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Sample records for hybrid classification scheme

  1. EEG Classification for Hybrid Brain-Computer Interface Using a Tensor Based Multiclass Multimodal Analysis Scheme.

    Science.gov (United States)

    Ji, Hongfei; Li, Jie; Lu, Rongrong; Gu, Rong; Cao, Lei; Gong, Xiaoliang

    2016-01-01

    Electroencephalogram- (EEG-) based brain-computer interface (BCI) systems usually utilize one type of changes in the dynamics of brain oscillations for control, such as event-related desynchronization/synchronization (ERD/ERS), steady state visual evoked potential (SSVEP), and P300 evoked potentials. There is a recent trend to detect more than one of these signals in one system to create a hybrid BCI. However, in this case, EEG data were always divided into groups and analyzed by the separate processing procedures. As a result, the interactive effects were ignored when different types of BCI tasks were executed simultaneously. In this work, we propose an improved tensor based multiclass multimodal scheme especially for hybrid BCI, in which EEG signals are denoted as multiway tensors, a nonredundant rank-one tensor decomposition model is proposed to obtain nonredundant tensor components, a weighted fisher criterion is designed to select multimodal discriminative patterns without ignoring the interactive effects, and support vector machine (SVM) is extended to multiclass classification. Experiment results suggest that the proposed scheme can not only identify the different changes in the dynamics of brain oscillations induced by different types of tasks but also capture the interactive effects of simultaneous tasks properly. Therefore, it has great potential use for hybrid BCI.

  2. Small-scale classification schemes

    DEFF Research Database (Denmark)

    Hertzum, Morten

    2004-01-01

    Small-scale classification schemes are used extensively in the coordination of cooperative work. This study investigates the creation and use of a classification scheme for handling the system requirements during the redevelopment of a nation-wide information system. This requirements...... classification inherited a lot of its structure from the existing system and rendered requirements that transcended the framework laid out by the existing system almost invisible. As a result, the requirements classification became a defining element of the requirements-engineering process, though its main...... effects remained largely implicit. The requirements classification contributed to constraining the requirements-engineering process by supporting the software engineers in maintaining some level of control over the process. This way, the requirements classification provided the software engineers...

  3. A Classification Scheme for Production System Processes

    DEFF Research Database (Denmark)

    Sørensen, Daniel Grud Hellerup; Brunø, Thomas Ditlev; Nielsen, Kjeld

    2018-01-01

    Manufacturing companies often have difficulties developing production platforms, partly due to the complexity of many production systems and difficulty determining which processes constitute a platform. Understanding production processes is an important step to identifying candidate processes...... for a production platform based on existing production systems. Reviewing a number of existing classifications and taxonomies, a consolidated classification scheme for processes in production of discrete products has been outlined. The classification scheme helps ensure consistency during mapping of existing...

  4. A hierarchical classification scheme of psoriasis images

    DEFF Research Database (Denmark)

    Maletti, Gabriela Mariel; Ersbøll, Bjarne Kjær

    2003-01-01

    A two-stage hierarchical classification scheme of psoriasis lesion images is proposed. These images are basically composed of three classes: normal skin, lesion and background. The scheme combines conventional tools to separate the skin from the background in the first stage, and the lesion from...

  5. hybrid modulation scheme fo rid modulation scheme fo dulation

    African Journals Online (AJOL)

    eobe

    control technique is done through simulations and ex control technique .... HYBRID MODULATION SCHEME FOR CASCADED H-BRIDGE INVERTER CELLS. C. I. Odeh ..... and OR operations. Referring to ... MATLAB/SIMULINK environment.

  6. A Classification Scheme for Literary Characters

    Directory of Open Access Journals (Sweden)

    Matthew Berry

    2017-10-01

    Full Text Available There is no established classification scheme for literary characters in narrative theory short of generic categories like protagonist vs. antagonist or round vs. flat. This is so despite the ubiquity of stock characters that recur across media, cultures, and historical time periods. We present here a proposal of a systematic psychological scheme for classifying characters from the literary and dramatic fields based on a modification of the Thomas-Kilmann (TK Conflict Mode Instrument used in applied studies of personality. The TK scheme classifies personality along the two orthogonal dimensions of assertiveness and cooperativeness. To examine the validity of a modified version of this scheme, we had 142 participants provide personality ratings for 40 characters using two of the Big Five personality traits as well as assertiveness and cooperativeness from the TK scheme. The results showed that assertiveness and cooperativeness were orthogonal dimensions, thereby supporting the validity of using a modified version of TK’s two-dimensional scheme for classifying characters.

  7. A classification scheme for LWR fuel assemblies

    Energy Technology Data Exchange (ETDEWEB)

    Moore, R.S.; Williamson, D.A.; Notz, K.J.

    1988-11-01

    With over 100 light water nuclear reactors operating nationwide, representing designs by four primary vendors, and with reload fuel manufactured by these vendors and additional suppliers, a wide variety of fuel assembly types are in existence. At Oak Ridge National Laboratory, both the Systems Integration Program and the Characteristics Data Base project required a classification scheme for these fuels. This scheme can be applied to other areas and is expected to be of value to many Office of Civilian Radioactive Waste Management programs. To develop the classification scheme, extensive information on the fuel assemblies that have been and are being manufactured by the various nuclear fuel vendors was compiled, reviewed, and evaluated. It was determined that it is possible to characterize assemblies in a systematic manner, using a combination of physical factors. A two-stage scheme was developed consisting of 79 assembly types, which are grouped into 22 assembly classes. The assembly classes are determined by the general design of the reactor cores in which the assemblies are, or were, used. The general BWR and PWR classes are divided differently but both are based on reactor core configuration. 2 refs., 15 tabs.

  8. A classification scheme for LWR fuel assemblies

    International Nuclear Information System (INIS)

    Moore, R.S.; Williamson, D.A.; Notz, K.J.

    1988-11-01

    With over 100 light water nuclear reactors operating nationwide, representing designs by four primary vendors, and with reload fuel manufactured by these vendors and additional suppliers, a wide variety of fuel assembly types are in existence. At Oak Ridge National Laboratory, both the Systems Integration Program and the Characteristics Data Base project required a classification scheme for these fuels. This scheme can be applied to other areas and is expected to be of value to many Office of Civilian Radioactive Waste Management programs. To develop the classification scheme, extensive information on the fuel assemblies that have been and are being manufactured by the various nuclear fuel vendors was compiled, reviewed, and evaluated. It was determined that it is possible to characterize assemblies in a systematic manner, using a combination of physical factors. A two-stage scheme was developed consisting of 79 assembly types, which are grouped into 22 assembly classes. The assembly classes are determined by the general design of the reactor cores in which the assemblies are, or were, used. The general BWR and PWR classes are divided differently but both are based on reactor core configuration. 2 refs., 15 tabs

  9. A classification scheme for risk assessment methods.

    Energy Technology Data Exchange (ETDEWEB)

    Stamp, Jason Edwin; Campbell, Philip LaRoche

    2004-08-01

    This report presents a classification scheme for risk assessment methods. This scheme, like all classification schemes, provides meaning by imposing a structure that identifies relationships. Our scheme is based on two orthogonal aspects--level of detail, and approach. The resulting structure is shown in Table 1 and is explained in the body of the report. Each cell in the Table represent a different arrangement of strengths and weaknesses. Those arrangements shift gradually as one moves through the table, each cell optimal for a particular situation. The intention of this report is to enable informed use of the methods so that a method chosen is optimal for a situation given. This report imposes structure on the set of risk assessment methods in order to reveal their relationships and thus optimize their usage.We present a two-dimensional structure in the form of a matrix, using three abstraction levels for the rows and three approaches for the columns. For each of the nine cells in the matrix we identify the method type by name and example. The matrix helps the user understand: (1) what to expect from a given method, (2) how it relates to other methods, and (3) how best to use it. Each cell in the matrix represent a different arrangement of strengths and weaknesses. Those arrangements shift gradually as one moves through the table, each cell optimal for a particular situation. The intention of this report is to enable informed use of the methods so that a method chosen is optimal for a situation given. The matrix, with type names in the cells, is introduced in Table 2 on page 13 below. Unless otherwise stated we use the word 'method' in this report to refer to a 'risk assessment method', though often times we use the full phrase. The use of the terms 'risk assessment' and 'risk management' are close enough that we do not attempt to distinguish them in this report. The remainder of this report is organized as follows. In

  10. A Classification Scheme for Glaciological AVA Responses

    Science.gov (United States)

    Booth, A.; Emir, E.

    2014-12-01

    A classification scheme is proposed for amplitude vs. angle (AVA) responses as an aid to the interpretation of seismic reflectivity in glaciological research campaigns. AVA responses are a powerful tool in characterising the material properties of glacier ice and its substrate. However, before interpreting AVA data, careful true amplitude processing is required to constrain basal reflectivity and compensate amplitude decay mechanisms, including anelastic attenuation and spherical divergence. These fundamental processing steps can be difficult to design in cases of noisy data, e.g. where a target reflection is contaminated by surface wave energy (in the case of shallow glaciers) or by energy reflected from out of the survey plane. AVA methods have equally powerful usage in estimating the fluid fill of potential hydrocarbon reservoirs. However, such applications seldom use true amplitude data and instead consider qualitative AVA responses using a well-defined classification scheme. Such schemes are often defined in terms of the characteristics of best-fit responses to the observed reflectivity, e.g. the intercept (I) and gradient (G) of a linear approximation to the AVA data. The position of the response on a cross-plot of I and G then offers a diagnostic attribute for certain fluid types. We investigate the advantages in glaciology of emulating this practice, and develop a cross-plot based on the 3-term Shuey AVA approximation (using I, G, and a curvature term C). Model AVA curves define a clear lithification trend: AVA responses to stiff (lithified) substrates fall discretely into one quadrant of the cross-plot, with positive I and negative G, whereas those to fluid-rich substrates plot diagonally opposite (in the negative I and positive G quadrant). The remaining quadrants are unoccupied by plausible single-layer responses and may therefore be diagnostic of complex thin-layer reflectivity, and the magnitude and polarity of the C term serves as a further indicator

  11. State of the Art in the Cramer Classification Scheme and ...

    Science.gov (United States)

    Slide presentation at the SOT FDA Colloquium on State of the Art in the Cramer Classification Scheme and Threshold of Toxicological Concern in College Park, MD. Slide presentation at the SOT FDA Colloquium on State of the Art in the Cramer Classification Scheme and Threshold of Toxicological Concern in College Park, MD.

  12. A hybrid Lagrangian Voronoi-SPH scheme

    Science.gov (United States)

    Fernandez-Gutierrez, D.; Souto-Iglesias, A.; Zohdi, T. I.

    2017-11-01

    A hybrid Lagrangian Voronoi-SPH scheme, with an explicit weakly compressible formulation for both the Voronoi and SPH sub-domains, has been developed. The SPH discretization is substituted by Voronoi elements close to solid boundaries, where SPH consistency and boundary conditions implementation become problematic. A buffer zone to couple the dynamics of both sub-domains is used. This zone is formed by a set of particles where fields are interpolated taking into account SPH particles and Voronoi elements. A particle may move in or out of the buffer zone depending on its proximity to a solid boundary. The accuracy of the coupled scheme is discussed by means of a set of well-known verification benchmarks.

  13. Maxillectomy defects: a suggested classification scheme.

    Science.gov (United States)

    Akinmoladun, V I; Dosumu, O O; Olusanya, A A; Ikusika, O F

    2013-06-01

    The term "maxillectomy" has been used to describe a variety of surgical procedures for a spectrum of diseases involving a diverse anatomical site. Hence, classifications of maxillectomy defects have often made communication difficult. This article highlights this problem, emphasises the need for a uniform system of classification and suggests a classification system which is simple and comprehensive. Articles related to this subject, especially those with specified classifications of maxillary surgical defects were sourced from the internet through Google, Scopus and PubMed using the search terms maxillectomy defects classification. A manual search through available literature was also done. The review of the materials revealed many classifications and modifications of classifications from the descriptive, reconstructive and prosthodontic perspectives. No globally acceptable classification exists among practitioners involved in the management of diseases in the mid-facial region. There were over 14 classifications of maxillary defects found in the English literature. Attempts made to address the inadequacies of previous classifications have tended to result in cumbersome and relatively complex classifications. A single classification that is based on both surgical and prosthetic considerations is most desirable and is hereby proposed.

  14. Sound classification of dwellings - Comparison of schemes in Europe

    DEFF Research Database (Denmark)

    Rasmussen, Birgit

    2009-01-01

    National sound classification schemes for dwellings exist in nine countries in Europe, and proposals are under preparation in more countries. The schemes specify class criteria concerning several acoustic aspects, the main criteria being about airborne and impact sound insulation between dwellings......, facade sound insulation and installation noise. The quality classes reflect dierent levels of acoustical comfort. The paper presents and compares the sound classification schemes in Europe. The schemes have been implemented and revised gradually since the 1990es. However, due to lack of coordination...

  15. Establishment of water quality classification scheme: a case study of ...

    African Journals Online (AJOL)

    A water quality classification scheme based on 11 routinely measured physicochemical variables has been developed for the Calabar River Estuary. The variables considered include water temperature, pH. Eh, DO, DO saturation, BOD5, COD, TSS, turbidity, NH4-N and electrical conductivity. Classification of water source ...

  16. International proposal for an acoustic classification scheme for dwellings

    DEFF Research Database (Denmark)

    Rasmussen, Birgit

    2014-01-01

    Acoustic classification schemes specify different quality levels for acoustic conditions. Regulations and classification schemes for dwellings typically include criteria for airborne and impact sound insulation, façade sound insulation and service equipment noise. However, although important...... classes, implying also trade barriers. Thus, a harmonized classification scheme would be useful, and the European COST Action TU0901 "Integrating and Harmonizing Sound Insulation Aspects in Sustainable Urban Housing Constructions", running 2009-2013 with members from 32 countries, including three overseas...... for quality of life, information about acoustic conditions is rarely available, neither for new or existing housing. Regulatory acoustic requirements will, if enforced, ensure a corresponding quality for new dwellings, but satisfactory conditions for occupants are not guaranteed. Consequently, several...

  17. Mapping of the Universe of Knowledge in Different Classification Schemes

    Directory of Open Access Journals (Sweden)

    M. P. Satija

    2017-06-01

    Full Text Available Given the variety of approaches to mapping the universe of knowledge that have been presented and discussed in the literature, the purpose of this paper is to systematize their main principles and their applications in the major general modern library classification schemes. We conducted an analysis of the literature on classification and the main classification systems, namely Dewey/Universal Decimal Classification, Cutter’s Expansive Classification, Subject Classification of J.D. Brown, Colon Classification, Library of Congress Classification, Bibliographic Classification, Rider’s International Classification, Bibliothecal Bibliographic Klassification (BBK, and Broad System of Ordering (BSO. We conclude that the arrangement of the main classes can be done following four principles that are not mutually exclusive: ideological principle, social purpose principle, scientific order, and division by discipline. The paper provides examples and analysis of each system. We also conclude that as knowledge is ever-changing, classifications also change and present a different structure of knowledge depending upon the society and time of their design.

  18. Transporter taxonomy - a comparison of different transport protein classification schemes.

    Science.gov (United States)

    Viereck, Michael; Gaulton, Anna; Digles, Daniela; Ecker, Gerhard F

    2014-06-01

    Currently, there are more than 800 well characterized human membrane transport proteins (including channels and transporters) and there are estimates that about 10% (approx. 2000) of all human genes are related to transport. Membrane transport proteins are of interest as potential drug targets, for drug delivery, and as a cause of side effects and drug–drug interactions. In light of the development of Open PHACTS, which provides an open pharmacological space, we analyzed selected membrane transport protein classification schemes (Transporter Classification Database, ChEMBL, IUPHAR/BPS Guide to Pharmacology, and Gene Ontology) for their ability to serve as a basis for pharmacology driven protein classification. A comparison of these membrane transport protein classification schemes by using a set of clinically relevant transporters as use-case reveals the strengths and weaknesses of the different taxonomy approaches.

  19. A Classification Scheme for Career Education Resource Materials.

    Science.gov (United States)

    Koontz, Ronald G.

    The introductory section of the paper expresses its purpose: to devise a classification scheme for career education resource material, which will be used to develop the USOE Office of Career Education Resource Library and will be disseminated to interested State departments of education and local school districts to assist them in classifying…

  20. New Course Design: Classification Schemes and Information Architecture.

    Science.gov (United States)

    Weinberg, Bella Hass

    2002-01-01

    Describes a course developed at St. John's University (New York) in the Division of Library and Information Science that relates traditional classification schemes to information architecture and Web sites. Highlights include functional aspects of information architecture, that is, the way content is structured; assignments; student reactions; and…

  1. Social Constructivism: Botanical Classification Schemes of Elementary School Children.

    Science.gov (United States)

    Tull, Delena

    The assertion that there is a social component to children's construction of knowledge about natural phenomena is supported by evidence from an examination of children's classification schemes for plants. An ethnographic study was conducted with nine sixth grade children in central Texas. The children classified plants in the outdoors, in a…

  2. Proposal of a new classification scheme for periocular injuries

    Directory of Open Access Journals (Sweden)

    Devi Prasad Mohapatra

    2017-01-01

    Full Text Available Background: Eyelids are important structures and play a role in protecting the globe from trauma, brightness, in maintaining the integrity of tear films and moving the tears towards the lacrimal drainage system and contribute to aesthetic appearance of the face. Ophthalmic trauma is an important cause of morbidity among individuals and has also been responsible for additional cost of healthcare. Periocular trauma involving eyelids and adjacent structures has been found to have increased recently probably due to increased pace of life and increased dependence on machinery. A comprehensive classification of periocular trauma would help in stratifying these injuries as well as study outcomes. Material and Methods: This study was carried out at our institute from June 2015 to Dec 2015. We searched multiple English language databases for existing classification systems for periocular trauma. We designed a system of classification of periocular soft tissue injuries based on clinico-anatomical presentations. This classification was applied prospectively to patients presenting with periocular soft tissue injuries to our department. Results: A comprehensive classification scheme was designed consisting of five types of periocular injuries. A total of 38 eyelid injuries in 34 patients were evaluated in this study. According to the System for Peri-Ocular Trauma (SPOT classification, Type V injuries were most common. SPOT Type II injuries were more common isolated injuries among all zones. Discussion: Classification systems are necessary in order to provide a framework in which to scientifically study the etiology, pathogenesis, and treatment of diseases in an orderly fashion. The SPOT classification has taken into account the periocular soft tissue injuries i.e., upper eyelid, lower eyelid, medial and lateral canthus injuries., based on observed clinico-anatomical patterns of eyelid injuries. Conclusion: The SPOT classification seems to be a reliable

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

    Energy Technology Data Exchange (ETDEWEB)

    Jürgens, Björn, E-mail: bjurgens@agenciaidea.es [Agency of Innovation and Development of Andalusia, CITPIA PATLIB Centre (Spain); Herrero-Solana, Victor, E-mail: victorhs@ugr.es [University of Granada, SCImago-UGR (SEJ036) (Spain)

    2017-04-15

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

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

    International Nuclear Information System (INIS)

    Jürgens, Björn; Herrero-Solana, Victor

    2017-01-01

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

  5. Modern radiosurgical and endovascular classification schemes for brain arteriovenous malformations.

    Science.gov (United States)

    Tayebi Meybodi, Ali; Lawton, Michael T

    2018-05-04

    Stereotactic radiosurgery (SRS) and endovascular techniques are commonly used for treating brain arteriovenous malformations (bAVMs). They are usually used as ancillary techniques to microsurgery but may also be used as solitary treatment options. Careful patient selection requires a clear estimate of the treatment efficacy and complication rates for the individual patient. As such, classification schemes are an essential part of patient selection paradigm for each treatment modality. While the Spetzler-Martin grading system and its subsequent modifications are commonly used for microsurgical outcome prediction for bAVMs, the same system(s) may not be easily applicable to SRS and endovascular therapy. Several radiosurgical- and endovascular-based grading scales have been proposed for bAVMs. However, a comprehensive review of these systems including a discussion on their relative advantages and disadvantages is missing. This paper is dedicated to modern classification schemes designed for SRS and endovascular techniques.

  6. A hybrid pi control scheme for airship hovering

    International Nuclear Information System (INIS)

    Ashraf, Z.; Choudhry, M.A.; Hanif, A.

    2012-01-01

    Airship provides us many attractive applications in aerospace industry including transportation of heavy payloads, tourism, emergency management, communication, hover and vision based applications. Hovering control of airship has many utilizations in different engineering fields. However, it is a difficult problem to sustain the hover condition maintaining controllability. So far, different solutions have been proposed in literature but most of them are difficult in analysis and implementation. In this paper, we have presented a simple and efficient scheme to design a multi input multi output hybrid PI control scheme for airship. It can maintain stability of the plant by rejecting disturbance inputs to ensure robustness. A control scheme based on feedback theory is proposed that uses principles of optimality with integral action for hovering applications. Simulations are carried out in MTALAB for examining the proposed control scheme for hovering in different wind conditions. Comparison of the technique with an existing scheme is performed, describing the effectiveness of control scheme. (author)

  7. A New Well Classification Scheme For The Nigerian Oil Industry

    International Nuclear Information System (INIS)

    Ojoh, K.

    2002-01-01

    Oil was discovered in the Niger Delta Basin in 1956, with Oloibiri 1, after 21 wildcats had been drilled with lack of success. In the 46 years since, 25 companies have discovered 52 Billion barrels, of which 20 Billion has been produced, leaving proven reserves of 32 Billion Barrels.Between now and 2010, the country would like to add 15 billion barrels of oil to these reserves. The target is 40 Billion barrels. The National aspiration is to be able to obtain OPEC quota to produce 4 million barrels of oil per day. A large percentage of the reserves additions will definitely come from the deepwater segment of the basin, where fields of over 500 Million barrels are expected. Exploration also continues on the shelf and on land, but the rate of discovery in these areas is - after 46 years of constant effort - constrained by the relative maturity of the basin.The challenges are that few, small, untested structures remain on shelf and land, whereas most undiscovered reserves are in stratigraphic accumulations within known producing areas. These are only visible on 3-D seismic after it is processed using state-of-the-art, high-technology attribute analyses. In the deepwater province, the stratigraphy throws up problems of reservoir continuity. Channels and lobe fans have complex spatial distribution which systematically require more than the classical two appraisal wells in conventional classification.The industry agrees that the current well classification scheme, which came into place in 1977, needs to be overhauled to take cognisance of these challenges.At a workshop last May, a Well Classification Committee comprising members from OPTS, DEWOG, NAIPEC as well as the DPR was mandated to produce a well classification scheme for the industry. This paper examines the current scheme and comes with a technically sound, widely accepted alternative, complete with exhaustive illustrations

  8. Construction of a knowledge classification scheme for sharing and usage of knowledge

    International Nuclear Information System (INIS)

    Yoo, Jae Bok; Oh, Jeong Hoon; Lee, Ji Ho; Ko, Young Chul

    2003-12-01

    To efficiently share knowledge among our members on the basis of knowledge management system, first of all, we need to systematically design the knowledge classification scheme that we can classify these knowledge well. The objective of this project is to construct the most suitable knowledge classification scheme that all of us can share them in Korea Atomic Energy Research Institute(KAERI). To construct the knowledge classification scheme all over the our organization, we established a few principles to design it and examined related many classification schemes. And we carried out 3 steps to complete the best desirable KAERI's knowledge classification scheme, that is, 1) the step to design a draft of the knowledge classification scheme, 2) the step to revise a draft of the knowledge classification scheme, 3) the step to verify the revised scheme and to decide its scheme. The scheme completed as a results of this project is consisted of total 218 items, that is, sections of 8 items, classes of 43 items and sub-classes of 167 items. We expect that the knowledge classification scheme designed as the results of this project can be played an important role as the frame to share knowledge among our members when we introduce knowledge management system in our organization. In addition, we expect that methods to design its scheme as well as this scheme itself can be applied when design a knowledge classification scheme at the other R and D institutes and enterprises

  9. Conceptual scheme of a hybrid mesocatalytic fusion reactor

    International Nuclear Information System (INIS)

    Petrov, Yu.V.

    1988-01-01

    To test the practical realization of the mesocatalytic method for energy production a preliminary engineering analysis and calculation of the separate units of the conceptual scheme of the hybrid mesocatalytic reactor was made. The construction and efficiency of the most characteristic separate blocks of the conceptual scheme for muon-catalyzed fusion are examined. The muon catalysis cycle in a dt mixture was assessed. The kinetics and energetics of muon production through a pion-forming target and a converter were evaluated. Concomitant questions, particularly the removal of helium from hydrogen, are discussed. Fusion chamber requirements were calculated and problems of heat removal were assessed. Blanket construction and efficiency were examined. The efficiency of different methods for power generation were comparatively reviewed including hybrid thermonuclear, electronuclear nuclear, and hybrid mesocatalytic methods. Energy balances and economic restrictions were examined

  10. Classification schemes for knowledge translation interventions: a practical resource for researchers.

    Science.gov (United States)

    Slaughter, Susan E; Zimmermann, Gabrielle L; Nuspl, Megan; Hanson, Heather M; Albrecht, Lauren; Esmail, Rosmin; Sauro, Khara; Newton, Amanda S; Donald, Maoliosa; Dyson, Michele P; Thomson, Denise; Hartling, Lisa

    2017-12-06

    As implementation science advances, the number of interventions to promote the translation of evidence into healthcare, health systems, or health policy is growing. Accordingly, classification schemes for these knowledge translation (KT) interventions have emerged. A recent scoping review identified 51 classification schemes of KT interventions to integrate evidence into healthcare practice; however, the review did not evaluate the quality of the classification schemes or provide detailed information to assist researchers in selecting a scheme for their context and purpose. This study aimed to further examine and assess the quality of these classification schemes of KT interventions, and provide information to aid researchers when selecting a classification scheme. We abstracted the following information from each of the original 51 classification scheme articles: authors' objectives; purpose of the scheme and field of application; socioecologic level (individual, organizational, community, system); adaptability (broad versus specific); target group (patients, providers, policy-makers), intent (policy, education, practice), and purpose (dissemination versus implementation). Two reviewers independently evaluated the methodological quality of the development of each classification scheme using an adapted version of the AGREE II tool. Based on these assessments, two independent reviewers reached consensus about whether to recommend each scheme for researcher use, or not. Of the 51 original classification schemes, we excluded seven that were not specific classification schemes, not accessible or duplicates. Of the remaining 44 classification schemes, nine were not recommended. Of the 35 recommended classification schemes, ten focused on behaviour change and six focused on population health. Many schemes (n = 29) addressed practice considerations. Fewer schemes addressed educational or policy objectives. Twenty-five classification schemes had broad applicability

  11. CANDELS Visual Classifications: Scheme, Data Release, and First Results

    Science.gov (United States)

    Kartaltepe, Jeyhan S.; Mozena, Mark; Kocevski, Dale; McIntosh, Daniel H.; Lotz, Jennifer; Bell, Eric F.; Faber, Sandy; Ferguson, Henry; Koo, David; Bassett, Robert; hide

    2014-01-01

    We have undertaken an ambitious program to visually classify all galaxies in the five CANDELS fields down to H <24.5 involving the dedicated efforts of 65 individual classifiers. Once completed, we expect to have detailed morphological classifications for over 50,000 galaxies spanning 0 < z < 4 over all the fields. Here, we present our detailed visual classification scheme, which was designed to cover a wide range of CANDELS science goals. This scheme includes the basic Hubble sequence types, but also includes a detailed look at mergers and interactions, the clumpiness of galaxies, k-corrections, and a variety of other structural properties. In this paper, we focus on the first field to be completed - GOODS-S, which has been classified at various depths. The wide area coverage spanning the full field (wide+deep+ERS) includes 7634 galaxies that have been classified by at least three different people. In the deep area of the field, 2534 galaxies have been classified by at least five different people at three different depths. With this paper, we release to the public all of the visual classifications in GOODS-S along with the Perl/Tk GUI that we developed to classify galaxies. We present our initial results here, including an analysis of our internal consistency and comparisons among multiple classifiers as well as a comparison to the Sersic index. We find that the level of agreement among classifiers is quite good and depends on both the galaxy magnitude and the galaxy type, with disks showing the highest level of agreement and irregulars the lowest. A comparison of our classifications with the Sersic index and restframe colors shows a clear separation between disk and spheroid populations. Finally, we explore morphological k-corrections between the V-band and H-band observations and find that a small fraction (84 galaxies in total) are classified as being very different between these two bands. These galaxies typically have very clumpy and extended morphology or

  12. A Hybrid Data Compression Scheme for Improved VNC

    Directory of Open Access Journals (Sweden)

    Xiaozheng (Jane Zhang

    2007-04-01

    Full Text Available Virtual Network Computing (VNC has emerged as a promising technology in distributed computing environment since its invention in the late nineties. Successful application of VNC requires rapid data transfer from one machine to another over a TCP/IP network connection. However transfer of screen data consumes much network bandwidth and current data encoding schemes for VNC are far from being ideal. This paper seeks to improve screen data compression techniques to enable VNC over slow connections and present a reasonable speed and image quality. In this paper, a hybrid technique is proposed for improving coding efficiency. The algorithm first divides a screen image into pre-defined regions and applies encoding schemes to each area according to the region characteristics. Second, correlation of screen data in consecutive frames is exploited where multiple occurrences of similar image contents are detected. The improved results are demonstrated in a dynamic environment with various screen image types and desktop manipulation.

  13. Study of Hybrid Localization Noncooperative Scheme in Wireless Sensor Network

    Directory of Open Access Journals (Sweden)

    Irfan Dwiguna Sumitra

    2017-01-01

    Full Text Available In this paper, we evaluated the experiment and analysis measurement accuracy to determine object location based on wireless sensor network (WSN. The algorithm estimates the position of sensor nodes employing received signal strength (RSS from scattered nodes in the environment, in particular for the indoor building. Besides that, we considered another algorithm based on weight centroid localization (WCL. In particular testbed, we combined both RSS and WCL as hybrid localization in case of noncooperative scheme with considering that source nodes directly communicate only with anchor nodes. Our experimental result shows localization accuracy of more than 90% and obtained the estimation error reduction to 4% compared to existing algorithms.

  14. Stable radio frequency dissemination by simple hybrid frequency modulation scheme.

    Science.gov (United States)

    Yu, Longqiang; Wang, Rong; Lu, Lin; Zhu, Yong; Wu, Chuanxin; Zhang, Baofu; Wang, Peizhang

    2014-09-15

    In this Letter, we propose a fiber-based stable radio frequency transfer system by a hybrid frequency modulation scheme. Creatively, two radio frequency signals are combined and simultaneously transferred by only one laser diode. One frequency component is used to detect the phase fluctuation, and the other one is the derivative compensated signal providing a stable frequency for the remote end. A proper ratio of the frequencies of the components is well maintained by parameter m to avoid interference between them. Experimentally, a stable 200 MHz signal is transferred over 100 km optical fiber with the help of a 1 GHz detecting signal, and fractional instability of 2×10(-17) at 10(5) s is achieved.

  15. Development and test of a classification scheme for human factors in incident reports

    International Nuclear Information System (INIS)

    Miller, R.; Freitag, M.; Wilpert, B.

    1997-01-01

    The Research Center System Safety of the Berlin University of Technology conducted a research project on the analysis of Human Factors (HF) aspects in incident reported by German Nuclear Power Plants. Based on psychological theories and empirical studies a classification scheme was developed which permits the identification of human involvement in incidents. The classification scheme was applied in an epidemiological study to a selection of more than 600 HF - relevant incidents. The results allow insights into HF related problem areas. An additional study proved that the application of the classification scheme produces results which are reliable and independent from raters. (author). 13 refs, 1 fig

  16. A scheme for a flexible classification of dietary and health biomarkers

    DEFF Research Database (Denmark)

    Gao, Qian; Pratico, Giulia; Scalbert, Augustin

    2017-01-01

    to have a solid scheme for biomarker classification that will provide a well-defined ontology for the field. In this manuscript, we provide an improved scheme for biomarker classification based on their intended use rather than the technology or outcomes (six subclasses are suggested: food compound intake...... in the scientific literature. However, the existing concepts for classification of biomarkers in the dietary and health area may be ambiguous, leading to uncertainty about their application. In order to better understand the potential of biomarkers and to communicate their use and application, it is imperative...... with previous biomarker classification for this field of research....

  17. Sound classification schemes in Europe - Quality classes intended for renovated housing

    DEFF Research Database (Denmark)

    Rasmussen, Birgit

    2010-01-01

    exposure in the home included in the proposed main objectives for a housing policy. In most countries in Europe, building regulations specify minimum requirements concerning acoustical conditions for new dwellings. In addition, several countries have introduced sound classification schemes with classes...... intended to reflect different levels of acoustical comfort. Consequently, acoustic requirements for a dwelling can be specified as the legal minimum requirements or as a specific class in a classification scheme. Most schemes have both higher classes than corresponding to the regulatory requirements...

  18. Data classification based on the hybrid intellectual technology

    Directory of Open Access Journals (Sweden)

    Demidova Liliya

    2018-01-01

    Full Text Available In this paper the data classification technique, implying the consistent application of the SVM and Parzen classifiers, has been suggested. The Parser classifier applies to data which can be both correctly and erroneously classified using the SVM classifier, and are located in the experimentally defined subareas near the hyperplane which separates the classes. A herewith, the SVM classifier is used with the default parameters values, and the optimal parameters values of the Parser classifier are determined using the genetic algorithm. The experimental results confirming the effectiveness of the proposed hybrid intellectual data classification technology have been presented.

  19. Acoustic classification schemes in Europe – Applicability for new, existing and renovated housing

    DEFF Research Database (Denmark)

    Rasmussen, Birgit

    2016-01-01

    The first acoustic classification schemes for dwellings were published in the 1990’es as national standards with the main purpose to introduce the possibility of specifying easily stricter acoustic criteria for new-build than the minimum requirements found in building regulations. Since then, more...... countries have introduced acoustic classification schemes, the first countries updated more times and some countries introduced acoustic classification also for other building categories. However, the classification schemes continued to focus on new buildings and have in general limited applicability...... for existing buildings from before implementation of acoustic regulations, typically in the 1950’es or later. The paper will summarize main characteristics, differences and similarities of the current national quality classes for housing in ten countries in Europe. In addition, the status and challenges...

  20. Electroencephalography epilepsy classifications using hybrid cuckoo search and neural network

    Science.gov (United States)

    Pratiwi, A. B.; Damayanti, A.; Miswanto

    2017-07-01

    Epilepsy is a condition that affects the brain and causes repeated seizures. This seizure is episodes that can vary and nearly undetectable to long periods of vigorous shaking or brain contractions. Epilepsy often can be confirmed with an electrocephalography (EEG). Neural Networks has been used in biomedic signal analysis, it has successfully classified the biomedic signal, such as EEG signal. In this paper, a hybrid cuckoo search and neural network are used to recognize EEG signal for epilepsy classifications. The weight of the multilayer perceptron is optimized by the cuckoo search algorithm based on its error. The aim of this methods is making the network faster to obtained the local or global optimal then the process of classification become more accurate. Based on the comparison results with the traditional multilayer perceptron, the hybrid cuckoo search and multilayer perceptron provides better performance in term of error convergence and accuracy. The purpose methods give MSE 0.001 and accuracy 90.0 %.

  1. OO (12) limit and complete classification of symmetry schemes in ...

    Indian Academy of Sciences (India)

    The generators of (12) are derived and the quantum number of (12) for a given boson number is determined by identifying the corresponding quasi-spin algebra. The (12) algebra generates two symmetry schemes and for both of them, complete classification of the basis states and typical spectra are given. With the ...

  2. On argumentation schemes and the natural classification of arguments

    NARCIS (Netherlands)

    Katzav, J.K.; Reed, C.

    2004-01-01

    We develop conceptions of arguments and of argument types that will, by serving as the basis for developing a natural classification of arguments, benefit work in artificial intelligence. Focusing only on arguments construed as the semantic entities that are the outcome of processes of reasoning, we

  3. Development of a Regional Habitat Classification Scheme for the ...

    African Journals Online (AJOL)

    development, image processing techniques and field survey methods are outlined. Habitat classification, and regional-scale comparisons of relative habitat composition are described. The study demonstrates the use of remote sensing data to construct digital habitat maps for the comparison of regional habitat coverage, ...

  4. Sound classification of dwellings – A diversity of national schemes in Europe

    DEFF Research Database (Denmark)

    Rasmussen, Birgit

    2011-01-01

    Sound classification schemes for dwellings exist in ten countries in Europe, typically prepared and published as national standards. The schemes define quality classes intended to reflect different levels of acoustical comfort. The main criteria concern airborne and impact sound insulation between...... dwellings, facade sound insulation and installation noise. This paper presents the sound classification schemes in Europe and compares the class criteria for sound insulation between dwellings. The schemes have been implemented and revised gradually since the early 1990s. However, due to lack...... constructions fulfilling different classes. The current variety of descriptors and classes also causes trade barriers. Thus, there is a need to harmonize characteristics of the schemes, and a European COST Action TU0901 "Integrating and Harmonizing Sound Insulation Aspects in Sustainable Urban Housing...

  5. On argumentation schemes and the natural classification of arguments

    OpenAIRE

    Katzav, K.; Reed, C.

    2004-01-01

    We develop conceptions of arguments and of argument types that will, by serving as the basis for developing a natural classification of arguments, benefit work in artificial intelligence. Focusing only on arguments construed as the semantic entities that are the outcome of processes of reasoning, we outline and clarify our view that an argument is a proposition that represents a fact as both conveying some other fact and as doing so wholly. Further, we outline our view that, with respect to a...

  6. Secure searching of biomarkers through hybrid homomorphic encryption scheme.

    Science.gov (United States)

    Kim, Miran; Song, Yongsoo; Cheon, Jung Hee

    2017-07-26

    As genome sequencing technology develops rapidly, there has lately been an increasing need to keep genomic data secure even when stored in the cloud and still used for research. We are interested in designing a protocol for the secure outsourcing matching problem on encrypted data. We propose an efficient method to securely search a matching position with the query data and extract some information at the position. After decryption, only a small amount of comparisons with the query information should be performed in plaintext state. We apply this method to find a set of biomarkers in encrypted genomes. The important feature of our method is to encode a genomic database as a single element of polynomial ring. Since our method requires a single homomorphic multiplication of hybrid scheme for query computation, it has the advantage over the previous methods in parameter size, computation complexity, and communication cost. In particular, the extraction procedure not only prevents leakage of database information that has not been queried by user but also reduces the communication cost by half. We evaluate the performance of our method and verify that the computation on large-scale personal data can be securely and practically outsourced to a cloud environment during data analysis. It takes about 3.9 s to search-and-extract the reference and alternate sequences at the queried position in a database of size 4M. Our solution for finding a set of biomarkers in DNA sequences shows the progress of cryptographic techniques in terms of their capability can support real-world genome data analysis in a cloud environment.

  7. Hybrid overlay metrology with CDSEM in a BEOL patterning scheme

    Science.gov (United States)

    Leray, Philippe; Jehoul, Christiane; Inoue, Osamu; Okagawa, Yutaka

    2015-03-01

    Overlay metrology accuracy is a major concern for our industry. Advanced logic process require more tighter overlay control for multipatterning schemes. TIS (Tool Induced Shift) and WIS (Wafer Induced Shift) are the main issues for IBO (Image Based Overlay) and DBO (Diffraction Based Overlay). Methods of compensation have been introduced, some are even very efficient to reduce these measured offsets. Another related question is about the overlay target designs. These targets are never fully representative of the design rules, strong efforts have been achieved, but the device cannot be completely duplicated. Ideally, we would like to measure in the device itself to verify the real overlay value. Top down CDSEM can measure critical dimensions of any structure, it is not dependent of specific target design. It can also measure the overlay errors but only in specific cases like LELE (Litho Etch Litho Etch) after final patterning. In this paper, we will revisit the capability of the CDSEM at final patterning by measuring overlay in dedicated targets as well as inside a logic and an SRAM design. In the dedicated overlay targets, we study the measurement differences between design rules gratings and relaxed pitch gratings. These relaxed pitch which are usually used in IBO or DBO targets. Beyond this "simple" LELE case, we will explore the capability of the CDSEM to measure overlay even if not at final patterning, at litho level. We will assess the hybridization of DBO and CDSEM for reference to optical tools after final patterning. We will show that these reference data can be used to validate the DBO overlay results (correctables and residual fingerprints).

  8. A Hybrid DGTD-MNA Scheme for Analyzing Complex Electromagnetic Systems

    KAUST Repository

    Li, Peng; Jiang, Li-Jun; Bagci, Hakan

    2015-01-01

    lumped circuit elements, the standard Newton-Raphson method is applied at every time step. Additionally, a local time-stepping scheme is developed to improve the efficiency of the hybrid solver. Numerical examples consisting of EM systems loaded

  9. The Nutraceutical Bioavailability Classification Scheme: Classifying Nutraceuticals According to Factors Limiting their Oral Bioavailability.

    Science.gov (United States)

    McClements, David Julian; Li, Fang; Xiao, Hang

    2015-01-01

    The oral bioavailability of a health-promoting dietary component (nutraceutical) may be limited by various physicochemical and physiological phenomena: liberation from food matrices, solubility in gastrointestinal fluids, interaction with gastrointestinal components, chemical degradation or metabolism, and epithelium cell permeability. Nutraceutical bioavailability can therefore be improved by designing food matrices that control their bioaccessibility (B*), absorption (A*), and transformation (T*) within the gastrointestinal tract (GIT). This article reviews the major factors influencing the gastrointestinal fate of nutraceuticals, and then uses this information to develop a new scheme to classify the major factors limiting nutraceutical bioavailability: the nutraceutical bioavailability classification scheme (NuBACS). This new scheme is analogous to the biopharmaceutical classification scheme (BCS) used by the pharmaceutical industry to classify drug bioavailability, but it contains additional factors important for understanding nutraceutical bioavailability in foods. The article also highlights potential strategies for increasing the oral bioavailability of nutraceuticals based on their NuBACS designation (B*A*T*).

  10. Simple adaptive sparse representation based classification schemes for EEG based brain-computer interface applications.

    Science.gov (United States)

    Shin, Younghak; Lee, Seungchan; Ahn, Minkyu; Cho, Hohyun; Jun, Sung Chan; Lee, Heung-No

    2015-11-01

    One of the main problems related to electroencephalogram (EEG) based brain-computer interface (BCI) systems is the non-stationarity of the underlying EEG signals. This results in the deterioration of the classification performance during experimental sessions. Therefore, adaptive classification techniques are required for EEG based BCI applications. In this paper, we propose simple adaptive sparse representation based classification (SRC) schemes. Supervised and unsupervised dictionary update techniques for new test data and a dictionary modification method by using the incoherence measure of the training data are investigated. The proposed methods are very simple and additional computation for the re-training of the classifier is not needed. The proposed adaptive SRC schemes are evaluated using two BCI experimental datasets. The proposed methods are assessed by comparing classification results with the conventional SRC and other adaptive classification methods. On the basis of the results, we find that the proposed adaptive schemes show relatively improved classification accuracy as compared to conventional methods without requiring additional computation. Copyright © 2015 Elsevier Ltd. All rights reserved.

  11. Hybrid Modulation Scheme for Cascaded H-Bridge Inverter Cells ...

    African Journals Online (AJOL)

    This work proposes a switching technique for cascaded H-Bridge (CHB) cells. Single carrier Sinusoidal PWM (SCSPWM) scheme is employed in the generation of the gating signals. A sequential switching and base PWM circulation schemes are presented for this fundamental cascaded multilevel inverter topology.

  12. Optical Code-Division Multiple-Access and Wavelength Division Multiplexing: Hybrid Scheme Review

    OpenAIRE

    P. Susthitha Menon; Sahbudin Shaari; Isaac A.M. Ashour; Hesham A. Bakarman

    2012-01-01

    Problem statement: Hybrid Optical Code-Division Multiple-Access (OCDMA) and Wavelength-Division Multiplexing (WDM) have flourished as successful schemes for expanding the transmission capacity as well as enhancing the security for OCDMA. However, a comprehensive review related to this hybrid system are lacking currently. Approach: The purpose of this paper is to review the literature on OCDMA-WDM overlay systems, including our hybrid approach of one-dimensional coding of SAC OCDMA with WDM si...

  13. Developing a contributing factor classification scheme for Rasmussen's AcciMap: Reliability and validity evaluation.

    Science.gov (United States)

    Goode, N; Salmon, P M; Taylor, N Z; Lenné, M G; Finch, C F

    2017-10-01

    One factor potentially limiting the uptake of Rasmussen's (1997) Accimap method by practitioners is the lack of a contributing factor classification scheme to guide accident analyses. This article evaluates the intra- and inter-rater reliability and criterion-referenced validity of a classification scheme developed to support the use of Accimap by led outdoor activity (LOA) practitioners. The classification scheme has two levels: the system level describes the actors, artefacts and activity context in terms of 14 codes; the descriptor level breaks the system level codes down into 107 specific contributing factors. The study involved 11 LOA practitioners using the scheme on two separate occasions to code a pre-determined list of contributing factors identified from four incident reports. Criterion-referenced validity was assessed by comparing the codes selected by LOA practitioners to those selected by the method creators. Mean intra-rater reliability scores at the system (M = 83.6%) and descriptor (M = 74%) levels were acceptable. Mean inter-rater reliability scores were not consistently acceptable for both coding attempts at the system level (M T1  = 68.8%; M T2  = 73.9%), and were poor at the descriptor level (M T1  = 58.5%; M T2  = 64.1%). Mean criterion referenced validity scores at the system level were acceptable (M T1  = 73.9%; M T2  = 75.3%). However, they were not consistently acceptable at the descriptor level (M T1  = 67.6%; M T2  = 70.8%). Overall, the results indicate that the classification scheme does not currently satisfy reliability and validity requirements, and that further work is required. The implications for the design and development of contributing factors classification schemes are discussed. Copyright © 2017 Elsevier Ltd. All rights reserved.

  14. A hybrid ensemble learning approach to star-galaxy classification

    Science.gov (United States)

    Kim, Edward J.; Brunner, Robert J.; Carrasco Kind, Matias

    2015-10-01

    There exist a variety of star-galaxy classification techniques, each with their own strengths and weaknesses. In this paper, we present a novel meta-classification framework that combines and fully exploits different techniques to produce a more robust star-galaxy classification. To demonstrate this hybrid, ensemble approach, we combine a purely morphological classifier, a supervised machine learning method based on random forest, an unsupervised machine learning method based on self-organizing maps, and a hierarchical Bayesian template-fitting method. Using data from the CFHTLenS survey (Canada-France-Hawaii Telescope Lensing Survey), we consider different scenarios: when a high-quality training set is available with spectroscopic labels from DEEP2 (Deep Extragalactic Evolutionary Probe Phase 2 ), SDSS (Sloan Digital Sky Survey), VIPERS (VIMOS Public Extragalactic Redshift Survey), and VVDS (VIMOS VLT Deep Survey), and when the demographics of sources in a low-quality training set do not match the demographics of objects in the test data set. We demonstrate that our Bayesian combination technique improves the overall performance over any individual classification method in these scenarios. Thus, strategies that combine the predictions of different classifiers may prove to be optimal in currently ongoing and forthcoming photometric surveys, such as the Dark Energy Survey and the Large Synoptic Survey Telescope.

  15. A New Feature Ensemble with a Multistage Classification Scheme for Breast Cancer Diagnosis

    Directory of Open Access Journals (Sweden)

    Idil Isikli Esener

    2017-01-01

    Full Text Available A new and effective feature ensemble with a multistage classification is proposed to be implemented in a computer-aided diagnosis (CAD system for breast cancer diagnosis. A publicly available mammogram image dataset collected during the Image Retrieval in Medical Applications (IRMA project is utilized to verify the suggested feature ensemble and multistage classification. In achieving the CAD system, feature extraction is performed on the mammogram region of interest (ROI images which are preprocessed by applying a histogram equalization followed by a nonlocal means filtering. The proposed feature ensemble is formed by concatenating the local configuration pattern-based, statistical, and frequency domain features. The classification process of these features is implemented in three cases: a one-stage study, a two-stage study, and a three-stage study. Eight well-known classifiers are used in all cases of this multistage classification scheme. Additionally, the results of the classifiers that provide the top three performances are combined via a majority voting technique to improve the recognition accuracy on both two- and three-stage studies. A maximum of 85.47%, 88.79%, and 93.52% classification accuracies are attained by the one-, two-, and three-stage studies, respectively. The proposed multistage classification scheme is more effective than the single-stage classification for breast cancer diagnosis.

  16. Hybrid flux splitting schemes for numerical resolution of two-phase flows

    Energy Technology Data Exchange (ETDEWEB)

    Flaatten, Tore

    2003-07-01

    This thesis deals with the construction of numerical schemes for approximating. solutions to a hyperbolic two-phase flow model. Numerical schemes for hyperbolic models are commonly divided in two main classes: Flux Vector Splitting (FVS) schemes which are based on scalar computations and Flux Difference Splitting (FDS) schemes which are based on matrix computations. FVS schemes are more efficient than FDS schemes, but FDS schemes are more accurate. The canonical FDS schemes are the approximate Riemann solvers which are based on a local decomposition of the system into its full wave structure. In this thesis the mathematical structure of the model is exploited to construct a class of hybrid FVS/FDS schemes, denoted as Mixture Flux (MF) schemes. This approach is based on a splitting of the system in two components associated with the pressure and volume fraction variables respectively, and builds upon hybrid FVS/FDS schemes previously developed for one-phase flow models. Through analysis and numerical experiments it is demonstrated that the MF approach provides several desirable features, including (1) Improved efficiency compared to standard approximate Riemann solvers, (2) Robustness under stiff conditions, (3) Accuracy on linear and nonlinear phenomena. In particular it is demonstrated that the framework allows for an efficient weakly implicit implementation, focusing on an accurate resolution of slow transients relevant for the petroleum industry. (author)

  17. A Classification Scheme for Adult Education. Education Libraries Bulletin, Supplement Twelve.

    Science.gov (United States)

    Greaves, Monica A., Comp.

    This classification scheme, based on the 'facet formula' theory of Ranganathan, is designed primarily for the library of the National Institute of Adult Education in London, England. Kinds of persons being educated (educands), methods and problems of education, specific countries, specific organizations, and forms in which the information is…

  18. Standard land-cover classification scheme for remote-sensing applications in South Africa

    CSIR Research Space (South Africa)

    Thompson, M

    1996-01-01

    Full Text Available For large areas, satellite remote-sensing techniques have now become the single most effective method for land-cover and land-use data acquisition. However, the majority of land-cover (and land-use) classification schemes used have been developed...

  19. Dose classification scheme for digital imaging techniques in diagnostic radiology

    International Nuclear Information System (INIS)

    Hojreh, A.

    2002-04-01

    CT all clinical questions can be answered with certainty and regardless of clinical experience of the involved physician. They are often recommended by the equipment manufacturers and should be reviewed critically because of their high radiation exposure. Conclusion: the classification of applicable doses in three classes can generally be considered as a practicable way of dose reduction. (author)

  20. A New Hybrid Channel Access Scheme for Ad Hoc Networks

    National Research Council Canada - National Science Library

    Wang, Yu; Garcia-Luna-Aceves, J. J

    2002-01-01

    Many contention-based channel access schemes have been proposed for multi-hop ad hoc networks in the recent past, and they can be divided into two categories, sender-initiated and receiver-initiated...

  1. An intelligent hybrid scheme for optimizing parking space: A Tabu metaphor and rough set based approach

    Directory of Open Access Journals (Sweden)

    Soumya Banerjee

    2011-03-01

    Full Text Available Congested roads, high traffic, and parking problems are major concerns for any modern city planning. Congestion of on-street spaces in official neighborhoods may give rise to inappropriate parking areas in office and shopping mall complex during the peak time of official transactions. This paper proposes an intelligent and optimized scheme to solve parking space problem for a small city (e.g., Mauritius using a reactive search technique (named as Tabu Search assisted by rough set. Rough set is being used for the extraction of uncertain rules that exist in the databases of parking situations. The inclusion of rough set theory depicts the accuracy and roughness, which are used to characterize uncertainty of the parking lot. Approximation accuracy is employed to depict accuracy of a rough classification [1] according to different dynamic parking scenarios. And as such, the hybrid metaphor proposed comprising of Tabu Search and rough set could provide substantial research directions for other similar hard optimization problems.

  2. VLSI Implementation of Hybrid Wave-Pipelined 2D DWT Using Lifting Scheme

    Directory of Open Access Journals (Sweden)

    G. Seetharaman

    2008-01-01

    Full Text Available A novel approach is proposed in this paper for the implementation of 2D DWT using hybrid wave-pipelining (WP. A digital circuit may be operated at a higher frequency by using either pipelining or WP. Pipelining requires additional registers and it results in more area, power dissipation and clock routing complexity. Wave-pipelining does not have any of these disadvantages but requires complex trial and error procedure for tuning the clock period and clock skew between input and output registers. In this paper, a hybrid scheme is proposed to get the benefits of both pipelining and WP techniques. In this paper, two automation schemes are proposed for the implementation of 2D DWT using hybrid WP on both Xilinx, San Jose, CA, USA and Altera FPGAs. In the first scheme, Built-in self-test (BIST approach is used to choose the clock skew and clock period for I/O registers between the wave-pipelined blocks. In the second approach, an on-chip soft-core processor is used to choose the clock skew and clock period. The results for the hybrid WP are compared with nonpipelined and pipelined approaches. From the implementation results, the hybrid WP scheme requires the same area but faster than the nonpipelined scheme by a factor of 1.25–1.39. The pipelined scheme is faster than the hybrid scheme by a factor of 1.15–1.39 at the cost of an increase in the number of registers by a factor of 1.78–2.73, increase in the number of LEs by a factor of 1.11–1.32 and it increases the clock routing complexity.

  3. Large-eddy simulation/Reynolds-averaged Navier-Stokes hybrid schemes for high speed flows

    Science.gov (United States)

    Xiao, Xudong

    Three LES/RANS hybrid schemes have been proposed for the prediction of high speed separated flows. Each method couples the k-zeta (Enstrophy) BANS model with an LES subgrid scale one-equation model by using a blending function that is coordinate system independent. Two of these functions are based on turbulence dissipation length scale and grid size, while the third one has no explicit dependence on the grid. To implement the LES/RANS hybrid schemes, a new rescaling-reintroducing method is used to generate time-dependent turbulent inflow conditions. The hybrid schemes have been tested on a Mach 2.88 flow over 25 degree compression-expansion ramp and a Mach 2.79 flow over 20 degree compression ramp. A special computation procedure has been designed to prevent the separation zone from expanding upstream to the recycle-plane. The code is parallelized using Message Passing Interface (MPI) and is optimized for running on IBM-SP3 parallel machine. The scheme was validated first for a flat plate. It was shown that the blending function has to be monotonic to prevent the RANS region from appearing in the LES region. In the 25 deg ramp case, the hybrid schemes provided better agreement with experiment in the recovery region. Grid refinement studies demonstrated the importance of using a grid independent blend function and further improvement with experiment in the recovery region. In the 20 deg ramp case, with a relatively finer grid, the hybrid scheme characterized by grid independent blending function well predicted the flow field in both the separation region and the recovery region. Therefore, with "appropriately" fine grid, current hybrid schemes are promising for the simulation of shock wave/boundary layer interaction problems.

  4. A comparison between national scheme for the acoustic classification of dwellings in Europe and in the U.S

    DEFF Research Database (Denmark)

    Berardi, Umberto; Rasmussen, Birgit

    2015-01-01

    , focusing on sound insulation performance, national schemes for sound classification of dwellings have been developed in several European countries. These schemes define acoustic classes according to different levels of sound insulation. Due to the lack of coordination among countries, a significant...... scheme may facilitate exchanging experiences about constructions fulfilling different classes, reducing trade barriers, and finally increasing the sound insulation of dwellings....... diversity in terms of descriptors, number of classes, and class intervals occurred between national schemes. However, a proposal ”acoustic classification scheme for dwellings” has been developed recently in the European COST Action TU0901 with 32 member countries. This proposal has been accepted as an ISO...

  5. Evaluation of Effectiveness of Wavelet Based Denoising Schemes Using ANN and SVM for Bearing Condition Classification

    Directory of Open Access Journals (Sweden)

    Vijay G. S.

    2012-01-01

    Full Text Available The wavelet based denoising has proven its ability to denoise the bearing vibration signals by improving the signal-to-noise ratio (SNR and reducing the root-mean-square error (RMSE. In this paper seven wavelet based denoising schemes have been evaluated based on the performance of the Artificial Neural Network (ANN and the Support Vector Machine (SVM, for the bearing condition classification. The work consists of two parts, the first part in which a synthetic signal simulating the defective bearing vibration signal with Gaussian noise was subjected to these denoising schemes. The best scheme based on the SNR and the RMSE was identified. In the second part, the vibration signals collected from a customized Rolling Element Bearing (REB test rig for four bearing conditions were subjected to these denoising schemes. Several time and frequency domain features were extracted from the denoised signals, out of which a few sensitive features were selected using the Fisher’s Criterion (FC. Extracted features were used to train and test the ANN and the SVM. The best denoising scheme identified, based on the classification performances of the ANN and the SVM, was found to be the same as the one obtained using the synthetic signal.

  6. An approach toward a combined scheme for the petrographic classification of fly ash: Revision and clarification

    Science.gov (United States)

    Hower, J.C.; Suarez-Ruiz, I.; Mastalerz, Maria

    2005-01-01

    Hower and Mastalerz's classification scheme for fly ash is modified to make more widely acceptable. First, proper consideration is given to the potential role of anthracite in the development of isotropic and anisotropic chars. Second, the role of low-reflectance inertinite in producing vesicular chars is noted. It is shown that noncoal chars in the fuel can potentially produce chars that have the potential to stretch the limits of the classification. With care, it is possible to classify certain biomass chars as being distinct from coal-derived chars.

  7. A Hybrid Data Compression Scheme for Improved VNC

    OpenAIRE

    Xiaozheng (Jane) Zhang; Hirofumi Takahashi

    2007-01-01

    Virtual Network Computing (VNC) has emerged as a promising technology in distributed computing environment since its invention in the late nineties. Successful application of VNC requires rapid data transfer from one machine to another over a TCP/IP network connection. However transfer of screen data consumes much network bandwidth and current data encoding schemes for VNC are far from being ideal. This paper seeks to improve screen data compression techniques to enable VNC over slow connecti...

  8. Development of a Hazard Classification Scheme for Substances Used in the Fraudulent Adulteration of Foods.

    Science.gov (United States)

    Everstine, Karen; Abt, Eileen; McColl, Diane; Popping, Bert; Morrison-Rowe, Sara; Lane, Richard W; Scimeca, Joseph; Winter, Carl; Ebert, Andrew; Moore, Jeffrey C; Chin, Henry B

    2018-01-01

    Food fraud, the intentional misrepresentation of the true identity of a food product or ingredient for economic gain, is a threat to consumer confidence and public health and has received increased attention from both regulators and the food industry. Following updates to food safety certification standards and publication of new U.S. regulatory requirements, we undertook a project to (i) develop a scheme to classify food fraud-related adulterants based on their potential health hazard and (ii) apply this scheme to the adulterants in a database of 2,970 food fraud records. The classification scheme was developed by a panel of experts in food safety and toxicology from the food industry, academia, and the U.S. Food and Drug Administration. Categories and subcategories were created through an iterative process of proposal, review, and validation using a subset of substances known to be associated with the fraudulent adulteration of foods. Once developed, the scheme was applied to the adulterants in the database. The resulting scheme included three broad categories: 1, potentially hazardous adulterants; 2, adulterants that are unlikely to be hazardous; and 3, unclassifiable adulterants. Categories 1 and 2 consisted of seven subcategories intended to further define the range of hazard potential for adulterants. Application of the scheme to the 1,294 adulterants in the database resulted in 45% of adulterants classified in category 1 (potentially hazardous). Twenty-seven percent of the 1,294 adulterants had a history of causing consumer illness or death, were associated with safety-related regulatory action, or were classified as allergens. These results reinforce the importance of including a consideration of food fraud-related adulterants in food safety systems. This classification scheme supports food fraud mitigation efforts and hazard identification as required in the U.S. Food Safety Modernization Act Preventive Controls Rules.

  9. Joint efforts to harmonize sound insulation descriptors and classification schemes in Europe (COST TU0901)

    DEFF Research Database (Denmark)

    Rasmussen, Birgit

    2010-01-01

    Sound insulation descriptors, regulatory requirements and classification schemes in Europe represent a high degree of diversity. One implication is very little exchange of experience of housing design and construction details for different levels of sound insulation; another is trade barriers...... for building systems and products. Unfortunately, there is evidence for a development in the "wrong" direction. For example, sound classification schemes for dwellings exist in nine countries. There is no sign on increasing harmonization, rather the contrary, as more countries are preparing proposals with new......, new housing must meet the needs of the people and offer comfort. Also for existing housing, sound insulation aspects should be taken into account, when renovating housing; otherwise the renovation is not “sustainable”. A joint European Action, COST TU0901 "Integrating and Harmonizing Sound Insulation...

  10. Acoustic classification of buildings in Europe – Main characteristics of national schemes for housing, schools, hospitals and office buildings

    DEFF Research Database (Denmark)

    Rasmussen, Birgit

    2018-01-01

    schemes define limit values for a number of acoustic performance areas, typically airborne and impact sound insulation, service equipment noise, traffic noise and reverberation time, i.e. the same as in regulations. Comparative studies of the national acoustic classification schemes in Europe show main......Building regulations specify minimum requirements, and more than ten countries in Europe have published national acoustic classification schemes with quality classes, the main purpose being to introduce easy specification of stricter acoustic criteria than defined in regulations. The very first...... classification schemes were published in the mid 1990’es and for dwellings only. Since then, more countries have introduced such schemes, some including also other building categories like e.g. schools, hospitals and office buildings, and the first countries have made updates more times. Acoustic classification...

  11. An Empirical Study on User-oriented Association Analysis of Library Classification Schemes

    Directory of Open Access Journals (Sweden)

    Hsiao-Tieh Pu

    2002-12-01

    Full Text Available Library classification schemes are mostly organized based on disciplines with a hierarchical structure. From the user point of view, some highly related yet non-hierarchical classes may not be easy to perceive in these schemes. This paper is to discover hidden associations between classes by analyzing users’ usage of library collections. The proposed approach employs collaborative filtering techniques to discover associated classes based on the circulation patterns of similar users. Many associated classes scattered across different subject hierarchies could be discovered from the circulation patterns of similar users. The obtained association norms between classes were found to be useful in understanding users' subject preferences for a given class. Classification schemes can, therefore, be made more adaptable to changes of users and the uses of different library collections. There are implications for applications in information organization and retrieval as well. For example, catalogers could refer to the ranked associated classes when they perform multi-classification, and users could also browse the associated classes for related subjects in an enhanced OPAC system. In future research, more empirical studies will be needed to validate the findings, and methods for obtaining user-oriented associations can still be improved.[Article content in Chinese

  12. Assessment of hybrid rotation-translation scan schemes for in vivo animal SPECT imaging

    International Nuclear Information System (INIS)

    Xia Yan; Liu Yaqiang; Wang Shi; Ma Tianyu; Yao Rutao; Deng Xiao

    2013-01-01

    To perform in vivo animal single photon emission computed tomography imaging on a stationary detector gantry, we introduced a hybrid rotation-translation (HRT) tomographic scan, a combination of translational and limited angle rotational movements of the image object, to minimize gravity-induced animal motion. To quantitatively assess the performance of ten HRT scan schemes and the conventional rotation-only scan scheme, two simulated phantoms were first scanned with each scheme to derive the corresponding image resolution (IR) in the image field of view. The IR results of all the scan schemes were visually assessed and compared with corresponding outputs of four scan scheme evaluation indices, i.e. sampling completeness (SC), sensitivity (S), conventional system resolution (SR), and a newly devised directional spatial resolution (DR) that measures the resolution in any specified orientation. A representative HRT scheme was tested with an experimental phantom study. Eight of the ten HRT scan schemes evaluated achieved a superior performance compared to two other HRT schemes and the rotation-only scheme in terms of phantom image resolution. The same eight HRT scan schemes also achieved equivalent or better performance in terms of the four quantitative indices than the conventional rotation-only scheme. As compared to the conventional index SR, the new index DR appears to be a more relevant indicator of system resolution performance. The experimental phantom image obtained from the selected HRT scheme was satisfactory. We conclude that it is feasible to perform in vivo animal imaging with a HRT scan scheme and SC and DR are useful predictors for quantitatively assessing the performance of a scan scheme. (paper)

  13. DREAM: Classification scheme for dialog acts in clinical research query mediation.

    Science.gov (United States)

    Hoxha, Julia; Chandar, Praveen; He, Zhe; Cimino, James; Hanauer, David; Weng, Chunhua

    2016-02-01

    Clinical data access involves complex but opaque communication between medical researchers and query analysts. Understanding such communication is indispensable for designing intelligent human-machine dialog systems that automate query formulation. This study investigates email communication and proposes a novel scheme for classifying dialog acts in clinical research query mediation. We analyzed 315 email messages exchanged in the communication for 20 data requests obtained from three institutions. The messages were segmented into 1333 utterance units. Through a rigorous process, we developed a classification scheme and applied it for dialog act annotation of the extracted utterances. Evaluation results with high inter-annotator agreement demonstrate the reliability of this scheme. This dataset is used to contribute preliminary understanding of dialog acts distribution and conversation flow in this dialog space. Copyright © 2015 Elsevier Inc. All rights reserved.

  14. Mental Task Classification Scheme Utilizing Correlation Coefficient Extracted from Interchannel Intrinsic Mode Function.

    Science.gov (United States)

    Rahman, Md Mostafizur; Fattah, Shaikh Anowarul

    2017-01-01

    In view of recent increase of brain computer interface (BCI) based applications, the importance of efficient classification of various mental tasks has increased prodigiously nowadays. In order to obtain effective classification, efficient feature extraction scheme is necessary, for which, in the proposed method, the interchannel relationship among electroencephalogram (EEG) data is utilized. It is expected that the correlation obtained from different combination of channels will be different for different mental tasks, which can be exploited to extract distinctive feature. The empirical mode decomposition (EMD) technique is employed on a test EEG signal obtained from a channel, which provides a number of intrinsic mode functions (IMFs), and correlation coefficient is extracted from interchannel IMF data. Simultaneously, different statistical features are also obtained from each IMF. Finally, the feature matrix is formed utilizing interchannel correlation features and intrachannel statistical features of the selected IMFs of EEG signal. Different kernels of the support vector machine (SVM) classifier are used to carry out the classification task. An EEG dataset containing ten different combinations of five different mental tasks is utilized to demonstrate the classification performance and a very high level of accuracy is achieved by the proposed scheme compared to existing methods.

  15. Agent-based power sharing scheme for active hybrid power sources

    Science.gov (United States)

    Jiang, Zhenhua

    The active hybridization technique provides an effective approach to combining the best properties of a heterogeneous set of power sources to achieve higher energy density, power density and fuel efficiency. Active hybrid power sources can be used to power hybrid electric vehicles with selected combinations of internal combustion engines, fuel cells, batteries, and/or supercapacitors. They can be deployed in all-electric ships to build a distributed electric power system. They can also be used in a bulk power system to construct an autonomous distributed energy system. An important aspect in designing an active hybrid power source is to find a suitable control strategy that can manage the active power sharing and take advantage of the inherent scalability and robustness benefits of the hybrid system. This paper presents an agent-based power sharing scheme for active hybrid power sources. To demonstrate the effectiveness of the proposed agent-based power sharing scheme, simulation studies are performed for a hybrid power source that can be used in a solar car as the main propulsion power module. Simulation results clearly indicate that the agent-based control framework is effective to coordinate the various energy sources and manage the power/voltage profiles.

  16. A second-order iterative implicit-explicit hybrid scheme for hyperbolic systems of conservation laws

    International Nuclear Information System (INIS)

    Dai, Wenlong; Woodward, P.R.

    1996-01-01

    An iterative implicit-explicit hybrid scheme is proposed for hyperbolic systems of conservation laws. Each wave in a system may be implicitly, or explicitly, or partially implicitly and partially explicitly treated depending on its associated Courant number in each numerical cell, and the scheme is able to smoothly switch between implicit and explicit calculations. The scheme is of Godunov-type in both explicit and implicit regimes, is in a strict conservation form, and is accurate to second-order in both space and time for all Courant numbers. The computer code for the scheme is easy to vectorize. Multicolors proposed in this paper may reduce the number of iterations required to reach a converged solution by several orders for a large time step. The feature of the scheme is shown through numerical examples. 38 refs., 12 figs

  17. A new scheme for urban impervious surface classification from SAR images

    Science.gov (United States)

    Zhang, Hongsheng; Lin, Hui; Wang, Yunpeng

    2018-05-01

    Urban impervious surfaces have been recognized as a significant indicator for various environmental and socio-economic studies. There is an increasingly urgent demand for timely and accurate monitoring of the impervious surfaces with satellite technology from local to global scales. In the past decades, optical remote sensing has been widely employed for this task with various techniques. However, there are still a range of challenges, e.g. handling cloud contamination on optical data. Therefore, the Synthetic Aperture Radar (SAR) was introduced for the challenging task because it is uniquely all-time- and all-weather-capable. Nevertheless, with an increasing number of SAR data applied, the methodology used for impervious surfaces classification remains unchanged from the methods used for optical datasets. This shortcoming has prevented the community from fully exploring the potential of using SAR data for impervious surfaces classification. We proposed a new scheme that is comparable to the well-known and fundamental Vegetation-Impervious surface-Soil (V-I-S) model for mapping urban impervious surfaces. Three scenes of fully polarimetric Radsarsat-2 data for the cities of Shenzhen, Hong Kong and Macau were employed to test and validate the proposed methodology. Experimental results indicated that the overall accuracy and Kappa coefficient were 96.00% and 0.8808 in Shenzhen, 93.87% and 0.8307 in Hong Kong and 97.48% and 0.9354 in Macau, indicating the applicability and great potential of the new scheme for impervious surfaces classification using polarimetric SAR data. Comparison with the traditional scheme indicated that this new scheme was able to improve the overall accuracy by up to 4.6% and Kappa coefficient by up to 0.18.

  18. A Multi-layer Hybrid Framework for Dimensional Emotion Classification

    NARCIS (Netherlands)

    Nicolaou, Mihalis A.; Gunes, Hatice; Pantic, Maja

    2011-01-01

    This paper investigates dimensional emotion prediction and classification from naturalistic facial expressions. Similarly to many pattern recognition problems, dimensional emotion classification requires generating multi-dimensional outputs. To date, classification for valence and arousal dimensions

  19. Medical X-ray Image Hierarchical Classification Using a Merging and Splitting Scheme in Feature Space.

    Science.gov (United States)

    Fesharaki, Nooshin Jafari; Pourghassem, Hossein

    2013-07-01

    Due to the daily mass production and the widespread variation of medical X-ray images, it is necessary to classify these for searching and retrieving proposes, especially for content-based medical image retrieval systems. In this paper, a medical X-ray image hierarchical classification structure based on a novel merging and splitting scheme and using shape and texture features is proposed. In the first level of the proposed structure, to improve the classification performance, similar classes with regard to shape contents are grouped based on merging measures and shape features into the general overlapped classes. In the next levels of this structure, the overlapped classes split in smaller classes based on the classification performance of combination of shape and texture features or texture features only. Ultimately, in the last levels, this procedure is also continued forming all the classes, separately. Moreover, to optimize the feature vector in the proposed structure, we use orthogonal forward selection algorithm according to Mahalanobis class separability measure as a feature selection and reduction algorithm. In other words, according to the complexity and inter-class distance of each class, a sub-space of the feature space is selected in each level and then a supervised merging and splitting scheme is applied to form the hierarchical classification. The proposed structure is evaluated on a database consisting of 2158 medical X-ray images of 18 classes (IMAGECLEF 2005 database) and accuracy rate of 93.6% in the last level of the hierarchical structure for an 18-class classification problem is obtained.

  20. A hybrid convection scheme for use in non-hydrostatic numerical weather prediction models

    Directory of Open Access Journals (Sweden)

    Volker Kuell

    2008-12-01

    Full Text Available The correct representation of convection in numerical weather prediction (NWP models is essential for quantitative precipitation forecasts. Due to its small horizontal scale convection usually has to be parameterized, e.g. by mass flux convection schemes. Classical schemes originally developed for use in coarse grid NWP models assume zero net convective mass flux, because the whole circulation of a convective cell is confined to the local grid column and all convective mass fluxes cancel out. However, in contemporary NWP models with grid sizes of a few kilometers this assumption becomes questionable, because here convection is partially resolved on the grid. To overcome this conceptual problem we propose a hybrid mass flux convection scheme (HYMACS in which only the convective updrafts and downdrafts are parameterized. The generation of the larger scale environmental subsidence, which may cover several grid columns, is transferred to the grid scale equations. This means that the convection scheme now has to generate a net convective mass flux exerting a direct dynamical forcing to the grid scale model via pressure gradient forces. The hybrid convection scheme implemented into the COSMO model of Deutscher Wetterdienst (DWD is tested in an idealized simulation of a sea breeze circulation initiating convection in a realistic manner. The results are compared with analogous simulations with the classical Tiedtke and Kain-Fritsch convection schemes.

  1. Hybrid Collaborative Learning for Classification and Clustering in Sensor Networks

    Science.gov (United States)

    Wagstaff, Kiri L.; Sosnowski, Scott; Lane, Terran

    2012-01-01

    Traditionally, nodes in a sensor network simply collect data and then pass it on to a centralized node that archives, distributes, and possibly analyzes the data. However, analysis at the individual nodes could enable faster detection of anomalies or other interesting events as well as faster responses, such as sending out alerts or increasing the data collection rate. There is an additional opportunity for increased performance if learners at individual nodes can communicate with their neighbors. In previous work, methods were developed by which classification algorithms deployed at sensor nodes can communicate information about event labels to each other, building on prior work with co-training, self-training, and active learning. The idea of collaborative learning was extended to function for clustering algorithms as well, similar to ideas from penta-training and consensus clustering. However, collaboration between these learner types had not been explored. A new protocol was developed by which classifiers and clusterers can share key information about their observations and conclusions as they learn. This is an active collaboration in which learners of either type can query their neighbors for information that they then use to re-train or re-learn the concept they are studying. The protocol also supports broadcasts from the classifiers and clusterers to the rest of the network to announce new discoveries. Classifiers observe an event and assign it a label (type). Clusterers instead group observations into clusters without assigning them a label, and they collaborate in terms of pairwise constraints between two events [same-cluster (mustlink) or different-cluster (cannot-link)]. Fundamentally, these two learner types speak different languages. To bridge this gap, the new communication protocol provides four types of exchanges: hybrid queries for information, hybrid "broadcasts" of learned information, each specified for classifiers-to-clusterers, and clusterers

  2. A new classification scheme of plastic wastes based upon recycling labels

    Energy Technology Data Exchange (ETDEWEB)

    Özkan, Kemal, E-mail: kozkan@ogu.edu.tr [Computer Engineering Dept., Eskişehir Osmangazi University, 26480 Eskişehir (Turkey); Ergin, Semih, E-mail: sergin@ogu.edu.tr [Electrical Electronics Engineering Dept., Eskişehir Osmangazi University, 26480 Eskişehir (Turkey); Işık, Şahin, E-mail: sahini@ogu.edu.tr [Computer Engineering Dept., Eskişehir Osmangazi University, 26480 Eskişehir (Turkey); Işıklı, İdil, E-mail: idil.isikli@bilecik.edu.tr [Electrical Electronics Engineering Dept., Bilecik University, 11210 Bilecik (Turkey)

    2015-01-15

    experimental setup with a camera and homogenous backlighting. Due to the giving global solution for a classification problem, Support Vector Machine (SVM) is selected to achieve the classification task and majority voting technique is used as the decision mechanism. This technique equally weights each classification result and assigns the given plastic object to the class that the most classification results agree on. The proposed classification scheme provides high accuracy rate, and also it is able to run in real-time applications. It can automatically classify the plastic bottle types with approximately 90% recognition accuracy. Besides this, the proposed methodology yields approximately 96% classification rate for the separation of PET or non-PET plastic types. It also gives 92% accuracy for the categorization of non-PET plastic types into HPDE or PP.

  3. A new classification scheme of plastic wastes based upon recycling labels

    International Nuclear Information System (INIS)

    Özkan, Kemal; Ergin, Semih; Işık, Şahin; Işıklı, İdil

    2015-01-01

    experimental setup with a camera and homogenous backlighting. Due to the giving global solution for a classification problem, Support Vector Machine (SVM) is selected to achieve the classification task and majority voting technique is used as the decision mechanism. This technique equally weights each classification result and assigns the given plastic object to the class that the most classification results agree on. The proposed classification scheme provides high accuracy rate, and also it is able to run in real-time applications. It can automatically classify the plastic bottle types with approximately 90% recognition accuracy. Besides this, the proposed methodology yields approximately 96% classification rate for the separation of PET or non-PET plastic types. It also gives 92% accuracy for the categorization of non-PET plastic types into HPDE or PP

  4. Proposed classification scheme for high-level and other radioactive wastes

    International Nuclear Information System (INIS)

    Kocher, D.C.; Croff, A.G.

    1986-01-01

    The Nuclear Waste Policy Act (NWPA) of 1982 defines high-level radioactive waste (HLW) as: (A) the highly radioactive material resulting from the reprocessing of spent nuclear fuel....that contains fission products in sufficient concentrations; and (B) other highly radioactive material that the Commission....determines....requires permanent isolation. This paper presents a generally applicable quantitative definition of HLW that addresses the description in paragraph (B). The approach also results in definitions of other waste classes, i.e., transuranic (TRU) and low-level waste (LLW). A basic waste classification scheme results from the quantitative definitions

  5. Hybrid threshold adaptable quantum secret sharing scheme with reverse Huffman-Fibonacci-tree coding.

    Science.gov (United States)

    Lai, Hong; Zhang, Jun; Luo, Ming-Xing; Pan, Lei; Pieprzyk, Josef; Xiao, Fuyuan; Orgun, Mehmet A

    2016-08-12

    With prevalent attacks in communication, sharing a secret between communicating parties is an ongoing challenge. Moreover, it is important to integrate quantum solutions with classical secret sharing schemes with low computational cost for the real world use. This paper proposes a novel hybrid threshold adaptable quantum secret sharing scheme, using an m-bonacci orbital angular momentum (OAM) pump, Lagrange interpolation polynomials, and reverse Huffman-Fibonacci-tree coding. To be exact, we employ entangled states prepared by m-bonacci sequences to detect eavesdropping. Meanwhile, we encode m-bonacci sequences in Lagrange interpolation polynomials to generate the shares of a secret with reverse Huffman-Fibonacci-tree coding. The advantages of the proposed scheme is that it can detect eavesdropping without joint quantum operations, and permits secret sharing for an arbitrary but no less than threshold-value number of classical participants with much lower bandwidth. Also, in comparison with existing quantum secret sharing schemes, it still works when there are dynamic changes, such as the unavailability of some quantum channel, the arrival of new participants and the departure of participants. Finally, we provide security analysis of the new hybrid quantum secret sharing scheme and discuss its useful features for modern applications.

  6. A Classification Scheme for Analyzing Mobile Apps Used to Prevent and Manage Disease in Late Life

    Science.gov (United States)

    Wang, Aiguo; Lu, Xin; Chen, Hongtu; Li, Changqun; Levkoff, Sue

    2014-01-01

    Background There are several mobile apps that offer tools for disease prevention and management among older adults, and promote health behaviors that could potentially reduce or delay the onset of disease. A classification scheme that categorizes apps could be useful to both older adult app users and app developers. Objective The objective of our study was to build and evaluate the effectiveness of a classification scheme that classifies mobile apps available for older adults in the “Health & Fitness” category of the iTunes App Store. Methods We constructed a classification scheme for mobile apps according to three dimensions: (1) the Precede-Proceed Model (PPM), which classifies mobile apps in terms of predisposing, enabling, and reinforcing factors for behavior change; (2) health care process, specifically prevention versus management of disease; and (3) health conditions, including physical health and mental health. Content analysis was conducted by the research team on health and fitness apps designed specifically for older adults, as well as those applicable to older adults, released during the months of June and August 2011 and August 2012. Face validity was assessed by a different group of individuals, who were not related to the study. A reliability analysis was conducted to confirm the accuracy of the coding scheme of the sample apps in this study. Results After applying sample inclusion and exclusion criteria, a total of 119 apps were included in the study sample, of which 26/119 (21.8%) were released in June 2011, 45/119 (37.8%) in August 2011, and 48/119 (40.3%) in August 2012. Face validity was determined by interviewing 11 people, who agreed that this scheme accurately reflected the nature of this application. The entire study sample was successfully coded, demonstrating satisfactory inter-rater reliability by two independent coders (95.8% initial concordance and 100% concordance after consensus was reached). The apps included in the study sample

  7. Optimal design of a hybridization scheme with a fuel cell using genetic optimization

    Science.gov (United States)

    Rodriguez, Marco A.

    Fuel cell is one of the most dependable "green power" technologies, readily available for immediate application. It enables direct conversion of hydrogen and other gases into electric energy without any pollution of the environment. However, the efficient power generation is strictly stationary process that cannot operate under dynamic environment. Consequently, fuel cell becomes practical only within a specially designed hybridization scheme, capable of power storage and power management functions. The resultant technology could be utilized to its full potential only when both the fuel cell element and the entire hybridization scheme are optimally designed. The design optimization in engineering is among the most complex computational tasks due to its multidimensionality, nonlinearity, discontinuity and presence of constraints in the underlying optimization problem. this research aims at the optimal utilization of the fuel cell technology through the use of genetic optimization, and advance computing. This study implements genetic optimization in the definition of optimum hybridization rules for a PEM fuel cell/supercapacitor power system. PEM fuel cells exhibit high energy density but they are not intended for pulsating power draw applications. They work better in steady state operation and thus, are often hybridized. In a hybrid system, the fuel cell provides power during steady state operation while capacitors or batteries augment the power of the fuel cell during power surges. Capacitors and batteries can also be recharged when the motor is acting as a generator. Making analogies to driving cycles, three hybrid system operating modes are investigated: 'Flat' mode, 'Uphill' mode, and 'Downhill' mode. In the process of discovering the switching rules for these three modes, we also generate a model of a 30W PEM fuel cell. This study also proposes the optimum design of a 30W PEM fuel cell. The PEM fuel cell model and hybridization's switching rules are postulated

  8. A new hybrid numerical scheme for modelling elastodynamics in unbounded media with near-source heterogeneities

    Science.gov (United States)

    Hajarolasvadi, Setare; Elbanna, Ahmed E.

    2017-11-01

    The finite difference (FD) and the spectral boundary integral (SBI) methods have been used extensively to model spontaneously-propagating shear cracks in a variety of engineering and geophysical applications. In this paper, we propose a new modelling approach in which these two methods are combined through consistent exchange of boundary tractions and displacements. Benefiting from the flexibility of FD and the efficiency of SBI methods, the proposed hybrid scheme will solve a wide range of problems in a computationally efficient way. We demonstrate the validity of the approach using two examples for dynamic rupture propagation: one in the presence of a low-velocity layer and the other in which off-fault plasticity is permitted. We discuss possible potential uses of the hybrid scheme in earthquake cycle simulations as well as an exact absorbing boundary condition.

  9. Frequency response control of semiconductor laser by using hybrid modulation scheme.

    Science.gov (United States)

    Mieda, Shigeru; Yokota, Nobuhide; Isshiki, Ryuto; Kobayashi, Wataru; Yasaka, Hiroshi

    2016-10-31

    A hybrid modulation scheme that simultaneously applies the direct current modulation and intra-cavity loss modulation to a semiconductor laser is proposed. Both numerical calculations using rate equations and experiments using a fabricated laser show that the hybrid modulation scheme can control the frequency response of the laser by changing a modulation ratio and time delay between the two modulations. The modulation ratio and time delay provide the degree of signal mixing of the two modulations and an optimum condition is found when a non-flat frequency response for the intra-cavity loss modulation is compensated by that for the direct current modulation. We experimentally confirm a 8.64-dB improvement of the modulation sensitivity at 20 GHz compared with the pure direct current modulation with a 0.7-dB relaxation oscillation peak.

  10. Exponential Synchronization of Networked Chaotic Delayed Neural Network by a Hybrid Event Trigger Scheme.

    Science.gov (United States)

    Fei, Zhongyang; Guan, Chaoxu; Gao, Huijun; Zhongyang Fei; Chaoxu Guan; Huijun Gao; Fei, Zhongyang; Guan, Chaoxu; Gao, Huijun

    2018-06-01

    This paper is concerned with the exponential synchronization for master-slave chaotic delayed neural network with event trigger control scheme. The model is established on a network control framework, where both external disturbance and network-induced delay are taken into consideration. The desired aim is to synchronize the master and slave systems with limited communication capacity and network bandwidth. In order to save the network resource, we adopt a hybrid event trigger approach, which not only reduces the data package sending out, but also gets rid of the Zeno phenomenon. By using an appropriate Lyapunov functional, a sufficient criterion for the stability is proposed for the error system with extended ( , , )-dissipativity performance index. Moreover, hybrid event trigger scheme and controller are codesigned for network-based delayed neural network to guarantee the exponential synchronization between the master and slave systems. The effectiveness and potential of the proposed results are demonstrated through a numerical example.

  11. Hybrid Scheme for Modeling Local Field Potentials from Point-Neuron Networks.

    Science.gov (United States)

    Hagen, Espen; Dahmen, David; Stavrinou, Maria L; Lindén, Henrik; Tetzlaff, Tom; van Albada, Sacha J; Grün, Sonja; Diesmann, Markus; Einevoll, Gaute T

    2016-12-01

    With rapidly advancing multi-electrode recording technology, the local field potential (LFP) has again become a popular measure of neuronal activity in both research and clinical applications. Proper understanding of the LFP requires detailed mathematical modeling incorporating the anatomical and electrophysiological features of neurons near the recording electrode, as well as synaptic inputs from the entire network. Here we propose a hybrid modeling scheme combining efficient point-neuron network models with biophysical principles underlying LFP generation by real neurons. The LFP predictions rely on populations of network-equivalent multicompartment neuron models with layer-specific synaptic connectivity, can be used with an arbitrary number of point-neuron network populations, and allows for a full separation of simulated network dynamics and LFPs. We apply the scheme to a full-scale cortical network model for a ∼1 mm 2 patch of primary visual cortex, predict laminar LFPs for different network states, assess the relative LFP contribution from different laminar populations, and investigate effects of input correlations and neuron density on the LFP. The generic nature of the hybrid scheme and its public implementation in hybridLFPy form the basis for LFP predictions from other and larger point-neuron network models, as well as extensions of the current application with additional biological detail. © The Author 2016. Published by Oxford University Press.

  12. Fused man-machine classification schemes to enhance diagnosis of breast microcalcifications

    Science.gov (United States)

    Andreadis, Ioannis; Sevastianos, Chatzistergos; George, Spyrou; Konstantina, Nikita

    2017-11-01

    Computer aided diagnosis (CAD x ) approaches are developed towards the effective discrimination between benign and malignant clusters of microcalcifications. Different sources of information are exploited, such as features extracted from the image analysis of the region of interest, features related to the location of the cluster inside the breast, age of the patient and descriptors provided by the radiologists while performing their diagnostic task. A series of different CAD x schemes are implemented, each of which uses a different category of features and adopts a variety of machine learning algorithms and alternative image processing techniques. A novel framework is introduced where these independent diagnostic components are properly combined according to features critical to a radiologist in an attempt to identify the most appropriate CAD x schemes for the case under consideration. An open access database (Digital Database of Screening Mammography (DDSM)) has been elaborated to construct a large dataset with cases of varying subtlety, in order to ensure the development of schemes with high generalization ability, as well as extensive evaluation of their performance. The obtained results indicate that the proposed framework succeeds in improving the diagnostic procedure, as the achieved overall classification performance outperforms all the independent single diagnostic components, as well as the radiologists that assessed the same cases, in terms of accuracy, sensitivity, specificity and area under the curve following receiver operating characteristic analysis.

  13. A risk-based classification scheme for genetically modified foods. I: Conceptual development.

    Science.gov (United States)

    Chao, Eunice; Krewski, Daniel

    2008-12-01

    The predominant paradigm for the premarket assessment of genetically modified (GM) foods reflects heightened public concern by focusing on foods modified by recombinant deoxyribonucleic acid (rDNA) techniques, while foods modified by other methods of genetic modification are generally not assessed for safety. To determine whether a GM product requires less or more regulatory oversight and testing, we developed and evaluated a risk-based classification scheme (RBCS) for crop-derived GM foods. The results of this research are presented in three papers. This paper describes the conceptual development of the proposed RBCS that focuses on two categories of adverse health effects: (1) toxic and antinutritional effects, and (2) allergenic effects. The factors that may affect the level of potential health risks of GM foods are identified. For each factor identified, criteria for differentiating health risk potential are developed. The extent to which a GM food satisfies applicable criteria for each factor is rated separately. A concern level for each category of health effects is then determined by aggregating the ratings for the factors using predetermined aggregation rules. An overview of the proposed scheme is presented, as well as the application of the scheme to a hypothetical GM food.

  14. A novel fractal image compression scheme with block classification and sorting based on Pearson's correlation coefficient.

    Science.gov (United States)

    Wang, Jianji; Zheng, Nanning

    2013-09-01

    Fractal image compression (FIC) is an image coding technology based on the local similarity of image structure. It is widely used in many fields such as image retrieval, image denoising, image authentication, and encryption. FIC, however, suffers from the high computational complexity in encoding. Although many schemes are published to speed up encoding, they do not easily satisfy the encoding time or the reconstructed image quality requirements. In this paper, a new FIC scheme is proposed based on the fact that the affine similarity between two blocks in FIC is equivalent to the absolute value of Pearson's correlation coefficient (APCC) between them. First, all blocks in the range and domain pools are chosen and classified using an APCC-based block classification method to increase the matching probability. Second, by sorting the domain blocks with respect to APCCs between these domain blocks and a preset block in each class, the matching domain block for a range block can be searched in the selected domain set in which these APCCs are closer to APCC between the range block and the preset block. Experimental results show that the proposed scheme can significantly speed up the encoding process in FIC while preserving the reconstructed image quality well.

  15. Fused man-machine classification schemes to enhance diagnosis of breast microcalcifications

    International Nuclear Information System (INIS)

    Andreadis, Ioannis; Sevastianos, Chatzistergos; Konstantina, Nikita; George, Spyrou

    2017-01-01

    Computer aided diagnosis (CAD x ) approaches are developed towards the effective discrimination between benign and malignant clusters of microcalcifications. Different sources of information are exploited, such as features extracted from the image analysis of the region of interest, features related to the location of the cluster inside the breast, age of the patient and descriptors provided by the radiologists while performing their diagnostic task. A series of different CAD x schemes are implemented, each of which uses a different category of features and adopts a variety of machine learning algorithms and alternative image processing techniques. A novel framework is introduced where these independent diagnostic components are properly combined according to features critical to a radiologist in an attempt to identify the most appropriate CAD x schemes for the case under consideration. An open access database (Digital Database of Screening Mammography (DDSM)) has been elaborated to construct a large dataset with cases of varying subtlety, in order to ensure the development of schemes with high generalization ability, as well as extensive evaluation of their performance. The obtained results indicate that the proposed framework succeeds in improving the diagnostic procedure, as the achieved overall classification performance outperforms all the independent single diagnostic components, as well as the radiologists that assessed the same cases, in terms of accuracy, sensitivity, specificity and area under the curve following receiver operating characteristic analysis. (paper)

  16. Numerical study of a hybrid jet impingement/micro-channel cooling scheme

    International Nuclear Information System (INIS)

    Barrau, Jérôme; Omri, Mohammed; Chemisana, Daniel; Rosell, Joan; Ibañez, Manel; Tadrist, Lounes

    2012-01-01

    A new hybrid jet impingement/micro-channel cooling scheme is studied numerically for use in high-heat-flux thermal management of electronic and power devices. The device is developed with the objective of improving the temperature uniformity of the cooled object. A numerical model based on the k–ω SST turbulent model is developed and validated experimentally. This model is used to carry out a parametrical characterization of the heat sink. The study shows that variations in key parameters of jet impingement and micro-channel technologies allow for the cooling scheme to obtain a wide range of temperature profiles for the cooled object. - Highlights: ► A new hybrid cooling scheme is numerically studied. ► The cooling scheme combines the benefits of jet impingement and micro-channel flows. ► The numerical model is validated by comparison with experimental results. ► The temperature distribution can be adapted to the needs of the cooled system.

  17. A Hybrid DGTD-MNA Scheme for Analyzing Complex Electromagnetic Systems

    KAUST Repository

    Li, Peng

    2015-01-07

    A hybrid electromagnetics (EM)-circuit simulator for analyzing complex systems consisting of EM devices loaded with nonlinear multi-port lumped circuits is described. The proposed scheme splits the computational domain into two subsystems: EM and circuit subsystems, where field interactions are modeled using Maxwell and Kirchhoff equations, respectively. Maxwell equations are discretized using a discontinuous Galerkin time domain (DGTD) scheme while Kirchhoff equations are discretized using a modified nodal analysis (MNA)-based scheme. The coupling between the EM and circuit subsystems is realized at the lumped ports, where related EM fields and circuit voltages and currents are allowed to “interact’’ via numerical flux. To account for nonlinear lumped circuit elements, the standard Newton-Raphson method is applied at every time step. Additionally, a local time-stepping scheme is developed to improve the efficiency of the hybrid solver. Numerical examples consisting of EM systems loaded with single and multiport linear/nonlinear circuit networks are presented to demonstrate the accuracy, efficiency, and applicability of the proposed solver.

  18. Digital-Analog Hybrid Scheme and Its Application to Chaotic Random Number Generators

    Science.gov (United States)

    Yuan, Zeshi; Li, Hongtao; Miao, Yunchi; Hu, Wen; Zhu, Xiaohua

    2017-12-01

    Practical random number generation (RNG) circuits are typically achieved with analog devices or digital approaches. Digital-based techniques, which use field programmable gate array (FPGA) and graphics processing units (GPU) etc. usually have better performances than analog methods as they are programmable, efficient and robust. However, digital realizations suffer from the effect of finite precision. Accordingly, the generated random numbers (RNs) are actually periodic instead of being real random. To tackle this limitation, in this paper we propose a novel digital-analog hybrid scheme that employs the digital unit as the main body, and minimum analog devices to generate physical RNs. Moreover, the possibility of realizing the proposed scheme with only one memory element is discussed. Without loss of generality, we use the capacitor and the memristor along with FPGA to construct the proposed hybrid system, and a chaotic true random number generator (TRNG) circuit is realized, producing physical RNs at a throughput of Gbit/s scale. These RNs successfully pass all the tests in the NIST SP800-22 package, confirming the significance of the scheme in practical applications. In addition, the use of this new scheme is not restricted to RNGs, and it also provides a strategy to solve the effect of finite precision in other digital systems.

  19. A new classification scheme of plastic wastes based upon recycling labels.

    Science.gov (United States)

    Özkan, Kemal; Ergin, Semih; Işık, Şahin; Işıklı, Idil

    2015-01-01

    results agree on. The proposed classification scheme provides high accuracy rate, and also it is able to run in real-time applications. It can automatically classify the plastic bottle types with approximately 90% recognition accuracy. Besides this, the proposed methodology yields approximately 96% classification rate for the separation of PET or non-PET plastic types. It also gives 92% accuracy for the categorization of non-PET plastic types into HPDE or PP. Copyright © 2014 Elsevier Ltd. All rights reserved.

  20. Proposing a Hybrid Model Based on Robson's Classification for Better Impact on Trends of Cesarean Deliveries.

    Science.gov (United States)

    Hans, Punit; Rohatgi, Renu

    2017-06-01

    To construct a hybrid model classification for cesarean section (CS) deliveries based on the woman-characteristics (Robson's classification with additional layers of indications for CS, keeping in view low-resource settings available in India). This is a cross-sectional study conducted at Nalanda Medical College, Patna. All the women delivered from January 2016 to May 2016 in the labor ward were included. Results obtained were compared with the values obtained for India, from secondary analysis of WHO multi-country survey (2010-2011) by Joshua Vogel and colleagues' study published in "The Lancet Global Health." The three classifications (indication-based, Robson's and hybrid model) applied for categorization of the cesarean deliveries from the same sample of data and a semiqualitative evaluations done, considering the main characteristics, strengths and weaknesses of each classification system. The total number of women delivered during study period was 1462, out of which CS deliveries were 471. Overall, CS rate calculated for NMCH, hospital in this specified period, was 32.21% ( p  = 0.001). Hybrid model scored 23/23, and scores of Robson classification and indication-based classification were 21/23 and 10/23, respectively. Single-study centre and referral bias are the limitations of the study. Given the flexibility of the classifications, we constructed a hybrid model based on the woman-characteristics system with additional layers of other classification. Indication-based classification answers why, Robson classification answers on whom, while through our hybrid model we get to know why and on whom cesarean deliveries are being performed.

  1. A gas kinetic scheme for hybrid simulation of partially rarefied flows

    Science.gov (United States)

    Colonia, S.; Steijl, R.; Barakos, G.

    2017-06-01

    Approaches to predict flow fields that display rarefaction effects incur a cost in computational time and memory considerably higher than methods commonly employed for continuum flows. For this reason, to simulate flow fields where continuum and rarefied regimes coexist, hybrid techniques have been introduced. In the present work, analytically defined gas-kinetic schemes based on the Shakhov and Rykov models for monoatomic and diatomic gas flows, respectively, are proposed and evaluated with the aim to be used in the context of hybrid simulations. This should reduce the region where more expensive methods are needed by extending the validity of the continuum formulation. Moreover, since for high-speed rare¦ed gas flows it is necessary to take into account the nonequilibrium among the internal degrees of freedom, the extension of the approach to employ diatomic gas models including rotational relaxation process is a mandatory first step towards realistic simulations. Compared to previous works of Xu and coworkers, the presented scheme is de¦ned directly on the basis of kinetic models which involve a Prandtl number correction. Moreover, the methods are defined fully analytically instead of making use of Taylor expansion for the evaluation of the required derivatives. The scheme has been tested for various test cases and Mach numbers proving to produce reliable predictions in agreement with other approaches for near-continuum flows. Finally, the performance of the scheme, in terms of memory and computational time, compared to discrete velocity methods makes it a compelling alternative in place of more complex methods for hybrid simulations of weakly rarefied flows.

  2. A Hybrid Scheme for Fine-Grained Search and Access Authorization in Fog Computing Environment

    Science.gov (United States)

    Xiao, Min; Zhou, Jing; Liu, Xuejiao; Jiang, Mingda

    2017-01-01

    In the fog computing environment, the encrypted sensitive data may be transferred to multiple fog nodes on the edge of a network for low latency; thus, fog nodes need to implement a search over encrypted data as a cloud server. Since the fog nodes tend to provide service for IoT applications often running on resource-constrained end devices, it is necessary to design lightweight solutions. At present, there is little research on this issue. In this paper, we propose a fine-grained owner-forced data search and access authorization scheme spanning user-fog-cloud for resource constrained end users. Compared to existing schemes only supporting either index encryption with search ability or data encryption with fine-grained access control ability, the proposed hybrid scheme supports both abilities simultaneously, and index ciphertext and data ciphertext are constructed based on a single ciphertext-policy attribute based encryption (CP-ABE) primitive and share the same key pair, thus the data access efficiency is significantly improved and the cost of key management is greatly reduced. Moreover, in the proposed scheme, the resource constrained end devices are allowed to rapidly assemble ciphertexts online and securely outsource most of decryption task to fog nodes, and mediated encryption mechanism is also adopted to achieve instantaneous user revocation instead of re-encrypting ciphertexts with many copies in many fog nodes. The security and the performance analysis show that our scheme is suitable for a fog computing environment. PMID:28629131

  3. A Hybrid Scheme for Fine-Grained Search and Access Authorization in Fog Computing Environment.

    Science.gov (United States)

    Xiao, Min; Zhou, Jing; Liu, Xuejiao; Jiang, Mingda

    2017-06-17

    In the fog computing environment, the encrypted sensitive data may be transferred to multiple fog nodes on the edge of a network for low latency; thus, fog nodes need to implement a search over encrypted data as a cloud server. Since the fog nodes tend to provide service for IoT applications often running on resource-constrained end devices, it is necessary to design lightweight solutions. At present, there is little research on this issue. In this paper, we propose a fine-grained owner-forced data search and access authorization scheme spanning user-fog-cloud for resource constrained end users. Compared to existing schemes only supporting either index encryption with search ability or data encryption with fine-grained access control ability, the proposed hybrid scheme supports both abilities simultaneously, and index ciphertext and data ciphertext are constructed based on a single ciphertext-policy attribute based encryption (CP-ABE) primitive and share the same key pair, thus the data access efficiency is significantly improved and the cost of key management is greatly reduced. Moreover, in the proposed scheme, the resource constrained end devices are allowed to rapidly assemble ciphertexts online and securely outsource most of decryption task to fog nodes, and mediated encryption mechanism is also adopted to achieve instantaneous user revocation instead of re-encrypting ciphertexts with many copies in many fog nodes. The security and the performance analysis show that our scheme is suitable for a fog computing environment.

  4. A hierarchical approach of hybrid image classification for land use and land cover mapping

    Directory of Open Access Journals (Sweden)

    Rahdari Vahid

    2018-01-01

    Full Text Available Remote sensing data analysis can provide thematic maps describing land-use and land-cover (LULC in a short period. Using proper image classification method in an area, is important to overcome the possible limitations of satellite imageries for producing land-use and land-cover maps. In the present study, a hierarchical hybrid image classification method was used to produce LULC maps using Landsat Thematic mapper TM for the year of 1998 and operational land imager OLI for the year of 2016. Images were classified using the proposed hybrid image classification method, vegetation cover crown percentage map from normalized difference vegetation index, Fisher supervised classification and object-based image classification methods. Accuracy assessment results showed that the hybrid classification method produced maps with total accuracy up to 84 percent with kappa statistic value 0.81. Results of this study showed that the proposed classification method worked better with OLI sensor than with TM. Although OLI has a higher radiometric resolution than TM, the produced LULC map using TM is almost accurate like OLI, which is because of LULC definitions and image classification methods used.

  5. Proposed classification scheme for high-level and other radioactive wastes

    International Nuclear Information System (INIS)

    Kocher, D.C.; Croff, A.G.

    1986-01-01

    The Nuclear Waste Policy Act (NWPA) of 1982 defines high-level (radioactive) waste (HLW) as (A) the highly radioactive material resulting from the reprocessing of spent nuclear fuel...that contains fission products in sufficient concentrations; and (B) other highly radioactive material that the Commission...determines...requires permanent isolation. This paper presents a generally applicable quantitative definition of HLW that addresses the description in paragraph B. The approach also results in definitions of other wastes classes, i.e., transuranic (TRU) and low-level waste (LLW). The basic waste classification scheme that results from the quantitative definitions of highly radioactive and requires permanent isolation is depicted. The concentrations of radionuclides that correspond to these two boundaries, and that may be used to classify radioactive wastes, are given

  6. Harmonization of sound insulation descriptors and classification schemes in Europe: COST Action TU0901

    DEFF Research Database (Denmark)

    Rasmussen, Birgit

    -in-Chief. Handbook of noise and vibration control, USA: Wiley and Son; 2007 [Ch. 114]. [4] COST Action TU0901 “Integrating and Harmonizing Sound Insulation Aspects in Sustainable Urban Housing Constructions”, 2009-2013, www.cost.eu/index.php?id=240&action_number=tu0901 (public information at COST website) or http...... insulation requirements seems unrealistic. However, by preparing a harmonized European classification scheme with a number of quality classes, member states could select a "harmonized" class fitting the national needs and conditions. A joint European Action, COST Action TU0901 "Integrating and Harmonizing...... on good workmanship. The paper will summarize the background, discuss the present situation in Europe and describe the joint efforts to reduce the diversity in Europe, thus supporting and initiating – where needed – improvement of sound insulation of new and existing dwellings in Europe to the benefit...

  7. Kernel Clustering with a Differential Harmony Search Algorithm for Scheme Classification

    Directory of Open Access Journals (Sweden)

    Yu Feng

    2017-01-01

    Full Text Available This paper presents a kernel fuzzy clustering with a novel differential harmony search algorithm to coordinate with the diversion scheduling scheme classification. First, we employed a self-adaptive solution generation strategy and differential evolution-based population update strategy to improve the classical harmony search. Second, we applied the differential harmony search algorithm to the kernel fuzzy clustering to help the clustering method obtain better solutions. Finally, the combination of the kernel fuzzy clustering and the differential harmony search is applied for water diversion scheduling in East Lake. A comparison of the proposed method with other methods has been carried out. The results show that the kernel clustering with the differential harmony search algorithm has good performance to cooperate with the water diversion scheduling problems.

  8. Sound classification of dwellings in the Nordic countries – Differences and similarities between the five national schemes

    DEFF Research Database (Denmark)

    Rasmussen, Birgit

    2012-01-01

    having several similarities. In 2012, status is that number and denotations of classes for dwellings are identical in the Nordic countries, but the structures of the standards and several details are quite different. Also the issues dealt with are different. Examples of differences are sound insulation...... for classification of such buildings. This paper presents and compares the main class criteria for sound insulation of dwellings and summarizes differences and similarities in criteria and in structures of standards. Classification schemes for dwellings also exist in several other countries in Europe......In all five Nordic countries, sound classification schemes for dwellings have been published in national standards being implemented and revised gradually since the late 1990s. The national classification criteria for dwellings originate from a common Nordic INSTA-B proposal from the 1990s, thus...

  9. A Novel Loss Recovery and Tracking Scheme for Maneuvering Target in Hybrid WSNs.

    Science.gov (United States)

    Qian, Hanwang; Fu, Pengcheng; Li, Baoqing; Liu, Jianpo; Yuan, Xiaobing

    2018-01-25

    Tracking a mobile target, which aims to timely monitor the invasion of specific target, is one of the most prominent applications in wireless sensor networks (WSNs). Traditional tracking methods in WSNs only based on static sensor nodes (SNs) have several critical problems. For example, to void the loss of mobile target, many SNs must be active to track the target in all possible directions, resulting in excessive energy consumption. Additionally, when entering coverage holes in the monitoring area, the mobile target may be missing and then its state is unknown during this period. To tackle these problems, in this paper, a few mobile sensor nodes (MNs) are introduced to cooperate with SNs to form a hybrid WSN due to their stronger abilities and less constrained energy. Then, we propose a valid target tracking scheme for hybrid WSNs to dynamically schedule the MNs and SNs. Moreover, a novel loss recovery mechanism is proposed to find the lost target and recover the tracking with fewer SNs awakened. Furthermore, to improve the robustness and accuracy of the recovery mechanism, an adaptive unscented Kalman filter (AUKF) algorithm is raised to dynamically adjust the process noise covariance. Simulation results demonstrate that our tracking scheme for maneuvering target in hybrid WSNs can not only track the target effectively even if the target is lost but also maintain an excellent accuracy and robustness with fewer activated nodes.

  10. A new hybrid scheme for simulations of highly collisional RF-driven plasmas

    International Nuclear Information System (INIS)

    Eremin, Denis; Hemke, Torben; Mussenbrock, Thomas

    2016-01-01

    This work describes a new 1D hybrid approach for modeling atmospheric pressure discharges featuring complex chemistry. In this approach electrons are described fully kinetically using particle-in-cell/Monte-Carlo (PIC/MCC) scheme, whereas the heavy species are modeled within a fluid description. Validity of the popular drift-diffusion approximation is verified against a ‘full’ fluid model accounting for the ion inertia and a fully kinetic PIC/MCC code for ions as well as electrons. The fluid models require knowledge of the momentum exchange frequency and dependence of the ion mobilities on the electric field when the ions are in equilibrium with the latter. To this end an auxiliary Monte-Carlo scheme is constructed. It is demonstrated that the drift-diffusion approximation can overestimate ion transport in simulations of RF-driven discharges with heavy ion species operated in the γ mode at the atmospheric pressure or in all discharge simulations for lower pressures. This can lead to exaggerated plasma densities and incorrect profiles provided by the drift-diffusion models. Therefore, the hybrid code version featuring the full ion fluid model should be favored against the more popular drift-diffusion model, noting that the suggested numerical scheme for the former model implies only a small additional computational cost. (paper)

  11. A Hybrid Data Compression Scheme for Power Reduction in Wireless Sensors for IoT.

    Science.gov (United States)

    Deepu, Chacko John; Heng, Chun-Huat; Lian, Yong

    2017-04-01

    This paper presents a novel data compression and transmission scheme for power reduction in Internet-of-Things (IoT) enabled wireless sensors. In the proposed scheme, data is compressed with both lossy and lossless techniques, so as to enable hybrid transmission mode, support adaptive data rate selection and save power in wireless transmission. Applying the method to electrocardiogram (ECG), the data is first compressed using a lossy compression technique with a high compression ratio (CR). The residual error between the original data and the decompressed lossy data is preserved using entropy coding, enabling a lossless restoration of the original data when required. Average CR of 2.1 × and 7.8 × were achieved for lossless and lossy compression respectively with MIT/BIH database. The power reduction is demonstrated using a Bluetooth transceiver and is found to be reduced to 18% for lossy and 53% for lossless transmission respectively. Options for hybrid transmission mode, adaptive rate selection and system level power reduction make the proposed scheme attractive for IoT wireless sensors in healthcare applications.

  12. A conservative and a hybrid early rejection schemes for accelerating Monte Carlo molecular simulation

    KAUST Repository

    Kadoura, Ahmad Salim

    2014-03-17

    Molecular simulation could provide detailed description of fluid systems when compared to experimental techniques. They can also replace equations of state; however, molecular simulation usually costs considerable computational efforts. Several techniques have been developed to overcome such high computational costs. In this paper, two early rejection schemes, a conservative and a hybrid one, are introduced. In these two methods, undesired configurations generated by the Monte Carlo trials are rejected earlier than it would when using conventional algorithms. The methods are tested for structureless single-component Lennard-Jones particles in both canonical and NVT-Gibbs ensembles. The computational time reduction for both ensembles is observed at a wide range of thermodynamic conditions. Results show that computational time savings are directly proportional to the rejection rate of Monte Carlo trials. The proposed conservative scheme has shown to be successful in saving up to 40% of the computational time in the canonical ensemble and up to 30% in the NVT-Gibbs ensemble when compared to standard algorithms. In addition, it preserves the exact Markov chains produced by the Metropolis scheme. Further enhancement for NVT-Gibbs ensemble is achieved by combining this technique with the bond formation early rejection one. The hybrid method achieves more than 50% saving of the central processing unit (CPU) time.

  13. Classification Scheme for Diverse Sedimentary and Igneous Rocks Encountered by MSL in Gale Crater

    Science.gov (United States)

    Schmidt, M. E.; Mangold, N.; Fisk, M.; Forni, O.; McLennan, S.; Ming, D. W.; Sumner, D.; Sautter, V.; Williams, A. J.; Gellert, R.

    2015-01-01

    The Curiosity Rover landed in a lithologically and geochemically diverse region of Mars. We present a recommended rock classification framework based on terrestrial schemes, and adapted for the imaging and analytical capabilities of MSL as well as for rock types distinctive to Mars (e.g., high Fe sediments). After interpreting rock origin from textures, i.e., sedimentary (clastic, bedded), igneous (porphyritic, glassy), or unknown, the overall classification procedure (Fig 1) involves: (1) the characterization of rock type according to grain size and texture; (2) the assignment of geochemical modifiers according to Figs 3 and 4; and if applicable, in depth study of (3) mineralogy and (4) geologic/stratigraphic context. Sedimentary rock types are assigned by measuring grains in the best available resolution image (Table 1) and classifying according to the coarsest resolvable grains as conglomerate/breccia, (coarse, medium, or fine) sandstone, silt-stone, or mudstone. If grains are not resolvable in MAHLI images, grains in the rock are assumed to be silt sized or smaller than surface dust particles. Rocks with low color contrast contrast between grains (e.g., Dismal Lakes, sol 304) are classified according to minimum size of apparent grains from surface roughness or shadows outlining apparent grains. Igneous rocks are described as intrusive or extrusive depending on crystal size and fabric. Igneous textures may be described as granular, porphyritic, phaneritic, aphyric, or glassy depending on crystal size. Further descriptors may include terms such as vesicular or cumulate textures.

  14. PET/CT detectability and classification of simulated pulmonary lesions using an SUV correction scheme

    Science.gov (United States)

    Morrow, Andrew N.; Matthews, Kenneth L., II; Bujenovic, Steven

    2008-03-01

    Positron emission tomography (PET) and computed tomography (CT) together are a powerful diagnostic tool, but imperfect image quality allows false positive and false negative diagnoses to be made by any observer despite experience and training. This work investigates PET acquisition mode, reconstruction method and a standard uptake value (SUV) correction scheme on the classification of lesions as benign or malignant in PET/CT images, in an anthropomorphic phantom. The scheme accounts for partial volume effect (PVE) and PET resolution. The observer draws a region of interest (ROI) around the lesion using the CT dataset. A simulated homogenous PET lesion of the same shape as the drawn ROI is blurred with the point spread function (PSF) of the PET scanner to estimate the PVE, providing a scaling factor to produce a corrected SUV. Computer simulations showed that the accuracy of the corrected PET values depends on variations in the CT-drawn boundary and the position of the lesion with respect to the PET image matrix, especially for smaller lesions. Correction accuracy was affected slightly by mismatch of the simulation PSF and the actual scanner PSF. The receiver operating characteristic (ROC) study resulted in several observations. Using observer drawn ROIs, scaled tumor-background ratios (TBRs) more accurately represented actual TBRs than unscaled TBRs. For the PET images, 3D OSEM outperformed 2D OSEM, 3D OSEM outperformed 3D FBP, and 2D OSEM outperformed 2D FBP. The correction scheme significantly increased sensitivity and slightly increased accuracy for all acquisition and reconstruction modes at the cost of a small decrease in specificity.

  15. Design of a hybrid model for cardiac arrhythmia classification based on Daubechies wavelet transform.

    Science.gov (United States)

    Rajagopal, Rekha; Ranganathan, Vidhyapriya

    2018-06-05

    Automation in cardiac arrhythmia classification helps medical professionals make accurate decisions about the patient's health. The aim of this work was to design a hybrid classification model to classify cardiac arrhythmias. The design phase of the classification model comprises the following stages: preprocessing of the cardiac signal by eliminating detail coefficients that contain noise, feature extraction through Daubechies wavelet transform, and arrhythmia classification using a collaborative decision from the K nearest neighbor classifier (KNN) and a support vector machine (SVM). The proposed model is able to classify 5 arrhythmia classes as per the ANSI/AAMI EC57: 1998 classification standard. Level 1 of the proposed model involves classification using the KNN and the classifier is trained with examples from all classes. Level 2 involves classification using an SVM and is trained specifically to classify overlapped classes. The final classification of a test heartbeat pertaining to a particular class is done using the proposed KNN/SVM hybrid model. The experimental results demonstrated that the average sensitivity of the proposed model was 92.56%, the average specificity 99.35%, the average positive predictive value 98.13%, the average F-score 94.5%, and the average accuracy 99.78%. The results obtained using the proposed model were compared with the results of discriminant, tree, and KNN classifiers. The proposed model is able to achieve a high classification accuracy.

  16. Hybrid Scheme for Modeling Local Field Potentials from Point-Neuron Networks

    DEFF Research Database (Denmark)

    Hagen, Espen; Dahmen, David; Stavrinou, Maria L

    2016-01-01

    on populations of network-equivalent multicompartment neuron models with layer-specific synaptic connectivity, can be used with an arbitrary number of point-neuron network populations, and allows for a full separation of simulated network dynamics and LFPs. We apply the scheme to a full-scale cortical network......With rapidly advancing multi-electrode recording technology, the local field potential (LFP) has again become a popular measure of neuronal activity in both research and clinical applications. Proper understanding of the LFP requires detailed mathematical modeling incorporating the anatomical...... and electrophysiological features of neurons near the recording electrode, as well as synaptic inputs from the entire network. Here we propose a hybrid modeling scheme combining efficient point-neuron network models with biophysical principles underlying LFP generation by real neurons. The LFP predictions rely...

  17. Numerical schemes for the hybrid modeling approach of gas-particle turbulent flows

    International Nuclear Information System (INIS)

    Dorogan, K.

    2012-01-01

    Hybrid Moments/PDF methods have shown to be well suitable for the description of poly-dispersed turbulent two-phase flows in non-equilibrium which are encountered in some industrial situations involving chemical reactions, combustion or sprays. They allow to obtain a fine enough physical description of the poly-dispersity, non-linear source terms and convection phenomena. However, their approximations are noised with the statistical error, which in several situations may be a source of a bias. An alternative hybrid Moments-Moments/PDF approach examined in this work consists in coupling the Moments and the PDF descriptions, within the description of the dispersed phase itself. This hybrid method could reduce the statistical error and remove the bias. However, such a coupling is not straightforward in practice and requires the development of accurate and stable numerical schemes. The approaches introduced in this work rely on the combined use of the up-winding and relaxation-type techniques. They allow to obtain stable unsteady approximations for a system of partial differential equations containing non-smooth external data which are provided by the PDF part of the model. A comparison of the results obtained using the present method with those of the 'classical' hybrid approach is presented in terms of the numerical errors for a case of a co-current gas-particle wall jet. (author)

  18. Hybrid ARQ Scheme with Autonomous Retransmission for Multicasting in Wireless Sensor Networks.

    Science.gov (United States)

    Jung, Young-Ho; Choi, Jihoon

    2017-02-25

    A new hybrid automatic repeat request (HARQ) scheme for multicast service for wireless sensor networks is proposed in this study. In the proposed algorithm, the HARQ operation is combined with an autonomous retransmission method that ensure a data packet is transmitted irrespective of whether or not the packet is successfully decoded at the receivers. The optimal number of autonomous retransmissions is determined to ensure maximum spectral efficiency, and a practical method that adjusts the number of autonomous retransmissions for realistic conditions is developed. Simulation results show that the proposed method achieves higher spectral efficiency than existing HARQ techniques.

  19. Hybrid ARQ Scheme with Autonomous Retransmission for Multicasting in Wireless Sensor Networks

    Directory of Open Access Journals (Sweden)

    Young-Ho Jung

    2017-02-01

    Full Text Available A new hybrid automatic repeat request (HARQ scheme for multicast service for wireless sensor networks is proposed in this study. In the proposed algorithm, the HARQ operation is combined with an autonomous retransmission method that ensure a data packet is transmitted irrespective of whether or not the packet is successfully decoded at the receivers. The optimal number of autonomous retransmissions is determined to ensure maximum spectral efficiency, and a practical method that adjusts the number of autonomous retransmissions for realistic conditions is developed. Simulation results show that the proposed method achieves higher spectral efficiency than existing HARQ techniques.

  20. New hybrid reverse differential pulse position width modulation scheme for wireless optical communication

    Science.gov (United States)

    Liao, Renbo; Liu, Hongzhan; Qiao, Yaojun

    2014-05-01

    In order to improve the power efficiency and reduce the packet error rate of reverse differential pulse position modulation (RDPPM) for wireless optical communication (WOC), a hybrid reverse differential pulse position width modulation (RDPPWM) scheme is proposed, based on RDPPM and reverse pulse width modulation. Subsequently, the symbol structure of RDPPWM is briefly analyzed, and its performance is compared with that of other modulation schemes in terms of average transmitted power, bandwidth requirement, and packet error rate over ideal additive white Gaussian noise (AWGN) channels. Based on the given model, the simulation results show that the proposed modulation scheme has the advantages of improving the power efficiency and reducing the bandwidth requirement. Moreover, in terms of error probability performance, RDPPWM can achieve a much lower packet error rate than that of RDPPM. For example, at the same received signal power of -28 dBm, the packet error rate of RDPPWM can decrease to 2.6×10-12, while that of RDPPM is 2.2×10. Furthermore, RDPPWM does not need symbol synchronization at the receiving end. These considerations make RDPPWM a favorable candidate to select as the modulation scheme in the WOC systems.

  1. HYBRID SYSTEM BASED FUZZY-PID CONTROL SCHEMES FOR UNPREDICTABLE PROCESS

    Directory of Open Access Journals (Sweden)

    M.K. Tan

    2011-07-01

    Full Text Available In general, the primary aim of polymerization industry is to enhance the process operation in order to obtain high quality and purity product. However, a sudden and large amount of heat will be released rapidly during the mixing process of two reactants, i.e. phenol and formalin due to its exothermic behavior. The unpredictable heat will cause deviation of process temperature and hence affect the quality of the product. Therefore, it is vital to control the process temperature during the polymerization. In the modern industry, fuzzy logic is commonly used to auto-tune PID controller to control the process temperature. However, this method needs an experienced operator to fine tune the fuzzy membership function and universe of discourse via trial and error approach. Hence, the setting of fuzzy inference system might not be accurate due to the human errors. Besides that, control of the process can be challenging due to the rapid changes in the plant parameters which will increase the process complexity. This paper proposes an optimization scheme using hybrid of Q-learning (QL and genetic algorithm (GA to optimize the fuzzy membership function in order to allow the conventional fuzzy-PID controller to control the process temperature more effectively. The performances of the proposed optimization scheme are compared with the existing fuzzy-PID scheme. The results show that the proposed optimization scheme is able to control the process temperature more effectively even if disturbance is introduced.

  2. Hybrid model based unified scheme for endoscopic Cerenkov and radio-luminescence tomography: Simulation demonstration

    Science.gov (United States)

    Wang, Lin; Cao, Xin; Ren, Qingyun; Chen, Xueli; He, Xiaowei

    2018-05-01

    Cerenkov luminescence imaging (CLI) is an imaging method that uses an optical imaging scheme to probe a radioactive tracer. Application of CLI with clinically approved radioactive tracers has opened an opportunity for translating optical imaging from preclinical to clinical applications. Such translation was further improved by developing an endoscopic CLI system. However, two-dimensional endoscopic imaging cannot identify accurate depth and obtain quantitative information. Here, we present an imaging scheme to retrieve the depth and quantitative information from endoscopic Cerenkov luminescence tomography, which can also be applied for endoscopic radio-luminescence tomography. In the scheme, we first constructed a physical model for image collection, and then a mathematical model for characterizing the luminescent light propagation from tracer to the endoscopic detector. The mathematical model is a hybrid light transport model combined with the 3rd order simplified spherical harmonics approximation, diffusion, and radiosity equations to warrant accuracy and speed. The mathematical model integrates finite element discretization, regularization, and primal-dual interior-point optimization to retrieve the depth and the quantitative information of the tracer. A heterogeneous-geometry-based numerical simulation was used to explore the feasibility of the unified scheme, which demonstrated that it can provide a satisfactory balance between imaging accuracy and computational burden.

  3. Hybrid Model Based on Genetic Algorithms and SVM Applied to Variable Selection within Fruit Juice Classification

    Directory of Open Access Journals (Sweden)

    C. Fernandez-Lozano

    2013-01-01

    Full Text Available Given the background of the use of Neural Networks in problems of apple juice classification, this paper aim at implementing a newly developed method in the field of machine learning: the Support Vector Machines (SVM. Therefore, a hybrid model that combines genetic algorithms and support vector machines is suggested in such a way that, when using SVM as a fitness function of the Genetic Algorithm (GA, the most representative variables for a specific classification problem can be selected.

  4. Hybrid advection scheme for 3-dimensional atmospheric models. Testing and application for a study of NO{sub x} transport

    Energy Technology Data Exchange (ETDEWEB)

    Zubov, V A; Rozanov, E V [Main Geophysical Observatory, St.Petersburg (Russian Federation); Schlesinger, M E; Andronova, N G [Illinois Univ., Urbana-Champaign, IL (United States). Dept. of Atmospheric Sciences

    1998-12-31

    The problems of ozone depletion, climate change and atmospheric pollution strongly depend on the processes of production, destruction and transport of chemical species. A hybrid transport scheme was developed, consisting of the semi-Lagrangian scheme for horizontal advection and the Prather scheme for vertical transport, which have been used for the Atmospheric Chemical Transport model to calculate the distributions of different chemical species. The performance of the new hybrid scheme has been evaluated in comparison with other transport schemes on the basis of specially designed tests. The seasonal cycle of the distribution of N{sub 2}O simulated by the model, as well as the dispersion of NO{sub x} exhausted from subsonic aircraft, are in a good agreement with published data. (author) 8 refs.

  5. Hybrid advection scheme for 3-dimensional atmospheric models. Testing and application for a study of NO{sub x} transport

    Energy Technology Data Exchange (ETDEWEB)

    Zubov, V.A.; Rozanov, E.V. [Main Geophysical Observatory, St.Petersburg (Russian Federation); Schlesinger, M.E.; Andronova, N.G. [Illinois Univ., Urbana-Champaign, IL (United States). Dept. of Atmospheric Sciences

    1997-12-31

    The problems of ozone depletion, climate change and atmospheric pollution strongly depend on the processes of production, destruction and transport of chemical species. A hybrid transport scheme was developed, consisting of the semi-Lagrangian scheme for horizontal advection and the Prather scheme for vertical transport, which have been used for the Atmospheric Chemical Transport model to calculate the distributions of different chemical species. The performance of the new hybrid scheme has been evaluated in comparison with other transport schemes on the basis of specially designed tests. The seasonal cycle of the distribution of N{sub 2}O simulated by the model, as well as the dispersion of NO{sub x} exhausted from subsonic aircraft, are in a good agreement with published data. (author) 8 refs.

  6. Hybrid image classification technique for land-cover mapping in the Arctic tundra, North Slope, Alaska

    Science.gov (United States)

    Chaudhuri, Debasish

    Remotely sensed image classification techniques are very useful to understand vegetation patterns and species combination in the vast and mostly inaccessible arctic region. Previous researches that were done for mapping of land cover and vegetation in the remote areas of northern Alaska have considerably low accuracies compared to other biomes. The unique arctic tundra environment with short growing season length, cloud cover, low sun angles, snow and ice cover hinders the effectiveness of remote sensing studies. The majority of image classification research done in this area as reported in the literature used traditional unsupervised clustering technique with Landsat MSS data. It was also emphasized by previous researchers that SPOT/HRV-XS data lacked the spectral resolution to identify the small arctic tundra vegetation parcels. Thus, there is a motivation and research need to apply a new classification technique to develop an updated, detailed and accurate vegetation map at a higher spatial resolution i.e. SPOT-5 data. Traditional classification techniques in remotely sensed image interpretation are based on spectral reflectance values with an assumption of the training data being normally distributed. Hence it is difficult to add ancillary data in classification procedures to improve accuracy. The purpose of this dissertation was to develop a hybrid image classification approach that effectively integrates ancillary information into the classification process and combines ISODATA clustering, rule-based classifier and the Multilayer Perceptron (MLP) classifier which uses artificial neural network (ANN). The main goal was to find out the best possible combination or sequence of classifiers for typically classifying tundra type vegetation that yields higher accuracy than the existing classified vegetation map from SPOT data. Unsupervised ISODATA clustering and rule-based classification techniques were combined to produce an intermediate classified map which was

  7. Mammogram classification scheme using 2D-discrete wavelet and local binary pattern for detection of breast cancer

    Science.gov (United States)

    Adi Putra, Januar

    2018-04-01

    In this paper, we propose a new mammogram classification scheme to classify the breast tissues as normal or abnormal. Feature matrix is generated using Local Binary Pattern to all the detailed coefficients from 2D-DWT of the region of interest (ROI) of a mammogram. Feature selection is done by selecting the relevant features that affect the classification. Feature selection is used to reduce the dimensionality of data and features that are not relevant, in this paper the F-test and Ttest will be performed to the results of the feature extraction dataset to reduce and select the relevant feature. The best features are used in a Neural Network classifier for classification. In this research we use MIAS and DDSM database. In addition to the suggested scheme, the competent schemes are also simulated for comparative analysis. It is observed that the proposed scheme has a better say with respect to accuracy, specificity and sensitivity. Based on experiments, the performance of the proposed scheme can produce high accuracy that is 92.71%, while the lowest accuracy obtained is 77.08%.

  8. An efficient hybrid protection scheme with shared/dedicated backup paths on elastic optical networks

    Directory of Open Access Journals (Sweden)

    Nogbou G. Anoh

    2017-02-01

    Full Text Available Fast recovery and minimum utilization of resources are the two main criteria for determining the protection scheme quality. We address the problem of providing a hybrid protection approach on elastic optical networks under contiguity and continuity of available spectrum constraints. Two main hypotheses are used in this paper for backup paths computation. In the first case, it is assumed that backup paths resources are dedicated. In the second case, the assumption is that backup paths resources are available shared resources. The objective of the study is to minimize spectrum utilization to reduce blocking probability on a network. For this purpose, an efficient survivable Hybrid Protection Lightpath (HybPL algorithm is proposed for providing shared or dedicated backup path protection based on the efficient energy calculation and resource availability. Traditional First-Fit and Best-Fit schemes are employed to search and assign the available spectrum resources. The simulation results show that HybPL presents better performance in terms of blocking probability, compared with the Minimum Resources Utilization Dedicated Protection (MRU-DP algorithm which offers better performance than the Dedicated Protection (DP algorithm.

  9. A Hybrid Scheme Based on Pipelining and Multitasking in Mobile Application Processors for Advanced Video Coding

    Directory of Open Access Journals (Sweden)

    Muhammad Asif

    2015-01-01

    Full Text Available One of the key requirements for mobile devices is to provide high-performance computing at lower power consumption. The processors used in these devices provide specific hardware resources to handle computationally intensive video processing and interactive graphical applications. Moreover, processors designed for low-power applications may introduce limitations on the availability and usage of resources, which present additional challenges to the system designers. Owing to the specific design of the JZ47x series of mobile application processors, a hybrid software-hardware implementation scheme for H.264/AVC encoder is proposed in this work. The proposed scheme distributes the encoding tasks among hardware and software modules. A series of optimization techniques are developed to speed up the memory access and data transferring among memories. Moreover, an efficient data reusage design is proposed for the deblock filter video processing unit to reduce the memory accesses. Furthermore, fine grained macroblock (MB level parallelism is effectively exploited and a pipelined approach is proposed for efficient utilization of hardware processing cores. Finally, based on parallelism in the proposed design, encoding tasks are distributed between two processing cores. Experiments show that the hybrid encoder is 12 times faster than a highly optimized sequential encoder due to proposed techniques.

  10. Hybrid Numerical-Analytical Scheme for Calculating Elastic Wave Diffraction in Locally Inhomogeneous Waveguides

    Science.gov (United States)

    Glushkov, E. V.; Glushkova, N. V.; Evdokimov, A. A.

    2018-01-01

    Numerical simulation of traveling wave excitation, propagation, and diffraction in structures with local inhomogeneities (obstacles) is computationally expensive due to the need for mesh-based approximation of extended domains with the rigorous account for the radiation conditions at infinity. Therefore, hybrid numerical-analytic approaches are being developed based on the conjugation of a numerical solution in a local vicinity of the obstacle and/or source with an explicit analytic representation in the remaining semi-infinite external domain. However, in standard finite-element software, such a coupling with the external field, moreover, in the case of multimode expansion, is generally not provided. This work proposes a hybrid computational scheme that allows realization of such a conjugation using a standard software. The latter is used to construct a set of numerical solutions used as the basis for the sought solution in the local internal domain. The unknown expansion coefficients on this basis and on normal modes in the semi-infinite external domain are then determined from the conditions of displacement and stress continuity at the boundary between the two domains. We describe the implementation of this approach in the scalar and vector cases. To evaluate the reliability of the results and the efficiency of the algorithm, we compare it with a semianalytic solution to the problem of traveling wave diffraction by a horizontal obstacle, as well as with a finite-element solution obtained for a limited domain artificially restricted using absorbing boundaries. As an example, we consider the incidence of a fundamental antisymmetric Lamb wave onto surface and partially submerged elastic obstacles. It is noted that the proposed hybrid scheme can also be used to determine the eigenfrequencies and eigenforms of resonance scattering, as well as the characteristics of traveling waves in embedded waveguides.

  11. An adaptive hybrid EnKF-OI scheme for efficient state-parameter estimation of reactive contaminant transport models

    KAUST Repository

    El Gharamti, Mohamad; Valstar, Johan R.; Hoteit, Ibrahim

    2014-01-01

    Reactive contaminant transport models are used by hydrologists to simulate and study the migration and fate of industrial waste in subsurface aquifers. Accurate transport modeling of such waste requires clear understanding of the system's parameters, such as sorption and biodegradation. In this study, we present an efficient sequential data assimilation scheme that computes accurate estimates of aquifer contamination and spatially variable sorption coefficients. This assimilation scheme is based on a hybrid formulation of the ensemble Kalman filter (EnKF) and optimal interpolation (OI) in which solute concentration measurements are assimilated via a recursive dual estimation of sorption coefficients and contaminant state variables. This hybrid EnKF-OI scheme is used to mitigate background covariance limitations due to ensemble under-sampling and neglected model errors. Numerical experiments are conducted with a two-dimensional synthetic aquifer in which cobalt-60, a radioactive contaminant, is leached in a saturated heterogeneous clayey sandstone zone. Assimilation experiments are investigated under different settings and sources of model and observational errors. Simulation results demonstrate that the proposed hybrid EnKF-OI scheme successfully recovers both the contaminant and the sorption rate and reduces their uncertainties. Sensitivity analyses also suggest that the adaptive hybrid scheme remains effective with small ensembles, allowing to reduce the ensemble size by up to 80% with respect to the standard EnKF scheme. © 2014 Elsevier Ltd.

  12. An adaptive hybrid EnKF-OI scheme for efficient state-parameter estimation of reactive contaminant transport models

    KAUST Repository

    El Gharamti, Mohamad

    2014-09-01

    Reactive contaminant transport models are used by hydrologists to simulate and study the migration and fate of industrial waste in subsurface aquifers. Accurate transport modeling of such waste requires clear understanding of the system\\'s parameters, such as sorption and biodegradation. In this study, we present an efficient sequential data assimilation scheme that computes accurate estimates of aquifer contamination and spatially variable sorption coefficients. This assimilation scheme is based on a hybrid formulation of the ensemble Kalman filter (EnKF) and optimal interpolation (OI) in which solute concentration measurements are assimilated via a recursive dual estimation of sorption coefficients and contaminant state variables. This hybrid EnKF-OI scheme is used to mitigate background covariance limitations due to ensemble under-sampling and neglected model errors. Numerical experiments are conducted with a two-dimensional synthetic aquifer in which cobalt-60, a radioactive contaminant, is leached in a saturated heterogeneous clayey sandstone zone. Assimilation experiments are investigated under different settings and sources of model and observational errors. Simulation results demonstrate that the proposed hybrid EnKF-OI scheme successfully recovers both the contaminant and the sorption rate and reduces their uncertainties. Sensitivity analyses also suggest that the adaptive hybrid scheme remains effective with small ensembles, allowing to reduce the ensemble size by up to 80% with respect to the standard EnKF scheme. © 2014 Elsevier Ltd.

  13. A Hybrid Feature Selection Approach for Arabic Documents Classification

    NARCIS (Netherlands)

    Habib, Mena Badieh; Sarhan, Ahmed A. E.; Salem, Abdel-Badeeh M.; Fayed, Zaki T.; Gharib, Tarek F.

    Text Categorization (classification) is the process of classifying documents into a predefined set of categories based on their content. Text categorization algorithms usually represent documents as bags of words and consequently have to deal with huge number of features. Feature selection tries to

  14. Spatial and Spectral Hybrid Image Classification for Rice Lodging Assessment through UAV Imagery

    Directory of Open Access Journals (Sweden)

    Ming-Der Yang

    2017-06-01

    Full Text Available Rice lodging identification relies on manual in situ assessment and often leads to a compensation dispute in agricultural disaster assessment. Therefore, this study proposes a comprehensive and efficient classification technique for agricultural lands that entails using unmanned aerial vehicle (UAV imagery. In addition to spectral information, digital surface model (DSM and texture information of the images was obtained through image-based modeling and texture analysis. Moreover, single feature probability (SFP values were computed to evaluate the contribution of spectral and spatial hybrid image information to classification accuracy. The SFP results revealed that texture information was beneficial for the classification of rice and water, DSM information was valuable for lodging and tree classification, and the combination of texture and DSM information was helpful in distinguishing between artificial surface and bare land. Furthermore, a decision tree classification model incorporating SFP values yielded optimal results, with an accuracy of 96.17% and a Kappa value of 0.941, compared with that of a maximum likelihood classification model (90.76%. The rice lodging ratio in paddies at the study site was successfully identified, with three paddies being eligible for disaster relief. The study demonstrated that the proposed spatial and spectral hybrid image classification technology is a promising tool for rice lodging assessment.

  15. An improved fault detection classification and location scheme based on wavelet transform and artificial neural network for six phase transmission line using single end data only.

    Science.gov (United States)

    Koley, Ebha; Verma, Khushaboo; Ghosh, Subhojit

    2015-01-01

    Restrictions on right of way and increasing power demand has boosted development of six phase transmission. It offers a viable alternative for transmitting more power, without major modification in existing structure of three phase double circuit transmission system. Inspite of the advantages, low acceptance of six phase system is attributed to the unavailability of a proper protection scheme. The complexity arising from large number of possible faults in six phase lines makes the protection quite challenging. The proposed work presents a hybrid wavelet transform and modular artificial neural network based fault detector, classifier and locator for six phase lines using single end data only. The standard deviation of the approximate coefficients of voltage and current signals obtained using discrete wavelet transform are applied as input to the modular artificial neural network for fault classification and location. The proposed scheme has been tested for all 120 types of shunt faults with variation in location, fault resistance, fault inception angles. The variation in power system parameters viz. short circuit capacity of the source and its X/R ratio, voltage, frequency and CT saturation has also been investigated. The result confirms the effectiveness and reliability of the proposed protection scheme which makes it ideal for real time implementation.

  16. A Hybrid Computational Intelligence Approach Combining Genetic Programming And Heuristic Classification for Pap-Smear Diagnosis

    DEFF Research Database (Denmark)

    Tsakonas, Athanasios; Dounias, Georgios; Jantzen, Jan

    2001-01-01

    The paper suggests the combined use of different computational intelligence (CI) techniques in a hybrid scheme, as an effective approach to medical diagnosis. Getting to know the advantages and disadvantages of each computational intelligence technique in the recent years, the time has come...

  17. A new gamma-ray burst classification scheme from GRB 060614.

    Science.gov (United States)

    Gehrels, N; Norris, J P; Barthelmy, S D; Granot, J; Kaneko, Y; Kouveliotou, C; Markwardt, C B; Mészáros, P; Nakar, E; Nousek, J A; O'Brien, P T; Page, M; Palmer, D M; Parsons, A M; Roming, P W A; Sakamoto, T; Sarazin, C L; Schady, P; Stamatikos, M; Woosley, S E

    2006-12-21

    Gamma-ray bursts (GRBs) are known to come in two duration classes, separated at approximately 2 s. Long-duration bursts originate from star-forming regions in galaxies, have accompanying supernovae when these are near enough to observe and are probably caused by massive-star collapsars. Recent observations show that short-duration bursts originate in regions within their host galaxies that have lower star-formation rates, consistent with binary neutron star or neutron star-black hole mergers. Moreover, although their hosts are predominantly nearby galaxies, no supernovae have been so far associated with short-duration GRBs. Here we report that the bright, nearby GRB 060614 does not fit into either class. Its approximately 102-s duration groups it with long-duration GRBs, while its temporal lag and peak luminosity fall entirely within the short-duration GRB subclass. Moreover, very deep optical observations exclude an accompanying supernova, similar to short-duration GRBs. This combination of a long-duration event without an accompanying supernova poses a challenge to both the collapsar and the merging-neutron-star interpretations and opens the door to a new GRB classification scheme that straddles both long- and short-duration bursts.

  18. A risk-based classification scheme for genetically modified foods. II: Graded testing.

    Science.gov (United States)

    Chao, Eunice; Krewski, Daniel

    2008-12-01

    This paper presents a graded approach to the testing of crop-derived genetically modified (GM) foods based on concern levels in a proposed risk-based classification scheme (RBCS) and currently available testing methods. A graded approach offers the potential for more efficient use of testing resources by focusing less on lower concern GM foods, and more on higher concern foods. In this proposed approach to graded testing, products that are classified as Level I would have met baseline testing requirements that are comparable to what is widely applied to premarket assessment of GM foods at present. In most cases, Level I products would require no further testing, or very limited confirmatory analyses. For products classified as Level II or higher, additional testing would be required, depending on the type of the substance, prior dietary history, estimated exposure level, prior knowledge of toxicity of the substance, and the nature of the concern related to unintended changes in the modified food. Level III testing applies only to the assessment of toxic and antinutritional effects from intended changes and is tailored to the nature of the substance in question. Since appropriate test methods are not currently available for all effects of concern, future research to strengthen the testing of GM foods is discussed.

  19. A new hybrid-Lagrangian numerical scheme for gyrokinetic simulation of tokamak edge plasma

    Energy Technology Data Exchange (ETDEWEB)

    Ku, S., E-mail: sku@pppl.gov [Princeton Plasma Physics Laboratory, Princeton University, Princeton, NJ 08543 (United States); Hager, R.; Chang, C.S. [Princeton Plasma Physics Laboratory, Princeton University, Princeton, NJ 08543 (United States); Kwon, J.M. [National Fusion Research Institute (Korea, Republic of); Parker, S.E. [University of Colorado Boulder (United States)

    2016-06-15

    In order to enable kinetic simulation of non-thermal edge plasmas at a reduced computational cost, a new hybrid-Lagrangian δf scheme has been developed that utilizes the phase space grid in addition to the usual marker particles, taking advantage of the computational strengths from both sides. The new scheme splits the particle distribution function of a kinetic equation into two parts. Marker particles contain the fast space-time varying, δf, part of the distribution function and the coarse-grained phase-space grid contains the slow space-time varying part. The coarse-grained phase-space grid reduces the memory-requirement and the computing cost, while the marker particles provide scalable computing ability for the fine-grained physics. Weights of the marker particles are determined by a direct weight evolution equation instead of the differential form weight evolution equations that the conventional delta-f schemes use. The particle weight can be slowly transferred to the phase space grid, thereby reducing the growth of the particle weights. The non-Lagrangian part of the kinetic equation – e.g., collision operation, ionization, charge exchange, heat-source, radiative cooling, and others – can be operated directly on the phase space grid. Deviation of the particle distribution function on the velocity grid from a Maxwellian distribution function – driven by ionization, charge exchange and wall loss – is allowed to be arbitrarily large. The numerical scheme is implemented in the gyrokinetic particle code XGC1, which specializes in simulating the tokamak edge plasma that crosses the magnetic separatrix and is in contact with the material wall.

  20. A hybrid-drive nonisobaric-ignition scheme for inertial confinement fusion

    Energy Technology Data Exchange (ETDEWEB)

    He, X. T., E-mail: xthe@iapcm.ac.cn [Institute of Applied Physics and Computational Mathematics, P. O. Box 8009, Beijing 100094 (China); Center for Applied Physics and Technology, HEDPS, Peking University, Beijing 100871 (China); IFSA Collaborative Innovation Center of MoE, Shanghai Jiao-Tong University, Shanghai 200240 (China); Institute of Fusion Theory and Simulation, Zhejiang University, Hangzhou 310027 (China); Li, J. W.; Wang, L. F.; Liu, J.; Lan, K.; Ye, W. H. [Institute of Applied Physics and Computational Mathematics, P. O. Box 8009, Beijing 100094 (China); Center for Applied Physics and Technology, HEDPS, Peking University, Beijing 100871 (China); IFSA Collaborative Innovation Center of MoE, Shanghai Jiao-Tong University, Shanghai 200240 (China); Fan, Z. F.; Wu, J. F. [Institute of Applied Physics and Computational Mathematics, P. O. Box 8009, Beijing 100094 (China)

    2016-08-15

    A new hybrid-drive (HD) nonisobaric ignition scheme of inertial confinement fusion (ICF) is proposed, in which a HD pressure to drive implosion dynamics increases via increasing density rather than temperature in the conventional indirect drive (ID) and direct drive (DD) approaches. In this HD (combination of ID and DD) scheme, an assembled target of a spherical hohlraum and a layered deuterium-tritium capsule inside is used. The ID lasers first drive the shock to perform a spherical symmetry implosion and produce a large-scale corona plasma. Then, the DD lasers, whose critical surface in ID corona plasma is far from the radiation ablation front, drive a supersonic electron thermal wave, which slows down to a high-pressure electron compression wave, like a snowplow, piling up the corona plasma into high density and forming a HD pressurized plateau with a large width. The HD pressure is several times the conventional ID and DD ablation pressure and launches an enhanced precursor shock and a continuous compression wave, which give rise to the HD capsule implosion dynamics in a large implosion velocity. The hydrodynamic instabilities at imploding capsule interfaces are suppressed, and the continuous HD compression wave provides main pdV work large enough to hotspot, resulting in the HD nonisobaric ignition. The ignition condition and target design based on this scheme are given theoretically and by numerical simulations. It shows that the novel scheme can significantly suppress implosion asymmetry and hydrodynamic instabilities of current isobaric hotspot ignition design, and a high-gain ICF is promising.

  1. The "chessboard" classification scheme of mineral deposits: Mineralogy and geology from aluminum to zirconium

    Science.gov (United States)

    Dill, Harald G.

    2010-06-01

    Economic geology is a mixtum compositum of all geoscientific disciplines focused on one goal, finding new mineral depsosits and enhancing their exploitation. The keystones of this mixtum compositum are geology and mineralogy whose studies are centered around the emplacement of the ore body and the development of its minerals and rocks. In the present study, mineralogy and geology act as x- and y-coordinates of a classification chart of mineral resources called the "chessboard" (or "spreadsheet") classification scheme. Magmatic and sedimentary lithologies together with tectonic structures (1 -D/pipes, 2 -D/veins) are plotted along the x-axis in the header of the spreadsheet diagram representing the columns in this chart diagram. 63 commodity groups, encompassing minerals and elements are plotted along the y-axis, forming the lines of the spreadsheet. These commodities are subjected to a tripartite subdivision into ore minerals, industrial minerals/rocks and gemstones/ornamental stones. Further information on the various types of mineral deposits, as to the major ore and gangue minerals, the current models and the mode of formation or when and in which geodynamic setting these deposits mainly formed throughout the geological past may be obtained from the text by simply using the code of each deposit in the chart. This code can be created by combining the commodity (lines) shown by numbers plus lower caps with the host rocks or structure (columns) given by capital letters. Each commodity has a small preface on the mineralogy and chemistry and ends up with an outlook into its final use and the supply situation of the raw material on a global basis, which may be updated by the user through a direct link to databases available on the internet. In this case the study has been linked to the commodity database of the US Geological Survey. The internal subdivision of each commodity section corresponds to the common host rock lithologies (magmatic, sedimentary, and

  2. A NEW SAR CLASSIFICATION SCHEME FOR SEDIMENTS ON INTERTIDAL FLATS BASED ON MULTI-FREQUENCY POLARIMETRIC SAR IMAGERY

    Directory of Open Access Journals (Sweden)

    W. Wang

    2017-11-01

    Full Text Available We present a new classification scheme for muddy and sandy sediments on exposed intertidal flats, which is based on synthetic aperture radar (SAR data, and use ALOS-2 (L-band, Radarsat-2 (C-band and TerraSAR-X (X-band fully polarimetric SAR imagery to demonstrate its effectiveness. Four test sites on the German North Sea coast were chosen, which represent typical surface compositions of different sediments, vegetation, and habitats, and of which a large amount of SAR is used for our analyses. Both Freeman-Durden and Cloude-Pottier polarimetric decomposition are utilized, and an additional descriptor called Double-Bounce Eigenvalue Relative Difference (DERD is introduced into the feature sets instead of the original polarimetric intensity channels. The classification is conducted following Random Forest theory, and the results are verified using ground truth data from field campaigns and an existing classification based on optical imagery. In addition, the use of Kennaugh elements for classification purposes is demonstrated using both fully and dual-polarization multi-frequency and multi-temporal SAR data. Our results show that the proposed classification scheme can be applied for the discrimination of muddy and sandy sediments using L-, C-, and X-band SAR images, while SAR imagery acquired at short wavelengths (C- and X-band can also be used to detect more detailed features such as bivalve beds on intertidal flats.

  3. Classification of childhood epilepsies in a tertiary pediatric neurology clinic using a customized classification scheme from the international league against epilepsy 2010 report.

    Science.gov (United States)

    Khoo, Teik-Beng

    2013-01-01

    In its 2010 report, the International League Against Epilepsy Commission on Classification and Terminology had made a number of changes to the organization, terminology, and classification of seizures and epilepsies. This study aims to test the usefulness of this revised classification scheme on children with epilepsies aged between 0 and 18 years old. Of 527 patients, 75.1% only had 1 type of seizure and the commonest was focal seizure (61.9%). A specific electroclinical syndrome diagnosis could be made in 27.5%. Only 2.1% had a distinctive constellation. In this cohort, 46.9% had an underlying structural, metabolic, or genetic etiology. Among the important causes were pre-/perinatal insults, malformation of cortical development, intracranial infections, and neurocutaneous syndromes. However, 23.5% of the patients in our cohort were classified as having "epilepsies of unknown cause." The revised classification scheme is generally useful for pediatric patients. To make it more inclusive and clinically meaningful, some local customizations are required.

  4. Non-hydrostatic semi-elastic hybrid-coordinate SISL extension of HIRLAM. Part I: numerical scheme

    OpenAIRE

    Rõõm, Rein; Männik, Aarne; Luhamaa, Andres

    2007-01-01

    Two-time-level, semi-implicit, semi-Lagrangian (SISL) scheme is applied to the non-hydrostatic pressure coordinate equations, constituting a modified Miller–Pearce–White model, in hybrid-coordinate framework. Neutral background is subtracted in the initial continuous dynamics, yielding modified equations for geopotential, temperature and logarithmic surface pressure fluctuation. Implicit Lagrangian marching formulae for single time-step are derived. A disclosure scheme is presented, which res...

  5. Hybrid scheme of positron source at SPARC-LAB LNF facility

    Energy Technology Data Exchange (ETDEWEB)

    Abdrashitov, S.V., E-mail: abdsv@tpu.ru [National Research Tomsk Polytechnic University, Lenin Ave 30, 634050 Tomsk (Russian Federation); National Research Tomsk State University, Lenin Ave 36, 634050 Tomsk (Russian Federation); Bogdanov, O.V. [National Research Tomsk Polytechnic University, Lenin Ave 30, 634050 Tomsk (Russian Federation); Dabagov, S.B. [INFN Laboratori Nazionali di Frascati, Via E. Fermi 40, I-00044 Frascati, RM (Italy); RAS PN Lebedev Physical Institute, Leninskiy Prospekt 53, 119991 Moscow (Russian Federation); NRNU MEPhI, Kashirskoe Highway 31, 115409 Moscow (Russian Federation); Pivovarov, Yu.L.; Tukhfatullin, T.A. [National Research Tomsk Polytechnic University, Lenin Ave 30, 634050 Tomsk (Russian Federation)

    2015-07-15

    The hybrid scheme of the positron source for SPARC-LAB LNF facility (Frascati, Italy) is proposed. The comparison of the positron yield in a thin amorphous W converter of 0.1 mm thickness produced by bremsstrahlung, by axial 〈1 0 0〉 and planar (1 1 0) channeling radiations in a W crystal is performed for the positron energy range of 1 ÷ 3 MeV. It is shown that the radiation from 200 MeV electrons (parameters of SPARC-LAB LNF Frascati) in a 10 μm W crystal can produce positrons in the radiator of 0.1 mm thickness with the rate of 10–10{sup 2} s{sup −1} at planar channeling, of 10{sup 2}–10{sup 3} s{sup −1} at bremsstrahlung and of 10{sup 3}–10{sup 4} s{sup −1} at axial channeling.

  6. A Polar Fuzzy Control Scheme for Hybrid Power System Using Vehicle-To-Grid Technique

    Directory of Open Access Journals (Sweden)

    Mohammed Elsayed Lotfy

    2017-07-01

    Full Text Available A novel polar fuzzy (PF control approach for a hybrid power system is proposed in this research. The proposed control scheme remedies the issues of system frequency and the continuity of demand supply caused by renewable sources’ uncertainties. The hybrid power system consists of a wind turbine generator (WTG, solar photovoltaics (PV, a solar thermal power generator (STPG, a diesel engine generator (DEG, an aqua-electrolyzer (AE, an ultra-capacitor (UC, a fuel-cell (FC, and a flywheel (FW. Furthermore, due to the high cost of the battery energy storage system (BESS, a new idea of vehicle-to-grid (V2G control is applied to use the battery of the electric vehicle (EV as equivalent to large-scale energy storage units instead of small batteries to improve the frequency stability of the system. In addition, EV customers’ convenience is taken into account. A minimal-order observer is used to estimate the supply error. Then, the area control error (ACE signal is calculated in terms of the estimated supply error and the frequency deviation. ACE is considered in the frequency domain. Two PF approaches are utilized in the intended system. The mission of each controller is to mitigate one frequency component of ACE. The responsibility for ACE compensation is shared among all parts of the system according to their speed of response. The performance of the proposed control scheme is compared to the conventional fuzzy logic control (FLC. The effectiveness and robustness of the proposed control technique are verified by numerical simulations under various scenarios.

  7. Development of an Optimal Power Control Scheme for Wave-Offshore Hybrid Generation Systems

    Directory of Open Access Journals (Sweden)

    Seungmin Jung

    2015-08-01

    Full Text Available Integration technology of various distribution systems for improving renewable energy utilization has been receiving attention in the power system industry. The wave-offshore hybrid generation system (HGS, which has a capacity of over 10 MW, was recently developed by adopting several voltage source converters (VSC, while a control method for adopted power conversion systems has not yet been configured in spite of the unique system characteristics of the designated structure. This paper deals with a reactive power assignment method for the developed hybrid system to improve the power transfer efficiency of the entire system. Through the development and application processes for an optimization algorithm utilizing the real-time active power profiles of each generator, a feasibility confirmation of power transmission loss reduction was implemented. To find the practical effect of the proposed control scheme, the real system information regarding the demonstration process was applied from case studies. Also, an evaluation for the loss of the improvement rate was calculated.

  8. A hybrid Eulerian–Lagrangian numerical scheme for solving prognostic equations in fluid dynamics

    Directory of Open Access Journals (Sweden)

    E. Kaas

    2013-11-01

    Full Text Available A new hybrid Eulerian–Lagrangian numerical scheme (HEL for solving prognostic equations in fluid dynamics is proposed. The basic idea is to use an Eulerian as well as a fully Lagrangian representation of all prognostic variables. The time step in Lagrangian space is obtained as a translation of irregularly spaced Lagrangian parcels along downstream trajectories. Tendencies due to other physical processes than advection are calculated in Eulerian space, interpolated, and added to the Lagrangian parcel values. A directionally biased mixing amongst neighboring Lagrangian parcels is introduced. The rate of mixing is proportional to the local deformation rate of the flow. The time stepping in Eulerian representation is achieved in two steps: first a mass-conserving Eulerian or semi-Lagrangian scheme is used to obtain a provisional forecast. This forecast is then nudged towards target values defined from the irregularly spaced Lagrangian parcel values. The nudging procedure is defined in such a way that mass conservation and shape preservation is ensured in Eulerian space. The HEL scheme has been designed to be accurate, multi-tracer efficient, mass conserving, and shape preserving. In Lagrangian space only physically based mixing takes place; i.e., the problem of artificial numerical mixing is avoided. This property is desirable in atmospheric chemical transport models since spurious numerical mixing can impact chemical concentrations severely. The properties of HEL are here verified in two-dimensional tests. These include deformational passive transport on the sphere, and simulations with a semi-implicit shallow water model including topography.

  9. Efficient Hybrid Watermarking Scheme for Security and Transmission Bit Rate Enhancement of 3D Color-Plus-Depth Video Communication

    Science.gov (United States)

    El-Shafai, W.; El-Rabaie, S.; El-Halawany, M.; Abd El-Samie, F. E.

    2018-03-01

    Three-Dimensional Video-plus-Depth (3DV + D) comprises diverse video streams captured by different cameras around an object. Therefore, there is a great need to fulfill efficient compression to transmit and store the 3DV + D content in compressed form to attain future resource bounds whilst preserving a decisive reception quality. Also, the security of the transmitted 3DV + D is a critical issue for protecting its copyright content. This paper proposes an efficient hybrid watermarking scheme for securing the 3DV + D transmission, which is the homomorphic transform based Singular Value Decomposition (SVD) in Discrete Wavelet Transform (DWT) domain. The objective of the proposed watermarking scheme is to increase the immunity of the watermarked 3DV + D to attacks and achieve adequate perceptual quality. Moreover, the proposed watermarking scheme reduces the transmission-bandwidth requirements for transmitting the color-plus-depth 3DV over limited-bandwidth wireless networks through embedding the depth frames into the color frames of the transmitted 3DV + D. Thus, it saves the transmission bit rate and subsequently it enhances the channel bandwidth-efficiency. The performance of the proposed watermarking scheme is compared with those of the state-of-the-art hybrid watermarking schemes. The comparisons depend on both the subjective visual results and the objective results; the Peak Signal-to-Noise Ratio (PSNR) of the watermarked frames and the Normalized Correlation (NC) of the extracted watermark frames. Extensive simulation results on standard 3DV + D sequences have been conducted in the presence of attacks. The obtained results confirm that the proposed hybrid watermarking scheme is robust in the presence of attacks. It achieves not only very good perceptual quality with appreciated PSNR values and saving in the transmission bit rate, but also high correlation coefficient values in the presence of attacks compared to the existing hybrid watermarking schemes.

  10. Application of a Hybrid Detection and Location Scheme to Volcanic Systems

    Science.gov (United States)

    Thurber, C. H.; Lanza, F.; Roecker, S. W.

    2017-12-01

    We are using a hybrid method for automated detection and onset estimation, called REST, that combines a modified version of the nearest-neighbor similarity scheme of Rawles and Thurber (2015; RT15) with the regression approach of Kushnir et al. (1990; K90). This approach incorporates some of the windowing ideas proposed by RT15 into the regression techniques described in K90. The K90 and RT15 algorithms both define an onset as that sample where a segment of noise at earlier times is most "unlike" a segment of data at later times; the main difference between the approaches is how one defines "likeness." Hence, it is fairly straightforward to adapt the RT15 ideas to a K90 approach. We also incorporated the running mean normalization scheme of Bensen et al. (2007), used in ambient noise pre-processing, to reduce the effects of coherent signals (such as earthquakes) in defining noise segments. This is especially useful for aftershock sequences, when the persistent high amplitudes due to many earthquakes biases the true noise level. We use the fall-off of the K90 estimation function to assign uncertainties and the asymmetry of the function as a causality constraint. The detection and onset estimation stage is followed by iterative pick association and event location using a grid-search method. Some fine-tuning of some parameters is generally required for optimal results. We present 2 applications of this scheme to data from volcanic systems: Makushin volcano, Alaska, and Laguna del Maule (LdM), Chile. In both cases, there are permanent seismic networks, operated by the Alaska Volcano Observatory (AVO) and Observatorio Volcanológico de Los Andes del Sur (OVDAS), respectively, and temporary seismic arrays were deployed for a year or more. For Makushin, we have analyzed a year of data, from summer 2015 to summer 2016. The AVO catalog has 691 events in our study volume; REST processing yields 1784 more events. After quality control, the event numbers are 151 AVO events and

  11. Classification of Movement and Inhibition Using a Hybrid BCI.

    Science.gov (United States)

    Chmura, Jennifer; Rosing, Joshua; Collazos, Steven; Goodwin, Shikha J

    2017-01-01

    Brain-computer interfaces (BCIs) are an emerging technology that are capable of turning brain electrical activity into commands for an external device. Motor imagery (MI)-when a person imagines a motion without executing it-is widely employed in BCI devices for motor control because of the endogenous origin of its neural control mechanisms, and the similarity in brain activation to actual movements. Challenges with translating a MI-BCI into a practical device used outside laboratories include the extensive training required, often due to poor user engagement and visual feedback response delays; poor user flexibility/freedom to time the execution/inhibition of their movements, and to control the movement type (right arm vs. left leg) and characteristics (reaching vs. grabbing); and high false positive rates of motion control. Solutions to improve sensorimotor activation and user performance of MI-BCIs have been explored. Virtual reality (VR) motor-execution tasks have replaced simpler visual feedback (smiling faces, arrows) and have solved this problem to an extent. Hybrid BCIs (hBCIs) implementing an additional control signal to MI have improved user control capabilities to a limited extent. These hBCIs either fail to allow the patients to gain asynchronous control of their movements, or have a high false positive rate. We propose an immersive VR environment which provides visual feedback that is both engaging and immediate, but also uniquely engages a different cognitive process in the patient that generates event-related potentials (ERPs). These ERPs provide a key executive function for the users to execute/inhibit movements. Additionally, we propose signal processing strategies and machine learning algorithms to move BCIs toward developing long-term signal stability in patients with distinctive brain signals and capabilities to control motor signals. The hBCI itself and the VR environment we propose would help to move BCI technology outside laboratory

  12. Classification of Movement and Inhibition Using a Hybrid BCI

    Directory of Open Access Journals (Sweden)

    Jennifer Chmura

    2017-08-01

    Full Text Available Brain-computer interfaces (BCIs are an emerging technology that are capable of turning brain electrical activity into commands for an external device. Motor imagery (MI—when a person imagines a motion without executing it—is widely employed in BCI devices for motor control because of the endogenous origin of its neural control mechanisms, and the similarity in brain activation to actual movements. Challenges with translating a MI-BCI into a practical device used outside laboratories include the extensive training required, often due to poor user engagement and visual feedback response delays; poor user flexibility/freedom to time the execution/inhibition of their movements, and to control the movement type (right arm vs. left leg and characteristics (reaching vs. grabbing; and high false positive rates of motion control. Solutions to improve sensorimotor activation and user performance of MI-BCIs have been explored. Virtual reality (VR motor-execution tasks have replaced simpler visual feedback (smiling faces, arrows and have solved this problem to an extent. Hybrid BCIs (hBCIs implementing an additional control signal to MI have improved user control capabilities to a limited extent. These hBCIs either fail to allow the patients to gain asynchronous control of their movements, or have a high false positive rate. We propose an immersive VR environment which provides visual feedback that is both engaging and immediate, but also uniquely engages a different cognitive process in the patient that generates event-related potentials (ERPs. These ERPs provide a key executive function for the users to execute/inhibit movements. Additionally, we propose signal processing strategies and machine learning algorithms to move BCIs toward developing long-term signal stability in patients with distinctive brain signals and capabilities to control motor signals. The hBCI itself and the VR environment we propose would help to move BCI technology outside

  13. Computer-aided diagnosis scheme for histological classification of clustered microcalcifications on magnification mammograms

    International Nuclear Information System (INIS)

    Nakayama, Ryohei; Uchiyama, Yoshikazu; Watanabe, Ryoji; Katsuragawa, Shigehiko; Namba, Kiyoshi; Doi, Kunio

    2004-01-01

    The histological classification of clustered microcalcifications on mammograms can be difficult, and thus often require biopsy or follow-up. Our purpose in this study was to develop a computer-aided diagnosis schemefor identifying the histological classification of clustered microcalcifications on magnification mammograms in order to assist the radiologists' interpretation as a 'second opinion'. Our database consisted of 58 magnification mammograms, which included 35 malignant clustered microcalcifications (9 invasive carcinomas, 12 noninvasive carcinomas of the comedo type, and 14 noninvasive carcinomas of the noncomedo type) and 23 benign clustered microcalcifications (17 mastopathies and 6 fibroadenomas). The histological classifications of all clustered microcalcifications were proved by pathologic diagnosis. The clustered microcalcifications were first segmented by use of a novel filter bank and a thresholding technique. Five objective features on clustered microcalcifications were determined by taking into account subjective features that experienced the radiologists commonly use to identify possible histological classifications. The Bayes decision rule with five objective features was employed for distinguishing between five histological classifications. The classification accuracies for distinguishing between three malignant histological classifications were 77.8% (7/9) for invasive carcinoma, 75.0% (9/12) for noninvasive carcinoma of the comedo type, and 92.9% (13/14) for noninvasive carcinoma of the noncomedo type. The classification accuracies for distinguishing between two benign histological classifications were 94.1% (16/17) for mastopathy, and 100.0% (6/6) for fibroadenoma. This computerized method would be useful in assisting radiologists in their assessments of clustered microcalcifications

  14. A risk-based classification scheme for genetically modified foods. III: Evaluation using a panel of reference foods.

    Science.gov (United States)

    Chao, Eunice; Krewski, Daniel

    2008-12-01

    This paper presents an exploratory evaluation of four functional components of a proposed risk-based classification scheme (RBCS) for crop-derived genetically modified (GM) foods in a concordance study. Two independent raters assigned concern levels to 20 reference GM foods using a rating form based on the proposed RBCS. The four components of evaluation were: (1) degree of concordance, (2) distribution across concern levels, (3) discriminating ability of the scheme, and (4) ease of use. At least one of the 20 reference foods was assigned to each of the possible concern levels, demonstrating the ability of the scheme to identify GM foods of different concern with respect to potential health risk. There was reasonably good concordance between the two raters for the three separate parts of the RBCS. The raters agreed that the criteria in the scheme were sufficiently clear in discriminating reference foods into different concern levels, and that with some experience, the scheme was reasonably easy to use. Specific issues and suggestions for improvements identified in the concordance study are discussed.

  15. A Discrete Wavelet Based Feature Extraction and Hybrid Classification Technique for Microarray Data Analysis

    Directory of Open Access Journals (Sweden)

    Jaison Bennet

    2014-01-01

    Full Text Available Cancer classification by doctors and radiologists was based on morphological and clinical features and had limited diagnostic ability in olden days. The recent arrival of DNA microarray technology has led to the concurrent monitoring of thousands of gene expressions in a single chip which stimulates the progress in cancer classification. In this paper, we have proposed a hybrid approach for microarray data classification based on nearest neighbor (KNN, naive Bayes, and support vector machine (SVM. Feature selection prior to classification plays a vital role and a feature selection technique which combines discrete wavelet transform (DWT and moving window technique (MWT is used. The performance of the proposed method is compared with the conventional classifiers like support vector machine, nearest neighbor, and naive Bayes. Experiments have been conducted on both real and benchmark datasets and the results indicate that the ensemble approach produces higher classification accuracy than conventional classifiers. This paper serves as an automated system for the classification of cancer and can be applied by doctors in real cases which serve as a boon to the medical community. This work further reduces the misclassification of cancers which is highly not allowed in cancer detection.

  16. Automated classification of tropical shrub species: a hybrid of leaf shape and machine learning approach.

    Science.gov (United States)

    Murat, Miraemiliana; Chang, Siow-Wee; Abu, Arpah; Yap, Hwa Jen; Yong, Kien-Thai

    2017-01-01

    Plants play a crucial role in foodstuff, medicine, industry, and environmental protection. The skill of recognising plants is very important in some applications, including conservation of endangered species and rehabilitation of lands after mining activities. However, it is a difficult task to identify plant species because it requires specialized knowledge. Developing an automated classification system for plant species is necessary and valuable since it can help specialists as well as the public in identifying plant species easily. Shape descriptors were applied on the myDAUN dataset that contains 45 tropical shrub species collected from the University of Malaya (UM), Malaysia. Based on literature review, this is the first study in the development of tropical shrub species image dataset and classification using a hybrid of leaf shape and machine learning approach. Four types of shape descriptors were used in this study namely morphological shape descriptors (MSD), Histogram of Oriented Gradients (HOG), Hu invariant moments (Hu) and Zernike moments (ZM). Single descriptor, as well as the combination of hybrid descriptors were tested and compared. The tropical shrub species are classified using six different classifiers, which are artificial neural network (ANN), random forest (RF), support vector machine (SVM), k-nearest neighbour (k-NN), linear discriminant analysis (LDA) and directed acyclic graph multiclass least squares twin support vector machine (DAG MLSTSVM). In addition, three types of feature selection methods were tested in the myDAUN dataset, Relief, Correlation-based feature selection (CFS) and Pearson's coefficient correlation (PCC). The well-known Flavia dataset and Swedish Leaf dataset were used as the validation dataset on the proposed methods. The results showed that the hybrid of all descriptors of ANN outperformed the other classifiers with an average classification accuracy of 98.23% for the myDAUN dataset, 95.25% for the Flavia dataset and 99

  17. Adjoint optimization scheme for lower hybrid current rampup and profile control in Tokamak

    International Nuclear Information System (INIS)

    Litaudon, X.; Moreau, D.; Bizarro, J.P.; Hoang, G.T.; Kupfer, K.; Peysson, Y.; Shkarofsky, I.P.; Bonoli, P.

    1992-12-01

    The purpose of this work is to take into account and study the effect of the electric field profiles on the Lower Hybrid (LH) current drive efficiency during transient phases such as rampup. As a complement to the full ray-tracing / Fokker Planck studies, and for the purpose of optimization studies, we developed a simplified 1-D model based on the adjoint Karney-Fisch numerical results. This approach allows us to estimate the LH power deposition profile which would be required for ramping the current with prescribed rate, total current density profile (q-profile) and surface loop voltage. For rampup optimization studies, we can therefore scan the whole parameter space and eliminate a posteriori those scenarios which correspond to unrealistic deposition profiles. We thus obtain the time evolution of the LH power, minor radius of the plasma, volt-second consumption and total energy dissipated. Optimization can thus be performed with respect to any of those criteria. This scheme is illustrated by some numerical simulations performed with TORE-SUPRA and NET/ITER parameters. We conclude with a derivation of a simple and general scaling law for the flux consumption during the rampup phase

  18. On the fly all-optical packet switching based on hybrid WDM/OCDMA labeling scheme

    Science.gov (United States)

    Brahmi, Houssem; Giannoulis, Giannis; Menif, Mourad; Katopodis, Vasilis; Kalavrouziotis, Dimitrios; Kouloumentas, Christos; Groumas, Panos; Kanakis, Giannis; Stamatiadis, Christos; Avramopoulos, Hercules; Erasme, Didier

    2014-02-01

    We introduce a novel design of an all-optical packet routing node that allows for the selection and forwarding of optical packets based on the routing information contained in hybrid wavelength division multiplexing/optical code division multiple access (WDM/OCDMA) labels. A stripping paradigm of optical code-label is adopted. The router is built around an optical-code gate that consists in an optical flip-flop controlled by two fiber Bragg grating correlators and is combined with a Mach-Zehnder interferometer (MZI)-based forwarding gate. We experimentally verify the proof-of-principle operation of the proposed self-routing node under NRZ and OCDMA packet traffic conditions. The successful switching of elastic NRZ payload at 40 Gb/s controlled by DS-OCDMA coded labels and the forwarding operation of encoded data using EQC codes are presented. Proper auto-correlation functions are obtained with higher than 8.1 dB contrast ratio, suitable to efficiently trigger the latching device with a contrast ratio of 11.6 dB and switching times below 3.8 ns. Error-free operation is achieved with 1.5 dB penalty for 40 Gb/s NRZ data and with 2.1 dB penalty for DS-OCDMA packets. The scheme can further be applied to large-scale optical packet switching networks by exploiting efficient optical coders allocated at different WDM channels.

  19. An efficient hybrid pseudospectral/finite-difference scheme for solving the TTI pure P-wave equation

    KAUST Repository

    Zhan, Ge

    2013-02-19

    The pure P-wave equation for modelling and migration in tilted transversely isotropic (TTI) media has attracted more and more attention in imaging seismic data with anisotropy. The desirable feature is that it is absolutely free of shear-wave artefacts and the consequent alleviation of numerical instabilities generally suffered by some systems of coupled equations. However, due to several forward-backward Fourier transforms in wavefield updating at each time step, the computational cost is significant, and thereby hampers its prevalence. We propose to use a hybrid pseudospectral (PS) and finite-difference (FD) scheme to solve the pure P-wave equation. In the hybrid solution, most of the cost-consuming wavenumber terms in the equation are replaced by inexpensive FD operators, which in turn accelerates the computation and reduces the computational cost. To demonstrate the benefit in cost saving of the new scheme, 2D and 3D reverse-time migration (RTM) examples using the hybrid solution to the pure P-wave equation are carried out, and respective runtimes are listed and compared. Numerical results show that the hybrid strategy demands less computation time and is faster than using the PS method alone. Furthermore, this new TTI RTM algorithm with the hybrid method is computationally less expensive than that with the FD solution to conventional TTI coupled equations. © 2013 Sinopec Geophysical Research Institute.

  20. An efficient hybrid pseudospectral/finite-difference scheme for solving the TTI pure P-wave equation

    International Nuclear Information System (INIS)

    Zhan, Ge; Pestana, Reynam C; Stoffa, Paul L

    2013-01-01

    The pure P-wave equation for modelling and migration in tilted transversely isotropic (TTI) media has attracted more and more attention in imaging seismic data with anisotropy. The desirable feature is that it is absolutely free of shear-wave artefacts and the consequent alleviation of numerical instabilities generally suffered by some systems of coupled equations. However, due to several forward–backward Fourier transforms in wavefield updating at each time step, the computational cost is significant, and thereby hampers its prevalence. We propose to use a hybrid pseudospectral (PS) and finite-difference (FD) scheme to solve the pure P-wave equation. In the hybrid solution, most of the cost-consuming wavenumber terms in the equation are replaced by inexpensive FD operators, which in turn accelerates the computation and reduces the computational cost. To demonstrate the benefit in cost saving of the new scheme, 2D and 3D reverse-time migration (RTM) examples using the hybrid solution to the pure P-wave equation are carried out, and respective runtimes are listed and compared. Numerical results show that the hybrid strategy demands less computation time and is faster than using the PS method alone. Furthermore, this new TTI RTM algorithm with the hybrid method is computationally less expensive than that with the FD solution to conventional TTI coupled equations. (paper)

  1. Sound insulation and reverberation time for classrooms - Criteria in regulations and classification schemes in the Nordic countries

    DEFF Research Database (Denmark)

    Rasmussen, Birgit

    2016-01-01

    Acoustic regulations or guidelines for schools exist in all five Nordic countries. The acoustic criteria depend on room uses and deal with airborne and impact sound insulation, reverberation time, sound absorption, traffic noise, service equipment noise and other acoustic performance...... have become more extensive and stricter during the last two decades. The paper focuses on comparison of sound insulation and reverberation time criteria for classrooms in regulations and classification schemes in the Nordic countries. Limit values and changes over time will be discussed as well as how...... not identical. The national criteria for quality level C correspond to the national regulations or recommendations for new-build. The quality levels A and B are intended to define better acoustic performance than C, and D lower performance. Typically, acoustic regulations and classification criteria for schools...

  2. A hybrid clustering and classification approach for predicting crash injury severity on rural roads.

    Science.gov (United States)

    Hasheminejad, Seyed Hessam-Allah; Zahedi, Mohsen; Hasheminejad, Seyed Mohammad Hossein

    2018-03-01

    As a threat for transportation system, traffic crashes have a wide range of social consequences for governments. Traffic crashes are increasing in developing countries and Iran as a developing country is not immune from this risk. There are several researches in the literature to predict traffic crash severity based on artificial neural networks (ANNs), support vector machines and decision trees. This paper attempts to investigate the crash injury severity of rural roads by using a hybrid clustering and classification approach to compare the performance of classification algorithms before and after applying the clustering. In this paper, a novel rule-based genetic algorithm (GA) is proposed to predict crash injury severity, which is evaluated by performance criteria in comparison with classification algorithms like ANN. The results obtained from analysis of 13,673 crashes (5600 property damage, 778 fatal crashes, 4690 slight injuries and 2605 severe injuries) on rural roads in Tehran Province of Iran during 2011-2013 revealed that the proposed GA method outperforms other classification algorithms based on classification metrics like precision (86%), recall (88%) and accuracy (87%). Moreover, the proposed GA method has the highest level of interpretation, is easy to understand and provides feedback to analysts.

  3. Fast Schemes for Computing Similarities between Gaussian HMMs and Their Applications in Texture Image Classification

    Directory of Open Access Journals (Sweden)

    Chen Ling

    2005-01-01

    Full Text Available An appropriate definition and efficient computation of similarity (or distance measures between two stochastic models are of theoretical and practical interest. In this work, a similarity measure, that is, a modified "generalized probability product kernel," of Gaussian hidden Markov models is introduced. Two efficient schemes for computing this similarity measure are presented. The first scheme adopts a forward procedure analogous to the approach commonly used in probability evaluation of observation sequences on HMMs. The second scheme is based on the specially defined similarity transition matrix of two Gaussian hidden Markov models. Two scaling procedures are also proposed to solve the out-of-precision problem in the implementation. The effectiveness of the proposed methods has been evaluated on simulated observations with predefined model parameters, and on natural texture images. Promising experimental results have been observed.

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

    Science.gov (United States)

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

    2010-02-15

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

  5. Hybrid PAPR reduction scheme with Huffman coding and DFT-spread technique for direct-detection optical OFDM systems

    Science.gov (United States)

    Peng, Miao; Chen, Ming; Zhou, Hui; Wan, Qiuzhen; Jiang, LeYong; Yang, Lin; Zheng, Zhiwei; Chen, Lin

    2018-01-01

    High peak-to-average power ratio (PAPR) of the transmit signal is a major drawback in optical orthogonal frequency division multiplexing (OOFDM) system. In this paper, we propose and experimentally demonstrate a novel hybrid scheme, combined the Huffman coding and Discrete Fourier Transmission-Spread (DFT-spread), in order to reduce high PAPR in a 16-QAM short-reach intensity-modulated and direct-detection OOFDM (IMDD-OOFDM) system. The experimental results demonstrated that the hybrid scheme can reduce the PAPR by about 1.5, 2, 3 and 6 dB, and achieve 1.5, 1, 2.5 and 3 dB receiver sensitivity improvement compared to clipping, DFT-spread and Huffman coding and original OFDM signals, respectively, at an error vector magnitude (EVM) of -10 dB after transmission over 20 km standard single-mode fiber (SSMF). Furthermore, the throughput gain can be of the order of 30% by using the hybrid scheme compared with the cases of without applying the Huffman coding.

  6. Models of Marine Fish Biodiversity: Assessing Predictors from Three Habitat Classification Schemes.

    Science.gov (United States)

    Yates, Katherine L; Mellin, Camille; Caley, M Julian; Radford, Ben T; Meeuwig, Jessica J

    2016-01-01

    Prioritising biodiversity conservation requires knowledge of where biodiversity occurs. Such knowledge, however, is often lacking. New technologies for collecting biological and physical data coupled with advances in modelling techniques could help address these gaps and facilitate improved management outcomes. Here we examined the utility of environmental data, obtained using different methods, for developing models of both uni- and multivariate biodiversity metrics. We tested which biodiversity metrics could be predicted best and evaluated the performance of predictor variables generated from three types of habitat data: acoustic multibeam sonar imagery, predicted habitat classification, and direct observer habitat classification. We used boosted regression trees (BRT) to model metrics of fish species richness, abundance and biomass, and multivariate regression trees (MRT) to model biomass and abundance of fish functional groups. We compared model performance using different sets of predictors and estimated the relative influence of individual predictors. Models of total species richness and total abundance performed best; those developed for endemic species performed worst. Abundance models performed substantially better than corresponding biomass models. In general, BRT and MRTs developed using predicted habitat classifications performed less well than those using multibeam data. The most influential individual predictor was the abiotic categorical variable from direct observer habitat classification and models that incorporated predictors from direct observer habitat classification consistently outperformed those that did not. Our results show that while remotely sensed data can offer considerable utility for predictive modelling, the addition of direct observer habitat classification data can substantially improve model performance. Thus it appears that there are aspects of marine habitats that are important for modelling metrics of fish biodiversity that are

  7. Role of exact exchange in thermally-assisted-occupation density functional theory: A proposal of new hybrid schemes.

    Science.gov (United States)

    Chai, Jeng-Da

    2017-01-28

    We propose hybrid schemes incorporating exact exchange into thermally assisted-occupation-density functional theory (TAO-DFT) [J.-D. Chai, J. Chem. Phys. 136, 154104 (2012)] for an improved description of nonlocal exchange effects. With a few simple modifications, global and range-separated hybrid functionals in Kohn-Sham density functional theory (KS-DFT) can be combined seamlessly with TAO-DFT. In comparison with global hybrid functionals in KS-DFT, the resulting global hybrid functionals in TAO-DFT yield promising performance for systems with strong static correlation effects (e.g., the dissociation of H 2 and N 2 , twisted ethylene, and electronic properties of linear acenes), while maintaining similar performance for systems without strong static correlation effects. Besides, a reasonably accurate description of noncovalent interactions can be efficiently achieved through the inclusion of dispersion corrections in hybrid TAO-DFT. Relative to semilocal density functionals in TAO-DFT, global hybrid functionals in TAO-DFT are generally superior in performance for a wide range of applications, such as thermochemistry, kinetics, reaction energies, and optimized geometries.

  8. An Energy-Aware Hybrid ARQ Scheme with Multi-ACKs for Data Sensing Wireless Sensor Networks.

    Science.gov (United States)

    Zhang, Jinhuan; Long, Jun

    2017-06-12

    Wireless sensor networks (WSNs) are one of the important supporting technologies of edge computing. In WSNs, reliable communications are essential for most applications due to the unreliability of wireless links. In addition, network lifetime is also an important performance metric and needs to be considered in many WSN studies. In the paper, an energy-aware hybrid Automatic Repeat-reQuest protocol (ARQ) scheme is proposed to ensure energy efficiency under the guarantee of network transmission reliability. In the scheme, the source node sends data packets continuously with the correct window size and it does not need to wait for the acknowledgement (ACK) confirmation for each data packet. When the destination receives K data packets, it will return multiple copies of one ACK for confirmation to avoid ACK packet loss. The energy consumption of each node in flat circle network applying the proposed scheme is statistical analyzed and the cases under which it is more energy efficiency than the original scheme is discussed. Moreover, how to select parameters of the scheme is addressed to extend the network lifetime under the constraint of the network reliability. In addition, the energy efficiency of the proposed schemes is evaluated. Simulation results are presented to demonstrate that a node energy consumption reduction could be gained and the network lifetime is prolonged.

  9. Classification of High-Rise Residential Building Facilities: A Descriptive Survey on 170 Housing Scheme in Klang Valley

    Directory of Open Access Journals (Sweden)

    Abd Wahab Siti Rashidah Hanum

    2016-01-01

    Full Text Available High-rise residential building is a type of housing that has multi-dwelling units built on the same land. This type of housing has become popular each year in urban area due to the increasing cost of land. There are several common facilities provided in high-rise residential building. For example playground, swimming pool, gymnasium, 24 hours security system such as CCTV, access card and so on. Thus, maintenance works of the common facilities must be well organised. The purpose of this paper is to identify the classification of facilities provided at high rise residential building. The survey was done on 170 high-rise residential schemes by using stratified random sampling technique. The scope of this research is within Klang Valley area. This area is rapidly developed with high-rise residential building. The objective of this survey is to list down all the facilities provided in each sample of the schemes. The result, there are nine classification of facilities provided for high-rise residential building.

  10. Review and comparison study of hybrid diesel/solar/hydro/fuel cell energy schemes for a rural ICT Telecenter

    Energy Technology Data Exchange (ETDEWEB)

    Abdullah, M.O.; Yung, V.C.; Anyi, M.; Othman, A.K.; Ab. Hamid, K.B. [Universiti Malaysia Sarawak (UNIMAS), 94300 Kota Samarahan, Sarawak (Malaysia); Tarawe, J. [e-Bario ICT Telecenter, Bario, Sarawak (Malaysia)

    2010-02-15

    In this paper, the rural electrification study of an ICT Telecenter in particular reference to the Kelabit Highland of Sarawak is presented. The use of diesel generator and its associated environmental implications is first discussed. The cost-effectiveness of the present solar PV system and the solar/hydro schemes for rural electrification of the rural ICT are evaluated employing the HOMER simulation software, considering sustainability factors such as system efficiency, weather, fuel costs, operating and maintaining costs. Subsequently, simple novel Hybrid Energy Performance Equations and the associated Energy Performance Curves are derived and introduced, respectively, which provide a visualization model, simplifying hybrid system analysis. Results obtained in this study have shown that combined power schemes is more sustainable in terms of supplying electricity to the Telecenter compared to a stand-alone PV system due to prolong cloudy and dense haze periods. The hybrid systems can have efficiency range of {proportional_to}15%-75% compared to PV stand-alone of only {proportional_to}10%, indicating hybrid systems are more reliable and sustainable - in minimizing both energy losses and excess energy. (author)

  11. A hybrid sales forecasting scheme by combining independent component analysis with K-means clustering and support vector regression.

    Science.gov (United States)

    Lu, Chi-Jie; Chang, Chi-Chang

    2014-01-01

    Sales forecasting plays an important role in operating a business since it can be used to determine the required inventory level to meet consumer demand and avoid the problem of under/overstocking. Improving the accuracy of sales forecasting has become an important issue of operating a business. This study proposes a hybrid sales forecasting scheme by combining independent component analysis (ICA) with K-means clustering and support vector regression (SVR). The proposed scheme first uses the ICA to extract hidden information from the observed sales data. The extracted features are then applied to K-means algorithm for clustering the sales data into several disjoined clusters. Finally, the SVR forecasting models are applied to each group to generate final forecasting results. Experimental results from information technology (IT) product agent sales data reveal that the proposed sales forecasting scheme outperforms the three comparison models and hence provides an efficient alternative for sales forecasting.

  12. History of demand side management and classification of demand response control schemes

    NARCIS (Netherlands)

    Lampropoulos, I.; Kling, W.L.; Ribeiro, P.F.; Berg, van den J.

    2013-01-01

    The scope of this paper is to provide a review on the topic of demand side management. A historical overview provides a critical insight to applied cases, while the discovery of new evidence calls for reconsideration of the design of demand response control schemes. The developments at the demand

  13. Churn prediction on huge telecom data using hybrid firefly based classification

    Directory of Open Access Journals (Sweden)

    Ammar A.Q. Ahmed

    2017-11-01

    Full Text Available Churn prediction in telecom has become a major requirement due to the increase in the number of telecom providers. However due to the hugeness, sparsity and imbalanced nature of the data, churn prediction in telecom has always been a complex task. This paper presents a metaheuristic based churn prediction technique that performs churn prediction on huge telecom data. A hybridized form of Firefly algorithm is used as the classifier. It has been identified that the compute intensive component of the Firefly algorithm is the comparison block, where every firefly is compared with every other firefly to identify the one with the highest light intensity. This component is replaced by Simulated Annealing and the classification process is carried out. Experiments were conducted on the Orange dataset. It was observed that Firefly algorithm works best on churn data and the hybridized Firefly algorithm provides effective and faster results.

  14. Wittgenstein's philosophy and a dimensional approach to the classification of mental disorders -- a preliminary scheme.

    Science.gov (United States)

    Mackinejad, Kioumars; Sharifi, Vandad

    2006-01-01

    In this paper the importance of Wittgenstein's philosophical ideas for the justification of a dimensional approach to the classification of mental disorders is discussed. Some of his basic concepts in his Philosophical Investigations, such as 'family resemblances', 'grammar' and 'language-game' and their relations to the concept of mental disorder are explored.

  15. Liquid contrabands classification based on energy dispersive X-ray diffraction and hybrid discriminant analysis

    International Nuclear Information System (INIS)

    YangDai, Tianyi; Zhang, Li

    2016-01-01

    Energy dispersive X-ray diffraction (EDXRD) combined with hybrid discriminant analysis (HDA) has been utilized for classifying the liquid materials for the first time. The XRD spectra of 37 kinds of liquid contrabands and daily supplies were obtained using an EDXRD test bed facility. The unique spectra of different samples reveal XRD's capability to distinguish liquid contrabands from daily supplies. In order to create a system to detect liquid contrabands, the diffraction spectra were subjected to HDA which is the combination of principal components analysis (PCA) and linear discriminant analysis (LDA). Experiments based on the leave-one-out method demonstrate that HDA is a practical method with higher classification accuracy and lower noise sensitivity than the other methods in this application. The study shows the great capability and potential of the combination of XRD and HDA for liquid contrabands classification.

  16. Liquid contrabands classification based on energy dispersive X-ray diffraction and hybrid discriminant analysis

    Energy Technology Data Exchange (ETDEWEB)

    YangDai, Tianyi [Department of Engineering Physics, Tsinghua University, Beijing 100084 (China); Key Laboratory of Particle & Radiation Imaging (Tsinghua University), Ministry of Education (China); Zhang, Li, E-mail: zhangli@nuctech.com [Department of Engineering Physics, Tsinghua University, Beijing 100084 (China); Key Laboratory of Particle & Radiation Imaging (Tsinghua University), Ministry of Education (China)

    2016-02-01

    Energy dispersive X-ray diffraction (EDXRD) combined with hybrid discriminant analysis (HDA) has been utilized for classifying the liquid materials for the first time. The XRD spectra of 37 kinds of liquid contrabands and daily supplies were obtained using an EDXRD test bed facility. The unique spectra of different samples reveal XRD's capability to distinguish liquid contrabands from daily supplies. In order to create a system to detect liquid contrabands, the diffraction spectra were subjected to HDA which is the combination of principal components analysis (PCA) and linear discriminant analysis (LDA). Experiments based on the leave-one-out method demonstrate that HDA is a practical method with higher classification accuracy and lower noise sensitivity than the other methods in this application. The study shows the great capability and potential of the combination of XRD and HDA for liquid contrabands classification.

  17. Liquid contrabands classification based on energy dispersive X-ray diffraction and hybrid discriminant analysis

    Science.gov (United States)

    YangDai, Tianyi; Zhang, Li

    2016-02-01

    Energy dispersive X-ray diffraction (EDXRD) combined with hybrid discriminant analysis (HDA) has been utilized for classifying the liquid materials for the first time. The XRD spectra of 37 kinds of liquid contrabands and daily supplies were obtained using an EDXRD test bed facility. The unique spectra of different samples reveal XRD's capability to distinguish liquid contrabands from daily supplies. In order to create a system to detect liquid contrabands, the diffraction spectra were subjected to HDA which is the combination of principal components analysis (PCA) and linear discriminant analysis (LDA). Experiments based on the leave-one-out method demonstrate that HDA is a practical method with higher classification accuracy and lower noise sensitivity than the other methods in this application. The study shows the great capability and potential of the combination of XRD and HDA for liquid contrabands classification.

  18. Solution of the transport equation in stationary state and X Y geometry, using continuous and discontinuous hybrid nodal schemes

    International Nuclear Information System (INIS)

    Xolocostli M, V.; Valle G, E. del; Alonso V, G.

    2003-01-01

    In this work it is described the development and the application of the NH-FEM schemes, Hybrid Nodal schemes using the Finite Element method in the solution of the neutron transport equation in stationary state and X Y geometry, of which two families of schemes were developed, one of which corresponds to the continuous and the other to the discontinuous ones, inside those first its are had the Bi-Quadratic Bi Q, and to the Bi-cubic BiC, while for the seconds the Discontinuous Bi-lineal DBiL and the Discontinuous Bi-quadratic DBiQ. These schemes were implemented in a program to which was denominated TNHXY, Transport of neutrons with Hybrid Nodal schemes in X Y geometry. One of the immediate applications of the schemes NH-FEM it will be in the analysis of assemblies of nuclear fuel, particularly of the BWR type. The validation of the TNHXY program was made with two test problems or benchmark, already solved by other authors with numerical techniques and to compare results. The first of them consists in an it BWR fuel assemble in an arrangement 7x7 without rod and with control rod providing numerical results. The second is a fuel assemble of mixed oxides (MOX) in an arrangement 10x10. This last problem it is known as the Benchmark problem WPPR of the NEA Data Bank and the results are compared with those of other commercial codes as HELIOS, MCNP-4B and CPM-3. (Author)

  19. A proposed radiographic classification scheme for congenital thoracic vertebral malformations in brachycephalic "screw-tailed" dog breeds.

    Science.gov (United States)

    Gutierrez-Quintana, Rodrigo; Guevar, Julien; Stalin, Catherine; Faller, Kiterie; Yeamans, Carmen; Penderis, Jacques

    2014-01-01

    Congenital vertebral malformations are common in brachycephalic "screw-tailed" dog breeds such as French bulldogs, English bulldogs, Boston terriers, and pugs. The aim of this retrospective study was to determine whether a radiographic classification scheme developed for use in humans would be feasible for use in these dog breeds. Inclusion criteria were hospital admission between September 2009 and April 2013, neurologic examination findings available, diagnostic quality lateral and ventro-dorsal digital radiographs of the thoracic vertebral column, and at least one congenital vertebral malformation. Radiographs were retrieved and interpreted by two observers who were unaware of neurologic status. Vertebral malformations were classified based on a classification scheme modified from a previous human study and a consensus of both observers. Twenty-eight dogs met inclusion criteria (12 with neurologic deficits, 16 with no neurologic deficits). Congenital vertebral malformations affected 85/362 (23.5%) of thoracic vertebrae. Vertebral body formation defects were the most common (butterfly vertebrae 6.6%, ventral wedge-shaped vertebrae 5.5%, dorsal hemivertebrae 0.8%, and dorso-lateral hemivertebrae 0.5%). No lateral hemivertebrae or lateral wedge-shaped vertebrae were identified. The T7 vertebra was the most commonly affected (11/28 dogs), followed by T8 (8/28 dogs) and T12 (8/28 dogs). The number and type of vertebral malformations differed between groups (P = 0.01). Based on MRI, dorsal, and dorso-lateral hemivertebrae were the cause of spinal cord compression in 5/12 (41.6%) of dogs with neurologic deficits. Findings indicated that a modified human radiographic classification system of vertebral malformations is feasible for use in future studies of brachycephalic "screw-tailed" dogs. © 2014 American College of Veterinary Radiology.

  20. A Hybrid Single-Carrier/Multicarrier Transmission Scheme with Power Allocation

    Directory of Open Access Journals (Sweden)

    Luc Féty

    2007-11-01

    Full Text Available We propose a flexible transmission scheme which easily allows to switch between cyclic-prefixed single-carrier (CP-SC and cyclic-prefixed multicarrier (CP-MC transmissions. This scheme takes advantage of the best characteristic of each scheme, namely, the low peak-to-average power ratio (PAPR of the CP-SC scheme and the robustness to channel selectivity of the CP-MC scheme. Moreover, we derive the optimum power allocation for the CP-SC transmission considering a zero-forcing (ZF and a minimum mean-square error (MMSE receiver. By taking the PAPR into account, we are able to make a better analysis of the overall system and the results show the advantage of the CP-SC-MMSE scheme for flat and mild selective channels due to their low PAPR and that the CP-MC scheme is more advantageous for a narrow range of channels with severe selectivity.

  1. Using two classification schemes to develop vegetation indices of biological integrity for wetlands in West Virginia, USA.

    Science.gov (United States)

    Veselka, Walter; Rentch, James S; Grafton, William N; Kordek, Walter S; Anderson, James T

    2010-11-01

    Bioassessment methods for wetlands, and other bodies of water, have been developed worldwide to measure and quantify changes in "biological integrity." These assessments are based on a classification system, meant to ensure appropriate comparisons between wetland types. Using a local site-specific disturbance gradient, we built vegetation indices of biological integrity (Veg-IBIs) based on two commonly used wetland classification systems in the USA: One based on vegetative structure and the other based on a wetland's position in a landscape and sources of water. The resulting class-specific Veg-IBIs were comprised of 1-5 metrics that varied in their sensitivity to the disturbance gradient (R2=0.14-0.65). Moreover, the sensitivity to the disturbance gradient increased as metrics from each of the two classification schemes were combined (added). Using this information to monitor natural and created wetlands will help natural resource managers track changes in biological integrity of wetlands in response to anthropogenic disturbance and allows the use of vegetative communities to set ecological performance standards for mitigation banks.

  2. Towards the creation of a flexible classification scheme for voluntarily reported transfusion and laboratory safety events.

    Science.gov (United States)

    Whitehurst, Julie M; Schroder, John; Leonard, Dave; Horvath, Monica M; Cozart, Heidi; Ferranti, Jeffrey

    2012-05-18

    Transfusion and clinical laboratory services are high-volume activities involving complicated workflows across both ambulatory and inpatient environments. As a result, there are many opportunities for safety lapses, leading to patient harm and increased costs. Organizational techniques such as voluntary safety event reporting are commonly used to identify and prioritize risk areas across care settings. Creation of functional, standardized safety data structures that facilitate effective exploratory examination is therefore essential to drive quality improvement interventions. Unfortunately, voluntarily reported adverse event data can often be unstructured or ambiguously defined. To address this problem, we sought to create a "best-of-breed" patient safety classification for data contained in the Duke University Health System Safety Reporting System (SRS). Our approach was to implement the internationally recognized World Health Organization International Classification for Patient Safety Framework, supplemented with additional data points relevant to our organization. Data selection and integration into the hierarchical framework is discussed, as well as placement of the classification into the SRS. We evaluated the impact of the new SRS classification on system usage through comparisons of monthly average report rates and completion times before and after implementation. Monthly average inpatient transfusion reports decreased from 102.1 ± 14.3 to 91.6 ± 11.2, with the proportion of transfusion reports in our system remaining consistent before and after implementation. Monthly average transfusion report rates in the outpatient and homecare environments were not significantly different. Significant increases in clinical lab report rates were present across inpatient and outpatient environments, with the proportion of lab reports increasing after implementation. Report completion times increased modestly but not significantly from a practical standpoint. A

  3. A classification scheme of erroneous behaviors for human error probability estimations based on simulator data

    International Nuclear Information System (INIS)

    Kim, Yochan; Park, Jinkyun; Jung, Wondea

    2017-01-01

    Because it has been indicated that empirical data supporting the estimates used in human reliability analysis (HRA) is insufficient, several databases have been constructed recently. To generate quantitative estimates from human reliability data, it is important to appropriately sort the erroneous behaviors found in the reliability data. Therefore, this paper proposes a scheme to classify the erroneous behaviors identified by the HuREX (Human Reliability data Extraction) framework through a review of the relevant literature. A case study of the human error probability (HEP) calculations is conducted to verify that the proposed scheme can be successfully implemented for the categorization of the erroneous behaviors and to assess whether the scheme is useful for the HEP quantification purposes. Although continuously accumulating and analyzing simulator data is desirable to secure more reliable HEPs, the resulting HEPs were insightful in several important ways with regard to human reliability in off-normal conditions. From the findings of the literature review and the case study, the potential and limitations of the proposed method are discussed. - Highlights: • A taxonomy of erroneous behaviors is proposed to estimate HEPs from a database. • The cognitive models, procedures, HRA methods, and HRA databases were reviewed. • HEPs for several types of erroneous behaviors are calculated as a case study.

  4. PARALLEL IMPLEMENTATION OF MORPHOLOGICAL PROFILE BASED SPECTRAL-SPATIAL CLASSIFICATION SCHEME FOR HYPERSPECTRAL IMAGERY

    Directory of Open Access Journals (Sweden)

    B. Kumar

    2016-06-01

    Full Text Available Extended morphological profile (EMP is a good technique for extracting spectral-spatial information from the images but large size of hyperspectral images is an important concern for creating EMPs. However, with the availability of modern multi-core processors and commodity parallel processing systems like graphics processing units (GPUs at desktop level, parallel computing provides a viable option to significantly accelerate execution of such computations. In this paper, parallel implementation of an EMP based spectralspatial classification method for hyperspectral imagery is presented. The parallel implementation is done both on multi-core CPU and GPU. The impact of parallelization on speed up and classification accuracy is analyzed. For GPU, the implementation is done in compute unified device architecture (CUDA C. The experiments are carried out on two well-known hyperspectral images. It is observed from the experimental results that GPU implementation provides a speed up of about 7 times, while parallel implementation on multi-core CPU resulted in speed up of about 3 times. It is also observed that parallel implementation has no adverse impact on the classification accuracy.

  5. Automated classification of tropical shrub species: a hybrid of leaf shape and machine learning approach

    Directory of Open Access Journals (Sweden)

    Miraemiliana Murat

    2017-09-01

    Full Text Available Plants play a crucial role in foodstuff, medicine, industry, and environmental protection. The skill of recognising plants is very important in some applications, including conservation of endangered species and rehabilitation of lands after mining activities. However, it is a difficult task to identify plant species because it requires specialized knowledge. Developing an automated classification system for plant species is necessary and valuable since it can help specialists as well as the public in identifying plant species easily. Shape descriptors were applied on the myDAUN dataset that contains 45 tropical shrub species collected from the University of Malaya (UM, Malaysia. Based on literature review, this is the first study in the development of tropical shrub species image dataset and classification using a hybrid of leaf shape and machine learning approach. Four types of shape descriptors were used in this study namely morphological shape descriptors (MSD, Histogram of Oriented Gradients (HOG, Hu invariant moments (Hu and Zernike moments (ZM. Single descriptor, as well as the combination of hybrid descriptors were tested and compared. The tropical shrub species are classified using six different classifiers, which are artificial neural network (ANN, random forest (RF, support vector machine (SVM, k-nearest neighbour (k-NN, linear discriminant analysis (LDA and directed acyclic graph multiclass least squares twin support vector machine (DAG MLSTSVM. In addition, three types of feature selection methods were tested in the myDAUN dataset, Relief, Correlation-based feature selection (CFS and Pearson’s coefficient correlation (PCC. The well-known Flavia dataset and Swedish Leaf dataset were used as the validation dataset on the proposed methods. The results showed that the hybrid of all descriptors of ANN outperformed the other classifiers with an average classification accuracy of 98.23% for the myDAUN dataset, 95.25% for the Flavia

  6. A Hybrid Optimization Framework with POD-based Order Reduction and Design-Space Evolution Scheme

    Science.gov (United States)

    Ghoman, Satyajit S.

    The main objective of this research is to develop an innovative multi-fidelity multi-disciplinary design, analysis and optimization suite that integrates certain solution generation codes and newly developed innovative tools to improve the overall optimization process. The research performed herein is divided into two parts: (1) the development of an MDAO framework by integration of variable fidelity physics-based computational codes, and (2) enhancements to such a framework by incorporating innovative features extending its robustness. The first part of this dissertation describes the development of a conceptual Multi-Fidelity Multi-Strategy and Multi-Disciplinary Design Optimization Environment (M3 DOE), in context of aircraft wing optimization. M 3 DOE provides the user a capability to optimize configurations with a choice of (i) the level of fidelity desired, (ii) the use of a single-step or multi-step optimization strategy, and (iii) combination of a series of structural and aerodynamic analyses. The modularity of M3 DOE allows it to be a part of other inclusive optimization frameworks. The M 3 DOE is demonstrated within the context of shape and sizing optimization of the wing of a Generic Business Jet aircraft. Two different optimization objectives, viz. dry weight minimization, and cruise range maximization are studied by conducting one low-fidelity and two high-fidelity optimization runs to demonstrate the application scope of M3 DOE. The second part of this dissertation describes the development of an innovative hybrid optimization framework that extends the robustness of M 3 DOE by employing a proper orthogonal decomposition-based design-space order reduction scheme combined with the evolutionary algorithm technique. The POD method of extracting dominant modes from an ensemble of candidate configurations is used for the design-space order reduction. The snapshot of candidate population is updated iteratively using evolutionary algorithm technique of

  7. Fission--fusion systems: classification and critique

    International Nuclear Information System (INIS)

    Lidsky, L.M.

    1974-01-01

    A useful classification scheme for hybrid systems is described and some common features that the scheme makes apparent are pointed out. The early history of fusion-fission systems is reviewed. Some designs are described along with advantages and disadvantages of each. The extension to low and moderate Q devices is noted. (U.S.)

  8. Clinical presentation and outcome prediction of clinical, serological, and histopathological classification schemes in ANCA-associated vasculitis with renal involvement.

    Science.gov (United States)

    Córdova-Sánchez, Bertha M; Mejía-Vilet, Juan M; Morales-Buenrostro, Luis E; Loyola-Rodríguez, Georgina; Uribe-Uribe, Norma O; Correa-Rotter, Ricardo

    2016-07-01

    Several classification schemes have been developed for anti-neutrophil cytoplasmic antibody (ANCA)-associated vasculitis (AAV), with actual debate focusing on their clinical and prognostic performance. Sixty-two patients with renal biopsy-proven AAV from a single center in Mexico City diagnosed between 2004 and 2013 were analyzed and classified under clinical (granulomatosis with polyangiitis [GPA], microscopic polyangiitis [MPA], renal limited vasculitis [RLV]), serological (proteinase 3 anti-neutrophil cytoplasmic antibodies [PR3-ANCA], myeloperoxidase anti-neutrophil cytoplasmic antibodies [MPO-ANCA], ANCA negative), and histopathological (focal, crescenteric, mixed-type, sclerosing) categories. Clinical presentation parameters were compared at baseline between classification groups, and the predictive value of different classification categories for disease and renal remission, relapse, renal, and patient survival was analyzed. Serological classification predicted relapse rate (PR3-ANCA hazard ratio for relapse 2.93, 1.20-7.17, p = 0.019). There were no differences in disease or renal remission, renal, or patient survival between clinical and serological categories. Histopathological classification predicted response to therapy, with a poorer renal remission rate for sclerosing group and those with less than 25 % normal glomeruli; in addition, it adequately delimited 24-month glomerular filtration rate (eGFR) evolution, but it did not predict renal nor patient survival. On multivariate models, renal replacement therapy (RRT) requirement (HR 8.07, CI 1.75-37.4, p = 0.008) and proteinuria (HR 1.49, CI 1.03-2.14, p = 0.034) at presentation predicted renal survival, while age (HR 1.10, CI 1.01-1.21, p = 0.041) and infective events during the induction phase (HR 4.72, 1.01-22.1, p = 0.049) negatively influenced patient survival. At present, ANCA-based serological classification may predict AAV relapses, but neither clinical nor serological

  9. Development of a classification scheme for disease-related enzyme information

    Directory of Open Access Journals (Sweden)

    Söhngen Carola

    2011-08-01

    Full Text Available Abstract Background BRENDA (BRaunschweig ENzyme DAtabase, http://www.brenda-enzymes.org is a major resource for enzyme related information. First and foremost, it provides data which are manually curated from the primary literature. DRENDA (Disease RElated ENzyme information DAtabase complements BRENDA with a focus on the automatic search and categorization of enzyme and disease related information from title and abstracts of primary publications. In a two-step procedure DRENDA makes use of text mining and machine learning methods. Results Currently enzyme and disease related references are biannually updated as part of the standard BRENDA update. 910,897 relations of EC-numbers and diseases were extracted from titles or abstracts and are included in the second release in 2010. The enzyme and disease entity recognition has been successfully enhanced by a further relation classification via machine learning. The classification step has been evaluated by a 5-fold cross validation and achieves an F1 score between 0.802 ± 0.032 and 0.738 ± 0.033 depending on the categories and pre-processing procedures. In the eventual DRENDA content every category reaches a classification specificity of at least 96.7% and a precision that ranges from 86-98% in the highest confidence level, and 64-83% for the smallest confidence level associated with higher recall. Conclusions The DRENDA processing chain analyses PubMed, locates references with disease-related information on enzymes and categorises their focus according to the categories causal interaction, therapeutic application, diagnostic usage and ongoing research. The categorisation gives an impression on the focus of the located references. Thus, the relation categorisation can facilitate orientation within the rapidly growing number of references with impact on diseases and enzymes. The DRENDA information is available as additional information in BRENDA.

  10. Improved Wetland Classification Using Eight-Band High Resolution Satellite Imagery and a Hybrid Approach

    Directory of Open Access Journals (Sweden)

    Charles R. Lane

    2014-12-01

    Full Text Available Although remote sensing technology has long been used in wetland inventory and monitoring, the accuracy and detail level of wetland maps derived with moderate resolution imagery and traditional techniques have been limited and often unsatisfactory. We explored and evaluated the utility of a newly launched high-resolution, eight-band satellite system (Worldview-2; WV2 for identifying and classifying freshwater deltaic wetland vegetation and aquatic habitats in the Selenga River Delta of Lake Baikal, Russia, using a hybrid approach and a novel application of Indicator Species Analysis (ISA. We achieved an overall classification accuracy of 86.5% (Kappa coefficient: 0.85 for 22 classes of aquatic and wetland habitats and found that additional metrics, such as the Normalized Difference Vegetation Index and image texture, were valuable for improving the overall classification accuracy and particularly for discriminating among certain habitat classes. Our analysis demonstrated that including WV2’s four spectral bands from parts of the spectrum less commonly used in remote sensing analyses, along with the more traditional bandwidths, contributed to the increase in the overall classification accuracy by ~4% overall, but with considerable increases in our ability to discriminate certain communities. The coastal band improved differentiating open water and aquatic (i.e., vegetated habitats, and the yellow, red-edge, and near-infrared 2 bands improved discrimination among different vegetated aquatic and terrestrial habitats. The use of ISA provided statistical rigor in developing associations between spectral classes and field-based data. Our analyses demonstrated the utility of a hybrid approach and the benefit of additional bands and metrics in providing the first spatially explicit mapping of a large and heterogeneous wetland system.

  11. The Hybrid of Classification Tree and Extreme Learning Machine for Permeability Prediction in Oil Reservoir

    KAUST Repository

    Prasetyo Utomo, Chandra

    2011-06-01

    Permeability is an important parameter connected with oil reservoir. Predicting the permeability could save millions of dollars. Unfortunately, petroleum engineers have faced numerous challenges arriving at cost-efficient predictions. Much work has been carried out to solve this problem. The main challenge is to handle the high range of permeability in each reservoir. For about a hundred year, mathematicians and engineers have tried to deliver best prediction models. However, none of them have produced satisfying results. In the last two decades, artificial intelligence models have been used. The current best prediction model in permeability prediction is extreme learning machine (ELM). It produces fairly good results but a clear explanation of the model is hard to come by because it is so complex. The aim of this research is to propose a way out of this complexity through the design of a hybrid intelligent model. In this proposal, the system combines classification and regression models to predict the permeability value. These are based on the well logs data. In order to handle the high range of the permeability value, a classification tree is utilized. A benefit of this innovation is that the tree represents knowledge in a clear and succinct fashion and thereby avoids the complexity of all previous models. Finally, it is important to note that the ELM is used as a final predictor. Results demonstrate that this proposed hybrid model performs better when compared with support vector machines (SVM) and ELM in term of correlation coefficient. Moreover, the classification tree model potentially leads to better communication among petroleum engineers concerning this important process and has wider implications for oil reservoir management efficiency.

  12. A Hybrid Multiobjective Differential Evolution Algorithm and Its Application to the Optimization of Grinding and Classification

    Directory of Open Access Journals (Sweden)

    Yalin Wang

    2013-01-01

    Full Text Available The grinding-classification is the prerequisite process for full recovery of the nonrenewable minerals with both production quality and quantity objectives concerned. Its natural formulation is a constrained multiobjective optimization problem of complex expression since the process is composed of one grinding machine and two classification machines. In this paper, a hybrid differential evolution (DE algorithm with multi-population is proposed. Some infeasible solutions with better performance are allowed to be saved, and they participate randomly in the evolution. In order to exploit the meaningful infeasible solutions, a functionally partitioned multi-population mechanism is designed to find an optimal solution from all possible directions. Meanwhile, a simplex method for local search is inserted into the evolution process to enhance the searching strategy in the optimization process. Simulation results from the test of some benchmark problems indicate that the proposed algorithm tends to converge quickly and effectively to the Pareto frontier with better distribution. Finally, the proposed algorithm is applied to solve a multiobjective optimization model of a grinding and classification process. Based on the technique for order performance by similarity to ideal solution (TOPSIS, the satisfactory solution is obtained by using a decision-making method for multiple attributes.

  13. Three hybridization models based on local search scheme for job shop scheduling problem

    Science.gov (United States)

    Balbi Fraga, Tatiana

    2015-05-01

    This work presents three different hybridization models based on the general schema of Local Search Heuristics, named Hybrid Successive Application, Hybrid Neighborhood, and Hybrid Improved Neighborhood. Despite similar approaches might have already been presented in the literature in other contexts, in this work these models are applied to analyzes the solution of the job shop scheduling problem, with the heuristics Taboo Search and Particle Swarm Optimization. Besides, we investigate some aspects that must be considered in order to achieve better solutions than those obtained by the original heuristics. The results demonstrate that the algorithms derived from these three hybrid models are more robust than the original algorithms and able to get better results than those found by the single Taboo Search.

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

    OpenAIRE

    Hong, Keum-Shik; Khan, Muhammad Jawad

    2017-01-01

    In this article, non-invasive hybrid brain–computer interface (hBCI) technologies for improving classification accuracy and increasing the number of commands are reviewed. Hybridization combining more than two modalities is a new trend in brain imaging and prosthesis control. Electroencephalography (EEG), due to its easy use and fast temporal resolution, is most widely utilized in combination with other brain/non-brain signal acquisition modalities, for instance, functional near infrared spec...

  15. A new classification scheme of European cold-water coral habitats: Implications for ecosystem-based management of the deep sea

    Science.gov (United States)

    Davies, J. S.; Guillaumont, B.; Tempera, F.; Vertino, A.; Beuck, L.; Ólafsdóttir, S. H.; Smith, C. J.; Fosså, J. H.; van den Beld, I. M. J.; Savini, A.; Rengstorf, A.; Bayle, C.; Bourillet, J.-F.; Arnaud-Haond, S.; Grehan, A.

    2017-11-01

    Cold-water corals (CWC) can form complex structures which provide refuge, nursery grounds and physical support for a diversity of other living organisms. However, irrespectively from such ecological significance, CWCs are still vulnerable to human pressures such as fishing, pollution, ocean acidification and global warming Providing coherent and representative conservation of vulnerable marine ecosystems including CWCs is one of the aims of the Marine Protected Areas networks being implemented across European seas and oceans under the EC Habitats Directive, the Marine Strategy Framework Directive and the OSPAR Convention. In order to adequately represent ecosystem diversity, these initiatives require a standardised habitat classification that organises the variety of biological assemblages and provides consistent and functional criteria to map them across European Seas. One such classification system, EUNIS, enables a broad level classification of the deep sea based on abiotic and geomorphological features. More detailed lower biotope-related levels are currently under-developed, particularly with regards to deep-water habitats (>200 m depth). This paper proposes a hierarchical CWC biotope classification scheme that could be incorporated by existing classification schemes such as EUNIS. The scheme was developed within the EU FP7 project CoralFISH to capture the variability of CWC habitats identified using a wealth of seafloor imagery datasets from across the Northeast Atlantic and Mediterranean. Depending on the resolution of the imagery being interpreted, this hierarchical scheme allows data to be recorded from broad CWC biotope categories down to detailed taxonomy-based levels, thereby providing a flexible yet valuable information level for management. The CWC biotope classification scheme identifies 81 biotopes and highlights the limitations of the classification framework and guidance provided by EUNIS, the EC Habitats Directive, OSPAR and FAO; which largely

  16. Prototype-based Models for the Supervised Learning of Classification Schemes

    Science.gov (United States)

    Biehl, Michael; Hammer, Barbara; Villmann, Thomas

    2017-06-01

    An introduction is given to the use of prototype-based models in supervised machine learning. The main concept of the framework is to represent previously observed data in terms of so-called prototypes, which reflect typical properties of the data. Together with a suitable, discriminative distance or dissimilarity measure, prototypes can be used for the classification of complex, possibly high-dimensional data. We illustrate the framework in terms of the popular Learning Vector Quantization (LVQ). Most frequently, standard Euclidean distance is employed as a distance measure. We discuss how LVQ can be equipped with more general dissimilarites. Moreover, we introduce relevance learning as a tool for the data-driven optimization of parameterized distances.

  17. Brightness-preserving fuzzy contrast enhancement scheme for the detection and classification of diabetic retinopathy disease.

    Science.gov (United States)

    Datta, Niladri Sekhar; Dutta, Himadri Sekhar; Majumder, Koushik

    2016-01-01

    The contrast enhancement of retinal image plays a vital role for the detection of microaneurysms (MAs), which are an early sign of diabetic retinopathy disease. A retinal image contrast enhancement method has been presented to improve the MA detection technique. The success rate on low-contrast noisy retinal image analysis shows the importance of the proposed method. Overall, 587 retinal input images are tested for performance analysis. The average sensitivity and specificity are obtained as 95.94% and 99.21%, respectively. The area under curve is found as 0.932 for the receiver operating characteristics analysis. The classifications of diabetic retinopathy disease are also performed here. The experimental results show that the overall MA detection method performs better than the current state-of-the-art MA detection algorithms.

  18. WekaPyScript: Classification, Regression, and Filter Schemes for WEKA Implemented in Python

    Directory of Open Access Journals (Sweden)

    Christopher Beckham

    2016-08-01

    Full Text Available WekaPyScript is a package for the machine learning software WEKA that allows learning algorithms and preprocessing methods for classification and regression to be written in Python, as opposed to WEKA’s implementation language, Java. This opens up WEKA to its machine learning and scientific computing ecosystem. Furthermore, due to Python’s minimalist syntax, learning algorithms and preprocessing methods can be prototyped easily and utilised from within WEKA. WekaPyScript works by running a local Python server using the host’s installation of Python; as a result, any libraries installed in the host installation can be leveraged when writing a script for WekaPyScript. Three example scripts (two learning algorithms and one preprocessing method are presented.

  19. A Repetitive Control Scheme Aimed at Compensating the 6k + 1 Harmonics for a Three-Phase Hybrid Active Filter

    DEFF Research Database (Denmark)

    Luo, Zhaoxu; Su, Mei; Yang, Jian

    2016-01-01

    these disadvantages, many repetitive controllers with reduced delay time have been proposed, which can selectively compensate the odd harmonics or 6k±1 harmonics with delay time reduced to T0/2 and T0/3,repectively. To further study in this area, this paper proposes an improved repetitive scheme implemented...... in stationary reference frame, which only compensates the 6k+1 harmonics (e.g. -5, +7, -11, +13) in three-phase systems and reduces the time delay to T0/6 . So compared with the earlier reduced delay time repetitive controllers, the robustness and transient performance is further improved, the waste of control...... effort is reduced, and the possibility of amplifying and even injecting any harmonic noises into system is avoided to the greatest extent. Moreover, the proposed repetitive scheme is used in the control of a three-phase hybrid active power filter. The experimental results validate the effectiveness...

  20. A new approach to develop computer-aided diagnosis scheme of breast mass classification using deep learning technology.

    Science.gov (United States)

    Qiu, Yuchen; Yan, Shiju; Gundreddy, Rohith Reddy; Wang, Yunzhi; Cheng, Samuel; Liu, Hong; Zheng, Bin

    2017-01-01

    To develop and test a deep learning based computer-aided diagnosis (CAD) scheme of mammograms for classifying between malignant and benign masses. An image dataset involving 560 regions of interest (ROIs) extracted from digital mammograms was used. After down-sampling each ROI from 512×512 to 64×64 pixel size, we applied an 8 layer deep learning network that involves 3 pairs of convolution-max-pooling layers for automatic feature extraction and a multiple layer perceptron (MLP) classifier for feature categorization to process ROIs. The 3 pairs of convolution layers contain 20, 10, and 5 feature maps, respectively. Each convolution layer is connected with a max-pooling layer to improve the feature robustness. The output of the sixth layer is fully connected with a MLP classifier, which is composed of one hidden layer and one logistic regression layer. The network then generates a classification score to predict the likelihood of ROI depicting a malignant mass. A four-fold cross validation method was applied to train and test this deep learning network. The results revealed that this CAD scheme yields an area under the receiver operation characteristic curve (AUC) of 0.696±0.044, 0.802±0.037, 0.836±0.036, and 0.822±0.035 for fold 1 to 4 testing datasets, respectively. The overall AUC of the entire dataset is 0.790±0.019. This study demonstrates the feasibility of applying a deep learning based CAD scheme to classify between malignant and benign breast masses without a lesion segmentation, image feature computation and selection process.

  1. A New Approach to Develop Computer-aided Diagnosis Scheme of Breast Mass Classification Using Deep Learning Technology

    Science.gov (United States)

    Qiu, Yuchen; Yan, Shiju; Gundreddy, Rohith Reddy; Wang, Yunzhi; Cheng, Samuel; Liu, Hong; Zheng, Bin

    2017-01-01

    PURPOSE To develop and test a deep learning based computer-aided diagnosis (CAD) scheme of mammograms for classifying between malignant and benign masses. METHODS An image dataset involving 560 regions of interest (ROIs) extracted from digital mammograms was used. After down-sampling each ROI from 512×512 to 64×64 pixel size, we applied an 8 layer deep learning network that involves 3 pairs of convolution-max-pooling layers for automatic feature extraction and a multiple layer perceptron (MLP) classifier for feature categorization to process ROIs. The 3 pairs of convolution layers contain 20, 10, and 5 feature maps, respectively. Each convolution layer is connected with a max-pooling layer to improve the feature robustness. The output of the sixth layer is fully connected with a MLP classifier, which is composed of one hidden layer and one logistic regression layer. The network then generates a classification score to predict the likelihood of ROI depicting a malignant mass. A four-fold cross validation method was applied to train and test this deep learning network. RESULTS The results revealed that this CAD scheme yields an area under the receiver operation characteristic curve (AUC) of 0.696±0.044, 0.802±0.037, 0.836±0.036, and 0.822±0.035 for fold 1 to 4 testing datasets, respectively. The overall AUC of the entire dataset is 0.790±0.019. CONCLUSIONS This study demonstrates the feasibility of applying a deep learning based CAD scheme to classify between malignant and benign breast masses without a lesion segmentation, image feature computation and selection process. PMID:28436410

  2. A hybrid numerical prediction scheme for solar radiation estimation in un-gauged catchments.

    Science.gov (United States)

    Shamim, M. A.; Bray, M.; Ishak, A. M.; Remesan, R.; Han, D.

    2009-09-01

    The importance of solar radiation on earth's surface is depicted in its wide range of applications in the fields of meteorology, agricultural sciences, engineering, hydrology, crop water requirements, climatic changes and energy assessment. It is quite random in nature as it has to go through different processes of assimilation and dispersion while on its way to earth. Compared to other meteorological parameters, solar radiation is quite infrequently measured, for example, the worldwide ratio of stations collecting solar radiation to those collecting temperature is 1:500 (Badescu, 2008). Researchers, therefore, have to rely on indirect techniques of estimation that include nonlinear models, artificial intelligence (e.g. neural networks), remote sensing and numerical weather predictions (NWP). This study proposes a hybrid numerical prediction scheme for solar radiation estimation in un-gauged catchments. It uses the PSU/NCAR's Mesoscale Modelling system (MM5) (Grell et al., 1995) to parameterise the cloud effect on extraterrestrial radiation by dividing the atmosphere into four layers of very high (6-12 km), high (3-6 km), medium (1.5-3) and low (0-1.5) altitudes from earth. It is believed that various cloud forms exist within each of these layers. An hourly time series of upper air pressure and relative humidity data sets corresponding to all of these layers is determined for the Brue catchment, southwest UK, using MM5. Cloud Index (CI) was then determined using (Yang and Koike, 2002): 1 p?bi [ (Rh - Rh )] ci =------- max 0.0,---------cri dp pbi - ptipti (1- Rhcri) where, pbi and pti represent the air pressure at the top and bottom of each layer and Rhcri is the critical value of relative humidity at which a certain cloud type is formed. Output from a global clear sky solar radiation model (MRM v-5) (Kambezidis and Psiloglu, 2008) is used along with meteorological datasets of temperature and precipitation and astronomical information. The analysis is aided by the

  3. Auroral arc classification scheme based on the observed arc-associated electric field pattern

    International Nuclear Information System (INIS)

    Marklund, G.

    1983-06-01

    Radar and rocket electric field observations of auroral arcs have earlier been used to identify essentially four different arc types, namely anticorrelation and correlation arcs (with, respectively, decreased and increased arc-assocaited field) and asymmetric and reversal arcs. In this paper rocket double probe and supplementary observations from the literature, obtained under various geophysical conditions, are used to organize the different arc types on a physical rather than morphological basis. This classification is based on the relative influence on the arc electric field pattern from the two current continuity mechanisms, polarisation electric fields and Birkeland currents. In this context the tangential electric field plays an essential role and it is thus important that it can be obtained with both high accuracy and resolution. In situ observations by sounding rockets are shown to be better suited for this specific task than monostatic radar observations. Depending on the dominating mechanism, estimated quantitatively for a number of arc-crossings, the different arc types have been grouped into the following main categories: Polarisation arcs, Birkeland current arcs and combination arcs. Finally the high altitude potential distributions corresponding to some of the different arc types are presented. (author)

  4. Positivity-preserving CE/SE schemes for solving the compressible Euler and Navier–Stokes equations on hybrid unstructured meshes

    KAUST Repository

    Shen, Hua

    2018-05-28

    We construct positivity-preserving space–time conservation element and solution element (CE/SE) schemes for solving the compressible Euler and Navier–Stokes equations on hybrid unstructured meshes consisting of triangular and rectangular elements. The schemes use an a posteriori limiter to prevent negative densities and pressures based on the premise of preserving optimal accuracy. The limiter enforces a constraint for spatial derivatives and does not change the conservative property of CE/SE schemes. Several numerical examples suggest that the proposed schemes preserve accuracy for smooth flows and strictly preserve positivity of densities and pressures for the problems involving near vacuum and very strong discontinuities.

  5. [Molecular classification of breast cancer patients obtained through the technique of chromogenic in situ hybridization (CISH)].

    Science.gov (United States)

    Fernández, Angel; Reigosa, Aldo

    2013-12-01

    Breast cancer is a heterogeneous disease composed of a growing number of biological subtypes, with substantial variability of the disease progression within each category. The aim of this research was to classify the samples object of study according to the molecular classes of breast cancer: luminal A, luminal B, HER2 and triple negative, as a result of the state of HER2 amplification obtained by the technique of chromogenic in situ hybridization (CISH). The sample consisted of 200 biopsies fixed in 10% formalin, processed by standard techniques up to paraffin embedding, corresponding to patients diagnosed with invasive ductal carcinoma of the breast. These biopsies were obtained from patients from private practice and the Institute of Oncology "Dr. Miguel Pérez Carreño", for immunohistochemistry (IHC) of hormone receptors and HER2 made in the Hospital Metropolitano del Norte, Valencia, Venezuela. The molecular classification of the patient's tumors considering the expression of estrogen and progesterone receptors by IHC and HER2 amplification by CISH, allowed those cases originally classified as unknown, since they had an indeterminate (2+) outcome for HER2 expression by IHC, to be grouped into the different molecular classes. Also, this classification permitted that some cases, initially considered as belonging to a molecular class, were assigned to another class, after the revaluation of the HER2 status by CISH.

  6. Programming scheme based optimization of hybrid 4T-2R OxRAM NVSRAM

    Science.gov (United States)

    Majumdar, Swatilekha; Kingra, Sandeep Kaur; Suri, Manan

    2017-09-01

    In this paper, we present a novel single-cycle programming scheme for 4T-2R NVSRAM, exploiting pulse engineered input signals. OxRAM devices based on 3 nm thick bi-layer active switching oxide and 90 nm CMOS technology node were used for all simulations. The cell design is implemented for real-time non-volatility rather than last-bit, or power-down non-volatility. Detailed analysis of the proposed single-cycle, parallel RRAM device programming scheme is presented in comparison to the two-cycle sequential RRAM programming used for similar 4T-2R NVSRAM bit-cells. The proposed single-cycle programming scheme coupled with the 4T-2R architecture leads to several benefits such as- possibility of unconventional transistor sizing, 50% lower latency, 20% improvement in SNM and ∼20× reduced energy requirements, when compared against two-cycle programming approach.

  7. Experimental demonstration of optical data links using a hybrid CAP/QAM modulation scheme.

    Science.gov (United States)

    Wei, J L; Ingham, J D; Cheng, Q; Cunningham, D G; Penty, R V; White, I H

    2014-03-15

    The first known experimental demonstrations of a 10  Gb/s hybrid CAP-2/QAM-2 and a 20  Gb/s hybrid CAP-4/QAM-4 transmitter/receiver-based optical data link are performed. Successful transmission over 4.3 km of standard single-mode fiber (SMF) is achieved, with a link power penalty ∼0.4  dBo for CAP-2/QAM-2 and ∼1.5  dBo for CAP-4/QAM-4 at BER=10(-9).

  8. Advances in the discontinuous Galerkin method: Hybrid schemes and applications to the reactive infiltration instability in an upwelling compacting mantle

    Science.gov (United States)

    Schiemenz, Alan R.

    High-order methods are emerging in the scientific computing community as superior alternatives to the classical finite difference, finite volume, and continuous finite element methods. The discontinuous Galerkin (DG) method in particular combines many of the positive features of all of these methods. This thesis presents two projects involving the DG method. First, a Hybrid scheme is presented, which implements DG areas where the solution is considered smooth, while dropping the order of the scheme elsewhere and implementing a finite volume scheme with high-order, non-oscillatory solution reconstructions suitable for unstructured mesh. Two such reconstructions from the ENO class are considered in the Hybrid. Successful numerical results are presented for nonlinear systems of conservation laws in one dimension. Second, the high-order discontinuous Galerkin and Fourier spectral methods are applied to an application modeling three-phase fluid flow through a porous medium, undergoing solid-fluid reaction due to the reactive infiltration instability (RII). This model incorporates a solid upwelling term and an equation to track the abundance of the reacting mineral orthopyroxene (opx). After validating the numerical discretization, results are given that provide new insight into the formation of melt channels in the Earth's mantle. Mantle heterogeneities are observed to be one catalyst for the development of melt channels, and the dissolution of opx produces interesting bifurcations in the melt channels. An alternative formulation is considered where the mass transfer rate relative to velocity is taken to be infinitely large. In this setting, the stiffest terms are removed, greatly reducing the cost of time integration.

  9. Hybrid monitoring scheme for end-to-end performance enhancement of multicast-based real-time media

    Science.gov (United States)

    Park, Ju-Won; Kim, JongWon

    2004-10-01

    As real-time media applications based on IP multicast networks spread widely, end-to-end QoS (quality of service) provisioning for these applications have become very important. To guarantee the end-to-end QoS of multi-party media applications, it is essential to monitor the time-varying status of both network metrics (i.e., delay, jitter and loss) and system metrics (i.e., CPU and memory utilization). In this paper, targeting the multicast-enabled AG (Access Grid) a next-generation group collaboration tool based on multi-party media services, the applicability of hybrid monitoring scheme that combines active and passive monitoring is investigated. The active monitoring measures network-layer metrics (i.e., network condition) with probe packets while the passive monitoring checks both application-layer metrics (i.e., user traffic condition by analyzing RTCP packets) and system metrics. By comparing these hybrid results, we attempt to pinpoint the causes of performance degradation and explore corresponding reactions to improve the end-to-end performance. The experimental results show that the proposed hybrid monitoring can provide useful information to coordinate the performance improvement of multi-party real-time media applications.

  10. Application of a 5-tiered scheme for standardized classification of 2,360 unique mismatch repair gene variants in the InSiGHT locus-specific database

    DEFF Research Database (Denmark)

    Thompson, Bryony A; Spurdle, Amanda B; Plazzer, John-Paul

    2014-01-01

    and apply a standardized classification scheme to constitutional variants in the Lynch syndrome-associated genes MLH1, MSH2, MSH6 and PMS2. Unpublished data submission was encouraged to assist in variant classification and was recognized through microattribution. The scheme was refined by multidisciplinary...... are now possible for 1,370 variants that were not obviously protein truncating from nomenclature. This large-scale endeavor will facilitate the consistent management of families suspected to have Lynch syndrome and demonstrates the value of multidisciplinary collaboration in the curation......The clinical classification of hereditary sequence variants identified in disease-related genes directly affects clinical management of patients and their relatives. The International Society for Gastrointestinal Hereditary Tumours (InSiGHT) undertook a collaborative effort to develop, test...

  11. Non-hydrostatic semi-elastic hybrid-coordinate SISL extension of HIRLAM. Part I: numerical scheme

    Science.gov (United States)

    Rõõm, Rein; Männik, Aarne; Luhamaa, Andres

    2007-10-01

    Two-time-level, semi-implicit, semi-Lagrangian (SISL) scheme is applied to the non-hydrostatic pressure coordinate equations, constituting a modified Miller-Pearce-White model, in hybrid-coordinate framework. Neutral background is subtracted in the initial continuous dynamics, yielding modified equations for geopotential, temperature and logarithmic surface pressure fluctuation. Implicit Lagrangian marching formulae for single time-step are derived. A disclosure scheme is presented, which results in an uncoupled diagnostic system, consisting of 3-D Poisson equation for omega velocity and 2-D Helmholtz equation for logarithmic pressure fluctuation. The model is discretized to create a non-hydrostatic extension to numerical weather prediction model HIRLAM. The discretization schemes, trajectory computation algorithms and interpolation routines, as well as the physical parametrization package are maintained from parent hydrostatic HIRLAM. For stability investigation, the derived SISL model is linearized with respect to the initial, thermally non-equilibrium resting state. Explicit residuals of the linear model prove to be sensitive to the relative departures of temperature and static stability from the reference state. Relayed on the stability study, the semi-implicit term in the vertical momentum equation is replaced to the implicit term, which results in stability increase of the model.

  12. An enhanced forest classification scheme for modeling vegetation-climate interactions based on national forest inventory data

    Science.gov (United States)

    Majasalmi, Titta; Eisner, Stephanie; Astrup, Rasmus; Fridman, Jonas; Bright, Ryan M.

    2018-01-01

    Forest management affects the distribution of tree species and the age class of a forest, shaping its overall structure and functioning and in turn the surface-atmosphere exchanges of mass, energy, and momentum. In order to attribute climate effects to anthropogenic activities like forest management, good accounts of forest structure are necessary. Here, using Fennoscandia as a case study, we make use of Fennoscandic National Forest Inventory (NFI) data to systematically classify forest cover into groups of similar aboveground forest structure. An enhanced forest classification scheme and related lookup table (LUT) of key forest structural attributes (i.e., maximum growing season leaf area index (LAImax), basal-area-weighted mean tree height, tree crown length, and total stem volume) was developed, and the classification was applied for multisource NFI (MS-NFI) maps from Norway, Sweden, and Finland. To provide a complete surface representation, our product was integrated with the European Space Agency Climate Change Initiative Land Cover (ESA CCI LC) map of present day land cover (v.2.0.7). Comparison of the ESA LC and our enhanced LC products (https://doi.org/10.21350/7zZEy5w3) showed that forest extent notably (κ = 0.55, accuracy 0.64) differed between the two products. To demonstrate the potential of our enhanced LC product to improve the description of the maximum growing season LAI (LAImax) of managed forests in Fennoscandia, we compared our LAImax map with reference LAImax maps created using the ESA LC product (and related cross-walking table) and PFT-dependent LAImax values used in three leading land models. Comparison of the LAImax maps showed that our product provides a spatially more realistic description of LAImax in managed Fennoscandian forests compared to reference maps. This study presents an approach to account for the transient nature of forest structural attributes due to human intervention in different land models.

  13. Multi-agent system-based event-triggered hybrid control scheme for energy internet

    DEFF Research Database (Denmark)

    Dou, Chunxia; Yue, Dong; Han, Qing Long

    2017-01-01

    This paper is concerned with an event-triggered hybrid control for the energy Internet based on a multi-agent system approach with which renewable energy resources can be fully utilized to meet load demand with high security and well dynamical quality. In the design of control, a multi-agent system...

  14. A hybrid scheme for real-time prediction of bus trajectories

    NARCIS (Netherlands)

    Fadaei, Masoud; Cats, O.; Bhaskar, Ashish

    2016-01-01

    The uncertainty associated with public transport services can be partially counteracted by developing real-time models to predict downstream service conditions. In this study, a hybrid approach for predicting bus trajectories by integrating multiple predictors is proposed. The prediction model

  15. A hybrid scheme for absorbing edge reflections in numerical modeling of wave propagation

    KAUST Repository

    Liu, Yang; Sen, Mrinal K.

    2010-01-01

    We propose an efficient scheme to absorb reflections from the model boundaries in numerical solutions of wave equations. This scheme divides the computational domain into boundary, transition, and inner areas. The wavefields within the inner and boundary areas are computed by the wave equation and the one-way wave equation, respectively. The wavefields within the transition area are determined by a weighted combination of the wavefields computed by the wave equation and the one-way wave equation to obtain a smooth variation from the inner area to the boundary via the transition zone. The results from our finite-difference numerical modeling tests of the 2D acoustic wave equation show that the absorption enforced by this scheme gradually increases with increasing width of the transition area. We obtain equally good performance using pseudospectral and finite-element modeling with the same scheme. Our numerical experiments demonstrate that use of 10 grid points for absorbing edge reflections attains nearly perfect absorption. © 2010 Society of Exploration Geophysicists.

  16. A hybrid scheme for absorbing edge reflections in numerical modeling of wave propagation

    KAUST Repository

    Liu, Yang

    2010-03-01

    We propose an efficient scheme to absorb reflections from the model boundaries in numerical solutions of wave equations. This scheme divides the computational domain into boundary, transition, and inner areas. The wavefields within the inner and boundary areas are computed by the wave equation and the one-way wave equation, respectively. The wavefields within the transition area are determined by a weighted combination of the wavefields computed by the wave equation and the one-way wave equation to obtain a smooth variation from the inner area to the boundary via the transition zone. The results from our finite-difference numerical modeling tests of the 2D acoustic wave equation show that the absorption enforced by this scheme gradually increases with increasing width of the transition area. We obtain equally good performance using pseudospectral and finite-element modeling with the same scheme. Our numerical experiments demonstrate that use of 10 grid points for absorbing edge reflections attains nearly perfect absorption. © 2010 Society of Exploration Geophysicists.

  17. Gemstones and geosciences in space and time. Digital maps to the "Chessboard classification scheme of mineral deposits"

    Science.gov (United States)

    Dill, Harald G.; Weber, Berthold

    2013-12-01

    The gemstones, covering the spectrum from jeweler's to showcase quality, have been presented in a tripartite subdivision, by country, geology and geomorphology realized in 99 digital maps with more than 2600 mineralized sites. The various maps were designed based on the "Chessboard classification scheme of mineral deposits" proposed by Dill (2010a, 2010b) to reveal the interrelations between gemstone deposits and mineral deposits of other commodities and direct our thoughts to potential new target areas for exploration. A number of 33 categories were used for these digital maps: chromium, nickel, titanium, iron, manganese, copper, tin-tungsten, beryllium, lithium, zinc, calcium, boron, fluorine, strontium, phosphorus, zirconium, silica, feldspar, feldspathoids, zeolite, amphibole (tiger's eye), olivine, pyroxenoid, garnet, epidote, sillimanite-andalusite, corundum-spinel - diaspore, diamond, vermiculite-pagodite, prehnite, sepiolite, jet, and amber. Besides the political base map (gems by country) the mineral deposit is drawn on a geological map, illustrating the main lithologies, stratigraphic units and tectonic structure to unravel the evolution of primary gemstone deposits in time and space. The geomorphological map is to show the control of climate and subaerial and submarine hydrography on the deposition of secondary gemstone deposits. The digital maps are designed so as to be plotted as a paper version of different scale and to upgrade them for an interactive use and link them to gemological databases.

  18. Hybrid Iterative Scheme for Triple Hierarchical Variational Inequalities with Mixed Equilibrium, Variational Inclusion, and Minimization Constraints

    Directory of Open Access Journals (Sweden)

    Lu-Chuan Ceng

    2014-01-01

    Full Text Available We introduce and analyze a hybrid iterative algorithm by combining Korpelevich's extragradient method, the hybrid steepest-descent method, and the averaged mapping approach to the gradient-projection algorithm. It is proven that, under appropriate assumptions, the proposed algorithm converges strongly to a common element of the fixed point set of finitely many nonexpansive mappings, the solution set of a generalized mixed equilibrium problem (GMEP, the solution set of finitely many variational inclusions, and the solution set of a convex minimization problem (CMP, which is also a unique solution of a triple hierarchical variational inequality (THVI in a real Hilbert space. In addition, we also consider the application of the proposed algorithm to solving a hierarchical variational inequality problem with constraints of the GMEP, the CMP, and finitely many variational inclusions.

  19. Soccer player recognition by pixel classification in a hybrid color space

    Science.gov (United States)

    Vandenbroucke, Nicolas; Macaire, Ludovic; Postaire, Jack-Gerard

    1997-08-01

    discriminating color features which define the coordinates of each pixel in an 'hybrid color space.' Thanks to this hybrid color representation, each pixel can be assigned to one of the two classes by a minimum distance classification.

  20. Hybrid TE-TM scheme for time domain numerical calculations of wakefields in structures with walls of finite conductivity

    Directory of Open Access Journals (Sweden)

    Andranik Tsakanian

    2012-05-01

    Full Text Available In particle accelerators a preferred direction, the direction of motion, is well defined. If in a numerical calculation the (numerical dispersion in this direction is suppressed, a quite coarse mesh and moderate computational resources can be used to reach accurate results even for extremely short electron bunches. Several approaches have been proposed in the past decades to reduce the accumulated dispersion error in wakefield calculations for perfectly conducting structures. In this paper we extend the TE/TM splitting algorithm to a new hybrid scheme that allows for wakefield calculations in structures with walls of finite conductivity. The conductive boundary is modeled by one-dimensional wires connected to each boundary cell. A good agreement of the numerical simulations with analytical results and other numerical approaches is obtained.

  1. A hybrid feature selection and health indicator construction scheme for delay-time-based degradation modelling of rolling element bearings

    Science.gov (United States)

    Zhang, Bin; Deng, Congying; Zhang, Yi

    2018-03-01

    Rolling element bearings are mechanical components used frequently in most rotating machinery and they are also vulnerable links representing the main source of failures in such systems. Thus, health condition monitoring and fault diagnosis of rolling element bearings have long been studied to improve operational reliability and maintenance efficiency of rotatory machines. Over the past decade, prognosis that enables forewarning of failure and estimation of residual life attracted increasing attention. To accurately and efficiently predict failure of the rolling element bearing, the degradation requires to be well represented and modelled. For this purpose, degradation of the rolling element bearing is analysed with the delay-time-based model in this paper. Also, a hybrid feature selection and health indicator construction scheme is proposed for extraction of the bearing health relevant information from condition monitoring sensor data. Effectiveness of the presented approach is validated through case studies on rolling element bearing run-to-failure experiments.

  2. Classification

    Science.gov (United States)

    Clary, Renee; Wandersee, James

    2013-01-01

    In this article, Renee Clary and James Wandersee describe the beginnings of "Classification," which lies at the very heart of science and depends upon pattern recognition. Clary and Wandersee approach patterns by first telling the story of the "Linnaean classification system," introduced by Carl Linnacus (1707-1778), who is…

  3. A soft computing scheme incorporating ANN and MOV energy in fault detection, classification and distance estimation of EHV transmission line with FSC.

    Science.gov (United States)

    Khadke, Piyush; Patne, Nita; Singh, Arvind; Shinde, Gulab

    2016-01-01

    In this article, a novel and accurate scheme for fault detection, classification and fault distance estimation for a fixed series compensated transmission line is proposed. The proposed scheme is based on artificial neural network (ANN) and metal oxide varistor (MOV) energy, employing Levenberg-Marquardt training algorithm. The novelty of this scheme is the use of MOV energy signals of fixed series capacitors (FSC) as input to train the ANN. Such approach has never been used in any earlier fault analysis algorithms in the last few decades. Proposed scheme uses only single end measurement energy signals of MOV in all the 3 phases over one cycle duration from the occurrence of a fault. Thereafter, these MOV energy signals are fed as input to ANN for fault distance estimation. Feasibility and reliability of the proposed scheme have been evaluated for all ten types of fault in test power system model at different fault inception angles over numerous fault locations. Real transmission system parameters of 3-phase 400 kV Wardha-Aurangabad transmission line (400 km) with 40 % FSC at Power Grid Wardha Substation, India is considered for this research. Extensive simulation experiments show that the proposed scheme provides quite accurate results which demonstrate complete protection scheme with high accuracy, simplicity and robustness.

  4. Hybrid control scheme for distributed energy resource management in a market context

    DEFF Research Database (Denmark)

    Han, Xue; Bindner, Henrik W.; Mehmedalic, Jasmin

    2015-01-01

    In modernizing the electricity grid, distributed energy resources (DERs) can play an important role in accommodating intermittent energy sources, assisting system operation and the transition to a smart grid. Proper aggregation and coordination of the available DER units is required to provide...... flexibility to meet regular demand from the distribution system operator (DSO). By considering both their physical constraints and the economical system operation, this paper proposes a realtime hybrid management system for DER units in a market environment, which considers both the request from the DSO...

  5. A hybrid configuration interaction treatment based on seniority number and excitation schemes

    International Nuclear Information System (INIS)

    Alcoba, Diego R.; Capuzzi, Pablo; Torre, Alicia; Lain, Luis; Oña, Ofelia B.; Van Raemdonck, Mario; Bultinck, Patrick; Van Neck, Dimitri

    2014-01-01

    We present a configuration interaction method in which the Hamiltonian of an N-electron system is projected on Slater determinants selected according to the seniority-number criterion along with the traditional excitation-based procedure. This proposed method is especially useful to describe systems which exhibit dynamic (weak) correlation at determined geometric arrangements (where the excitation-based procedure is more suitable) but show static (strong) correlation at other arrangements (where the seniority-number technique is preferred). The hybrid method amends the shortcomings of both individual determinant selection procedures, yielding correct shapes of potential energy curves with results closer to those provided by the full configuration interaction method

  6. A hybrid configuration interaction treatment based on seniority number and excitation schemes

    Energy Technology Data Exchange (ETDEWEB)

    Alcoba, Diego R.; Capuzzi, Pablo [Departamento de Física, Facultad de Ciencias Exactas y Naturales, Universidad de Buenos Aires and Instituto de Física de Buenos Aires, Consejo Nacional de Investigaciones Científicas y Técnicas, Ciudad Universitaria, 1428 Buenos Aires (Argentina); Torre, Alicia; Lain, Luis, E-mail: qfplapel@lg.ehu.es [Departamento de Química Física, Facultad de Ciencia y Tecnología, Universidad del País Vasco, Apdo. 644 E-48080 Bilbao (Spain); Oña, Ofelia B. [Instituto de Investigaciones Fisicoquímicas Teóricas y Aplicadas, Universidad Nacional de La Plata, CCT La Plata, Consejo Nacional de Investigaciones Científicas y Técnicas, Diag. 113 y 64 (S/N), Sucursal 4, CC 16, 1900 La Plata (Argentina); Van Raemdonck, Mario; Bultinck, Patrick [Department of Inorganic and Physical Chemistry, Ghent University, Krijgslaan 281 (S3), 9000 Gent (Belgium); Van Neck, Dimitri [Center for Molecular Modelling, Ghent University, Technologiepark 903, 9052 Zwijnaarde (Belgium)

    2014-12-28

    We present a configuration interaction method in which the Hamiltonian of an N-electron system is projected on Slater determinants selected according to the seniority-number criterion along with the traditional excitation-based procedure. This proposed method is especially useful to describe systems which exhibit dynamic (weak) correlation at determined geometric arrangements (where the excitation-based procedure is more suitable) but show static (strong) correlation at other arrangements (where the seniority-number technique is preferred). The hybrid method amends the shortcomings of both individual determinant selection procedures, yielding correct shapes of potential energy curves with results closer to those provided by the full configuration interaction method.

  7. On board processing for future satellite communications systems: Comparison of FDM, TDM and hybrid accessing schemes

    Science.gov (United States)

    Berk, G.; Jean, P. N.; Rotholz, E.

    1982-01-01

    Several satellite uplink and downlink accessing schemes for customer premises service are compared. Four conceptual system designs are presented: satellite-routed frequency division multiple access (FDMA), satellite-switched time division multiple access (TDMA), processor-routed TDMA, and frequency-routed TDMA, operating in the 30/20 GHz band. The designs are compared on the basis of estimated satellite weight, system capacity, power consumption, and cost. The systems are analyzed for fixed multibeam coverage of the continental United States. Analysis shows that the system capacity is limited by the available satellite resources and by the terminal size and cost.

  8. Enhanced signaling scheme with admission control in the hybrid optical wireless (HOW) networks

    DEFF Research Database (Denmark)

    Yan, Ying; Yu, Hao; Wessing, Henrik

    2009-01-01

    that it can support stringent Quality of Service (QoS) requirements. In this paper, we describe and evaluate a resource management framework designed for the HOW networks. There are two parts in the resource management framework The first part is the Enhanced MPCP (E-MPCP) scheme aiming at improving signaling...... dropping probability depend on several factors. These factors include the frame duration, the traffic load and the total number of shared users. The results also highlight that our proposed system achieves significant improvements over the traditional approach in terms of user QoS guarantee and network...

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

    Science.gov (United States)

    Kaufung, Eva; Winkler, Stefan

    2014-05-01

    investigation on basis of a specifically developed visual classification scheme for specific regional moraine types. Our classification also takes the recently controversial discussion on the influence of major mass movement events (like rock avalanches) on glacier behavior into account by highlighting those moraines that may be influences/created by such events and require special attention. When completed, this study eventually may be a useful tool for an improved selection of future study sites by including such purpose-oriented geomorphological criteria.

  10. A hybrid finite-volume and finite difference scheme for depth-integrated non-hydrostatic model

    Science.gov (United States)

    Yin, Jing; Sun, Jia-wen; Wang, Xing-gang; Yu, Yong-hai; Sun, Zhao-chen

    2017-06-01

    A depth-integrated, non-hydrostatic model with hybrid finite difference and finite volume numerical algorithm is proposed in this paper. By utilizing a fraction step method, the governing equations are decomposed into hydrostatic and non-hydrostatic parts. The first part is solved by using the finite volume conservative discretization method, whilst the latter is considered by solving discretized Poisson-type equations with the finite difference method. The second-order accuracy, both in time and space, of the finite volume scheme is achieved by using an explicit predictor-correction step and linear construction of variable state in cells. The fluxes across the cell faces are computed in a Godunov-based manner by using MUSTA scheme. Slope and flux limiting technique is used to equip the algorithm with total variation dimensioning property for shock capturing purpose. Wave breaking is treated as a shock by switching off the non-hydrostatic pressure in the steep wave front locally. The model deals with moving wet/dry front in a simple way. Numerical experiments are conducted to verify the proposed model.

  11. A Hybrid Secure Scheme for Wireless Sensor Networks against Timing Attacks Using Continuous-Time Markov Chain and Queueing Model.

    Science.gov (United States)

    Meng, Tianhui; Li, Xiaofan; Zhang, Sha; Zhao, Yubin

    2016-09-28

    Wireless sensor networks (WSNs) have recently gained popularity for a wide spectrum of applications. Monitoring tasks can be performed in various environments. This may be beneficial in many scenarios, but it certainly exhibits new challenges in terms of security due to increased data transmission over the wireless channel with potentially unknown threats. Among possible security issues are timing attacks, which are not prevented by traditional cryptographic security. Moreover, the limited energy and memory resources prohibit the use of complex security mechanisms in such systems. Therefore, balancing between security and the associated energy consumption becomes a crucial challenge. This paper proposes a secure scheme for WSNs while maintaining the requirement of the security-performance tradeoff. In order to proceed to a quantitative treatment of this problem, a hybrid continuous-time Markov chain (CTMC) and queueing model are put forward, and the tradeoff analysis of the security and performance attributes is carried out. By extending and transforming this model, the mean time to security attributes failure is evaluated. Through tradeoff analysis, we show that our scheme can enhance the security of WSNs, and the optimal rekeying rate of the performance and security tradeoff can be obtained.

  12. An efficient and stable hybrid extended Lagrangian/self-consistent field scheme for solving classical mutual induction

    International Nuclear Information System (INIS)

    Albaugh, Alex; Demerdash, Omar; Head-Gordon, Teresa

    2015-01-01

    We have adapted a hybrid extended Lagrangian self-consistent field (EL/SCF) approach, developed for time reversible Born Oppenheimer molecular dynamics for quantum electronic degrees of freedom, to the problem of classical polarization. In this context, the initial guess for the mutual induction calculation is treated by auxiliary induced dipole variables evolved via a time-reversible velocity Verlet scheme. However, we find numerical instability, which is manifested as an accumulation in the auxiliary velocity variables, that in turn results in an unacceptable increase in the number of SCF cycles to meet even loose convergence tolerances for the real induced dipoles over the course of a 1 ns trajectory of the AMOEBA14 water model. By diagnosing the numerical instability as a problem of resonances that corrupt the dynamics, we introduce a simple thermostating scheme, illustrated using Berendsen weak coupling and Nose-Hoover chain thermostats, applied to the auxiliary dipole velocities. We find that the inertial EL/SCF (iEL/SCF) method provides superior energy conservation with less stringent convergence thresholds and a correspondingly small number of SCF cycles, to reproduce all properties of the polarization model in the NVT and NVE ensembles accurately. Our iEL/SCF approach is a clear improvement over standard SCF approaches to classical mutual induction calculations and would be worth investigating for application to ab initio molecular dynamics as well

  13. Classification

    DEFF Research Database (Denmark)

    Hjørland, Birger

    2017-01-01

    This article presents and discusses definitions of the term “classification” and the related concepts “Concept/conceptualization,”“categorization,” “ordering,” “taxonomy” and “typology.” It further presents and discusses theories of classification including the influences of Aristotle...... and Wittgenstein. It presents different views on forming classes, including logical division, numerical taxonomy, historical classification, hermeneutical and pragmatic/critical views. Finally, issues related to artificial versus natural classification and taxonomic monism versus taxonomic pluralism are briefly...

  14. An ensemble training scheme for machine-learning classification of Hyperion satellite imagery with independent hyperspectral libraries

    Science.gov (United States)

    Friedel, Michael; Buscema, Massimo

    2016-04-01

    A training scheme is proposed for the real-time classification of soil and vegetation (landscape) components in EO-1 Hyperion hyperspectral images. First, an auto-contractive map is used to compute connectivity of reflectance values for spectral bands (N=200) from independent laboratory spectral library components. Second, a minimum spanning tree is used to identify optimal grouping of training components from connectivity values. Third, the reflectance values for optimal landscape component signatures are sorted. Fourth, empirical distribution functions (EDF) are computed for each landscape component. Fifth, the Monte-Carlo technique is used to generate realizations (N=30) for each landscape EDF. The correspondence of component realizations to original signatures validates the stochastic procedure. Presentation of the realizations to the self-organizing map (SOM) is done using three different map sizes: 14x10, 28x20, and 40 x 30. In each case, the SOM training proceeds first with a rough phase (20 iterations using a Gaussian neighborhood with an initial and final radius of 11 units and 3 units) and then fine phase (400 iterations using a Gaussian neighborhood with an initial and final radius of 3 units and 1 unit). The initial and final learning rates of 0.5 and 0.05 decay linearly down to 10-5, and the Gaussian neighborhood function decreases exponentially (decay rate of 10-3 iteration-1) providing reasonable convergence. Following training of the three networks, each corresponding SOM is used to independently classify the original spectral library signatures. In comparing the different SOM networks, the 28x20 map size is chosen for independent reproducibility and processing speed. The corresponding universal distance matrix reveals separation of the seven component classes for this map size thereby supporting it use as a Hyperion classifier.

  15. A classification scheme for alternative oxidases reveals the taxonomic distribution and evolutionary history of the enzyme in angiosperms.

    Science.gov (United States)

    Costa, José Hélio; McDonald, Allison E; Arnholdt-Schmitt, Birgit; Fernandes de Melo, Dirce

    2014-11-01

    A classification scheme based on protein phylogenies and sequence harmony method was used to clarify the taxonomic distribution and evolutionary history of the alternative oxidase (AOX) in angiosperms. A large data set analyses showed that AOX1 and AOX2 subfamilies were distributed into 4 phylogenetic clades: AOX1a-c/1e, AOX1d, AOX2a-c and AOX2d. High diversity in AOX family compositions was found. While the AOX2 subfamily was not detected in monocots, the AOX1 subfamily has expanded (AOX1a-e) in the large majority of these plants. In addition, Poales AOX1b and 1d were orthologous to eudicots AOX1d and then renamed as AOX1d1 and 1d2. AOX1 or AOX2 losses were detected in some eudicot plants. Several AOX2 duplications (AOX2a-c) were identified in eudicot species, mainly in the asterids. The AOX2b originally identified in eudicots in the Fabales order (soybean, cowpea) was divergent from AOX2a-c showing some specific amino acids with AOX1d and then it was renamed as AOX2d. AOX1d and AOX2d seem to be stress-responsive, facultative and mutually exclusive among species suggesting a complementary role with an AOX1(a) in stress conditions. Based on the data collected, we present a model for the evolutionary history of AOX in angiosperms and highlight specific areas where further research would be most beneficial. Copyright © 2014 Elsevier B.V. All rights reserved.

  16. Efficient bounding schemes for the two-center hybrid flow shop scheduling problem with removal times.

    Science.gov (United States)

    Hidri, Lotfi; Gharbi, Anis; Louly, Mohamed Aly

    2014-01-01

    We focus on the two-center hybrid flow shop scheduling problem with identical parallel machines and removal times. The job removal time is the required duration to remove it from a machine after its processing. The objective is to minimize the maximum completion time (makespan). A heuristic and a lower bound are proposed for this NP-Hard problem. These procedures are based on the optimal solution of the parallel machine scheduling problem with release dates and delivery times. The heuristic is composed of two phases. The first one is a constructive phase in which an initial feasible solution is provided, while the second phase is an improvement one. Intensive computational experiments have been conducted to confirm the good performance of the proposed procedures.

  17. Preliminary analyses of neutronics schemes for three kinds waste transmutation blankets of fusion-fission hybrid

    International Nuclear Information System (INIS)

    Zhang Mingchun; Feng Kaiming; Li Zaixin; Zhao Fengchao

    2012-01-01

    The neutronics schemes of the helium-cooled waste transmutation blanket, sodium-cooled waste transmutation blanket and FLiBe-cooled waste transmutation blanket were preliminarily calculated and analysed by using the spheroidal tokamak (ST) plasma configuration. The neutronics properties of these blankets' were compared and analyzed. The results show that for the transmutation of "2"3"7Np, FLiBe-cooled waste transmutation blanket has the most superior transmutation performance. The calculation results of the helium-cooled waste transmutation blanket show that this transmutation blanket can run on a steady effective multiplication factor (k_e_f_f), steady power (P), and steady tritium production rate (TBR) state for a long operating time (9.62 years) by change "2"3"7Np's initial loading rate of the minor actinides (MA). (authors)

  18. Dynamic Simulation of a Trigeneration Scheme for Domestic Purposes Based on Hybrid Techniques

    Directory of Open Access Journals (Sweden)

    Luis Acevedo

    2016-11-01

    Full Text Available In this paper, the design of a system providing electricity by coupling photovoltaic/thermal (PVT collectors and a wind turbine (WT, sanitary hot water (SHW coming from the PVT and evacuated tube collectors (ETCs and fresh water (FW produced in two seawater desalting facilities (membrane distillation, MD, and reverse osmosis, RO, has been carefully analyzed by means of a dynamic model developed in TRNSYS®. This analysis is compulsory to operate a lab-scale pilot plant that is being erected at Zaragoza, Spain. A new model-type has been included in TRNSYS® in order to include the MD unit in the scheme. A sensitivity analysis of some free-design variables, such that the ETC surface, PVT and ETC tilt, water storage tank, batteries capacities, and mass flow rates delivered to the SHW service and/or feeding the MD unit has been performed in order to propose the definite design of the scheme. The proposed base case was able to produce up to 15,311 L per year in the MD system and cover an electric energy demand of 1890 kWh. Coverage of SHW, water (including RO and MD and power is respectively 99.3%, 100% and 70%. However, daily and yearly assessment of FW, SHW and power produced with the optimized design gave a better coverage of water and energy demands for a typical single family home. The improved and definite design was able to increase its MD production in 35% and the electric energy in 7% compared with base case.

  19. A Hybrid Quantum Evolutionary Algorithm with Improved Decoding Scheme for a Robotic Flow Shop Scheduling Problem

    Directory of Open Access Journals (Sweden)

    Weidong Lei

    2017-01-01

    Full Text Available We aim at solving the cyclic scheduling problem with a single robot and flexible processing times in a robotic flow shop, which is a well-known optimization problem in advanced manufacturing systems. The objective of the problem is to find an optimal robot move sequence such that the throughput rate is maximized. We propose a hybrid algorithm based on the Quantum-Inspired Evolutionary Algorithm (QEA and genetic operators for solving the problem. The algorithm integrates three different decoding strategies to convert quantum individuals into robot move sequences. The Q-gate is applied to update the states of Q-bits in each individual. Besides, crossover and mutation operators with adaptive probabilities are used to increase the population diversity. A repairing procedure is proposed to deal with infeasible individuals. Comparison results on both benchmark and randomly generated instances demonstrate that the proposed algorithm is more effective in solving the studied problem in terms of solution quality and computational time.

  20. A competitive carbon emissions scheme with hybrid fiscal incentives: The evidence from a taxi industry

    International Nuclear Information System (INIS)

    Liu, Yang; Han, Liyan; Yin, Ziqiao; Luo, Kongyi

    2017-01-01

    As two major approaches to reduce carbon emissions, command-and-control instruments and market-based carbon trading systems have their own weaknesses. Our paper first proposes a type of endogenous equilibrium methodology to dynamically derive the industrial carbon emissions standards. At the equilibrium, the sum of all carbon assets and liabilities is zero in the considered industry. Moreover, the standards fall over time with low-carbon technological advance. Most importantly, combining Pigou's and Coase's ideas, we construct a fiscal instrument accounting for both carbon taxes and allowances based on the dynamically improved emissions standards and carbon trading prices. This “No revenue for government” method implements a self-operated ecology for carbon trading market. Finally, considering the “Waterloo” recession of carbon prices, we introduce an adjustment factor into the model, which generates a negative-feedback mechanism with carbon prices. To support our idea, we present the application to Beijing taxi industry in detail and raise relative policy implications based on the evidence. - Highlights: • Dynamic endogenous equilibrium standards for carbon emissions. • A public policy oriented market mechanism combining command-and-control instruments and carbon trading. • Hybrid incentives to emission reduction combining carbon taxes and allowances. • The adjustment coefficient generating a negative feedback mechanism with carbon prices.

  1. Molecular dynamics simulations in hybrid particle-continuum schemes: Pitfalls and caveats

    Science.gov (United States)

    Stalter, S.; Yelash, L.; Emamy, N.; Statt, A.; Hanke, M.; Lukáčová-Medvid'ová, M.; Virnau, P.

    2018-03-01

    Heterogeneous multiscale methods (HMM) combine molecular accuracy of particle-based simulations with the computational efficiency of continuum descriptions to model flow in soft matter liquids. In these schemes, molecular simulations typically pose a computational bottleneck, which we investigate in detail in this study. We find that it is preferable to simulate many small systems as opposed to a few large systems, and that a choice of a simple isokinetic thermostat is typically sufficient while thermostats such as Lowe-Andersen allow for simulations at elevated viscosity. We discuss suitable choices for time steps and finite-size effects which arise in the limit of very small simulation boxes. We also argue that if colloidal systems are considered as opposed to atomistic systems, the gap between microscopic and macroscopic simulations regarding time and length scales is significantly smaller. We propose a novel reduced-order technique for the coupling to the macroscopic solver, which allows us to approximate a non-linear stress-strain relation efficiently and thus further reduce computational effort of microscopic simulations.

  2. Wastewater treatment using hybrid treatment schemes based on cavitation and Fenton chemistry: a review.

    Science.gov (United States)

    Bagal, Manisha V; Gogate, Parag R

    2014-01-01

    Advanced oxidation processes such as cavitation and Fenton chemistry have shown considerable promise for wastewater treatment applications due to the ease of operation and simple reactor design. In this review, hybrid methods based on cavitation coupled with Fenton process for the treatment of wastewater have been discussed. The basics of individual processes (Acoustic cavitation, Hydrodynamic cavitation, Fenton chemistry) have been discussed initially highlighting the need for combined processes. The different types of reactors used for the combined processes have been discussed with some recommendations for large scale operation. The effects of important operating parameters such as solution temperature, initial pH, initial pollutant concentration and Fenton's reagent dosage have been discussed with guidelines for selection of optimum parameters. The optimization of power density is necessary for ultrasonic processes (US) and combined processes (US/Fenton) whereas the inlet pressure needs to be optimized in the case of Hydrodynamic cavitation (HC) based processes. An overview of different pollutants degraded under optimized conditions using HC/Fenton and US/Fenton process with comparison with individual processes have been presented. It has been observed that the main mechanism for the synergy of the combined process depends on the generation of additional hydroxyl radicals and its proper utilization for the degradation of the pollutant, which is strongly dependent on the loading of hydrogen peroxide. Overall, efficient wastewater treatment with high degree of energy efficiency can be achieved using combined process operating under optimized conditions, as compared to the individual process. Copyright © 2013 Elsevier B.V. All rights reserved.

  3. Data of NODDI diffusion metrics in the brain and computer simulation of hybrid diffusion imaging (HYDI acquisition scheme

    Directory of Open Access Journals (Sweden)

    Chandana Kodiweera

    2016-06-01

    Full Text Available This article provides NODDI diffusion metrics in the brains of 52 healthy participants and computer simulation data to support compatibility of hybrid diffusion imaging (HYDI, “Hybrid diffusion imaging” [1] acquisition scheme in fitting neurite orientation dispersion and density imaging (NODDI model, “NODDI: practical in vivo neurite orientation dispersion and density imaging of the human brain” [2]. HYDI is an extremely versatile diffusion magnetic resonance imaging (dMRI technique that enables various analyzes methods using a single diffusion dataset. One of the diffusion data analysis methods is the NODDI computation, which models the brain tissue with three compartments: fast isotropic diffusion (e.g., cerebrospinal fluid, anisotropic hindered diffusion (e.g., extracellular space, and anisotropic restricted diffusion (e.g., intracellular space. The NODDI model produces microstructural metrics in the developing brain, aging brain or human brain with neurologic disorders. The first dataset provided here are the means and standard deviations of NODDI metrics in 48 white matter region-of-interest (ROI averaging across 52 healthy participants. The second dataset provided here is the computer simulation with initial conditions guided by the first dataset as inputs and gold standard for model fitting. The computer simulation data provide a direct comparison of NODDI indices computed from the HYDI acquisition [1] to the NODDI indices computed from the originally proposed acquisition [2]. These data are related to the accompanying research article “Age Effects and Sex Differences in Human Brain White Matter of Young to Middle-Aged Adults: A DTI, NODDI, and q-Space Study” [3].

  4. Day-ahead electricity prices forecasting by a modified CGSA technique and hybrid WT in LSSVM based scheme

    International Nuclear Information System (INIS)

    Shayeghi, H.; Ghasemi, A.

    2013-01-01

    Highlights: • Presenting a hybrid CGSA-LSSVM scheme for price forecasting. • Considering uncertainties for filtering in input data and feature selection to improve efficiency. • Using DWT input featured LSSVM approach to classify next-week prices. • Used three real markets to illustrate performance of the proposed price forecasting model. - Abstract: At the present time, day-ahead electricity market is closely associated with other commodity markets such as fuel market and emission market. Under such an environment, day-ahead electricity price forecasting has become necessary for power producers and consumers in the current deregulated electricity markets. Seeking for more accurate price forecasting techniques, this paper proposes a new combination of a Feature Selection (FS) technique based mutual information (MI) technique and Wavelet Transform (WT) in this study. Moreover, in this paper a new modified version of Gravitational Search Algorithm (GSA) optimization based chaos theory, namely Chaotic Gravitational Search Algorithm (CGSA) is developed to find the optimal parameters of Least Square Support Vector Machine (LSSVM) to predict electricity prices. The performance and price forecast accuracy of the proposed technique is assessed by means of real data from Iran’s, Ontario’s and Spain’s price markets. The simulation results from numerical tables and figures in different cases show that the proposed technique increases electricity price market forecasting accuracy than the other classical and heretical methods in the scientific researches

  5. Fuzzy Expert System based on a Novel Hybrid Stem Cell (HSC) Algorithm for Classification of Micro Array Data.

    Science.gov (United States)

    Vijay, S Arul Antran; GaneshKumar, P

    2018-02-21

    In the growing scenario, microarray data is extensively used since it provides a more comprehensive understanding of genetic variants among diseases. As the gene expression samples have high dimensionality it becomes tedious to analyze the samples manually. Hence an automated system is needed to analyze these samples. The fuzzy expert system offers a clear classification when compared to the machine learning and statistical methodologies. In fuzzy classification, knowledge acquisition would be a major concern. Despite several existing approaches for knowledge acquisition much effort is necessary to enhance the learning process. This paper proposes an innovative Hybrid Stem Cell (HSC) algorithm that utilizes Ant Colony optimization and Stem Cell algorithm for designing fuzzy classification system to extract the informative rules to form the membership functions from the microarray dataset. The HSC algorithm uses a novel Adaptive Stem Cell Optimization (ASCO) to improve the points of membership function and Ant Colony Optimization to produce the near optimum rule set. In order to extract the most informative genes from the large microarray dataset a method called Mutual Information is used. The performance results of the proposed technique evaluated using the five microarray datasets are simulated. These results prove that the proposed Hybrid Stem Cell (HSC) algorithm produces a precise fuzzy system than the existing methodologies.

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

    Science.gov (United States)

    Hong, Keum-Shik; Khan, Muhammad Jawad

    2017-01-01

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

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

    Science.gov (United States)

    Hong, Keum-Shik; Khan, Muhammad Jawad

    2017-01-01

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

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

    Directory of Open Access Journals (Sweden)

    Keum-Shik Hong

    2017-07-01

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

  9. Experimental Investigation for Fault Diagnosis Based on a Hybrid Approach Using Wavelet Packet and Support Vector Classification

    Directory of Open Access Journals (Sweden)

    Pengfei Li

    2014-01-01

    Full Text Available To deal with the difficulty to obtain a large number of fault samples under the practical condition for mechanical fault diagnosis, a hybrid method that combined wavelet packet decomposition and support vector classification (SVC is proposed. The wavelet packet is employed to decompose the vibration signal to obtain the energy ratio in each frequency band. Taking energy ratios as feature vectors, the pattern recognition results are obtained by the SVC. The rolling bearing and gear fault diagnostic results of the typical experimental platform show that the present approach is robust to noise and has higher classification accuracy and, thus, provides a better way to diagnose mechanical faults under the condition of small fault samples.

  10. A Hybrid Machine Learning Method for Fusing fMRI and Genetic Data: Combining both Improves Classification of Schizophrenia

    Directory of Open Access Journals (Sweden)

    Honghui Yang

    2010-10-01

    Full Text Available We demonstrate a hybrid machine learning method to classify schizophrenia patients and healthy controls, using functional magnetic resonance imaging (fMRI and single nucleotide polymorphism (SNP data. The method consists of four stages: (1 SNPs with the most discriminating information between the healthy controls and schizophrenia patients are selected to construct a support vector machine ensemble (SNP-SVME. (2 Voxels in the fMRI map contributing to classification are selected to build another SVME (Voxel-SVME. (3 Components of fMRI activation obtained with independent component analysis (ICA are used to construct a single SVM classifier (ICA-SVMC. (4 The above three models are combined into a single module using a majority voting approach to make a final decision (Combined SNP-fMRI. The method was evaluated by a fully-validated leave-one-out method using 40 subjects (20 patients and 20 controls. The classification accuracy was: 0.74 for SNP-SVME, 0.82 for Voxel-SVME, 0.83 for ICA-SVMC, and 0.87 for Combined SNP-fMRI. Experimental results show that better classification accuracy was achieved by combining genetic and fMRI data than using either alone, indicating that genetic and brain function representing different, but partially complementary aspects, of schizophrenia etiopathology. This study suggests an effective way to reassess biological classification of individuals with schizophrenia, which is also potentially useful for identifying diagnostically important markers for the disorder.

  11. Strong decays of sc-bar mesons in the covariant oscillator quark model with the U tilde (4)DS x O(3, 1)L-classification scheme

    International Nuclear Information System (INIS)

    Maeda, Tomohito; Yamada, Kenji; Oda, Masuho; Ishida, Shin

    2010-01-01

    We investigate the strong decays with one pseudoscalar emission of charmed strange mesons in the covariant oscillator quark model. The wave functions of composite sc-bar mesons are constructed as the irreducible representations of the U tilde (4) DS xO(3,1) L . Through the observed mass and results of decay study we discuss a novel assignment of observed charmed strange mesons from the viewpoint of the U tilde (4) DS x O(3,1) L -classification scheme. It is shown that D s0 * (2317) and D s1 (2460) are consistently explained as ground state chiralons, appeared in the U tilde (4) DS xO(3,1) L scheme. Furthermore, it is also found that recently-observed D s1 * (2710) could be described as first excited state chiralon. (author)

  12. Automated classification of bone marrow cells in microscopic images for diagnosis of leukemia: a comparison of two classification schemes with respect to the segmentation quality

    Science.gov (United States)

    Krappe, Sebastian; Benz, Michaela; Wittenberg, Thomas; Haferlach, Torsten; Münzenmayer, Christian

    2015-03-01

    The morphological analysis of bone marrow smears is fundamental for the diagnosis of leukemia. Currently, the counting and classification of the different types of bone marrow cells is done manually with the use of bright field microscope. This is a time consuming, partly subjective and tedious process. Furthermore, repeated examinations of a slide yield intra- and inter-observer variances. For this reason an automation of morphological bone marrow analysis is pursued. This analysis comprises several steps: image acquisition and smear detection, cell localization and segmentation, feature extraction and cell classification. The automated classification of bone marrow cells is depending on the automated cell segmentation and the choice of adequate features extracted from different parts of the cell. In this work we focus on the evaluation of support vector machines (SVMs) and random forests (RFs) for the differentiation of bone marrow cells in 16 different classes, including immature and abnormal cell classes. Data sets of different segmentation quality are used to test the two approaches. Automated solutions for the morphological analysis for bone marrow smears could use such a classifier to pre-classify bone marrow cells and thereby shortening the examination duration.

  13. Design of Passive Power Filter for Hybrid Series Active Power Filter using Estimation, Detection and Classification Method

    Science.gov (United States)

    Swain, Sushree Diptimayee; Ray, Pravat Kumar; Mohanty, K. B.

    2016-06-01

    This research paper discover the design of a shunt Passive Power Filter (PPF) in Hybrid Series Active Power Filter (HSAPF) that employs a novel analytic methodology which is superior than FFT analysis. This novel approach consists of the estimation, detection and classification of the signals. The proposed method is applied to estimate, detect and classify the power quality (PQ) disturbance such as harmonics. This proposed work deals with three methods: the harmonic detection through wavelet transform method, the harmonic estimation by Kalman Filter algorithm and harmonic classification by decision tree method. From different type of mother wavelets in wavelet transform method, the db8 is selected as suitable mother wavelet because of its potency on transient response and crouched oscillation at frequency domain. In harmonic compensation process, the detected harmonic is compensated through Hybrid Series Active Power Filter (HSAPF) based on Instantaneous Reactive Power Theory (IRPT). The efficacy of the proposed method is verified in MATLAB/SIMULINK domain and as well as with an experimental set up. The obtained results confirm the superiority of the proposed methodology than FFT analysis. This newly proposed PPF is used to make the conventional HSAPF more robust and stable.

  14. Design and simulation of a fuel cell hybrid emergency power system for a more electric aircraft: Evaluation of energy management schemes

    Science.gov (United States)

    Njoya Motapon, Souleman

    As the aircraft industries are moving toward more electric aircraft (MEA), the electrical peak load seen by the main and emergency generators becomes higher than in conventional aircraft. Consequently, there is a major concern regarding the aircraft emergency system, which consists of a ram air turbine (RAT) or air driven generator (ADG), to fulfill the load demand during critical situations; particularly at low aircraft speed where the output power is very low. A potential solution under study by most aircraft manufacturers is to replace the air turbine by a fuel cell hybrid system, consisting of fuel cell combined with other high power density sources such as supercapacitors or lithium-ion batteries. To ensure the fuel cell hybrid system will be able to meet the load demand, it must be properly designed and an effective energy management strategy must be tested with real situations load profile. This work aims at designing a fuel cell emergency power system of a more electric aircraft and comparing different energy management schemes (EMS); with the goal to ensure the load demand is fully satisfied within the constraints of each energy source. The fuel cell hybrid system considered in this study consists of fuel cell, lithium-ion batteries and supercapacitors, along with associated DC-DC and DC-AC converters. The energy management schemes addressed are state-of-the-art, most commonly used energy management techniques in fuel cell vehicle applications and include: the state machine control strategy, the rule based fuzzy logic strategy, the classical PI control strategy, the frequency decoupling/fuzzy logic control strategy and the equivalent consumption minimization strategy (ECMS). Moreover, a new optimal scheme based on maximizing the instantaneous energy of batteries/supercapacitors, to improve the fuel economy is proposed. An off-line optimization based scheme is also developed to ascertain the validity of the proposed strategy in terms of fuel consumption

  15. Asteroid taxonomic classifications

    International Nuclear Information System (INIS)

    Tholen, D.J.

    1989-01-01

    This paper reports on three taxonomic classification schemes developed and applied to the body of available color and albedo data. Asteroid taxonomic classifications according to two of these schemes are reproduced

  16. Seafloor classification using echo- waveforms: A method employing hybrid neural network architecture

    Digital Repository Service at National Institute of Oceanography (India)

    Chakraborty, B.; Mahale, V.; DeSouza, C.; Das, P.

    , neural network architecture, seafloor classification, self-organizing feature map (SOFM). I. INTRODUCTION S EAFLOOR classification and characterization using re- mote high-frequency acoustic system has been recognized as a useful tool (see [1...] and references therein). The seafloor’s characteristics are extremely complicated due to variations of the many parameters at different scales. The parameters include sediment grain size, relief height at the water–sediment inter- face, and variations within...

  17. Evaluation of a 5-tier scheme proposed for classification of sequence variants using bioinformatic and splicing assay data

    DEFF Research Database (Denmark)

    Walker, Logan C; Whiley, Phillip J; Houdayer, Claude

    2013-01-01

    BRCA1 and 176 BRCA2 unique variants, from 77 publications. At least six independent reviewers from research and/or clinical settings comprehensively examined splicing assay methods and data reported for 22 variant assays of 21 variants in four publications, and classified the variants using the 5-tier......Splicing assays are commonly undertaken in the clinical setting to assess the clinical relevance of sequence variants in disease predisposition genes. A 5-tier classification system incorporating both bioinformatic and splicing assay information was previously proposed as a method to provide...... of results, and the lack of quantitative data for the aberrant transcripts. We propose suggestions for minimum reporting guidelines for splicing assays, and improvements to the 5-tier splicing classification system to allow future evaluation of its performance as a clinical tool....

  18. Classification of Eucalyptus urograndis hybrids under different water availability based on biometric traits

    Directory of Open Access Journals (Sweden)

    Claudia D. Silva

    2014-08-01

    Full Text Available Aim of study: The eucalyptus grows rapidly and is well suitable to edaphic and bioclimatic conditions in several regions of of the world. The aim of this study was to assess the performance of Eucalyptus urograndis hybrids grown under different water availability conditions.Area of study: The study was performed in south-eastern of BrazilMaterial and Methods: We evaluated five commercial hybrids cultivated in pots with the substrate maintained at 65, 50, 35 and 20% maximum water retention capacity. The evaluation was based on the following characteristics: total height (cm, diameter (mm, number of leaves, leaf area (dm2, and dry weight (g plant-1 of leaf, stem + branches,   root, shoot and total and root/shoot ratio.Main results: All the characteristics evaluated were adversely affected by reduced availability of water in the substrate. The hybrids assessed performed differently in terms of biometric characteristics, irrespective of water availability. Water deficit resulted in a greater reduction in the dry weight production compared to number of leaves, diameter and height. Hybrids H2 and H5 have favorable traits for tolerating drought. The hybrid H2 shows a stronger slowdown in growth as soil moisture levels drop, although its growth rate is low, and H5 increases the root/shoot ratio but maintains growth in terms of height, even under drought conditions.Research highlights: The results obtained in our experiment show that productive hybrids sensitive to drought could also perform better under water deficit conditions, maintaining satisfactory growth despite significant drops in these characteristics.Keywords: Eucalyptus urograndis; water deficit; drought tolerance. 

  19. The Hybrid of Classification Tree and Extreme Learning Machine for Permeability Prediction in Oil Reservoir

    KAUST Repository

    Prasetyo Utomo, Chandra

    2011-01-01

    the permeability value. These are based on the well logs data. In order to handle the high range of the permeability value, a classification tree is utilized. A benefit of this innovation is that the tree represents knowledge in a clear and succinct fashion

  20. A hybrid MLP-CNN classifier for very fine resolution remotely sensed image classification

    Science.gov (United States)

    Zhang, Ce; Pan, Xin; Li, Huapeng; Gardiner, Andy; Sargent, Isabel; Hare, Jonathon; Atkinson, Peter M.

    2018-06-01

    The contextual-based convolutional neural network (CNN) with deep architecture and pixel-based multilayer perceptron (MLP) with shallow structure are well-recognized neural network algorithms, representing the state-of-the-art deep learning method and the classical non-parametric machine learning approach, respectively. The two algorithms, which have very different behaviours, were integrated in a concise and effective way using a rule-based decision fusion approach for the classification of very fine spatial resolution (VFSR) remotely sensed imagery. The decision fusion rules, designed primarily based on the classification confidence of the CNN, reflect the generally complementary patterns of the individual classifiers. In consequence, the proposed ensemble classifier MLP-CNN harvests the complementary results acquired from the CNN based on deep spatial feature representation and from the MLP based on spectral discrimination. Meanwhile, limitations of the CNN due to the adoption of convolutional filters such as the uncertainty in object boundary partition and loss of useful fine spatial resolution detail were compensated. The effectiveness of the ensemble MLP-CNN classifier was tested in both urban and rural areas using aerial photography together with an additional satellite sensor dataset. The MLP-CNN classifier achieved promising performance, consistently outperforming the pixel-based MLP, spectral and textural-based MLP, and the contextual-based CNN in terms of classification accuracy. This research paves the way to effectively address the complicated problem of VFSR image classification.

  1. NSCC-A NEW SCHEME OF CLASSIFICATION OF C-RICH STARS DEVISED FROM OPTICAL AND INFRARED OBSERVATIONS

    International Nuclear Information System (INIS)

    De Mello, A. B.; De Araujo, F. X.; Pereira, C. Bastos; Landaberry, S. J. Codina; Lorenz-Martins, S.

    2009-01-01

    A new classification system for carbon-rich stars is presented based on an analysis of 51 asymptotic giant branch carbon stars through the most relevant classifying indices available. The extension incorporated, which also represents the major advantage of this new system, is the combination of the usual optical indices that describe the photospheres of the objects, with new infrared ones, which allow an interpretation of the circumstellar environment of the carbon-rich stars. This new system is presented with the usual spectral subclasses and C 2 -, j-, MS-, and temperature indices, and also with the new SiC- (SiC/C.A. abundance estimation) and τ- (opacity) indices. The values for the infrared indices were carried out through a Monte Carlo simulation of the radiative transfer in the circumstellar envelopes of the stars. The full set of indices, when applied to our sample, resulted in a more efficient system of classification, since an examination in a wide spectral range allows us to obtain a complete scenario for carbon stars.

  2. A Ternary Hybrid EEG-NIRS Brain-Computer Interface for the Classification of Brain Activation Patterns during Mental Arithmetic, Motor Imagery, and Idle State.

    Science.gov (United States)

    Shin, Jaeyoung; Kwon, Jinuk; Im, Chang-Hwan

    2018-01-01

    The performance of a brain-computer interface (BCI) can be enhanced by simultaneously using two or more modalities to record brain activity, which is generally referred to as a hybrid BCI. To date, many BCI researchers have tried to implement a hybrid BCI system by combining electroencephalography (EEG) and functional near-infrared spectroscopy (NIRS) to improve the overall accuracy of binary classification. However, since hybrid EEG-NIRS BCI, which will be denoted by hBCI in this paper, has not been applied to ternary classification problems, paradigms and classification strategies appropriate for ternary classification using hBCI are not well investigated. Here we propose the use of an hBCI for the classification of three brain activation patterns elicited by mental arithmetic, motor imagery, and idle state, with the aim to elevate the information transfer rate (ITR) of hBCI by increasing the number of classes while minimizing the loss of accuracy. EEG electrodes were placed over the prefrontal cortex and the central cortex, and NIRS optodes were placed only on the forehead. The ternary classification problem was decomposed into three binary classification problems using the "one-versus-one" (OVO) classification strategy to apply the filter-bank common spatial patterns filter to EEG data. A 10 × 10-fold cross validation was performed using shrinkage linear discriminant analysis (sLDA) to evaluate the average classification accuracies for EEG-BCI, NIRS-BCI, and hBCI when the meta-classification method was adopted to enhance classification accuracy. The ternary classification accuracies for EEG-BCI, NIRS-BCI, and hBCI were 76.1 ± 12.8, 64.1 ± 9.7, and 82.2 ± 10.2%, respectively. The classification accuracy of the proposed hBCI was thus significantly higher than those of the other BCIs ( p < 0.005). The average ITR for the proposed hBCI was calculated to be 4.70 ± 1.92 bits/minute, which was 34.3% higher than that reported for a previous binary hBCI study.

  3. Pap Smear Diagnosis Using a Hybrid Intelligent Scheme Focusing on Genetic Algorithm Based Feature Selection and Nearest Neighbor Classification

    DEFF Research Database (Denmark)

    Marinakis, Yannis; Dounias, Georgios; Jantzen, Jan

    2009-01-01

    The term pap-smear refers to samples of human cells stained by the so-called Papanicolaou method. The purpose of the Papanicolaou method is to diagnose pre-cancerous cell changes before they progress to invasive carcinoma. In this paper a metaheuristic algorithm is proposed in order to classify t...... other previously applied intelligent approaches....

  4. Application of Islanding Detection and Classification of Power Quality Disturbance in Hybrid Energy System

    Science.gov (United States)

    Sun, L. B.; Wu, Z. S.; Yang, K. K.

    2018-04-01

    Islanding and power quality (PQ) disturbances in hybrid energy system become more serious with the application of renewable energy sources. In this paper, a novel method based on wavelet transform (WT) and modified feed forward neural network (FNN) is proposed to detect islanding and classify PQ problems. First, the performance indices, i.e., the energy content and SD of the transformed signal are extracted from the negative sequence component of the voltage signal at PCC using WT. Afterward, WT indices are fed to train FNNs midfield by Particle Swarm Optimization (PSO) which is a novel heuristic optimization method. Then, the results of simulation based on WT-PSOFNN are discussed in MATLAB/SIMULINK. Simulations on the hybrid power system show that the accuracy can be significantly improved by the proposed method in detecting and classifying of different disturbances connected to multiple distributed generations.

  5. Hybrid three-dimensional and support vector machine approach for automatic vehicle tracking and classification using a single camera

    Science.gov (United States)

    Kachach, Redouane; Cañas, José María

    2016-05-01

    Using video in traffic monitoring is one of the most active research domains in the computer vision community. TrafficMonitor, a system that employs a hybrid approach for automatic vehicle tracking and classification on highways using a simple stationary calibrated camera, is presented. The proposed system consists of three modules: vehicle detection, vehicle tracking, and vehicle classification. Moving vehicles are detected by an enhanced Gaussian mixture model background estimation algorithm. The design includes a technique to resolve the occlusion problem by using a combination of two-dimensional proximity tracking algorithm and the Kanade-Lucas-Tomasi feature tracking algorithm. The last module classifies the shapes identified into five vehicle categories: motorcycle, car, van, bus, and truck by using three-dimensional templates and an algorithm based on histogram of oriented gradients and the support vector machine classifier. Several experiments have been performed using both real and simulated traffic in order to validate the system. The experiments were conducted on GRAM-RTM dataset and a proper real video dataset which is made publicly available as part of this work.

  6. Semi-Supervised Active Learning for Sound Classification in Hybrid Learning Environments

    Science.gov (United States)

    Han, Wenjing; Coutinho, Eduardo; Li, Haifeng; Schuller, Björn; Yu, Xiaojie; Zhu, Xuan

    2016-01-01

    Coping with scarcity of labeled data is a common problem in sound classification tasks. Approaches for classifying sounds are commonly based on supervised learning algorithms, which require labeled data which is often scarce and leads to models that do not generalize well. In this paper, we make an efficient combination of confidence-based Active Learning and Self-Training with the aim of minimizing the need for human annotation for sound classification model training. The proposed method pre-processes the instances that are ready for labeling by calculating their classifier confidence scores, and then delivers the candidates with lower scores to human annotators, and those with high scores are automatically labeled by the machine. We demonstrate the feasibility and efficacy of this method in two practical scenarios: pool-based and stream-based processing. Extensive experimental results indicate that our approach requires significantly less labeled instances to reach the same performance in both scenarios compared to Passive Learning, Active Learning and Self-Training. A reduction of 52.2% in human labeled instances is achieved in both of the pool-based and stream-based scenarios on a sound classification task considering 16,930 sound instances. PMID:27627768

  7. Semi-Supervised Active Learning for Sound Classification in Hybrid Learning Environments.

    Science.gov (United States)

    Han, Wenjing; Coutinho, Eduardo; Ruan, Huabin; Li, Haifeng; Schuller, Björn; Yu, Xiaojie; Zhu, Xuan

    2016-01-01

    Coping with scarcity of labeled data is a common problem in sound classification tasks. Approaches for classifying sounds are commonly based on supervised learning algorithms, which require labeled data which is often scarce and leads to models that do not generalize well. In this paper, we make an efficient combination of confidence-based Active Learning and Self-Training with the aim of minimizing the need for human annotation for sound classification model training. The proposed method pre-processes the instances that are ready for labeling by calculating their classifier confidence scores, and then delivers the candidates with lower scores to human annotators, and those with high scores are automatically labeled by the machine. We demonstrate the feasibility and efficacy of this method in two practical scenarios: pool-based and stream-based processing. Extensive experimental results indicate that our approach requires significantly less labeled instances to reach the same performance in both scenarios compared to Passive Learning, Active Learning and Self-Training. A reduction of 52.2% in human labeled instances is achieved in both of the pool-based and stream-based scenarios on a sound classification task considering 16,930 sound instances.

  8. Hybrid Data Hiding Scheme Using Right-Most Digit Replacement and Adaptive Least Significant Bit for Digital Images

    Directory of Open Access Journals (Sweden)

    Mehdi Hussain

    2016-05-01

    Full Text Available The goal of image steganographic methods considers three main key issues: high embedding capacity, good visual symmetry/quality, and security. In this paper, a hybrid data hiding method combining the right-most digit replacement (RMDR with an adaptive least significant bit (ALSB is proposed to provide not only high embedding capacity but also maintain a good visual symmetry. The cover-image is divided into lower texture (symmetry patterns and higher texture (asymmetry patterns areas and these textures determine the selection of RMDR and ALSB methods, respectively, according to pixel symmetry. This paper has three major contributions. First, the proposed hybrid method enhanced the embedding capacity due to efficient ALSB utilization in the higher texture areas of cover images. Second, the proposed hybrid method maintains the high visual quality because RMDR has the closest selection process to generate the symmetry between stego and cover pixels. Finally, the proposed hybrid method is secure against statistical regular or singular (RS steganalysis and pixel difference histogram steganalysis because RMDR is capable of evading the risk of RS detection attacks due to pixel digits replacement instead of bits. Extensive experimental tests (over 1500+ cover images are conducted with recent least significant bit (LSB-based hybrid methods and it is demonstrated that the proposed hybrid method has a high embedding capacity (800,019 bits while maintaining good visual symmetry (39.00% peak signal-to-noise ratio (PSNR.

  9. Application of Snyder-Dolan classification scheme to the selection of "orthogonal" columns for fast screening of illicit drugs and impurity profiling of pharmaceuticals--I. Isocratic elution.

    Science.gov (United States)

    Fan, Wenzhe; Zhang, Yu; Carr, Peter W; Rutan, Sarah C; Dumarey, Melanie; Schellinger, Adam P; Pritts, Wayne

    2009-09-18

    Fourteen judiciously selected reversed phase columns were tested with 18 cationic drug solutes under the isocratic elution conditions advised in the Snyder-Dolan (S-D) hydrophobic subtraction method of column classification. The standard errors (S.E.) of the least squares regressions of logk' vs. logk'(REF) were obtained for a given column against a reference column and used to compare and classify columns based on their selectivity. The results are consistent with those obtained with a study of the 16 test solutes recommended by Snyder and Dolan. To the extent these drugs are representative, these results show that the S-D classification scheme is also generally applicable to pharmaceuticals under isocratic conditions. That is, those columns judged to be similar based on the 16 S-D solutes were similar based on the 18 drugs; furthermore those columns judged to have significantly different selectivities based on the 16 S-D probes appeared to be quite different for the drugs as well. Given that the S-D method has been used to classify more than 400 different types of reversed phases the extension to cationic drugs is a significant finding.

  10. Implicit and explicit schemes for mass consistency preservation in hybrid particle/finite-volume algorithms for turbulent reactive flows

    International Nuclear Information System (INIS)

    Popov, Pavel P.; Pope, Stephen B.

    2014-01-01

    This work addresses the issue of particle mass consistency in Large Eddy Simulation/Probability Density Function (LES/PDF) methods for turbulent reactive flows. Numerical schemes for the implicit and explicit enforcement of particle mass consistency (PMC) are introduced, and their performance is examined in a representative LES/PDF application, namely the Sandia–Sydney Bluff-Body flame HM1. A new combination of interpolation schemes for velocity and scalar fields is found to better satisfy PMC than multilinear and fourth-order Lagrangian interpolation. A second-order accurate time-stepping scheme for stochastic differential equations (SDE) is found to improve PMC relative to Euler time stepping, which is the first time that a second-order scheme is found to be beneficial, when compared to a first-order scheme, in an LES/PDF application. An explicit corrective velocity scheme for PMC enforcement is introduced, and its parameters optimized to enforce a specified PMC criterion with minimal corrective velocity magnitudes

  11. Computer-aided diagnostic scheme for the detection of lung nodules on chest radiographs: Localized search method based on anatomical classification

    International Nuclear Information System (INIS)

    Shiraishi, Junji; Li Qiang; Suzuki, Kenji; Engelmann, Roger; Doi, Kunio

    2006-01-01

    We developed an advanced computer-aided diagnostic (CAD) scheme for the detection of various types of lung nodules on chest radiographs intended for implementation in clinical situations. We used 924 digitized chest images (992 noncalcified nodules) which had a 500x500 matrix size with a 1024 gray scale. The images were divided randomly into two sets which were used for training and testing of the computerized scheme. In this scheme, the lung field was first segmented by use of a ribcage detection technique, and then a large search area (448x448 matrix size) within the chest image was automatically determined by taking into account the locations of a midline and a top edge of the segmented ribcage. In order to detect lung nodule candidates based on a localized search method, we divided the entire search area into 7x7 regions of interest (ROIs: 64x64 matrix size). In the next step, each ROI was classified anatomically into apical, peripheral, hilar, and diaphragm/heart regions by use of its image features. Identification of lung nodule candidates and extraction of image features were applied for each localized region (128x128 matrix size), each having its central part (64x64 matrix size) located at a position corresponding to a ROI that was classified anatomically in the previous step. Initial candidates were identified by use of the nodule-enhanced image obtained with the average radial-gradient filtering technique, in which the filter size was varied adaptively depending on the location and the anatomical classification of the ROI. We extracted 57 image features from the original and nodule-enhanced images based on geometric, gray-level, background structure, and edge-gradient features. In addition, 14 image features were obtained from the corresponding locations in the contralateral subtraction image. A total of 71 image features were employed for three sequential artificial neural networks (ANNs) in order to reduce the number of false-positive candidates. All

  12. CLASSIFICATION OF NEURAL NETWORK FOR TECHNICAL CONDITION OF TURBOFAN ENGINES BASED ON HYBRID ALGORITHM

    Directory of Open Access Journals (Sweden)

    Valentin Potapov

    2016-12-01

    Full Text Available Purpose: This work presents a method of diagnosing the technical condition of turbofan engines using hybrid neural network algorithm based on software developed for the analysis of data obtained in the aircraft life. Methods: allows the engine diagnostics with deep recognition to the structural assembly in the presence of single structural damage components of the engine running and the multifaceted damage. Results: of the optimization of neural network structure to solve the problems of evaluating technical state of the bypass turbofan engine, when used with genetic algorithms.

  13. Hybrid RGSA and Support Vector Machine Framework for Three-Dimensional Magnetic Resonance Brain Tumor Classification

    Directory of Open Access Journals (Sweden)

    R. Rajesh Sharma

    2015-01-01

    algorithm (RGSA. Support vector machines, over backpropagation network, and k-nearest neighbor are used to evaluate the goodness of classifier approach. The preliminary evaluation of the system is performed using 320 real-time brain MRI images. The system is trained and tested by using a leave-one-case-out method. The performance of the classifier is tested using the receiver operating characteristic curve of 0.986 (±002. The experimental results demonstrate the systematic and efficient feature extraction and feature selection algorithm to the performance of state-of-the-art feature classification methods.

  14. A Hierarchical Z-Scheme α-Fe2 O3 /g-C3 N4 Hybrid for Enhanced Photocatalytic CO2 Reduction.

    Science.gov (United States)

    Jiang, Zhifeng; Wan, Weiming; Li, Huaming; Yuan, Shouqi; Zhao, Huijun; Wong, Po Keung

    2018-03-01

    The challenge in the artificial photosynthesis of fossil resources from CO 2 by utilizing solar energy is to achieve stable photocatalysts with effective CO 2 adsorption capacity and high charge-separation efficiency. A hierarchical direct Z-scheme system consisting of urchin-like hematite and carbon nitride provides an enhanced photocatalytic activity of reduction of CO 2 to CO, yielding a CO evolution rate of 27.2 µmol g -1 h -1 without cocatalyst and sacrifice reagent, which is >2.2 times higher than that produced by g-C 3 N 4 alone (10.3 µmol g -1 h -1 ). The enhanced photocatalytic activity of the Z-scheme hybrid material can be ascribed to its unique characteristics to accelerate the reduction process, including: (i) 3D hierarchical structure of urchin-like hematite and preferable basic sites which promotes the CO 2 adsorption, and (ii) the unique Z-scheme feature efficiently promotes the separation of the electron-hole pairs and enhances the reducibility of electrons in the conduction band of the g-C 3 N 4 . The origin of such an obvious advantage of the hierarchical Z-scheme is not only explained based on the experimental data but also investigated by modeling CO 2 adsorption and CO adsorption on the three different atomic-scale surfaces via density functional theory calculation. The study creates new opportunities for hierarchical hematite and other metal-oxide-based Z-scheme system for solar fuel generation. © 2018 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

  15. A novel scheme for the validation of an automated classification method for epileptic spikes by comparison with multiple observers.

    Science.gov (United States)

    Sharma, Niraj K; Pedreira, Carlos; Centeno, Maria; Chaudhary, Umair J; Wehner, Tim; França, Lucas G S; Yadee, Tinonkorn; Murta, Teresa; Leite, Marco; Vos, Sjoerd B; Ourselin, Sebastien; Diehl, Beate; Lemieux, Louis

    2017-07-01

    To validate the application of an automated neuronal spike classification algorithm, Wave_clus (WC), on interictal epileptiform discharges (IED) obtained from human intracranial EEG (icEEG) data. Five 10-min segments of icEEG recorded in 5 patients were used. WC and three expert EEG reviewers independently classified one hundred IED events into IED classes or non-IEDs. First, we determined whether WC-human agreement variability falls within inter-reviewer agreement variability by calculating the variation of information for each classifier pair and quantifying the overlap between all WC-reviewer and all reviewer-reviewer pairs. Second, we compared WC and EEG reviewers' spike identification and individual spike class labels visually and quantitatively. The overlap between all WC-human pairs and all human pairs was >80% for 3/5 patients and >58% for the other 2 patients demonstrating WC falling within inter-human variation. The average sensitivity of spike marking for WC was 91% and >87% for all three EEG reviewers. Finally, there was a strong visual and quantitative similarity between WC and EEG reviewers. WC performance is indistinguishable to that of EEG reviewers' suggesting it could be a valid clinical tool for the assessment of IEDs. WC can be used to provide quantitative analysis of epileptic spikes. Copyright © 2017 International Federation of Clinical Neurophysiology. Published by Elsevier B.V. All rights reserved.

  16. Modeling and Analysis of Hybrid Cellular/WLAN Systems with Integrated Service-Based Vertical Handoff Schemes

    Science.gov (United States)

    Xia, Weiwei; Shen, Lianfeng

    We propose two vertical handoff schemes for cellular network and wireless local area network (WLAN) integration: integrated service-based handoff (ISH) and integrated service-based handoff with queue capabilities (ISHQ). Compared with existing handoff schemes in integrated cellular/WLAN networks, the proposed schemes consider a more comprehensive set of system characteristics such as different features of voice and data services, dynamic information about the admitted calls, user mobility and vertical handoffs in two directions. The code division multiple access (CDMA) cellular network and IEEE 802.11e WLAN are taken into account in the proposed schemes. We model the integrated networks by using multi-dimensional Markov chains and the major performance measures are derived for voice and data services. The important system parameters such as thresholds to prioritize handoff voice calls and queue sizes are optimized. Numerical results demonstrate that the proposed ISHQ scheme can maximize the utilization of overall bandwidth resources with the best quality of service (QoS) provisioning for voice and data services.

  17. A hybrid particle swarm optimization-SVM classification for automatic cardiac auscultation

    Directory of Open Access Journals (Sweden)

    Prasertsak Charoen

    2017-04-01

    Full Text Available Cardiac auscultation is a method for a doctor to listen to heart sounds, using a stethoscope, for examining the condition of the heart. Automatic cardiac auscultation with machine learning is a promising technique to classify heart conditions without need of doctors or expertise. In this paper, we develop a classification model based on support vector machine (SVM and particle swarm optimization (PSO for an automatic cardiac auscultation system. The model consists of two parts: heart sound signal processing part and a proposed PSO for weighted SVM (WSVM classifier part. In this method, the PSO takes into account the degree of importance for each feature extracted from wavelet packet (WP decomposition. Then, by using principle component analysis (PCA, the features can be selected. The PSO technique is used to assign diverse weights to different features for the WSVM classifier. Experimental results show that both continuous and binary PSO-WSVM models achieve better classification accuracy on the heart sound samples, by reducing system false negatives (FNs, compared to traditional SVM and genetic algorithm (GA based SVM.

  18. Secure Cooperative Spectrum Sensing via a Novel User-Classification Scheme in Cognitive Radios for Future Communication Technologies

    Directory of Open Access Journals (Sweden)

    Muhammad Usman

    2015-05-01

    Full Text Available Future communication networks would be required to deliver data on a far greater scale than is known to us today, thus mandating the maximal utilization of the available radio spectrum using cognitive radios. In this paper, we have proposed a novel cooperative spectrum sensing approach for cognitive radios. In cooperative spectrum sensing, the fusion center relies on reports of the cognitive users to make a global decision. The global decision is obtained by assigning weights to the reports received from cognitive users. Computation of such weights requires prior information of the probability of detection and the probability of false alarms, which are not readily available in real scenarios. Further, the cognitive users are divided into reliable and unreliable categories based on their weighted energy by using some empirical threshold. In this paper, we propose a method to classify the cognitive users into reliable, neutral and unreliable categories without using any pre-defined or empirically-obtained threshold. Moreover, the computation of weights does not require the detection, or false alarm probabilities, or an estimate of these probabilities. Reliable cognitive users are assigned the highest weights; neutral cognitive users are assigned medium weights (less than the reliable and higher than the unreliable cognitive users’ weights; and unreliable users are assigned the least weights. We show the performance improvement of our proposed method through simulations by comparing it with the conventional cooperative spectrum sensing scheme through different metrics, like receiver operating characteristic (ROC curve and mean square error. For clarity, we also show the effect of malicious users on detection probability and false alarm probability individually through simulations.

  19. Classification in context

    DEFF Research Database (Denmark)

    Mai, Jens Erik

    2004-01-01

    This paper surveys classification research literature, discusses various classification theories, and shows that the focus has traditionally been on establishing a scientific foundation for classification research. This paper argues that a shift has taken place, and suggests that contemporary...... classification research focus on contextual information as the guide for the design and construction of classification schemes....

  20. Hybrid Indoor-Based WLAN-WSN Localization Scheme for Improving Accuracy Based on Artificial Neural Network

    Directory of Open Access Journals (Sweden)

    Zahid Farid

    2016-01-01

    Full Text Available In indoor environments, WiFi (RSS based localization is sensitive to various indoor fading effects and noise during transmission, which are the main causes of localization errors that affect its accuracy. Keeping in view those fading effects, positioning systems based on a single technology are ineffective in performing accurate localization. For this reason, the trend is toward the use of hybrid positioning systems (combination of two or more wireless technologies in indoor/outdoor localization scenarios for getting better position accuracy. This paper presents a hybrid technique to implement indoor localization that adopts fingerprinting approaches in both WiFi and Wireless Sensor Networks (WSNs. This model exploits machine learning, in particular Artificial Natural Network (ANN techniques, for position calculation. The experimental results show that the proposed hybrid system improved the accuracy, reducing the average distance error to 1.05 m by using ANN. Applying Genetic Algorithm (GA based optimization technique did not incur any further improvement to the accuracy. Compared to the performance of GA optimization, the nonoptimized ANN performed better in terms of accuracy, precision, stability, and computational time. The above results show that the proposed hybrid technique is promising for achieving better accuracy in real-world positioning applications.

  1. Bacteriological investigations of the irradiation of fresh fish using a new classification scheme for bacteria of the fish skin

    International Nuclear Information System (INIS)

    Karnop, G.

    1975-01-01

    Investigations were made on the effect of irradiation with 36, 72, 108 and 144 kr, carried out once and twice, on the bacterial flora of the skin of red fish on the day of catching and after 9, 16 and 23 days of storage in ice. With an initial total count of the fish of 13,700 bacteria/cm 2 of skin surface irradiation with 36 kr (108 kr) on the day of catching caused a reduction of the total count to 11% (1.3%) of the nonirradiated fish on the 9th day of storage. Nearly all differences disappeared by the 16th day. A second irradiation with 36 kr and 108 kr on the 9th day reduced the bacterial count on a large scale by which on the 16th day the total count of these fishes was lower than that of the nonirradiated fish on the 9th day. Later on the differentiation disappeared quickly but there were small differences unlike the nonirradiated fish on the 23rd day. The rapid equalization during the last storage period is possibly only typical of the storage in boxes. A scheme for the characterization of types of spoilage bacteria recently established and based on the bacterial attack on leucine, β-alanine, creatine, creatinine and cystine yielded the following results: The different Pseudomonas types were reduced much more than Achromobacter types. The irradiation effect does not only consist in a reduction of the general total count of bacteria but also in the selective destruction of the most active spoilage bacteria with a very extensive enzymatic pattern which concerns many organic nitrogen compounds in the tissue of fish. By means of a sub-group of Pseudomonas and several maturity stages of the bacterial populations a 7 days delay of the bacterial evolution, caused by the second irradiation with 36 kr, could be observed. The useful effect of irradiation carried out twice with doses about 50 kr was discussed and estimated at a 10-12 days delay of the bacterial spoilage. (orig./MG) [de

  2. Bacteriological investigations of the irradiation of fresh fish using a new classification scheme for bacteria of the fish skin

    Energy Technology Data Exchange (ETDEWEB)

    Karnop, G [Bundesforschungsanstalt fuer Fischerei, Hamburg (F.R. Germany). Inst. fuer Biochemie und Technologie

    1975-04-01

    Investigations were made on the effect of irradiation with 36, 72, 108 and 144 kr, carried out once and twice, on the bacterial flora of the skin of red fish on the day of catching and after 9, 16 and 23 days of storage in ice. With an initial total count of the fish of 13,700 bacteria/cm/sup 2/ of skin surface irradiation with 36 kr (108 kr) on the day of catching caused a reduction of the total count to 11% (1.3%) of the nonirradiated fish on the 9th day of storage. Nearly all differences disappeared by the 16th day. A second irradiation with 36 kr and 108 kr on the 9th day reduced the bacterial count on a large scale by which on the 16th day the total count of these fishes was lower than that of the nonirradiated fish on the 9th day. Later on the differentiation disappeared quickly but there were small differences unlike the nonirradiated fish on the 23rd day. The rapid equalization during the last storage period is possibly only typical of the storage in boxes. A scheme for the characterization of types of spoilage bacteria recently established and based on the bacterial attack on leucine, ..beta..-alanine, creatine, creatinine and cystine yielded the following results: The different Pseudomonas types were reduced much more than Achromobacter types. The irradiation effect does not only consist in a reduction of the general total count of bacteria but also in the selective destruction of the most active spoilage bacteria with a very extensive enzymatic pattern which concerns many organic nitrogen compounds in the tissue of fish. By means of a sub-group of Pseudomonas and several maturity stages of the bacterial populations a 7 days delay of the bacterial evolution, caused by the second irradiation with 36 kr, could be observed. The useful effect of irradiation carried out twice with doses about 50 kr was discussed and estimated at a 10 to 12 days delay of the bacterial spoilage.

  3. A Quantum Hybrid PSO Combined with Fuzzy k-NN Approach to Feature Selection and Cell Classification in Cervical Cancer Detection

    Directory of Open Access Journals (Sweden)

    Abdullah M. Iliyasu

    2017-12-01

    Full Text Available A quantum hybrid (QH intelligent approach that blends the adaptive search capability of the quantum-behaved particle swarm optimisation (QPSO method with the intuitionistic rationality of traditional fuzzy k-nearest neighbours (Fuzzy k-NN algorithm (known simply as the Q-Fuzzy approach is proposed for efficient feature selection and classification of cells in cervical smeared (CS images. From an initial multitude of 17 features describing the geometry, colour, and texture of the CS images, the QPSO stage of our proposed technique is used to select the best subset features (i.e., global best particles that represent a pruned down collection of seven features. Using a dataset of almost 1000 images, performance evaluation of our proposed Q-Fuzzy approach assesses the impact of our feature selection on classification accuracy by way of three experimental scenarios that are compared alongside two other approaches: the All-features (i.e., classification without prior feature selection and another hybrid technique combining the standard PSO algorithm with the Fuzzy k-NN technique (P-Fuzzy approach. In the first and second scenarios, we further divided the assessment criteria in terms of classification accuracy based on the choice of best features and those in terms of the different categories of the cervical cells. In the third scenario, we introduced new QH hybrid techniques, i.e., QPSO combined with other supervised learning methods, and compared the classification accuracy alongside our proposed Q-Fuzzy approach. Furthermore, we employed statistical approaches to establish qualitative agreement with regards to the feature selection in the experimental scenarios 1 and 3. The synergy between the QPSO and Fuzzy k-NN in the proposed Q-Fuzzy approach improves classification accuracy as manifest in the reduction in number cell features, which is crucial for effective cervical cancer detection and diagnosis.

  4. Estimating persistence of brominated and chlorinated organic pollutants in air, water, soil, and sediments with the QSPR-based classification scheme.

    Science.gov (United States)

    Puzyn, T; Haranczyk, M; Suzuki, N; Sakurai, T

    2011-02-01

    We have estimated degradation half-lives of both brominated and chlorinated dibenzo-p-dioxins (PBDDs and PCDDs), furans (PBDFs and PCDFs), biphenyls (PBBs and PCBs), naphthalenes (PBNs and PCNs), diphenyl ethers (PBDEs and PCDEs) as well as selected unsubstituted polycyclic aromatic hydrocarbons (PAHs) in air, surface water, surface soil, and sediments (in total of 1,431 compounds in four compartments). Next, we compared the persistence between chloro- (relatively well-studied) and bromo- (less studied) analogs. The predictions have been performed based on the quantitative structure-property relationship (QSPR) scheme with use of k-nearest neighbors (kNN) classifier and the semi-quantitative system of persistence classes. The classification models utilized principal components derived from the principal component analysis of a set of 24 constitutional and quantum mechanical descriptors as input variables. Accuracies of classification (based on an external validation) were 86, 85, 87, and 75% for air, surface water, surface soil, and sediments, respectively. The persistence of all chlorinated species increased with increasing halogenation degree. In the case of brominated organic pollutants (Br-OPs), the trend was the same for air and sediments. However, we noticed that the opposite trend for persistence in surface water and soil. The results suggest that, due to high photoreactivity of C-Br chemical bonds, photolytic processes occurring in surface water and soil are able to play significant role in transforming and removing Br-OPs from these compartments. This contribution is the first attempt of classifying together Br-OPs and Cl-OPs according to their persistence, in particular, environmental compartments.

  5. Deep-subwavelength light routing in nanowire-loaded surface plasmon polariton waveguides: an alternative to the hybrid guiding scheme

    International Nuclear Information System (INIS)

    Bian, Yusheng; Gong, Qihuang

    2013-01-01

    Nanowire-loaded surface plasmon polariton waveguide is an extremely simple structure that can be naturally formed by directly dropping a dielectric cylinder onto a metallic substrate. However, despite the substantial emphasis devoted to its hybrid plasmonic counterparts, this waveguiding structure has been paid little attention to so far. Here in this paper, through comprehensive numerical analysis, we reveal that such a configuration can be leveraged to achieve deep-subwavelength field confinement with mode area more than one order of magnitude smaller than that of the conventional hybrid waveguide, while maintaining a moderate attenuation with propagation distance over tens of microns. Two-dimensional parameter mapping concerning physical dimension, shape and material of the nanowire as well as the refractive index of the cladding has disclosed the wide-range existence nature of this plasmonic mode and the feasibility to further balance its confinement and loss. (paper)

  6. Frequency Resource Sharing and Allocation Scheme Based on Coalition Formation Game in Hybrid D2D-Cellular Network

    Directory of Open Access Journals (Sweden)

    Qing Ou

    2015-01-01

    Full Text Available A distributed cooperation scheme on frequency resource sharing is proposed to improve the quality of service (QoS in device-to-device (D2D communications underlaying cellular networks. Specifically, we formulate the resource allocation problem as a coalition formation game with transferable utility, in which all users have the incentive to cooperate with some others and form a competitive group to maximize the probability of obtaining their favorite spectrum resources. Taking the cost for coalition formation into account, such as the path loss for data sharing, we prove that the core of the proposed game is empty, which shows the impossibility of grand coalition. Hence, we propose a distributed merge-and-split based coalition formation algorithm based on a new defined Max-Coalition order to effectively solve the coalition game. Compared with the exhaustive search, our algorithm has much lower computer complexity. In addition, we prove that stability and convergence of the proposed algorithm using the concept of a defection function. Finally, the simulation results show that the proposed scheme achieves a suboptimal performance in terms of network sum rate compared with the centralized optimal resource allocation scheme obtained via exhaustive search.

  7. Spatial prediction of landslides using a hybrid machine learning approach based on Random Subspace and Classification and Regression Trees

    Science.gov (United States)

    Pham, Binh Thai; Prakash, Indra; Tien Bui, Dieu

    2018-02-01

    A hybrid machine learning approach of Random Subspace (RSS) and Classification And Regression Trees (CART) is proposed to develop a model named RSSCART for spatial prediction of landslides. This model is a combination of the RSS method which is known as an efficient ensemble technique and the CART which is a state of the art classifier. The Luc Yen district of Yen Bai province, a prominent landslide prone area of Viet Nam, was selected for the model development. Performance of the RSSCART model was evaluated through the Receiver Operating Characteristic (ROC) curve, statistical analysis methods, and the Chi Square test. Results were compared with other benchmark landslide models namely Support Vector Machines (SVM), single CART, Naïve Bayes Trees (NBT), and Logistic Regression (LR). In the development of model, ten important landslide affecting factors related with geomorphology, geology and geo-environment were considered namely slope angles, elevation, slope aspect, curvature, lithology, distance to faults, distance to rivers, distance to roads, and rainfall. Performance of the RSSCART model (AUC = 0.841) is the best compared with other popular landslide models namely SVM (0.835), single CART (0.822), NBT (0.821), and LR (0.723). These results indicate that performance of the RSSCART is a promising method for spatial landslide prediction.

  8. Partial imputation to improve predictive modelling in insurance risk classification using a hybrid positive selection algorithm and correlation-based feature selection

    CSIR Research Space (South Africa)

    Duma, M

    2013-09-01

    Full Text Available of missing data, with a decline in performance as the amount of missing data increases. Wagner et al.18 presented a study aimed at constructing a multimodal, ensemble of classifiers for emotion recog- nition with missing values in one or multiple... classification accuracies of 55%, which includes certain generic fusion schemes and emotion adapted strategies like arousal, valence and cross-axis. There are four kinds of missing data mechanisms found in the literature, namely missing at random (MAR), miss...

  9. A Hybrid Scheme Motion Controller by Sliding Mode and Two-Degree-of-Freedom Controls to Minimize the Chattering

    Directory of Open Access Journals (Sweden)

    Chiu-Keng Lai

    2014-01-01

    Full Text Available Sliding mode control (SMC is rapped for the chattering due to high gain control. However, high gain control causes the system robust. For developing a system with robustness of SMC, a servo motor motion controller combining the two-degree-of-freedom (2DOF system and SMC is proposed. The discussed motion type is point-to-point control with the constraint of trapezoid velocity profile. SMC is designed to guide the motor motion to follow a predefined trail, and the inner 2DOF system is used to compensate the deterioration due to the adoption of load observer. The proposed hybrid system is realized on a PC-based motion controller, and the validness is verified by simulation and experimental results.

  10. A Control Scheme That Uses Dynamic Postural Synergies to Coordinate a Hybrid Walking Neuroprosthesis: Theory and Experiments.

    Science.gov (United States)

    Alibeji, Naji A; Molazadeh, Vahidreza; Dicianno, Brad E; Sharma, Nitin

    2018-01-01

    A hybrid walking neuroprosthesis that combines functional electrical stimulation (FES) with a powered lower limb exoskeleton can be used to restore walking in persons with paraplegia. It provides therapeutic benefits of FES and torque reliability of the powered exoskeleton. Moreover, by harnessing metabolic power of muscles via FES, the hybrid combination has a potential to lower power consumption and reduce actuator size in the powered exoskeleton. Its control design, however, must overcome the challenges of actuator redundancy due to the combined use of FES and electric motor. Further, dynamic disturbances such as electromechanical delay (EMD) and muscle fatigue must be considered during the control design process. This ensures stability and control performance despite disparate dynamics of FES and electric motor. In this paper, a general framework to coordinate FES of multiple gait-governing muscles with electric motors is presented. A muscle synergy-inspired control framework is used to derive the controller and is motivated mainly to address the actuator redundancy issue. Dynamic postural synergies between FES of the muscles and the electric motors were artificially generated through optimizations and result in key dynamic postures when activated. These synergies were used in the feedforward path of the control system. A dynamic surface control technique, modified with a delay compensation term, is used as the feedback controller to address model uncertainty, the cascaded muscle activation dynamics, and EMD. To address muscle fatigue, the stimulation levels in the feedforward path were gradually increased based on a model-based fatigue estimate. A Lyapunov-based stability approach was used to derive the controller and guarantee its stability. The synergy-based controller was demonstrated experimentally on an able-bodied subject and person with an incomplete spinal cord injury.

  11. A Control Scheme That Uses Dynamic Postural Synergies to Coordinate a Hybrid Walking Neuroprosthesis: Theory and Experiments

    Directory of Open Access Journals (Sweden)

    Naji A. Alibeji

    2018-04-01

    Full Text Available A hybrid walking neuroprosthesis that combines functional electrical stimulation (FES with a powered lower limb exoskeleton can be used to restore walking in persons with paraplegia. It provides therapeutic benefits of FES and torque reliability of the powered exoskeleton. Moreover, by harnessing metabolic power of muscles via FES, the hybrid combination has a potential to lower power consumption and reduce actuator size in the powered exoskeleton. Its control design, however, must overcome the challenges of actuator redundancy due to the combined use of FES and electric motor. Further, dynamic disturbances such as electromechanical delay (EMD and muscle fatigue must be considered during the control design process. This ensures stability and control performance despite disparate dynamics of FES and electric motor. In this paper, a general framework to coordinate FES of multiple gait-governing muscles with electric motors is presented. A muscle synergy-inspired control framework is used to derive the controller and is motivated mainly to address the actuator redundancy issue. Dynamic postural synergies between FES of the muscles and the electric motors were artificially generated through optimizations and result in key dynamic postures when activated. These synergies were used in the feedforward path of the control system. A dynamic surface control technique, modified with a delay compensation term, is used as the feedback controller to address model uncertainty, the cascaded muscle activation dynamics, and EMD. To address muscle fatigue, the stimulation levels in the feedforward path were gradually increased based on a model-based fatigue estimate. A Lyapunov-based stability approach was used to derive the controller and guarantee its stability. The synergy-based controller was demonstrated experimentally on an able-bodied subject and person with an incomplete spinal cord injury.

  12. Hybrid Quantum Mechanics/Molecular Mechanics Solvation Scheme for Computing Free Energies of Reactions at Metal-Water Interfaces.

    Science.gov (United States)

    Faheem, Muhammad; Heyden, Andreas

    2014-08-12

    We report the development of a quantum mechanics/molecular mechanics free energy perturbation (QM/MM-FEP) method for modeling chemical reactions at metal-water interfaces. This novel solvation scheme combines planewave density function theory (DFT), periodic electrostatic embedded cluster method (PEECM) calculations using Gaussian-type orbitals, and classical molecular dynamics (MD) simulations to obtain a free energy description of a complex metal-water system. We derive a potential of mean force (PMF) of the reaction system within the QM/MM framework. A fixed-size, finite ensemble of MM conformations is used to permit precise evaluation of the PMF of QM coordinates and its gradient defined within this ensemble. Local conformations of adsorbed reaction moieties are optimized using sequential MD-sampling and QM-optimization steps. An approximate reaction coordinate is constructed using a number of interpolated states and the free energy difference between adjacent states is calculated using the QM/MM-FEP method. By avoiding on-the-fly QM calculations and by circumventing the challenges associated with statistical averaging during MD sampling, a computational speedup of multiple orders of magnitude is realized. The method is systematically validated against the results of ab initio QM calculations and demonstrated for C-C cleavage in double-dehydrogenated ethylene glycol on a Pt (111) model surface.

  13. Hybrid Genetic Algorithm Fuzzy-Based Control Schemes for Small Power System with High-Penetration Wind Farms

    Directory of Open Access Journals (Sweden)

    Mohammed Elsayed Lotfy

    2018-03-01

    Full Text Available Wind is a clean, abundant, and inexhaustible source of energy. However, wind power is not constant, as windmill output is proportional to the cube of wind speed. As a result, the generated power of wind turbine generators (WTGs fluctuates significantly. Power fluctuation leads to frequency deviation and voltage flicker inside the system. This paper presents a new methodology for controlling system frequency and power. Two decentralized fuzzy logic-based control schemes with a high-penetration non-storage wind–diesel system are studied. First, one is implemented in the governor of conventional generators to damp frequency oscillation, while the other is applied to control the pitch angle system of wind turbines to smooth wind output power fluctuations and enhance the power system performance. A genetic algorithm (GA is employed to tune and optimize the membership function parameters of the fuzzy logic controllers to obtain optimal performance. The effectiveness of the suggested controllers is validated by time domain simulation for the standard IEEE nine-bus three-generator test system, including three wind farms. The robustness of the power system is checked under normal and faulty operating conditions.

  14. Efficient Power Scheduling in Smart Homes Using Hybrid Grey Wolf Differential Evolution Optimization Technique with Real Time and Critical Peak Pricing Schemes

    Directory of Open Access Journals (Sweden)

    Muqaddas Naz

    2018-02-01

    Full Text Available With the emergence of automated environments, energy demand by consumers is increasing rapidly. More than 80% of total electricity is being consumed in the residential sector. This brings a challenging task of maintaining the balance between demand and generation of electric power. In order to meet such challenges, a traditional grid is renovated by integrating two-way communication between the consumer and generation unit. To reduce electricity cost and peak load demand, demand side management (DSM is modeled as an optimization problem, and the solution is obtained by applying meta-heuristic techniques with different pricing schemes. In this paper, an optimization technique, the hybrid gray wolf differential evolution (HGWDE, is proposed by merging enhanced differential evolution (EDE and gray wolf optimization (GWO scheme using real-time pricing (RTP and critical peak pricing (CPP. Load shifting is performed from on-peak hours to off-peak hours depending on the electricity cost defined by the utility. However, there is a trade-off between user comfort and cost. To validate the performance of the proposed algorithm, simulations have been carried out in MATLAB. Results illustrate that using RTP, the peak to average ratio (PAR is reduced to 53.02%, 29.02% and 26.55%, while the electricity bill is reduced to 12.81%, 12.012% and 12.95%, respectively, for the 15-, 30- and 60-min operational time interval (OTI. On the other hand, the PAR and electricity bill are reduced to 47.27%, 22.91%, 22% and 13.04%, 12%, 11.11% using the CPP tariff.

  15. Renoprotection and the Bardoxolone Methyl Story - Is This the Right Way Forward A Novel View of Renoprotection in CKD Trials: A New Classification Scheme for Renoprotective Agents

    Directory of Open Access Journals (Sweden)

    Macaulay Onuigbo

    2013-04-01

    , and many more others yet to be identified, do concurrently and asymmetrically contribute to CKD initiation and propagation to end-stage renal disease (ESRD in our CKD patients. We conclude that current knowledge of CKD initiation and progression to ESRD, the natural history of CKD and the impacts of acute kidney injury on this continuum remain in their infancy and call for more research. Finally, we suggest a new classification scheme for renoprotective agents: (1 the single-pathway blockers that block a single putative pathogenetic pathway involved in CKD progression, as typified by ACE inhibitors and/or ARBs, and (2 the multiple-pathway blockers that are able to block or antagonize the effects of multiple pathogenetic pathways through their ability to simultaneously block, downstream, the effects of several pathways or mechanisms of CKD to ESRD progression and could therefore concurrently interfere with several unrelated upstream pathways or mechanisms. We surmise that maybe the ideal and truly renoprotective agent, clearly a multiple-pathway blocker, is on the horizon. This calls for more research efforts from all.

  16. Solution of the transport equation in stationary state and X Y geometry, using continuous and discontinuous hybrid nodal schemes; Solucion de la ecuacion de transporte en estado estacionario y geometria X Y, usando esquemas nodales hibridos continuos y discontinuos

    Energy Technology Data Exchange (ETDEWEB)

    Xolocostli M, V.; Valle G, E. del [IPN-ESFM, 07738 Mexico D.F. (Mexico); Alonso V, G. [ININ, 52045 Ocoyoacac, Estado de Mexico (Mexico)]. e-mail: xvicente@hotmail.com

    2003-07-01

    In this work it is described the development and the application of the NH-FEM schemes, Hybrid Nodal schemes using the Finite Element method in the solution of the neutron transport equation in stationary state and X Y geometry, of which two families of schemes were developed, one of which corresponds to the continuous and the other to the discontinuous ones, inside those first its are had the Bi-Quadratic Bi Q, and to the Bi-cubic BiC, while for the seconds the Discontinuous Bi-lineal DBiL and the Discontinuous Bi-quadratic DBiQ. These schemes were implemented in a program to which was denominated TNHXY, Transport of neutrons with Hybrid Nodal schemes in X Y geometry. One of the immediate applications of the schemes NH-FEM it will be in the analysis of assemblies of nuclear fuel, particularly of the BWR type. The validation of the TNHXY program was made with two test problems or benchmark, already solved by other authors with numerical techniques and to compare results. The first of them consists in an it BWR fuel assemble in an arrangement 7x7 without rod and with control rod providing numerical results. The second is a fuel assemble of mixed oxides (MOX) in an arrangement 10x10. This last problem it is known as the Benchmark problem WPPR of the NEA Data Bank and the results are compared with those of other commercial codes as HELIOS, MCNP-4B and CPM-3. (Author)

  17. Deep learning for hybrid EEG-fNIRS brain–computer interface: application to motor imagery classification

    Science.gov (United States)

    Chiarelli, Antonio Maria; Croce, Pierpaolo; Merla, Arcangelo; Zappasodi, Filippo

    2018-06-01

    Objective. Brain–computer interface (BCI) refers to procedures that link the central nervous system to a device. BCI was historically performed using electroencephalography (EEG). In the last years, encouraging results were obtained by combining EEG with other neuroimaging technologies, such as functional near infrared spectroscopy (fNIRS). A crucial step of BCI is brain state classification from recorded signal features. Deep artificial neural networks (DNNs) recently reached unprecedented complex classification outcomes. These performances were achieved through increased computational power, efficient learning algorithms, valuable activation functions, and restricted or back-fed neurons connections. By expecting significant overall BCI performances, we investigated the capabilities of combining EEG and fNIRS recordings with state-of-the-art deep learning procedures. Approach. We performed a guided left and right hand motor imagery task on 15 subjects with a fixed classification response time of 1 s and overall experiment length of 10 min. Left versus right classification accuracy of a DNN in the multi-modal recording modality was estimated and it was compared to standalone EEG and fNIRS and other classifiers. Main results. At a group level we obtained significant increase in performance when considering multi-modal recordings and DNN classifier with synergistic effect. Significance. BCI performances can be significantly improved by employing multi-modal recordings that provide electrical and hemodynamic brain activity information, in combination with advanced non-linear deep learning classification procedures.

  18. An Object-Based Classification of Mangroves Using a Hybrid Decision Tree—Support Vector Machine Approach

    Directory of Open Access Journals (Sweden)

    Benjamin W. Heumann

    2011-11-01

    Full Text Available Mangroves provide valuable ecosystem goods and services such as carbon sequestration, habitat for terrestrial and marine fauna, and coastal hazard mitigation. The use of satellite remote sensing to map mangroves has become widespread as it can provide accurate, efficient, and repeatable assessments. Traditional remote sensing approaches have failed to accurately map fringe mangroves and true mangrove species due to relatively coarse spatial resolution and/or spectral confusion with landward vegetation. This study demonstrates the use of the new Worldview-2 sensor, Object-based image analysis (OBIA, and support vector machine (SVM classification to overcome both of these limitations. An exploratory spectral separability showed that individual mangrove species could not be spectrally separated, but a distinction between true and associate mangrove species could be made. An OBIA classification was used that combined a decision-tree classification with the machine-learning SVM classification. Results showed an overall accuracy greater than 94% (kappa = 0.863 for classifying true mangroves species and other dense coastal vegetation at the object level. There remain serious challenges to accurately mapping fringe mangroves using remote sensing data due to spectral similarity of mangrove and associate species, lack of clear zonation between species, and mixed pixel effects, especially when vegetation is sparse or degraded.

  19. Application of a 5-tiered scheme for standardized classification of 2,360 unique mismatch repair gene variants in the InSiGHT locus-specific database

    NARCIS (Netherlands)

    Thompson, Bryony A.; Spurdle, Amanda B.; Plazzer, John-Paul; Greenblatt, Marc S.; Akagi, Kiwamu; Al-Mulla, Fahd; Bapat, Bharati; Bernstein, Inge; Capella, Gabriel; den Dunnen, Johan T.; du Sart, Desiree; Fabre, Aurelie; Farrell, Michael P.; Farrington, Susan M.; Frayling, Ian M.; Frebourg, Thierry; Goldgar, David E.; Heinen, Christopher D.; Holinski-Feder, Elke; Kohonen-Corish, Maija; Robinson, Kristina Lagerstedt; Leung, Suet Yi; Martins, Alexandra; Moller, Pal; Morak, Monika; Nystrom, Minna; Peltomaki, Paivi; Pineda, Marta; Qi, Ming; Ramesar, Rajkumar; Rasmussen, Lene Juel; Royer-Pokora, Brigitte; Scott, Rodney J.; Sijmons, Rolf; Tavtigian, Sean V.; Tops, Carli M.; Weber, Thomas; Wijnen, Juul; Woods, Michael O.; Macrae, Finlay; Genuardi, Maurizio

    The clinical classification of hereditary sequence variants identified in disease-related genes directly affects clinical management of patients and their relatives. The International Society for Gastrointestinal Hereditary Tumours (InSiGHT) undertook a collaborative effort to develop, test and

  20. Classification of Flotation Frothers

    Directory of Open Access Journals (Sweden)

    Jan Drzymala

    2018-02-01

    Full Text Available In this paper, a scheme of flotation frothers classification is presented. The scheme first indicates the physical system in which a frother is present and four of them i.e., pure state, aqueous solution, aqueous solution/gas system and aqueous solution/gas/solid system are distinguished. As a result, there are numerous classifications of flotation frothers. The classifications can be organized into a scheme described in detail in this paper. The frother can be present in one of four physical systems, that is pure state, aqueous solution, aqueous solution/gas and aqueous solution/gas/solid system. It results from the paper that a meaningful classification of frothers relies on choosing the physical system and next feature, trend, parameter or parameters according to which the classification is performed. The proposed classification can play a useful role in characterizing and evaluation of flotation frothers.

  1. Development and evaluation of a computer-aided diagnostic scheme for lung nodule detection in chest radiographs by means of two-stage nodule enhancement with support vector classification

    International Nuclear Information System (INIS)

    Chen Sheng; Suzuki, Kenji; MacMahon, Heber

    2011-01-01

    Purpose: To develop a computer-aided detection (CADe) scheme for nodules in chest radiographs (CXRs) with a high sensitivity and a low false-positive (FP) rate. Methods: The authors developed a CADe scheme consisting of five major steps, which were developed for improving the overall performance of CADe schemes. First, to segment the lung fields accurately, the authors developed a multisegment active shape model. Then, a two-stage nodule-enhancement technique was developed for improving the conspicuity of nodules. Initial nodule candidates were detected and segmented by using the clustering watershed algorithm. Thirty-one shape-, gray-level-, surface-, and gradient-based features were extracted from each segmented candidate for determining the feature space, including one of the new features based on the Canny edge detector to eliminate a major FP source caused by rib crossings. Finally, a nonlinear support vector machine (SVM) with a Gaussian kernel was employed for classification of the nodule candidates. Results: To evaluate and compare the scheme to other published CADe schemes, the authors used a publicly available database containing 140 nodules in 140 CXRs and 93 normal CXRs. The CADe scheme based on the SVM classifier achieved sensitivities of 78.6% (110/140) and 71.4% (100/140) with averages of 5.0 (1165/233) FPs/image and 2.0 (466/233) FPs/image, respectively, in a leave-one-out cross-validation test, whereas the CADe scheme based on a linear discriminant analysis classifier had a sensitivity of 60.7% (85/140) at an FP rate of 5.0 FPs/image. For nodules classified as ''very subtle'' and ''extremely subtle,'' a sensitivity of 57.1% (24/42) was achieved at an FP rate of 5.0 FPs/image. When the authors used a database developed at the University of Chicago, the sensitivities was 83.3% (40/48) and 77.1% (37/48) at an FP rate of 5.0 (240/48) FPs/image and 2.0 (96/48) FPs /image, respectively. Conclusions: These results compare favorably to those described for

  2. High-resolution multi-code implementation of unsteady Navier-Stokes flow solver based on paralleled overset adaptive mesh refinement and high-order low-dissipation hybrid schemes

    Science.gov (United States)

    Li, Gaohua; Fu, Xiang; Wang, Fuxin

    2017-10-01

    The low-dissipation high-order accurate hybrid up-winding/central scheme based on fifth-order weighted essentially non-oscillatory (WENO) and sixth-order central schemes, along with the Spalart-Allmaras (SA)-based delayed detached eddy simulation (DDES) turbulence model, and the flow feature-based adaptive mesh refinement (AMR), are implemented into a dual-mesh overset grid infrastructure with parallel computing capabilities, for the purpose of simulating vortex-dominated unsteady detached wake flows with high spatial resolutions. The overset grid assembly (OGA) process based on collection detection theory and implicit hole-cutting algorithm achieves an automatic coupling for the near-body and off-body solvers, and the error-and-try method is used for obtaining a globally balanced load distribution among the composed multiple codes. The results of flows over high Reynolds cylinder and two-bladed helicopter rotor show that the combination of high-order hybrid scheme, advanced turbulence model, and overset adaptive mesh refinement can effectively enhance the spatial resolution for the simulation of turbulent wake eddies.

  3. Quadcopter flight control using a low-cost hybrid interface with EEG-based classification and eye tracking.

    Science.gov (United States)

    Kim, Byung Hyung; Kim, Minho; Jo, Sungho

    2014-08-01

    We propose a wearable hybrid interface where eye movements and mental concentration directly influence the control of a quadcopter in three-dimensional space. This noninvasive and low-cost interface addresses limitations of previous work by supporting users to complete their complicated tasks in a constrained environment in which only visual feedback is provided. The combination of the two inputs augments the number of control commands to enable the flying robot to travel in eight different directions within the physical environment. Five human subjects participated in the experiments to test the feasibility of the hybrid interface. A front view camera on the hull of the quadcopter provided the only visual feedback to each remote subject on a laptop display. Based on the visual feedback, the subjects used the interface to navigate along pre-set target locations in the air. The flight performance was evaluated by comparing with a keyboard-based interface. We demonstrate the applicability of the hybrid interface to explore and interact with a three-dimensional physical space through a flying robot. Copyright © 2014 Elsevier Ltd. All rights reserved.

  4. Classification of Two Class Motor Imagery Tasks Using Hybrid GA-PSO Based K-Means Clustering.

    Science.gov (United States)

    Suraj; Tiwari, Purnendu; Ghosh, Subhojit; Sinha, Rakesh Kumar

    2015-01-01

    Transferring the brain computer interface (BCI) from laboratory condition to meet the real world application needs BCI to be applied asynchronously without any time constraint. High level of dynamism in the electroencephalogram (EEG) signal reasons us to look toward evolutionary algorithm (EA). Motivated by these two facts, in this work a hybrid GA-PSO based K-means clustering technique has been used to distinguish two class motor imagery (MI) tasks. The proposed hybrid GA-PSO based K-means clustering is found to outperform genetic algorithm (GA) and particle swarm optimization (PSO) based K-means clustering techniques in terms of both accuracy and execution time. The lesser execution time of hybrid GA-PSO technique makes it suitable for real time BCI application. Time frequency representation (TFR) techniques have been used to extract the feature of the signal under investigation. TFRs based features are extracted and relying on the concept of event related synchronization (ERD) and desynchronization (ERD) feature vector is formed.

  5. mRMR-ABC: A Hybrid Gene Selection Algorithm for Cancer Classification Using Microarray Gene Expression Profiling

    Directory of Open Access Journals (Sweden)

    Hala Alshamlan

    2015-01-01

    Full Text Available An artificial bee colony (ABC is a relatively recent swarm intelligence optimization approach. In this paper, we propose the first attempt at applying ABC algorithm in analyzing a microarray gene expression profile. In addition, we propose an innovative feature selection algorithm, minimum redundancy maximum relevance (mRMR, and combine it with an ABC algorithm, mRMR-ABC, to select informative genes from microarray profile. The new approach is based on a support vector machine (SVM algorithm to measure the classification accuracy for selected genes. We evaluate the performance of the proposed mRMR-ABC algorithm by conducting extensive experiments on six binary and multiclass gene expression microarray datasets. Furthermore, we compare our proposed mRMR-ABC algorithm with previously known techniques. We reimplemented two of these techniques for the sake of a fair comparison using the same parameters. These two techniques are mRMR when combined with a genetic algorithm (mRMR-GA and mRMR when combined with a particle swarm optimization algorithm (mRMR-PSO. The experimental results prove that the proposed mRMR-ABC algorithm achieves accurate classification performance using small number of predictive genes when tested using both datasets and compared to previously suggested methods. This shows that mRMR-ABC is a promising approach for solving gene selection and cancer classification problems.

  6. mRMR-ABC: A Hybrid Gene Selection Algorithm for Cancer Classification Using Microarray Gene Expression Profiling.

    Science.gov (United States)

    Alshamlan, Hala; Badr, Ghada; Alohali, Yousef

    2015-01-01

    An artificial bee colony (ABC) is a relatively recent swarm intelligence optimization approach. In this paper, we propose the first attempt at applying ABC algorithm in analyzing a microarray gene expression profile. In addition, we propose an innovative feature selection algorithm, minimum redundancy maximum relevance (mRMR), and combine it with an ABC algorithm, mRMR-ABC, to select informative genes from microarray profile. The new approach is based on a support vector machine (SVM) algorithm to measure the classification accuracy for selected genes. We evaluate the performance of the proposed mRMR-ABC algorithm by conducting extensive experiments on six binary and multiclass gene expression microarray datasets. Furthermore, we compare our proposed mRMR-ABC algorithm with previously known techniques. We reimplemented two of these techniques for the sake of a fair comparison using the same parameters. These two techniques are mRMR when combined with a genetic algorithm (mRMR-GA) and mRMR when combined with a particle swarm optimization algorithm (mRMR-PSO). The experimental results prove that the proposed mRMR-ABC algorithm achieves accurate classification performance using small number of predictive genes when tested using both datasets and compared to previously suggested methods. This shows that mRMR-ABC is a promising approach for solving gene selection and cancer classification problems.

  7. Positivity-preserving CE/SE schemes for solving the compressible Euler and Navier–Stokes equations on hybrid unstructured meshes

    KAUST Repository

    Shen, Hua; Parsani, Matteo

    2018-01-01

    . The schemes use an a posteriori limiter to prevent negative densities and pressures based on the premise of preserving optimal accuracy. The limiter enforces a constraint for spatial derivatives and does not change the conservative property of CE/SE schemes

  8. A segmentation and classification scheme for single tooth in MicroCT images based on 3D level set and k-means+.

    Science.gov (United States)

    Wang, Liansheng; Li, Shusheng; Chen, Rongzhen; Liu, Sze-Yu; Chen, Jyh-Cheng

    2017-04-01

    Accurate classification of different anatomical structures of teeth from medical images provides crucial information for the stress analysis in dentistry. Usually, the anatomical structures of teeth are manually labeled by experienced clinical doctors, which is time consuming. However, automatic segmentation and classification is a challenging task because the anatomical structures and surroundings of the tooth in medical images are rather complex. Therefore, in this paper, we propose an effective framework which is designed to segment the tooth with a Selective Binary and Gaussian Filtering Regularized Level Set (GFRLS) method improved by fully utilizing 3 dimensional (3D) information, and classify the tooth by employing unsupervised learning i.e., k-means++ method. In order to evaluate the proposed method, the experiments are conducted on the sufficient and extensive datasets of mandibular molars. The experimental results show that our method can achieve higher accuracy and robustness compared to other three clustering methods. Copyright © 2016 Elsevier Ltd. All rights reserved.

  9. An assessment of commonly employed satellite-based remote sensors for mapping mangrove species in Mexico using an NDVI-based classification scheme.

    Science.gov (United States)

    Valderrama-Landeros, L; Flores-de-Santiago, F; Kovacs, J M; Flores-Verdugo, F

    2017-12-14

    Optimizing the classification accuracy of a mangrove forest is of utmost importance for conservation practitioners. Mangrove forest mapping using satellite-based remote sensing techniques is by far the most common method of classification currently used given the logistical difficulties of field endeavors in these forested wetlands. However, there is now an abundance of options from which to choose in regards to satellite sensors, which has led to substantially different estimations of mangrove forest location and extent with particular concern for degraded systems. The objective of this study was to assess the accuracy of mangrove forest classification using different remotely sensed data sources (i.e., Landsat-8, SPOT-5, Sentinel-2, and WorldView-2) for a system located along the Pacific coast of Mexico. Specifically, we examined a stressed semiarid mangrove forest which offers a variety of conditions such as dead areas, degraded stands, healthy mangroves, and very dense mangrove island formations. The results indicated that Landsat-8 (30 m per pixel) had  the lowest overall accuracy at 64% and that WorldView-2 (1.6 m per pixel) had the highest at 93%. Moreover, the SPOT-5 and the Sentinel-2 classifications (10 m per pixel) were very similar having accuracies of 75 and 78%, respectively. In comparison to WorldView-2, the other sensors overestimated the extent of Laguncularia racemosa and underestimated the extent of Rhizophora mangle. When considering such type of sensors, the higher spatial resolution can be particularly important in mapping small mangrove islands that often occur in degraded mangrove systems.

  10. Development of a Classification Scheme for Examining Adverse Events Associated with Medical Devices, Specifically the DaVinci Surgical System as Reported in the FDA MAUDE Database.

    Science.gov (United States)

    Gupta, Priyanka; Schomburg, John; Krishna, Suprita; Adejoro, Oluwakayode; Wang, Qi; Marsh, Benjamin; Nguyen, Andrew; Genere, Juan Reyes; Self, Patrick; Lund, Erik; Konety, Badrinath R

    2017-01-01

    To examine the Manufacturer and User Facility Device Experience Database (MAUDE) database to capture adverse events experienced with the Da Vinci Surgical System. In addition, to design a standardized classification system to categorize the complications and machine failures associated with the device. Overall, 1,057,000 DaVinci procedures were performed in the United States between 2009 and 2012. Currently, no system exists for classifying and comparing device-related errors and complications with which to evaluate adverse events associated with the Da Vinci Surgical System. The MAUDE database was queried for events reports related to the DaVinci Surgical System between the years 2009 and 2012. A classification system was developed and tested among 14 robotic surgeons to associate a level of severity with each event and its relationship to the DaVinci Surgical System. Events were then classified according to this system and examined by using Chi-square analysis. Two thousand eight hundred thirty-seven events were identified, of which 34% were obstetrics and gynecology (Ob/Gyn); 19%, urology; 11%, other; and 36%, not specified. Our classification system had moderate agreement with a Kappa score of 0.52. Using our classification system, we identified 75% of the events as mild, 18% as moderate, 4% as severe, and 3% as life threatening or resulting in death. Seventy-seven percent were classified as definitely related to the device, 15% as possibly related, and 8% as not related. Urology procedures compared with Ob/Gyn were associated with more severe events (38% vs 26%, p tool with moderate inter-rater agreement that can be used to better understand device-related adverse events. The majority of robotic related events were mild but associated with the device.

  11. Acoustic classification of dwellings

    DEFF Research Database (Denmark)

    Berardi, Umberto; Rasmussen, Birgit

    2014-01-01

    insulation performance, national schemes for sound classification of dwellings have been developed in several European countries. These schemes define acoustic classes according to different levels of sound insulation. Due to the lack of coordination among countries, a significant diversity in terms...... exchanging experiences about constructions fulfilling different classes, reducing trade barriers, and finally increasing the sound insulation of dwellings.......Schemes for the classification of dwellings according to different building performances have been proposed in the last years worldwide. The general idea behind these schemes relates to the positive impact a higher label, and thus a better performance, should have. In particular, focusing on sound...

  12. An Evaluation of Different Training Sample Allocation Schemes for Discrete and Continuous Land Cover Classification Using Decision Tree-Based Algorithms

    Directory of Open Access Journals (Sweden)

    René Roland Colditz

    2015-07-01

    Full Text Available Land cover mapping for large regions often employs satellite images of medium to coarse spatial resolution, which complicates mapping of discrete classes. Class memberships, which estimate the proportion of each class for every pixel, have been suggested as an alternative. This paper compares different strategies of training data allocation for discrete and continuous land cover mapping using classification and regression tree algorithms. In addition to measures of discrete and continuous map accuracy the correct estimation of the area is another important criteria. A subset of the 30 m national land cover dataset of 2006 (NLCD2006 of the United States was used as reference set to classify NADIR BRDF-adjusted surface reflectance time series of MODIS at 900 m spatial resolution. Results show that sampling of heterogeneous pixels and sample allocation according to the expected area of each class is best for classification trees. Regression trees for continuous land cover mapping should be trained with random allocation, and predictions should be normalized with a linear scaling function to correctly estimate the total area. From the tested algorithms random forest classification yields lower errors than boosted trees of C5.0, and Cubist shows higher accuracies than random forest regression.

  13. Drug-like and non drug-like pattern classification based on simple topology descriptor using hybrid neural network.

    Science.gov (United States)

    Wan-Mamat, Wan Mohd Fahmi; Isa, Nor Ashidi Mat; Wahab, Habibah A; Wan-Mamat, Wan Mohd Fairuz

    2009-01-01

    An intelligent prediction system has been developed to discriminate drug-like and non drug-like molecules pattern. The system is constructed by using the application of advanced version of standard multilayer perceptron (MLP) neural network called Hybrid Multilayer Perceptron (HMLP) neural network and trained using Modified Recursive Prediction Error (MRPE) training algorithm. In this work, a well understood and easy excess Rule of Five + Veber filter properties are selected as the topological descriptor. The main idea behind the selection of this simple descriptor is to assure that the system could be used widely, beneficial and more advantageous regardless at all user level within a drug discovery organization.

  14. Automatic Picking of Foraminifera: Design of the Foraminifera Image Recognition and Sorting Tool (FIRST) Prototype and Results of the Image Classification Scheme

    Science.gov (United States)

    de Garidel-Thoron, T.; Marchant, R.; Soto, E.; Gally, Y.; Beaufort, L.; Bolton, C. T.; Bouslama, M.; Licari, L.; Mazur, J. C.; Brutti, J. M.; Norsa, F.

    2017-12-01

    Foraminifera tests are the main proxy carriers for paleoceanographic reconstructions. Both geochemical and taxonomical studies require large numbers of tests to achieve statistical relevance. To date, the extraction of foraminifera from the sediment coarse fraction is still done by hand and thus time-consuming. Moreover, the recognition of morphotypes, ecologically relevant, requires some taxonomical skills not easily taught. The automatic recognition and extraction of foraminifera would largely help paleoceanographers to overcome these issues. Recent advances in automatic image classification using machine learning opens the way to automatic extraction of foraminifera. Here we detail progress on the design of an automatic picking machine as part of the FIRST project. The machine handles 30 pre-sieved samples (100-1000µm), separating them into individual particles (including foraminifera) and imaging each in pseudo-3D. The particles are classified and specimens of interest are sorted either for Individual Foraminifera Analyses (44 per slide) and/or for classical multiple analyses (8 morphological classes per slide, up to 1000 individuals per hole). The classification is based on machine learning using Convolutional Neural Networks (CNNs), similar to the approach used in the coccolithophorid imaging system SYRACO. To prove its feasibility, we built two training image datasets of modern planktonic foraminifera containing approximately 2000 and 5000 images each, corresponding to 15 & 25 morphological classes. Using a CNN with a residual topology (ResNet) we achieve over 95% correct classification for each dataset. We tested the network on 160,000 images from 45 depths of a sediment core from the Pacific ocean, for which we have human counts. The current algorithm is able to reproduce the downcore variability in both Globigerinoides ruber and the fragmentation index (r2 = 0.58 and 0.88 respectively). The FIRST prototype yields some promising results for high

  15. Evaluation of the Melanocytic Pathology Assessment Tool and Hierarchy for Diagnosis (MPATH-Dx) classification scheme for diagnosis of cutaneous melanocytic neoplasms: Results from the International Melanoma Pathology Study Group.

    Science.gov (United States)

    Lott, Jason P; Elmore, Joann G; Zhao, Ge A; Knezevich, Stevan R; Frederick, Paul D; Reisch, Lisa M; Chu, Emily Y; Cook, Martin G; Duncan, Lyn M; Elenitsas, Rosalie; Gerami, Pedram; Landman, Gilles; Lowe, Lori; Messina, Jane L; Mihm, Martin C; van den Oord, Joost J; Rabkin, Michael S; Schmidt, Birgitta; Shea, Christopher R; Yun, Sook Jung; Xu, George X; Piepkorn, Michael W; Elder, David E; Barnhill, Raymond L

    2016-08-01

    Pathologists use diverse terminology when interpreting melanocytic neoplasms, potentially compromising quality of care. We sought to evaluate the Melanocytic Pathology Assessment Tool and Hierarchy for Diagnosis (MPATH-Dx) scheme, a 5-category classification system for melanocytic lesions. Participants (n = 16) of the 2013 International Melanoma Pathology Study Group Workshop provided independent case-level diagnoses and treatment suggestions for 48 melanocytic lesions. Individual diagnoses (including, when necessary, least and most severe diagnoses) were mapped to corresponding MPATH-Dx classes. Interrater agreement and correlation between MPATH-Dx categorization and treatment suggestions were evaluated. Most participants were board-certified dermatopathologists (n = 15), age 50 years or older (n = 12), male (n = 9), based in the United States (n = 11), and primary academic faculty (n = 14). Overall, participants generated 634 case-level diagnoses with treatment suggestions. Mean weighted kappa coefficients for diagnostic agreement after MPATH-Dx mapping (assuming least and most severe diagnoses, when necessary) were 0.70 (95% confidence interval 0.68-0.71) and 0.72 (95% confidence interval 0.71-0.73), respectively, whereas correlation between MPATH-Dx categorization and treatment suggestions was 0.91. This was a small sample size of experienced pathologists in a testing situation. Varying diagnostic nomenclature can be classified into a concise hierarchy using the MPATH-Dx scheme. Further research is needed to determine whether this classification system can facilitate diagnostic concordance in general pathology practice and improve patient care. Copyright © 2016 American Academy of Dermatology, Inc. Published by Elsevier Inc. All rights reserved.

  16. A hybrid gene selection approach for microarray data classification using cellular learning automata and ant colony optimization.

    Science.gov (United States)

    Vafaee Sharbaf, Fatemeh; Mosafer, Sara; Moattar, Mohammad Hossein

    2016-06-01

    This paper proposes an approach for gene selection in microarray data. The proposed approach consists of a primary filter approach using Fisher criterion which reduces the initial genes and hence the search space and time complexity. Then, a wrapper approach which is based on cellular learning automata (CLA) optimized with ant colony method (ACO) is used to find the set of features which improve the classification accuracy. CLA is applied due to its capability to learn and model complicated relationships. The selected features from the last phase are evaluated using ROC curve and the most effective while smallest feature subset is determined. The classifiers which are evaluated in the proposed framework are K-nearest neighbor; support vector machine and naïve Bayes. The proposed approach is evaluated on 4 microarray datasets. The evaluations confirm that the proposed approach can find the smallest subset of genes while approaching the maximum accuracy. Copyright © 2016 Elsevier Inc. All rights reserved.

  17. THE ROLE OF STARBURST-ACTIVE GALACTIC NUCLEUS COMPOSITES IN LUMINOUS INFRARED GALAXY MERGERS: INSIGHTS FROM THE NEW OPTICAL CLASSIFICATION SCHEME

    International Nuclear Information System (INIS)

    Yuan, T.-T.; Kewley, L. J.; Sanders, D. B.

    2010-01-01

    We investigate the fraction of starbursts, starburst-active galactic nucleus (AGN) composites, Seyferts, and low-ionization narrow emission-line region galaxies (LINERs) as a function of infrared luminosity (L IR ) and merger progress for ∼500 infrared (IR)-selected galaxies. Using the new optical classifications afforded by the extremely large data set of the Sloan Digital Sky Survey, we find that the fraction of LINERs in IR-selected samples is rare ( IR > 10 12 L sun ), starburst-AGN composite galaxies dominate at early-intermediate stages of the merger, and AGN galaxies dominate during the final merger stages. Our results are consistent with models for IR-luminous galaxies where mergers of gas-rich spirals fuel both starburst and AGN, and where the AGN becomes increasingly dominant during the final merger stages of the most luminous IR objects.

  18. Application of Snyder-Dolan Classification Scheme to the Selection of “Orthogonal” Columns for Fast Screening for Illicit Drugs and Impurity Profiling of Pharmaceuticals - I. Isocratic Elution

    Science.gov (United States)

    Fan, Wenzhe; Zhang, Yu; Carr, Peter W.; Rutan, Sarah C.; Dumarey, Melanie; Schellinger, Adam P.; Pritts, Wayne

    2011-01-01

    Fourteen judiciously selected reversed-phase columns were tested with 18 cationic drug solutes under the isocratic elution conditions advised in the Snyder-Dolan (S-D) hydrophobic subtraction method of column classification. The standard errors (S.E.) of the least squares regressions of log k′ vs. log k′REF were obtained for a given column against a reference column and used to compare and classify columns based on their selectivity. The results are consistent with those obtained with a study of the 16 test solutes recommended by Snyder and Dolan. To the extent that these drugs are representative these results show that the S-D classification scheme is also generally applicable to pharmaceuticals under isocratic conditions. That is, those columns judged to be similar based on the S-D 16 solutes were similar based on the 18 drugs; furthermore those columns judged to have significantly different selectivities based on the 16 S-D probes appeared to be quite different for the drugs as well. Given that the S-D method has been used to classify more than 400 different types of reversed phases the extension to cationic drugs is a significant finding. PMID:19698948

  19. THROUGHPUT ANALYSIS OF EXTENDED ARQ SCHEMES

    African Journals Online (AJOL)

    PUBLICATIONS1

    ABSTRACT. Various Automatic Repeat Request (ARQ) schemes have been used to combat errors that befall in- formation transmitted in digital communication systems. Such schemes include simple ARQ, mixed mode ARQ and Hybrid ARQ (HARQ). In this study we introduce extended ARQ schemes and derive.

  20. An Exact and Grid-free Numerical Scheme for the Hybrid Two Phase Traffic Flow Model Based on the Lighthill-Whitham-Richards Model with Bounded Acceleration

    KAUST Repository

    Qiu, Shanwen

    2012-07-01

    In this article, we propose a new grid-free and exact solution method for computing solutions associated with an hybrid traffic flow model based on the Lighthill- Whitham-Richards (LWR) partial differential equation. In this hybrid flow model, the vehicles satisfy the LWR equation whenever possible, and have a fixed acceleration otherwise. We first present a grid-free solution method for the LWR equation based on the minimization of component functions. We then show that this solution method can be extended to compute the solutions to the hybrid model by proper modification of the component functions, for any concave fundamental diagram. We derive these functions analytically for the specific case of a triangular fundamental diagram. We also show that the proposed computational method can handle fixed or moving bottlenecks.

  1. Multiple-correction hybrid k-exact schemes for high-order compressible RANS-LES simulations on fully unstructured grids

    Science.gov (United States)

    Pont, Grégoire; Brenner, Pierre; Cinnella, Paola; Maugars, Bruno; Robinet, Jean-Christophe

    2017-12-01

    A Godunov's type unstructured finite volume method suitable for highly compressible turbulent scale-resolving simulations around complex geometries is constructed by using a successive correction technique. First, a family of k-exact Godunov schemes is developed by recursively correcting the truncation error of the piecewise polynomial representation of the primitive variables. The keystone of the proposed approach is a quasi-Green gradient operator which ensures consistency on general meshes. In addition, a high-order single-point quadrature formula, based on high-order approximations of the successive derivatives of the solution, is developed for flux integration along cell faces. The proposed family of schemes is compact in the algorithmic sense, since it only involves communications between direct neighbors of the mesh cells. The numerical properties of the schemes up to fifth-order are investigated, with focus on their resolvability in terms of number of mesh points required to resolve a given wavelength accurately. Afterwards, in the aim of achieving the best possible trade-off between accuracy, computational cost and robustness in view of industrial flow computations, we focus more specifically on the third-order accurate scheme of the family, and modify locally its numerical flux in order to reduce the amount of numerical dissipation in vortex-dominated regions. This is achieved by switching from the upwind scheme, mostly applied in highly compressible regions, to a fourth-order centered one in vortex-dominated regions. An analytical switch function based on the local grid Reynolds number is adopted in order to warrant numerical stability of the recentering process. Numerical applications demonstrate the accuracy and robustness of the proposed methodology for compressible scale-resolving computations. In particular, supersonic RANS/LES computations of the flow over a cavity are presented to show the capability of the scheme to predict flows with shocks

  2. Classification of focal liver lesions on ultrasound images by extracting hybrid textural features and using an artificial neural network.

    Science.gov (United States)

    Hwang, Yoo Na; Lee, Ju Hwan; Kim, Ga Young; Jiang, Yuan Yuan; Kim, Sung Min

    2015-01-01

    This paper focuses on the improvement of the diagnostic accuracy of focal liver lesions by quantifying the key features of cysts, hemangiomas, and malignant lesions on ultrasound images. The focal liver lesions were divided into 29 cysts, 37 hemangiomas, and 33 malignancies. A total of 42 hybrid textural features that composed of 5 first order statistics, 18 gray level co-occurrence matrices, 18 Law's, and echogenicity were extracted. A total of 29 key features that were selected by principal component analysis were used as a set of inputs for a feed-forward neural network. For each lesion, the performance of the diagnosis was evaluated by using the positive predictive value, negative predictive value, sensitivity, specificity, and accuracy. The results of the experiment indicate that the proposed method exhibits great performance, a high diagnosis accuracy of over 96% among all focal liver lesion groups (cyst vs. hemangioma, cyst vs. malignant, and hemangioma vs. malignant) on ultrasound images. The accuracy was slightly increased when echogenicity was included in the optimal feature set. These results indicate that it is possible for the proposed method to be applied clinically.

  3. A Classification Methodology and Retrieval Model to Support Software Reuse

    Science.gov (United States)

    1988-01-01

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

  4. Colour schemes

    DEFF Research Database (Denmark)

    van Leeuwen, Theo

    2013-01-01

    This chapter presents a framework for analysing colour schemes based on a parametric approach that includes not only hue, value and saturation, but also purity, transparency, luminosity, luminescence, lustre, modulation and differentiation.......This chapter presents a framework for analysing colour schemes based on a parametric approach that includes not only hue, value and saturation, but also purity, transparency, luminosity, luminescence, lustre, modulation and differentiation....

  5. Unsupervised Analysis of Array Comparative Genomic Hybridization Data from Early-Onset Colorectal Cancer Reveals Equivalence with Molecular Classification and Phenotypes

    Directory of Open Access Journals (Sweden)

    María Arriba

    2017-01-01

    Full Text Available AIM: To investigate whether chromosomal instability (CIN is associated with tumor phenotypes and/or with global genomic status based on MSI (microsatellite instability and CIMP (CpG island methylator phenotype in early-onset colorectal cancer (EOCRC. METHODS: Taking as a starting point our previous work in which tumors from 60 EOCRC cases (≤45 years at the time of diagnosis were analyzed by array comparative genomic hybridization (aCGH, in the present study we performed an unsupervised hierarchical clustering analysis of those aCGH data in order to unveil possible associations between the CIN profile and the clinical features of the tumors. In addition, we evaluated the MSI and the CIMP statuses of the samples with the aim of investigating a possible relationship between copy number alterations (CNAs and the MSI/CIMP condition in EOCRC. RESULTS: Based on the similarity of the CNAs detected, the unsupervised analysis stratified samples into two main clusters (A, B and four secondary clusters (A1, A2, B3, B4. The different subgroups showed a certain correspondence with the molecular classification of colorectal cancer (CRC, which enabled us to outline an algorithm to categorize tumors according to their CIMP status. Interestingly, each subcluster showed some distinctive clinicopathological features. But more interestingly, the CIN of each subcluster mainly affected particular chromosomes, allowing us to define chromosomal regions more specifically affected depending on the CIMP/MSI status of the samples. CONCLUSIONS: Our findings may provide a basis for a new form of classifying EOCRC according to the genomic status of the tumors.

  6. A classification scheme for young stellar objects using the wide-field infrared survey explorer AllWISE catalog: revealing low-density star formation in the outer galaxy

    Energy Technology Data Exchange (ETDEWEB)

    Koenig, X. P. [Department of Astronomy, Yale University, New Haven, CT 06511 (United States); Leisawitz, D. T. [NASA Goddard Space Flight Center, Greenbelt, MD 20771 (United States)

    2014-08-20

    We present an assessment of the performance of WISE and the AllWISE data release for a section of the Galactic Plane. We lay out an approach to increasing the reliability of point-source photometry extracted from the AllWISE catalog in Galactic Plane regions using parameters provided in the catalog. We use the resulting catalog to construct a new, revised young star detection and classification scheme combining WISE and 2MASS near- and mid-infrared colors and magnitudes and test it in a section of the outer Milky Way. The clustering properties of the candidate Class I and II stars using a nearest neighbor density calculation and the two-point correlation function suggest that the majority of stars do form in massive star-forming regions, and any isolated mode of star formation is at most a small fraction of the total star forming output of the Galaxy. We also show that the isolated component may be very small and could represent the tail end of a single mechanism of star formation in line with models of molecular cloud collapse with supersonic turbulence and not a separate mode all to itself.

  7. A solar PV augmented hybrid scheme for enhanced wind power generation through improved control strategy for grid connected doubly fed induction generator

    Directory of Open Access Journals (Sweden)

    Adikanda Parida

    2016-12-01

    Full Text Available In this paper, a wind power generation scheme using a grid connected doubly fed induction generator (DFIG augmented with solar PV has been proposed. A reactive power-based rotor speed and position estimation technique with reduced machine parameter sensitivity is also proposed to improve the performance of the DFIG controller. The estimation algorithm is based on model reference adaptive system (MRAS, which uses the air gap reactive power as the adjustable variable. The overall generation reliability of the wind energy conversion system can be considerably improved as both solar and wind energy can supplement each other during lean periods of either of the sources. The rotor-side DC-link voltage and active power generation at the stator terminals of the DFIG are maintained constant with minimum storage battery capacity using single converter arrangement without grid-side converter (GSC. The proposed scheme has been simulated and experimentally validated with a practical 2.5 kW DFIG using dSPACE CP1104 module which produced satisfactory results.

  8. Tradable schemes

    NARCIS (Netherlands)

    J.K. Hoogland (Jiri); C.D.D. Neumann

    2000-01-01

    textabstractIn this article we present a new approach to the numerical valuation of derivative securities. The method is based on our previous work where we formulated the theory of pricing in terms of tradables. The basic idea is to fit a finite difference scheme to exact solutions of the pricing

  9. The Influence of Second-Hand Cigarette Smoke Exposure during Childhood and Active Cigarette Smoking on Crohn's Disease Phenotype Defined by the Montreal Classification Scheme in a Western Cape Population, South Africa.

    Directory of Open Access Journals (Sweden)

    Tawanda Chivese

    Full Text Available Smoking may worsen the disease outcomes in patients with Crohn's disease (CD, however the effect of exposure to second-hand cigarette smoke during childhood is unclear. In South Africa, no such literature exists. The aim of this study was to investigate whether disease phenotype, at time of diagnosis of CD, was associated with exposure to second-hand cigarette during childhood and active cigarette smoking habits.A cross sectional examination of all consecutive CD patients seen during the period September 2011-January 2013 at 2 large inflammatory bowel disease centers in the Western Cape, South Africa was performed. Data were collected via review of patient case notes, interviewer-administered questionnaire and clinical examination by the attending gastroenterologist. Disease phenotype (behavior and location was evaluated at time of diagnosis, according to the Montreal Classification scheme. In addition, disease behavior was stratified as 'complicated' or 'uncomplicated', using predefined definitions. Passive cigarette smoke exposure was evaluated during 3 age intervals: 0-5, 6-10, and 11-18 years.One hundred and ninety four CD patients were identified. Cigarette smoking during the 6 months prior to, or at time of diagnosis was significantly associated with ileo-colonic (L3 disease (RRR = 3.63; 95% CI, 1.32-9.98, p = 0.012 and ileal (L1 disease (RRR = 3.54; 95% CI, 1.06-11.83, p = 0.040 compared with colonic disease. In smokers, childhood passive cigarette smoke exposure during the 0-5 years age interval was significantly associated with ileo-colonic CD location (RRR = 21.3; 95% CI, 1.16-391.55, p = 0.040. No significant association between smoking habits and disease behavior at diagnosis, whether defined by the Montreal scheme, or stratified as 'complicated' vs 'uncomplicated', was observed.Smoking habits were associated with ileo-colonic (L3 and ileal (L1 disease at time of diagnosis in a South African cohort.

  10. Sound classification of dwellings

    DEFF Research Database (Denmark)

    Rasmussen, Birgit

    2012-01-01

    National schemes for sound classification of dwellings exist in more than ten countries in Europe, typically published as national standards. The schemes define quality classes reflecting different levels of acoustical comfort. Main criteria concern airborne and impact sound insulation between...... dwellings, facade sound insulation and installation noise. The schemes have been developed, implemented and revised gradually since the early 1990s. However, due to lack of coordination between countries, there are significant discrepancies, and new standards and revisions continue to increase the diversity...... is needed, and a European COST Action TU0901 "Integrating and Harmonizing Sound Insulation Aspects in Sustainable Urban Housing Constructions", has been established and runs 2009-2013, one of the main objectives being to prepare a proposal for a European sound classification scheme with a number of quality...

  11. Update on diabetes classification.

    Science.gov (United States)

    Thomas, Celeste C; Philipson, Louis H

    2015-01-01

    This article highlights the difficulties in creating a definitive classification of diabetes mellitus in the absence of a complete understanding of the pathogenesis of the major forms. This brief review shows the evolving nature of the classification of diabetes mellitus. No classification scheme is ideal, and all have some overlap and inconsistencies. The only diabetes in which it is possible to accurately diagnose by DNA sequencing, monogenic diabetes, remains undiagnosed in more than 90% of the individuals who have diabetes caused by one of the known gene mutations. The point of classification, or taxonomy, of disease, should be to give insight into both pathogenesis and treatment. It remains a source of frustration that all schemes of diabetes mellitus continue to fall short of this goal. Copyright © 2015 Elsevier Inc. All rights reserved.

  12. Acoustic reverse-time migration using GPU card and POSIX thread based on the adaptive optimal finite-difference scheme and the hybrid absorbing boundary condition

    Science.gov (United States)

    Cai, Xiaohui; Liu, Yang; Ren, Zhiming

    2018-06-01

    Reverse-time migration (RTM) is a powerful tool for imaging geologically complex structures such as steep-dip and subsalt. However, its implementation is quite computationally expensive. Recently, as a low-cost solution, the graphic processing unit (GPU) was introduced to improve the efficiency of RTM. In the paper, we develop three ameliorative strategies to implement RTM on GPU card. First, given the high accuracy and efficiency of the adaptive optimal finite-difference (FD) method based on least squares (LS) on central processing unit (CPU), we study the optimal LS-based FD method on GPU. Second, we develop the CPU-based hybrid absorbing boundary condition (ABC) to the GPU-based one by addressing two issues of the former when introduced to GPU card: time-consuming and chaotic threads. Third, for large-scale data, the combinatorial strategy for optimal checkpointing and efficient boundary storage is introduced for the trade-off between memory and recomputation. To save the time of communication between host and disk, the portable operating system interface (POSIX) thread is utilized to create the other CPU core at the checkpoints. Applications of the three strategies on GPU with the compute unified device architecture (CUDA) programming language in RTM demonstrate their efficiency and validity.

  13. Hybrid Optimization of Object-Based Classification in High-Resolution Images Using Continous ANT Colony Algorithm with Emphasis on Building Detection

    Science.gov (United States)

    Tamimi, E.; Ebadi, H.; Kiani, A.

    2017-09-01

    Automatic building detection from High Spatial Resolution (HSR) images is one of the most important issues in Remote Sensing (RS). Due to the limited number of spectral bands in HSR images, using other features will lead to improve accuracy. By adding these features, the presence probability of dependent features will be increased, which leads to accuracy reduction. In addition, some parameters should be determined in Support Vector Machine (SVM) classification. Therefore, it is necessary to simultaneously determine classification parameters and select independent features according to image type. Optimization algorithm is an efficient method to solve this problem. On the other hand, pixel-based classification faces several challenges such as producing salt-paper results and high computational time in high dimensional data. Hence, in this paper, a novel method is proposed to optimize object-based SVM classification by applying continuous Ant Colony Optimization (ACO) algorithm. The advantages of the proposed method are relatively high automation level, independency of image scene and type, post processing reduction for building edge reconstruction and accuracy improvement. The proposed method was evaluated by pixel-based SVM and Random Forest (RF) classification in terms of accuracy. In comparison with optimized pixel-based SVM classification, the results showed that the proposed method improved quality factor and overall accuracy by 17% and 10%, respectively. Also, in the proposed method, Kappa coefficient was improved by 6% rather than RF classification. Time processing of the proposed method was relatively low because of unit of image analysis (image object). These showed the superiority of the proposed method in terms of time and accuracy.

  14. HYBRID OPTIMIZATION OF OBJECT-BASED CLASSIFICATION IN HIGH-RESOLUTION IMAGES USING CONTINOUS ANT COLONY ALGORITHM WITH EMPHASIS ON BUILDING DETECTION

    Directory of Open Access Journals (Sweden)

    E. Tamimi

    2017-09-01

    Full Text Available Automatic building detection from High Spatial Resolution (HSR images is one of the most important issues in Remote Sensing (RS. Due to the limited number of spectral bands in HSR images, using other features will lead to improve accuracy. By adding these features, the presence probability of dependent features will be increased, which leads to accuracy reduction. In addition, some parameters should be determined in Support Vector Machine (SVM classification. Therefore, it is necessary to simultaneously determine classification parameters and select independent features according to image type. Optimization algorithm is an efficient method to solve this problem. On the other hand, pixel-based classification faces several challenges such as producing salt-paper results and high computational time in high dimensional data. Hence, in this paper, a novel method is proposed to optimize object-based SVM classification by applying continuous Ant Colony Optimization (ACO algorithm. The advantages of the proposed method are relatively high automation level, independency of image scene and type, post processing reduction for building edge reconstruction and accuracy improvement. The proposed method was evaluated by pixel-based SVM and Random Forest (RF classification in terms of accuracy. In comparison with optimized pixel-based SVM classification, the results showed that the proposed method improved quality factor and overall accuracy by 17% and 10%, respectively. Also, in the proposed method, Kappa coefficient was improved by 6% rather than RF classification. Time processing of the proposed method was relatively low because of unit of image analysis (image object. These showed the superiority of the proposed method in terms of time and accuracy.

  15. Classifying Classifications

    DEFF Research Database (Denmark)

    Debus, Michael S.

    2017-01-01

    This paper critically analyzes seventeen game classifications. The classifications were chosen on the basis of diversity, ranging from pre-digital classification (e.g. Murray 1952), over game studies classifications (e.g. Elverdam & Aarseth 2007) to classifications of drinking games (e.g. LaBrie et...... al. 2013). The analysis aims at three goals: The classifications’ internal consistency, the abstraction of classification criteria and the identification of differences in classification across fields and/or time. Especially the abstraction of classification criteria can be used in future endeavors...... into the topic of game classifications....

  16. A Computer Oriented Scheme for Coding Chemicals in the Field of Biomedicine.

    Science.gov (United States)

    Bobka, Marilyn E.; Subramaniam, J.B.

    The chemical coding scheme of the Medical Coding Scheme (MCS), developed for use in the Comparative Systems Laboratory (CSL), is outlined and evaluated in this report. The chemical coding scheme provides a classification scheme and encoding method for drugs and chemical terms. Using the scheme complicated chemical structures may be expressed…

  17. Constraining a hybrid volatility basis-set model for aging of wood-burning emissions using smog chamber experiments: a box-model study based on the VBS scheme of the CAMx model (v5.40)

    Science.gov (United States)

    Ciarelli, Giancarlo; El Haddad, Imad; Bruns, Emily; Aksoyoglu, Sebnem; Möhler, Ottmar; Baltensperger, Urs; Prévôt, André S. H.

    2017-06-01

    In this study, novel wood combustion aging experiments performed at different temperatures (263 and 288 K) in a ˜ 7 m3 smog chamber were modelled using a hybrid volatility basis set (VBS) box model, representing the emission partitioning and their oxidation against OH. We combine aerosol-chemistry box-model simulations with unprecedented measurements of non-traditional volatile organic compounds (NTVOCs) from a high-resolution proton transfer reaction mass spectrometer (PTR-MS) and with organic aerosol measurements from an aerosol mass spectrometer (AMS). Due to this, we are able to observationally constrain the amounts of different NTVOC aerosol precursors (in the model) relative to low volatility and semi-volatile primary organic material (OMsv), which is partitioned based on current published volatility distribution data. By comparing the NTVOC / OMsv ratios at different temperatures, we determine the enthalpies of vaporization of primary biomass-burning organic aerosols. Further, the developed model allows for evaluating the evolution of oxidation products of the semi-volatile and volatile precursors with aging. More than 30 000 box-model simulations were performed to retrieve the combination of parameters that best fit the observed organic aerosol mass and O : C ratios. The parameters investigated include the NTVOC reaction rates and yields as well as enthalpies of vaporization and the O : C of secondary organic aerosol surrogates. Our results suggest an average ratio of NTVOCs to the sum of non-volatile and semi-volatile organic compounds of ˜ 4.75. The mass yields of these compounds determined for a wide range of atmospherically relevant temperatures and organic aerosol (OA) concentrations were predicted to vary between 8 and 30 % after 5 h of continuous aging. Based on the reaction scheme used, reaction rates of the NTVOC mixture range from 3.0 × 10-11 to 4. 0 × 10-11 cm3 molec-1 s-1. The average enthalpy of vaporization of secondary organic aerosol

  18. Constraining a hybrid volatility basis-set model for aging of wood-burning emissions using smog chamber experiments: a box-model study based on the VBS scheme of the CAMx model (v5.40

    Directory of Open Access Journals (Sweden)

    G. Ciarelli

    2017-06-01

    Full Text Available In this study, novel wood combustion aging experiments performed at different temperatures (263 and 288 K in a ∼ 7 m3 smog chamber were modelled using a hybrid volatility basis set (VBS box model, representing the emission partitioning and their oxidation against OH. We combine aerosol–chemistry box-model simulations with unprecedented measurements of non-traditional volatile organic compounds (NTVOCs from a high-resolution proton transfer reaction mass spectrometer (PTR-MS and with organic aerosol measurements from an aerosol mass spectrometer (AMS. Due to this, we are able to observationally constrain the amounts of different NTVOC aerosol precursors (in the model relative to low volatility and semi-volatile primary organic material (OMsv, which is partitioned based on current published volatility distribution data. By comparing the NTVOC ∕ OMsv ratios at different temperatures, we determine the enthalpies of vaporization of primary biomass-burning organic aerosols. Further, the developed model allows for evaluating the evolution of oxidation products of the semi-volatile and volatile precursors with aging. More than 30 000 box-model simulations were performed to retrieve the combination of parameters that best fit the observed organic aerosol mass and O : C ratios. The parameters investigated include the NTVOC reaction rates and yields as well as enthalpies of vaporization and the O : C of secondary organic aerosol surrogates. Our results suggest an average ratio of NTVOCs to the sum of non-volatile and semi-volatile organic compounds of ∼ 4.75. The mass yields of these compounds determined for a wide range of atmospherically relevant temperatures and organic aerosol (OA concentrations were predicted to vary between 8 and 30 % after 5 h of continuous aging. Based on the reaction scheme used, reaction rates of the NTVOC mixture range from 3.0 × 10−11 to 4. 0 × 10−11 cm3 molec−1 s−1

  19. An Unequal Secure Encryption Scheme for H.264/AVC Video Compression Standard

    Science.gov (United States)

    Fan, Yibo; Wang, Jidong; Ikenaga, Takeshi; Tsunoo, Yukiyasu; Goto, Satoshi

    H.264/AVC is the newest video coding standard. There are many new features in it which can be easily used for video encryption. In this paper, we propose a new scheme to do video encryption for H.264/AVC video compression standard. We define Unequal Secure Encryption (USE) as an approach that applies different encryption schemes (with different security strength) to different parts of compressed video data. This USE scheme includes two parts: video data classification and unequal secure video data encryption. Firstly, we classify the video data into two partitions: Important data partition and unimportant data partition. Important data partition has small size with high secure protection, while unimportant data partition has large size with low secure protection. Secondly, we use AES as a block cipher to encrypt the important data partition and use LEX as a stream cipher to encrypt the unimportant data partition. AES is the most widely used symmetric cryptography which can ensure high security. LEX is a new stream cipher which is based on AES and its computational cost is much lower than AES. In this way, our scheme can achieve both high security and low computational cost. Besides the USE scheme, we propose a low cost design of hybrid AES/LEX encryption module. Our experimental results show that the computational cost of the USE scheme is low (about 25% of naive encryption at Level 0 with VEA used). The hardware cost for hybrid AES/LEX module is 4678 Gates and the AES encryption throughput is about 50Mbps.

  20. Prediction of cause of death from forensic autopsy reports using text classification techniques: A comparative study.

    Science.gov (United States)

    Mujtaba, Ghulam; Shuib, Liyana; Raj, Ram Gopal; Rajandram, Retnagowri; Shaikh, Khairunisa

    2018-07-01

    Automatic text classification techniques are useful for classifying plaintext medical documents. This study aims to automatically predict the cause of death from free text forensic autopsy reports by comparing various schemes for feature extraction, term weighing or feature value representation, text classification, and feature reduction. For experiments, the autopsy reports belonging to eight different causes of death were collected, preprocessed and converted into 43 master feature vectors using various schemes for feature extraction, representation, and reduction. The six different text classification techniques were applied on these 43 master feature vectors to construct a classification model that can predict the cause of death. Finally, classification model performance was evaluated using four performance measures i.e. overall accuracy, macro precision, macro-F-measure, and macro recall. From experiments, it was found that that unigram features obtained the highest performance compared to bigram, trigram, and hybrid-gram features. Furthermore, in feature representation schemes, term frequency, and term frequency with inverse document frequency obtained similar and better results when compared with binary frequency, and normalized term frequency with inverse document frequency. Furthermore, the chi-square feature reduction approach outperformed Pearson correlation, and information gain approaches. Finally, in text classification algorithms, support vector machine classifier outperforms random forest, Naive Bayes, k-nearest neighbor, decision tree, and ensemble-voted classifier. Our results and comparisons hold practical importance and serve as references for future works. Moreover, the comparison outputs will act as state-of-art techniques to compare future proposals with existing automated text classification techniques. Copyright © 2017 Elsevier Ltd and Faculty of Forensic and Legal Medicine. All rights reserved.

  1. Additive operator-difference schemes splitting schemes

    CERN Document Server

    Vabishchevich, Petr N

    2013-01-01

    Applied mathematical modeling isconcerned with solving unsteady problems. This bookshows how toconstruct additive difference schemes to solve approximately unsteady multi-dimensional problems for PDEs. Two classes of schemes are highlighted: methods of splitting with respect to spatial variables (alternating direction methods) and schemes of splitting into physical processes. Also regionally additive schemes (domain decomposition methods)and unconditionally stable additive schemes of multi-component splitting are considered for evolutionary equations of first and second order as well as for sy

  2. 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...

  3. A hybrid multibreath wash-in wash-out lung function quantification scheme in human subjects using hyperpolarized 3 He MRI for simultaneous assessment of specific ventilation, alveolar oxygen tension, oxygen uptake, and air trapping.

    Science.gov (United States)

    Hamedani, Hooman; Kadlecek, Stephen; Xin, Yi; Siddiqui, Sarmad; Gatens, Heather; Naji, Joseph; Ishii, Masaru; Cereda, Maurizio; Rossman, Milton; Rizi, Rahim

    2017-08-01

    To present a method for simultaneous acquisition of alveolar oxygen tension (P A O 2 ), specific ventilation (SV), and apparent diffusion coefficient (ADC) of hyperpolarized (HP) gas in the human lung, allowing reinterpretation of the P A O 2 and SV maps to produce a map of oxygen uptake (R). An imaging scheme was designed with a series of identical normoxic HP gas wash-in breaths to measure ADC, SV, P A O 2 , and R in less than 2 min. Signal dynamics were fit to an iterative recursive model that regionally solved for these parameters. This measurement was successfully performed in 12 subjects classified in three healthy, smoker, and chronic obstructive pulmonary disease (COPD) cohorts. The overall whole lung ADC, SV, P A O 2 , and R in healthy, smoker, and COPD subjects was 0.20 ± 0.03 cm 2 /s, 0.39 ± 0.06,113 ± 2 Torr, and 1.55 ± 0.35 Torr/s, respectively, in healthy subjects; 0.21 ± 0.03 cm 2 /s, 0.33 ± 0.06, 115.9 ± 4 Torr, and 0.97 ± 0.2 Torr/s, respectively, in smokers; and 0.25 ± 0.06 cm 2 /s, 0.23 ± 0.08, 114.8 ± 6.0Torr, and 0.94 ± 0.12 Torr/s, respectively, in subjects with COPD. Hetrogeneity of SV, P A O 2 , and R were indicators of both smoking-related changes and disease, and the severity of the disease correlated with the degree of this heterogeneity. Subjects with symptoms showed reduced oxygen uptake and specific ventilation. High-resolution, nearly coregistered and quantitative measures of lung function and structure were obtained with less than 1 L of HP gas. This hybrid multibreath technique produced measures of lung function that revealed clear differences among the cohorts and subjects and were confirmed by correlations with global lung measurements. Magn Reson Med 78:611-624, 2017. © 2016 International Society for Magnetic Resonance in Medicine. © 2016 International Society for Magnetic Resonance in Medicine.

  4. Decimal Classification Editions

    Directory of Open Access Journals (Sweden)

    Zenovia Niculescu

    2009-01-01

    Full Text Available The study approaches the evolution of Dewey Decimal Classification editions from the perspective of updating the terminology, reallocating and expanding the main and auxilary structure of Dewey indexing language. The comparative analysis of DDC editions emphasizes the efficiency of Dewey scheme from the point of view of improving the informational offer, through basic index terms, revised and developed, as well as valuing the auxilary notations.

  5. Decimal Classification Editions

    OpenAIRE

    Zenovia Niculescu

    2009-01-01

    The study approaches the evolution of Dewey Decimal Classification editions from the perspective of updating the terminology, reallocating and expanding the main and auxilary structure of Dewey indexing language. The comparative analysis of DDC editions emphasizes the efficiency of Dewey scheme from the point of view of improving the informational offer, through basic index terms, revised and developed, as well as valuing the auxilary notations.

  6. Glueballs, hybrids, multiquarks

    Energy Technology Data Exchange (ETDEWEB)

    Klempt, Eberhard [Helmholtz-Institut fuer Strahlen-und Kernphysik der Rheinischen Friedrich-Wilhelms Universitaet, Nussallee 14-16, D-53115 Bonn (Germany)], E-mail: klempt@hiskp.uni-bonn.de; Zaitsev, Alexander [Institute for High-Energy Physics, Moscow Region, RU-142284 Protvino (Russian Federation)

    2007-12-15

    Glueballs, hybrids and multiquark states are predicted as bound states in models guided by quantum chromo dynamics (QCD), by QCD sum rules or QCD on a lattice. Estimates for the (scalar) glueball ground state are in the mass range from 1000 to 1800 MeV, followed by a tensor and a pseudoscalar glueball at higher mass. Experiments have reported evidence for an abundance of meson resonances with 0{sup -+},0{sup ++} and 2{sup ++} quantum numbers. In particular, the sector of scalar mesons is full of surprises starting from the elusive {sigma} and {kappa} mesons. The a{sub 0}(980) and f{sub 0}(980), discussed extensively in the literature, are reviewed with emphasis on their Janus-like appearance as KK-bar molecules, tetraquark states or qq-bar mesons. Most exciting is the possibility that the three mesons f{sub 0}(1370), f{sub 0}(1500), and f{sub 0}(1710) might reflect the appearance of a scalar glueball in the world of quarkonia. However, the existence of f{sub 0}(1370) is not beyond doubt and there is evidence that both f{sub 0}(1500) and f{sub 0}(1710) are flavour octet states, possibly in a tetraquark composition. We suggest a scheme in which the scalar glueball is dissolved into the wide background into which all scalar flavour-singlet mesons collapse. There is an abundance of meson resonances with the quantum numbers of the {eta}. Three states are reported below 1.5GeV/c{sup 2} whereas quark models expect only one, perhaps two. One of these states, {iota}(1440), was the prime glueball candidate for a long time. We show that {iota}(1440) is the first radial excitation of the {eta} meson. Hybrids may have exotic quantum numbers which are not accessible by qq-bar mesons. There are several claims for J{sup PC}=1{sup -+} exotics, some of them with properties as predicted from the flux tube model interpreting the quark-antiquark binding by a gluon string. The evidence for these states depends partly on the assumption that meson-meson interactions are dominated by s

  7. Channel access delay and buffer distribution of two-user opportunistic scheduling schemes in wireless networks

    KAUST Repository

    Hossain, Md Jahangir; Alouini, Mohamed-Slim; Bhargava, Vijay K.

    2010-01-01

    In our earlier works, we proposed rate adaptive hierarchical modulation-assisted two-best user opportunistic scheduling (TBS) and hybrid two-user scheduling (HTS) schemes. The proposed schemes are innovative in the sense that they include a second

  8. Higher-Order Hybrid Gaussian Kernel in Meshsize Boosting Algorithm

    African Journals Online (AJOL)

    In this paper, we shall use higher-order hybrid Gaussian kernel in a meshsize boosting algorithm in kernel density estimation. Bias reduction is guaranteed in this scheme like other existing schemes but uses the higher-order hybrid Gaussian kernel instead of the regular fixed kernels. A numerical verification of this scheme ...

  9. Analysis of load balance in hybrid partitioning | Talib | Botswana ...

    African Journals Online (AJOL)

    In information retrieval systems, there are three types of index partitioning schemes - term partitioning, document partitioning, and hybrid partitioning. The hybrid-partitioning scheme combines both term and document partitioning schemes. Term partitioning provides high concurrency, which means that queries can be ...

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

    Science.gov (United States)

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

    2006-11-01

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

  11. Hybrid functional pseudopotentials

    Science.gov (United States)

    Yang, Jing; Tan, Liang Z.; Rappe, Andrew M.

    2018-02-01

    The consistency between the exchange-correlation functional used in pseudopotential construction and in the actual density functional theory calculation is essential for the accurate prediction of fundamental properties of materials. However, routine hybrid density functional calculations at present still rely on generalized gradient approximation pseudopotentials due to the lack of hybrid functional pseudopotentials. Here, we present a scheme for generating hybrid functional pseudopotentials, and we analyze the importance of pseudopotential density functional consistency for hybrid functionals. For the PBE0 hybrid functional, we benchmark our pseudopotentials for structural parameters and fundamental electronic gaps of the Gaussian-2 (G2) molecular dataset and some simple solids. Our results show that using our PBE0 pseudopotentials in PBE0 calculations improves agreement with respect to all-electron calculations.

  12. Four-state discrimination scheme beyond the heterodyne limit

    DEFF Research Database (Denmark)

    Muller, C. R.; Castaneda, Mario A. Usuga; Wittmann, C.

    2012-01-01

    We propose and experimentally demonstrate a hybrid discrimination scheme for the quadrature phase shift keying protocol, which outperforms heterodyne detection for any signal power. The discrimination is composed of a quadrature measurement, feed forward and photon detection.......We propose and experimentally demonstrate a hybrid discrimination scheme for the quadrature phase shift keying protocol, which outperforms heterodyne detection for any signal power. The discrimination is composed of a quadrature measurement, feed forward and photon detection....

  13. Optimal sampling schemes for vegetation and geological field visits

    CSIR Research Space (South Africa)

    Debba, Pravesh

    2012-07-01

    Full Text Available The presentation made to Wits Statistics Department was on common classification methods used in the field of remote sensing, and the use of remote sensing to design optimal sampling schemes for field visits with applications in vegetation...

  14. Land Cover - Minnesota Land Cover Classification System

    Data.gov (United States)

    Minnesota Department of Natural Resources — Land cover data set based on the Minnesota Land Cover Classification System (MLCCS) coding scheme. This data was produced using a combination of aerial photograph...

  15. Hybrid classification: the case of the acquisition procedure documentation within and ouside the Public Contracts information systems in Alto Adige Region

    Directory of Open Access Journals (Sweden)

    Francesca Delneri

    2017-05-01

    Full Text Available With reference to the acquisition procedures, the related documentation is created and managed mostly on the platform of the subcontracting institution, partly on the Alto Adige Public Sector Contracts information system. With a partial integration between this system and the platform made available by the Agenzia per i procedimenti e la vigilanza in materia di contratti pubblici di lavori, servizi e forniture, classification and filing information can be assigned to the documents coming from both platform, while the reunification of documents related to the same process is transferred to the preservation system as unique archive of the administration.

  16. Hybridized Tetraquarks

    CERN Document Server

    Esposito, A.; Polosa, A.D.

    2016-01-01

    We propose a new interpretation of the neutral and charged X, Z exotic hadron resonances. Hybridized-tetraquarks are neither purely compact tetraquark states nor bound or loosely bound molecules. The latter would require a negative or zero binding energy whose counterpart in h-tetraquarks is a positive quantity. The formation mechanism of this new class of hadrons is inspired by that of Feshbach metastable states in atomic physics. The recent claim of an exotic resonance in the Bs pi+- channel by the D0 collaboration and the negative result presented subsequently by the LHCb collaboration are understood in this scheme, together with a considerable portion of available data on X, Z particles. Considerations on a state with the same quantum numbers as the X(5568) are also made.

  17. A New Adaptive Hungarian Mating Scheme in Genetic Algorithms

    Directory of Open Access Journals (Sweden)

    Chanju Jung

    2016-01-01

    Full Text Available In genetic algorithms, selection or mating scheme is one of the important operations. In this paper, we suggest an adaptive mating scheme using previously suggested Hungarian mating schemes. Hungarian mating schemes consist of maximizing the sum of mating distances, minimizing the sum, and random matching. We propose an algorithm to elect one of these Hungarian mating schemes. Every mated pair of solutions has to vote for the next generation mating scheme. The distance between parents and the distance between parent and offspring are considered when they vote. Well-known combinatorial optimization problems, the traveling salesperson problem, and the graph bisection problem are used for the test bed of our method. Our adaptive strategy showed better results than not only pure and previous hybrid schemes but also existing distance-based mating schemes.

  18. A repeat-until-success quantum computing scheme

    Energy Technology Data Exchange (ETDEWEB)

    Beige, A [School of Physics and Astronomy, University of Leeds, Leeds LS2 9JT (United Kingdom); Lim, Y L [DSO National Laboratories, 20 Science Park Drive, Singapore 118230, Singapore (Singapore); Kwek, L C [Department of Physics, National University of Singapore, 2 Science Drive 3, Singapore 117542, Singapore (Singapore)

    2007-06-15

    Recently we proposed a hybrid architecture for quantum computing based on stationary and flying qubits: the repeat-until-success (RUS) quantum computing scheme. The scheme is largely implementation independent. Despite the incompleteness theorem for optical Bell-state measurements in any linear optics set-up, it allows for the implementation of a deterministic entangling gate between distant qubits. Here we review this distributed quantum computation scheme, which is ideally suited for integrated quantum computation and communication purposes.

  19. A repeat-until-success quantum computing scheme

    International Nuclear Information System (INIS)

    Beige, A; Lim, Y L; Kwek, L C

    2007-01-01

    Recently we proposed a hybrid architecture for quantum computing based on stationary and flying qubits: the repeat-until-success (RUS) quantum computing scheme. The scheme is largely implementation independent. Despite the incompleteness theorem for optical Bell-state measurements in any linear optics set-up, it allows for the implementation of a deterministic entangling gate between distant qubits. Here we review this distributed quantum computation scheme, which is ideally suited for integrated quantum computation and communication purposes

  20. [Susceptibility to strategy of the drug component of the IPHCC+RxGroups classification system in a risk-adjusted morbidity compensation scheme--a conceptional and data-supported analysis].

    Science.gov (United States)

    Behrend, C; Felder, S; Busse, R

    2007-01-01

    A report commissioned by the German Ministry of Health recommends to the existing scheme for calculating risk-adjusted transfers to sickness funds supplement with the IPHCC+RxGroups method. The method is based on inpatient diagnoses and prescribed drugs as health status measures deduced from prior use. The present study investigates the sickness fund's expected net return from gaming based on the drug component of the risk adjuster. The study explores three possible strategies using the RxGroups method. For the stimulations, insurees are assigned to additional indications or to higher valued RxGroups within the same indication. Then, costs and financial benefits attributable to the altered drug use are estimated and compared with the status quo. The study uses 2000 and 2001 sample data of more than 370,000 insurees of Germany's company-based sickness funds system (BKK). While upgrading increases overall costs, it can be beneficial for the individual sickness funds. Their net return crucially depends on the number of sickness funds gaming the system: the more participating in the game, the smaller is the average net return. Moreover, not participating often is even worse, which in turn points to a prisoner's dilemma. When extending the risk adjustment scheme in social health insurance, the German legislator should take into account the perverse incentives of risk adjusters such as the described prescription drug model.

  1. Mirror hybrid reactor optimization studies

    International Nuclear Information System (INIS)

    Bender, D.J.

    1976-01-01

    A system model of the mirror hybrid reactor has been developed. The major components of the model include (1) the reactor description, (2) a capital cost analysis, (3) various fuel management schemes, and (4) an economic analysis that includes the hybrid plus its associated fission burner reactors. The results presented describe the optimization of the mirror hybrid reactor, the objective being to minimize the cost of electricity from the hybrid fission-burner reactor complex. We have examined hybrid reactors with two types of blankets, one containing natural uranium, the other thorium. The major difference between the two optimized reactors is that the uranium hybrid is a significant net electrical power producer, whereas the thorium hybrid just about breaks even on electrical power. Our projected costs for fissile fuel production are approximately 50 $/g for 239 Pu and approximately 125 $/g for 233 U

  2. Automatic Hierarchical Color Image Classification

    Directory of Open Access Journals (Sweden)

    Jing Huang

    2003-02-01

    Full Text Available Organizing images into semantic categories can be extremely useful for content-based image retrieval and image annotation. Grouping images into semantic classes is a difficult problem, however. Image classification attempts to solve this hard problem by using low-level image features. In this paper, we propose a method for hierarchical classification of images via supervised learning. This scheme relies on using a good low-level feature and subsequently performing feature-space reconfiguration using singular value decomposition to reduce noise and dimensionality. We use the training data to obtain a hierarchical classification tree that can be used to categorize new images. Our experimental results suggest that this scheme not only performs better than standard nearest-neighbor techniques, but also has both storage and computational advantages.

  3. Finite Boltzmann schemes

    NARCIS (Netherlands)

    Sman, van der R.G.M.

    2006-01-01

    In the special case of relaxation parameter = 1 lattice Boltzmann schemes for (convection) diffusion and fluid flow are equivalent to finite difference/volume (FD) schemes, and are thus coined finite Boltzmann (FB) schemes. We show that the equivalence is inherent to the homology of the

  4. Classification of radioactive waste

    International Nuclear Information System (INIS)

    1994-01-01

    Radioactive wastes are generated in a number of different kinds of facilities and arise in a wide range of concentrations of radioactive materials and in a variety of physical and chemical forms. To simplify their management, a number of schemes have evolved for classifying radioactive waste according to the physical, chemical and radiological properties of significance to those facilities managing this waste. These schemes have led to a variety of terminologies, differing from country to country and even between facilities in the same country. This situation makes it difficult for those concerned to communicate with one another regarding waste management practices. This document revises and updates earlier IAEA references on radioactive waste classification systems given in IAEA Technical Reports Series and Safety Series. Guidance regarding exemption of materials from regulatory control is consistent with IAEA Safety Series and the RADWASS documents published under IAEA Safety Series. 11 refs, 2 figs, 2 tab

  5. Quadratically convergent MCSCF scheme using Fock operators

    International Nuclear Information System (INIS)

    Das, G.

    1981-01-01

    A quadratically convergent formulation of the MCSCF method using Fock operators is presented. Among its advantages the present formulation is quadratically convergent unlike the earlier ones based on Fock operators. In contrast to other quadratically convergent schemes as well as the one based on generalized Brillouin's theorem, this method leads easily to a hybrid scheme where the weakly coupled orbitals (such as the core) are handled purely by Fock equations, while the rest of the orbitals are treated by a quadratically convergent approach with a truncated virtual space obtained by the use of the corresponding Fock equations

  6. Prospects for Hybrid Breeding in Bioenergy Grasses

    DEFF Research Database (Denmark)

    Aguirre, Andrea Arias; Studer, Bruno; Frei, Ursula

    2012-01-01

    , we address crucial topics to implement hybrid breeding, such as the availability and development of heterotic groups, as well as biological mechanisms for hybridization control such as self-incompatibility (SI) and male sterility (MS). Finally, we present potential hybrid breeding schemes based on SI...... of different hybrid breeding schemes to optimally exploit heterosis for biomass yield in perennial ryegrass (Lolium perenne L.) and switchgrass (Panicum virgatum), two perennial model grass species for bioenergy production. Starting with a careful evaluation of current population and synthetic breeding methods...

  7. Elucidation of molecular kinetic schemes from macroscopic traces using system identification.

    Directory of Open Access Journals (Sweden)

    Miguel Fribourg

    2017-02-01

    Full Text Available Overall cellular responses to biologically-relevant stimuli are mediated by networks of simpler lower-level processes. Although information about some of these processes can now be obtained by visualizing and recording events at the molecular level, this is still possible only in especially favorable cases. Therefore the development of methods to extract the dynamics and relationships between the different lower-level (microscopic processes from the overall (macroscopic response remains a crucial challenge in the understanding of many aspects of physiology. Here we have devised a hybrid computational-analytical method to accomplish this task, the SYStems-based MOLecular kinetic scheme Extractor (SYSMOLE. SYSMOLE utilizes system-identification input-output analysis to obtain a transfer function between the stimulus and the overall cellular response in the Laplace-transformed domain. It then derives a Markov-chain state molecular kinetic scheme uniquely associated with the transfer function by means of a classification procedure and an analytical step that imposes general biological constraints. We first tested SYSMOLE with synthetic data and evaluated its performance in terms of its rate of convergence to the correct molecular kinetic scheme and its robustness to noise. We then examined its performance on real experimental traces by analyzing macroscopic calcium-current traces elicited by membrane depolarization. SYSMOLE derived the correct, previously known molecular kinetic scheme describing the activation and inactivation of the underlying calcium channels and correctly identified the accepted mechanism of action of nifedipine, a calcium-channel blocker clinically used in patients with cardiovascular disease. Finally, we applied SYSMOLE to study the pharmacology of a new class of glutamate antipsychotic drugs and their crosstalk mechanism through a heteromeric complex of G protein-coupled receptors. Our results indicate that our methodology

  8. Classification of Radioactive Waste. General Safety Guide

    International Nuclear Information System (INIS)

    2009-01-01

    This publication is a revision of an earlier Safety Guide of the same title issued in 1994. It recommends revised waste management strategies that reflect changes in practices and approaches since then. It sets out a classification system for the management of waste prior to disposal and for disposal, driven by long term safety considerations. It includes a number of schemes for classifying radioactive waste that can be used to assist with planning overall national approaches to radioactive waste management and to assist with operational management at facilities. Contents: 1. Introduction; 2. The radioactive waste classification scheme; Appendix: The classification of radioactive waste; Annex I: Evolution of IAEA standards on radioactive waste classification; Annex II: Methods of classification; Annex III: Origin and types of radioactive waste

  9. Classification of Radioactive Waste. General Safety Guide

    Energy Technology Data Exchange (ETDEWEB)

    NONE

    2009-11-15

    This publication is a revision of an earlier Safety Guide of the same title issued in 1994. It recommends revised waste management strategies that reflect changes in practices and approaches since then. It sets out a classification system for the management of waste prior to disposal and for disposal, driven by long term safety considerations. It includes a number of schemes for classifying radioactive waste that can be used to assist with planning overall national approaches to radioactive waste management and to assist with operational management at facilities. Contents: 1. Introduction; 2. The radioactive waste classification scheme; Appendix: The classification of radioactive waste; Annex I: Evolution of IAEA standards on radioactive waste classification; Annex II: Methods of classification; Annex III: Origin and types of radioactive waste.

  10. Hybrid cognitive engine for radio systems adaptation

    KAUST Repository

    Alqerm, Ismail; Shihada, Basem

    2017-01-01

    of our hybrid engine is validated using software defined radios implementation and simulation in multi-carrier environment. The system throughput, signal to noise and interference ratio, and packet error rate are obtained and compared with other schemes

  11. Discriminant forest classification method and system

    Science.gov (United States)

    Chen, Barry Y.; Hanley, William G.; Lemmond, Tracy D.; Hiller, Lawrence J.; Knapp, David A.; Mugge, Marshall J.

    2012-11-06

    A hybrid machine learning methodology and system for classification that combines classical random forest (RF) methodology with discriminant analysis (DA) techniques to provide enhanced classification capability. A DA technique which uses feature measurements of an object to predict its class membership, such as linear discriminant analysis (LDA) or Andersen-Bahadur linear discriminant technique (AB), is used to split the data at each node in each of its classification trees to train and grow the trees and the forest. When training is finished, a set of n DA-based decision trees of a discriminant forest is produced for use in predicting the classification of new samples of unknown class.

  12. Scheme Program Documentation Tools

    DEFF Research Database (Denmark)

    Nørmark, Kurt

    2004-01-01

    are separate and intended for different documentation purposes they are related to each other in several ways. Both tools are based on XML languages for tool setup and for documentation authoring. In addition, both tools rely on the LAML framework which---in a systematic way---makes an XML language available...... as named functions in Scheme. Finally, the Scheme Elucidator is able to integrate SchemeDoc resources as part of an internal documentation resource....

  13. Efficient Fingercode Classification

    Science.gov (United States)

    Sun, Hong-Wei; Law, Kwok-Yan; Gollmann, Dieter; Chung, Siu-Leung; Li, Jian-Bin; Sun, Jia-Guang

    In this paper, we present an efficient fingerprint classification algorithm which is an essential component in many critical security application systems e. g. systems in the e-government and e-finance domains. Fingerprint identification is one of the most important security requirements in homeland security systems such as personnel screening and anti-money laundering. The problem of fingerprint identification involves searching (matching) the fingerprint of a person against each of the fingerprints of all registered persons. To enhance performance and reliability, a common approach is to reduce the search space by firstly classifying the fingerprints and then performing the search in the respective class. Jain et al. proposed a fingerprint classification algorithm based on a two-stage classifier, which uses a K-nearest neighbor classifier in its first stage. The fingerprint classification algorithm is based on the fingercode representation which is an encoding of fingerprints that has been demonstrated to be an effective fingerprint biometric scheme because of its ability to capture both local and global details in a fingerprint image. We enhance this approach by improving the efficiency of the K-nearest neighbor classifier for fingercode-based fingerprint classification. Our research firstly investigates the various fast search algorithms in vector quantization (VQ) and the potential application in fingerprint classification, and then proposes two efficient algorithms based on the pyramid-based search algorithms in VQ. Experimental results on DB1 of FVC 2004 demonstrate that our algorithms can outperform the full search algorithm and the original pyramid-based search algorithms in terms of computational efficiency without sacrificing accuracy.

  14. Hybrid undulator numerical optimization

    Energy Technology Data Exchange (ETDEWEB)

    Hairetdinov, A.H. [Kurchatov Institute, Moscow (Russian Federation); Zukov, A.A. [Solid State Physics Institute, Chernogolovka (Russian Federation)

    1995-12-31

    3D properties of the hybrid undulator scheme arc studied numerically using PANDIRA code. It is shown that there exist two well defined sets of undulator parameters which provide either maximum on-axis field amplitude or minimal higher harmonics amplitude of the basic undulator field. Thus the alternative between higher field amplitude or pure sinusoidal field exists. The behavior of the undulator field amplitude and harmonics structure for a large set of (undulator gap)/(undulator wavelength) values is demonstrated.

  15. New guidelines for dam safety classification

    International Nuclear Information System (INIS)

    Dascal, O.

    1999-01-01

    Elements are outlined of recommended new guidelines for safety classification of dams. Arguments are provided for the view that dam classification systems should require more than one system as follows: (a) classification for selection of design criteria, operation procedures and emergency measures plans, based on potential consequences of a dam failure - the hazard classification of water retaining structures; (b) classification for establishment of surveillance activities and for safety evaluation of dams, based on the probability and consequences of failure - the risk classification of water retaining structures; and (c) classification for establishment of water management plans, for safety evaluation of the entire project, for preparation of emergency measures plans, for definition of the frequency and extent of maintenance operations, and for evaluation of changes and modifications required - the hazard classification of the project. The hazard classification of the dam considers, as consequence, mainly the loss of lives or persons in jeopardy and the property damages to third parties. Difficulties in determining the risk classification of the dam lie in the fact that no tool exists to evaluate the probability of the dam's failure. To overcome this, the probability of failure can be substituted for by a set of dam characteristics that express the failure potential of the dam and its foundation. The hazard classification of the entire project is based on the probable consequences of dam failure influencing: loss of life, persons in jeopardy, property and environmental damage. The classification scheme is illustrated for dam threatening events such as earthquakes and floods. 17 refs., 5 tabs

  16. Multiresolution signal decomposition schemes

    NARCIS (Netherlands)

    J. Goutsias (John); H.J.A.M. Heijmans (Henk)

    1998-01-01

    textabstract[PNA-R9810] Interest in multiresolution techniques for signal processing and analysis is increasing steadily. An important instance of such a technique is the so-called pyramid decomposition scheme. This report proposes a general axiomatic pyramid decomposition scheme for signal analysis

  17. Face recognition: database acquisition, hybrid algorithms, and human studies

    Science.gov (United States)

    Gutta, Srinivas; Huang, Jeffrey R.; Singh, Dig; Wechsler, Harry

    1997-02-01

    One of the most important technologies absent in traditional and emerging frontiers of computing is the management of visual information. Faces are accessible `windows' into the mechanisms that govern our emotional and social lives. The corresponding face recognition tasks considered herein include: (1) Surveillance, (2) CBIR, and (3) CBIR subject to correct ID (`match') displaying specific facial landmarks such as wearing glasses. We developed robust matching (`classification') and retrieval schemes based on hybrid classifiers and showed their feasibility using the FERET database. The hybrid classifier architecture consist of an ensemble of connectionist networks--radial basis functions-- and decision trees. The specific characteristics of our hybrid architecture include (a) query by consensus as provided by ensembles of networks for coping with the inherent variability of the image formation and data acquisition process, and (b) flexible and adaptive thresholds as opposed to ad hoc and hard thresholds. Experimental results, proving the feasibility of our approach, yield (i) 96% accuracy, using cross validation (CV), for surveillance on a data base consisting of 904 images (ii) 97% accuracy for CBIR tasks, on a database of 1084 images, and (iii) 93% accuracy, using CV, for CBIR subject to correct ID match tasks on a data base of 200 images.

  18. Adaptive protection scheme

    Directory of Open Access Journals (Sweden)

    R. Sitharthan

    2016-09-01

    Full Text Available This paper aims at modelling an electronically coupled distributed energy resource with an adaptive protection scheme. The electronically coupled distributed energy resource is a microgrid framework formed by coupling the renewable energy source electronically. Further, the proposed adaptive protection scheme provides a suitable protection to the microgrid for various fault conditions irrespective of the operating mode of the microgrid: namely, grid connected mode and islanded mode. The outstanding aspect of the developed adaptive protection scheme is that it monitors the microgrid and instantly updates relay fault current according to the variations that occur in the system. The proposed adaptive protection scheme also employs auto reclosures, through which the proposed adaptive protection scheme recovers faster from the fault and thereby increases the consistency of the microgrid. The effectiveness of the proposed adaptive protection is studied through the time domain simulations carried out in the PSCAD⧹EMTDC software environment.

  19. Overview of hybrid electric vehicle trend

    Science.gov (United States)

    Wang, Haomiao; Yang, Weidong; Chen, Yingshu; Wang, Yun

    2018-04-01

    With the increase of per capita energy consumption, environmental pollution is worsening. Using new alternative sources of energy, reducing the use of conventional fuel-powered engines is imperative. Due to the short period, pure electric vehicles cannot be mass-produced and there are many problems such as imperfect charging facilities. Therefore, the development of hybrid electric vehicles is particularly important in a certain period. In this paper, the classification of hybrid vehicle, research status of hybrid vehicle and future development trends of hybrid vehicles is introduced. It is conducive to the public understanding of hybrid electric vehicles, which has a certain theoretical significance.

  20. The Net Enabled Waste Management Database in the context of radioactive waste classification

    International Nuclear Information System (INIS)

    Csullog, G.W.; Burcl, R.; Tonkay, D.; Petoe, A.

    2002-01-01

    There is an emerging, international consensus that a common, comprehensive radioactive waste classification system is needed, which derives from the fact that the implementation of radioactive waste classification within countries is highly diverse. Within IAEA Member States, implementation ranges from none to complex systems that vary a great deal from one another. Both the IAEA and the European Commission have recommended common classification schemes but only for the purpose of facilitating communication with the public and national- and international-level organizations and to serve as the basis for developing comprehensive, national waste classification schemes. In the context described above, the IAEA's newly developed Net Enabled Waste Management Database (NEWMDB) contains a feature, the Waste Class Matrix, that Member States use to describe the waste classification schemes they use and to compare them with the IAEA's proposed waste classification scheme. Member States then report waste inventories to the NEWMDB according to their own waste classification schemes, allowing traceability back to nationally based reports. The IAEA uses the information provided in the Waste Class Matrix to convert radioactive waste inventory data reported according to a wide variety of classifications into an single inventory according to the IAEA's proposed scheme. This approach allows the international community time to develop a comprehensive, common classification scheme and allows Member States time to develop and implement effective, operational waste classification schemes while, at the same time, the IAEA can collect the information needed to compile a comprehensive, international radioactive waste inventory. (author)

  1. Tissue Classification

    DEFF Research Database (Denmark)

    Van Leemput, Koen; Puonti, Oula

    2015-01-01

    Computational methods for automatically segmenting magnetic resonance images of the brain have seen tremendous advances in recent years. So-called tissue classification techniques, aimed at extracting the three main brain tissue classes (white matter, gray matter, and cerebrospinal fluid), are now...... well established. In their simplest form, these methods classify voxels independently based on their intensity alone, although much more sophisticated models are typically used in practice. This article aims to give an overview of often-used computational techniques for brain tissue classification...

  2. KNN BASED CLASSIFICATION OF DIGITAL MODULATED SIGNALS

    Directory of Open Access Journals (Sweden)

    Sajjad Ahmed Ghauri

    2016-11-01

    Full Text Available Demodulation process without the knowledge of modulation scheme requires Automatic Modulation Classification (AMC. When receiver has limited information about received signal then AMC become essential process. AMC finds important place in the field many civil and military fields such as modern electronic warfare, interfering source recognition, frequency management, link adaptation etc. In this paper we explore the use of K-nearest neighbor (KNN for modulation classification with different distance measurement methods. Five modulation schemes are used for classification purpose which is Binary Phase Shift Keying (BPSK, Quadrature Phase Shift Keying (QPSK, Quadrature Amplitude Modulation (QAM, 16-QAM and 64-QAM. Higher order cummulants (HOC are used as an input feature set to the classifier. Simulation results shows that proposed classification method provides better results for the considered modulation formats.

  3. Detecting Urban Transport Modes Using a Hybrid Knowledge Driven Framework from GPS Trajectory

    Directory of Open Access Journals (Sweden)

    Rahul Deb Das

    2016-11-01

    Full Text Available Transport mode information is essential for understanding people’s movement behavior and travel demand estimation. Current approaches extract travel information once the travel is complete. Such approaches are limited in terms of generating just-in-time information for a number of mobility based applications, e.g., real time mode specific patronage estimation. In order to detect the transport modalities from GPS trajectories, various machine learning approaches have already been explored. However, the majority of them produce only a single conclusion from a given set of evidences, ignoring the uncertainty of any mode classification. Also, the existing machine learning approaches fall short in explaining their reasoning scheme. In contrast, a fuzzy expert system can explain its reasoning scheme in a human readable format along with a provision of inferring different outcome possibilities, but lacks the adaptivity and learning ability of machine learning. In this paper, a novel hybrid knowledge driven framework is developed by integrating a fuzzy logic and a neural network to complement each other’s limitations. Thus the aim of this paper is to automate the tuning process in order to generate an intelligent hybrid model that can perform effectively in near-real time mode detection using GPS trajectory. Tests demonstrate that a hybrid knowledge driven model works better than a purely knowledge driven model and at per the machine learning models in the context of transport mode detection.

  4. Threshold Signature Schemes Application

    Directory of Open Access Journals (Sweden)

    Anastasiya Victorovna Beresneva

    2015-10-01

    Full Text Available This work is devoted to an investigation of threshold signature schemes. The systematization of the threshold signature schemes was done, cryptographic constructions based on interpolation Lagrange polynomial, elliptic curves and bilinear pairings were examined. Different methods of generation and verification of threshold signatures were explored, the availability of practical usage of threshold schemes in mobile agents, Internet banking and e-currency was shown. The topics of further investigation were given and it could reduce a level of counterfeit electronic documents signed by a group of users.

  5. Ototoxicity (cochleotoxicity) classifications: A review.

    Science.gov (United States)

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

    2016-01-01

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

  6. Hybrid Semantic Analysis of Tweets: A Case Study of Tweets on Girl-Child in India

    Directory of Open Access Journals (Sweden)

    M. Madhukar

    2017-10-01

    Full Text Available Social networks have become one of the major and important parts of daily life. Besides sharing ones views the social networking sites can also be very efficiently used to judge the behavior and attitude of individuals towards the posts. Analysis of the mood of public on a particular social issue can be judged by several methods. Analysis of the society mood towards any particular news in form of tweets is investigated in this paper. The key objective behind this research is to increase the accuracy and effectiveness of the classification by the process of Natural Language Processing (NLP Techniques while focusing on semantics and World Sense Disambiguation. The process of classification includes the combination of the effect of various independent classifiers on one particular classification problem. The data that is available in the form of tweets on twitter can easily frame the insight of the public attitude towards the particular tweet. The proposed work implements a hybrid method that includes Hybrid K, clustering and boosting. A comparison of this scheme versus a K-means/SVM approach is provided. Results are shown and discussed.

  7. Oral epithelial dysplasia classification systems

    DEFF Research Database (Denmark)

    Warnakulasuriya, S; Reibel, J; Bouquot, J

    2008-01-01

    At a workshop coordinated by the WHO Collaborating Centre for Oral Cancer and Precancer in the United Kingdom issues related to potentially malignant disorders of the oral cavity were discussed by an expert group. The consensus views of the Working Group are presented in a series of papers....... In this report, we review the oral epithelial dysplasia classification systems. The three classification schemes [oral epithelial dysplasia scoring system, squamous intraepithelial neoplasia and Ljubljana classification] were presented and the Working Group recommended epithelial dysplasia grading for routine...... use. Although most oral pathologists possibly recognize and accept the criteria for grading epithelial dysplasia, firstly based on architectural features and then of cytology, there is great variability in their interpretation of the presence, degree and significance of the individual criteria...

  8. Transporter Classification Database (TCDB)

    Data.gov (United States)

    U.S. Department of Health & Human Services — The Transporter Classification Database details a comprehensive classification system for membrane transport proteins known as the Transporter Classification (TC)...

  9. CSR schemes in agribusiness

    DEFF Research Database (Denmark)

    Pötz, Katharina Anna; Haas, Rainer; Balzarova, Michaela

    2013-01-01

    of schemes that can be categorized on focus areas, scales, mechanisms, origins, types and commitment levels. Research limitations/implications – The findings contribute to conceptual and empirical research on existing models to compare and analyse CSR standards. Sampling technique and depth of analysis limit......Purpose – The rise of CSR followed a demand for CSR standards and guidelines. In a sector already characterized by a large number of standards, the authors seek to ask what CSR schemes apply to agribusiness, and how they can be systematically compared and analysed. Design....../methodology/approach – Following a deductive-inductive approach the authors develop a model to compare and analyse CSR schemes based on existing studies and on coding qualitative data on 216 CSR schemes. Findings – The authors confirm that CSR standards and guidelines have entered agribusiness and identify a complex landscape...

  10. Tabled Execution in Scheme

    Energy Technology Data Exchange (ETDEWEB)

    Willcock, J J; Lumsdaine, A; Quinlan, D J

    2008-08-19

    Tabled execution is a generalization of memorization developed by the logic programming community. It not only saves results from tabled predicates, but also stores the set of currently active calls to them; tabled execution can thus provide meaningful semantics for programs that seemingly contain infinite recursions with the same arguments. In logic programming, tabled execution is used for many purposes, both for improving the efficiency of programs, and making tasks simpler and more direct to express than with normal logic programs. However, tabled execution is only infrequently applied in mainstream functional languages such as Scheme. We demonstrate an elegant implementation of tabled execution in Scheme, using a mix of continuation-passing style and mutable data. We also show the use of tabled execution in Scheme for a problem in formal language and automata theory, demonstrating that tabled execution can be a valuable tool for Scheme users.

  11. Evaluating statistical cloud schemes

    OpenAIRE

    Grützun, Verena; Quaas, Johannes; Morcrette , Cyril J.; Ament, Felix

    2015-01-01

    Statistical cloud schemes with prognostic probability distribution functions have become more important in atmospheric modeling, especially since they are in principle scale adaptive and capture cloud physics in more detail. While in theory the schemes have a great potential, their accuracy is still questionable. High-resolution three-dimensional observational data of water vapor and cloud water, which could be used for testing them, are missing. We explore the potential of ground-based re...

  12. Gamma spectrometry; level schemes

    International Nuclear Information System (INIS)

    Blachot, J.; Bocquet, J.P.; Monnand, E.; Schussler, F.

    1977-01-01

    The research presented dealt with: a new beta emitter, isomer of 131 Sn; the 136 I levels fed through the radioactive decay of 136 Te (20.9s); the A=145 chain (β decay of Ba, La and Ce, and level schemes for 145 La, 145 Ce, 145 Pr); the A=47 chain (La and Ce, β decay, and the level schemes of 147 Ce and 147 Pr) [fr

  13. Scheme of energy utilities

    International Nuclear Information System (INIS)

    2002-04-01

    This scheme defines the objectives relative to the renewable energies and the rational use of the energy in the framework of the national energy policy. It evaluates the needs and the potentialities of the regions and preconizes the actions between the government and the territorial organizations. The document is presented in four parts: the situation, the stakes and forecasts; the possible actions for new measures; the scheme management and the regional contributions analysis. (A.L.B.)

  14. Position list word aligned hybrid

    DEFF Research Database (Denmark)

    Deliege, Francois; Pedersen, Torben Bach

    2010-01-01

    Compressed bitmap indexes are increasingly used for efficiently querying very large and complex databases. The Word Aligned Hybrid (WAH) bitmap compression scheme is commonly recognized as the most efficient compression scheme in terms of CPU efficiency. However, WAH compressed bitmaps use a lot...... of storage space. This paper presents the Position List Word Aligned Hybrid (PLWAH) compression scheme that improves significantly over WAH compression by better utilizing the available bits and new CPU instructions. For typical bit distributions, PLWAH compressed bitmaps are often half the size of WAH...... bitmaps and, at the same time, offer an even better CPU efficiency. The results are verified by theoretical estimates and extensive experiments on large amounts of both synthetic and real-world data....

  15. Designing Z-scheme 2D-C{sub 3}N{sub 4}/Ag{sub 3}VO{sub 4} hybrid structures for improved photocatalysis and photocatalytic mechanism insight

    Energy Technology Data Exchange (ETDEWEB)

    She, Xiaojie; Yi, Jianjian; Xu, Yuanguo; Huang, Liying; Ji, Haiyan; Xu, Hui; Li, Huaming [School of the Environment and Safety Engineering, Institute for Energy Research, Jiangsu University, Zhenjiang 212013 (China); Song, Yanhua [School of Environmental and Chemical, Engineering, Jiangsu University of Science and Technology, Zhenjiang 212003 (China)

    2017-06-15

    The two-dimensional oxygen-modified g-C{sub 3}N{sub 4} nanosheets-loaded Ag{sub 3}VO{sub 4} (2D-C{sub 3}N{sub 4}/Ag{sub 3}VO{sub 4}) photocatalysts were synthesized successfully via a facile in situ deposition method. The comprehensive characterizations were employed to characterize the morphologies, structures, chemical states, optical and electronic properties and photocatalytic performances of the samples. The 20% 2D-C{sub 3}N{sub 4}/Ag{sub 3}VO{sub 4} showed the best photocatalytic activity on the degradation of RhB and BPA. The enhanced photocatalytic activity is ascribed to the effective electron-hole separation efficiency and the larger specific surface area. The photogenerated electrons and holes can quickly separate by Z-scheme passageway in composite. Through ESR analysis, the photocatalytic mechanism was also researched in detail. (copyright 2017 WILEY-VCH Verlag GmbH and Co. KGaA, Weinheim)

  16. A circulation classification scheme applicable in GSM studies

    Czech Academy of Sciences Publication Activity Database

    Huth, Radan

    2000-01-01

    Roč. 67, - (2000), s. 1-18 ISSN 0177-798X R&D Projects: GA ČR GA205/96/1670; GA ČR GA205/99/1561 Institutional research plan: CEZ:AV0Z3042911 Subject RIV: DG - Athmosphere Sciences, Meteorology Impact factor: 0.832, year: 2000

  17. Development of a Regional Habitat Classification Scheme for the ...

    African Journals Online (AJOL)

    A collaborative expedition between Khaled bin Sultan Living Oceans Foundation, Cambridge Coastal Research Unit and Seychelles Centre for Marine Research and Technology – Marine Parks Authority (SCMRT-MPA) was conducted to the southern Seychelles, western Indian Ocean, in January 2005. This resulted in a ...

  18. Soil Suitability Classification of Tomas Irrigation Scheme for Irrigated ...

    African Journals Online (AJOL)

    The need for sustainable rice production in Nigeria cannot be over-emphasized. Since rice can be grown both under rain-fed and irrigated conditions, the need for soil suitability evaluation becomes very necessary in order for supply to meet up with demand. Six land qualities viz; climate, soil physical properties, drainage, ...

  19. Investigation into Text Classification With Kernel Based Schemes

    Science.gov (United States)

    2010-03-01

    Document Matrix TDMs Term-Document Matrices TMG Text to Matrix Generator TN True Negative TP True Positive VSM Vector Space Model xxii THIS PAGE...are represented as a term-document matrix, common evaluation metrics, and the software package Text to Matrix Generator ( TMG ). The classifier...AND METRICS This chapter introduces the indexing capabilities of the Text to Matrix Generator ( TMG ) Toolbox. Specific attention is placed on the

  20. limit and complete classification of symmetry schemes in proton ...

    Indian Academy of Sciences (India)

    Proton–neutron interacting boson model; pnIBM; symmetry limits; complete classifica- tion; F spin; F spin .... Dynamical symmetry limits of pnIBM correspond to the group chains starting withU(12) generating N ...... value must be. MFs = MF MFd.

  1. The Software Invention Cube: A classification scheme for software inventions

    NARCIS (Netherlands)

    Bergstra, J.A.; Klint, P.

    2008-01-01

    The patent system protects inventions. The requirement that a software invention should make ‘a technical contribution’ turns out to be untenable in practice and this raises the question, what constitutes an invention in the realm of software. The authors developed the Software Invention Cube

  2. Dose classification scheme for computed tomography of the paranasal sinuses

    International Nuclear Information System (INIS)

    Hojreh, A.; Czerny, C.; Kainberger, F.

    2005-01-01

    Purpose: The purpose of this study was to define objective and reproducible standards for the quality of CT images as a function of radiation doses and therapeutic validity. Materials and methods: CT images of the paranasal sinuses of 145 patients (77 female, 68 male; 5-83 years old; mean age, 39.9 years) were classified both subjectively (with a view toward their validity for the planning of functional endoscopic sinus surgery, FESS) and objectively by defining the pixel noise (the standard deviation, STD, of the CT number) in a homogeneous region of interest (ROI), centered on the M. masseter and on the frontal lobe. These measurements were then compared to measurements obtained from scan images of a water-filled Perspex phantom. Results: The pixel noise measured in the phantom images was nearly identical to the respective values on the M. masseter on the patient images. The use of an edge-enhancing reconstruction algorithm and low-dose protocols, with a pixel noise amounting to 70-90 Hounsfield Units (HU), are indicated for children, chronic sinusitis, and septum deviation, while standard protocols, with a pixel noise of 50-70 HU, are recommended for the preoperative planning and postoperative control of FESS. The pixel noise for high-dose protocols is less than 50 HU; nonetheless, such protocols should generally be avoided. Conclusion: The pixel noise measured in a water-filled Perspex phantom is indicative of the clinical potential and image quality of paranasal sinus CT scans. Alternatively, the M. masseter can be chosen as an ROI to measure the pixel noise in order to obtain a rough estimate of the image quality or radiation dose class

  3. Collaborative Multi-Layer Network Coding in Hybrid Cellular Cognitive Radio Networks

    KAUST Repository

    Moubayed, Abdallah J.; Sorour, Sameh; Al-Naffouri, Tareq Y.; Alouini, Mohamed-Slim

    2015-01-01

    In this paper, as an extension to [1], we propose a prioritized multi-layer network coding scheme for collaborative packet recovery in hybrid (interweave and underlay) cellular cognitive radio networks. This scheme allows the uncoordinated

  4. Collaborative Multi-Layer Network Coding For Hybrid Cellular Cognitive Radio Networks

    KAUST Repository

    Moubayed, Abdallah J.

    2014-01-01

    In this thesis, as an extension to [1], we propose a prioritized multi-layer network coding scheme for collaborative packet recovery in hybrid (interweave and underlay) cellular cognitive radio networks. This scheme allows the uncoordinated

  5. A Semisupervised Cascade Classification Algorithm

    Directory of Open Access Journals (Sweden)

    Stamatis Karlos

    2016-01-01

    Full Text Available Classification is one of the most important tasks of data mining techniques, which have been adopted by several modern applications. The shortage of enough labeled data in the majority of these applications has shifted the interest towards using semisupervised methods. Under such schemes, the use of collected unlabeled data combined with a clearly smaller set of labeled examples leads to similar or even better classification accuracy against supervised algorithms, which use labeled examples exclusively during the training phase. A novel approach for increasing semisupervised classification using Cascade Classifier technique is presented in this paper. The main characteristic of Cascade Classifier strategy is the use of a base classifier for increasing the feature space by adding either the predicted class or the probability class distribution of the initial data. The classifier of the second level is supplied with the new dataset and extracts the decision for each instance. In this work, a self-trained NB∇C4.5 classifier algorithm is presented, which combines the characteristics of Naive Bayes as a base classifier and the speed of C4.5 for final classification. We performed an in-depth comparison with other well-known semisupervised classification methods on standard benchmark datasets and we finally reached to the point that the presented technique has better accuracy in most cases.

  6. Towards Symbolic Encryption Schemes

    DEFF Research Database (Denmark)

    Ahmed, Naveed; Jensen, Christian D.; Zenner, Erik

    2012-01-01

    , namely an authenticated encryption scheme that is secure under chosen ciphertext attack. Therefore, many reasonable encryption schemes, such as AES in the CBC or CFB mode, are not among the implementation options. In this paper, we report new attacks on CBC and CFB based implementations of the well......Symbolic encryption, in the style of Dolev-Yao models, is ubiquitous in formal security models. In its common use, encryption on a whole message is specified as a single monolithic block. From a cryptographic perspective, however, this may require a resource-intensive cryptographic algorithm......-known Needham-Schroeder and Denning-Sacco protocols. To avoid such problems, we advocate the use of refined notions of symbolic encryption that have natural correspondence to standard cryptographic encryption schemes....

  7. Compact Spreader Schemes

    Energy Technology Data Exchange (ETDEWEB)

    Placidi, M.; Jung, J. -Y.; Ratti, A.; Sun, C.

    2014-07-25

    This paper describes beam distribution schemes adopting a novel implementation based on low amplitude vertical deflections combined with horizontal ones generated by Lambertson-type septum magnets. This scheme offers substantial compactness in the longitudinal layouts of the beam lines and increased flexibility for beam delivery of multiple beam lines on a shot-to-shot basis. Fast kickers (FK) or transverse electric field RF Deflectors (RFD) provide the low amplitude deflections. Initially proposed at the Stanford Linear Accelerator Center (SLAC) as tools for beam diagnostics and more recently adopted for multiline beam pattern schemes, RFDs offer repetition capabilities and a likely better amplitude reproducibility when compared to FKs, which, in turn, offer more modest financial involvements both in construction and operation. Both solutions represent an ideal approach for the design of compact beam distribution systems resulting in space and cost savings while preserving flexibility and beam quality.

  8. Adaptive transmission schemes for MISO spectrum sharing systems

    KAUST Repository

    Bouida, Zied

    2013-06-01

    We propose three adaptive transmission techniques aiming to maximize the capacity of a multiple-input-single-output (MISO) secondary system under the scenario of an underlay cognitive radio network. In the first scheme, namely the best antenna selection (BAS) scheme, the antenna maximizing the capacity of the secondary link is used for transmission. We then propose an orthogonal space time bloc code (OSTBC) transmission scheme using the Alamouti scheme with transmit antenna selection (TAS), namely the TAS/STBC scheme. The performance improvement offered by this scheme comes at the expense of an increased complexity and delay when compared to the BAS scheme. As a compromise between these schemes, we propose a hybrid scheme using BAS when only one antenna verifies the interference condition and TAS/STBC when two or more antennas are illegible for communication. We first derive closed-form expressions of the statistics of the received signal-to-interference-and-noise ratio (SINR) at the secondary receiver (SR). These results are then used to analyze the performance of the proposed techniques in terms of the average spectral efficiency, the average number of transmit antennas, and the average bit error rate (BER). This performance is then illustrated via selected numerical examples. © 2013 IEEE.

  9. A Hybrid ICA-SVM Approach for Determining the Quality Variables at Fault in a Multivariate Process

    Directory of Open Access Journals (Sweden)

    Yuehjen E. Shao

    2012-01-01

    Full Text Available The monitoring of a multivariate process with the use of multivariate statistical process control (MSPC charts has received considerable attention. However, in practice, the use of MSPC chart typically encounters a difficulty. This difficult involves which quality variable or which set of the quality variables is responsible for the generation of the signal. This study proposes a hybrid scheme which is composed of independent component analysis (ICA and support vector machine (SVM to determine the fault quality variables when a step-change disturbance existed in a multivariate process. The proposed hybrid ICA-SVM scheme initially applies ICA to the Hotelling T2 MSPC chart to generate independent components (ICs. The hidden information of the fault quality variables can be identified in these ICs. The ICs are then served as the input variables of the classifier SVM for performing the classification process. The performance of various process designs is investigated and compared with the typical classification method. Using the proposed approach, the fault quality variables for a multivariate process can be accurately and reliably determined.

  10. A method to incorporate uncertainty in the classification of remote sensing images

    OpenAIRE

    Gonçalves, Luísa M. S.; Fonte, Cidália C.; Júlio, Eduardo N. B. S.; Caetano, Mario

    2009-01-01

    The aim of this paper is to investigate if the incorporation of the uncertainty associated with the classification of surface elements into the classification of landscape units (LUs) increases the results accuracy. To this end, a hybrid classification method is developed, including uncertainty information in the classification of very high spatial resolution multi-spectral satellite images, to obtain a map of LUs. The developed classification methodology includes the following...

  11. New analytic unitarization schemes

    International Nuclear Information System (INIS)

    Cudell, J.-R.; Predazzi, E.; Selyugin, O. V.

    2009-01-01

    We consider two well-known classes of unitarization of Born amplitudes of hadron elastic scattering. The standard class, which saturates at the black-disk limit includes the standard eikonal representation, while the other class, which goes beyond the black-disk limit to reach the full unitarity circle, includes the U matrix. It is shown that the basic properties of these schemes are independent of the functional form used for the unitarization, and that U matrix and eikonal schemes can be extended to have similar properties. A common form of unitarization is proposed interpolating between both classes. The correspondence with different nonlinear equations are also briefly examined.

  12. Functional Basis of Microorganism Classification.

    Science.gov (United States)

    Zhu, Chengsheng; Delmont, Tom O; Vogel, Timothy M; Bromberg, Yana

    2015-08-01

    Correctly identifying nearest "neighbors" of a given microorganism is important in industrial and clinical applications where close relationships imply similar treatment. Microbial classification based on similarity of physiological and genetic organism traits (polyphasic similarity) is experimentally difficult and, arguably, subjective. Evolutionary relatedness, inferred from phylogenetic markers, facilitates classification but does not guarantee functional identity between members of the same taxon or lack of similarity between different taxa. Using over thirteen hundred sequenced bacterial genomes, we built a novel function-based microorganism classification scheme, functional-repertoire similarity-based organism network (FuSiON; flattened to fusion). Our scheme is phenetic, based on a network of quantitatively defined organism relationships across the known prokaryotic space. It correlates significantly with the current taxonomy, but the observed discrepancies reveal both (1) the inconsistency of functional diversity levels among different taxa and (2) an (unsurprising) bias towards prioritizing, for classification purposes, relatively minor traits of particular interest to humans. Our dynamic network-based organism classification is independent of the arbitrary pairwise organism similarity cut-offs traditionally applied to establish taxonomic identity. Instead, it reveals natural, functionally defined organism groupings and is thus robust in handling organism diversity. Additionally, fusion can use organism meta-data to highlight the specific environmental factors that drive microbial diversification. Our approach provides a complementary view to cladistic assignments and holds important clues for further exploration of microbial lifestyles. Fusion is a more practical fit for biomedical, industrial, and ecological applications, as many of these rely on understanding the functional capabilities of the microbes in their environment and are less concerned with

  13. Functional Basis of Microorganism Classification

    Science.gov (United States)

    Zhu, Chengsheng; Delmont, Tom O.; Vogel, Timothy M.; Bromberg, Yana

    2015-01-01

    Correctly identifying nearest “neighbors” of a given microorganism is important in industrial and clinical applications where close relationships imply similar treatment. Microbial classification based on similarity of physiological and genetic organism traits (polyphasic similarity) is experimentally difficult and, arguably, subjective. Evolutionary relatedness, inferred from phylogenetic markers, facilitates classification but does not guarantee functional identity between members of the same taxon or lack of similarity between different taxa. Using over thirteen hundred sequenced bacterial genomes, we built a novel function-based microorganism classification scheme, functional-repertoire similarity-based organism network (FuSiON; flattened to fusion). Our scheme is phenetic, based on a network of quantitatively defined organism relationships across the known prokaryotic space. It correlates significantly with the current taxonomy, but the observed discrepancies reveal both (1) the inconsistency of functional diversity levels among different taxa and (2) an (unsurprising) bias towards prioritizing, for classification purposes, relatively minor traits of particular interest to humans. Our dynamic network-based organism classification is independent of the arbitrary pairwise organism similarity cut-offs traditionally applied to establish taxonomic identity. Instead, it reveals natural, functionally defined organism groupings and is thus robust in handling organism diversity. Additionally, fusion can use organism meta-data to highlight the specific environmental factors that drive microbial diversification. Our approach provides a complementary view to cladistic assignments and holds important clues for further exploration of microbial lifestyles. Fusion is a more practical fit for biomedical, industrial, and ecological applications, as many of these rely on understanding the functional capabilities of the microbes in their environment and are less concerned

  14. Dissimilarity-based classification of anatomical tree structures

    DEFF Research Database (Denmark)

    Sørensen, Lauge; Lo, Pechin Chien Pau; Dirksen, Asger

    2011-01-01

    A novel method for classification of abnormality in anatomical tree structures is presented. A tree is classified based on direct comparisons with other trees in a dissimilarity-based classification scheme. The pair-wise dissimilarity measure between two trees is based on a linear assignment betw...

  15. Dissimilarity-based classification of anatomical tree structures

    DEFF Research Database (Denmark)

    Sørensen, Lauge Emil Borch Laurs; Lo, Pechin Chien Pau; Dirksen, Asger

    2011-01-01

    A novel method for classification of abnormality in anatomical tree structures is presented. A tree is classified based on direct comparisons with other trees in a dissimilarity-based classification scheme. The pair-wise dissimilarity measure between two trees is based on a linear assignment...

  16. Classification of Ship Routing and Scheduling Problems in Liner Shipping

    DEFF Research Database (Denmark)

    Kjeldsen, Karina Hjortshøj

    2011-01-01

    This article provides a classification scheme for ship routing and scheduling problems in liner shipping in line with the current and future operational conditions of the liner shipping industry. Based on the classification, the literature is divided into groups whose main characteristics...

  17. Dewey Decimal Classification for U. S. Conn: An Advantage?

    Science.gov (United States)

    Marek, Kate

    This paper examines the use of the Dewey Decimal Classification (DDC) system at the U. S. Conn Library at Wayne State College (WSC) in Nebraska. Several developments in the last 20 years which have eliminated the trend toward reclassification of academic library collections from DDC to the Library of Congress (LC) classification scheme are…

  18. Echo-waveform classification using model and model free techniques: Experimental study results from central western continental shelf of India

    Digital Repository Service at National Institute of Oceanography (India)

    Chakraborty, B.; Navelkar, G.S.; Desai, R.G.P.; Janakiraman, G.; Mahale, V.; Fernandes, W.A.; Rao, N.

    seafloor of India, but unable to provide a suitable means for seafloor classification. This paper also suggests a hybrid artificial neural network (ANN) architecture i.e. Learning Vector Quantisation (LVQ) for seafloor classification. An analysis...

  19. Insights into the photocatalytic mechanism of mediator-free direct Z-scheme g-C3N4/Bi2MoO6(010) and g-C3N4/Bi2WO6(010) heterostructures: A hybrid density functional theory study

    Science.gov (United States)

    Opoku, Francis; Govender, Krishna Kuben; Sittert, Cornelia Gertina Catharina Elizabeth van; Govender, Penny Poomani

    2018-01-01

    Graphite-like carbon nitride (g-C3N4)-based heterostructures have received much attention due to their prominent photocatalytic activity. The g-C3N4/Bi2WO6 and g-C3N4/Bi2MoO6 heterostructures, which follow a typical hetero-junction charge transfer mechanisms show a weak potential for hydrogen evolution and reactive radical generation under visible light irradiation. A mediator-free Z-scheme g-C3N4/Bi2MoO6(010) and g-C3N4/Bi2WO6(010) heterostructures photocatalyst are designed for the first time using first-principles studies. Moreover, theoretical understanding of the underlying mechanism, the effects of interfacial composition and the role the interface play in the overall photoactivity is still unexplained. The calculated band gap of the heterostructures is reduced compared to the bulk Bi2WO6 and Bi2MoO6. In this study, we systematically calculated energy band structure, optical properties and charge transfer of the g-C3N4/Bi2MoO6(010) and g-C3N4/Bi2WO6(010) heterostructures using the hybrid density functional theory approach. The results show that the charge transfer at the interface of the heterostructures induces a built-in potential, which benefits the separation of photogenerated charge carriers. The g-C3N4/Bi2MoO6(010) heterostructure with more negative adhesion energy (-1.10 eVA-2) is predicted to have a better adsorptive ability and can form more easily compared to the g-C3N4/Bi2WO6(010) interface (-1.16 eVA-2). Therefore, our results show that the g-C3N4 interaction with Bi2MoO6 is stronger than Bi2WO6, which is also verified by the smaller vertical separation (3.25 Å) between Bi2MoO6 and g-C3N4 compared to the g-C3N4/Bi2WO6(010) interface (3.36 Å). The optical absorption verifies that these proposed Z-scheme heterostructures are excellent visible light harvesting semiconductor photocatalyst materials. This enhancement is ascribed to the role of g-C3N4 monolayer as an electron acceptor and the direct Z-scheme charge carrier transfer at the interface of

  20. Statistical analysis of textural features for improved classification of oral histopathological images.

    Science.gov (United States)

    Muthu Rama Krishnan, M; Shah, Pratik; Chakraborty, Chandan; Ray, Ajoy K

    2012-04-01

    The objective of this paper is to provide an improved technique, which can assist oncopathologists in correct screening of oral precancerous conditions specially oral submucous fibrosis (OSF) with significant accuracy on the basis of collagen fibres in the sub-epithelial connective tissue. The proposed scheme is composed of collagen fibres segmentation, its textural feature extraction and selection, screening perfomance enhancement under Gaussian transformation and finally classification. In this study, collagen fibres are segmented on R,G,B color channels using back-probagation neural network from 60 normal and 59 OSF histological images followed by histogram specification for reducing the stain intensity variation. Henceforth, textural features of collgen area are extracted using fractal approaches viz., differential box counting and brownian motion curve . Feature selection is done using Kullback-Leibler (KL) divergence criterion and the screening performance is evaluated based on various statistical tests to conform Gaussian nature. Here, the screening performance is enhanced under Gaussian transformation of the non-Gaussian features using hybrid distribution. Moreover, the routine screening is designed based on two statistical classifiers viz., Bayesian classification and support vector machines (SVM) to classify normal and OSF. It is observed that SVM with linear kernel function provides better classification accuracy (91.64%) as compared to Bayesian classifier. The addition of fractal features of collagen under Gaussian transformation improves Bayesian classifier's performance from 80.69% to 90.75%. Results are here studied and discussed.

  1. Improving breast cancer classification with mammography, supported on an appropriate variable selection analysis

    Science.gov (United States)

    Pérez, Noel; Guevara, Miguel A.; Silva, Augusto

    2013-02-01

    This work addresses the issue of variable selection within the context of breast cancer classification with mammography. A comprehensive repository of feature vectors was used including a hybrid subset gathering image-based and clinical features. It aimed to gather experimental evidence of variable selection in terms of cardinality, type and find a classification scheme that provides the best performance over the Area Under Receiver Operating Characteristics Curve (AUC) scores using the ranked features subset. We evaluated and classified a total of 300 subsets of features formed by the application of Chi-Square Discretization, Information-Gain, One-Rule and RELIEF methods in association with Feed-Forward Backpropagation Neural Network (FFBP), Support Vector Machine (SVM) and Decision Tree J48 (DTJ48) Machine Learning Algorithms (MLA) for a comparative performance evaluation based on AUC scores. A variable selection analysis was performed for Single-View Ranking and Multi-View Ranking groups of features. Features subsets representing Microcalcifications (MCs), Masses and both MCs and Masses lesions achieved AUC scores of 0.91, 0.954 and 0.934 respectively. Experimental evidence demonstrated that classification performance was improved by combining image-based and clinical features. The most important clinical and image-based features were StromaDistortion and Circularity respectively. Other less important but worth to use due to its consistency were Contrast, Perimeter, Microcalcification, Correlation and Elongation.

  2. 4. Payment Schemes

    Indian Academy of Sciences (India)

    Home; Journals; Resonance – Journal of Science Education; Volume 6; Issue 2. Electronic Commerce - Payment Schemes. V Rajaraman. Series Article Volume 6 Issue 2 February 2001 pp 6-13. Fulltext. Click here to view fulltext PDF. Permanent link: https://www.ias.ac.in/article/fulltext/reso/006/02/0006-0013 ...

  3. Contract saving schemes

    NARCIS (Netherlands)

    Ronald, R.; Smith, S.J.; Elsinga, M.; Eng, O.S.; Fox O'Mahony, L.; Wachter, S.

    2012-01-01

    Contractual saving schemes for housing are institutionalised savings programmes normally linked to rights to loans for home purchase. They are diverse types as they have been developed differently in each national context, but normally fall into categories of open, closed, compulsory, and ‘free

  4. Alternative reprocessing schemes evaluation

    International Nuclear Information System (INIS)

    1979-02-01

    This paper reviews the parameters which determine the inaccessibility of the plutonium in reprocessing plants. Among the various parameters, the physical and chemical characteristics of the materials, the various processing schemes and the confinement are considered. The emphasis is placed on that latter parameter, and the advantages of an increased confinement in the socalled PIPEX reprocessing plant type are presented

  5. Introduction to association schemes

    NARCIS (Netherlands)

    Seidel, J.J.

    1991-01-01

    The present paper gives an introduction to the theory of association schemes, following Bose-Mesner (1959), Biggs (1974), Delsarte (1973), Bannai-Ito (1984) and Brouwer-Cohen-Neumaier (1989). Apart from definitions and many examples, also several proofs and some problems are included. The paragraphs

  6. Reaction schemes of immunoanalysis

    International Nuclear Information System (INIS)

    Delaage, M.; Barbet, J.

    1991-01-01

    The authors apply a general theory for multiple equilibria to the reaction schemes of immunoanalysis, competition and sandwich. This approach allows the manufacturer to optimize the system and provide the user with interpolation functions for the standard curve and its first derivative as well, thus giving access to variance [fr

  7. Alternative health insurance schemes

    DEFF Research Database (Denmark)

    Keiding, Hans; Hansen, Bodil O.

    2002-01-01

    In this paper, we present a simple model of health insurance with asymmetric information, where we compare two alternative ways of organizing the insurance market. Either as a competitive insurance market, where some risks remain uninsured, or as a compulsory scheme, where however, the level...... competitive insurance; this situation turns out to be at least as good as either of the alternatives...

  8. Toward functional classification of neuronal types.

    Science.gov (United States)

    Sharpee, Tatyana O

    2014-09-17

    How many types of neurons are there in the brain? This basic neuroscience question remains unsettled despite many decades of research. Classification schemes have been proposed based on anatomical, electrophysiological, or molecular properties. However, different schemes do not always agree with each other. This raises the question of whether one can classify neurons based on their function directly. For example, among sensory neurons, can a classification scheme be devised that is based on their role in encoding sensory stimuli? Here, theoretical arguments are outlined for how this can be achieved using information theory by looking at optimal numbers of cell types and paying attention to two key properties: correlations between inputs and noise in neural responses. This theoretical framework could help to map the hierarchical tree relating different neuronal classes within and across species. Copyright © 2014 Elsevier Inc. All rights reserved.

  9. Hyperspectral Image Classification Using Discriminative Dictionary Learning

    International Nuclear Information System (INIS)

    Zongze, Y; Hao, S; Kefeng, J; Huanxin, Z

    2014-01-01

    The hyperspectral image (HSI) processing community has witnessed a surge of papers focusing on the utilization of sparse prior for effective HSI classification. In sparse representation based HSI classification, there are two phases: sparse coding with an over-complete dictionary and classification. In this paper, we first apply a novel fisher discriminative dictionary learning method, which capture the relative difference in different classes. The competitive selection strategy ensures that atoms in the resulting over-complete dictionary are the most discriminative. Secondly, motivated by the assumption that spatially adjacent samples are statistically related and even belong to the same materials (same class), we propose a majority voting scheme incorporating contextual information to predict the category label. Experiment results show that the proposed method can effectively strengthen relative discrimination of the constructed dictionary, and incorporating with the majority voting scheme achieve generally an improved prediction performance

  10. Dense Iterative Contextual Pixel Classification using Kriging

    DEFF Research Database (Denmark)

    Ganz, Melanie; Loog, Marco; Brandt, Sami

    2009-01-01

    have been proposed to this end, e.g., iterative contextual pixel classification, iterated conditional modes, and other approaches related to Markov random fields. A problem of these methods, however, is their computational complexity, especially when dealing with high-resolution images in which......In medical applications, segmentation has become an ever more important task. One of the competitive schemes to perform such segmentation is by means of pixel classification. Simple pixel-based classification schemes can be improved by incorporating contextual label information. Various methods...... relatively long range interactions may play a role. We propose a new method based on Kriging that makes it possible to include such long range interactions, while keeping the computations manageable when dealing with large medical images....

  11. Evolutionary algorithm based heuristic scheme for nonlinear heat transfer equations.

    Science.gov (United States)

    Ullah, Azmat; Malik, Suheel Abdullah; Alimgeer, Khurram Saleem

    2018-01-01

    In this paper, a hybrid heuristic scheme based on two different basis functions i.e. Log Sigmoid and Bernstein Polynomial with unknown parameters is used for solving the nonlinear heat transfer equations efficiently. The proposed technique transforms the given nonlinear ordinary differential equation into an equivalent global error minimization problem. Trial solution for the given nonlinear differential equation is formulated using a fitness function with unknown parameters. The proposed hybrid scheme of Genetic Algorithm (GA) with Interior Point Algorithm (IPA) is opted to solve the minimization problem and to achieve the optimal values of unknown parameters. The effectiveness of the proposed scheme is validated by solving nonlinear heat transfer equations. The results obtained by the proposed scheme are compared and found in sharp agreement with both the exact solution and solution obtained by Haar Wavelet-Quasilinearization technique which witnesses the effectiveness and viability of the suggested scheme. Moreover, the statistical analysis is also conducted for investigating the stability and reliability of the presented scheme.

  12. Evolutionary algorithm based heuristic scheme for nonlinear heat transfer equations.

    Directory of Open Access Journals (Sweden)

    Azmat Ullah

    Full Text Available In this paper, a hybrid heuristic scheme based on two different basis functions i.e. Log Sigmoid and Bernstein Polynomial with unknown parameters is used for solving the nonlinear heat transfer equations efficiently. The proposed technique transforms the given nonlinear ordinary differential equation into an equivalent global error minimization problem. Trial solution for the given nonlinear differential equation is formulated using a fitness function with unknown parameters. The proposed hybrid scheme of Genetic Algorithm (GA with Interior Point Algorithm (IPA is opted to solve the minimization problem and to achieve the optimal values of unknown parameters. The effectiveness of the proposed scheme is validated by solving nonlinear heat transfer equations. The results obtained by the proposed scheme are compared and found in sharp agreement with both the exact solution and solution obtained by Haar Wavelet-Quasilinearization technique which witnesses the effectiveness and viability of the suggested scheme. Moreover, the statistical analysis is also conducted for investigating the stability and reliability of the presented scheme.

  13. Solar wind and geomagnetism: toward a standard classification of geomagnetic activity from 1868 to 2009

    Directory of Open Access Journals (Sweden)

    J. L. Zerbo

    2012-02-01

    Full Text Available We examined solar activity with a large series of geomagnetic data from 1868 to 2009. We have revisited the geomagnetic activity classification scheme of Legrand and Simon (1989 and improve their scheme by lowering the minimum Aa index value for shock and recurrent activity from 40 to 20 nT. This improved scheme allows us to clearly classify about 80% of the geomagnetic activity in this time period instead of only 60% for the previous Legrand and Simon classification.

  14. Classification of the web

    DEFF Research Database (Denmark)

    Mai, Jens Erik

    2004-01-01

    This paper discusses the challenges faced by investigations into the classification of the Web and outlines inquiries that are needed to use principles for bibliographic classification to construct classifications of the Web. This paper suggests that the classification of the Web meets challenges...... that call for inquiries into the theoretical foundation of bibliographic classification theory....

  15. On Converting Secret Sharing Scheme to Visual Secret Sharing Scheme

    Directory of Open Access Journals (Sweden)

    Wang Daoshun

    2010-01-01

    Full Text Available Abstract Traditional Secret Sharing (SS schemes reconstruct secret exactly the same as the original one but involve complex computation. Visual Secret Sharing (VSS schemes decode the secret without computation, but each share is m times as big as the original and the quality of the reconstructed secret image is reduced. Probabilistic visual secret sharing (Prob.VSS schemes for a binary image use only one subpixel to share the secret image; however the probability of white pixels in a white area is higher than that in a black area in the reconstructed secret image. SS schemes, VSS schemes, and Prob. VSS schemes have various construction methods and advantages. This paper first presents an approach to convert (transform a -SS scheme to a -VSS scheme for greyscale images. The generation of the shadow images (shares is based on Boolean XOR operation. The secret image can be reconstructed directly by performing Boolean OR operation, as in most conventional VSS schemes. Its pixel expansion is significantly smaller than that of VSS schemes. The quality of the reconstructed images, measured by average contrast, is the same as VSS schemes. Then a novel matrix-concatenation approach is used to extend the greyscale -SS scheme to a more general case of greyscale -VSS scheme.

  16. Hybrid analysis of multiaxis electromagnetic data for discrimination of munitions and explosives of concern

    Science.gov (United States)

    Friedel, M. J.; Asch, T. H.; Oden, C.

    2012-08-01

    The remediation of land containing munitions and explosives of concern, otherwise known as unexploded ordnance, is an ongoing problem facing the U.S. Department of Defense and similar agencies worldwide that have used or are transferring training ranges or munitions disposal areas to civilian control. The expense associated with cleanup of land previously used for military training and war provides impetus for research towards enhanced discrimination of buried unexploded ordnance. Towards reducing that expense, a multiaxis electromagnetic induction data collection and software system, called ALLTEM, was designed and tested with support from the U.S. Department of Defense Environmental Security Technology Certification Program. ALLTEM is an on-time time-domain system that uses a continuous triangle-wave excitation to measure the target-step response rather than traditional impulse response. The system cycles through three orthogonal transmitting loops and records a total of 19 different transmitting and receiving loop combinations with a nominal spatial data sampling interval of 20 cm. Recorded data are pre-processed and then used in a hybrid discrimination scheme involving both data-driven and numerical classification techniques. The data-driven classification scheme is accomplished in three steps. First, field observations are used to train a type of unsupervised artificial neural network, a self-organizing map (SOM). Second, the SOM is used to simultaneously estimate target parameters (depth, azimuth, inclination, item type and weight) by iterative minimization of the topographic error vectors. Third, the target classification is accomplished by evaluating histograms of the estimated parameters. The numerical classification scheme is also accomplished in three steps. First, the Biot-Savart law is used to model the primary magnetic fields from the transmitter coils and the secondary magnetic fields generated by currents induced in the target materials in the

  17. Hybrid analysis of multiaxis electromagnetic data for discrimination of munitions and explosives of concern

    Science.gov (United States)

    Friedel, M.J.; Asch, T.H.; Oden, C.

    2012-01-01

    The remediation of land containing munitions and explosives of concern, otherwise known as unexploded ordnance, is an ongoing problem facing the U.S. Department of Defense and similar agencies worldwide that have used or are transferring training ranges or munitions disposal areas to civilian control. The expense associated with cleanup of land previously used for military training and war provides impetus for research towards enhanced discrimination of buried unexploded ordnance. Towards reducing that expense, a multiaxis electromagnetic induction data collection and software system, called ALLTEM, was designed and tested with support from the U.S. Department of Defense Environmental Security Technology Certification Program. ALLTEM is an on-time time-domain system that uses a continuous triangle-wave excitation to measure the target-step response rather than traditional impulse response. The system cycles through three orthogonal transmitting loops and records a total of 19 different transmitting and receiving loop combinations with a nominal spatial data sampling interval of 20 cm. Recorded data are pre-processed and then used in a hybrid discrimination scheme involving both data-driven and numerical classification techniques. The data-driven classification scheme is accomplished in three steps. First, field observations are used to train a type of unsupervised artificial neural network, a self-organizing map (SOM). Second, the SOM is used to simultaneously estimate target parameters (depth, azimuth, inclination, item type and weight) by iterative minimization of the topographic error vectors. Third, the target classification is accomplished by evaluating histograms of the estimated parameters. The numerical classification scheme is also accomplished in three steps. First, the Biot–Savart law is used to model the primary magnetic fields from the transmitter coils and the secondary magnetic fields generated by currents induced in the target materials in the

  18. Selectively strippable paint schemes

    Science.gov (United States)

    Stein, R.; Thumm, D.; Blackford, Roger W.

    1993-03-01

    In order to meet the requirements of more environmentally acceptable paint stripping processes many different removal methods are under evaluation. These new processes can be divided into mechanical and chemical methods. ICI has developed a paint scheme with intermediate coat and fluid resistant polyurethane topcoat which can be stripped chemically in a short period of time with methylene chloride free and phenol free paint strippers.

  19. Hybrid and rogue kinases encoded in the genomes of model eukaryotes.

    Directory of Open Access Journals (Sweden)

    Ramaswamy Rakshambikai

    Full Text Available The highly modular nature of protein kinases generates diverse functional roles mediated by evolutionary events such as domain recombination, insertion and deletion of domains. Usually domain architecture of a kinase is related to the subfamily to which the kinase catalytic domain belongs. However outlier kinases with unusual domain architectures serve in the expansion of the functional space of the protein kinase family. For example, Src kinases are made-up of SH2 and SH3 domains in addition to the kinase catalytic domain. A kinase which lacks these two domains but retains sequence characteristics within the kinase catalytic domain is an outlier that is likely to have modes of regulation different from classical src kinases. This study defines two types of outlier kinases: hybrids and rogues depending on the nature of domain recombination. Hybrid kinases are those where the catalytic kinase domain belongs to a kinase subfamily but the domain architecture is typical of another kinase subfamily. Rogue kinases are those with kinase catalytic domain characteristic of a kinase subfamily but the domain architecture is typical of neither that subfamily nor any other kinase subfamily. This report provides a consolidated set of such hybrid and rogue kinases gleaned from six eukaryotic genomes-S.cerevisiae, D. melanogaster, C.elegans, M.musculus, T.rubripes and H.sapiens-and discusses their functions. The presence of such kinases necessitates a revisiting of the classification scheme of the protein kinase family using full length sequences apart from classical classification using solely the sequences of kinase catalytic domains. The study of these kinases provides a good insight in engineering signalling pathways for a desired output. Lastly, identification of hybrids and rogues in pathogenic protozoa such as P.falciparum sheds light on possible strategies in host-pathogen interactions.

  20. Scalable Nonlinear Compact Schemes

    Energy Technology Data Exchange (ETDEWEB)

    Ghosh, Debojyoti [Argonne National Lab. (ANL), Argonne, IL (United States); Constantinescu, Emil M. [Univ. of Chicago, IL (United States); Brown, Jed [Univ. of Colorado, Boulder, CO (United States)

    2014-04-01

    In this work, we focus on compact schemes resulting in tridiagonal systems of equations, specifically the fifth-order CRWENO scheme. We propose a scalable implementation of the nonlinear compact schemes by implementing a parallel tridiagonal solver based on the partitioning/substructuring approach. We use an iterative solver for the reduced system of equations; however, we solve this system to machine zero accuracy to ensure that no parallelization errors are introduced. It is possible to achieve machine-zero convergence with few iterations because of the diagonal dominance of the system. The number of iterations is specified a priori instead of a norm-based exit criterion, and collective communications are avoided. The overall algorithm thus involves only point-to-point communication between neighboring processors. Our implementation of the tridiagonal solver differs from and avoids the drawbacks of past efforts in the following ways: it introduces no parallelization-related approximations (multiprocessor solutions are exactly identical to uniprocessor ones), it involves minimal communication, the mathematical complexity is similar to that of the Thomas algorithm on a single processor, and it does not require any communication and computation scheduling.

  1. A comprehensive sensitivity analysis of microarray breast cancer classification under feature variability

    Directory of Open Access Journals (Sweden)

    Reinders Marcel JT

    2009-11-01

    Full Text Available Abstract Background Large discrepancies in signature composition and outcome concordance have been observed between different microarray breast cancer expression profiling studies. This is often ascribed to differences in array platform as well as biological variability. We conjecture that other reasons for the observed discrepancies are the measurement error associated with each feature and the choice of preprocessing method. Microarray data are known to be subject to technical variation and the confidence intervals around individual point estimates of expression levels can be wide. Furthermore, the estimated expression values also vary depending on the selected preprocessing scheme. In microarray breast cancer classification studies, however, these two forms of feature variability are almost always ignored and hence their exact role is unclear. Results We have performed a comprehensive sensitivity analysis of microarray breast cancer classification under the two types of feature variability mentioned above. We used data from six state of the art preprocessing methods, using a compendium consisting of eight diferent datasets, involving 1131 hybridizations, containing data from both one and two-color array technology. For a wide range of classifiers, we performed a joint study on performance, concordance and stability. In the stability analysis we explicitly tested classifiers for their noise tolerance by using perturbed expression profiles that are based on uncertainty information directly related to the preprocessing methods. Our results indicate that signature composition is strongly influenced by feature variability, even if the array platform and the stratification of patient samples are identical. In addition, we show that there is often a high level of discordance between individual class assignments for signatures constructed on data coming from different preprocessing schemes, even if the actual signature composition is identical

  2. Carnegie's New Community Engagement Classification: Affirming Higher Education's Role in Community

    Science.gov (United States)

    Driscoll, Amy

    2009-01-01

    In 2005, the Carnegie Foundation for the Advancement of Teaching (CFAT) stirred the higher education world with the announcement of a new classification for institutions that engage with community. The classification, community engagement, is the first in a set of planned classification schemes resulting from the foundation's reexamination of the…

  3. CLASSIFICATION OF LEARNING MANAGEMENT SYSTEMS

    Directory of Open Access Journals (Sweden)

    Yu. B. Popova

    2016-01-01

    Full Text Available Using of information technologies and, in particular, learning management systems, increases opportunities of teachers and students in reaching their goals in education. Such systems provide learning content, help organize and monitor training, collect progress statistics and take into account the individual characteristics of each user. Currently, there is a huge inventory of both paid and free systems are physically located both on college servers and in the cloud, offering different features sets of different licensing scheme and the cost. This creates the problem of choosing the best system. This problem is partly due to the lack of comprehensive classification of such systems. Analysis of more than 30 of the most common now automated learning management systems has shown that a classification of such systems should be carried out according to certain criteria, under which the same type of system can be considered. As classification features offered by the author are: cost, functionality, modularity, keeping the customer’s requirements, the integration of content, the physical location of a system, adaptability training. Considering the learning management system within these classifications and taking into account the current trends of their development, it is possible to identify the main requirements to them: functionality, reliability, ease of use, low cost, support for SCORM standard or Tin Can API, modularity and adaptability. According to the requirements at the Software Department of FITR BNTU under the guidance of the author since 2009 take place the development, the use and continuous improvement of their own learning management system.

  4. Hybrid reactors

    International Nuclear Information System (INIS)

    Moir, R.W.

    1980-01-01

    The rationale for hybrid fusion-fission reactors is the production of fissile fuel for fission reactors. A new class of reactor, the fission-suppressed hybrid promises unusually good safety features as well as the ability to support 25 light-water reactors of the same nuclear power rating, or even more high-conversion-ratio reactors such as the heavy-water type. One 4000-MW nuclear hybrid can produce 7200 kg of 233 U per year. To obtain good economics, injector efficiency times plasma gain (eta/sub i/Q) should be greater than 2, the wall load should be greater than 1 MW.m -2 , and the hybrid should cost less than 6 times the cost of a light-water reactor. Introduction rates for the fission-suppressed hybrid are usually rapid

  5. Hazard classification methodology

    International Nuclear Information System (INIS)

    Brereton, S.J.

    1996-01-01

    This document outlines the hazard classification methodology used to determine the hazard classification of the NIF LTAB, OAB, and the support facilities on the basis of radionuclides and chemicals. The hazard classification determines the safety analysis requirements for a facility

  6. A cancelable biometric scheme based on multi-lead ECGs.

    Science.gov (United States)

    Peng-Tzu Chen; Shun-Chi Wu; Jui-Hsuan Hsieh

    2017-07-01

    Biometric technologies offer great advantages over other recognition methods, but there are concerns that they may compromise the privacy of individuals. In this paper, an electrocardiogram (ECG)-based cancelable biometric scheme is proposed to relieve such concerns. In this scheme, distinct biometric templates for a given beat bundle are constructed via "subspace collapsing." To determine the identity of any unknown beat bundle, the multiple signal classification (MUSIC) algorithm, incorporating a "suppression and poll" strategy, is adopted. Unlike the existing cancelable biometric schemes, knowledge of the distortion transform is not required for recognition. Experiments with real ECGs from 285 subjects are presented to illustrate the efficacy of the proposed scheme. The best recognition rate of 97.58 % was achieved under the test condition N train = 10 and N test = 10.

  7. Classification of proteins: available structural space for molecular modeling.

    Science.gov (United States)

    Andreeva, Antonina

    2012-01-01

    The wealth of available protein structural data provides unprecedented opportunity to study and better understand the underlying principles of protein folding and protein structure evolution. A key to achieving this lies in the ability to analyse these data and to organize them in a coherent classification scheme. Over the past years several protein classifications have been developed that aim to group proteins based on their structural relationships. Some of these classification schemes explore the concept of structural neighbourhood (structural continuum), whereas other utilize the notion of protein evolution and thus provide a discrete rather than continuum view of protein structure space. This chapter presents a strategy for classification of proteins with known three-dimensional structure. Steps in the classification process along with basic definitions are introduced. Examples illustrating some fundamental concepts of protein folding and evolution with a special focus on the exceptions to them are presented.

  8. The theory of hybrid stochastic algorithms

    International Nuclear Information System (INIS)

    Duane, S.; Kogut, J.B.

    1986-01-01

    The theory of hybrid stochastic algorithms is developed. A generalized Fokker-Planck equation is derived and is used to prove that the correct equilibrium distribution is generated by the algorithm. Systematic errors following from the discrete time-step used in the numerical implementation of the scheme are computed. Hybrid algorithms which simulate lattice gauge theory with dynamical fermions are presented. They are optimized in computer simulations and their systematic errors and efficiencies are studied. (orig.)

  9. A Theoretical Analysis of Why Hybrid Ensembles Work

    Directory of Open Access Journals (Sweden)

    Kuo-Wei Hsu

    2017-01-01

    Full Text Available Inspired by the group decision making process, ensembles or combinations of classifiers have been found favorable in a wide variety of application domains. Some researchers propose to use the mixture of two different types of classification algorithms to create a hybrid ensemble. Why does such an ensemble work? The question remains. Following the concept of diversity, which is one of the fundamental elements of the success of ensembles, we conduct a theoretical analysis of why hybrid ensembles work, connecting using different algorithms to accuracy gain. We also conduct experiments on classification performance of hybrid ensembles of classifiers created by decision tree and naïve Bayes classification algorithms, each of which is a top data mining algorithm and often used to create non-hybrid ensembles. Therefore, through this paper, we provide a complement to the theoretical foundation of creating and using hybrid ensembles.

  10. ESCAP mobile training scheme.

    Science.gov (United States)

    Yasas, F M

    1977-01-01

    In response to a United Nations resolution, the Mobile Training Scheme (MTS) was set up to provide training to the trainers of national cadres engaged in frontline and supervisory tasks in social welfare and rural development. The training is innovative in its being based on an analysis of field realities. The MTS team consisted of a leader, an expert on teaching methods and materials, and an expert on action research and evaluation. The country's trainers from different departments were sent to villages to work for a short period and to report their problems in fulfilling their roles. From these grass roots experiences, they made an analysis of the job, determining what knowledge, attitude and skills it required. Analysis of daily incidents and problems were used to produce indigenous teaching materials drawn from actual field practice. How to consider the problems encountered through government structures for policy making and decisions was also learned. Tasks of the students were to identify the skills needed for role performance by job analysis, daily diaries and project histories; to analyze the particular community by village profiles; to produce indigenous teaching materials; and to practice the role skills by actual role performance. The MTS scheme was tried in Nepal in 1974-75; 3 training programs trained 25 trainers and 51 frontline workers; indigenous teaching materials were created; technical papers written; and consultations were provided. In Afghanistan the scheme was used in 1975-76; 45 participants completed the training; seminars were held; and an ongoing Council was created. It is hoped that the training program will be expanded to other countries.

  11. Bonus schemes and trading activity

    NARCIS (Netherlands)

    Pikulina, E.S.; Renneboog, L.D.R.; ter Horst, J.R.; Tobler, P.N.

    2014-01-01

    Little is known about how different bonus schemes affect traders' propensity to trade and which bonus schemes improve traders' performance. We study the effects of linear versus threshold bonus schemes on traders' behavior. Traders buy and sell shares in an experimental stock market on the basis of

  12. Succesful labelling schemes

    DEFF Research Database (Denmark)

    Juhl, Hans Jørn; Stacey, Julia

    2001-01-01

    . In the spring of 2001 MAPP carried out an extensive consumer study with special emphasis on the Nordic environmentally friendly label 'the swan'. The purpose was to find out how much consumers actually know and use various labelling schemes. 869 households were contacted and asked to fill in a questionnaire...... it into consideration when I go shopping. The respondent was asked to pick the most suitable answer, which described her use of each label. 29% - also called 'the labelling blind' - responded that they basically only knew the recycling label and the Government controlled organic label 'Ø-mærket'. Another segment of 6...

  13. Scheme of stepmotor control

    International Nuclear Information System (INIS)

    Grashilin, V.A.; Karyshev, Yu.Ya.

    1982-01-01

    A 6-cycle scheme of step motor is described. The block-diagram and the basic circuit of the step motor control are presented. The step motor control comprises a pulse shaper, electronic commutator and power amplifiers. The step motor supply from 6-cycle electronic commutator provides for higher reliability and accuracy than from 3-cycle commutator. The control of step motor work is realised by the program given by the external source of control signals. Time-dependent diagrams for step motor control are presented. The specifications of the step-motor is given

  14. Hybrid keyword search auctions

    KAUST Repository

    Goel, Ashish; Munagala, Kamesh

    2009-01-01

    Search auctions have become a dominant source of revenue generation on the Internet. Such auctions have typically used per-click bidding and pricing. We propose the use of hybrid auctions where an advertiser can make a per-impression as well as a per-click bid, and the auctioneer then chooses one of the two as the pricing mechanism. We assume that the advertiser and the auctioneer both have separate beliefs (called priors) on the click-probability of an advertisement. We first prove that the hybrid auction is truthful, assuming that the advertisers are risk-neutral. We then show that this auction is superior to the existing per-click auction in multiple ways: 1. We show that risk-seeking advertisers will choose only a per-impression bid whereas risk-averse advertisers will choose only a per-click bid, and argue that both kind of advertisers arise naturally. Hence, the ability to bid in a hybrid fashion is important to account for the risk characteristics of the advertisers. 2. For obscure keywords, the auctioneer is unlikely to have a very sharp prior on the click-probabilities. In such situations, we show that having the extra information from the advertisers in the form of a per-impression bid can result in significantly higher revenue. 3. An advertiser who believes that its click-probability is much higher than the auctioneer's estimate can use per-impression bids to correct the auctioneer's prior without incurring any extra cost. 4. The hybrid auction can allow the advertiser and auctioneer to implement complex dynamic programming strategies to deal with the uncertainty in the click-probability using the same basic auction. The per-click and per-impression bidding schemes can only be used to implement two extreme cases of these strategies. As Internet commerce matures, we need more sophisticated pricing models to exploit all the information held by each of the participants. We believe that hybrid auctions could be an important step in this direction. The hybrid

  15. Hybrid keyword search auctions

    KAUST Repository

    Goel, Ashish

    2009-01-01

    Search auctions have become a dominant source of revenue generation on the Internet. Such auctions have typically used per-click bidding and pricing. We propose the use of hybrid auctions where an advertiser can make a per-impression as well as a per-click bid, and the auctioneer then chooses one of the two as the pricing mechanism. We assume that the advertiser and the auctioneer both have separate beliefs (called priors) on the click-probability of an advertisement. We first prove that the hybrid auction is truthful, assuming that the advertisers are risk-neutral. We then show that this auction is superior to the existing per-click auction in multiple ways: 1. We show that risk-seeking advertisers will choose only a per-impression bid whereas risk-averse advertisers will choose only a per-click bid, and argue that both kind of advertisers arise naturally. Hence, the ability to bid in a hybrid fashion is important to account for the risk characteristics of the advertisers. 2. For obscure keywords, the auctioneer is unlikely to have a very sharp prior on the click-probabilities. In such situations, we show that having the extra information from the advertisers in the form of a per-impression bid can result in significantly higher revenue. 3. An advertiser who believes that its click-probability is much higher than the auctioneer\\'s estimate can use per-impression bids to correct the auctioneer\\'s prior without incurring any extra cost. 4. The hybrid auction can allow the advertiser and auctioneer to implement complex dynamic programming strategies to deal with the uncertainty in the click-probability using the same basic auction. The per-click and per-impression bidding schemes can only be used to implement two extreme cases of these strategies. As Internet commerce matures, we need more sophisticated pricing models to exploit all the information held by each of the participants. We believe that hybrid auctions could be an important step in this direction. The

  16. Packet reversed packet combining scheme

    International Nuclear Information System (INIS)

    Bhunia, C.T.

    2006-07-01

    The packet combining scheme is a well defined simple error correction scheme with erroneous copies at the receiver. It offers higher throughput combined with ARQ protocols in networks than that of basic ARQ protocols. But packet combining scheme fails to correct errors when the errors occur in the same bit locations of two erroneous copies. In the present work, we propose a scheme that will correct error if the errors occur at the same bit location of the erroneous copies. The proposed scheme when combined with ARQ protocol will offer higher throughput. (author)

  17. A full quantum network scheme

    International Nuclear Information System (INIS)

    Ma Hai-Qiang; Wei Ke-Jin; Yang Jian-Hui; Li Rui-Xue; Zhu Wu

    2014-01-01

    We present a full quantum network scheme using a modified BB84 protocol. Unlike other quantum network schemes, it allows quantum keys to be distributed between two arbitrary users with the help of an intermediary detecting user. Moreover, it has good expansibility and prevents all potential attacks using loopholes in a detector, so it is more practical to apply. Because the fiber birefringence effects are automatically compensated, the scheme is distinctly stable in principle and in experiment. The simple components for every user make our scheme easier for many applications. The experimental results demonstrate the stability and feasibility of this scheme. (general)

  18. A hybrid iterative scheme for optimal control problems governed by ...

    African Journals Online (AJOL)

    MRT

    KEY WORDS: Optimal control problem; Fredholm integral equation; ... control problems governed by Fredholm integral and integro-differential equations is given in (Brunner and Yan, ..... The exact optimal trajectory and control functions are. 2.

  19. Hybrid composites

    CSIR Research Space (South Africa)

    Jacob John, Maya

    2009-04-01

    Full Text Available mixed short sisal/glass hybrid fibre reinforced low density polyethylene composites was investigated by Kalaprasad et al [25].Chemical surface modifications such as alkali, acetic anhydride, stearic acid, permanganate, maleic anhydride, silane...

  20. Computer-aided classification of breast masses using contrast-enhanced digital mammograms

    Science.gov (United States)

    Danala, Gopichandh; Aghaei, Faranak; Heidari, Morteza; Wu, Teresa; Patel, Bhavika; Zheng, Bin

    2018-02-01

    By taking advantages of both mammography and breast MRI, contrast-enhanced digital mammography (CEDM) has emerged as a new promising imaging modality to improve efficacy of breast cancer screening and diagnosis. The primary objective of study is to develop and evaluate a new computer-aided detection and diagnosis (CAD) scheme of CEDM images to classify between malignant and benign breast masses. A CEDM dataset consisting of 111 patients (33 benign and 78 malignant) was retrospectively assembled. Each case includes two types of images namely, low-energy (LE) and dual-energy subtracted (DES) images. First, CAD scheme applied a hybrid segmentation method to automatically segment masses depicting on LE and DES images separately. Optimal segmentation results from DES images were also mapped to LE images and vice versa. Next, a set of 109 quantitative image features related to mass shape and density heterogeneity was initially computed. Last, four multilayer perceptron-based machine learning classifiers integrated with correlationbased feature subset evaluator and leave-one-case-out cross-validation method was built to classify mass regions depicting on LE and DES images, respectively. Initially, when CAD scheme was applied to original segmentation of DES and LE images, the areas under ROC curves were 0.7585+/-0.0526 and 0.7534+/-0.0470, respectively. After optimal segmentation mapping from DES to LE images, AUC value of CAD scheme significantly increased to 0.8477+/-0.0376 (pbreast tissue on lesions, segmentation accuracy was significantly improved as compared to regular mammograms, the study demonstrated that computer-aided classification of breast masses using CEDM images yielded higher performance.

  1. MeMoVolc report on classification and dynamics of volcanic explosive eruptions

    Science.gov (United States)

    Bonadonna, C.; Cioni, R.; Costa, A.; Druitt, T.; Phillips, J.; Pioli, L.; Andronico, D.; Harris, A.; Scollo, S.; Bachmann, O.; Bagheri, G.; Biass, S.; Brogi, F.; Cashman, K.; Dominguez, L.; Dürig, T.; Galland, O.; Giordano, G.; Gudmundsson, M.; Hort, M.; Höskuldsson, A.; Houghton, B.; Komorowski, J. C.; Küppers, U.; Lacanna, G.; Le Pennec, J. L.; Macedonio, G.; Manga, M.; Manzella, I.; Vitturi, M. de'Michieli; Neri, A.; Pistolesi, M.; Polacci, M.; Ripepe, M.; Rossi, E.; Scheu, B.; Sulpizio, R.; Tripoli, B.; Valade, S.; Valentine, G.; Vidal, C.; Wallenstein, N.

    2016-11-01

    Classifications of volcanic eruptions were first introduced in the early twentieth century mostly based on qualitative observations of eruptive activity, and over time, they have gradually been developed to incorporate more quantitative descriptions of the eruptive products from both deposits and observations of active volcanoes. Progress in physical volcanology, and increased capability in monitoring, measuring and modelling of explosive eruptions, has highlighted shortcomings in the way we classify eruptions and triggered a debate around the need for eruption classification and the advantages and disadvantages of existing classification schemes. Here, we (i) review and assess existing classification schemes, focussing on subaerial eruptions; (ii) summarize the fundamental processes that drive and parameters that characterize explosive volcanism; (iii) identify and prioritize the main research that will improve the understanding, characterization and classification of volcanic eruptions and (iv) provide a roadmap for producing a rational and comprehensive classification scheme. In particular, classification schemes need to be objective-driven and simple enough to permit scientific exchange and promote transfer of knowledge beyond the scientific community. Schemes should be comprehensive and encompass a variety of products, eruptive styles and processes, including for example, lava flows, pyroclastic density currents, gas emissions and cinder cone or caldera formation. Open questions, processes and parameters that need to be addressed and better characterized in order to develop more comprehensive classification schemes and to advance our understanding of volcanic eruptions include conduit processes and dynamics, abrupt transitions in eruption regime, unsteadiness, eruption energy and energy balance.

  2. Hybrid intermediaries

    OpenAIRE

    Cetorelli, Nicola

    2014-01-01

    I introduce the concept of hybrid intermediaries: financial conglomerates that control a multiplicity of entity types active in the "assembly line" process of modern financial intermediation, a system that has become known as shadow banking. The complex bank holding companies of today are the best example of hybrid intermediaries, but I argue that financial firms from the "nonbank" space can just as easily evolve into conglomerates with similar organizational structure, thus acquiring the cap...

  3. Fuzzy set classifier for waste classification tracking

    International Nuclear Information System (INIS)

    Gavel, D.T.

    1992-01-01

    We have developed an expert system based on fuzzy logic theory to fuse the data from multiple sensors and make classification decisions for objects in a waste reprocessing stream. Fuzzy set theory has been applied in decision and control applications with some success, particularly by the Japanese. We have found that the fuzzy logic system is rather easy to design and train, a feature that can cut development costs considerably. With proper training, the classification accuracy is quite high. We performed several tests sorting radioactive test samples using a gamma spectrometer to compare fuzzy logic to more conventional sorting schemes

  4. Classification and global distribution of ocean precipitation types based on satellite passive microwave signatures

    Science.gov (United States)

    Gautam, Nitin

    The main objectives of this thesis are to develop a robust statistical method for the classification of ocean precipitation based on physical properties to which the SSM/I is sensitive and to examine how these properties vary globally and seasonally. A two step approach is adopted for the classification of oceanic precipitation classes from multispectral SSM/I data: (1)we subjectively define precipitation classes using a priori information about the precipitating system and its possible distinct signature on SSM/I data such as scattering by ice particles aloft in the precipitating cloud, emission by liquid rain water below freezing level, the difference of polarization at 19 GHz-an indirect measure of optical depth, etc.; (2)we then develop an objective classification scheme which is found to reproduce the subjective classification with high accuracy. This hybrid strategy allows us to use the characteristics of the data to define and encode classes and helps retain the physical interpretation of classes. The classification methods based on k-nearest neighbor and neural network are developed to objectively classify six precipitation classes. It is found that the classification method based neural network yields high accuracy for all precipitation classes. An inversion method based on minimum variance approach was used to retrieve gross microphysical properties of these precipitation classes such as column integrated liquid water path, column integrated ice water path, and column integrated min water path. This classification method is then applied to 2 years (1991-92) of SSM/I data to examine and document the seasonal and global distribution of precipitation frequency corresponding to each of these objectively defined six classes. The characteristics of the distribution are found to be consistent with assumptions used in defining these six precipitation classes and also with well known climatological patterns of precipitation regions. The seasonal and global

  5. Defuzzification Strategies for Fuzzy Classifications of Remote Sensing Data

    Directory of Open Access Journals (Sweden)

    Peter Hofmann

    2016-06-01

    Full Text Available The classes in fuzzy classification schemes are defined as fuzzy sets, partitioning the feature space through fuzzy rules, defined by fuzzy membership functions. Applying fuzzy classification schemes in remote sensing allows each pixel or segment to be an incomplete member of more than one class simultaneously, i.e., one that does not fully meet all of the classification criteria for any one of the classes and is member of more than one class simultaneously. This can lead to fuzzy, ambiguous and uncertain class assignation, which is unacceptable for many applications, indicating the need for a reliable defuzzification method. Defuzzification in remote sensing has to date, been performed by “crisp-assigning” each fuzzy-classified pixel or segment to the class for which it best fulfills the fuzzy classification rules, regardless of its classification fuzziness, uncertainty or ambiguity (maximum method. The defuzzification of an uncertain or ambiguous fuzzy classification leads to a more or less reliable crisp classification. In this paper the most common parameters for expressing classification uncertainty, fuzziness and ambiguity are analysed and discussed in terms of their ability to express the reliability of a crisp classification. This is done by means of a typical practical example from Object Based Image Analysis (OBIA.

  6. Classification of nasolabial folds in Asians and the corresponding surgical approaches: By Shanghai 9th People's Hospital.

    Science.gov (United States)

    Zhang, Lu; Tang, Meng-Yao; Jin, Rong; Zhang, Ying; Shi, Yao-Ming; Sun, Bao-Shan; Zhang, Yu-Guang

    2015-07-01

    One of the earliest signs of aging appears in the nasolabial fold, which is a special anatomical region that requires many factors for comprehensive assessment. Hence, it is inadequate to rely on a single index to facilitate the classification of nasolabial folds. Through clinical observation, we have observed that traditional filling treatments provide little improvement for some patients, which prompted us to seek a more specific and scientific classification standard and assessment system. A total of 900 patients who sought facial rejuvenation treatment in Shanghai 9th People's Hospital were invited in this study. We observed the different nasolabial fold traits for different age groups and in different states, and the results were compared with the Wrinkle Severity Rating Scale (WSRS). We summarized the data, presented a classification scheme, and proposed a selection of treatment options. Consideration of the anatomical and histological features of nasolabial folds allowed us to divide nasolabial folds into five types, namely the skin type, fat pad type, muscular type, bone retrusion type, and hybrid type. Because different types of nasolabial folds require different treatments, it is crucial to accurately assess and correctly classify the conditions. Copyright © 2015 British Association of Plastic, Reconstructive and Aesthetic Surgeons. Published by Elsevier Ltd. All rights reserved.

  7. SAW Classification Algorithm for Chinese Text Classification

    OpenAIRE

    Xiaoli Guo; Huiyu Sun; Tiehua Zhou; Ling Wang; Zhaoyang Qu; Jiannan Zang

    2015-01-01

    Considering the explosive growth of data, the increased amount of text data’s effect on the performance of text categorization forward the need for higher requirements, such that the existing classification method cannot be satisfied. Based on the study of existing text classification technology and semantics, this paper puts forward a kind of Chinese text classification oriented SAW (Structural Auxiliary Word) algorithm. The algorithm uses the special space effect of Chinese text where words...

  8. Synchronization and Desynchronizing Control Schemes for Supermarket Refrigeration Systems

    DEFF Research Database (Denmark)

    Larsen, Lars Finn Sloth; Thybo, Claus Thybo; Izadi-Zamanabadi, Roozbeh

    2007-01-01

    A supermarket refrigeration system is a hybrid system with switched nonlinear dynamics and discrete-valued input variables such as opening/closing of valves and start/stop of compressors. Practical and simulation studies have shown that the use of distributed hysteresis controllers to operate...... complexity for desynchronizing the valve operations while improving performance. Simulation results indicate the potential increase in efficiency and reduction in wear comparing with traditional control schemes....

  9. On the Feature Selection and Classification Based on Information Gain for Document Sentiment Analysis

    Directory of Open Access Journals (Sweden)

    Asriyanti Indah Pratiwi

    2018-01-01

    Full Text Available Sentiment analysis in a movie review is the needs of today lifestyle. Unfortunately, enormous features make the sentiment of analysis slow and less sensitive. Finding the optimum feature selection and classification is still a challenge. In order to handle an enormous number of features and provide better sentiment classification, an information-based feature selection and classification are proposed. The proposed method reduces more than 90% unnecessary features while the proposed classification scheme achieves 96% accuracy of sentiment classification. From the experimental results, it can be concluded that the combination of proposed feature selection and classification achieves the best performance so far.

  10. Impact of different parameterization schemes on simulation of mesoscale convective system over south-east India

    Science.gov (United States)

    Madhulatha, A.; Rajeevan, M.

    2018-02-01

    Main objective of the present paper is to examine the role of various parameterization schemes in simulating the evolution of mesoscale convective system (MCS) occurred over south-east India. Using the Weather Research and Forecasting (WRF) model, numerical experiments are conducted by considering various planetary boundary layer, microphysics, and cumulus parameterization schemes. Performances of different schemes are evaluated by examining boundary layer, reflectivity, and precipitation features of MCS using ground-based and satellite observations. Among various physical parameterization schemes, Mellor-Yamada-Janjic (MYJ) boundary layer scheme is able to produce deep boundary layer height by simulating warm temperatures necessary for storm initiation; Thompson (THM) microphysics scheme is capable to simulate the reflectivity by reasonable distribution of different hydrometeors during various stages of system; Betts-Miller-Janjic (BMJ) cumulus scheme is able to capture the precipitation by proper representation of convective instability associated with MCS. Present analysis suggests that MYJ, a local turbulent kinetic energy boundary layer scheme, which accounts strong vertical mixing; THM, a six-class hybrid moment microphysics scheme, which considers number concentration along with mixing ratio of rain hydrometeors; and BMJ, a closure cumulus scheme, which adjusts thermodynamic profiles based on climatological profiles might have contributed for better performance of respective model simulations. Numerical simulation carried out using the above combination of schemes is able to capture storm initiation, propagation, surface variations, thermodynamic structure, and precipitation features reasonably well. This study clearly demonstrates that the simulation of MCS characteristics is highly sensitive to the choice of parameterization schemes.

  11. Modified Aggressive Packet Combining Scheme

    International Nuclear Information System (INIS)

    Bhunia, C.T.

    2010-06-01

    In this letter, a few schemes are presented to improve the performance of aggressive packet combining scheme (APC). To combat error in computer/data communication networks, ARQ (Automatic Repeat Request) techniques are used. Several modifications to improve the performance of ARQ are suggested by recent research and are found in literature. The important modifications are majority packet combining scheme (MjPC proposed by Wicker), packet combining scheme (PC proposed by Chakraborty), modified packet combining scheme (MPC proposed by Bhunia), and packet reversed packet combining (PRPC proposed by Bhunia) scheme. These modifications are appropriate for improving throughput of conventional ARQ protocols. Leung proposed an idea of APC for error control in wireless networks with the basic objective of error control in uplink wireless data network. We suggest a few modifications of APC to improve its performance in terms of higher throughput, lower delay and higher error correction capability. (author)

  12. Transmission usage cost allocation schemes

    International Nuclear Information System (INIS)

    Abou El Ela, A.A.; El-Sehiemy, R.A.

    2009-01-01

    This paper presents different suggested transmission usage cost allocation (TCA) schemes to the system individuals. Different independent system operator (ISO) visions are presented using the proportional rata and flow-based TCA methods. There are two proposed flow-based TCA schemes (FTCA). The first FTCA scheme generalizes the equivalent bilateral exchanges (EBE) concepts for lossy networks through two-stage procedure. The second FTCA scheme is based on the modified sensitivity factors (MSF). These factors are developed from the actual measurements of power flows in transmission lines and the power injections at different buses. The proposed schemes exhibit desirable apportioning properties and are easy to implement and understand. Case studies for different loading conditions are carried out to show the capability of the proposed schemes for solving the TCA problem. (author)

  13. Secure Hybrid Encryption from Weakened Key Encapsulation

    NARCIS (Netherlands)

    D. Hofheinz (Dennis); E. Kiltz (Eike); A. Menezes

    2007-01-01

    textabstractWe put forward a new paradigm for building hybrid encryption schemes from constrained chosen-ciphertext secure (CCCA) key-encapsulation mechanisms (KEMs) plus authenticated symmetric encryption. Constrained chosen-ciphertext security is a new security notion for KEMs that we propose. It

  14. Improving the performance of univariate control charts for abnormal detection and classification

    Science.gov (United States)

    Yiakopoulos, Christos; Koutsoudaki, Maria; Gryllias, Konstantinos; Antoniadis, Ioannis

    2017-03-01

    Bearing failures in rotating machinery can cause machine breakdown and economical loss, if no effective actions are taken on time. Therefore, it is of prime importance to detect accurately the presence of faults, especially at their early stage, to prevent sequent damage and reduce costly downtime. The machinery fault diagnosis follows a roadmap of data acquisition, feature extraction and diagnostic decision making, in which mechanical vibration fault feature extraction is the foundation and the key to obtain an accurate diagnostic result. A challenge in this area is the selection of the most sensitive features for various types of fault, especially when the characteristics of failures are difficult to be extracted. Thus, a plethora of complex data-driven fault diagnosis methods are fed by prominent features, which are extracted and reduced through traditional or modern algorithms. Since most of the available datasets are captured during normal operating conditions, the last decade a number of novelty detection methods, able to work when only normal data are available, have been developed. In this study, a hybrid method combining univariate control charts and a feature extraction scheme is introduced focusing towards an abnormal change detection and classification, under the assumption that measurements under normal operating conditions of the machinery are available. The feature extraction method integrates the morphological operators and the Morlet wavelets. The effectiveness of the proposed methodology is validated on two different experimental cases with bearing faults, demonstrating that the proposed approach can improve the fault detection and classification performance of conventional control charts.

  15. Performance analysis of switching based hybrid FSO/RF transmission

    KAUST Repository

    Usman, Muneer

    2014-09-01

    Hybrid free space optical (FSO)/ radio frequency (RF) systems have emerged as a promising solution for high data rate wireless back haul.We present and analyze a switching based transmission scheme for hybrid FSO/RF system. Specifically, either FSO or RF link will be active at a certain time instance, with FSO link enjoying a higher priority. Analytical expressions have been obtained for the outage probability, average bit error rate and ergodic capacity for the resulting system. Numerical examples are presented to compare the performance of the hybrid scheme with FSO only scenario.

  16. Performance analysis of switching based hybrid FSO/RF transmission

    KAUST Repository

    Usman, Muneer; Yang, Hongchuan; Alouini, Mohamed-Slim

    2014-01-01

    Hybrid free space optical (FSO)/ radio frequency (RF) systems have emerged as a promising solution for high data rate wireless back haul.We present and analyze a switching based transmission scheme for hybrid FSO/RF system. Specifically, either FSO or RF link will be active at a certain time instance, with FSO link enjoying a higher priority. Analytical expressions have been obtained for the outage probability, average bit error rate and ergodic capacity for the resulting system. Numerical examples are presented to compare the performance of the hybrid scheme with FSO only scenario.

  17. CLASSIFICATION AND DIAGNOSTICS OF ANEMIA IN CHILDREN

    OpenAIRE

    A. G. Rumyantsev

    2011-01-01

    Anemia in children is one of the most frequent somatic diseases. Criteria of anemia diagnosis are strictly regulated as decrease of hemoglobin/erythrocytes level accompanies majority of infectious, inflammatory, autoimmune, hereditary diseases and, in several cases, it is estimated as transitory disease in some periods of children’s growth and development. The article presents main classification and differential diagnostic schemes of anemia. Diagnostics makes accent on laboratory analysis; t...

  18. Measuring External Face Appearance for Face Classification

    OpenAIRE

    Masip, David; Lapedriza, Agata; Vitria, Jordi

    2007-01-01

    In this chapter we introduce the importance of the external features in face classification problems, and propose a methodology to extract the external features obtaining an aligned feature set. The extracted features can be used as input to any standard pattern recognition classifier, as the classic feature extraction approaches dealing with internal face regions in the literature. The resulting scheme follows a top-down segmentation approach to deal with the diversity inherent to the extern...

  19. Integrated resource management for Hybrid Optical Wireless (HOW) networks

    DEFF Research Database (Denmark)

    Yan, Ying; Yu, Hao; Wessing, Henrik

    2009-01-01

    Efficient utilization of available bandwidth over hybrid optical wireless networks is a critical issue, especially for multimedia applications with high data rates and stringent Quality of Service (QoS) requirements. In this paper, we propose an integrated resource management including an enhanced...... resource sharing scheme and an integrated admission control scheme for the hybrid optical wireless networks. It provides QoS guarantees for connections through both optical and wireless domain. Simulation results show that our proposed scheme improves QoS performances in terms of high throughput and low...

  20. Active flywheel control for hybrid vehicle; Compensation active des pulsations de couple dans un vehicule hybride

    Energy Technology Data Exchange (ETDEWEB)

    Tnani, S.; Coirault, P.; Champenois, G. [Ecole Superieure d' Ingenieurs, Lab. d' Automatique et d' Informatique Industrielle, 86 - Poitiers (France)

    2005-01-01

    In the paper, the authors propose a novel control strategy of torque ripple on hybrid vehicle. The combustion engine ripple's are reduced by using an active filter and an AC machine which is mounted on the crank-shaft to generate on inverse torque sequence. The control strategy is based on a multi-objectives state feedback synthesis. A complete modelling of the hybrid propulsion of the vehicle is achieved. Simulation results highlight the interest of the control scheme. (authors)

  1. Hybrid drive train technologies for vehicles

    NARCIS (Netherlands)

    Hofman, T.; Folkson, R.

    This chapter provides a classification of electric hybrid systems for cars and describes the conflicting design challenges involved in designing advanced vehicle propulsion systems. In addition, the chapter provides an analysis of the solution methods currently provided in literature on the coupled

  2. TFOS DEWS II Definition and Classification Report.

    Science.gov (United States)

    Craig, Jennifer P; Nichols, Kelly K; Akpek, Esen K; Caffery, Barbara; Dua, Harminder S; Joo, Choun-Ki; Liu, Zuguo; Nelson, J Daniel; Nichols, Jason J; Tsubota, Kazuo; Stapleton, Fiona

    2017-07-01

    The goals of the TFOS DEWS II Definition and Classification Subcommittee were to create an evidence-based definition and a contemporary classification system for dry eye disease (DED). The new definition recognizes the multifactorial nature of dry eye as a disease where loss of homeostasis of the tear film is the central pathophysiological concept. Ocular symptoms, as a broader term that encompasses reports of discomfort or visual disturbance, feature in the definition and the key etiologies of tear film instability, hyperosmolarity, and ocular surface inflammation and damage were determined to be important for inclusion in the definition. In the light of new data, neurosensory abnormalities were also included in the definition for the first time. In the classification of DED, recent evidence supports a scheme based on the pathophysiology where aqueous deficient and evaporative dry eye exist as a continuum, such that elements of each are considered in diagnosis and management. Central to the scheme is a positive diagnosis of DED with signs and symptoms, and this is directed towards management to restore homeostasis. The scheme also allows consideration of various related manifestations, such as non-obvious disease involving ocular surface signs without related symptoms, including neurotrophic conditions where dysfunctional sensation exists, and cases where symptoms exist without demonstrable ocular surface signs, including neuropathic pain. This approach is not intended to override clinical assessment and judgment but should prove helpful in guiding clinical management and research. Copyright © 2017 Elsevier Inc. All rights reserved.

  3. Hyper- and hybrid nonlocality

    Science.gov (United States)

    Li, Yanna; Gessner, Manuel; Li, Weidong; Smerzi, Augusto

    2018-02-01

    The controlled generation and identification of quantum correlations, usually encoded in either qubits or continuous degrees of freedom, builds the foundation of quantum information science. Recently, more sophisticated approaches, involving a combination of two distinct degrees of freedom, have been proposed to improve on the traditional strategies. Hyperentanglement describes simultaneous entanglement in more than one distinct degree of freedom, whereas hybrid entanglement refers to entanglement shared between a discrete and a continuous degree of freedom. In this work we propose a scheme that allows us to combine the two approaches, and to extend them to the strongest form of quantum correlations. Specifically, we show how two identical, initially separated particles can be manipulated to produce Bell nonlocality among their spins, among their momenta, as well as across their spins and momenta. We discuss possible experimental realizations with atomic and photonic systems.

  4. Music genre classification via likelihood fusion from multiple feature models

    Science.gov (United States)

    Shiu, Yu; Kuo, C.-C. J.

    2005-01-01

    Music genre provides an efficient way to index songs in a music database, and can be used as an effective means to retrieval music of a similar type, i.e. content-based music retrieval. A new two-stage scheme for music genre classification is proposed in this work. At the first stage, we examine a couple of different features, construct their corresponding parametric models (e.g. GMM and HMM) and compute their likelihood functions to yield soft classification results. In particular, the timbre, rhythm and temporal variation features are considered. Then, at the second stage, these soft classification results are integrated to result in a hard decision for final music genre classification. Experimental results are given to demonstrate the performance of the proposed scheme.

  5. Identification of hybrid node and link communities in complex networks.

    Science.gov (United States)

    He, Dongxiao; Jin, Di; Chen, Zheng; Zhang, Weixiong

    2015-03-02

    Identifying communities in complex networks is an effective means for analyzing complex systems, with applications in diverse areas such as social science, engineering, biology and medicine. Finding communities of nodes and finding communities of links are two popular schemes for network analysis. These schemes, however, have inherent drawbacks and are inadequate to capture complex organizational structures in real networks. We introduce a new scheme and an effective approach for identifying complex mixture structures of node and link communities, called hybrid node-link communities. A central piece of our approach is a probabilistic model that accommodates node, link and hybrid node-link communities. Our extensive experiments on various real-world networks, including a large protein-protein interaction network and a large network of semantically associated words, illustrated that the scheme for hybrid communities is superior in revealing network characteristics. Moreover, the new approach outperformed the existing methods for finding node or link communities separately.

  6. Identification of hybrid node and link communities in complex networks

    Science.gov (United States)

    He, Dongxiao; Jin, Di; Chen, Zheng; Zhang, Weixiong

    2015-03-01

    Identifying communities in complex networks is an effective means for analyzing complex systems, with applications in diverse areas such as social science, engineering, biology and medicine. Finding communities of nodes and finding communities of links are two popular schemes for network analysis. These schemes, however, have inherent drawbacks and are inadequate to capture complex organizational structures in real networks. We introduce a new scheme and an effective approach for identifying complex mixture structures of node and link communities, called hybrid node-link communities. A central piece of our approach is a probabilistic model that accommodates node, link and hybrid node-link communities. Our extensive experiments on various real-world networks, including a large protein-protein interaction network and a large network of semantically associated words, illustrated that the scheme for hybrid communities is superior in revealing network characteristics. Moreover, the new approach outperformed the existing methods for finding node or link communities separately.

  7. Password Authentication Based on Fractal Coding Scheme

    Directory of Open Access Journals (Sweden)

    Nadia M. G. Al-Saidi

    2012-01-01

    Full Text Available Password authentication is a mechanism used to authenticate user identity over insecure communication channel. In this paper, a new method to improve the security of password authentication is proposed. It is based on the compression capability of the fractal image coding to provide an authorized user a secure access to registration and login process. In the proposed scheme, a hashed password string is generated and encrypted to be captured together with the user identity using text to image mechanisms. The advantage of fractal image coding is to be used to securely send the compressed image data through a nonsecured communication channel to the server. The verification of client information with the database system is achieved in the server to authenticate the legal user. The encrypted hashed password in the decoded fractal image is recognized using optical character recognition. The authentication process is performed after a successful verification of the client identity by comparing the decrypted hashed password with those which was stored in the database system. The system is analyzed and discussed from the attacker’s viewpoint. A security comparison is performed to show that the proposed scheme provides an essential security requirement, while their efficiency makes it easier to be applied alone or in hybrid with other security methods. Computer simulation and statistical analysis are presented.

  8. Adaptive PCA based fault diagnosis scheme in imperial smelting process.

    Science.gov (United States)

    Hu, Zhikun; Chen, Zhiwen; Gui, Weihua; Jiang, Bin

    2014-09-01

    In this paper, an adaptive fault detection scheme based on a recursive principal component analysis (PCA) is proposed to deal with the problem of false alarm due to normal process changes in real process. Our further study is also dedicated to develop a fault isolation approach based on Generalized Likelihood Ratio (GLR) test and Singular Value Decomposition (SVD) which is one of general techniques of PCA, on which the off-set and scaling fault can be easily isolated with explicit off-set fault direction and scaling fault classification. The identification of off-set and scaling fault is also applied. The complete scheme of PCA-based fault diagnosis procedure is proposed. The proposed scheme is first applied to Imperial Smelting Process, and the results show that the proposed strategies can be able to mitigate false alarms and isolate faults efficiently. Copyright © 2013 ISA. Published by Elsevier Ltd. All rights reserved.

  9. Classification of debris flow phenomena in the Faroe Islands

    DEFF Research Database (Denmark)

    Dahl, Mads-Peter Jakob; E. Mortensen, Lis; Jensen, Niels H.

    2012-01-01

    Landslides and debris flow phenomena in particular constitute a threat to human activities in the Faroe Islands. As a contribution to ongoing landslide risk management research, this paper proposes a classification scheme for debris flow phenomena in the Faroe Islands. The scheme, produced through...... a multidisciplinary study involving geomorphological fieldwork and qualitative collection of indigenous landslide knowledge, presents physical characteristics to classify debris flow phenomena into groups named with Faroese terms. The following landslide definitions are proposed. Brekku-skriðulop (English translation...... with international landslide classification systems, significantly increases the knowledge of debris flow phenomena and promotes a consistent terminology of these within the Faroe Islands....

  10. Hybrid classifiers methods of data, knowledge, and classifier combination

    CERN Document Server

    Wozniak, Michal

    2014-01-01

    This book delivers a definite and compact knowledge on how hybridization can help improving the quality of computer classification systems. In order to make readers clearly realize the knowledge of hybridization, this book primarily focuses on introducing the different levels of hybridization and illuminating what problems we will face with as dealing with such projects. In the first instance the data and knowledge incorporated in hybridization were the action points, and then a still growing up area of classifier systems known as combined classifiers was considered. This book comprises the aforementioned state-of-the-art topics and the latest research results of the author and his team from Department of Systems and Computer Networks, Wroclaw University of Technology, including as classifier based on feature space splitting, one-class classification, imbalance data, and data stream classification.

  11. Web Page Classification Method Using Neural Networks

    Science.gov (United States)

    Selamat, Ali; Omatu, Sigeru; Yanagimoto, Hidekazu; Fujinaka, Toru; Yoshioka, Michifumi

    Automatic categorization is the only viable method to deal with the scaling problem of the World Wide Web (WWW). In this paper, we propose a news web page classification method (WPCM). The WPCM uses a neural network with inputs obtained by both the principal components and class profile-based features (CPBF). Each news web page is represented by the term-weighting scheme. As the number of unique words in the collection set is big, the principal component analysis (PCA) has been used to select the most relevant features for the classification. Then the final output of the PCA is combined with the feature vectors from the class-profile which contains the most regular words in each class before feeding them to the neural networks. We have manually selected the most regular words that exist in each class and weighted them using an entropy weighting scheme. The fixed number of regular words from each class will be used as a feature vectors together with the reduced principal components from the PCA. These feature vectors are then used as the input to the neural networks for classification. The experimental evaluation demonstrates that the WPCM method provides acceptable classification accuracy with the sports news datasets.

  12. Inventory classification based on decoupling points

    Directory of Open Access Journals (Sweden)

    Joakim Wikner

    2015-01-01

    Full Text Available The ideal state of continuous one-piece flow may never be achieved. Still the logistics manager can improve the flow by carefully positioning inventory to buffer against variations. Strategies such as lean, postponement, mass customization, and outsourcing all rely on strategic positioning of decoupling points to separate forecast-driven from customer-order-driven flows. Planning and scheduling of the flow are also based on classification of decoupling points as master scheduled or not. A comprehensive classification scheme for these types of decoupling points is introduced. The approach rests on identification of flows as being either demand based or supply based. The demand or supply is then combined with exogenous factors, classified as independent, or endogenous factors, classified as dependent. As a result, eight types of strategic as well as tactical decoupling points are identified resulting in a process-based framework for inventory classification that can be used for flow design.

  13. Coordinated renewable energy support schemes

    DEFF Research Database (Denmark)

    Morthorst, P.E.; Jensen, S.G.

    2006-01-01

    . The first example covers countries with regional power markets that also regionalise their support schemes, the second countries with separate national power markets that regionalise their support schemes. The main findings indicate that the almost ideal situation exists if the region prior to regionalising...

  14. CANONICAL BACKWARD DIFFERENTIATION SCHEMES FOR ...

    African Journals Online (AJOL)

    This paper describes a new nonlinear backward differentiation schemes for the numerical solution of nonlinear initial value problems of first order ordinary differential equations. The schemes are based on rational interpolation obtained from canonical polynomials. They are A-stable. The test problems show that they give ...

  15. Hybrid stars

    Indian Academy of Sciences (India)

    Hybrid stars. AsHOK GOYAL. Department of Physics and Astrophysics, University of Delhi, Delhi 110 007, India. Abstract. Recently there have been important developments in the determination of neutron ... number and the electric charge. ... available to the system to rearrange concentration of charges for a given fraction of.

  16. Enhanced land use/cover classification of heterogeneous tropical landscapes using support vector machines and textural homogeneity

    Science.gov (United States)

    Paneque-Gálvez, Jaime; Mas, Jean-François; Moré, Gerard; Cristóbal, Jordi; Orta-Martínez, Martí; Luz, Ana Catarina; Guèze, Maximilien; Macía, Manuel J.; Reyes-García, Victoria

    2013-08-01

    Land use/cover classification is a key research field in remote sensing and land change science as thematic maps derived from remotely sensed data have become the basis for analyzing many socio-ecological issues. However, land use/cover classification remains a difficult task and it is especially challenging in heterogeneous tropical landscapes where nonetheless such maps are of great importance. The present study aims at establishing an efficient classification approach to accurately map all broad land use/cover classes in a large, heterogeneous tropical area, as a basis for further studies (e.g., land use/cover change, deforestation and forest degradation). Specifically, we first compare the performance of parametric (maximum likelihood), non-parametric (k-nearest neighbor and four different support vector machines - SVM), and hybrid (unsupervised-supervised) classifiers, using hard and soft (fuzzy) accuracy assessments. We then assess, using the maximum likelihood algorithm, what textural indices from the gray-level co-occurrence matrix lead to greater classification improvements at the spatial resolution of Landsat imagery (30 m), and rank them accordingly. Finally, we use the textural index that provides the most accurate classification results to evaluate whether its usefulness varies significantly with the classifier used. We classified imagery corresponding to dry and wet seasons and found that SVM classifiers outperformed all the rest. We also found that the use of some textural indices, but particularly homogeneity and entropy, can significantly improve classifications. We focused on the use of the homogeneity index, which has so far been neglected in land use/cover classification efforts, and found that this index along with reflectance bands significantly increased the overall accuracy of all the classifiers, but particularly of SVM. We observed that improvements in producer's and user's accuracies through the inclusion of homogeneity were different

  17. Polsar Land Cover Classification Based on Hidden Polarimetric Features in Rotation Domain and Svm Classifier

    Science.gov (United States)

    Tao, C.-S.; Chen, S.-W.; Li, Y.-Z.; Xiao, S.-P.

    2017-09-01

    Land cover classification is an important application for polarimetric synthetic aperture radar (PolSAR) data utilization. Rollinvariant polarimetric features such as H / Ani / text-decoration: overline">α / Span are commonly adopted in PolSAR land cover classification. However, target orientation diversity effect makes PolSAR images understanding and interpretation difficult. Only using the roll-invariant polarimetric features may introduce ambiguity in the interpretation of targets' scattering mechanisms and limit the followed classification accuracy. To address this problem, this work firstly focuses on hidden polarimetric feature mining in the rotation domain along the radar line of sight using the recently reported uniform polarimetric matrix rotation theory and the visualization and characterization tool of polarimetric coherence pattern. The former rotates the acquired polarimetric matrix along the radar line of sight and fully describes the rotation characteristics of each entry of the matrix. Sets of new polarimetric features are derived to describe the hidden scattering information of the target in the rotation domain. The latter extends the traditional polarimetric coherence at a given rotation angle to the rotation domain for complete interpretation. A visualization and characterization tool is established to derive new polarimetric features for hidden information exploration. Then, a classification scheme is developed combing both the selected new hidden polarimetric features in rotation domain and the commonly used roll-invariant polarimetric features with a support vector machine (SVM) classifier. Comparison experiments based on AIRSAR and multi-temporal UAVSAR data demonstrate that compared with the conventional classification scheme which only uses the roll-invariant polarimetric features, the proposed classification scheme achieves both higher classification accuracy and better robustness. For AIRSAR data, the overall classification

  18. POLSAR LAND COVER CLASSIFICATION BASED ON HIDDEN POLARIMETRIC FEATURES IN ROTATION DOMAIN AND SVM CLASSIFIER

    Directory of Open Access Journals (Sweden)

    C.-S. Tao

    2017-09-01

    Full Text Available Land cover classification is an important application for polarimetric synthetic aperture radar (PolSAR data utilization. Rollinvariant polarimetric features such as H / Ani / α / Span are commonly adopted in PolSAR land cover classification. However, target orientation diversity effect makes PolSAR images understanding and interpretation difficult. Only using the roll-invariant polarimetric features may introduce ambiguity in the interpretation of targets’ scattering mechanisms and limit the followed classification accuracy. To address this problem, this work firstly focuses on hidden polarimetric feature mining in the rotation domain along the radar line of sight using the recently reported uniform polarimetric matrix rotation theory and the visualization and characterization tool of polarimetric coherence pattern. The former rotates the acquired polarimetric matrix along the radar line of sight and fully describes the rotation characteristics of each entry of the matrix. Sets of new polarimetric features are derived to describe the hidden scattering information of the target in the rotation domain. The latter extends the traditional polarimetric coherence at a given rotation angle to the rotation domain for complete interpretation. A visualization and characterization tool is established to derive new polarimetric features for hidden information exploration. Then, a classification scheme is developed combing both the selected new hidden polarimetric features in rotation domain and the commonly used roll-invariant polarimetric features with a support vector machine (SVM classifier. Comparison experiments based on AIRSAR and multi-temporal UAVSAR data demonstrate that compared with the conventional classification scheme which only uses the roll-invariant polarimetric features, the proposed classification scheme achieves both higher classification accuracy and better robustness. For AIRSAR data, the overall classification accuracy

  19. Hand eczema classification

    DEFF Research Database (Denmark)

    Diepgen, T L; Andersen, Klaus Ejner; Brandao, F M

    2008-01-01

    of the disease is rarely evidence based, and a classification system for different subdiagnoses of hand eczema is not agreed upon. Randomized controlled trials investigating the treatment of hand eczema are called for. For this, as well as for clinical purposes, a generally accepted classification system...... A classification system for hand eczema is proposed. Conclusions It is suggested that this classification be used in clinical work and in clinical trials....

  20. Minimum acceptable face velocities of laboratory fume hoods and guidelines for their classification

    International Nuclear Information System (INIS)

    Bolton, N.E.; Porter, W.E.; Alcorn, S.P.; Everett, W.S.; Hunt, J.B.; Morehead, J.F.; Higdon, H.F.

    1978-06-01

    Data developed to support the requirement of a 100 LFM minimum face velocity requirement for laboratory fume hoods are summarized. Also included is a description of the Y-12 test hood as well as guidelines for a hood classification scheme