efficiency of the software development process. We are investigating how to efficiently model embedded software and its environment to verify the requirements for the system controlled by the software. The

  13. LC Circuits for Diagnosing Embedded Piezoelectric Devices

    Science.gov (United States)

    Chattin, Richard L.; Fox, Robert Lee; Moses, Robert W.; Shams, Qamar A.

    2005-01-01

    A recently invented method of nonintrusively detecting faults in piezoelectric devices involves measurement of the resonance frequencies of inductor capacitor (LC) resonant circuits. The method is intended especially to enable diagnosis of piezoelectric sensors, actuators, and sensor/actuators that are embedded in structures and/or are components of multilayer composite material structures.

  14. Pixels to Graphs by Associative Embedding

    KAUST Repository

    Newell, Alejandro; Deng, Jia

    2017-01-01

    network such that it takes in an input image and produces a full graph. This is done end-to-end in a single stage with the use of associative embeddings. The network learns to simultaneously identify all of the elements that make up a graph and piece them

  15. Simultaneous embedding: edge orderings, relative positions, cutvertices

    NARCIS (Netherlands)

    Bläsius, T.; Karrer, A.; Rutter, I.

    A simultaneous embedding (with fixed edges) of two graphs (Formula presented.) and (Formula presented.) with common graph (Formula presented.) is a pair of planar drawings of (Formula presented.) and (Formula presented.) that coincide on G. It is an open question whether there is a polynomial-time

  16. Polarizable Density Embedding Coupled Cluster Method

    DEFF Research Database (Denmark)

    Hršak, Dalibor; Olsen, Jógvan Magnus Haugaard; Kongsted, Jacob

    2018-01-01

    by an embedding potential consisting of a set of fragment densities obtained from calculations on isolated fragments with a quantum-chemistry method such as Hartree-Fock (HF) or Kohn-Sham density functional theory (KS-DFT) and dressed with a set of atom-centered anisotropic dipole-dipole polarizabilities...

  17. Excited States in Solution through Polarizable Embedding

    DEFF Research Database (Denmark)

    Olsen, Jógvan Magnus; Aidas, Kestutis; Kongsted, Jacob

    2010-01-01

    mechanical calculation. The polarizable embedding potential is described by an atomistic representation including terms up to localized octupoles and anisotropic polarizabilities. It is generally applicable to any quantum chemical description but is here implemented for the case of Kohn−Sham density...

  18. On Verification Modelling of Embedded Systems

    NARCIS (Netherlands)

    Brinksma, Hendrik; Mader, Angelika H.

    Computer-aided verification of embedded systems hinges on the availability of good verification models of the systems at hand. Such models must be much simpler than full design models or specifications to be of practical value, because of the unavoidable combinatorial complexities in the

  19. Is Embedded Librarianship Right for Your Institution?

    Science.gov (United States)

    Muir, Gordon; Heller-Ross, Holly

    2010-01-01

    Embedded librarians, connected with students and faculty inside the classroom, lab and studio, have new opportunities for preparing students for research and for collaborating with faculty on course-integrated information literacy, research assignment design, teaching, assignment interpretation, and timely student assistance. What makes embedded…

  20. Feature-based component model for design of embedded systems

    Science.gov (United States)

    Zha, Xuan Fang; Sriram, Ram D.

    2004-11-01

    An embedded system is a hybrid of hardware and software, which combines software's flexibility and hardware real-time performance. Embedded systems can be considered as assemblies of hardware and software components. An Open Embedded System Model (OESM) is currently being developed at NIST to provide a standard representation and exchange protocol for embedded systems and system-level design, simulation, and testing information. This paper proposes an approach to representing an embedded system feature-based model in OESM, i.e., Open Embedded System Feature Model (OESFM), addressing models of embedded system artifacts, embedded system components, embedded system features, and embedded system configuration/assembly. The approach provides an object-oriented UML (Unified Modeling Language) representation for the embedded system feature model and defines an extension to the NIST Core Product Model. The model provides a feature-based component framework allowing the designer to develop a virtual embedded system prototype through assembling virtual components. The framework not only provides a formal precise model of the embedded system prototype but also offers the possibility of designing variation of prototypes whose members are derived by changing certain virtual components with different features. A case study example is discussed to illustrate the embedded system model.

  1. Fast and effective embedded systems design applying the ARM mbed

    CERN Document Server

    Toulson, Rob

    2012-01-01

    A hands-on introduction to the field of embedded systems; A focus on fast prototyping of embedded systems; All key embedded system concepts covered through simple and effective experimentation; An understanding of ARM technology, one of the world's leaders; A practical introduction to embedded C; Applies possibly the most accessible set of tools available in the embedded world.  This book is an introduction to embedded systems design, using the ARM mbed and C programming language as development tools. The mbed provides a compact, self-contained and low-cost hardware core, and the

  2. Manifold Embedding and Semantic Segmentation for Intraoperative Guidance With Hyperspectral Brain Imaging.

    Science.gov (United States)

    Ravi, Daniele; Fabelo, Himar; Callic, Gustavo Marrero; Yang, Guang-Zhong

    2017-09-01

    Recent advances in hyperspectral imaging have made it a promising solution for intra-operative tissue characterization, with the advantages of being non-contact, non-ionizing, and non-invasive. Working with hyperspectral images in vivo, however, is not straightforward as the high dimensionality of the data makes real-time processing challenging. In this paper, a novel dimensionality reduction scheme and a new processing pipeline are introduced to obtain a detailed tumor classification map for intra-operative margin definition during brain surgery. However, existing approaches to dimensionality reduction based on manifold embedding can be time consuming and may not guarantee a consistent result, thus hindering final tissue classification. The proposed framework aims to overcome these problems through a process divided into two steps: dimensionality reduction based on an extension of the T-distributed stochastic neighbor approach is first performed and then a semantic segmentation technique is applied to the embedded results by using a Semantic Texton Forest for tissue classification. Detailed in vivo validation of the proposed method has been performed to demonstrate the potential clinical value of the system.

  3. Adaptive behavior of neighboring neurons during adaptation-induced plasticity of orientation tuning in V1

    Directory of Open Access Journals (Sweden)

    Shumikhina Svetlana

    2009-12-01

    Full Text Available Abstract Background Sensory neurons display transient changes of their response properties following prolonged exposure to an appropriate stimulus (adaptation. In adult cat primary visual cortex, orientation-selective neurons shift their preferred orientation after being adapted to a non-preferred orientation. The direction of those shifts, towards (attractive or away (repulsive from the adapter depends mostly on adaptation duration. How the adaptive behavior of a neuron is related to that of its neighbors remains unclear. Results Here we show that in most cases (75%, cells shift their preferred orientation in the same direction as their neighbors. We also found that cells shifting preferred orientation differently from their neighbors (25% display three interesting properties: (i larger variance of absolute shift amplitude, (ii wider tuning bandwidth and (iii larger range of preferred orientations among the cluster of cells. Several response properties of V1 neurons depend on their location within the cortical orientation map. Our results suggest that recording sites with both attractive and repulsive shifts following adaptation may be located in close proximity to iso-orientation domain boundaries or pinwheel centers. Indeed, those regions have a more diverse orientation distribution of local inputs that could account for the three properties above. On the other hand, sites with all cells shifting their preferred orientation in the same direction could be located within iso-orientation domains. Conclusions Our results suggest that the direction and amplitude of orientation preference shifts in V1 depend on location within the orientation map. This anisotropy of adaptation-induced plasticity, comparable to that of the visual cortex itself, could have important implications for our understanding of visual adaptation at the psychophysical level.

  4. A γ dose distribution evaluation technique using the k-d tree for nearest neighbor searching

    International Nuclear Information System (INIS)

    Yuan Jiankui; Chen Weimin

    2010-01-01

    Purpose: The authors propose an algorithm based on the k-d tree for nearest neighbor searching to improve the γ calculation time for 2D and 3D dose distributions. Methods: The γ calculation method has been widely used for comparisons of dose distributions in clinical treatment plans and quality assurances. By specifying the acceptable dose and distance-to-agreement criteria, the method provides quantitative measurement of the agreement between the reference and evaluation dose distributions. The γ value indicates the acceptability. In regions where γ≤1, the predefined criterion is satisfied and thus the agreement is acceptable; otherwise, the agreement fails. Although the concept of the method is not complicated and a quick naieve implementation is straightforward, an efficient and robust implementation is not trivial. Recent algorithms based on exhaustive searching within a maximum radius, the geometric Euclidean distance, and the table lookup method have been proposed to improve the computational time for multidimensional dose distributions. Motivated by the fact that the least searching time for finding a nearest neighbor can be an O(log N) operation with a k-d tree, where N is the total number of the dose points, the authors propose an algorithm based on the k-d tree for the γ evaluation in this work. Results: In the experiment, the authors found that the average k-d tree construction time per reference point is O(log N), while the nearest neighbor searching time per evaluation point is proportional to O(N 1/k ), where k is between 2 and 3 for two-dimensional and three-dimensional dose distributions, respectively. Conclusions: Comparing with other algorithms such as exhaustive search and sorted list O(N), the k-d tree algorithm for γ evaluation is much more efficient.

  5. Tricriticality in the q-neighbor Ising model on a partially duplex clique.

    Science.gov (United States)

    Chmiel, Anna; Sienkiewicz, Julian; Sznajd-Weron, Katarzyna

    2017-12-01

    We analyze a modified kinetic Ising model, a so-called q-neighbor Ising model, with Metropolis dynamics [Phys. Rev. E 92, 052105 (2015)PLEEE81539-375510.1103/PhysRevE.92.052105] on a duplex clique and a partially duplex clique. In the q-neighbor Ising model each spin interacts only with q spins randomly chosen from its whole neighborhood. In the case of a duplex clique the change of a spin is allowed only if both levels simultaneously induce this change. Due to the mean-field-like nature of the model we are able to derive the analytic form of transition probabilities and solve the corresponding master equation. The existence of the second level changes dramatically the character of the phase transition. In the case of the monoplex clique, the q-neighbor Ising model exhibits a continuous phase transition for q=3, discontinuous phase transition for q≥4, and for q=1 and q=2 the phase transition is not observed. On the other hand, in the case of the duplex clique continuous phase transitions are observed for all values of q, even for q=1 and q=2. Subsequently we introduce a partially duplex clique, parametrized by r∈[0,1], which allows us to tune the network from monoplex (r=0) to duplex (r=1). Such a generalized topology, in which a fraction r of all nodes appear on both levels, allows us to obtain the critical value of r=r^{*}(q) at which a tricriticality (switch from continuous to discontinuous phase transition) appears.

  6. A method of neighbor classes based SVM classification for optical printed Chinese character recognition.

    Science.gov (United States)

    Zhang, Jie; Wu, Xiaohong; Yu, Yanmei; Luo, Daisheng

    2013-01-01

    In optical printed Chinese character recognition (OPCCR), many classifiers have been proposed for the recognition. Among the classifiers, support vector machine (SVM) might be the best classifier. However, SVM is a classifier for two classes. When it is used for multi-classes in OPCCR, its computation is time-consuming. Thus, we propose a neighbor classes based SVM (NC-SVM) to reduce the computation consumption of SVM. Experiments of NC-SVM classification for OPCCR have been done. The results of the experiments have shown that the NC-SVM we proposed can effectively reduce the computation time in OPCCR.

  7. Penerapan Metode K-nearest Neighbor pada Penentuan Grade Dealer Sepeda Motor

    OpenAIRE

    Leidiyana, Henny

    2017-01-01

    The mutually beneficial cooperation is a very important thing for a leasing and dealer. Incentives for marketing is given in order to get consumers as much as possible. But sometimes the surveyor objectivity is lost due to the conspiracy on the field of marketing and surveyors. To overcome this, leasing a variety of ways one of them is doing ranking against the dealer. In this study the application of the k-Nearest Neighbor method and Euclidean distance measurement to determine the grade deal...

  8. Fast and Accuracy Control Chart Pattern Recognition using a New cluster-k-Nearest Neighbor

    OpenAIRE

    Samir Brahim Belhaouari

    2009-01-01

    By taking advantage of both k-NN which is highly accurate and K-means cluster which is able to reduce the time of classification, we can introduce Cluster-k-Nearest Neighbor as "variable k"-NN dealing with the centroid or mean point of all subclasses generated by clustering algorithm. In general the algorithm of K-means cluster is not stable, in term of accuracy, for that reason we develop another algorithm for clustering our space which gives a higher accuracy than K-means cluster, less ...

  9. Tuberculosis control in Bolivia, Chile, Colombia and Peru: why does incidence vary so much between neighbors?

    Science.gov (United States)

    Sobero, R A; Peabody, J W

    2006-11-01

    In 2003, Peru and Bolivia reported the highest annual tuberculosis (TB) incidence rates in the Americas. Neighboring Colombia and Chile had lower annual incidence rates despite their proximity. To determine what factors contribute to differences in TB incidence rates among Chile, Colombia, Bolivia and Peru. Multiple sources of literature dating between 1990 and 2005 were used and World Health Organization TB control guidelines were consulted for policy level comparisons. Comprehensive implementation of the DOTS strategy is the main factor explaining the differences in TB incidence rates, even after considering socio-economic factors. Cross-national comparisons suggest ways to improve regional DOTS implementation.

  10. Neighbor-directed histidine N(τ) alkylation. A route to imidazolium-containing phosphopeptide macrocycles

    Energy Technology Data Exchange (ETDEWEB)

    Qian, Wen-Jian [National Cancer Inst., Frederick, MD (United States); Park, Jung-Eun [National Cancer Inst., Bethesda, MD (United States); Grant, Robert [Massachusetts Inst. of Technology (MIT), Cambridge, MA (United States); Lai, Christopher C. [National Cancer Inst., Frederick, MD (United States); Kelley, James A. [National Cancer Inst., Frederick, MD (United States); Yaffe, Michael B. [Massachusetts Inst. of Technology (MIT), Cambridge, MA (United States); Lee, Kyung S. [National Cancer Inst., Bethesda, MD (United States); Burke, Terrence R. [National Cancer Inst., Frederick, MD (United States)

    2015-07-07

    Our recently discovered, selective, on-resin route to N(τ)-alkylated imidazolium-containing histidine residues affords new strategies for peptide mimetic design. In this, we demonstrate the use of this chemistry to prepare a series of macrocyclic phosphopeptides, in which imidazolium groups serve as ring-forming junctions. These cationic moieties subsequently serve to charge-mask the phosphoamino acid group that directed their formation. Furthermore, neighbor-directed histidine N(τ)-alkylation opens the door to new families of phosphopeptidomimetics for use in a range of chemical biology contexts.

  11. Low-spin identical bands in neighboring odd-A and even-even nuclei

    International Nuclear Information System (INIS)

    Baktash, C.; Winchell, D.F.; Garrett, J.D.; Smith, A.

    1992-01-01

    A comprehensive study of odd-A rotational bands in normally deformed rare-earth nuclei indicates that a large number of seniority-one configurations (21% for odd-Z nuclei) at low spin have moments of inertia nearly identical to that of the seniority-zero configuration of the neighboring even-even nucleus with one less nucleon. It is difficult to reconcile these results with conventional models of nuclear pair correlation, which predict variations of about 15% in the moments of inertia of configurations differing by one unit in seniority

  12. Seismic clusters analysis in Northeastern Italy by the nearest-neighbor approach

    Science.gov (United States)

    Peresan, Antonella; Gentili, Stefania

    2018-01-01

    The main features of earthquake clusters in Northeastern Italy are explored, with the aim to get new insights on local scale patterns of seismicity in the area. The study is based on a systematic analysis of robustly and uniformly detected seismic clusters, which are identified by a statistical method, based on nearest-neighbor distances of events in the space-time-energy domain. The method permits us to highlight and investigate the internal structure of earthquake sequences, and to differentiate the spatial properties of seismicity according to the different topological features of the clusters structure. To analyze seismicity of Northeastern Italy, we use information from local OGS bulletins, compiled at the National Institute of Oceanography and Experimental Geophysics since 1977. A preliminary reappraisal of the earthquake bulletins is carried out and the area of sufficient completeness is outlined. Various techniques are considered to estimate the scaling parameters that characterize earthquakes occurrence in the region, namely the b-value and the fractal dimension of epicenters distribution, required for the application of the nearest-neighbor technique. Specifically, average robust estimates of the parameters of the Unified Scaling Law for Earthquakes, USLE, are assessed for the whole outlined region and are used to compute the nearest-neighbor distances. Clusters identification by the nearest-neighbor method turn out quite reliable and robust with respect to the minimum magnitude cutoff of the input catalog; the identified clusters are well consistent with those obtained from manual aftershocks identification of selected sequences. We demonstrate that the earthquake clusters have distinct preferred geographic locations, and we identify two areas that differ substantially in the examined clustering properties. Specifically, burst-like sequences are associated with the north-western part and swarm-like sequences with the south-eastern part of the study

  13. A Novel Quantum Solution to Privacy-Preserving Nearest Neighbor Query in Location-Based Services

    Science.gov (United States)

    Luo, Zhen-yu; Shi, Run-hua; Xu, Min; Zhang, Shun

    2018-04-01

    We present a cheating-sensitive quantum protocol for Privacy-Preserving Nearest Neighbor Query based on Oblivious Quantum Key Distribution and Quantum Encryption. Compared with the classical related protocols, our proposed protocol has higher security, because the security of our protocol is based on basic physical principles of quantum mechanics, instead of difficulty assumptions. Especially, our protocol takes single photons as quantum resources and only needs to perform single-photon projective measurement. Therefore, it is feasible to implement this protocol with the present technologies.

  14. Chaotic synchronization of nearest-neighbor diffusive coupling Hindmarsh-Rose neural networks in noisy environments

    International Nuclear Information System (INIS)

    Fang Xiaoling; Yu Hongjie; Jiang Zonglai

    2009-01-01

    The chaotic synchronization of Hindmarsh-Rose neural networks linked by a nonlinear coupling function is discussed. The HR neural networks with nearest-neighbor diffusive coupling form are treated as numerical examples. By the construction of a special nonlinear-coupled term, the chaotic system is coupled symmetrically. For three and four neurons network, a certain region of coupling strength corresponding to full synchronization is given, and the effect of network structure and noise position are analyzed. For five and more neurons network, the full synchronization is very difficult to realize. All the results have been proved by the calculation of the maximum conditional Lyapunov exponent.

  15. The Impactof the Kurdish Question on Turkey's Relations with its Middle Eastern neighbors

    OpenAIRE

    Asil, Muhammet Ali

    2013-01-01

    Tezin basılısı İstanbul Şehir Üniversitesi Kütüphanesi'ndedir. This dissertation analyzes the “Kurdish Question” from an International Relations perspective. Focusing on the impact of the Kurdish question on Turkey’s relations in the last decade with its Middle Eastern neighbors, i.e. Iran, Syria, and Iraq, and with the European Union; this study shows how Turkey-Middle East and Turkey-EU relations are shaped differently. In the search for reasons for this difference, Realist and Liberal I...

  16. Low-spin identical bands in neighboring odd-A and even-even nuclei

    International Nuclear Information System (INIS)

    Baktash, C.; Winchell, D.F.; Garrett, J.D.; Smith, A.

    1993-01-01

    A comprehensive study of odd-A rotational bands in normally deformed rare-earth nuclei indicates that a large number of seniority-one configurations (21 % for odd-Z nuclei) at low spin have moments of inertia nearly identical to that of the seniority-zero configuration of the neighboring even-even nucleus with one less nucleon. It is difficult to reconcile these results with conventional models of nuclear pair correlation, which predict variations of about 15% in the moments of inertia of configurations differing by one unit in seniority. (orig.)

  17. The Activation of Embedded Words in Spoken Word Recognition

    Science.gov (United States)

    Zhang, Xujin; Samuel, Arthur G.

    2015-01-01

    The current study investigated how listeners understand English words that have shorter words embedded in them. A series of auditory-auditory priming experiments assessed the activation of six types of embedded words (2 embedded positions × 3 embedded proportions) under different listening conditions. Facilitation of lexical decision responses to targets (e.g., pig) associated with words embedded in primes (e.g., hamster) indexed activation of the embedded words (e.g., ham). When the listening conditions were optimal, isolated embedded words (e.g., ham) primed their targets in all six conditions (Experiment 1a). Within carrier words (e.g., hamster), the same set of embedded words produced priming only when they were at the beginning or comprised a large proportion of the carrier word (Experiment 1b). When the listening conditions were made suboptimal by expanding or compressing the primes, significant priming was found for isolated embedded words (Experiment 2a), but no priming was produced when the carrier words were compressed/expanded (Experiment 2b). Similarly, priming was eliminated when the carrier words were presented with one segment replaced by noise (Experiment 3). When cognitive load was imposed, priming for embedded words was again found when they were presented in isolation (Experiment 4a), but not when they were embedded in the carrier words (Experiment 4b). The results suggest that both embedded position and proportion play important roles in the activation of embedded words, but that such activation only occurs under unusually good listening conditions. PMID:25593407

  18. The Activation of Embedded Words in Spoken Word Recognition.

    Science.gov (United States)

    Zhang, Xujin; Samuel, Arthur G

    2015-01-01

    The current study investigated how listeners understand English words that have shorter words embedded in them. A series of auditory-auditory priming experiments assessed the activation of six types of embedded words (2 embedded positions × 3 embedded proportions) under different listening conditions. Facilitation of lexical decision responses to targets (e.g., pig) associated with words embedded in primes (e.g., hamster ) indexed activation of the embedded words (e.g., ham ). When the listening conditions were optimal, isolated embedded words (e.g., ham ) primed their targets in all six conditions (Experiment 1a). Within carrier words (e.g., hamster ), the same set of embedded words produced priming only when they were at the beginning or comprised a large proportion of the carrier word (Experiment 1b). When the listening conditions were made suboptimal by expanding or compressing the primes, significant priming was found for isolated embedded words (Experiment 2a), but no priming was produced when the carrier words were compressed/expanded (Experiment 2b). Similarly, priming was eliminated when the carrier words were presented with one segment replaced by noise (Experiment 3). When cognitive load was imposed, priming for embedded words was again found when they were presented in isolation (Experiment 4a), but not when they were embedded in the carrier words (Experiment 4b). The results suggest that both embedded position and proportion play important roles in the activation of embedded words, but that such activation only occurs under unusually good listening conditions.

  19. Sequence correction of random coil chemical shifts: correlation between neighbor correction factors and changes in the Ramachandran distribution

    DEFF Research Database (Denmark)

    Kjærgaard, Magnus; Poulsen, Flemming Martin

    2011-01-01

    Random coil chemical shifts are necessary for secondary chemical shift analysis, which is the main NMR method for identification of secondary structure in proteins. One of the largest challenges in the determination of random coil chemical shifts is accounting for the effect of neighboring residues....... The contributions from the neighboring residues are typically removed by using neighbor correction factors determined based on each residue's effect on glycine chemical shifts. Due to its unusual conformational freedom, glycine may be particularly unrepresentative for the remaining residue types. In this study, we...... in the conformational ensemble are an important source of neighbor effects in disordered proteins. Glutamine derived random coil chemical shifts and correction factors modestly improve our ability to predict (13)C chemical shifts of intrinsically disordered proteins compared to existing datasets, and may thus improve...

  20. Diagnosis of Diabetes Diseases Using an Artificial Immune Recognition System2 (AIRS2) with Fuzzy K-nearest Neighbor

    OpenAIRE

    CHIKH, Mohamed Amine; SAIDI, Meryem; SETTOUTI, Nesma

    2012-01-01

    The use of expert systems and artificial intelligence techniques in disease diagnosis has been increasing gradually. Artificial Immune Recognition System (AIRS) is one of the methods used in medical classification problems. AIRS2 is a more efficient version of the AIRS algorithm. In this paper, we used a modified AIRS2 called MAIRS2 where we replace the K- nearest neighbors algorithm with the fuzzy K-nearest neighbors to improve the diagnostic accuracy of diabetes diseases. The diabetes disea...

  1. EFFECT OF EMBEDDING METHODS VERSUS FIXATIVE TYPE ON KARYOMETRIC MEASURES

    NARCIS (Netherlands)

    BOON, ME; VANDERPOEL, HG; TAN, CJA; KOK, LP

    The influence of fixation and embedding methods in seven urologic tumor samples was studied karyometrically for 12 preparatory techniques. Routine histologic formalin fixation was compared with Carbowax and Kryofix fixatives. Also, histologic material was studied embedded in paraffin and plastic

  2. Embedding of reactor wastes in plastic resins

    International Nuclear Information System (INIS)

    1979-01-01

    STEAG Kernenergie GmbH is so far the only firm commercially to condition radioactive bead ion exchange resins by embedding in polystyrene resins. The objective of the work reported here was to study and develop methods for immobilization of other reactor wastes in plastic resins. Comparison studies on high quality cement however showed favourable results for cement with respect to process safety and economy. For this reason STEAG interrupted its work in the field of resin embedding after about one year. The work carried out during this period is surveyed in this report, which includes a comprehensive literature study on reactor wastes and their solidification in plastic resins as well as on regulations with regard to radioactive waste disposal in the member states of the European Communities

  3. Constraint Embedding for Multibody System Dynamics

    Science.gov (United States)

    Jain, Abhinandan

    2009-01-01

    This paper describes a constraint embedding approach for the handling of local closure constraints in multibody system dynamics. The approach uses spatial operator techniques to eliminate local-loop constraints from the system and effectively convert the system into tree-topology systems. This approach allows the direct derivation of recursive O(N) techniques for solving the system dynamics and avoiding the expensive steps that would otherwise be required for handling the closedchain dynamics. The approach is very effective for systems where the constraints are confined to small-subgraphs within the system topology. The paper provides background on the spatial operator O(N) algorithms, the extensions for handling embedded constraints, and concludes with some examples of such constraints.

  4. Modelling and Analyses of Embedded Systems Design

    DEFF Research Database (Denmark)

    Brekling, Aske Wiid

    We present the MoVES languages: a language with which embedded systems can be specified at a stage in the development process where an application is identified and should be mapped to an execution platform (potentially multi- core). We give a formal model for MoVES that captures and gives......-based verification is a promising approach for assisting developers of embedded systems. We provide examples of system verifications that, in size and complexity, point in the direction of industrially-interesting systems....... semantics to the elements of specifications in the MoVES language. We show that even for seem- ingly simple systems, the complexity of verifying real-time constraints can be overwhelming - but we give an upper limit to the size of the search-space that needs examining. Furthermore, the formal model exposes...

  5. Synchronous correlation matrices and Connes’ embedding conjecture

    Energy Technology Data Exchange (ETDEWEB)

    Dykema, Kenneth J., E-mail: kdykema@math.tamu.edu [Department of Mathematics, Texas A& M University, College Station, Texas 77843-3368 (United States); Paulsen, Vern, E-mail: vern@math.uh.edu [Department of Mathematics, University of Houston, Houston, Texas 77204 (United States)

    2016-01-15

    In the work of Paulsen et al. [J. Funct. Anal. (in press); preprint arXiv:1407.6918], the concept of synchronous quantum correlation matrices was introduced and these were shown to correspond to traces on certain C*-algebras. In particular, synchronous correlation matrices arose in their study of various versions of quantum chromatic numbers of graphs and other quantum versions of graph theoretic parameters. In this paper, we develop these ideas further, focusing on the relations between synchronous correlation matrices and microstates. We prove that Connes’ embedding conjecture is equivalent to the equality of two families of synchronous quantum correlation matrices. We prove that if Connes’ embedding conjecture has a positive answer, then the tracial rank and projective rank are equal for every graph. We then apply these results to more general non-local games.

  6. Dynamic temperature measurements with embedded optical sensors.

    Energy Technology Data Exchange (ETDEWEB)

    Dolan, Daniel H.,; Seagle, Christopher T; Ao, Tommy

    2013-10-01

    This report summarizes LDRD project number 151365, \\Dynamic Temperature Measurements with Embedded Optical Sensors". The purpose of this project was to develop an optical sensor capable of detecting modest temperature states (<1000 K) with nanosecond time resolution, a recurring diagnostic need in dynamic compression experiments at the Sandia Z machine. Gold sensors were selected because the visible re ectance spectrum of gold varies strongly with temperature. A variety of static and dynamic measurements were performed to assess re ectance changes at di erent temperatures and pressures. Using a minimal optical model for gold, a plausible connection between static calibrations and dynamic measurements was found. With re nements to the model and diagnostic upgrades, embedded gold sensors seem capable of detecting minor (<50 K) temperature changes under dynamic compression.

  7. A ferroelectric memory technology for embedded LSI

    CERN Document Server

    Kunio, T

    1999-01-01

    We have developed an FeRAM (Ferroelectric Random Access Memory) embedded smart card LSI by using double metal 0.8- mu m CMOS technology. The smart-card has a 256-byte FeRAM macro and an 8-bit microcontroller. The FeRAM macro has the $9 performance of 10/sup 8/ endurance cycles and is half the size of an EEPROM macro. We have also developed a new CMVP (Capacitor on Meta/Via Stacked Plug) cell for an advanced FeRAM embedded LSI by using 0.25- mu m CMOS technology. $9 The ferroelectric capacitors of this cell are fabricated after the multiple interconnect is formed, and a cell area of 3.2 mu m/sup 2/ is obtained. (8 refs).

  8. Global embeddings for branes at toric singularities

    CERN Document Server

    Balasubramanian, Vijay; Braun, Volker; García-Etxebarria, Iñaki

    2012-01-01

    We describe how local toric singularities, including the Toric Lego construction, can be embedded in compact Calabi-Yau manifolds. We study in detail the addition of D-branes, including non-compact flavor branes as typically used in semi-realistic model building. The global geometry provides constraints on allowable local models. As an illustration of our discussion we focus on D3 and D7-branes on (the partially resolved) (dP0)^3 singularity, its embedding in a specific Calabi-Yau manifold as a hypersurface in a toric variety, the related type IIB orientifold compactification, as well as the corresponding F-theory uplift. Our techniques generalize naturally to complete intersections, and to a large class of F-theory backgrounds with singularities.

  9. Metamaterial Embedded Wearable Rectangular Microstrip Patch Antenna

    Directory of Open Access Journals (Sweden)

    J. G. Joshi

    2012-01-01

    Full Text Available This paper presents an indigenous low-cost metamaterial embedded wearable rectangular microstrip patch antenna using polyester substrate for IEEE 802.11a WLAN applications. The proposed antenna resonates at 5.10 GHz with a bandwidth and gain of 97 MHz and 4.92 dBi, respectively. The electrical size of this antenna is 0.254λ×0.5λ. The slots are cut in rectangular patch to reduce the bending effect. This leads to mismatch the impedance at WLAN frequency band; hence, a metamaterial square SRR is embedded inside the slot. A prototype antenna has been fabricated and tested, and the measured results are presented in this paper. The simulated and measured results of the proposed antenna are found to be in good agreement. The bending effect on the performance of this antenna is experimentally verified.

  10. Physical Activity Recognition from Smartphone Embedded Sensors

    DEFF Research Database (Denmark)

    Prudêncio, João; Aguiar, Ana; Roetter, Daniel Enrique Lucani

    2013-01-01

    The ubiquity of smartphones has motivated efforts to use the embedded sensors to detect various aspects of user context to transparently provide personalized and contextualized services to the user. One relevant piece of context is the physical activity of the smartphone user. In this paper, we...... propose a novel set of features for distinguishing five physical activities using only sensors embedded in the smartphone. Specifically, we introduce features that are normalized using the orientation sensor such that horizontal and vertical movements are explicitly computed. We evaluate a neural network...... classifier in experiments in the wild with multiple users and hardware, we achieve accuracies above 90% for a single user and phone, and above 65% for multiple users, which is higher that similar works on the same set of activities, demonstrating the potential of our approach....

  11. Engineering embedded systems physics, programs, circuits

    CERN Document Server

    Hintenaus, Peter

    2015-01-01

    This is a textbook for graduate and final-year-undergraduate computer-science and electrical-engineering students interested in the hardware and software aspects of embedded and cyberphysical systems design. It is comprehensive and self-contained, covering everything from the basics to case-study implementation. Emphasis is placed on the physical nature of the problem domain and of the devices used. The reader is assumed to be familiar on a theoretical level with mathematical tools like ordinary differential equation and Fourier transforms. In this book these tools will be put to practical use. Engineering Embedded Systems begins by addressing basic material on signals and systems, before introducing to electronics. Treatment of digital electronics accentuating synchronous circuits and including high-speed effects proceeds to micro-controllers, digital signal processors and programmable logic. Peripheral units and decentralized networks are given due weight. The properties of analog circuits and devices like ...

  12. Learning for VMM + WTA Embedded Classifiers

    Science.gov (United States)

    2016-03-31

    Learning for VMM + WTA Embedded Classifiers Jennifer Hasler and Sahil Shah Electrical and Computer Engineering Georgia Institute of Technology...enabling correct classification of each novel acoustic signal (generator, idle car, and idle truck ). The classification structure requires, after...measured on our SoC FPAA IC. The test input is composed of signals from urban environment for 3 objects (generator, idle car, and idle truck

  13. Mycobacterium avium Infection after Acupoint Embedding Therapy

    Directory of Open Access Journals (Sweden)

    Jiao Zhang, MD

    2017-09-01

    Full Text Available Summary:. Nontuberculous mycobacterium is a ubiquitous environmental organism that is unusual to cause a true infection, but it can cause severe cutaneous infections. In this case report, we present a successful treatment for a Chinese patient with Mycobacterium avium cutaneous infection after acupoint embedding therapy. We managed to conduct pathogenic detection, drug sensitive test, and multidisciplinary consultation. Finally, a systematic treatment strategy of nontuberculous mycobacterium was performed. Twenty-two-month follow-up revealed excellent outcome without any recurrence.

  14. Smooth embeddings with Stein surface images

    OpenAIRE

    Gompf, Robert E.

    2011-01-01

    A simple characterization is given of open subsets of a complex surface that smoothly perturb to Stein open subsets. As applications, complex 2-space C^2 contains domains of holomorphy (Stein open subsets) that are exotic R^4's, and others homotopy equivalent to the 2-sphere but cut out by smooth, compact 3-manifolds. Pseudoconvex embeddings of Brieskorn spheres and other 3-manifolds into complex surfaces are constructed, as are pseudoconcave holomorphic fillings (with disagreeing contact and...

  15. Low-Latency Embedded Vision Processor (LLEVS)

    Science.gov (United States)

    2016-03-01

    algorithms, low-latency video processing, embedded image processor, wearable electronics, helmet-mounted systems, alternative night / day imaging...external subsystems and data sources with the device. The establishment of data interfaces in terms of data transfer rates, formats and types are...video signals from Near-visible Infrared (NVIR) sensor, Shortwave IR (SWIR) and Longwave IR (LWIR) is the main processing for Night Vision (NI) system

  16. Photoluminescence of nanocrystals embedded in oxide matrices

    International Nuclear Information System (INIS)

    Estrada, C.; Gonzalez, J.A.; Kunold, A.; Reyes-Esqueda, J.A.; Pereyra, P.

    2006-12-01

    We used the theory of finite periodic systems to explain the photoluminescence spectra dependence on the average diameter of nanocrystals embedded in oxide matrices. Because of the broad matrix band gap, the photoluminescence response is basically determined by isolated nanocrystals and sequences of a few of them. With this model we were able to reproduce the shape and displacement of the experimentally observed photoluminescence spectra. (author)

  17. Scheduling Driven Partitioning of Heterogeneous Embedded Systems

    DEFF Research Database (Denmark)

    Pop, Paul; Eles, Petru; Peng, Zebo

    1998-01-01

    In this paper we present an algorithm for system level hardware/software partitioning of heterogeneous embedded systems. The system is represented as an abstract graph which captures both data-flow and the flow of control. Given an architecture consisting of several processors, ASICs and shared...... busses, our partitioning algorithm finds the partitioning with the smallest hardware cost and is able to predict and guarantee the performance of the system in terms of worst case delay....

  18. Embedded Ultrasonics for SHM of Space Applications

    Science.gov (United States)

    2012-07-30

    information on material properties and other forms of damage such as cracks, structural fatigue and/or impact events. This synergistic aspect of the embedded...larger the phase shift. However, high excitation levels could contribute to sensor fatigue and levels in a range 15 to 20 (110 to 130 volts) are...joints each featuring three bolts. Piezoelectric wafers ( PZT ) with UNF electrodes were bonded to the isogrid panels using 3M 2216 epoxy

  19. Word Embedding Perturbation for Sentence Classification

    OpenAIRE

    Zhang, Dongxu; Yang, Zhichao

    2018-01-01

    In this technique report, we aim to mitigate the overfitting problem of natural language by applying data augmentation methods. Specifically, we attempt several types of noise to perturb the input word embedding, such as Gaussian noise, Bernoulli noise, and adversarial noise, etc. We also apply several constraints on different types of noise. By implementing these proposed data augmentation methods, the baseline models can gain improvements on several sentence classification tasks.

  20. Integrated Design Tools for Embedded Control Systems

    OpenAIRE

    Jovanovic, D.S.; Hilderink, G.H.; Broenink, Johannes F.; Karelse, F.

    2001-01-01

    Currently, computer-based control systems are still being implemented using the same techniques as 10 years ago. The purpose of this project is the development of a design framework, consisting of tools and libraries, which allows the designer to build high reliable heterogeneous real-time embedded systems in a very short time at a fraction of the present day costs. The ultimate focus of current research is on transformation control laws to efficient concurrent algorithms, with concerns about...

  1. 2-surface twistors, embeddings and symmetries

    International Nuclear Information System (INIS)

    Jeffryes, B.P.

    1987-01-01

    2-Surface twistor space was introduced in connection with a proposal for a quasi-local definition of mass and angular momentum within general relativity. Properties of the 2-surface twistor space are related to the possibilities for embedding the 2-surface in real and complex conformally flat spaces. The additional properties of the twistor space resulting from symmetries of the 2-surface are discussed, with particular detail on axisymmetric 2-surfaces. (author)

  2. Embedding Versus Immersion in General Relativity

    OpenAIRE

    Monte, Edmundo M.

    2009-01-01

    We briefly discuss the concepts of immersion and embedding of space-times in higher-dimensional spaces. We revisit the classical work by Kasner in which he constructs a model of immersion of the Schwarzschild exterior solution into a six-dimensional pseudo-Euclidean manifold. We show that, from a physical point of view, this model is not entirely satisfactory since the causal structure of the immersed space-time is not preserved by the immersion.

  3. Consistent Alignment of World Embedding Models

    Science.gov (United States)

    2017-03-02

    propose a solution that aligns variations of the same model (or different models) in a joint low-dimensional la- tent space leveraging carefully...representations of linguistic enti- ties, most often referred to as embeddings. This includes techniques that rely on matrix factoriza- tion (Levy & Goldberg ...higher, the variation is much higher as well. As we increase the size of the neighborhood, or improve the quality of our sample by only picking the most

  4. System Description: Embedding Verification into Microsoft Excel

    OpenAIRE

    Collins, Graham; Dennis, Louise Abigail

    2000-01-01

    The aim of the PROSPER project is to allow the embedding of existing verification technology into applications in such a way that the theorem proving is hidden, or presented to the end user in a natural way. This paper describes a system built to test whether the PROSPER toolkit satisfied this aim. The system combines the toolkit with Microsoft Excel, a popular commercial spreadsheet application.

  5. Intelligent Machine Parts with Surface Embedded Sensors

    OpenAIRE

    Østbø, Niels Peter

    2009-01-01

    A surface embedded temperature sensor has successfully been fabricated on a customized industrial bolt. The aluminum substrate of the bolt was electrically isolated by plasma electrolytic oxidation followed by the fabrication of a type T thermocouple and finally covered by a wear resistant DLC coating. This bolt is part of our work to develop smart machine parts that are capable of reporting their current physical status under real working conditions enabling both new tools for condition base...

  6. Development of an Erlang System Adaopted to Embedded Devices

    OpenAIRE

    Andersson, Fredrik; Bergström, Fabian

    2011-01-01

    Erlang is a powerful and robust language for writing massively parallel and distributed applications. With the introduction of multi-core ARM processors, the embedded market will be looking for ways of taking advantage of the newfound opportunities for parallelism. To support the development of embedded applications using Erlang we want to provide Erlang and Embedded developers with a run-time system suited for embedded devices. We have managed to shrink the disk size of the Erlang runtime sy...

  7. Critical points in an algebra of elementary embeddings

    OpenAIRE

    Dougherty, Randall

    1992-01-01

    Given two elementary embeddings from the collection of sets of rank less than $\\lambda$ to itself, one can combine them to obtain another such embedding in two ways: by composition, and by applying one to (initial segments of) the other. Hence, a single such nontrivial embedding $j$ generates an algebra of embeddings via these two operations, which satisfies certain laws (for example, application distributes over both composition and application). Laver has shown, among other things, that thi...

  8. A Markov chain Monte Carlo Expectation Maximization Algorithm for Statistical Analysis of DNA Sequence Evolution with Neighbor-Dependent Substitution Rates

    DEFF Research Database (Denmark)

    Hobolth, Asger

    2008-01-01

    The evolution of DNA sequences can be described by discrete state continuous time Markov processes on a phylogenetic tree. We consider neighbor-dependent evolutionary models where the instantaneous rate of substitution at a site depends on the states of the neighboring sites. Neighbor...

  9. Aftershock identification problem via the nearest-neighbor analysis for marked point processes

    Science.gov (United States)

    Gabrielov, A.; Zaliapin, I.; Wong, H.; Keilis-Borok, V.

    2007-12-01

    The centennial observations on the world seismicity have revealed a wide variety of clustering phenomena that unfold in the space-time-energy domain and provide most reliable information about the earthquake dynamics. However, there is neither a unifying theory nor a convenient statistical apparatus that would naturally account for the different types of seismic clustering. In this talk we present a theoretical framework for nearest-neighbor analysis of marked processes and obtain new results on hierarchical approach to studying seismic clustering introduced by Baiesi and Paczuski (2004). Recall that under this approach one defines an asymmetric distance D in space-time-energy domain such that the nearest-neighbor spanning graph with respect to D becomes a time- oriented tree. We demonstrate how this approach can be used to detect earthquake clustering. We apply our analysis to the observed seismicity of California and synthetic catalogs from ETAS model and show that the earthquake clustering part is statistically different from the homogeneous part. This finding may serve as a basis for an objective aftershock identification procedure.

  10. A Distributed Approach to Continuous Monitoring of Constrained k-Nearest Neighbor Queries in Road Networks

    Directory of Open Access Journals (Sweden)

    Hyung-Ju Cho

    2012-01-01

    Full Text Available Given two positive parameters k and r, a constrained k-nearest neighbor (CkNN query returns the k closest objects within a network distance r of the query location in road networks. In terms of the scalability of monitoring these CkNN queries, existing solutions based on central processing at a server suffer from a sudden and sharp rise in server load as well as messaging cost as the number of queries increases. In this paper, we propose a distributed and scalable scheme called DAEMON for the continuous monitoring of CkNN queries in road networks. Our query processing is distributed among clients (query objects and server. Specifically, the server evaluates CkNN queries issued at intersections of road segments, retrieves the objects on the road segments between neighboring intersections, and sends responses to the query objects. Finally, each client makes its own query result using this server response. As a result, our distributed scheme achieves close-to-optimal communication costs and scales well to large numbers of monitoring queries. Exhaustive experimental results demonstrate that our scheme substantially outperforms its competitor in terms of query processing time and messaging cost.

  11. Gastronomy Tourism in Several Neighbor Countries of Indonesia: a Brief Review

    Directory of Open Access Journals (Sweden)

    Kurniasih Sukenti

    2014-04-01

    Full Text Available Gastronomy tourism, also called culinary tourism or food tourism, is a kind of tourism that provide attractions based on the culinary aspect owned by a country, region, or area. It is not only offers food and beverages as the main objects in its attractions, but also everything related to food activities ranging from food ingredients, preparation, processing, serving, as well as the cultural and local values. A well-managed culinary tourism will be a supportive program in developing and enhancing the tourism sector in a country. The objective of this paper is to describe the profile of gastronomy tourism in several neighbor countries of Indonesia, i.e. Hongkong, Singapore, Thailand, and Malaysia. This brief review is also discussed the potential of Indonesia gastronomy in supporting government’s tourism program. Basically, Indonesia has more enormous potential asset in managing its cultural heritages in term of culinary than its neighbor countries. A well-managed gastronomy tourism plays not only an important role in enhancing the economic sector, but also contribute in preserving the natural and cultural resources. Keywords: gastronomy tourism, culinary tourism, food tourism.

  12. Hyperplane distance neighbor clustering based on local discriminant analysis for complex chemical processes monitoring

    Energy Technology Data Exchange (ETDEWEB)

    Lu, Chunhong; Xiao, Shaoqing; Gu, Xiaofeng [Jiangnan University, Wuxi (China)

    2014-11-15

    The collected training data often include both normal and faulty samples for complex chemical processes. However, some monitoring methods, such as partial least squares (PLS), principal component analysis (PCA), independent component analysis (ICA) and Fisher discriminant analysis (FDA), require fault-free data to build the normal operation model. These techniques are applicable after the preliminary step of data clustering is applied. We here propose a novel hyperplane distance neighbor clustering (HDNC) based on the local discriminant analysis (LDA) for chemical process monitoring. First, faulty samples are separated from normal ones using the HDNC method. Then, the optimal subspace for fault detection and classification can be obtained using the LDA approach. The proposed method takes the multimodality within the faulty data into account, and thus improves the capability of process monitoring significantly. The HDNC-LDA monitoring approach is applied to two simulation processes and then compared with the conventional FDA based on the K-nearest neighbor (KNN-FDA) method. The results obtained in two different scenarios demonstrate the superiority of the HDNC-LDA approach in terms of fault detection and classification accuracy.

  13. Interacting Effects Induced by Two Neighboring Pits Considering Relative Position Parameters and Pit Depth

    Directory of Open Access Journals (Sweden)

    Yongfang Huang

    2017-04-01

    Full Text Available For pre-corroded aluminum alloy 7075-T6, the interacting effects of two neighboring pits on the stress concentration are comprehensively analyzed by considering various relative position parameters (inclination angle θ and dimensionless spacing parameter λ and pit depth (d with the finite element method. According to the severity of the stress concentration, the critical corrosion regions, bearing high susceptibility to fatigue damage, are determined for intersecting and adjacent pits, respectively. A straightforward approach is accordingly proposed to conservatively estimate the combined stress concentration factor induced by two neighboring pits, and a concrete application example is presented. It is found that for intersecting pits, the normalized stress concentration factor Ktnor increases with the increase of θ and λ and always reaches its maximum at θ = 90°, yet for adjacent pits, Ktnor decreases with the increase of λ and the maximum value appears at a slight asymmetric location. The simulations reveal that Ktnor follows a linear and an exponential relationship with the dimensionless depth parameter Rd for intersecting and adjacent cases, respectively.

  14. Sistem Rekomendasi Pada E-Commerce Menggunakan K-Nearest Neighbor

    Directory of Open Access Journals (Sweden)

    Chandra Saha Dewa Prasetya

    2017-09-01

    The growing number of product information available on the internet brings challenges to both customer and online businesses in the e-commerce environment. Customer often have difficulty when looking for products on the internet because of the number of products sold on the internet. In addition, online businessman often experience difficulties because they has much data about products, customers and transactions, thus causing online businessman have difficulty to promote the right product to a particular customer target. A recommendation system was developed to address those problem with various methods such as Collaborative Filtering, ContentBased, and Hybrid. Collaborative filtering method uses customer’s rating data, content based using product content such as title or description, and hybrid using both as the basis of the recommendation. In this research, the k-nearest neighbor algorithm is used to determine the top-n product recommendations for each buyer. The result of this research method Content Based outperforms other methods because the sparse data, that is the condition where the number of rating given by the customers is relatively little compared the number of products available in e-commerce. Keywords: recomendation system, k-nearest neighbor, collaborative filtering, content based.

  15. Spectral neighbor analysis method for automated generation of quantum-accurate interatomic potentials

    Energy Technology Data Exchange (ETDEWEB)

    Thompson, Aidan P. [Sandia National Laboratories (SNL-NM), Albuquerque, NM (United States). Multiscale Science Dept.; Swiler, Laura P. [Sandia National Laboratories (SNL-NM), Albuquerque, NM (United States). Optimization and Uncertainty Quantification Dept.; Trott, Christian R. [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States). Scalable Algorithms Dept.; Foiles, Stephen M. [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States). Computational Materials and Data Science Dept.; Tucker, Garritt J. [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States). Computational Materials and Data Science Dept.; Drexel Univ., Philadelphia, PA (United States). Dept. of Materials Science and Engineering

    2015-03-15

    Here, we present a new interatomic potential for solids and liquids called Spectral Neighbor Analysis Potential (SNAP). The SNAP potential has a very general form and uses machine-learning techniques to reproduce the energies, forces, and stress tensors of a large set of small configurations of atoms, which are obtained using high-accuracy quantum electronic structure (QM) calculations. The local environment of each atom is characterized by a set of bispectrum components of the local neighbor density projected onto a basis of hyperspherical harmonics in four dimensions. The bispectrum components are the same bond-orientational order parameters employed by the GAP potential [1]. The SNAP potential, unlike GAP, assumes a linear relationship between atom energy and bispectrum components. The linear SNAP coefficients are determined using weighted least-squares linear regression against the full QM training set. This allows the SNAP potential to be fit in a robust, automated manner to large QM data sets using many bispectrum components. The calculation of the bispectrum components and the SNAP potential are implemented in the LAMMPS parallel molecular dynamics code. We demonstrate that a previously unnoticed symmetry property can be exploited to reduce the computational cost of the force calculations by more than one order of magnitude. We present results for a SNAP potential for tantalum, showing that it accurately reproduces a range of commonly calculated properties of both the crystalline solid and the liquid phases. In addition, unlike simpler existing potentials, SNAP correctly predicts the energy barrier for screw dislocation migration in BCC tantalum.

  16. Spectral neighbor analysis method for automated generation of quantum-accurate interatomic potentials

    Energy Technology Data Exchange (ETDEWEB)

    Thompson, A.P., E-mail: athomps@sandia.gov [Multiscale Science Department, Sandia National Laboratories, PO Box 5800, MS 1322, Albuquerque, NM 87185 (United States); Swiler, L.P., E-mail: lpswile@sandia.gov [Optimization and Uncertainty Quantification Department, Sandia National Laboratories, PO Box 5800, MS 1318, Albuquerque, NM 87185 (United States); Trott, C.R., E-mail: crtrott@sandia.gov [Scalable Algorithms Department, Sandia National Laboratories, PO Box 5800, MS 1322, Albuquerque, NM 87185 (United States); Foiles, S.M., E-mail: foiles@sandia.gov [Computational Materials and Data Science Department, Sandia National Laboratories, PO Box 5800, MS 1411, Albuquerque, NM 87185 (United States); Tucker, G.J., E-mail: gtucker@coe.drexel.edu [Computational Materials and Data Science Department, Sandia National Laboratories, PO Box 5800, MS 1411, Albuquerque, NM 87185 (United States); Department of Materials Science and Engineering, Drexel University, Philadelphia, PA 19104 (United States)

    2015-03-15

    We present a new interatomic potential for solids and liquids called Spectral Neighbor Analysis Potential (SNAP). The SNAP potential has a very general form and uses machine-learning techniques to reproduce the energies, forces, and stress tensors of a large set of small configurations of atoms, which are obtained using high-accuracy quantum electronic structure (QM) calculations. The local environment of each atom is characterized by a set of bispectrum components of the local neighbor density projected onto a basis of hyperspherical harmonics in four dimensions. The bispectrum components are the same bond-orientational order parameters employed by the GAP potential [1]. The SNAP potential, unlike GAP, assumes a linear relationship between atom energy and bispectrum components. The linear SNAP coefficients are determined using weighted least-squares linear regression against the full QM training set. This allows the SNAP potential to be fit in a robust, automated manner to large QM data sets using many bispectrum components. The calculation of the bispectrum components and the SNAP potential are implemented in the LAMMPS parallel molecular dynamics code. We demonstrate that a previously unnoticed symmetry property can be exploited to reduce the computational cost of the force calculations by more than one order of magnitude. We present results for a SNAP potential for tantalum, showing that it accurately reproduces a range of commonly calculated properties of both the crystalline solid and the liquid phases. In addition, unlike simpler existing potentials, SNAP correctly predicts the energy barrier for screw dislocation migration in BCC tantalum.

  17. Predicting Audience Location on the Basis of the k-Nearest Neighbor Multilabel Classification

    Directory of Open Access Journals (Sweden)

    Haitao Wu

    2014-01-01

    Full Text Available Understanding audience location information in online social networks is important in designing recommendation systems, improving information dissemination, and so on. In this paper, we focus on predicting the location distribution of audiences on YouTube. And we transform this problem to a multilabel classification problem, while we find there exist three problems when the classical k-nearest neighbor based algorithm for multilabel classification (ML-kNN is used to predict location distribution. Firstly, the feature weights are not considered in measuring the similarity degree. Secondly, it consumes considerable computing time in finding similar items by traversing all the training set. Thirdly, the goal of ML-kNN is to find relevant labels for every sample which is different from audience location prediction. To solve these problems, we propose the methods of measuring similarity based on weight, quickly finding similar items, and ranking a specific number of labels. On the basis of these methods and the ML-kNN, the k-nearest neighbor based model for audience location prediction (AL-kNN is proposed for predicting audience location. The experiments based on massive YouTube data show that the proposed model can more accurately predict the location of YouTube video audience than the ML-kNN, MLNB, and Rank-SVM methods.

  18. Automated web usage data mining and recommendation system using K-Nearest Neighbor (KNN classification method

    Directory of Open Access Journals (Sweden)

    D.A. Adeniyi

    2016-01-01

    Full Text Available The major problem of many on-line web sites is the presentation of many choices to the client at a time; this usually results to strenuous and time consuming task in finding the right product or information on the site. In this work, we present a study of automatic web usage data mining and recommendation system based on current user behavior through his/her click stream data on the newly developed Really Simple Syndication (RSS reader website, in order to provide relevant information to the individual without explicitly asking for it. The K-Nearest-Neighbor (KNN classification method has been trained to be used on-line and in Real-Time to identify clients/visitors click stream data, matching it to a particular user group and recommend a tailored browsing option that meet the need of the specific user at a particular time. To achieve this, web users RSS address file was extracted, cleansed, formatted and grouped into meaningful session and data mart was developed. Our result shows that the K-Nearest Neighbor classifier is transparent, consistent, straightforward, simple to understand, high tendency to possess desirable qualities and easy to implement than most other machine learning techniques specifically when there is little or no prior knowledge about data distribution.

  19. Competing growth processes induced by next-nearest-neighbor interactions: Effects on meandering wavelength and stiffness

    Science.gov (United States)

    Blel, Sonia; Hamouda, Ajmi BH.; Mahjoub, B.; Einstein, T. L.

    2017-02-01

    In this paper we explore the meandering instability of vicinal steps with a kinetic Monte Carlo simulations (kMC) model including the attractive next-nearest-neighbor (NNN) interactions. kMC simulations show that increase of the NNN interaction strength leads to considerable reduction of the meandering wavelength and to weaker dependence of the wavelength on the deposition rate F. The dependences of the meandering wavelength on the temperature and the deposition rate obtained with simulations are in good quantitative agreement with the experimental result on the meandering instability of Cu(0 2 24) [T. Maroutian et al., Phys. Rev. B 64, 165401 (2001), 10.1103/PhysRevB.64.165401]. The effective step stiffness is found to depend not only on the strength of NNN interactions and the Ehrlich-Schwoebel barrier, but also on F. We argue that attractive NNN interactions intensify the incorporation of adatoms at step edges and enhance step roughening. Competition between NNN and nearest-neighbor interactions results in an alternative form of meandering instability which we call "roughening-limited" growth, rather than attachment-detachment-limited growth that governs the Bales-Zangwill instability. The computed effective wavelength and the effective stiffness behave as λeff˜F-q and β˜eff˜F-p , respectively, with q ≈p /2 .

  20. Neighbor Detection Induces Organ-Specific Transcriptomes, Revealing Patterns Underlying Hypocotyl-Specific Growth.

    Science.gov (United States)

    Kohnen, Markus V; Schmid-Siegert, Emanuel; Trevisan, Martine; Petrolati, Laure Allenbach; Sénéchal, Fabien; Müller-Moulé, Patricia; Maloof, Julin; Xenarios, Ioannis; Fankhauser, Christian

    2016-12-01

    In response to neighbor proximity, plants increase the growth of specific organs (e.g., hypocotyls) to enhance access to sunlight. Shade enhances the activity of Phytochrome Interacting Factors (PIFs) by releasing these bHLH transcription factors from phytochrome B-mediated inhibition. PIFs promote elongation by inducing auxin production in cotyledons. In order to elucidate spatiotemporal aspects of the neighbor proximity response, we separately analyzed gene expression patterns in the major light-sensing organ (cotyledons) and in rapidly elongating hypocotyls of Arabidopsis thaliana PIFs initiate transcriptional reprogramming in both organs within 15 min, comprising regulated expression of several early auxin response genes. This suggests that hypocotyl growth is elicited by both local and distal auxin signals. We show that cotyledon-derived auxin is both necessary and sufficient to initiate hypocotyl growth, but we also provide evidence for the functional importance of the local PIF-induced response. With time, the transcriptional response diverges increasingly between organs. We identify genes whose differential expression may underlie organ-specific elongation. Finally, we uncover a growth promotion gene expression signature shared between different developmentally regulated growth processes and responses to the environment in different organs. © 2016 American Society of Plant Biologists. All rights reserved.

  1. Spectral neighbor analysis method for automated generation of quantum-accurate interatomic potentials

    International Nuclear Information System (INIS)

    Thompson, A.P.; Swiler, L.P.; Trott, C.R.; Foiles, S.M.; Tucker, G.J.

    2015-01-01

    We present a new interatomic potential for solids and liquids called Spectral Neighbor Analysis Potential (SNAP). The SNAP potential has a very general form and uses machine-learning techniques to reproduce the energies, forces, and stress tensors of a large set of small configurations of atoms, which are obtained using high-accuracy quantum electronic structure (QM) calculations. The local environment of each atom is characterized by a set of bispectrum components of the local neighbor density projected onto a basis of hyperspherical harmonics in four dimensions. The bispectrum components are the same bond-orientational order parameters employed by the GAP potential [1]. The SNAP potential, unlike GAP, assumes a linear relationship between atom energy and bispectrum components. The linear SNAP coefficients are determined using weighted least-squares linear regression against the full QM training set. This allows the SNAP potential to be fit in a robust, automated manner to large QM data sets using many bispectrum components. The calculation of the bispectrum components and the SNAP potential are implemented in the LAMMPS parallel molecular dynamics code. We demonstrate that a previously unnoticed symmetry property can be exploited to reduce the computational cost of the force calculations by more than one order of magnitude. We present results for a SNAP potential for tantalum, showing that it accurately reproduces a range of commonly calculated properties of both the crystalline solid and the liquid phases. In addition, unlike simpler existing potentials, SNAP correctly predicts the energy barrier for screw dislocation migration in BCC tantalum

  2. Exposure measurement in the neighboring hospital beds during an x-ray procedure in hospitalization unit

    Energy Technology Data Exchange (ETDEWEB)

    Goto, Rafael E.; Capeleti, Felipe F.; Cabete, Henrique V., E-mail: rafael.goto@fcmsantacasasp.edu.br, E-mail: felipe.capeleti@fcmsantacasasp.edu.br, E-mail: henrique@gmpbrasil.com.br [Faculdade de Ciencias Medicas da Santa Casa Sao Paulo, SP (Brazil); GMP Consultoria em Radioprotecao e Fisica Medica e Assessoria LTDA, Sao Paulo, SP (Brazil)

    2017-11-01

    There are lots of discussion about the exposure in hospitalization units in Brazil, especially around labor legislation and economic advantages of unhealthiness. With the attention focused on hospitalized patients, there were measured the exposure in neighboring beds of the patient submitted to an X-ray procedure with a mobile X-ray system that could be used to illustrate the discussion with consistent values. The most common X-ray procedure made in hospitalization units are chests images with techniques between 70 to 120 kV and 5 to 20 mAs. The measurement was made during routine exposure and simulations using a scattering phantom with Radcal AccuPro electrometer and 1800cc ionization chamber in a private hospital and a philanthropic hospital, both in Sao Paulo, Brazil. The ionization chambers are placed at 2 meters distance of the patient exposed of both sides during the routine procedure. During the simulation, a nylon phantom of 20 centimeters thick and 30 x 30 cm² size was placed on the bed, a typical exposure technique was used and the exposure was measured surrounding the phantom at 0.6, 1.0 and 2.0 meters distance for scattered radiation characterization. Initial results showed that the neighboring exposure at about 2 meters distance from the exposed patient bed have low values, even when exposure is integrated during the length of hospital stay. Therefore, the exposure in hospitalization units are very low compared to the exams doses. (author). (author)

  3. Carbon-hydrogen defects with a neighboring oxygen atom in n-type Si

    Science.gov (United States)

    Gwozdz, K.; Stübner, R.; Kolkovsky, Vl.; Weber, J.

    2017-07-01

    We report on the electrical activation of neutral carbon-oxygen complexes in Si by wet-chemical etching at room temperature. Two deep levels, E65 and E75, are observed by deep level transient spectroscopy in n-type Czochralski Si. The activation enthalpies of E65 and E75 are obtained as EC-0.11 eV (E65) and EC-0.13 eV (E75). The electric field dependence of their emission rates relates both levels to single acceptor states. From the analysis of the depth profiles, we conclude that the levels belong to two different defects, which contain only one hydrogen atom. A configuration is proposed, where the CH1BC defect, with hydrogen in the bond-centered position between neighboring C and Si atoms, is disturbed by interstitial oxygen in the second nearest neighbor position to substitutional carbon. The significant reduction of the CH1BC concentration in samples with high oxygen concentrations limits the use of this defect for the determination of low concentrations of substitutional carbon in Si samples.

  4. Disentangling neighbors and extended range density oscillations in monatomic amorphous semiconductors.

    Science.gov (United States)

    Roorda, S; Martin, C; Droui, M; Chicoine, M; Kazimirov, A; Kycia, S

    2012-06-22

    High energy x-ray diffraction measurements of pure amorphous Ge were made and its radial distribution function (RDF) was determined at high resolution, revealing new information on the atomic structure of amorphous semiconductors. Fine structure in the second peak in the RDF provides evidence that a fraction of third neighbors are closer than some second neighbors; taking this into account leads to a narrow distribution of tetrahedral bond angles, (8.5 ± 0.1)°. A small peak which appears near 5 Å upon thermal annealing shows that some ordering in the dihedral bond-angle distribution takes place during structural relaxation. Extended range order is detected (in both a-Ge and a-Si) which persists to beyond 20 Å, and both the periodicity and its decay length increase upon thermal annealing. Previously, the effect of structural relaxation was only detected at intermediate range, involving reduced tetrahedral bond-angle distortions. These results enhance our understanding of the atomic order in continuous random networks and place significantly more stringent requirements on computer models intending to describe these networks, or their alternatives which attempt to describe the structure in terms of an arrangement of paracrystals.

  5. Mapping DNA methylation by transverse current sequencing: Reduction of noise from neighboring nucleotides

    Science.gov (United States)

    Alvarez, Jose; Massey, Steven; Kalitsov, Alan; Velev, Julian

    Nanopore sequencing via transverse current has emerged as a competitive candidate for mapping DNA methylation without needed bisulfite-treatment, fluorescent tag, or PCR amplification. By eliminating the error producing amplification step, long read lengths become feasible, which greatly simplifies the assembly process and reduces the time and the cost inherent in current technologies. However, due to the large error rates of nanopore sequencing, single base resolution has not been reached. A very important source of noise is the intrinsic structural noise in the electric signature of the nucleotide arising from the influence of neighboring nucleotides. In this work we perform calculations of the tunneling current through DNA molecules in nanopores using the non-equilibrium electron transport method within an effective multi-orbital tight-binding model derived from first-principles calculations. We develop a base-calling algorithm accounting for the correlations of the current through neighboring bases, which in principle can reduce the error rate below any desired precision. Using this method we show that we can clearly distinguish DNA methylation and other base modifications based on the reading of the tunneling current.

  6. Data delivery method based on neighbor nodes' information in a mobile ad hoc network.

    Science.gov (United States)

    Kashihara, Shigeru; Hayashi, Takuma; Taenaka, Yuzo; Okuda, Takeshi; Yamaguchi, Suguru

    2014-01-01

    This paper proposes a data delivery method based on neighbor nodes' information to achieve reliable communication in a mobile ad hoc network (MANET). In a MANET, it is difficult to deliver data reliably due to instabilities in network topology and wireless network condition which result from node movement. To overcome such unstable communication, opportunistic routing and network coding schemes have lately attracted considerable attention. Although an existing method that employs such schemes, MAC-independent opportunistic routing and encoding (MORE), Chachulski et al. (2007), improves the efficiency of data delivery in an unstable wireless mesh network, it does not address node movement. To efficiently deliver data in a MANET, the method proposed in this paper thus first employs the same opportunistic routing and network coding used in MORE and also uses the location information and transmission probabilities of neighbor nodes to adapt to changeable network topology and wireless network condition. The simulation experiments showed that the proposed method can achieve efficient data delivery with low network load when the movement speed is relatively slow.

  7. Data Delivery Method Based on Neighbor Nodes’ Information in a Mobile Ad Hoc Network

    Directory of Open Access Journals (Sweden)

    Shigeru Kashihara

    2014-01-01

    Full Text Available This paper proposes a data delivery method based on neighbor nodes’ information to achieve reliable communication in a mobile ad hoc network (MANET. In a MANET, it is difficult to deliver data reliably due to instabilities in network topology and wireless network condition which result from node movement. To overcome such unstable communication, opportunistic routing and network coding schemes have lately attracted considerable attention. Although an existing method that employs such schemes, MAC-independent opportunistic routing and encoding (MORE, Chachulski et al. (2007, improves the efficiency of data delivery in an unstable wireless mesh network, it does not address node movement. To efficiently deliver data in a MANET, the method proposed in this paper thus first employs the same opportunistic routing and network coding used in MORE and also uses the location information and transmission probabilities of neighbor nodes to adapt to changeable network topology and wireless network condition. The simulation experiments showed that the proposed method can achieve efficient data delivery with low network load when the movement speed is relatively slow.

  8. Power-Controlled MAC Protocols with Dynamic Neighbor Prediction for Ad hoc Networks

    Institute of Scientific and Technical Information of China (English)

    LI Meng; ZHANG Lin; XIAO Yong-kang; SHAN Xiu-ming

    2004-01-01

    Energy and bandwidth are the scarce resources in ad hoc networks because most of the mobile nodes are battery-supplied and share the exclusive wireless medium. Integrating the power control into MAC protocol is a promising technique to fully exploit these precious resources of ad hoc wireless networks. In this paper, a new intelligent power-controlled Medium Access Control (MAC) (iMAC) protocol with dynamic neighbor prediction is proposed. Through the elaborate design of the distributed transmit-receive strategy of mobile nodes, iMAC greatly outperforms the prevailing IEEE 802.11 MAC protocols in not only energy conservation but also network throughput. Using the Dynamic Neighbor Prediction (DNP), iMAC performs well in mobile scenes. To the best of our knowledge, iMAC is the first protocol that considers the performance deterioration of power-controlled MAC protocols in mobile scenes and then proposes a solution. Simulation results indicate that DNP is important and necessary for power-controlled MAC protocols in mobile ad hoc networks.

  9. Sequential nearest-neighbor effects on computed {sup 13}C{sup {alpha}} chemical shifts

    Energy Technology Data Exchange (ETDEWEB)

    Vila, Jorge A. [Cornell University, Baker Laboratory of Chemistry and Chemical Biology (United States); Serrano, Pedro; Wuethrich, Kurt [The Scripps Research Institute, Department of Molecular Biology (United States); Scheraga, Harold A., E-mail: has5@cornell.ed [Cornell University, Baker Laboratory of Chemistry and Chemical Biology (United States)

    2010-09-15

    To evaluate sequential nearest-neighbor effects on quantum-chemical calculations of {sup 13}C{sup {alpha}} chemical shifts, we selected the structure of the nucleic acid binding (NAB) protein from the SARS coronavirus determined by NMR in solution (PDB id 2K87). NAB is a 116-residue {alpha}/{beta} protein, which contains 9 prolines and has 50% of its residues located in loops and turns. Overall, the results presented here show that sizeable nearest-neighbor effects are seen only for residues preceding proline, where Pro introduces an overestimation, on average, of 1.73 ppm in the computed {sup 13}C{sup {alpha}} chemical shifts. A new ensemble of 20 conformers representing the NMR structure of the NAB, which was calculated with an input containing backbone torsion angle constraints derived from the theoretical {sup 13}C{sup {alpha}} chemical shifts as supplementary data to the NOE distance constraints, exhibits very similar topology and comparable agreement with the NOE constraints as the published NMR structure. However, the two structures differ in the patterns of differences between observed and computed {sup 13}C{sup {alpha}} chemical shifts, {Delta}{sub ca,i}, for the individual residues along the sequence. This indicates that the {Delta}{sub ca,i} -values for the NAB protein are primarily a consequence of the limited sampling by the bundles of 20 conformers used, as in common practice, to represent the two NMR structures, rather than of local flaws in the structures.

  10. δ-Generalized Labeled Multi-Bernoulli Filter Using Amplitude Information of Neighboring Cells

    Directory of Open Access Journals (Sweden)

    Chao Liu

    2018-04-01

    Full Text Available The amplitude information (AI of echoed signals plays an important role in radar target detection and tracking. A lot of research shows that the introduction of AI enables the tracking algorithm to distinguish targets from clutter better and then improves the performance of data association. The current AI-aided tracking algorithms only consider the signal amplitude in the range-azimuth cell where measurement exists. However, since radar echoes always contain backscattered signals from multiple cells, the useful information of neighboring cells would be lost if directly applying those existing methods. In order to solve this issue, a new δ-generalized labeled multi-Bernoulli (δ-GLMB filter is proposed. It exploits the AI of radar echoes from neighboring cells to construct a united amplitude likelihood ratio, and then plugs it into the update process and the measurement-track assignment cost matrix of the δ-GLMB filter. Simulation results show that the proposed approach has better performance in target’s state and number estimation than that of the δ-GLMB only using single-cell AI in low signal-to-clutter-ratio (SCR environment.

  11. Hyperplane distance neighbor clustering based on local discriminant analysis for complex chemical processes monitoring

    International Nuclear Information System (INIS)

    Lu, Chunhong; Xiao, Shaoqing; Gu, Xiaofeng

    2014-01-01

    The collected training data often include both normal and faulty samples for complex chemical processes. However, some monitoring methods, such as partial least squares (PLS), principal component analysis (PCA), independent component analysis (ICA) and Fisher discriminant analysis (FDA), require fault-free data to build the normal operation model. These techniques are applicable after the preliminary step of data clustering is applied. We here propose a novel hyperplane distance neighbor clustering (HDNC) based on the local discriminant analysis (LDA) for chemical process monitoring. First, faulty samples are separated from normal ones using the HDNC method. Then, the optimal subspace for fault detection and classification can be obtained using the LDA approach. The proposed method takes the multimodality within the faulty data into account, and thus improves the capability of process monitoring significantly. The HDNC-LDA monitoring approach is applied to two simulation processes and then compared with the conventional FDA based on the K-nearest neighbor (KNN-FDA) method. The results obtained in two different scenarios demonstrate the superiority of the HDNC-LDA approach in terms of fault detection and classification accuracy

  12. A Machine Learning Ensemble Classifier for Early Prediction of Diabetic Retinopathy.

    Science.gov (United States)

    S K, Somasundaram; P, Alli

    2017-11-09

    The main complication of diabetes is Diabetic retinopathy (DR), retinal vascular disease and it leads to the blindness. Regular screening for early DR disease detection is considered as an intensive labor and resource oriented task. Therefore, automatic detection of DR diseases is performed only by using the computational technique is the great solution. An automatic method is more reliable to determine the presence of an abnormality in Fundus images (FI) but, the classification process is poorly performed. Recently, few research works have been designed for analyzing texture discrimination capacity in FI to distinguish the healthy images. However, the feature extraction (FE) process was not performed well, due to the high dimensionality. Therefore, to identify retinal features for DR disease diagnosis and early detection using Machine Learning and Ensemble Classification method, called, Machine Learning Bagging Ensemble Classifier (ML-BEC) is designed. The ML-BEC method comprises of two stages. The first stage in ML-BEC method comprises extraction of the candidate objects from Retinal Images (RI). The candidate objects or the features for DR disease diagnosis include blood vessels, optic nerve, neural tissue, neuroretinal rim, optic disc size, thickness and variance. These features are initially extracted by applying Machine Learning technique called, t-distributed Stochastic Neighbor Embedding (t-SNE). Besides, t-SNE generates a probability distribution across high-dimensional images where the images are separated into similar and dissimilar pairs. Then, t-SNE describes a similar probability distribution across the points in the low-dimensional map. This lessens the Kullback-Leibler divergence among two distributions regarding the locations of the points on the map. The second stage comprises of application of ensemble classifiers to the extracted features for providing accurate analysis of digital FI using machine learning. In this stage, an automatic detection

  13. Intelligence for embedded systems a methodological approach

    CERN Document Server

    Alippi, Cesare

    2014-01-01

    Addressing current issues of which any engineer or computer scientist should be aware, this monograph is a response to the need to adopt a new computational paradigm as the methodological basis for designing pervasive embedded systems with sensor capabilities. The requirements of this paradigm are to control complexity, to limit cost and energy consumption, and to provide adaptation and cognition abilities allowing the embedded system to interact proactively with the real world. The quest for such intelligence requires the formalization of a new generation of intelligent systems able to exploit advances in digital architectures and in sensing technologies. The book sheds light on the theory behind intelligence for embedded systems with specific focus on: ·        robustness (the robustness of a computational flow and its evaluation); ·        intelligence (how to mimic the adaptation and cognition abilities of the human brain), ·        the capacity to learn in non-stationary and evolv...

  14. Embedding of radioactive wastes by thermosetting resins

    International Nuclear Information System (INIS)

    Baer, A.; Traxler, A.; Limongi, A.; Thiery, D.

    The process for embedding radioactive wastes in thermosetting resins perfected and applied at the Grenoble Nuclear Research Center and its application to the treatment of radioactive wastes from Light-Water Nuclear Power Plants (PWR and BWR) are presented. The various types of wastes are enumerated and their activities and quantities are estimated: evaporator concentrates, ion exchange resins, filtration sludges, filters, various solid wastes, etc. The authors review the orientations of the research performed and indicate, for each type of waste considered, the cycle of treatment operations from rendering the radioelements insoluble to drying the concentrates to final embedding. The operational safety of the process and the safety of transport and storage of the embedded wastes are investigated. The essential technical features concerning the safety of the installation and of the final product obtained are presented. In particular, results are presented from tests of resistance to fire, irradiation, leaching, etc., these being characteristics which represent safety criteria. The economic aspects of the process are considered by presenting the influences of the reduction of volume and weight of wastes to be stored, simplicity of installations and cost of primary materials

  15. Costs and benefits of embedded generation

    International Nuclear Information System (INIS)

    1996-01-01

    Ilex Associates has been appointed by ETSU to examine the underlying costs and benefits of embedded generation (i.e. generation which is directly connected into a REF's distribution network instead of the national transmission network). The main impetus for this work stems from the need to understand the true value of embedded generation in time to review the development of further NFFO contracts following the expiry of the, so called, ''nuclear levy''. This is particularly important at this time because of the view expressed by the Director General of Electricity Supply (DGES) that to continue to receive support renewables technologies should be able to demonstrate good progress in converging towards a market price. The prime objectives of this study are to determine the costs and benefits of connecting and operating a generator that is embedded in a local Regional Electricity Company's (REC's) distribution network compared to the alternative option of providing electricity from a large generating station which is connected directly to the transmission system (and colloquially known as directly connected generation). (UK)

  16. Platelet lysate embedded scaffolds for skin regeneration.

    Science.gov (United States)

    Sandri, Giuseppina; Bonferoni, Maria Cristina; Rossi, Silvia; Ferrari, Franca; Mori, Michela; Cervio, Marila; Riva, Federica; Liakos, Ioannis; Athanassiou, Athanassia; Saporito, Francesca; Marini, Lara; Caramella, Carla

    2015-04-01

    The work presents the development of acellular scaffolds extemporaneously embedded with platelet lysate (PL), as an innovative approach in the field of tissue regeneration/reparation. PL embedded scaffolds should have a tridimensional architecture to support cell migration and growth, in order to restore skin integrity. For this reason, chondroitin sulfate (CS) was associated with sodium alginate (SA) to prepare highly porous systems. The developed scaffolds were characterized for chemical stability to γ-radiation, morphology, hydration and mechanical properties. Moreover, the capability of fibroblasts and endothelial cells to populate the scaffold was evaluated by means of proliferation test 3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyltetrazolium bromide (MTT) and confocal laser scanning microscopy study. The scaffolds, not altered by sterilization, were characterized by limited swelling and high flexibility, by foam-like structure with bubbles that formed a high surface area and irregular texture suitable for cell adhesion. Cell growth and scaffold population were evident on the bubble surface, where the cells appeared anchored to the scaffold structure. Scaffold network based on CS and SA demonstrated to be an effective support to enhance and to allow fibroblasts and endothelial cells (human umbilical vein endothelial cells, HUVEC) adhesion and proliferation. In particular, it could be hypothesized that cell adhesion was facilitated by the synergic effect of PL and CS. Although further in vivo evaluation is needed, on the basis of in vitro results, PL embedded scaffolds seem promising systems for skin wound healing.

  17. Societal embedding of climate-friendly innovations

    International Nuclear Information System (INIS)

    Vaeyrynen, E.; Kivisaari, Sirkku; Lovio, R.

    2002-01-01

    This project assesses the possibilities of constructing a market for climate-friendly energy technologies by applying the process of 'societal embedding of innovations'. The term refers to an interactive learning process amongst three groups of key actors: producers, users and societal actors. Their co-operation shapes the innovation to fit the needs of the market and contributes to creation of conditions in which the innovation can be adopted. The project consists of two case studies: (1) Shaping of the ESCO energy service concept in Finnish municipalities and (2) Increasing the use of wood pellets in single-family houses. The case studies have illustrated the possibilities and limitations concerning the application of societal embedding in the energy sector. The project indicates that societal embedding may promote the implementation of climate-friendly energy technologies in at least three ways. Firstly, the process mobilises key actors to cooperation. This generates interactive learning on the problem and its solving. Market construction is forged ahead by mutual adaptation of the innovation and its environment. Secondly, this approach offers a tool to examine the societal quality of the innovation, a question related vitally to climate change. Thirdly, by producing new knowledge of the needs on the market this approach supports the societal actors in choosing different instruments to induce the intended transition to sustainability. (orig.)

  18. Applications of scenarios in early embedded system design space exploration

    NARCIS (Netherlands)

    van Stralen, P.

    2014-01-01

    One of the challenges during embedded system design is the application driven design. Due to the application driven design, the objectives that are steering the design of an embedded system are mainly based on the needs of the application(s). Examples of embedded system objectives are performance,

  19. Is embedding entailed in consumer valuation of food safety characteristics?

    DEFF Research Database (Denmark)

    Mørkbak, Morten Raun; Christensen, Tove; Gyrd-Hansen, Dorte

    2011-01-01

    Consumers' preferences for food safety characteristics are investigated with a particular focus on the existence of an embedding effect. Embedding exists if consumer valuation of food safety is insensitive to scope. We conduct between-attribute external tests for embedding in two choice experiments...

  20. Programming Embedded Systems With C and GNU Development Tools

    CERN Document Server

    Barr, Michael

    2009-01-01

    Whether you're writing your first embedded program, designing the latest generation of hand-held whatchamacalits, or managing the people who do, this book is for you. Programming Embedded Systems will help you develop the knowledge and skills you need to achieve proficiency with embedded software.

  1. Rhombic embeddings of planar graphs with faces of degree 4

    OpenAIRE

    Kenyon, Richard; Schlenker, Jean-Marc

    2003-01-01

    Given a finite or infinite planar graph all of whose faces have degree 4, we study embeddings in the plane in which all edges have length 1, that is, in which every face is a rhombus. We give a necessary and sufficient condition for the existence of such an embedding, as well as a description of the set of all such embeddings.

  2. Positive indirect interactions between neighboring plant species via a lizard pollinator.

    OpenAIRE

    Hansen, D M; Kiesbüy, H C; Jones, C G; Müller, C B

    2007-01-01

    In natural communities, species are embedded in networks of direct and indirect interactions. Most studies on indirect interactions have focused on how they affect predator-prey or competitive relationships. However, it is equally likely that indirect interactions play an important structuring role in mutualistic relationships in a natural community. We demonstrate experimentally that on a small spatial scale, dense thickets of endemic Pandanus plants have a strong positive trait-mediated ind...

  3. Embedded Linux platform for data acquisition systems

    International Nuclear Information System (INIS)

    Patel, Jigneshkumar J.; Reddy, Nagaraj; Kumari, Praveena; Rajpal, Rachana; Pujara, Harshad; Jha, R.; Kalappurakkal, Praveen

    2014-01-01

    Highlights: • The design and the development of data acquisition system on FPGA based reconfigurable hardware platform. • Embedded Linux configuration and compilation for FPGA based systems. • Hardware logic IP core and its Linux device driver development for the external peripheral to interface it with the FPGA based system. - Abstract: This scalable hardware–software system is designed and developed to explore the emerging open standards for data acquisition requirement of Tokamak experiments. To address the future need for a scalable data acquisition and control system for fusion experiments, we have explored the capability of software platform using Open Source Embedded Linux Operating System on a programmable hardware platform such as FPGA. The idea was to identify the platform which can be customizable, flexible and scalable to support the data acquisition system requirements. To do this, we have selected FPGA based reconfigurable and scalable hardware platform to design the system with Embedded Linux based operating system for flexibility in software development and Gigabit Ethernet interface for high speed data transactions. The proposed hardware–software platform using FPGA and Embedded Linux OS offers a single chip solution with processor, peripherals such ADC interface controller, Gigabit Ethernet controller, memory controller amongst other peripherals. The Embedded Linux platform for data acquisition is implemented and tested on a Virtex-5 FXT FPGA ML507 which has PowerPC 440 (PPC440) [2] hard block on FPGA. For this work, we have used the Linux Kernel version 2.6.34 with BSP support for the ML507 platform. It is downloaded from the Xilinx [1] GIT server. Cross-compiler tool chain is created using the Buildroot scripts. The Linux Kernel and Root File System are configured and compiled using the cross-tools to support the hardware platform. The Analog to Digital Converter (ADC) IO module is designed and interfaced with the ML507 through Xilinx

  4. Embedded Linux platform for data acquisition systems

    Energy Technology Data Exchange (ETDEWEB)

    Patel, Jigneshkumar J., E-mail: jjp@ipr.res.in [Institute for Plasma Research, Gandhinagar, Gujarat (India); Reddy, Nagaraj, E-mail: nagaraj.reddy@coreel.com [Sandeepani School of Embedded System Design, Bangalore, Karnataka (India); Kumari, Praveena, E-mail: praveena@ipr.res.in [Institute for Plasma Research, Gandhinagar, Gujarat (India); Rajpal, Rachana, E-mail: rachana@ipr.res.in [Institute for Plasma Research, Gandhinagar, Gujarat (India); Pujara, Harshad, E-mail: pujara@ipr.res.in [Institute for Plasma Research, Gandhinagar, Gujarat (India); Jha, R., E-mail: rjha@ipr.res.in [Institute for Plasma Research, Gandhinagar, Gujarat (India); Kalappurakkal, Praveen, E-mail: praveen.k@coreel.com [Sandeepani School of Embedded System Design, Bangalore, Karnataka (India)

    2014-05-15

    Highlights: • The design and the development of data acquisition system on FPGA based reconfigurable hardware platform. • Embedded Linux configuration and compilation for FPGA based systems. • Hardware logic IP core and its Linux device driver development for the external peripheral to interface it with the FPGA based system. - Abstract: This scalable hardware–software system is designed and developed to explore the emerging open standards for data acquisition requirement of Tokamak experiments. To address the future need for a scalable data acquisition and control system for fusion experiments, we have explored the capability of software platform using Open Source Embedded Linux Operating System on a programmable hardware platform such as FPGA. The idea was to identify the platform which can be customizable, flexible and scalable to support the data acquisition system requirements. To do this, we have selected FPGA based reconfigurable and scalable hardware platform to design the system with Embedded Linux based operating system for flexibility in software development and Gigabit Ethernet interface for high speed data transactions. The proposed hardware–software platform using FPGA and Embedded Linux OS offers a single chip solution with processor, peripherals such ADC interface controller, Gigabit Ethernet controller, memory controller amongst other peripherals. The Embedded Linux platform for data acquisition is implemented and tested on a Virtex-5 FXT FPGA ML507 which has PowerPC 440 (PPC440) [2] hard block on FPGA. For this work, we have used the Linux Kernel version 2.6.34 with BSP support for the ML507 platform. It is downloaded from the Xilinx [1] GIT server. Cross-compiler tool chain is created using the Buildroot scripts. The Linux Kernel and Root File System are configured and compiled using the cross-tools to support the hardware platform. The Analog to Digital Converter (ADC) IO module is designed and interfaced with the ML507 through Xilinx

  5. Influence of parasite density and sample storage time on the reliability of Entamoeba histolytica-specific PCR from formalin-fixed and paraffin-embedded tissues.

    Science.gov (United States)

    Frickmann, Hagen; Tenner-Racz, Klara; Eggert, Petra; Schwarz, Norbert G; Poppert, Sven; Tannich, Egbert; Hagen, Ralf M

    2013-12-01

    We report on the reliability of polymerase chain reaction (PCR) for the detection of Entamoeba histolytica from formalin-fixed, paraffin-embedded tissue in comparison with microscopy and have determined predictors that may influence PCR results. E. histolytica-specific and Entamoeba dispar-specific real-time PCR and microscopy from adjacent histologic sections were performed using a collection of formalin-fixed, paraffin-embedded tissue specimens obtained from patients with invasive amebiasis. Specimens had been collected during the previous 4 decades. Association of sample age, parasite density, and reliability of PCR was analyzed. E. histolytica PCR was positive in 20 of 34 biopsies (58.8%); 2 of these 20 were microscopically negative for amebae in neighboring tissue sections. PCR was negative in 9 samples with visible amebae in neighboring sections and in 5 samples without visible parasites in neighboring sections. PCR was negative in all specimens that were older than 3 decades. Low parasite counts and sample ages older than 20 years were predictors for false-negative PCR results. All samples were negative for E. dispar DNA. PCR is suitable for the detection of E. histolytica in formalin-fixed, paraffin-embedded tissue samples that are younger than 2 decades and that contain intermediate to high parasite numbers. Negative results in older samples were due to progressive degradation of DNA over time as indicated by control PCRs targeting the human 18S rRNA gene. Moreover, our findings support previous suggestions that only E. histolytica but not E. dispar is responsible for invasive amebiasis.

  6. Modern Embedded Computing Designing Connected, Pervasive, Media-Rich Systems

    CERN Document Server

    Barry, Peter

    2012-01-01

    Modern embedded systems are used for connected, media-rich, and highly integrated handheld devices such as mobile phones, digital cameras, and MP3 players. All of these embedded systems require networking, graphic user interfaces, and integration with PCs, as opposed to traditional embedded processors that can perform only limited functions for industrial applications. While most books focus on these controllers, Modern Embedded Computing provides a thorough understanding of the platform architecture of modern embedded computing systems that drive mobile devices. The book offers a comprehen

  7. Projective embeddings of homogeneous spaces with small boundary

    International Nuclear Information System (INIS)

    Arzhantsev, Ivan V

    2009-01-01

    We study open equivariant projective embeddings of homogeneous spaces such that the complement of the open orbit has codimension at least 2. We establish a criterion for the existence of such an embedding, prove that the set of isomorphism classes of such embeddings is finite, and give a construction of the embeddings in terms of Geometric Invariant Theory. A generalization of Cox's construction and the theory of bunched rings enable us to describe in combinatorial terms the basic geometric properties of embeddings with small boundary

  8. Methodology and Supporting Toolset Advancing Embedded Systems Quality

    DEFF Research Database (Denmark)

    Berger, Michael Stübert; Soler, José; Brewka, Lukasz Jerzy

    2013-01-01

    Software quality is of primary importance in the development of embedded systems that are often used in safety-critical applications. Moreover, as the life cycle of embedded products becomes increasingly tighter, productivity and quality are simultaneously required and closely interrelated towards...... delivering competitive products. In this context, the MODUS (Methodology and supporting toolset advancing embedded systems quality) project aims to provide a pragmatic and viable solution that will allow SMEs to substantially improve their positioning in the embedded-systems development market. This paper...... will describe the MODUS project with focus on the technical methodologies that will be developed advancing embedded system quality....

  9. Quantum thetas on noncommutative Td with general embeddings

    International Nuclear Information System (INIS)

    Chang-Young, Ee; Kim, Hoil

    2008-01-01

    In this paper, we construct quantum theta functions over noncommutative T d with general embeddings. Manin has constructed quantum theta functions from the lattice embedding into vector space x finite group. We extend Manin's construction of quantum thetas to the case of general embedding of vector space x lattice x torus. It turns out that only for the vector space part of the embedding there exists the holomorphic theta vector, while for the lattice part there does not. Furthermore, the so-called quantum translations from embedding into the lattice part become non-additive, while those from the vector space part are additive

  10. Historical harvests reduce neighboring old-growth basal area across a forest landscape.

    Science.gov (United States)

    Bell, David M; Spies, Thomas A; Pabst, Robert

    2017-07-01

    While advances in remote sensing have made stand, landscape, and regional assessments of the direct impacts of disturbance on forests quite common, the edge influence of timber harvesting on the structure of neighboring unharvested forests has not been examined extensively. In this study, we examine the impact of historical timber harvests on basal area patterns of neighboring old-growth forests to assess the magnitude and scale of harvest edge influence in a forest landscape of western Oregon, USA. We used lidar data and forest plot measurements to construct 30-m resolution live tree basal area maps in lower and middle elevation mature and old-growth forests. We assessed how edge influence on total, upper canopy, and lower canopy basal area varied across this forest landscape as a function of harvest characteristics (i.e., harvest size and age) and topographic conditions in the unharvested area. Upper canopy, lower canopy, and total basal area increased with distance from harvest edge and elevation. Forests within 75 m of harvest edges (20% of unharvested forests) had 4% to 6% less live tree basal area compared with forest interiors. An interaction between distance from harvest edge and elevation indicated that elevation altered edge influence in this landscape. We observed a positive edge influence at low elevations (800 m). Surprisingly, we found no or weak effects of harvest age (13-60 yr) and harvest area (0.2-110 ha) on surrounding unharvested forest basal area, implying that edge influence was relatively insensitive to the scale of disturbance and multi-decadal recovery processes. Our study indicates that the edge influence of past clearcutting on the structure of neighboring uncut old-growth forests is widespread and persistent. These indirect and diffuse legacies of historical timber harvests complicate forest management decision-making in old-growth forest landscapes by broadening the traditional view of stand boundaries. Furthermore, the consequences

  11. Allotment gardening and health: a comparative survey among allotment gardeners and their neighbors without an allotment.

    Science.gov (United States)

    van den Berg, Agnes E; van Winsum-Westra, Marijke; de Vries, Sjerp; van Dillen, Sonja M E

    2010-11-23

    The potential contribution of allotment gardens to a healthy and active life-style is increasingly recognized, especially for elderly populations. However, few studies have empirically examined beneficial effects of allotment gardening. In the present study the health, well-being and physical activity of older and younger allotment gardeners was compared to that of controls without an allotment. A survey was conducted among 121 members of 12 allotment sites in the Netherlands and a control group of 63 respondents without an allotment garden living next to the home addresses of allotment gardeners. The survey included five self-reported health measures (perceived general health, acute health complaints, physical constraints, chronic illnesses, and consultations with GP), four self-reported well-being measures (stress, life satisfaction, loneliness, and social contacts with friends) and one measure assessing self-reported levels of physical activity in summer. Respondents were divided into a younger and older group at the median of 62 years which equals the average retirement age in the Netherlands. After adjusting for income, education level, gender, stressful life events, physical activity in winter, and access to a garden at home as covariates, both younger and older allotment gardeners reported higher levels of physical activity during the summer than neighbors in corresponding age categories. The impacts of allotment gardening on health and well-being were moderated by age. Allotment gardeners of 62 years and older scored significantly or marginally better on all measures of health and well-being than neighbors in the same age category. Health and well-being of younger allotment gardeners did not differ from younger neighbors. The greater health and well-being benefits of allotment gardening for older gardeners may be related to the finding that older allotment gardeners were more oriented towards gardening and being active, and less towards passive relaxation

  12. Allotment gardening and health: a comparative survey among allotment gardeners and their neighbors without an allotment

    Directory of Open Access Journals (Sweden)

    van Winsum-Westra Marijke

    2010-11-01

    Full Text Available Abstract Background The potential contribution of allotment gardens to a healthy and active life-style is increasingly recognized, especially for elderly populations. However, few studies have empirically examined beneficial effects of allotment gardening. In the present study the health, well-being and physical activity of older and younger allotment gardeners was compared to that of controls without an allotment. Methods A survey was conducted among 121 members of 12 allotment sites in the Netherlands and a control group of 63 respondents without an allotment garden living next to the home addresses of allotment gardeners. The survey included five self-reported health measures (perceived general health, acute health complaints, physical constraints, chronic illnesses, and consultations with GP, four self-reported well-being measures (stress, life satisfaction, loneliness, and social contacts with friends and one measure assessing self-reported levels of physical activity in summer. Respondents were divided into a younger and older group at the median of 62 years which equals the average retirement age in the Netherlands. Results After adjusting for income, education level, gender, stressful life events, physical activity in winter, and access to a garden at home as covariates, both younger and older allotment gardeners reported higher levels of physical activity during the summer than neighbors in corresponding age categories. The impacts of allotment gardening on health and well-being were moderated by age. Allotment gardeners of 62 years and older scored significantly or marginally better on all measures of health and well-being than neighbors in the same age category. Health and well-being of younger allotment gardeners did not differ from younger neighbors. The greater health and well-being benefits of allotment gardening for older gardeners may be related to the finding that older allotment gardeners were more oriented towards gardening

  13. ASSESSMENT OF SEISMIC ANALYSIS METHODOLOGIES FOR DEEPLY EMBEDDED NPP STRUCTURES

    International Nuclear Information System (INIS)

    XU, J.; MILLER, C.; COSTANTINO, C.; HOFMAYER, C.; GRAVES, H. NRC.

    2005-01-01

    Several of the new generation nuclear power plant designs have structural configurations which are proposed to be deeply embedded. Since current seismic analysis methodologies have been applied to shallow embedded structures (e.g., ASCE 4 suggest that simple formulations may be used to model embedment effect when the depth of embedment is less than 30% of its foundation radius), the US Nuclear Regulatory Commission is sponsoring a program at the Brookhaven National Laboratory with the objective of investigating the extent to which procedures acceptable for shallow embedment depths are adequate for larger embedment depths. This paper presents the results of a study comparing the response spectra obtained from two of the more popular analysis methods for structural configurations varying from shallow embedment to complete embedment. A typical safety related structure embedded in a soil profile representative of a typical nuclear power plant site was utilized in the study and the depths of burial (DOB) considered range from 25-100% the height of the structure. Included in the paper are: (1) the description of a simplified analysis and a detailed approach for the SSI analyses of a structure with various DOB, (2) the comparison of the analysis results for the different DOBs between the two methods, and (3) the performance assessment of the analysis methodologies for SSI analyses of deeply embedded structures. The resulting assessment from this study has indicated that simplified methods may be capable of capturing the seismic response for much deeper embedded structures than would be normally allowed by the standard practice

  14. Embeddings for the Schwarzschild metric: classification and new results

    International Nuclear Information System (INIS)

    Paston, S A; Sheykin, A A

    2012-01-01

    We suggest a method to search the embeddings of Riemannian spaces with a high enough symmetry in a flat ambient space. It is based on a procedure of construction surfaces with a given symmetry. The method is used to classify the embeddings of the Schwarzschild metric which have the symmetry of this solution, and all such embeddings in a six-dimensional ambient space (i.e. a space with a minimal possible dimension) are constructed. Four of the six possible embeddings are already known, while the two others are new. One of the new embeddings is asymptotically flat, while the other embeddings in a six-dimensional ambient space do not have this property. The asymptotically flat embedding can be of use in the analysis of the many-body problem, as well as for the development of gravity description as a theory of a surface in a flat ambient space. (paper)

  15. Obstacle Detection for Intelligent Transportation Systems Using Deep Stacked Autoencoder and k-Nearest Neighbor Scheme

    KAUST Repository

    Dairi, Abdelkader; Harrou, Fouzi; Sun, Ying; Senouci, Mohamed

    2018-01-01

    Obstacle detection is an essential element for the development of intelligent transportation systems so that accidents can be avoided. In this study, we propose a stereovisionbased method for detecting obstacles in urban environment. The proposed method uses a deep stacked auto-encoders (DSA) model that combines the greedy learning features with the dimensionality reduction capacity and employs an unsupervised k-nearest neighbors algorithm (KNN) to accurately and reliably detect the presence of obstacles. We consider obstacle detection as an anomaly detection problem. We evaluated the proposed method by using practical data from three publicly available datasets, the Malaga stereovision urban dataset (MSVUD), the Daimler urban segmentation dataset (DUSD), and Bahnhof dataset. Also, we compared the efficiency of DSA-KNN approach to the deep belief network (DBN)-based clustering schemes. Results show that the DSA-KNN is suitable to visually monitor urban scenes.

  16. Phosphorous vacancy nearest neighbor hopping induced instabilities in InP capacitors II. Computer simulation

    International Nuclear Information System (INIS)

    Juang, M.T.; Wager, J.F.; Van Vechten, J.A.

    1988-01-01

    Drain current drift in InP metal insulator semiconductor devices display distinct activation energies and pre-exponential factors. The authors have given evidence that these result from two physical mechanisms: thermionic tunneling of electrons into native oxide traps and phosphorous vacancy nearest neighbor hopping (PVNNH). They here present a computer simulation of the effect of the PVNHH mechanism on flatband voltage shift vs. bias stress time measurements. The simulation is based on an analysis of the kinetics of the PVNNH defect reaction sequence in which the electron concentration in the channel is related to the applied bias by a solution of the Poisson equation. The simulation demonstrates quantitatively that the temperature dependence of the flatband shift is associated with PVNNH for temperatures above room temperature

  17. Thermodynamics of alternating spin chains with competing nearest- and next-nearest-neighbor interactions: Ising model

    Science.gov (United States)

    Pini, Maria Gloria; Rettori, Angelo

    1993-08-01

    The thermodynamical properties of an alternating spin (S,s) one-dimensional (1D) Ising model with competing nearest- and next-nearest-neighbor interactions are exactly calculated using a transfer-matrix technique. In contrast to the case S=s=1/2, previously investigated by Harada, the alternation of different spins (S≠s) along the chain is found to give rise to two-peaked static structure factors, signaling the coexistence of different short-range-order configurations. The relevance of our calculations with regard to recent experimental data by Gatteschi et al. in quasi-1D molecular magnetic materials, R (hfac)3 NITEt (R=Gd, Tb, Dy, Ho, Er, . . .), is discussed; hfac is hexafluoro-acetylacetonate and NlTEt is 2-Ethyl-4,4,5,5-tetramethyl-4,5-dihydro-1H-imidazolyl-1-oxyl-3-oxide.

  18. Proteomic characterization of host response to Yersinia pestis and near neighbors

    International Nuclear Information System (INIS)

    Chromy, Brett A.; Perkins, Julie; Heidbrink, Jenny L.; Gonzales, Arlene D.; Murphy, Gloria A.; Fitch, J. Patrick; McCutchen-Maloney, Sandra L.

    2004-01-01

    Host-pathogen interactions result in protein expression changes within both the host and the pathogen. Here, results from proteomic characterization of host response following exposure to Yersinia pestis, the causative agent of plague, and to two near neighbors, Yersinia pseudotuberculosis and Yersinia enterocolitica, are reported. Human monocyte-like cells were chosen as a model for macrophage immune response to pathogen exposure. Two-dimensional electrophoresis followed by mass spectrometry was used to identify host proteins with differential expression following exposure to these three closely related Yersinia species. This comparative proteomic characterization of host response clearly shows that host protein expression patterns are distinct for the different pathogen exposures, and contributes to further understanding of Y. pestis virulence and host defense mechanisms. This work also lays the foundation for future studies aimed at defining biomarkers for presymptomatic detection of plague

  19. Tensile twin nucleation events coupled to neighboring slip observed in three dimensions

    International Nuclear Information System (INIS)

    Lind, J.; Li, S.F.; Pokharel, R.; Lienert, U.; Rollett, A.D.; Suter, R.M.

    2014-01-01

    Low-symmetry crystals and polycrystals have anisotropic mechanical properties which, given better understanding of their deformation modes, could lead to development of next generation materials. Understanding how grains in a bulk polycrystal interact will guide and improve material modeling. Here, we show that tensile twins, in hexagonal close-packed metals, form where the macroscopic stress does not generate appropriate shear stress and vice versa. We use non-destructive high-energy X-ray diffraction microscopy to map local crystal orientations in three dimensions in a series of tensile strain states in a zirconium polycrystal. Twins and intragranular orientation variations are observed and it is found that deformation-induced rotations in neighboring grains are spatially correlated with many twins. We conclude that deformation twinning involves complex multigrain interactions which must be included in polycrystal plasticity models

  20. Nearest neighbor spacing distributions of low-lying levels of vibrational nuclei

    International Nuclear Information System (INIS)

    Abul-Magd, A.Y.; Simbel, M.H.

    1996-01-01

    Energy-level statistics are considered for nuclei whose Hamiltonian is divided into intrinsic and collective-vibrational terms. The levels are described as a random superposition of independent sequences, each corresponding to a given number of phonons. The intrinsic motion is assumed chaotic. The level spacing distribution is found to be intermediate between the Wigner and Poisson distributions and similar in form to the spacing distribution of a system with classical phase space divided into separate regular and chaotic domains. We have obtained approximate expressions for the nearest neighbor spacing and cumulative spacing distribution valid when the level density is described by a constant-temperature formula and not involving additional free parameters. These expressions have been able to achieve good agreement with the experimental spacing distributions. copyright 1996 The American Physical Society

  1. Fringe field interference of neighbor magnets in China spallation neutron source

    International Nuclear Information System (INIS)

    Li, L.; Kang, W.; Wu, X.; Deng, C.D.; Li, S.; Yang, M.; Zhou, J.X.; Liu, Y.Q.; Wu, Y.W.

    2016-01-01

    In CSNS accelerator construction, the field measurement of all RCS magnets have been finished and the magnets have been installed in the tunnel before the end of 2015. The electromagnetic quadrupoles have a large aperture and the core-to-core distance between magnets is rather short in some places. The corrector magnet or the sextupole magnet is closer to one of the quadrupole magnets which caused certain interference. The interference caused by magnetic fringe field has been appeared and it becomes a significant issue in beam dynamics for beam loss control in this high-intensity proton accelerator. We have performed 3D computing simulations to study integral field distributions between the quadrupole and the corrector magnets, and the sextupole and the other quadrupole magnets. The effect of the magnetic fringe field and the interference has been investigated with different distances of the neighbor magnets. The simulation and the field measurement results will be introduced in this paper.

  2. A SURVEY ON DELAY AND NEIGHBOR NODE MONITORING BASED WORMHOLE ATTACK PREVENTION AND DETECTION

    Directory of Open Access Journals (Sweden)

    Sudhir T Bagade

    2016-12-01

    Full Text Available In Mobile Ad-hoc Networks (MANET, network layer attacks, for example wormhole attacks, disrupt the network routing operations and can be used for data theft. Wormhole attacks are of two types: hidden and exposed wormhole. There are various mechanisms in literature which are used to prevent and detect wormhole attacks. In this paper, we survey wormhole prevention and detection techniques and present our critical observations for each. These techniques are based on cryptographic mechanisms, monitoring of packet transmission delay and control packet forwarding behavior of neighbor nodes. We compare the techniques using the following criteria- extra resources needed applicability to different network topologies and routing protocols, prevention/detection capability, etc. We conclude the paper with potential research directions.

  3. K-Nearest Neighbor Intervals Based AP Clustering Algorithm for Large Incomplete Data

    Directory of Open Access Journals (Sweden)

    Cheng Lu

    2015-01-01

    Full Text Available The Affinity Propagation (AP algorithm is an effective algorithm for clustering analysis, but it can not be directly applicable to the case of incomplete data. In view of the prevalence of missing data and the uncertainty of missing attributes, we put forward a modified AP clustering algorithm based on K-nearest neighbor intervals (KNNI for incomplete data. Based on an Improved Partial Data Strategy, the proposed algorithm estimates the KNNI representation of missing attributes by using the attribute distribution information of the available data. The similarity function can be changed by dealing with the interval data. Then the improved AP algorithm can be applicable to the case of incomplete data. Experiments on several UCI datasets show that the proposed algorithm achieves impressive clustering results.

  4. Obstacle Detection for Intelligent Transportation Systems Using Deep Stacked Autoencoder and k-Nearest Neighbor Scheme

    KAUST Repository

    Dairi, Abdelkader

    2018-04-30

    Obstacle detection is an essential element for the development of intelligent transportation systems so that accidents can be avoided. In this study, we propose a stereovisionbased method for detecting obstacles in urban environment. The proposed method uses a deep stacked auto-encoders (DSA) model that combines the greedy learning features with the dimensionality reduction capacity and employs an unsupervised k-nearest neighbors algorithm (KNN) to accurately and reliably detect the presence of obstacles. We consider obstacle detection as an anomaly detection problem. We evaluated the proposed method by using practical data from three publicly available datasets, the Malaga stereovision urban dataset (MSVUD), the Daimler urban segmentation dataset (DUSD), and Bahnhof dataset. Also, we compared the efficiency of DSA-KNN approach to the deep belief network (DBN)-based clustering schemes. Results show that the DSA-KNN is suitable to visually monitor urban scenes.

  5. Probability-neighbor method of accelerating geometry treatment in reactor Monte Carlo code RMC

    International Nuclear Information System (INIS)

    She, Ding; Li, Zeguang; Xu, Qi; Wang, Kan; Yu, Ganglin

    2011-01-01

    Probability neighbor method (PNM) is proposed in this paper to accelerate geometry treatment of Monte Carlo (MC) simulation and validated in self-developed reactor Monte Carlo code RMC. During MC simulation by either ray-tracking or delta-tracking method, large amounts of time are spent in finding out which cell one particle is located in. The traditional way is to search cells one by one with certain sequence defined previously. However, this procedure becomes very time-consuming when the system contains a large number of cells. Considering that particles have different probability to enter different cells, PNM method optimizes the searching sequence, i.e., the cells with larger probability are searched preferentially. The PNM method is implemented in RMC code and the numerical results show that the considerable time of geometry treatment in MC calculation for complicated systems is saved, especially effective in delta-tracking simulation. (author)

  6. Humanitarian Cleft Lip/Palate Surgeries in Buddhist Thailand and Neighboring Countries.

    Science.gov (United States)

    Uemura, Tetsuji; Preeyanont, Piyoros; Udnoon, Sopridee

    2015-06-01

    This study evaluates surgeries done on patients with cleft lip and/or palate in Thailand and its neighboring countries from 1988 to 2008. This 21-year-long volunteer surgical mission was sponsored by Duang-Kaew Foundation, a volunteer organization. Countries involved, besides Thailand, were Vietnam, Myanmar, Laos, Cambodia, China, Sri Lanka, Bhutan, and India. The same surgical method for primary and secondary repair of lip and/or palate was used throughout: Onizuka method by single surgeon, the second author mainly. We assessed, by way of the patients' medical records including their background, the results of surgeries. The healing rates and complication rates associated with patients for primary and secondary repair of lip and/or palate. The study consisted of a total of 6832 patients: 3120 with cleft lip (CL); 2190 with cleft palate (CP); and 1522 with cleft lip and palate (CLP). Their primary cases were 675 (CL), 799 (CP), and 301 (CLP). All CP operations were done under general anesthesia. Of the CL surgeries, 10% of adult cases were done under local anesthesia. Of all the patients, 78%, or 5329, had one surgery; and 22%, or 1503, had 2 or more surgeries. Good healing was seen in 73.3%, whereas wound infection was noted in 2.0% and healing by second intention was in 1.2% of all cases. It is important that the Onizuka method was the only method used in all the countries throughout the mission period. The method has an advantage over other methods in that its design is simple enough so that even a beginning plastic surgeon can easily master, and operative results are constantly good regardless of who did the operation. The Duang-Kaew Foundation's long-term surgical program helped reduce the number of untreated patients to manageable levels for local health care providers in Thailand and neighboring countries for as long as 21 years.

  7. Lysenin Toxin Membrane Insertion Is pH-Dependent but Independent of Neighboring Lysenins.

    Science.gov (United States)

    Munguira, Ignacio L B; Takahashi, Hirohide; Casuso, Ignacio; Scheuring, Simon

    2017-11-07

    Pore-forming toxins form a family of proteins that act as virulence factors of pathogenic bacteria, but similar proteins are found in all kingdoms of life, including the vertebrate immune system. They are secreted as soluble monomers that oligomerize on target membranes in the so-called prepore state; after activation, they insert into the membrane and adopt the pore state. Lysenin is a pore-forming toxin from the earthworm Eisenida foetida, of which both the soluble and membrane-inserted structures are solved. However, the activation and membrane-insertion mechanisms have remained elusive. Here, we used high-speed atomic force microscopy to directly visualize the membrane-insertion mechanism. Changing the environmental pH from pH 7.5 to below pH 6.0 favored membrane insertion. We detected a short α-helix in the soluble structure that comprised three glutamic acids (Glu92, Glu94, and Glu97) that we hypothesized may represent a pH-sensor (as in similar toxins, e.g., Listeriolysin). Mutant lysenin still can form pores, but mutating these glutamic acids to glutamines rendered the toxin pH-insensitive. On the other hand, toxins in the pore state did not favor insertion of neighboring prepores; indeed, pore insertion breaks the hexagonal ordered domains of prepores and separates from neighboring molecules in the membrane. pH-dependent activation of toxins may represent a common feature of pore-forming toxins. High-speed atomic force microscopy with single-molecule resolution at high temporal resolution and the possibility of exchanging buffers during the experiments presents itself as a unique tool for the study of toxin-state conversion. Copyright © 2017 Biophysical Society. Published by Elsevier Inc. All rights reserved.

  8. Thyroid monitoring for residents of disaster-affected and neighboring areas

    International Nuclear Information System (INIS)

    Ito, Shigeki

    2014-01-01

    The devastating environmental contamination caused by the nuclear disaster at the Fukushima Daiichi Nuclear Power Station of The Tokyo Electric Power Company is exposing the residents of the disaster-affected areas to health risks attributable to radiation exposure, and fear of the development of 131 I-induced thyroid cancer, which is a stochastic effect of radiation and is particularly high. As part of the response to nuclear disasters by the government of the municipality where the nuclear power station is located and in operation and by the governments of neighboring municipalities, it is necessary to conduct thyroid monitoring for the purpose of alleviating the fears of residents of the disaster-affected areas as well as those living in the contaminated, even if only slightly, neighboring areas (local residents). This health monitoring needs to be implemented without delay in the case of a disaster along with dissemination of a portable type thyroid monitoring system available at evacuation centers, etc. for assessing thyroid exposure doses. The establishment of a system for developing personnel ready to perform monitoring is also essential. Assessing thyroid exposure doses is indispensable as a means of assuring local residents not only of safety but also of security from the risks of radiation. To date, contamination has not been detected in people, except for residents contaminated by a large amount of iodine, by employing the mobile type of thyroid monitoring system. However, when local residents seeking security desire thyroid monitoring, it is preferable that a portable type simplified thyroid monitoring system be used as a means of ensuring security against radiation. (author)

  9. Wildflower Plantings Do Not Compete With Neighboring Almond Orchards for Pollinator Visits.

    Science.gov (United States)

    Lundin, Ola; Ward, Kimiora L; Artz, Derek R; Boyle, Natalie K; Pitts-Singer, Theresa L; Williams, Neal M

    2017-06-01

    The engineering of flowering agricultural field borders has emerged as a research and policy priority to mitigate threats to pollinators. Studies have, however, rarely addressed the potential that flowering field borders might compete with neighboring crops for pollinator visits if they both are in bloom at the same time, despite this being a concern expressed by growers. We evaluated how wildflower plantings added to orchard borders in a large (512 ha) commercial almond orchard affected honey bee and wild bee visitation to orchard borders and the crop. The study was conducted over two consecutive seasons using three large (0.48 ha) wildflower plantings paired with control orchard borders in a highly simplified agricultural landscape in California. Honey bee (Apis mellifera L.) and wild bee visitation to wildflower plots were at least an order of magnitude higher than to control plots, but increased honey bee visitation to wildflower plots did not lead to any detectable shifts in honey bee visitation to almond flowers in the neighboring orchard. Wild bees were rarely observed visiting almond flowers irrespective of border treatment, indicating a limited short-term potential for augmenting crop pollination using wild bees in highly simplified agricultural landscapes. Although further studies are warranted on bee visitation and crop yield from spatially independent orchards, this study indicates that growers can support bees with alternative forage in almond orchards without risking competition between the wildflower plantings and the crop. © The Authors 2017. Published by Oxford University Press on behalf of Entomological Society of America. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

  10. Improved Fuzzy K-Nearest Neighbor Using Modified Particle Swarm Optimization

    Science.gov (United States)

    Jamaluddin; Siringoringo, Rimbun

    2017-12-01

    Fuzzy k-Nearest Neighbor (FkNN) is one of the most powerful classification methods. The presence of fuzzy concepts in this method successfully improves its performance on almost all classification issues. The main drawbackof FKNN is that it is difficult to determine the parameters. These parameters are the number of neighbors (k) and fuzzy strength (m). Both parameters are very sensitive. This makes it difficult to determine the values of ‘m’ and ‘k’, thus making FKNN difficult to control because no theories or guides can deduce how proper ‘m’ and ‘k’ should be. This study uses Modified Particle Swarm Optimization (MPSO) to determine the best value of ‘k’ and ‘m’. MPSO is focused on the Constriction Factor Method. Constriction Factor Method is an improvement of PSO in order to avoid local circumstances optima. The model proposed in this study was tested on the German Credit Dataset. The test of the data/The data test has been standardized by UCI Machine Learning Repository which is widely applied to classification problems. The application of MPSO to the determination of FKNN parameters is expected to increase the value of classification performance. Based on the experiments that have been done indicating that the model offered in this research results in a better classification performance compared to the Fk-NN model only. The model offered in this study has an accuracy rate of 81%, while. With using Fk-NN model, it has the accuracy of 70%. At the end is done comparison of research model superiority with 2 other classification models;such as Naive Bayes and Decision Tree. This research model has a better performance level, where Naive Bayes has accuracy 75%, and the decision tree model has 70%

  11. Tularemia, a re-emerging infectious disease in Iran and neighboring countrie

    Science.gov (United States)

    Zargar, Afsaneh; Maurin, Max; Mostafavi, Ehsan

    2015-01-01

    OBJECTIVES: Tularemia is a zoonotic disease transmitted by direct contact with infected animals and through arthropod bites, inhalation of contaminated aerosols, ingestion of contaminated meat or water, and skin contact with any infected material. It is widespread throughout the northern hemisphere, including Iran and its neighbors to the north, northeast, and northwest. METHODS: In this paper, the epidemiology of tularemia as a re-emerging infectious disease in the world with a focus on Iran and the neighboring countries is reviewed. RESULTS: In Iran, positive serological tests were first reported in 1973, in wildlife and domestic livestock in the northwestern and southeastern parts of the country. The first human case was reported in 1980 in the southwest of Iran, and recent studies conducted among at-risk populations in the western, southeastern, and southwestern parts of Iran revealed seroprevalences of 14.4, 6.52, and 6%, respectively. CONCLUSIONS: Several factors may explain the absence of reported tularemia cases in Iran since 1980. Tularemia may be underdiagnosed in Iran because Francisella tularensis subspecies holarctica is likely to be the major etiological agent and usually causes mild to moderately severe disease. Furthermore, tularemia is not a disease extensively studied in the medical educational system in Iran, and empirical therapy may be effective in many cases. Finally, it should be noted that laboratories capable of diagnosing tularemia have only been established in the last few years. Since both recent and older studies have consistently found tularemia antibodies in humans and animals, the surveillance of this disease should receive more attention. In particular, it would be worthwhile for clinical researchers to confirm tularemia cases more often by isolating F. tularensis from infected humans and animals. PMID:25773439

  12. Rapid and Robust Cross-Correlation-Based Seismic Phase Identification Using an Approximate Nearest Neighbor Method

    Science.gov (United States)

    Tibi, R.; Young, C. J.; Gonzales, A.; Ballard, S.; Encarnacao, A. V.

    2016-12-01

    The matched filtering technique involving the cross-correlation of a waveform of interest with archived signals from a template library has proven to be a powerful tool for detecting events in regions with repeating seismicity. However, waveform correlation is computationally expensive, and therefore impractical for large template sets unless dedicated distributed computing hardware and software are used. In this study, we introduce an Approximate Nearest Neighbor (ANN) approach that enables the use of very large template libraries for waveform correlation without requiring a complex distributed computing system. Our method begins with a projection into a reduced dimensionality space based on correlation with a randomized subset of the full template archive. Searching for a specified number of nearest neighbors is accomplished by using randomized K-dimensional trees. We used the approach to search for matches to each of 2700 analyst-reviewed signal detections reported for May 2010 for the IMS station MKAR. The template library in this case consists of a dataset of more than 200,000 analyst-reviewed signal detections for the same station from 2002-2014 (excluding May 2010). Of these signal detections, 60% are teleseismic first P, and 15% regional phases (Pn, Pg, Sn, and Lg). The analyses performed on a standard desktop computer shows that the proposed approach performs the search of the large template libraries about 20 times faster than the standard full linear search, while achieving recall rates greater than 80%, with the recall rate increasing for higher correlation values. To decide whether to confirm a match, we use a hybrid method involving a cluster approach for queries with two or more matches, and correlation score for single matches. Of the signal detections that passed our confirmation process, 52% were teleseismic first P, and 30% were regional phases.

  13. A Regression-based K nearest neighbor algorithm for gene function prediction from heterogeneous data

    Directory of Open Access Journals (Sweden)

    Ruzzo Walter L

    2006-03-01

    Full Text Available Abstract Background As a variety of functional genomic and proteomic techniques become available, there is an increasing need for functional analysis methodologies that integrate heterogeneous data sources. Methods In this paper, we address this issue by proposing a general framework for gene function prediction based on the k-nearest-neighbor (KNN algorithm. The choice of KNN is motivated by its simplicity, flexibility to incorporate different data types and adaptability to irregular feature spaces. A weakness of traditional KNN methods, especially when handling heterogeneous data, is that performance is subject to the often ad hoc choice of similarity metric. To address this weakness, we apply regression methods to infer a similarity metric as a weighted combination of a set of base similarity measures, which helps to locate the neighbors that are most likely to be in the same class as the target gene. We also suggest a novel voting scheme to generate confidence scores that estimate the accuracy of predictions. The method gracefully extends to multi-way classification problems. Results We apply this technique to gene function prediction according to three well-known Escherichia coli classification schemes suggested by biologists, using information derived from microarray and genome sequencing data. We demonstrate that our algorithm dramatically outperforms the naive KNN methods and is competitive with support vector machine (SVM algorithms for integrating heterogenous data. We also show that by combining different data sources, prediction accuracy can improve significantly. Conclusion Our extension of KNN with automatic feature weighting, multi-class prediction, and probabilistic inference, enhance prediction accuracy significantly while remaining efficient, intuitive and flexible. This general framework can also be applied to similar classification problems involving heterogeneous datasets.

  14. Detection of Burkholderia pseudomallei O-antigen serotypes in near-neighbor species

    Directory of Open Access Journals (Sweden)

    Stone Joshua K

    2012-11-01

    Full Text Available Abstract Background Burkholderia pseudomallei is the etiological agent of melioidosis and a CDC category B select agent with no available effective vaccine. Previous immunizations in mice have utilized the lipopolysaccharide (LPS as a potential vaccine target because it is known as one of the most important antigenic epitopes in B. pseudomallei. Complicating this strategy are the four different B. pseudomallei LPS O-antigen types: A, B, B2, and rough. Sero-crossreactivity is common among O-antigens of Burkholderia species. Here, we identified the presence of multiple B. pseudomallei O-antigen types and sero-crossreactivity in its near-neighbor species. Results PCR screening of O-antigen biosynthesis genes, phenotypic characterization using SDS-PAGE, and immunoblot analysis showed that majority of B. mallei and B. thailandensis strains contained the typical O-antigen type A. In contrast, most of B. ubonensis and B. thailandensis-like strains expressed the atypical O-antigen types B and B2, respectively. Most B. oklahomensis strains expressed a distinct and non-seroreactive O-antigen type, except strain E0147 which expressed O-antigen type A. O-antigen type B2 was also detected in B. thailandensis 82172, B. ubonensis MSMB108, and Burkholderia sp. MSMB175. Interestingly, B. thailandensis-like MSMB43 contained a novel serotype B positive O-antigen. Conclusions This study expands the number of species which express B. pseudomallei O-antigen types. Further work is required to elucidate the full structures and how closely these are to the B. pseudomallei O-antigens, which will ultimately determine the efficacy of the near-neighbor B serotypes for vaccine development.

  15. Distance-Constraint k-Nearest Neighbor Searching in Mobile Sensor Networks.

    Science.gov (United States)

    Han, Yongkoo; Park, Kisung; Hong, Jihye; Ulamin, Noor; Lee, Young-Koo

    2015-07-27

    The κ-Nearest Neighbors ( κNN) query is an important spatial query in mobile sensor networks. In this work we extend κNN to include a distance constraint, calling it a l-distant κ-nearest-neighbors (l-κNN) query, which finds the κ sensor nodes nearest to a query point that are also at or greater distance from each other. The query results indicate the objects nearest to the area of interest that are scattered from each other by at least distance l. The l-κNN query can be used in most κNN applications for the case of well distributed query results. To process an l-κNN query, we must discover all sets of κNN sensor nodes and then find all pairs of sensor nodes in each set that are separated by at least a distance l. Given the limited battery and computing power of sensor nodes, this l-κNN query processing is problematically expensive in terms of energy consumption. In this paper, we propose a greedy approach for l-κNN query processing in mobile sensor networks. The key idea of the proposed approach is to divide the search space into subspaces whose all sides are l. By selecting κ sensor nodes from the other subspaces near the query point, we guarantee accurate query results for l-κNN. In our experiments, we show that the proposed method exhibits superior performance compared with a post-processing based method using the κNN query in terms of energy efficiency, query latency, and accuracy.

  16. Spacecraft Jitter Attenuation Using Embedded Piezoelectric Actuators

    Science.gov (United States)

    Belvin, W. Keith

    1995-01-01

    Remote sensing from spacecraft requires precise pointing of measurement devices in order to achieve adequate spatial resolution. Unfortunately, various spacecraft disturbances induce vibrational jitter in the remote sensing instruments. The NASA Langley Research Center has performed analysis, simulations, and ground tests to identify the more promising technologies for minimizing spacecraft pointing jitter. These studies have shown that the use of smart materials to reduce spacecraft jitter is an excellent match between a maturing technology and an operational need. This paper describes the use of embedding piezoelectric actuators for vibration control and payload isolation. In addition, recent advances in modeling, simulation, and testing of spacecraft pointing jitter are discussed.

  17. Embedded generation and network management issues

    Energy Technology Data Exchange (ETDEWEB)

    NONE

    2000-07-01

    This report focuses on the characteristics of power generators that are important to accommodation in a distribution system. Part 1 examines the differences between transmission and distribution systems, and issues such as randomness, diversity, predictability, and controllability associated with accommodation in a distribution system. Part 2 concentrates on technical and operational issues relating to embedded generation, and the possible impact of the New Electricity Trading Arrangements. Commercial issues, contractual relationships for network charging and provision of services, and possible ways forward are examined in the last three parts of the report.

  18. SPARQL for Networks of Embedded Systems

    OpenAIRE

    Boldt, Dennis; Hasemann, Henning; Kröller, Alexander; Karnstedt, Marcel; von der Weth, Christian

    2014-01-01

    The Semantic Web (or Web of Data) represents the successful efforts towards linking and sharing data over the Web. The cornerstones of the Web of Data are RDF as data format and SPARQL as de-facto standard query language. Recent trends show the evolution of the Web of Data towards the Web of Things, integrating embedded devices and smart objects. Data stemming from such devices do not share a common format, making the integration and querying impossible. To overcome this problem, we present o...

  19. Safety-critical Java for embedded systems

    DEFF Research Database (Denmark)

    Schoeberl, Martin; Dalsgaard, Andreas Engelbredt; Hansen, René Rydhof

    2016-01-01

    This paper presents the motivation for and outcomes of an engineering research project on certifiable Javafor embedded systems. The project supports the upcoming standard for safety-critical Java, which defines asubset of Java and libraries aiming for development of high criticality systems....... The outcome of this projectinclude prototype safety-critical Java implementations, a time-predictable Java processor, analysis tools formemory safety, and example applications to explore the usability of safety-critical Java for this applicationarea. The text summarizes developments and key contributions...

  20. An Embedded Librarian Program: Eight Years On.

    Science.gov (United States)

    Freiburger, Gary; Martin, Jennifer R; Nuñez, Annabelle V

    2016-01-01

    This article examines an embedded librarian program eight years after implementation in a large academic health center. Librarians were physically moved into the colleges of pharmacy, public health, and nursing. Statistics are reported as well as comments from the participating librarians and faculty members. Strong relationships have been built between librarians, faculty members, and students. Locating the librarians among faculty and students led to a better understanding of client needs and an increased awareness of librarian competencies and services resulting in partnerships and greater utilization of library services.