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.

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.

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...

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...

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

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 ...

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.

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.

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

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.

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…

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.

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.)

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)

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.

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)

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.

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…

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.

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.

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…

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

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.

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...

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.

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.

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

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

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.

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.

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...

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.

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.

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.

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*).

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%.

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...

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.

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.

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.

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.

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.

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…

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;

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...

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.

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.

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.

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.

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

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...

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.

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.

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 %.

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.

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

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...

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.

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.

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.

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)

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.

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.

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.

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...

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

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.

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.

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

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.

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)

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

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.

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.

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.

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

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.

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)

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...

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.

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.

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.

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.

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.

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)

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.

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.

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

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.

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.

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.

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

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.

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)

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.

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.

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

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.

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.

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.

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)

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.

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...

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...

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.

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.

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.

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.

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.

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.

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.

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.

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)

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.

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.

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

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

Churn prediction on huge telecom data using hybrid firefly based classification

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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.

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

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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.

A Hybrid ICA-SVM Approach for Determining the Quality Variables at Fault in a Multivariate Process

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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.

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

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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.

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

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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.

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

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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

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.

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

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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.

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

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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.

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

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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

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.

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...

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

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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.

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

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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.

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

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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.

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....

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

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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.

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

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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.

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.

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.

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.

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

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.

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.

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...

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.

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.

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.

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...

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.

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

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.

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.

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.

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.

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.

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.

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.

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.

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.

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...

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.

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.

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.

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)

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.

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

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.

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....

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.

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 ...

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.

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.

A general range-separated double-hybrid density-functional theory.

Science.gov (United States)

Kalai, Cairedine; Toulouse, Julien

2018-04-28

A range-separated double-hybrid (RSDH) scheme which generalizes the usual range-separated hybrids and double hybrids is developed. This scheme consistently uses a two-parameter Coulomb-attenuating-method (CAM)-like decomposition of the electron-electron interaction for both exchange and correlation in order to combine Hartree-Fock exchange and second-order Møller-Plesset (MP2) correlation with a density functional. The RSDH scheme relies on an exact theory which is presented in some detail. Several semi-local approximations are developed for the short-range exchange-correlation density functional involved in this scheme. After finding optimal values for the two parameters of the CAM-like decomposition, the RSDH scheme is shown to have a relatively small basis dependence and to provide atomization energies, reaction barrier heights, and weak intermolecular interactions globally more accurate or comparable to range-separated MP2 or standard MP2. The RSDH scheme represents a new family of double hybrids with minimal empiricism which could be useful for general chemical applications.

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...

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.

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

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 ...

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...

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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

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

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…

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.

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...

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.

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.

Cheese Classification, Characterization, and Categorization: A Global Perspective.

Science.gov (United States)

Almena-Aliste, Montserrat; Mietton, Bernard

2014-02-01

Cheese is one of the most fascinating, complex, and diverse foods enjoyed today. Three elements constitute the cheese ecosystem: ripening agents, consisting of enzymes and microorganisms; the composition of the fresh cheese; and the environmental conditions during aging. These factors determine and define not only the sensory quality of the final cheese product but also the vast diversity of cheeses produced worldwide. How we define and categorize cheese is a complicated matter. There are various approaches to cheese classification, and a global approach for classification and characterization is needed. We review current cheese classification schemes and the limitations inherent in each of the schemes described. While some classification schemes are based on microbiological criteria, others rely on descriptions of the technologies used for cheese production. The goal of this review is to present an overview of comprehensive and practical integrative classification models in order to better describe cheese diversity and the fundamental differences within cheeses, as well as to connect fundamental technological, microbiological, chemical, and sensory characteristics to contribute to an overall characterization of the main families of cheese, including the expanding world of American artisanal cheeses.

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

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

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.

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

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.

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.

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.

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

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....

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.

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.

A new hybrid BCI paradigm based on P300 and SSVEP.

Science.gov (United States)

Wang, Minjue; Daly, Ian; Allison, Brendan Z; Jin, Jing; Zhang, Yu; Chen, Lanlan; Wang, Xingyu

2015-04-15

P300 and steady-state visual evoked potential (SSVEP) approaches have been widely used for brain-computer interface (BCI) systems. However, neither of these approaches can work for all subjects. Some groups have reported that a hybrid BCI that combines two or more approaches might provide BCI functionality to more users. Hybrid P300/SSVEP BCIs have only recently been developed and validated, and very few avenues to improve performance have been explored. The present study compares an established hybrid P300/SSVEP BCIs paradigm to a new paradigm in which shape changing, instead of color changing, is adopted for P300 evocation to decrease the degradation on SSVEP strength. The result shows that the new hybrid paradigm presented in this paper yields much better performance than the normal hybrid paradigm. A performance increase of nearly 20% in SSVEP classification is achieved using the new hybrid paradigm in comparison with the normal hybrid paradigm. All the paradigms except the normal hybrid paradigm used in this paper obtain 100% accuracy in P300 classification. The new hybrid P300/SSVEP BCIs paradigm in which shape changing, instead of color changing, could obtain as high classification accuracy of SSVEP as the traditional SSVEP paradigm and could obtain as high classification accuracy of P300 as the traditional P300 paradigm. P300 did not interfere with the SSVEP response using the new hybrid paradigm presented in this paper, which was superior to the normal hybrid P300/SSVEP paradigm. Copyright © 2014 Elsevier B.V. All rights reserved.

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....

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.

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.

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.

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

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...

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...

A novel hybrid approach with multidimensional-like effects for compressible flow computations

Science.gov (United States)

Kalita, Paragmoni; Dass, Anoop K.

2017-07-01

A multidimensional scheme achieves good resolution of strong and weak shocks irrespective of whether the discontinuities are aligned with or inclined to the grid. However, these schemes are computationally expensive. This paper achieves similar effects by hybridizing two schemes, namely, AUSM and DRLLF and coupling them through a novel shock switch that operates - unlike existing switches - on the gradient of the Mach number across the cell-interface. The schemes that are hybridized have contrasting properties. The AUSM scheme captures grid-aligned (and strong) shocks crisply but it is not so good for non-grid-aligned weaker shocks, whereas the DRLLF scheme achieves sharp resolution of non-grid-aligned weaker shocks, but is not as good for grid-aligned strong shocks. It is our experience that if conventional shock switches based on variables like density, pressure or Mach number are used to combine the schemes, the desired effect of crisp resolution of grid-aligned and non-grid-aligned discontinuities are not obtained. To circumvent this problem we design a shock switch based - for the first time - on the gradient of the cell-interface Mach number with very impressive results. Thus the strategy of hybridizing two carefully selected schemes together with the innovative design of the shock switch that couples them, affords a method that produces the effects of a multidimensional scheme with a lower computational cost. It is further seen that hybridization of the AUSM scheme with the recently developed DRLLFV scheme using the present shock switch gives another scheme that provides crisp resolution for both shocks and boundary layers. Merits of the scheme are established through a carefully selected set of numerical experiments.

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.

Physiotherapy movement based classification approaches to low back pain: comparison of subgroups through review and developer/expert survey

Directory of Open Access Journals (Sweden)

Karayannis Nicholas V

2012-02-01

Full Text Available Abstract Background Several classification schemes, each with its own philosophy and categorizing method, subgroup low back pain (LBP patients with the intent to guide treatment. Physiotherapy derived schemes usually have a movement impairment focus, but the extent to which other biological, psychological, and social factors of pain are encompassed requires exploration. Furthermore, within the prevailing 'biological' domain, the overlap of subgrouping strategies within the orthopaedic examination remains unexplored. The aim of this study was "to review and clarify through developer/expert survey, the theoretical basis and content of physical movement classification schemes, determine their relative reliability and similarities/differences, and to consider the extent of incorporation of the bio-psycho-social framework within the schemes". Methods A database search for relevant articles related to LBP and subgrouping or classification was conducted. Five dominant movement-based schemes were identified: Mechanical Diagnosis and Treatment (MDT, Treatment Based Classification (TBC, Pathoanatomic Based Classification (PBC, Movement System Impairment Classification (MSI, and O'Sullivan Classification System (OCS schemes. Data were extracted and a survey sent to the classification scheme developers/experts to clarify operational criteria, reliability, decision-making, and converging/diverging elements between schemes. Survey results were integrated into the review and approval obtained for accuracy. Results Considerable diversity exists between schemes in how movement informs subgrouping and in the consideration of broader neurosensory, cognitive, emotional, and behavioural dimensions of LBP. Despite differences in assessment philosophy, a common element lies in their objective to identify a movement pattern related to a pain reduction strategy. Two dominant movement paradigms emerge: (i loading strategies (MDT, TBC, PBC aimed at eliciting a phenomenon

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.

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.

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...

Hybrid nodal methods in the solution of the diffusion equations in X Y geometry

International Nuclear Information System (INIS)

Hernandez M, N.; Alonso V, G.; Valle G, E. del

2003-01-01

In 1979, Hennart and collaborators applied several schemes of classic finite element in the numerical solution of the diffusion equations in X Y geometry and stationary state. Almost two decades then, in 1996, himself and other collaborators carried out a similar work but using nodal schemes type finite element. Continuing in this last direction, in this work a group it is described a set of several Hybrid Nodal schemes denominated (NH) as well as their application to solve the diffusion equations in multigroup in stationary state and X Y geometry. The term hybrid nodal it means that such schemes interpolate not only Legendre moments of face and of cell but also the values of the scalar flow of neutrons in the four corners of each cell or element of the spatial discretization of the domain of interest. All the schemes here considered are polynomials like they were it their predecessors. Particularly, its have developed and applied eight different hybrid nodal schemes that its are very nearby related with those developed by Hennart and collaborators in the past. It is treated of schemes in those that nevertheless that decreases the number of interpolation parameters it is conserved the accurate in relation to the bi-quadratic and bi-cubic schemes. Of these eight, three were described and applied in a previous work. It is the bi-lineal classic scheme as well as the hybrid nodal schemes, bi-quadratic and bi-cubic for that here only are described the other 5 hybrid nodal schemes although they are provided numerical results for several test problems with all them. (Author)

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.

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.

Cluster synchronization in community network with hybrid coupling

International Nuclear Information System (INIS)

Yang, Lixin; Jiang, Jun; Liu, Xiaojun

2016-01-01

Highlights: • A community network model with hybrid coupling is proposed. • Control scheme is designed via combining adaptive external coupling strength and feedback control. • The influence of topology structure on synchronization of community network is discussed. - Abstract: A general model of community network with hybrid coupling is proposed in this paper. In the community network model with hybrid coupling, the inner connections are in the same type of coupling within the same community and in different types of coupling in different communities. The connections between different pair of communities are also nonidentical. Cluster synchronization of community network with hybrid coupling is investigated via adaptive couplings control scheme. Effective controllers are designed for constructing an effective control scheme and adjusting automatically the adaptive external coupling strength by taking external coupling strength as adaptive variables on a small fraction of network edges. Moreover, the impact of the topology on the synchronizability of community network is investigated. The numerical results reveal that the number of links between communities and the degree of the connector nodes have significant effects on the synchronization performance.

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

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

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.

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.

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

Hybrid analysis of multiaxis electromagnetic data for discrimination of munitions and explosives of concern

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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

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

Defuzzification Strategies for Fuzzy Classifications of Remote Sensing Data

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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.

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

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

Hybrid overlay metrology with CDSEM in a BEOL patterning scheme

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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).

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.

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.

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.

Discriminant forest classification method and system

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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.

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.

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)

Do thoraco-lumbar spinal injuries classification systems exhibit lower inter- and intra-observer agreement than other fractures classifications?: A comparison using fractures of the trochanteric area of the proximal femur as contrast model.

Science.gov (United States)

Urrutia, Julio; Zamora, Tomas; Klaber, Ianiv; Carmona, Maximiliano; Palma, Joaquin; Campos, Mauricio; Yurac, Ratko

2016-04-01

It has been postulated that the complex patterns of spinal injuries have prevented adequate agreement using thoraco-lumbar spinal injuries (TLSI) classifications; however, limb fracture classifications have also shown variable agreements. This study compared agreement using two TLSI classifications with agreement using two classifications of fractures of the trochanteric area of the proximal femur (FTAPF). Six evaluators classified the radiographs and computed tomography scans of 70 patients with acute TLSI using the Denis and the new AO Spine thoraco-lumbar injury classifications. Additionally, six evaluators classified the radiographs of 70 patients with FTAPF using the Tronzo and the AO schemes. Six weeks later, all cases were presented in a random sequence for repeat assessment. The Kappa coefficient (κ) was used to determine agreement. Inter-observer agreement: For TLSI, using the AOSpine classification, the mean κ was 0.62 (0.57-0.66) considering fracture types, and 0.55 (0.52-0.57) considering sub-types; using the Denis classification, κ was 0.62 (0.59-0.65). For FTAPF, with the AO scheme, the mean κ was 0.58 (0.54-0.63) considering fracture types and 0.31 (0.28-0.33) considering sub-types; for the Tronzo classification, κ was 0.54 (0.50-0.57). Intra-observer agreement: For TLSI, using the AOSpine scheme, the mean κ was 0.77 (0.72-0.83) considering fracture types, and 0.71 (0.67-0.76) considering sub-types; for the Denis classification, κ was 0.76 (0.71-0.81). For FTAPF, with the AO scheme, the mean κ was 0.75 (0.69-0.81) considering fracture types and 0.45 (0.39-0.51) considering sub-types; for the Tronzo classification, κ was 0.64 (0.58-0.70). Using the main types of AO classifications, inter- and intra-observer agreement of TLSI were comparable to agreement evaluating FTAPF; including sub-types, inter- and intra-observer agreement evaluating TLSI were significantly better than assessing FTAPF. Inter- and intra-observer agreements using the Denis

TFM classification and staging of oral submucous fibrosis: A new proposal.

Science.gov (United States)

Arakeri, Gururaj; Thomas, Deepak; Aljabab, Abdulsalam S; Hunasgi, Santosh; Rai, Kirthi Kumar; Hale, Beverley; Fonseca, Felipe Paiva; Gomez, Ricardo Santiago; Rahimi, Siavash; Merkx, Matthias A W; Brennan, Peter A

2018-04-01

We have evaluated the rationale of existing grading and staging schemes of oral submucous fibrosis (OSMF) based on how they are categorized. A novel classification and staging scheme is proposed. A total of 300 OSMF patients were evaluated for agreement between functional, clinical, and histopathological staging. Bilateral biopsies were assessed in 25 patients to evaluate for any differences in histopathological staging of OSMF in the same mouth. Extent of clinician agreement for categorized staging data was evaluated using Cohen's weighted kappa analysis. Cross-tabulation was performed on categorical grading data to understand the intercorrelation, and the unweighted kappa analysis was used to assess the bilateral grade agreement. Probabilities of less than 0.05 were considered significant. Data were analyzed using SPSS Statistics (version 25.0, IBM, USA). A low agreement was found between all the stages depicting the independent nature of trismus, clinical features, and histopathological components (K = 0.312, 0.167, 0.152) in OSMF. Following analysis, a three-component classification scheme (TFM classification) was developed that describes the severity of each independently, grouping them using a novel three-tier staging scheme as a guide to the treatment plan. The proposed classification and staging could be useful for effective communication, categorization, and for recording data and prognosis, and for guiding treatment plans. Furthermore, the classification considers OSMF malignant transformation in detail. © 2018 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.

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

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

The family and family structure classification redefined for the current times

Directory of Open Access Journals (Sweden)

Rahul Sharma

2013-01-01

Full Text Available The family is a basic unit of study in many medical and social science disciplines. Definitions of family have varied from country to country, and also within country. Because of this and the changing realities of the current times, there is a felt need for redefining the family and the common family structure types, for the purpose of study of the family as a factor in health and other variables of interest. A redefinition of a ′′family′′ has been proposed and various nuances of the definition are also discussed in detail. A classification scheme for the various types of family has also been put forward. A few exceptional case scenarios have been envisaged and their classification as per the new scheme is discussed, in a bid to clarify the classification scheme further. The proposed scheme should prove to be of use across various countries and cultures, for broadly classifying the family structure. The unique scenarios of particular cultures can be taken into account by defining region or culture-specific subtypes of the overall types of family structure.

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, ...

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.

The impact of catchment source group classification on the accuracy of sediment fingerprinting outputs.

Science.gov (United States)

Pulley, Simon; Foster, Ian; Collins, Adrian L

2017-06-01

The objective classification of sediment source groups is at present an under-investigated aspect of source tracing studies, which has the potential to statistically improve discrimination between sediment sources and reduce uncertainty. This paper investigates this potential using three different source group classification schemes. The first classification scheme was simple surface and subsurface groupings (Scheme 1). The tracer signatures were then used in a two-step cluster analysis to identify the sediment source groupings naturally defined by the tracer signatures (Scheme 2). The cluster source groups were then modified by splitting each one into a surface and subsurface component to suit catchment management goals (Scheme 3). The schemes were tested using artificial mixtures of sediment source samples. Controlled corruptions were made to some of the mixtures to mimic the potential causes of tracer non-conservatism present when using tracers in natural fluvial environments. It was determined how accurately the known proportions of sediment sources in the mixtures were identified after unmixing modelling using the three classification schemes. The cluster analysis derived source groups (2) significantly increased tracer variability ratios (inter-/intra-source group variability) (up to 2122%, median 194%) compared to the surface and subsurface groupings (1). As a result, the composition of the artificial mixtures was identified an average of 9.8% more accurately on the 0-100% contribution scale. It was found that the cluster groups could be reclassified into a surface and subsurface component (3) with no significant increase in composite uncertainty (a 0.1% increase over Scheme 2). The far smaller effects of simulated tracer non-conservatism for the cluster analysis based schemes (2 and 3) was primarily attributed to the increased inter-group variability producing a far larger sediment source signal that the non-conservatism noise (1). Modified cluster analysis

General concept of a gas engine for a hybrid vehicle, operating on methanol dissociation products

International Nuclear Information System (INIS)

Tartakovsky, L.; Aleinikov, Y.; Fainberg, V.; Garbar, A.; Gutman, M.; Hetsroni, G.; Schindler, Y.; Zvirin, Y.

1998-01-01

The paper presents a general concept of a hybrid propulsion system, based on an SI internal combustion engine fueled by methanol dissociation products (MDP). The proposed hybrid propulsion scheme is a series hybrid, which allows the engine to be operated in an on-off mode at constant optimal regime. The engine is fed by gaseous products of methanol dissociation (mainly hydrogen and carbon monoxide) emerging from an on-board catalytic reformer. The general scheme and base operation features of the propulsion system are described. The benefits that may be achieved by combining the well-known idea of on-board methanol dissociation with the hybrid vehicle concept are discussed. The proposed scheme is compared with those of systems operating on gasoline, liquid methanol, hydrogen and also with the multi-regime (not hybrid) engine fed by MDP

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

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.

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

New KF-PP-SVM classification method for EEG in brain-computer interfaces.

Science.gov (United States)

Yang, Banghua; Han, Zhijun; Zan, Peng; Wang, Qian

2014-01-01

Classification methods are a crucial direction in the current study of brain-computer interfaces (BCIs). To improve the classification accuracy for electroencephalogram (EEG) signals, a novel KF-PP-SVM (kernel fisher, posterior probability, and support vector machine) classification method is developed. Its detailed process entails the use of common spatial patterns to obtain features, based on which the within-class scatter is calculated. Then the scatter is added into the kernel function of a radial basis function to construct a new kernel function. This new kernel is integrated into the SVM to obtain a new classification model. Finally, the output of SVM is calculated based on posterior probability and the final recognition result is obtained. To evaluate the effectiveness of the proposed KF-PP-SVM method, EEG data collected from laboratory are processed with four different classification schemes (KF-PP-SVM, KF-SVM, PP-SVM, and SVM). The results showed that the overall average improvements arising from the use of the KF-PP-SVM scheme as opposed to KF-SVM, PP-SVM and SVM schemes are 2.49%, 5.83 % and 6.49 % respectively.

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...

Low-Dissipation Advection Schemes Designed for Large Eddy Simulations of Hypersonic Propulsion Systems

Science.gov (United States)

White, Jeffrey A.; Baurle, Robert A.; Fisher, Travis C.; Quinlan, Jesse R.; Black, William S.

2012-01-01

The 2nd-order upwind inviscid flux scheme implemented in the multi-block, structured grid, cell centered, finite volume, high-speed reacting flow code VULCAN has been modified to reduce numerical dissipation. This modification was motivated by the desire to improve the codes ability to perform large eddy simulations. The reduction in dissipation was accomplished through a hybridization of non-dissipative and dissipative discontinuity-capturing advection schemes that reduces numerical dissipation while maintaining the ability to capture shocks. A methodology for constructing hybrid-advection schemes that blends nondissipative fluxes consisting of linear combinations of divergence and product rule forms discretized using 4th-order symmetric operators, with dissipative, 3rd or 4th-order reconstruction based upwind flux schemes was developed and implemented. A series of benchmark problems with increasing spatial and fluid dynamical complexity were utilized to examine the ability of the candidate schemes to resolve and propagate structures typical of turbulent flow, their discontinuity capturing capability and their robustness. A realistic geometry typical of a high-speed propulsion system flowpath was computed using the most promising of the examined schemes and was compared with available experimental data to demonstrate simulation fidelity.

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…

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.

Etiological classification of ischemic stroke in young patients: a comparative study of TOAST, CCS, and ASCO.

Science.gov (United States)

Gökçal, Elif; Niftaliyev, Elvin; Asil, Talip

2017-09-01

Analysis of stroke subtypes is important for making treatment decisions and prognostic evaluations. The TOAST classification system is most commonly used, but the CCS and ASCO classification systems might be more useful to identify stroke etiologies in young patients whose strokes have a wide range of different causes. In this manuscript, we aim to compare the differences in subtype classification between TOAST, CCS, and ASCO in young stroke patients. The TOAST, CCS, and ASCO classification schemes were applied to 151 patients with ischemic stroke aged 18-49 years old and the proportion of subtypes classified by each scheme was compared. For comparison, determined etiologies were defined as cases with evident and probable subtypes when using the CCS scheme and cases with grade 1 and 2 subtypes but no other grade 1 subtype when using the ASCO scheme. The McNemar test with Bonferroni correction was used to assess significance. By TOAST, 41.1% of patients' stroke etiology was classified as undetermined etiology, 19.2% as cardioembolic, 13.2% as large artery atherosclerosis, 11.3% as small vessel occlusion, and 15.2% as other causes. Compared with TOAST, both CCS and ASCO assigned fewer patients to the undetermined etiology group (30.5% p CCS and ASCO classification schemes in young stroke patients seems feasible, and using both schemes may result in fewer patients being classified as undetermined etiology. New studies with more patients and a prospective design are needed to explore this topic further.

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

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.

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

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...

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

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...

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.

Strong Convergence of Hybrid Algorithm for Asymptotically Nonexpansive Mappings in Hilbert Spaces

Directory of Open Access Journals (Sweden)

Juguo Su

2012-01-01

Full Text Available The hybrid algorithms for constructing fixed points of nonlinear mappings have been studied extensively in recent years. The advantage of this methods is that one can prove strong convergence theorems while the traditional iteration methods just have weak convergence. In this paper, we propose two types of hybrid algorithm to find a common fixed point of a finite family of asymptotically nonexpansive mappings in Hilbert spaces. One is cyclic Mann's iteration scheme, and the other is cyclic Halpern's iteration scheme. We prove the strong convergence theorems for both iteration schemes.

MAS Based Event-Triggered Hybrid Control for Smart Microgrids

DEFF Research Database (Denmark)

Dou, Chunxia; Liu, Bin; Guerrero, Josep M.

2013-01-01

This paper is focused on an advanced control for autonomous microgrids. In order to improve the performance regarding security and stability, a hierarchical decentralized coordinated control scheme is proposed based on multi-agents structure. Moreover, corresponding to the multi-mode and the hybrid...... haracteristics of microgrids, an event-triggered hybrid control, including three kinds of switching controls, is designed to intelligently reconstruct operation mode when the security stability assessment indexes or the constraint conditions are violated. The validity of proposed control scheme is demonstrated...

Classification of instability after reverse shoulder arthroplasty guides surgical management and outcomes.

Science.gov (United States)

Abdelfattah, Adham; Otto, Randall J; Simon, Peter; Christmas, Kaitlyn N; Tanner, Gregory; LaMartina, Joey; Levy, Jonathan C; Cuff, Derek J; Mighell, Mark A; Frankle, Mark A

2018-04-01

Revision of unstable reverse shoulder arthroplasty (RSA) remains a significant challenge. The purpose of this study was to determine the reliability of a new treatment-guiding classification for instability after RSA, to describe the clinical outcomes of patients stabilized operatively, and to identify those with higher risk of recurrence. All patients undergoing revision for instability after RSA were identified at our institution. Demographic, clinical, radiographic, and intraoperative data were collected. A classification was developed using all identified causes of instability after RSA and allocating them to 1 of 3 defined treatment-guiding categories. Eight surgeons reviewed all data and applied the classification scheme to each case. Interobserver and intraobserver reliability was used to evaluate the classification scheme. Preoperative clinical outcomes were compared with final follow-up in stabilized shoulders. Forty-three revision cases in 34 patients met the inclusion for study. Five patients remained unstable after revision. Persistent instability most commonly occurred in persistent deltoid dysfunction and postoperative acromial fractures but also in 1 case of soft tissue impingement. Twenty-one patients remained stable at minimum 2 years of follow-up and had significant improvement of clinical outcome scores and range of motion. Reliability of the classification scheme showed substantial and almost perfect interobserver and intraobserver agreement among all the participants (κ = 0.699 and κ = 0.851, respectively). Instability after RSA can be successfully treated with revision surgery using the reliable treatment-guiding classification scheme presented herein. However, more understanding is needed for patients with greater risk of recurrent instability after revision surgery. Copyright © 2017 Journal of Shoulder and Elbow Surgery Board of Trustees. Published by Elsevier Inc. All rights reserved.

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.

Joint Adaptive Modulation and Combining for Hybrid FSO/RF Systems

KAUST Repository

Rakia, Tamer

2015-11-12

In this paper, we present and analyze a new transmission scheme for hybrid FSO/RF communication system based on joint adaptive modulation and adaptive combining. Specifically, the data rate on the FSO link is adjusted in discrete manner according to the FSO link\\'s instantaneous received signal-to-noise-ratio (SNR). If the FSO link\\'s quality is too poor to maintain the target bit-error-rate, the system activates the RF link along with the FSO link. When the RF link is activated, simultaneous transmission of the same modulated data takes place on both links, where the received signals from both links are combined using maximal ratio combining scheme. In this case, the data rate of the system is adjusted according to the instantaneous combined SNRs. Novel analytical expression for the cumulative distribution function (CDF) of the received SNR for the proposed adaptive hybrid system is obtained. This CDF expression is used to study the spectral and outage performances of the proposed adaptive hybrid FSO/RF system. Numerical examples are presented to compare the performance of the proposed adaptive hybrid FSO/RF system with that of switch-over hybrid FSO/RF and FSO-only systems employing the same adaptive modulation schemes. © 2015 IEEE.

The Classification of Hysteria and Related Disorders: Historical and Phenomenological Considerations

Science.gov (United States)

North, Carol S.

2015-01-01

This article examines the history of the conceptualization of dissociative, conversion, and somatoform syndromes in relation to one another, chronicles efforts to classify these and other phenomenologically-related psychopathology in the American diagnostic system for mental disorders, and traces the subsequent divergence in opinions of dissenting sectors on classification of these disorders. This article then considers the extensive phenomenological overlap across these disorders in empirical research, and from this foundation presents a new model for the conceptualization of these disorders. The classification of disorders formerly known as hysteria and phenomenologically-related syndromes has long been contentious and unsettled. Examination of the long history of the conceptual difficulties, which remain inherent in existing classification schemes for these disorders, can help to address the continuing controversy. This review clarifies the need for a major conceptual revision of the current classification of these disorders. A new phenomenologically-based classification scheme for these disorders is proposed that is more compatible with the agnostic and atheoretical approach to diagnosis of mental disorders used by the current classification system. PMID:26561836

The Classification of Hysteria and Related Disorders: Historical and Phenomenological Considerations

Directory of Open Access Journals (Sweden)

Carol S. North

2015-11-01

Full Text Available This article examines the history of the conceptualization of dissociative, conversion, and somatoform syndromes in relation to one another, chronicles efforts to classify these and other phenomenologically-related psychopathology in the American diagnostic system for mental disorders, and traces the subsequent divergence in opinions of dissenting sectors on classification of these disorders. This article then considers the extensive phenomenological overlap across these disorders in empirical research, and from this foundation presents a new model for the conceptualization of these disorders. The classification of disorders formerly known as hysteria and phenomenologically-related syndromes has long been contentious and unsettled. Examination of the long history of the conceptual difficulties, which remain inherent in existing classification schemes for these disorders, can help to address the continuing controversy. This review clarifies the need for a major conceptual revision of the current classification of these disorders. A new phenomenologically-based classification scheme for these disorders is proposed that is more compatible with the agnostic and atheoretical approach to diagnosis of mental disorders used by the current classification system.

Classification of diffuse lung diseases: why and how.

Science.gov (United States)

Hansell, David M

2013-09-01

The understanding of complex lung diseases, notably the idiopathic interstitial pneumonias and small airways diseases, owes as much to repeated attempts over the years to classify them as to any single conceptual breakthrough. One of the many benefits of a successful classification scheme is that it allows workers, within and between disciplines, to be clear that they are discussing the same disease. This may be of particular importance in the recruitment of individuals for a clinical trial that requires a standardized and homogeneous study population. Different specialties require fundamentally different things from a classification: for epidemiologic studies, a classification that requires categorization of individuals according to histopathologic pattern is not usually practicable. Conversely, a scheme that simply divides diffuse parenchymal disease into inflammatory and noninflammatory categories is unlikely to further the understanding about the pathogenesis of disease. Thus, for some disease groupings, for example, pulmonary vasculopathies, there may be several appropriate classifications, each with its merits and demerits. There has been an interesting shift in the past few years, from the accepted primacy of histopathology as the sole basis on which the classification of parenchymal lung disease has rested, to new ways of considering how these entities relate to each other. Some inventive thinking has resulted in new classifications that undoubtedly benefit patients and clinicians in their endeavor to improve management and outcome. The challenge of understanding the logic behind current classifications and their shortcomings are explored in various examples of lung diseases.

PARAMETER ESTIMATION OF THE HYBRID CENSORED LOMAX DISTRIBUTION

Directory of Open Access Journals (Sweden)

Samir Kamel Ashour

2010-12-01

Full Text Available Survival analysis is used in various fields for analyzing data involving the duration between two events. It is also known as event history analysis, lifetime data analysis, reliability analysis or time to event analysis. One of the difficulties which arise in this area is the presence of censored data. The lifetime of an individual is censored when it cannot be exactly measured but partial information is available. Different circumstances can produce different types of censoring. The two most common censoring schemes used in life testing experiments are Type-I and Type-II censoring schemes. Hybrid censoring scheme is mixture of Type-I and Type-II censoring scheme. In this paper we consider the estimation of parameters of Lomax distribution based on hybrid censored data. The parameters are estimated by the maximum likelihood and Bayesian methods. The Fisher information matrix has been obtained and it can be used for constructing asymptotic confidence intervals.

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...

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.

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

High speed corner and gap-seal computations using an LU-SGS scheme

Science.gov (United States)

Coirier, William J.

1989-01-01

The hybrid Lower-Upper Symmetric Gauss-Seidel (LU-SGS) algorithm was added to a widely used series of 2D/3D Euler/Navier-Stokes solvers and was demonstrated for a particular class of high-speed flows. A limited study was conducted to compare the hybrid LU-SGS for approximate Newton iteration and diagonalized Beam-Warming (DBW) schemes on a work and convergence history basis. The hybrid LU-SGS algorithm is more efficient and easier to implement than the DBW scheme originally present in the code for the cases considered. The code was validated for the hypersonic flow through two mutually perpendicular flat plates and then used to investigate the flow field in and around a simplified scramjet module gap seal configuration. Due to the similarities, the gap seal flow was compared to hypersonic corner flow at the same freestream conditions and Reynolds number.

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.

A multigrid solution method for mixed hybrid finite elements

Energy Technology Data Exchange (ETDEWEB)

Schmid, W. [Universitaet Augsburg (Germany)

1996-12-31

We consider the multigrid solution of linear equations arising within the discretization of elliptic second order boundary value problems of the form by mixed hybrid finite elements. Using the equivalence of mixed hybrid finite elements and non-conforming nodal finite elements, we construct a multigrid scheme for the corresponding non-conforming finite elements, and, by this equivalence, for the mixed hybrid finite elements, following guidelines from Arbogast/Chen. For a rectangular triangulation of the computational domain, this non-conforming schemes are the so-called nodal finite elements. We explicitly construct prolongation and restriction operators for this type of non-conforming finite elements. We discuss the use of plain multigrid and the multilevel-preconditioned cg-method and compare their efficiency in numerical tests.

Deterministic linear-optics quantum computing based on a hybrid approach

International Nuclear Information System (INIS)

Lee, Seung-Woo; Jeong, Hyunseok

2014-01-01

We suggest a scheme for all-optical quantum computation using hybrid qubits. It enables one to efficiently perform universal linear-optical gate operations in a simple and near-deterministic way using hybrid entanglement as off-line resources

Deterministic linear-optics quantum computing based on a hybrid approach

Energy Technology Data Exchange (ETDEWEB)

Lee, Seung-Woo; Jeong, Hyunseok [Center for Macroscopic Quantum Control, Department of Physics and Astronomy, Seoul National University, Seoul, 151-742 (Korea, Republic of)

2014-12-04

We suggest a scheme for all-optical quantum computation using hybrid qubits. It enables one to efficiently perform universal linear-optical gate operations in a simple and near-deterministic way using hybrid entanglement as off-line resources.

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....

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

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.

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.

MR/PET quantification tools: Registration, segmentation, classification, and MR-based attenuation correction

Science.gov (United States)

Fei, Baowei; Yang, Xiaofeng; Nye, Jonathon A.; Aarsvold, John N.; Raghunath, Nivedita; Cervo, Morgan; Stark, Rebecca; Meltzer, Carolyn C.; Votaw, John R.

2012-01-01

Purpose: Combined MR/PET is a relatively new, hybrid imaging modality. A human MR/PET prototype system consisting of a Siemens 3T Trio MR and brain PET insert was installed and tested at our institution. Its present design does not offer measured attenuation correction (AC) using traditional transmission imaging. This study is the development of quantification tools including MR-based AC for quantification in combined MR/PET for brain imaging. Methods: The developed quantification tools include image registration, segmentation, classification, and MR-based AC. These components were integrated into a single scheme for processing MR/PET data. The segmentation method is multiscale and based on the Radon transform of brain MR images. It was developed to segment the skull on T1-weighted MR images. A modified fuzzy C-means classification scheme was developed to classify brain tissue into gray matter, white matter, and cerebrospinal fluid. Classified tissue is assigned an attenuation coefficient so that AC factors can be generated. PET emission data are then reconstructed using a three-dimensional ordered sets expectation maximization method with the MR-based AC map. Ten subjects had separate MR and PET scans. The PET with [11C]PIB was acquired using a high-resolution research tomography (HRRT) PET. MR-based AC was compared with transmission (TX)-based AC on the HRRT. Seventeen volumes of interest were drawn manually on each subject image to compare the PET activities between the MR-based and TX-based AC methods. Results: For skull segmentation, the overlap ratio between our segmented results and the ground truth is 85.2 ± 2.6%. Attenuation correction results from the ten subjects show that the difference between the MR and TX-based methods was <6.5%. Conclusions: MR-based AC compared favorably with conventional transmission-based AC. Quantitative tools including registration, segmentation, classification, and MR-based AC have been developed for use in combined MR

MR/PET quantification tools: Registration, segmentation, classification, and MR-based attenuation correction

Energy Technology Data Exchange (ETDEWEB)

Fei, Baowei, E-mail: bfei@emory.edu [Department of Radiology and Imaging Sciences, Emory University School of Medicine, 1841 Clifton Road Northeast, Atlanta, Georgia 30329 (United States); Department of Biomedical Engineering, Emory University and Georgia Institute of Technology, Atlanta, Georgia 30322 (United States); Department of Mathematics and Computer Sciences, Emory University, Atlanta, Georgia 30322 (United States); Yang, Xiaofeng; Nye, Jonathon A.; Raghunath, Nivedita; Votaw, John R. [Department of Radiology and Imaging Sciences, Emory University School of Medicine, Atlanta, Georgia 30329 (United States); Aarsvold, John N. [Department of Radiology and Imaging Sciences, Emory University School of Medicine, Atlanta, Georgia 30329 (United States); Nuclear Medicine Service, Atlanta Veterans Affairs Medical Center, Atlanta, Georgia 30033 (United States); Cervo, Morgan; Stark, Rebecca [The Medical Physics Graduate Program in the George W. Woodruff School, Georgia Institute of Technology, Atlanta, Georgia 30332 (United States); Meltzer, Carolyn C. [Department of Radiology and Imaging Sciences, Emory University School of Medicine, Atlanta, Georgia 30329 (United States); Department of Neurology and Department of Psychiatry and Behavior Sciences, Emory University School of Medicine, Atlanta, Georgia 30322 (United States)

2012-10-15

Purpose: Combined MR/PET is a relatively new, hybrid imaging modality. A human MR/PET prototype system consisting of a Siemens 3T Trio MR and brain PET insert was installed and tested at our institution. Its present design does not offer measured attenuation correction (AC) using traditional transmission imaging. This study is the development of quantification tools including MR-based AC for quantification in combined MR/PET for brain imaging. Methods: The developed quantification tools include image registration, segmentation, classification, and MR-based AC. These components were integrated into a single scheme for processing MR/PET data. The segmentation method is multiscale and based on the Radon transform of brain MR images. It was developed to segment the skull on T1-weighted MR images. A modified fuzzy C-means classification scheme was developed to classify brain tissue into gray matter, white matter, and cerebrospinal fluid. Classified tissue is assigned an attenuation coefficient so that AC factors can be generated. PET emission data are then reconstructed using a three-dimensional ordered sets expectation maximization method with the MR-based AC map. Ten subjects had separate MR and PET scans. The PET with [{sup 11}C]PIB was acquired using a high-resolution research tomography (HRRT) PET. MR-based AC was compared with transmission (TX)-based AC on the HRRT. Seventeen volumes of interest were drawn manually on each subject image to compare the PET activities between the MR-based and TX-based AC methods. Results: For skull segmentation, the overlap ratio between our segmented results and the ground truth is 85.2 ± 2.6%. Attenuation correction results from the ten subjects show that the difference between the MR and TX-based methods was <6.5%. Conclusions: MR-based AC compared favorably with conventional transmission-based AC. Quantitative tools including registration, segmentation, classification, and MR-based AC have been developed for use in combined MR/PET.

MR/PET quantification tools: Registration, segmentation, classification, and MR-based attenuation correction

International Nuclear Information System (INIS)

Fei, Baowei; Yang, Xiaofeng; Nye, Jonathon A.; Raghunath, Nivedita; Votaw, John R.; Aarsvold, John N.; Cervo, Morgan; Stark, Rebecca; Meltzer, Carolyn C.

2012-01-01

Purpose: Combined MR/PET is a relatively new, hybrid imaging modality. A human MR/PET prototype system consisting of a Siemens 3T Trio MR and brain PET insert was installed and tested at our institution. Its present design does not offer measured attenuation correction (AC) using traditional transmission imaging. This study is the development of quantification tools including MR-based AC for quantification in combined MR/PET for brain imaging. Methods: The developed quantification tools include image registration, segmentation, classification, and MR-based AC. These components were integrated into a single scheme for processing MR/PET data. The segmentation method is multiscale and based on the Radon transform of brain MR images. It was developed to segment the skull on T1-weighted MR images. A modified fuzzy C-means classification scheme was developed to classify brain tissue into gray matter, white matter, and cerebrospinal fluid. Classified tissue is assigned an attenuation coefficient so that AC factors can be generated. PET emission data are then reconstructed using a three-dimensional ordered sets expectation maximization method with the MR-based AC map. Ten subjects had separate MR and PET scans. The PET with ["1"1C]PIB was acquired using a high-resolution research tomography (HRRT) PET. MR-based AC was compared with transmission (TX)-based AC on the HRRT. Seventeen volumes of interest were drawn manually on each subject image to compare the PET activities between the MR-based and TX-based AC methods. Results: For skull segmentation, the overlap ratio between our segmented results and the ground truth is 85.2 ± 2.6%. Attenuation correction results from the ten subjects show that the difference between the MR and TX-based methods was <6.5%. Conclusions: MR-based AC compared favorably with conventional transmission-based AC. Quantitative tools including registration, segmentation, classification, and MR-based AC have been developed for use in combined MR/PET.

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

Computerized classification of mass lesions in digital mammograms

International Nuclear Information System (INIS)

Giger, M.L.; Doi, K.; Yin, F.F.; Schmidt, R.A.; Vyborny, C.J.

1989-01-01

Subjective classification of masses on mammograms is a difficult task. On average, about 25% of masses referred for surgical biopsy are actually malignant. The authors are developing, as an aid to radiologists, a computerized scheme for the classification of lesions in mammograms to reduce the false-negative and false-positive diagnoses of malignancies. The classification scheme involves the extraction of border information from the mammographic lesion in order to quantify the degree of spiculation, which is related to the possibility of malignancy. Clinical film mammograms are digitized with an optical drum scanner (0.1-mm pixel size) for analysis on a Micro VAX 3500 computer. Border information (fluctuations) is obtained from the difference between the lesion border and its smoothed border. Using the rms variation of the frequency content of these fluctuations, approximately 85% of the cancerous lesions were correctly classified as malignant, while 15% of benign lesions were misclassified, in a preliminary study

[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.

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.

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…

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...

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.

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.

Hybrid Message-Embedded Cipher Using Logistic Map

OpenAIRE

Mishra, Mina; Mankar, V. H.

2012-01-01

The proposed hybrid message embedded scheme consists of hill cipher combined with message embedded chaotic scheme. Message-embedded scheme using non-linear feedback shift register as non-linear function and 1-D logistic map as chaotic map is modified, analyzed and tested for avalanche property and strength against known plaintext attack and brute-force attack. Parameter of logistic map acts as a secret key. As we know that the minimum key space to resist brute-force attack is 2100, and it is ...

System-wide hybrid MPC-PID control of a continuous pharmaceutical tablet manufacturing process via direct compaction.

Science.gov (United States)

Singh, Ravendra; Ierapetritou, Marianthi; Ramachandran, Rohit

2013-11-01

The next generation of QbD based pharmaceutical products will be manufactured through continuous processing. This will allow the integration of online/inline monitoring tools, coupled with an efficient advanced model-based feedback control systems, to achieve precise control of process variables, so that the predefined product quality can be achieved consistently. The direct compaction process considered in this study is highly interactive and involves time delays for a number of process variables due to sensor placements, process equipment dimensions, and the flow characteristics of the solid material. A simple feedback regulatory control system (e.g., PI(D)) by itself may not be sufficient to achieve the tight process control that is mandated by regulatory authorities. The process presented herein comprises of coupled dynamics involving slow and fast responses, indicating the requirement of a hybrid control scheme such as a combined MPC-PID control scheme. In this manuscript, an efficient system-wide hybrid control strategy for an integrated continuous pharmaceutical tablet manufacturing process via direct compaction has been designed. The designed control system is a hybrid scheme of MPC-PID control. An effective controller parameter tuning strategy involving an ITAE method coupled with an optimization strategy has been used for tuning of both MPC and PID parameters. The designed hybrid control system has been implemented in a first-principles model-based flowsheet that was simulated in gPROMS (Process System Enterprise). Results demonstrate enhanced performance of critical quality attributes (CQAs) under the hybrid control scheme compared to only PID or MPC control schemes, illustrating the potential of a hybrid control scheme in improving pharmaceutical manufacturing operations. Copyright © 2013 Elsevier B.V. All rights reserved.

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...

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

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

Classification of Metal-Deficient Dwarfs in the Vilnius Photometric System

Directory of Open Access Journals (Sweden)

Lazauskaitė R.

2003-12-01

Full Text Available Methods used for the quantitative classification of metal-deficient stars in the Vilnius photometric system are reviewed. We present a new calibration of absolute magnitudes for dwarfs and subdwarfs, based on Hipparcos parallaxes. The new classification scheme is applied to a sample of Population II visual binaries.

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.

Waste-acceptance criteria and risk-based thinking for radioactive-waste classification

International Nuclear Information System (INIS)

Lowenthal, M.D.

1998-01-01

The US system of radioactive-waste classification and its development provide a reference point for the discussion of risk-based thinking in waste classification. The official US system is described and waste-acceptance criteria for disposal sites are introduced because they constitute a form of de facto waste classification. Risk-based classification is explored and it is found that a truly risk-based system is context-dependent: risk depends not only on the waste-management activity but, for some activities such as disposal, it depends on the specific physical context. Some of the elements of the official US system incorporate risk-based thinking, but like many proposed alternative schemes, the physical context of disposal is ignored. The waste-acceptance criteria for disposal sites do account for this context dependence and could be used as a risk-based classification scheme for disposal. While different classes would be necessary for different management activities, the waste-acceptance criteria would obviate the need for the current system and could better match wastes to disposal environments saving money or improving safety or both

A Soft Intelligent Risk Evaluation Model for Credit Scoring Classification

Directory of Open Access Journals (Sweden)

Mehdi Khashei

2015-09-01

Full Text Available Risk management is one of the most important branches of business and finance. Classification models are the most popular and widely used analytical group of data mining approaches that can greatly help financial decision makers and managers to tackle credit risk problems. However, the literature clearly indicates that, despite proposing numerous classification models, credit scoring is often a difficult task. On the other hand, there is no universal credit-scoring model in the literature that can be accurately and explanatorily used in all circumstances. Therefore, the research for improving the efficiency of credit-scoring models has never stopped. In this paper, a hybrid soft intelligent classification model is proposed for credit-scoring problems. In the proposed model, the unique advantages of the soft computing techniques are used in order to modify the performance of the traditional artificial neural networks in credit scoring. Empirical results of Australian credit card data classifications indicate that the proposed hybrid model outperforms its components, and also other classification models presented for credit scoring. Therefore, the proposed model can be considered as an appropriate alternative tool for binary decision making in business and finance, especially in high uncertainty conditions.

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.

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...

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.

Practical Switching-Based Hybrid FSO/RF Transmission and Its Performance Analysis

KAUST Repository

Usman, Muneer

2014-10-01

Hybrid free-space optical (FSO)/radio-frequency (RF) systems have emerged as a promising solution for high-data-rate wireless backhaul. We present and analyze a switching-based transmission scheme for the hybrid FSO/RF system. Specifically, either the FSO or RF link will be active at a certain time instance, with the FSO link enjoying a higher priority. We considered both a single-threshold case and a dual-threshold case for FSO link operation. 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 the FSO-only scenario.

Practical Switching-Based Hybrid FSO/RF Transmission and Its Performance Analysis

KAUST Repository

Usman, Muneer; Hong-Chuan Yang; 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 backhaul. We present and analyze a switching-based transmission scheme for the hybrid FSO/RF system. Specifically, either the FSO or RF link will be active at a certain time instance, with the FSO link enjoying a higher priority. We considered both a single-threshold case and a dual-threshold case for FSO link operation. 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 the FSO-only scenario.

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...

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 ...

Positivity-preserving space-time CE/SE scheme for high speed flows

KAUST Repository

Shen, Hua

2017-03-02

We develop a space-time conservation element and solution element (CE/SE) scheme using a simple slope limiter to preserve the positivity of the density and pressure in computations of inviscid and viscous high-speed flows. In general, the limiter works with all existing CE/SE schemes. Here, we test the limiter on a central Courant number insensitive (CNI) CE/SE scheme implemented on hybrid unstructured meshes. Numerical examples show that the proposed limiter preserves the positivity of the density and pressure without disrupting the conservation law; it also improves robustness without losing accuracy in solving high-speed flows.

Positivity-preserving space-time CE/SE scheme for high speed flows

KAUST Repository

Shen, Hua; Parsani, Matteo

2017-01-01

We develop a space-time conservation element and solution element (CE/SE) scheme using a simple slope limiter to preserve the positivity of the density and pressure in computations of inviscid and viscous high-speed flows. In general, the limiter works with all existing CE/SE schemes. Here, we test the limiter on a central Courant number insensitive (CNI) CE/SE scheme implemented on hybrid unstructured meshes. Numerical examples show that the proposed limiter preserves the positivity of the density and pressure without disrupting the conservation law; it also improves robustness without losing accuracy in solving high-speed flows.

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...

Classification Formula and Generation Algorithm of Cycle Decomposition Expression for Dihedral Groups

Directory of Open Access Journals (Sweden)

Dakun Zhang

2013-01-01

Full Text Available The necessary of classification research on common formula of group (dihedral group cycle decomposition expression is illustrated. It includes the reflection and rotation conversion, which derived six common formulae on cycle decomposition expressions of group; it designed the generation algorithm on the cycle decomposition expressions of group, which is based on the method of replacement conversion and the classification formula; algorithm analysis and the results of the process show that the generation algorithm which is based on the classification formula is outperformed by the general algorithm which is based on replacement conversion; it has great significance to solve the enumeration of the necklace combinational scheme, especially the structural problems of combinational scheme, by using group theory and computer.

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.)

A combined reconstruction-classification method for diffuse optical tomography

Energy Technology Data Exchange (ETDEWEB)

Hiltunen, P [Department of Biomedical Engineering and Computational Science, Helsinki University of Technology, PO Box 3310, FI-02015 TKK (Finland); Prince, S J D; Arridge, S [Department of Computer Science, University College London, Gower Street London, WC1E 6B (United Kingdom)], E-mail: petri.hiltunen@tkk.fi, E-mail: s.prince@cs.ucl.ac.uk, E-mail: s.arridge@cs.ucl.ac.uk

2009-11-07

We present a combined classification and reconstruction algorithm for diffuse optical tomography (DOT). DOT is a nonlinear ill-posed inverse problem. Therefore, some regularization is needed. We present a mixture of Gaussians prior, which regularizes the DOT reconstruction step. During each iteration, the parameters of a mixture model are estimated. These associate each reconstructed pixel with one of several classes based on the current estimate of the optical parameters. This classification is exploited to form a new prior distribution to regularize the reconstruction step and update the optical parameters. The algorithm can be described as an iteration between an optimization scheme with zeroth-order variable mean and variance Tikhonov regularization and an expectation-maximization scheme for estimation of the model parameters. We describe the algorithm in a general Bayesian framework. Results from simulated test cases and phantom measurements show that the algorithm enhances the contrast of the reconstructed images with good spatial accuracy. The probabilistic classifications of each image contain only a few misclassified pixels.

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

Science.gov (United States)

Chen, Shizhi; Yang, Xiaodong; Tian, Yingli

2015-09-01

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

Comparing the performance of flat and hierarchical Habitat/Land-Cover classification models in a NATURA 2000 site

Science.gov (United States)

Gavish, Yoni; O'Connell, Jerome; Marsh, Charles J.; Tarantino, Cristina; Blonda, Palma; Tomaselli, Valeria; Kunin, William E.

2018-02-01

The increasing need for high quality Habitat/Land-Cover (H/LC) maps has triggered considerable research into novel machine-learning based classification models. In many cases, H/LC classes follow pre-defined hierarchical classification schemes (e.g., CORINE), in which fine H/LC categories are thematically nested within more general categories. However, none of the existing machine-learning algorithms account for this pre-defined hierarchical structure. Here we introduce a novel Random Forest (RF) based application of hierarchical classification, which fits a separate local classification model in every branching point of the thematic tree, and then integrates all the different local models to a single global prediction. We applied the hierarchal RF approach in a NATURA 2000 site in Italy, using two land-cover (CORINE, FAO-LCCS) and one habitat classification scheme (EUNIS) that differ from one another in the shape of the class hierarchy. For all 3 classification schemes, both the hierarchical model and a flat model alternative provided accurate predictions, with kappa values mostly above 0.9 (despite using only 2.2-3.2% of the study area as training cells). The flat approach slightly outperformed the hierarchical models when the hierarchy was relatively simple, while the hierarchical model worked better under more complex thematic hierarchies. Most misclassifications came from habitat pairs that are thematically distant yet spectrally similar. In 2 out of 3 classification schemes, the additional constraints of the hierarchical model resulted with fewer such serious misclassifications relative to the flat model. The hierarchical model also provided valuable information on variable importance which can shed light into "black-box" based machine learning algorithms like RF. We suggest various ways by which hierarchical classification models can increase the accuracy and interpretability of H/LC classification maps.

Hybrid B-Spline Collocation Method for Solving the Generalized Burgers-Fisher and Burgers-Huxley Equations

Directory of Open Access Journals (Sweden)

Imtiaz Wasim

2018-01-01

Full Text Available In this study, we introduce a new numerical technique for solving nonlinear generalized Burgers-Fisher and Burgers-Huxley equations using hybrid B-spline collocation method. This technique is based on usual finite difference scheme and Crank-Nicolson method which are used to discretize the time derivative and spatial derivatives, respectively. Furthermore, hybrid B-spline function is utilized as interpolating functions in spatial dimension. The scheme is verified unconditionally stable using the Von Neumann (Fourier method. Several test problems are considered to check the accuracy of the proposed scheme. The numerical results are in good agreement with known exact solutions and the existing schemes in literature.

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...

Centrifuge: rapid and sensitive classification of metagenomic sequences.

Science.gov (United States)

Kim, Daehwan; Song, Li; Breitwieser, Florian P; Salzberg, Steven L

2016-12-01

Centrifuge is a novel microbial classification engine that enables rapid, accurate, and sensitive labeling of reads and quantification of species on desktop computers. The system uses an indexing scheme based on the Burrows-Wheeler transform (BWT) and the Ferragina-Manzini (FM) index, optimized specifically for the metagenomic classification problem. Centrifuge requires a relatively small index (4.2 GB for 4078 bacterial and 200 archaeal genomes) and classifies sequences at very high speed, allowing it to process the millions of reads from a typical high-throughput DNA sequencing run within a few minutes. Together, these advances enable timely and accurate analysis of large metagenomics data sets on conventional desktop computers. Because of its space-optimized indexing schemes, Centrifuge also makes it possible to index the entire NCBI nonredundant nucleotide sequence database (a total of 109 billion bases) with an index size of 69 GB, in contrast to k-mer-based indexing schemes, which require far more extensive space. © 2016 Kim et al.; Published by Cold Spring Harbor Laboratory Press.

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.

Solar wind classification from a machine learning perspective

Science.gov (United States)

Heidrich-Meisner, V.; Wimmer-Schweingruber, R. F.

2017-12-01

It is a very well known fact that the ubiquitous solar wind comes in at least two varieties, the slow solar wind and the coronal hole wind. The simplified view of two solar wind types has been frequently challenged. Existing solar wind categorization schemes rely mainly on different combinations of the solar wind proton speed, the O and C charge state ratios, the Alfvén speed, the expected proton temperature and the specific proton entropy. In available solar wind classification schemes, solar wind from stream interaction regimes is often considered either as coronal hole wind or slow solar wind, although their plasma properties are different compared to "pure" coronal hole or slow solar wind. As shown in Neugebauer et al. (2016), even if only two solar wind types are assumed, available solar wind categorization schemes differ considerably for intermediate solar wind speeds. Thus, the decision boundary between the coronal hole and the slow solar wind is so far not well defined.In this situation, a machine learning approach to solar wind classification can provide an additional perspective.We apply a well-known machine learning method, k-means, to the task of solar wind classification in order to answer the following questions: (1) How many solar wind types can reliably be identified in our data set comprised of ten years of solar wind observations from the Advanced Composition Explorer (ACE)? (2) Which combinations of solar wind parameters are particularly useful for solar wind classification?Potential subtypes of slow solar wind are of particular interest because they can provide hints of respective different source regions or release mechanisms of slow solar wind.

A NEW CLASSIFICATION METHOD FOR GAMMA-RAY BURSTS

International Nuclear Information System (INIS)

Lue Houjun; Liang Enwei; Zhang Binbin; Zhang Bing

2010-01-01

Recent Swift observations suggest that the traditional long versus short gamma-ray burst (GRB) classification scheme does not always associate GRBs to the two physically motivated model types, i.e., Type II (massive star origin) versus Type I (compact star origin). We propose a new phenomenological classification method of GRBs by introducing a new parameter ε = E γ,iso,52 /E 5/3 p,z,2 , where E γ,iso is the isotropic gamma-ray energy (in units of 10 52 erg) and E p,z is the cosmic rest-frame spectral peak energy (in units of 100 keV). For those short GRBs with 'extended emission', both quantities are defined for the short/hard spike only. With the current complete sample of GRBs with redshift and E p measurements, the ε parameter shows a clear bimodal distribution with a separation at ε ∼ 0.03. The high-ε region encloses the typical long GRBs with high luminosity, some high-z 'rest-frame-short' GRBs (such as GRB 090423 and GRB 080913), as well as some high-z short GRBs (such as GRB 090426). All these GRBs have been claimed to be of Type II origin based on other observational properties in the literature. All the GRBs that are argued to be of Type I origin are found to be clustered in the low-ε region. They can be separated from some nearby low-luminosity long GRBs (in 3σ) by an additional T 90 criterion, i.e., T 90,z ∼< 5 s in the Swift/BAT band. We suggest that this new classification scheme can better match the physically motivated Type II/I classification scheme.

Direct switching control of DC-DC power electronic converters using hybrid system theory

Energy Technology Data Exchange (ETDEWEB)

Zhao, J.; Lin, F. [Wayne State Univ., Detroit, MI (United States). Dept. of Electrical and Computer Engineering; Wang, C. [Wayne State Univ., Detroit, MI (United States). Dept. of Electrical and Computer Engineering; Wayne State Univ., Detroit, MI (United States). Div. of Engineering Technology

2010-07-01

A direct switching control (DSC) scheme for power electronics converters was described. The system was designed for use in both traditional and renewable energy applications as well as in electric drive vehicles. The proposed control scheme was based on a detailed hybrid system converter model that used model predictive control (MPC), piecewise affine (PWA) approximations and constrained optimal control methods. A DC-DC converter was modelled as a hybrid machine. Switching among different modes of the DC-DC converter were modelled as discrete events controlled by the hybrid controller. The modelling scheme was applied to a Buck converter. The DSC was used to control the switch of the power converter based on a hybrid machine model. Results of the study showed that the method can be used to regulate output voltage and inductor currents. The method also provides fast transient responses and effectively regulates both currents and voltage. The controller can be used to provide immediate responses to dynamic disturbances and output voltage fluctuations. 23 refs., 7 figs.

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

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.

Wavelet Based Protection Scheme for Multi Terminal Transmission System with PV and Wind Generation

Science.gov (United States)

Manju Sree, Y.; Goli, Ravi kumar; Ramaiah, V.

2017-08-01

A hybrid generation is a part of large power system in which number of sources usually attached to a power electronic converter and loads are clustered can operate independent of the main power system. The protection scheme is crucial against faults based on traditional over current protection since there are adequate problems due to fault currents in the mode of operation. This paper adopts a new approach for detection, discrimination of the faults for multi terminal transmission line protection in presence of hybrid generation. Transient current based protection scheme is developed with discrete wavelet transform. Fault indices of all phase currents at all terminals are obtained by analyzing the detail coefficients of current signals using bior 1.5 mother wavelet. This scheme is tested for different types of faults and is found effective for detection and discrimination of fault with various fault inception angle and fault impedance.

Improving Rydberg Excitations within Time-Dependent Density Functional Theory with Generalized Gradient Approximations: The Exchange-Enhancement-for-Large-Gradient Scheme.

Science.gov (United States)

Li, Shaohong L; Truhlar, Donald G

2015-07-14

Time-dependent density functional theory (TDDFT) with conventional local and hybrid functionals such as the local and hybrid generalized gradient approximations (GGA) seriously underestimates the excitation energies of Rydberg states, which limits its usefulness for applications such as spectroscopy and photochemistry. We present here a scheme that modifies the exchange-enhancement factor to improve GGA functionals for Rydberg excitations within the TDDFT framework while retaining their accuracy for valence excitations and for the thermochemical energetics calculated by ground-state density functional theory. The scheme is applied to a popular hybrid GGA functional and tested on data sets of valence and Rydberg excitations and atomization energies, and the results are encouraging. The scheme is simple and flexible. It can be used to correct existing functionals, and it can also be used as a strategy for the development of new functionals.

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)

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

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)

Risk classification and cream skimming on the deregulated German insurance market

OpenAIRE

Beschorner, Patrick F. E.

2003-01-01

In a two-stage model insurance companies first decide upon risk classification and then compete in prices. I show that the observed heterogeneous behavior of similar firms is compatible with rational behavior. On the deregulated German insurance market individual application of classification schemes induces welfare losses due to cream skimming. Classification costs and pricing above marginal cost can be prevented by common industry-wide loss statistics which already exist to a rudimentary ex...

De Facto Exchange Rate Regime Classifications Are Better Than You Think

OpenAIRE

Michael Bleaney; Mo Tian; Lin Yin

2015-01-01

Several de facto exchange rate regime classifications have been widely used in empirical research, but they are known to disagree with one another to a disturbing extent. We dissect the algorithms employed and argue that they can be significantly improved. We implement the improvements, and show that there is a far higher agreement rate between the modified classifications. We conclude that the current pessimism about de facto exchange rate regime classification schemes is unwarranted.

Bayesian inference for hybrid discrete-continuous stochastic kinetic models

International Nuclear Information System (INIS)

Sherlock, Chris; Golightly, Andrew; Gillespie, Colin S

2014-01-01

We consider the problem of efficiently performing simulation and inference for stochastic kinetic models. Whilst it is possible to work directly with the resulting Markov jump process (MJP), computational cost can be prohibitive for networks of realistic size and complexity. In this paper, we consider an inference scheme based on a novel hybrid simulator that classifies reactions as either ‘fast’ or ‘slow’ with fast reactions evolving as a continuous Markov process whilst the remaining slow reaction occurrences are modelled through a MJP with time-dependent hazards. A linear noise approximation (LNA) of fast reaction dynamics is employed and slow reaction events are captured by exploiting the ability to solve the stochastic differential equation driving the LNA. This simulation procedure is used as a proposal mechanism inside a particle MCMC scheme, thus allowing Bayesian inference for the model parameters. We apply the scheme to a simple application and compare the output with an existing hybrid approach and also a scheme for performing inference for the underlying discrete stochastic model. (paper)

Segmentation of Clinical Endoscopic Images Based on the Classification of Topological Vector Features

Directory of Open Access Journals (Sweden)

O. A. Dunaeva

2013-01-01

Full Text Available In this work, we describe a prototype of an automatic segmentation system and annotation of endoscopy images. The used algorithm is based on the classification of vectors of the topological features of the original image. We use the image processing scheme which includes image preprocessing, calculation of vector descriptors defined for every point of the source image and the subsequent classification of descriptors. Image preprocessing includes finding and selecting artifacts and equalizating the image brightness. In this work, we give the detailed algorithm of the construction of topological descriptors and the classifier creating procedure based on mutual sharing the AdaBoost scheme and a naive Bayes classifier. In the final section, we show the results of the classification of real endoscopic images.

Autonomous Control of Interlinking Converter With Energy Storage in Hybrid AC–DC Microgrid

DEFF Research Database (Denmark)

Loh, Poh Chiang; Li, Ding; Chai, Yi Kang

2013-01-01

, simplicity, and industry relevance of the converter. The desired operating features of the hybrid microgrid can then be added through this interlinking converter. To demonstrate, an appropriate control scheme is now developed for controlling the interlinking converter. The objective is to keep the hybrid......The coexistence of ac and dc subgrids in a hybrid microgrid is likely given that modern distributed sources can either be ac or dc. Linking these subgrids is a power converter, whose topology should preferably be not too unconventional. This is to avoid unnecessary compromises to reliability...... microgrid in autonomous operation with active power proportionally shared among its distributed sources. Power sharing here should depend only on the source ratings and not their placements within the hybrid microgrid. The proposed scheme can also be extended to include energy storage within...

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].

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.

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.

GPGPU Accelerated Deep Object Classification on a Heterogeneous Mobile Platform

Directory of Open Access Journals (Sweden)

Syed Tahir Hussain Rizvi

2016-12-01

Full Text Available Deep convolutional neural networks achieve state-of-the-art performance in image classification. The computational and memory requirements of such networks are however huge, and that is an issue on embedded devices due to their constraints. Most of this complexity derives from the convolutional layers and in particular from the matrix multiplications they entail. This paper proposes a complete approach to image classification providing common layers used in neural networks. Namely, the proposed approach relies on a heterogeneous CPU-GPU scheme for performing convolutions in the transform domain. The Compute Unified Device Architecture(CUDA-based implementation of the proposed approach is evaluated over three different image classification networks on a Tegra K1 CPU-GPU mobile processor. Experiments show that the presented heterogeneous scheme boasts a 50× speedup over the CPU-only reference and outperforms a GPU-based reference by 2×, while slashing the power consumption by nearly 30%.

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.

Knowledge-based sea ice classification by polarimetric SAR

DEFF Research Database (Denmark)

Skriver, Henning; Dierking, Wolfgang

2004-01-01

Polarimetric SAR images acquired at C- and L-band over sea ice in the Greenland Sea, Baltic Sea, and Beaufort Sea have been analysed with respect to their potential for ice type classification. The polarimetric data were gathered by the Danish EMISAR and the US AIRSAR which both are airborne...... systems. A hierarchical classification scheme was chosen for sea ice because our knowledge about magnitudes, variations, and dependences of sea ice signatures can be directly considered. The optimal sequence of classification rules and the rules themselves depend on the ice conditions/regimes. The use...... of the polarimetric phase information improves the classification only in the case of thin ice types but is not necessary for thicker ice (above about 30 cm thickness)...

An HARQ scheme with antenna switching for V-BLAST system

Directory of Open Access Journals (Sweden)

Bonghoe Kim

2004-12-01

Full Text Available Bell-labs layered space-time (BLAST achieves high spectral efficiency in rich scattering environments by transmitting independent data streams via each transmit antenna. However, this high spectral efficiency is significantly reduced if the signals ate the receiver go through correlated channels. In this paper, we propose a hybrid automatic request (HARQ scheme to alleviate the adverse effect of the channel correlation by simply switching the transmission in retransmission. With the proposed scheme, we can achieve significant improvement over the correlated channels with negligible complexity increase.

Event-triggered hybrid control based on multi-Agent systems for Microgrids

DEFF Research Database (Denmark)

Dou, Chun-xia; Liu, Bin; Guerrero, Josep M.

2014-01-01

This paper is focused on a multi-agent system based event-triggered hybrid control for intelligently restructuring the operating mode of an microgrid (MG) to ensure the energy supply with high security, stability and cost effectiveness. Due to the microgrid is composed of different types...... of distributed energy resources, thus it is typical hybrid dynamic network. Considering the complex hybrid behaviors, a hierarchical decentralized coordinated control scheme is firstly constructed based on multi-agent sys-tem, then, the hybrid model of the microgrid is built by using differential hybrid Petri...

Scaling theory and the classification of phase transitions

International Nuclear Information System (INIS)

Hilfer, R.

1992-01-01

In this paper, the recent classification theory for phase transitions and its relation with the foundations of statistical physics is reviewed. First it is outlined how Ehrenfests classification scheme can be generalized into a general thermodynamic classification theory for phase transitions. The classification theory implies scaling and multiscaling thereby eliminating the need to postulate the scaling hypothesis as a fourth law of thermodynamics. The new classification has also led to the discovery and distinction of nonequilibrium transitions within equilibrium statistical physics. Nonequilibrium phase transitions are distinguished from equilibrium transitions by orders less than unity and by the fact the equilibrium thermodynamics and statistical mechanics become inapplicable at the critical point. The latter fact requires a change in the Gibbs assumption underlying the canonical and grandcanonical ensembles in order to recover the thermodynamic description in the critical limit

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

Macro-level integrated renewable energy production schemes for sustainable development

International Nuclear Information System (INIS)

Subhadra, Bobban G.

2011-01-01

The production of renewable clean energy is a prime necessity for the sustainable future existence of our planet. However, because of the resource-intensive nature, and other challenges associated with these new generation renewable energy sources, novel industrial frameworks need to be co-developed. Integrated renewable energy production schemes with foundations on resource sharing, carbon neutrality, energy-efficient design, source reduction, green processing plan, anthropogenic use of waste resources for the production green energy along with the production of raw material for allied food and chemical industries is imperative for the sustainable development of this sector especially in an emission-constrained future industrial scenario. To attain these objectives, the scope of hybrid renewable production systems and integrated renewable energy industrial ecology is briefly described. Further, the principles of Integrated Renewable Energy Park (IREP) approach, an example for macro-level energy production, and its benefits and global applications are also explored. - Research highlights: → Discusses the need for macro-level renewable energy production schemes. → Scope of hybrid and integrated industrial ecology for renewable energy production. → Integrated Renewable Energy Parks (IREPs): A macro-level energy production scheme. → Discusses the principle foundations and global applications of IREPs. → Describes the significance of IREPs in the carbon-neutral future business arena.

An Unscented Kalman-Particle Hybrid Filter for Space Object Tracking

Science.gov (United States)

Raihan A. V, Dilshad; Chakravorty, Suman

2018-03-01

Optimal and consistent estimation of the state of space objects is pivotal to surveillance and tracking applications. However, probabilistic estimation of space objects is made difficult by the non-Gaussianity and nonlinearity associated with orbital mechanics. In this paper, we present an unscented Kalman-particle hybrid filtering framework for recursive Bayesian estimation of space objects. The hybrid filtering scheme is designed to provide accurate and consistent estimates when measurements are sparse without incurring a large computational cost. It employs an unscented Kalman filter (UKF) for estimation when measurements are available. When the target is outside the field of view (FOV) of the sensor, it updates the state probability density function (PDF) via a sequential Monte Carlo method. The hybrid filter addresses the problem of particle depletion through a suitably designed filter transition scheme. To assess the performance of the hybrid filtering approach, we consider two test cases of space objects that are assumed to undergo full three dimensional orbital motion under the effects of J 2 and atmospheric drag perturbations. It is demonstrated that the hybrid filters can furnish fast, accurate and consistent estimates outperforming standard UKF and particle filter (PF) implementations.

Classification of Recommender Expertise in the Wikipedia Recommender System

DEFF Research Database (Denmark)

Jensen, Christian D.; Pilkauskas, Povilas; Lefévre, Thomas

2011-01-01

to the quality of articles. The Wikipedia Recommender System (WRS) was developed to help users determine the credibility of articles based on feedback from other Wikipedia users. The WRS implements a collaborative filtering system with trust metrics, i.e., it provides a rating of articles which emphasizes...... an evaluation of four existing knowledge classification schemes with respect to these requirements. This evaluation helped us identify a classification scheme, which we have implemented in the current version of the Wikipedia Recommender System....... feedback from recommenders that the user has agreed with in the past. This exposes the problem that most recommenders are not equally competent in all subject areas. The first WRS prototype did not include an evaluation of the areas of expertise of recommenders, so the trust metric used in the article...

Classification of Recommender Expertise in the Wikipedia Recommender System

DEFF Research Database (Denmark)

Jensen, Christian D.; Pilkauskas, Povilas; Lefevre, Thomas

2011-01-01

to the quality of articles. The Wikipedia Recommender System (WRS) was developed to help users determine the credibility of articles based on feedback from other Wikipedia users. The WRS implements a collaborative filtering system with trust metrics, i.e., it provides a rating of articles "which emphasizes...... an evaluation of four existing knowledge classification schemes with respect to these requirements. This evaluation helped us identify a classification scheme, which we have implemented in the current version of the Wikipedia Recommender System....... feedback from recommenders that the user has agreed with in the past. This exposes the problem that most recommenders are not equally competent in all subject areas. The first WRS prototype did not include an evaluation of the areas of expertise of recommenders, so the trust metric used in the article...

Chaos-based partial image encryption scheme based on linear fractional and lifting wavelet transforms

Science.gov (United States)

Belazi, Akram; Abd El-Latif, Ahmed A.; Diaconu, Adrian-Viorel; Rhouma, Rhouma; Belghith, Safya

2017-01-01

In this paper, a new chaos-based partial image encryption scheme based on Substitution-boxes (S-box) constructed by chaotic system and Linear Fractional Transform (LFT) is proposed. It encrypts only the requisite parts of the sensitive information in Lifting-Wavelet Transform (LWT) frequency domain based on hybrid of chaotic maps and a new S-box. In the proposed encryption scheme, the characteristics of confusion and diffusion are accomplished in three phases: block permutation, substitution, and diffusion. Then, we used dynamic keys instead of fixed keys used in other approaches, to control the encryption process and make any attack impossible. The new S-box was constructed by mixing of chaotic map and LFT to insure the high confidentiality in the inner encryption of the proposed approach. In addition, the hybrid compound of S-box and chaotic systems strengthened the whole encryption performance and enlarged the key space required to resist the brute force attacks. Extensive experiments were conducted to evaluate the security and efficiency of the proposed approach. In comparison with previous schemes, the proposed cryptosystem scheme showed high performances and great potential for prominent prevalence in cryptographic applications.

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

Grid-connected Photovoltaic Micro-inverter with New Hybrid Control LLC Resonant Converter

DEFF Research Database (Denmark)

Xingkui, Mao; Qisheng, Huang; Qingbo, Ke

2016-01-01

A high-efficiency photovoltaic (PV) micro-inverter consisting of two power stages i.e. a LLC resonant converter with a new hybrid control scheme and a dc-ac inverter is proposed, studied and designed in this paper. In the first power stage, the new hybrid control combining pulse-frequency modulat......A high-efficiency photovoltaic (PV) micro-inverter consisting of two power stages i.e. a LLC resonant converter with a new hybrid control scheme and a dc-ac inverter is proposed, studied and designed in this paper. In the first power stage, the new hybrid control combining pulse......-frequency modulation (PFM) and phase-shift pulse-width modulation (PS-PWM) is employed on a full-bridge LLC dc-dc converter, in order to achieve high efficiency when PV output voltage varies in a wide range. Moreover, a maximum power point tracking (MPPT) method based on power perturbation is implemented in the dc...

Etiologic classification of TIA and minor stroke by A-S-C-O and causative classification system as compared to TOAST reduces the proportion of patients categorized as cause undetermined.

Science.gov (United States)

Desai, Jamsheed A; Abuzinadah, Ahmad R; Imoukhuede, Oje; Bernbaum, Manya L; Modi, Jayesh; Demchuk, Andrew M; Coutts, Shelagh B

2014-01-01

The assortment of patients based on the underlying pathophysiology is central to preventing recurrent stroke after a transient ischemic attack and minor stroke (TIA-MS). The causative classification of stroke (CCS) and the A-S-C-O (A for atherosclerosis, S for small vessel disease, C for Cardiac source, O for other cause) classification schemes have recently been developed. These systems have not been specifically applied to the TIA-MS population. We hypothesized that both CCS and A-S-C-O would increase the proportion of patients with a definitive etiologic mechanism for TIA-MS as compared with TOAST. Patients were analyzed from the CATCH study. A single-stroke physician assigned all patients to an etiologic subtype using published algorithms for TOAST, CCS and ASCO. We compared the proportions in the various categories for each classification scheme and then the association with stroke progression or recurrence was assessed. TOAST, CCS and A-S-C-O classification schemes were applied in 469 TIA-MS patients. When compared to TOAST both CCS (58.0 vs. 65.3%; p TIA and minor stroke patients classified as 'cause undetermined.' ASCO resulted in the fewest patients classified as cause undetermined. Stroke recurrence after TIA-MS is highest in patients with multiple high-risk etiologies or cryptogenic stroke classified by ASCO. © 2014 S. Karger AG, Basel.

Semi-Supervised Classification for Fault Diagnosis in Nuclear Power Plants

International Nuclear Information System (INIS)

Ma, Jian Ping; Jiang, Jin

2014-01-01

Pattern classification methods have become important tools for fault diagnosis in industrial systems. However, it is normally difficult to obtain reliable labeled data to train a supervised pattern classification model for applications in a nuclear power plant (NPP). However, unlabeled data easily become available through increased deployment of supervisory, control, and data acquisition (SCADA) systems. In this paper, a fault diagnosis scheme based on semi-supervised classification (SSC) method is developed with specific applications for NPP. In this scheme, newly measured plant data are treated as unlabeled data. They are integrated with selected labeled data to train a SSC model which is then used to estimate labels of the new data. Compared to exclusive supervised approaches, the proposed scheme requires significantly less number of labeled data to train a classifier. Furthermore, it is shown that higher degree of uncertainties in the labeled data can be tolerated. The developed scheme has been validated using the data generated from a desktop NPP simulator and also from a physical NPP simulator using a graph-based SSC algorithm. Two case studies have been used in the validation process. In the first case study, three faults have been simulated on the desktop simulator. These faults have all been classified successfully with only four labeled data points per fault case. In the second case, six types of fault are simulated on the physical NPP simulator. All faults have been successfully diagnosed. The results have demonstrated that SSC is a promising tool for fault diagnosis

High-order asynchrony-tolerant finite difference schemes for partial differential equations

Science.gov (United States)

Aditya, Konduri; Donzis, Diego A.

2017-12-01

Synchronizations of processing elements (PEs) in massively parallel simulations, which arise due to communication or load imbalances between PEs, significantly affect the scalability of scientific applications. We have recently proposed a method based on finite-difference schemes to solve partial differential equations in an asynchronous fashion - synchronization between PEs is relaxed at a mathematical level. While standard schemes can maintain their stability in the presence of asynchrony, their accuracy is drastically affected. In this work, we present a general methodology to derive asynchrony-tolerant (AT) finite difference schemes of arbitrary order of accuracy, which can maintain their accuracy when synchronizations are relaxed. We show that there are several choices available in selecting a stencil to derive these schemes and discuss their effect on numerical and computational performance. We provide a simple classification of schemes based on the stencil and derive schemes that are representative of different classes. Their numerical error is rigorously analyzed within a statistical framework to obtain the overall accuracy of the solution. Results from numerical experiments are used to validate the performance of the schemes.

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

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

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.

An overview of the EU Member States support schemes for the promotion of renewable energy sources

Energy Technology Data Exchange (ETDEWEB)

Poullikkas, Andreas; Kourtis, George; Hadjipaschalis, Ioannis [Electricity Authority of Cyprus, P.O. Box 24506, 1399 Nicosia (Cyprus)

2012-07-01

In this work, an overview of the European Union (EU) Member States support schemes for the promotion of renewable energy sources (RES) is provided. In particular, the status of the electricity generation capacity as well as the RES mixture in the Member States is described. Moreover, the different support schemes such as, investment support, feed-in tariffs (FiTs), tradable green certificates, and fiscal and financial measures which the Member States have adopted for the promotion of RES technologies are discussed in detail. Some Member States are implementing a single support scheme for the promotion of RES for power generation (RES-E), e.g., seven Member States use FiTs, or implement a hybrid support scheme by combining all or some of the four categories of the RES-E supporting schemes. Although, these support schemes have increased the penetration of the RES-E technologies in the Member States, still there is a long way in order to achieve the 2020 target. The reason for this may be that the way these schemes have been used so far, i.e., either as single support schemes or in combination of FiTs or tradable green certificates with investment support and fiscal and financial measures, has been ineffective. A more effective combination could be a hybrid scheme consisting of FiTs with tradable green certificates measures, as in the case of Italy and United Kingdom, that will increase the RES-E penetration and eliminate the possible technical problems which will arise from this increased penetration and have an effect in the stability of the power system.

Acoustic classification of housing according to ISO/CD 19488 compared with VDI 4100 and DEGA Recommendation 103

DEFF Research Database (Denmark)

Rasmussen, Birgit

2017-01-01

and for further development of design tools. Due to the high diversity in Europe, the European COST Action TU0901 ”Integrating and Harmonizing Sound Insulation Aspects in Sustainable Urban Housing Constructions” was established in 2009 with preparation of a proposal for an acoustic classification scheme...... and impact sound insulation between dwellings, facade sound insulation and service equipment noise. The schemes have been implemented and revised gradually since the 1990es. However, due to lack of coordination, there are significant discrepancies, implying obstacles for exchange of experience......In Europe, national acoustic classification schemes for housing exist in about ten countries. The schemes specify a number of quality classes, reflecting different levels of acoustic protection, and include class criteria concerning several acoustic aspects, main criteria being about airborne...

Interobserver and intraobserver reliability of two classification systems for intra-articular calcaneal fractures.

Science.gov (United States)

Lauder, Anthony J; Inda, David J; Bott, Aaron M; Clare, Michael P; Fitzgibbons, Timothy C; Mormino, Matthew A

2006-04-01

For a fracture classification to be useful it must provide prognostic significance, interobserver reliability, and intraobserver reproducibility. Most studies have found reliability and reproducibility to be poor for fracture classification schemes. The purpose of this study was to evaluate the interobserver and intraobserver reliability of the Sanders and Crosby-Fitzgibbons classification systems, two commonly used methods for classifying intra-articular calcaneal fractures. Twenty-five CT scans of intra-articular calcaneal fractures occurring at one trauma center were reviewed. The CT images were presented to eight observers (two orthopaedic surgery chief residents, two foot and ankle fellows, two fellowship-trained orthopaedic trauma surgeons, and two fellowship-trained foot and ankle surgeons) on two separate occasions 8 weeks apart. On each viewing, observers were asked to classify the fractures according to both the Sanders and Crosby-Fitzgibbons systems. Interobserver reliability and intraobserver reproducibility were assessed with computer-generated kappa statistics (SAS software; SAS Institute Inc., Cary, North Carolina). Total unanimity (eight of eight observers assigned the same fracture classification) was achieved only 24% (six of 25) of the time with the Sanders system and 36% (nine of 25) of the time with the Crosby-Fitzgibbons scheme. Interobserver reliability for the Sanders classification method reached a moderate (kappa = 0.48, 0.50) level of agreement, when the subclasses were included. The agreement level increased but remained in the moderate (kappa = 0.55, 0.55) range when the subclasses were excluded. Interobserver agreement reached a substantial (kappa = 0.63, 0.63) level with the Crosby-Fitzgibbons system. Intraobserver reproducibility was better for both schemes. The Sanders system with subclasses included reached moderate (kappa = 0.57) agreement, while ignoring the subclasses brought agreement into the substantial (kappa = 0.77) range

Assessing Measures of Order Flow Toxicity via Perfect Trade Classification

DEFF Research Database (Denmark)

Andersen, Torben G.; Bondarenko, Oleg

. The VPIN metric involves decomposing volume into active buys and sells. We use the best-bid-offer (BBO) files from the CME Group to construct (near) perfect trade classification measures for the E-mini S&P 500 futures contract. We investigate the accuracy of the ELO Bulk Volume Classification (BVC) scheme...... systematic classification errors that are correlated with trading volume and return volatility. When controlling for trading intensity and volatility, the BVC-VPIN measure has no incremental predictive power for future volatility. We conclude that VPIN is not suitable for measuring order flow imbalances....

A Hybrid MPC-PID Control System Design for the Continuous Purification and Processing of Active Pharmaceutical Ingredients

Directory of Open Access Journals (Sweden)

Maitraye Sen

2014-05-01

Full Text Available In this work, a hybrid MPC (model predictive control-PID (proportional-integral-derivative control system has been designed for the continuous purification and processing framework of active pharmaceutical ingredients (APIs. The specific unit operations associated with the purification and processing of API have been developed from first-principles and connected in a continuous framework in the form of a flowsheet model. These integrated unit operations are highly interactive along with the presence of process delays. Therefore, a hybrid MPC-PID is a promising alternative to achieve the desired control loop performance as mandated by the regulatory authorities. The integrated flowsheet model has been simulated in gPROMSTM (Process System Enterprise, London, UK. This flowsheet model has been linearized in order to design the control scheme. The ability to track the set point and reject disturbances has been evaluated. A comparative study between the performance of the hybrid MPC-PID and a PID-only control scheme has been presented. The results show that an enhanced control loop performance can be obtained under the hybrid control scheme and demonstrate that such a scheme has high potential in improving the efficiency of pharmaceutical manufacturing operations.

Simulation of a Wall-Bounded Flow using a Hybrid LES/RAS Approach with Turbulence Recycling

Science.gov (United States)

Quinlan, Jesse R.; Mcdaniel, James; Baurle, Robert A.

2012-01-01

Simulations of a supersonic recessed-cavity flow are performed using a hybrid large-eddy/ Reynolds-averaged simulation approach utilizing an inflow turbulence recycling procedure and hybridized inviscid flux scheme. Calorically perfect air enters the three-dimensional domain at a free stream Mach number of 2.92. Simulations are performed to assess grid sensitivity of the solution, efficacy of the turbulence recycling, and effect of the shock sensor used with the hybridized inviscid flux scheme. Analysis of the turbulent boundary layer upstream of the rearward-facing step for each case indicates excellent agreement with theoretical predictions. Mean velocity and pressure results are compared to Reynolds-averaged simulations and experimental data for each case, and these comparisons indicate good agreement on the finest grid. Simulations are repeated on a coarsened grid, and results indicate strong grid density sensitivity. The effect of turbulence recycling on the solution is illustrated by performing coarse grid simulations with and without inflow turbulence recycling. Two shock sensors, one of Ducros and one of Larsson, are assessed for use with the hybridized inviscid flux reconstruction scheme.

Sustainable process design & analysis of hybrid separations

DEFF Research Database (Denmark)

Kumar Tula, Anjan; Befort, Bridgette; Garg, Nipun

2016-01-01

Distillation is an energy intensive operation in chemical process industries. There are around 40,000 distillation columns in operation in the US, requiring approximately 40% of the total energy consumption in US chemical process industries. However, analysis of separations by distillation has...... shown that more than 50% of energy is spent in purifying the last 5-10% of the distillate product. Membrane modules on the other hand can achieve high purity separations at lower energy costs, but if the flux is high, it requires large membrane area. A hybrid scheme where distillation and membrane...... modules are combined such that each operates at its highest efficiency, has the potential for significant energy reduction without significant increase of capital costs. This paper presents a method for sustainable design of hybrid distillation-membrane schemes with guaranteed reduction of energy...

Evaluation of methods for extraction of the volitional EMG in dynamic hybrid muscle activation

Directory of Open Access Journals (Sweden)

Mizrahi Joseph

2006-11-01

Full Text Available Abstract Background Hybrid muscle activation is a modality used for muscle force enhancement, in which muscle contraction is generated from two different excitation sources: volitional and external, by means of electrical stimulation (ES. Under hybrid activation, the overall EMG signal is the combination of the volitional and ES-induced components. In this study, we developed a computational scheme to extract the volitional EMG envelope from the overall dynamic EMG signal, to serve as an input signal for control purposes, and for evaluation of muscle forces. Methods A "synthetic" database was created from in-vivo experiments on the Tibialis Anterior of the right foot to emulate hybrid EMG signals, including the volitional and induced components. The database was used to evaluate the results obtained from six signal processing schemes, including seven different modules for filtration, rectification and ES component removal. The schemes differed from each other by their module combinations, as follows: blocking window only, comb filter only, blocking window and comb filter, blocking window and peak envelope, comb filter and peak envelope and, finally, blocking window, comb filter and peak envelope. Results and conclusion The results showed that the scheme including all the modules led to an excellent approximation of the volitional EMG envelope, as extracted from the hybrid signal, and underlined the importance of the artifact blocking window module in the process. The results of this work have direct implications on the development of hybrid muscle activation rehabilitation systems for the enhancement of weakened muscles.

A hybrid mammalian cell cycle model

Directory of Open Access Journals (Sweden)

Vincent Noël

2013-08-01

Full Text Available Hybrid modeling provides an effective solution to cope with multiple time scales dynamics in systems biology. Among the applications of this method, one of the most important is the cell cycle regulation. The machinery of the cell cycle, leading to cell division and proliferation, combines slow growth, spatio-temporal re-organisation of the cell, and rapid changes of regulatory proteins concentrations induced by post-translational modifications. The advancement through the cell cycle comprises a well defined sequence of stages, separated by checkpoint transitions. The combination of continuous and discrete changes justifies hybrid modelling approaches to cell cycle dynamics. We present a piecewise-smooth version of a mammalian cell cycle model, obtained by hybridization from a smooth biochemical model. The approximate hybridization scheme, leading to simplified reaction rates and binary event location functions, is based on learning from a training set of trajectories of the smooth model. We discuss several learning strategies for the parameters of the hybrid model.

Ship Classification with High Resolution TerraSAR-X Imagery Based on Analytic Hierarchy Process

Directory of Open Access Journals (Sweden)

Zhi Zhao

2013-01-01

Full Text Available Ship surveillance using space-borne synthetic aperture radar (SAR, taking advantages of high resolution over wide swaths and all-weather working capability, has attracted worldwide attention. Recent activity in this field has concentrated mainly on the study of ship detection, but the classification is largely still open. In this paper, we propose a novel ship classification scheme based on analytic hierarchy process (AHP in order to achieve better performance. The main idea is to apply AHP on both feature selection and classification decision. On one hand, the AHP based feature selection constructs a selection decision problem based on several feature evaluation measures (e.g., discriminability, stability, and information measure and provides objective criteria to make comprehensive decisions for their combinations quantitatively. On the other hand, we take the selected feature sets as the input of KNN classifiers and fuse the multiple classification results based on AHP, in which the feature sets’ confidence is taken into account when the AHP based classification decision is made. We analyze the proposed classification scheme and demonstrate its results on a ship dataset that comes from TerraSAR-X SAR images.

On hybrid cooperation in underlay cognitive radio networks

KAUST Repository

Mahmood, Nurul Huda

2013-09-01

Cooperative communication is a promising strategy to enhance the performance of a communication network as it helps to improve the coverage area and the outage performance. However, such enhancement comes at the expense of increased resource utilization, which is undesirable; more so in the case of opportunistic wireless systems such as cognitive radio networks. In order to balance the performance gains from cooperative communication against the possible over-utilization of resources, we propose and analyze an adaptive-cooperation technique for underlay cognitive radio networks, termed as hybrid-cooperation. Under the proposed cooperation scheme, secondary users in a cognitive radio network cooperate adaptively to enhance the spectral efficiency and the error performance of the network. The bit error rate, the spectral efficiency and the outage performance of the network under the proposed hybrid cooperation scheme with amplify-and-forward relaying are analyzed in this paper, and compared against conventional cooperation technique. Findings of the analytical performance analyses are further validated numerically through selected computer-based Monte-Carlo simulations. The proposed scheme is found to achieve significantly better performance in terms of the spectral efficiency and the bit error rate, compared to the conventional amplify-and-forward cooperation scheme. © 2013 IEEE.

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

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.

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.

Optimization of hybrid model on hajj travel

Science.gov (United States)

Cahyandari, R.; Ariany, R. L.; Sukono

2018-03-01

Hajj travel insurance is an insurance product offered by the insurance company in preparing funds to perform the pilgrimage. This insurance product helps would-be pilgrims to set aside a fund of saving hajj with regularly, but also provides funds of profit sharing (mudharabah) and insurance protection. Scheme of insurance product fund management is largely using the hybrid model, which is the fund from would-be pilgrims will be divided into three account management, that is personal account, tabarru’, and ujrah. Scheme of hybrid model on hajj travel insurance was already discussed at the earlier paper with titled “The Hybrid Model Algorithm on Sharia Insurance”, taking the example case of Mitra Mabrur Plus product from Bumiputera company. On these advanced paper, will be made the previous optimization model design, with partition of benefit the tabarru’ account. Benefits such as compensation for 40 critical illness which initially only for participants of insurance only, on optimization is intended for participants of the insurance and his heir, also to benefit the hospital bills. Meanwhile, the benefits of death benefit is given if the participant is fixed die.

A study on the control of a hybrid MTDC system supplying a passive network

DEFF Research Database (Denmark)

Kotb, Omar; Ghandhari, Mehrdad; Eriksson, Robert

2014-01-01

A hybrid Multi-Terminal DC (MTDC) system can combine the benefits of both Line Commutated Converter (LCC) and Voltage Source Converter (VSC) technologies in the form of reduced losses and flexibility to connect to weak and passive grids. In this paper, an analysis of control strategies used...... in a hybrid MTDC system is presented. A case study of a four terminal hybrid MTDC system supplying a passive AC network was considered for simulation study. A control scheme based on voltage margin was developed to cope with the condition of main DC voltage controlling station tripping. Two various control...... scenarios for controlling the VSCs connected to the passive network were presented and compared. The system performance was studied through EMTP-RV simulations under different disturbances. The results show the ability of selected converter control modes and proposed control schemes to operate the hybrid...

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.

Hybrid silica materials for detection of toxic species and clinical diagnosis

OpenAIRE

Pascual Vidal, Lluís

2017-01-01

The present PhD thesis entitled "Silica Hybrid Materials for detection of toxic species and clinical diagnosis" is focused on the design and synthesis of new hybrid materials, using different silica supports as inorganic scaffolds, with applications in recognition, sensing and diagnostic protocols. The first chapter of the PhD thesis is devoted to the definition and classification of hybrid materials, relying on concepts of Nanotechnology, Supramolecular and Materials Chemistry. State o...

Control of hybrid AC/DC microgrid under islanding operational conditions

DEFF Research Database (Denmark)

Ding, G.; Gao, F.; Zhang, S.

2014-01-01

This paper presents control methods for hybrid AC/DC microgrid under islanding operation condition. The control schemes for AC sub-microgrid and DC sub-microgrid are investigated according to the power sharing requirement and operational reliability. In addition, the key control schemes...... of interlinking converter with DC-link capacitor or energy storage, which will devote to the proper power sharing between AC and DC sub-microgrids to maintain AC and DC side voltage stable, is reviewed. Combining the specific control methods developed for AC and DC sub-microgrids with interlinking converter......, the whole hybrid AC/DC microgrid can manage the power flow transferred between sub-microgrids for improving on the operational quality and efficiency....

DSMC-LBM mapping scheme for rarefied and non-rarefied gas flows

NARCIS (Netherlands)

Di Staso, G.; Clercx, H.J.H.; Succi, S.; Toschi, F.

2016-01-01

We present the formulation of a kinetic mapping scheme between the Direct Simulation Monte Carlo (DSMC) and the Lattice Boltzmann Method (LBM) which is at the basis of the hybrid model used to couple the two methods in view of efficiently and accurately simulate isothermal flows characterized by

A Hybrid Approach to Protect Palmprint Templates

Directory of Open Access Journals (Sweden)

Hailun Liu

2014-01-01

Full Text Available Biometric template protection is indispensable to protect personal privacy in large-scale deployment of biometric systems. Accuracy, changeability, and security are three critical requirements for template protection algorithms. However, existing template protection algorithms cannot satisfy all these requirements well. In this paper, we propose a hybrid approach that combines random projection and fuzzy vault to improve the performances at these three points. Heterogeneous space is designed for combining random projection and fuzzy vault properly in the hybrid scheme. New chaff point generation method is also proposed to enhance the security of the heterogeneous vault. Theoretical analyses of proposed hybrid approach in terms of accuracy, changeability, and security are given in this paper. Palmprint database based experimental results well support the theoretical analyses and demonstrate the effectiveness of proposed hybrid approach.

Hybrid Neuro-Fuzzy Classifier Based On Nefclass Model

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Bogdan Gliwa

2011-01-01

Full Text Available The paper presents hybrid neuro-fuzzy classifier, based on NEFCLASS model, which wasmodified. The presented classifier was compared to popular classifiers – neural networks andk-nearest neighbours. Efficiency of modifications in classifier was compared with methodsused in original model NEFCLASS (learning methods. Accuracy of classifier was testedusing 3 datasets from UCI Machine Learning Repository: iris, wine and breast cancer wisconsin.Moreover, influence of ensemble classification methods on classification accuracy waspresented.

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.

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

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

Classification of the Weyl tensor in higher dimensions and applications

International Nuclear Information System (INIS)

Coley, A

2008-01-01

We review the theory of alignment in Lorentzian geometry and apply it to the algebraic classification of the Weyl tensor in higher dimensions. This classification reduces to the well-known Petrov classification of the Weyl tensor in four dimensions. We discuss the algebraic classification of a number of known higher dimensional spacetimes. There are many applications of the Weyl classification scheme, especially when used in conjunction with the higher dimensional frame formalism that has been developed in order to generalize the four-dimensional Newman-Penrose formalism. For example, we discuss higher dimensional generalizations of the Goldberg-Sachs theorem and the peeling theorem. We also discuss the higher dimensional Lorentzian spacetimes with vanishing scalar curvature invariants and constant scalar curvature invariants, which are of interest since they are solutions of supergravity theory. (topical review)

Hybrid EEG-fNIRS-Based Eight-Command Decoding for BCI: Application to Quadcopter Control.

Science.gov (United States)

Khan, Muhammad Jawad; Hong, Keum-Shik

2017-01-01

In this paper, a hybrid electroencephalography-functional near-infrared spectroscopy (EEG-fNIRS) scheme to decode eight active brain commands from the frontal brain region for brain-computer interface is presented. A total of eight commands are decoded by fNIRS, as positioned on the prefrontal cortex, and by EEG, around the frontal, parietal, and visual cortices. Mental arithmetic, mental counting, mental rotation, and word formation tasks are decoded with fNIRS, in which the selected features for classification and command generation are the peak, minimum, and mean ΔHbO values within a 2-s moving window. In the case of EEG, two eyeblinks, three eyeblinks, and eye movement in the up/down and left/right directions are used for four-command generation. The features in this case are the number of peaks and the mean of the EEG signal during 1 s window. We tested the generated commands on a quadcopter in an open space. An average accuracy of 75.6% was achieved with fNIRS for four-command decoding and 86% with EEG for another four-command decoding. The testing results show the possibility of controlling a quadcopter online and in real-time using eight commands from the prefrontal and frontal cortices via the proposed hybrid EEG-fNIRS interface.

Advanced lattice Boltzmann scheme for high-Reynolds-number magneto-hydrodynamic flows

Science.gov (United States)

De Rosis, Alessandro; Lévêque, Emmanuel; Chahine, Robert

2018-06-01

Is the lattice Boltzmann method suitable to investigate numerically high-Reynolds-number magneto-hydrodynamic (MHD) flows? It is shown that a standard approach based on the Bhatnagar-Gross-Krook (BGK) collision operator rapidly yields unstable simulations as the Reynolds number increases. In order to circumvent this limitation, it is here suggested to address the collision procedure in the space of central moments for the fluid dynamics. Therefore, an hybrid lattice Boltzmann scheme is introduced, which couples a central-moment scheme for the velocity with a BGK scheme for the space-and-time evolution of the magnetic field. This method outperforms the standard approach in terms of stability, allowing us to simulate high-Reynolds-number MHD flows with non-unitary Prandtl number while maintaining accuracy and physical consistency.

Evaluation of the Chinese Fine Spatial Resolution Hyperspectral Satellite TianGong-1 in Urban Land-Cover Classification

Directory of Open Access Journals (Sweden)

Xueke Li

2016-05-01

Full Text Available The successful launch of the Chinese high spatial resolution hyperspectral satellite TianGong-1 (TG-1 opens up new possibilities for applications of remotely-sensed satellite imagery. One of the main goals of the TG-1 mission is to provide observations of surface attributes at local and landscape spatial scales to map urban land cover accurately using the hyperspectral technique. This study attempted to evaluate the TG-1 datasets for urban feature analysis, using existing data over Beijing, China, by comparing the TG-1 (with a spatial resolution of 10 m to EO-1 Hyperion (with a spatial resolution of 30 m. The spectral feature of TG-1 was first analyzed and, thus, finding out optimal hyperspectral wavebands useful for the discrimination of urban areas. Based on this, the pixel-based maximum likelihood classifier (PMLC, pixel-based support vector machine (PSVM, hybrid maximum likelihood classifier (HMLC, and hybrid support vector machine (HSVM were implemented, as well as compared in the application of mapping urban land cover types. The hybrid classifier approach, which integrates the pixel-based classifier and the object-based segmentation approach, was demonstrated as an effective alternative to the conventional pixel-based classifiers for processing the satellite hyperspectral data, especially the fine spatial resolution data. For TG-1 imagery, the pixel-based urban classification was obtained with an average overall accuracy of 89.1%, whereas the hybrid urban classification was obtained with an average overall accuracy of 91.8%. For Hyperion imagery, the pixel-based urban classification was obtained with an average overall accuracy of 85.9%, whereas the hybrid urban classification was obtained with an average overall accuracy of 86.7%. Overall, it can be concluded that the fine spatial resolution satellite hyperspectral data TG-1 is promising in delineating complex urban scenes, especially when using an appropriate classifier, such as the

A study for Unsafe Act classification under crew interaction during procedure-driven operation

International Nuclear Information System (INIS)

Choi, Sun Yeong; Park, Jinkyun; Kim, Yochan; Kim, Seunghwan; Jung, Wondea

2016-01-01

Highlights: • The procedure driven operation was divided into four stages by considering the crew relations such as instructions and responses. • Ten patterns of UA occurrence paths and the related operators per path were identified. • The UA type classification scheme was proposed based on the ten patterns of UA occurrence paths. • A case study to implement the UA type classification and to define the related operators per UA was performed. • The UA type classification scheme can be practical in that it prevents bias by subjective judgment. - Abstract: In this study, a method for UA (Unsafe Act) classification under a simulated procedure driven operation was proposed. To this end, a procedure driven operation was divided into four stages by considering the crew relations such as instructions and responses. Based on the four stages of a procedure driven operation, ten patterns of UA occurrence paths and the related operators per path were identified. From the ten types of UA occurrence paths including related operators, it is practicable to trace when and by whom a UA is initiated during a procedure driven operation, and the interaction or causality among the crew after the UA is initiated. Therefore, the types of UAs were classified into ‘Instruction UA’, ‘Reporting UA’, and ‘Execution UA’ by considering the initiation time and initiator of UA. A case study to implement the UA type classification and to define the related operators per UA was performed with the ISLOCA scenario simulator training data. The UA classification scheme proposed in this paper can be practical in that it does not require expertise relatively in a human performance analysis and it prevents bias by subjective judgment because it is based on an observation-based approach to exclude subjective judgment.

Speed-up of ab initio hybrid Monte Carlo and ab initio path integral hybrid Monte Carlo simulations by using an auxiliary potential energy surface

International Nuclear Information System (INIS)

Nakayama, Akira; Taketsugu, Tetsuya; Shiga, Motoyuki

2009-01-01

Efficiency of the ab initio hybrid Monte Carlo and ab initio path integral hybrid Monte Carlo methods is enhanced by employing an auxiliary potential energy surface that is used to update the system configuration via molecular dynamics scheme. As a simple illustration of this method, a dual-level approach is introduced where potential energy gradients are evaluated by computationally less expensive ab initio electronic structure methods. (author)

Changing patient classification system for hospital reimbursement in Romania.

Science.gov (United States)

Radu, Ciprian-Paul; Chiriac, Delia Nona; Vladescu, Cristian

2010-06-01

To evaluate the effects of the change in the diagnosis-related group (DRG) system on patient morbidity and hospital financial performance in the Romanian public health care system. Three variables were assessed before and after the classification switch in July 2007: clinical outcomes, the case mix index, and hospital budgets, using the database of the National School of Public Health and Health Services Management, which contains data regularly received from hospitals reimbursed through the Romanian DRG scheme (291 in 2009). The lack of a Romanian system for the calculation of cost-weights imposed the necessity to use an imported system, which was criticized by some clinicians for not accurately reflecting resource consumption in Romanian hospitals. The new DRG classification system allowed a more accurate clinical classification. However, it also exposed a lack of physicians' knowledge on diagnosing and coding procedures, which led to incorrect coding. Consequently, the reported hospital morbidity changed after the DRG switch, reflecting an increase in the national case-mix index of 25% in 2009 (compared with 2007). Since hospitals received the same reimbursement over the first two years after the classification switch, the new DRG system led them sometimes to change patients' diagnoses in order to receive more funding. Lack of oversight of hospital coding and reporting to the national reimbursement scheme allowed the increase in the case-mix index. The complexity of the new classification system requires more resources (human and financial), better monitoring and evaluation, and improved legislation in order to achieve better hospital resource allocation and more efficient patient care.

Hybrid nodal methods in the solution of the diffusion equations in X Y geometry; Metodos nodales hibridos en la solucion de las ecuaciones de difusion en geometria XY

Energy Technology Data Exchange (ETDEWEB)

Hernandez M, N. [CFE, Carretera Cardel-Nautla Km. 43.5, 91680 Veracruz (Mexico); Alonso V, G.; Valle G, E. del [IPN-ESFM, 07738 Mexico D.F. (Mexico)]. e-mail: nhmiranda@mexico.com

2003-07-01

In 1979, Hennart and collaborators applied several schemes of classic finite element in the numerical solution of the diffusion equations in X Y geometry and stationary state. Almost two decades then, in 1996, himself and other collaborators carried out a similar work but using nodal schemes type finite element. Continuing in this last direction, in this work a group it is described a set of several Hybrid Nodal schemes denominated (NH) as well as their application to solve the diffusion equations in multigroup in stationary state and X Y geometry. The term hybrid nodal it means that such schemes interpolate not only Legendre moments of face and of cell but also the values of the scalar flow of neutrons in the four corners of each cell or element of the spatial discretization of the domain of interest. All the schemes here considered are polynomials like they were it their predecessors. Particularly, its have developed and applied eight different hybrid nodal schemes that its are very nearby related with those developed by Hennart and collaborators in the past. It is treated of schemes in those that nevertheless that decreases the number of interpolation parameters it is conserved the accurate in relation to the bi-quadratic and bi-cubic schemes. Of these eight, three were described and applied in a previous work. It is the bi-lineal classic scheme as well as the hybrid nodal schemes, bi-quadratic and bi-cubic for that here only are described the other 5 hybrid nodal schemes although they are provided numerical results for several test problems with all them. (Author)

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.

Optical hybrid quantum teleportation and its applications

Science.gov (United States)

Takeda, Shuntaro; Okada, Masanori; Furusawa, Akira

2017-08-01

Quantum teleportation, a transfer protocol of quantum states, is the essence of many sophisticated quantum information protocols. There have been two complementary approaches to optical quantum teleportation: discrete variables (DVs) and continuous variables (CVs). However, both approaches have pros and cons. Here we take a "hybrid" approach to overcome the current limitations: CV quantum teleportation of DVs. This approach enabled the first realization of deterministic quantum teleportation of photonic qubits without post-selection. We also applied the hybrid scheme to several experiments, including entanglement swapping between DVs and CVs, conditional CV teleportation of single photons, and CV teleportation of qutrits. We are now aiming at universal, scalable, and fault-tolerant quantum computing based on these hybrid technologies.

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.

Achieving a hybrid brain-computer interface with tactile selective attention and motor imagery

Science.gov (United States)

Ahn, Sangtae; Ahn, Minkyu; Cho, Hohyun; Jun, Sung Chan

2014-12-01

Objective. We propose a new hybrid brain-computer interface (BCI) system that integrates two different EEG tasks: tactile selective attention (TSA) using a vibro-tactile stimulator on the left/right finger and motor imagery (MI) of left/right hand movement. Event-related desynchronization (ERD) from the MI task and steady-state somatosensory evoked potential (SSSEP) from the TSA task are retrieved and combined into two hybrid senses. Approach. One hybrid approach is to measure two tasks simultaneously; the features of each task are combined for testing. Another hybrid approach is to measure two tasks consecutively (TSA first and MI next) using only MI features. For comparison with the hybrid approaches, the TSA and MI tasks are measured independently. Main results. Using a total of 16 subject datasets, we analyzed the BCI classification performance for MI, TSA and two hybrid approaches in a comparative manner; we found that the consecutive hybrid approach outperformed the others, yielding about a 10% improvement in classification accuracy relative to MI alone. It is understood that TSA may play a crucial role as a prestimulus in that it helps to generate earlier ERD prior to MI and thus sustains ERD longer and to a stronger degree; this ERD may give more discriminative information than ERD in MI alone. Significance. Overall, our proposed consecutive hybrid approach is very promising for the development of advanced BCI systems.

Hydrological Climate Classification: Can We Improve on Köppen-Geiger?

Science.gov (United States)

Knoben, W.; Woods, R. A.; Freer, J. E.

2017-12-01

Classification is essential in the study of complex natural systems, yet hydrology so far has no formal way to structure the climate forcing which underlies hydrologic response. Various climate classification systems can be borrowed from other disciplines but these are based on different organizing principles than a hydrological classification might use. From gridded global data we calculate a gridded aridity index, an aridity seasonality index and a rain-vs-snow index, which we use to cluster global locations into climate groups. We then define the membership degree of nearly 1100 catchments to each of our climate groups based on each catchment's climate and investigate the extent to which streamflow responses within each climate group are similar. We compare this climate classification approach with the often-used Köppen-Geiger classification, using statistical tests based on streamflow signature values. We find that three climate indices are sufficient to distinguish 18 different climate types world-wide. Climates tend to change gradually in space and catchments can thus belong to multiple climate groups, albeit with different degrees of membership. Streamflow responses within a climate group tend to be similar, regardless of the catchments' geographical proximity. A Wilcoxon two-sample test based on streamflow signature values for each climate group shows that the new classification can distinguish different flow regimes using this classification scheme. The Köppen-Geiger approach uses 29 climate classes but is less able to differentiate streamflow regimes. Climate forcing exerts a strong control on typical hydrologic response and both change gradually in space. This makes arbitrary hard boundaries in any classification scheme difficult to defend. Any hydrological classification should thus acknowledge these gradual changes in forcing. Catchment characteristics (soil or vegetation type, land use, etc) can vary more quickly in space than climate does, which

Hydrologic landscape regionalisation using deductive classification and random forests.

Directory of Open Access Journals (Sweden)

Stuart C Brown

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

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).

Performance analyses of a hybrid geothermal–fossil power generation system using low-enthalpy geothermal resources

International Nuclear Information System (INIS)

Liu, Qiang; Shang, Linlin; Duan, Yuanyuan

2016-01-01

Highlights: • Geothermal energy is used to preheat the feedwater in a coal-fired power unit. • The performance of a hybrid geothermal–fossil power generation system is analyzed. • Models for both parallel and serial geothermal preheating schemes are presented. • Effects of geothermal source temperatures, distances and heat losses are analyzed. • Power increase of the hybrid system over an ORC and tipping distance are discussed. - Abstract: Low-enthalpy geothermal heat can be efficiently utilized for feedwater preheating in coal-fired power plants by replacing some of the high-grade steam that can then be used to generate more power. This study analyzes a hybrid geothermal–fossil power generation system including a supercritical 1000 MW power unit and a geothermal feedwater preheating system. This study models for parallel and serial geothermal preheating schemes and analyzes the thermodynamic performance of the hybrid geothermal–fossil power generation system for various geothermal resource temperatures. The models are used to analyze the effects of the temperature matching between the geothermal water and the feedwater, the heat losses and pumping power during the geothermal water transport and the resource distance and temperature on the power increase to improve the power generation. The serial geothermal preheating (SGP) scheme generally generates more additional power than the parallel geothermal preheating (PGP) scheme for geothermal resource temperatures of 100–130 °C, but the SGP scheme generates slightly less additional power than the PGP scheme when the feedwater is preheated to as high a temperature as possible before entering the deaerator for geothermal resource temperatures higher than 140 °C. The additional power decreases as the geothermal source distance increases since the pipeline pumping power increases and the geothermal water temperature decreases due to heat losses. More than 50% of the power decrease is due to geothermal

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.

A Semisupervised Cascade Classification Algorithm

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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.

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.

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.

Analysis of product efficiency of hybrid vehicles and promotion policies

International Nuclear Information System (INIS)

Choi, Hyundo; Oh, Inha

2010-01-01

The key aim of this study is to evaluate the product efficiency of current hybrid vehicles and suggest effective policies to promote hybrid vehicles in the Korean automobile market and development trends of hybrid vehicles. The efficiency levels for car models sold in Korea, including hybrid ones, were measured using the recently developed discrete additive data envelopment analysis (DEA) model that reflects consumer preference. The result of the analysis shows that current hybrid vehicles on the market are still at lower competitive advantage than traditional car models with conventional combustion engines and we can suggest a mix of incentive policies to promote the competitiveness of hybrid vehicles. In addition, we also identify two distinctive trends of hybrid vehicle development: environment-oriented hybrid vehicles and performance-oriented hybrid vehicles. It implies that the government should take account of development trends of hybrid vehicles to achieve the policy goals in designing support schemes and automobile companies that are willing to develop hybrid vehicles can also gain some insights for making strategic decisions. (author)

Modern classification and outcome predictors of surgery in patients with brain arteriovenous malformations.

Science.gov (United States)

Tayebi Meybodi, Ali; Lawton, Michael T

2018-02-23

Brain arteriovenous malformations (bAVM) are challenging lesions. Part of this challenge stems from the infinite diversity of these lesions regarding shape, location, anatomy, and physiology. This diversity has called on a variety of treatment modalities for these lesions, of which microsurgical resection prevails as the mainstay of treatment. As such, outcome prediction and managing strategy mainly rely on unraveling the nature of these complex tangles and ways each lesion responds to various therapeutic modalities. This strategy needs the ability to decipher each lesion through accurate and efficient categorization. Therefore, classification schemes are essential parts of treatment planning and outcome prediction. This article summarizes different surgical classification schemes and outcome predictors proposed for bAVMs.

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

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...

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....

Design and management of energy-efficient hybrid electrical energy storage systems

CERN Document Server

Kim, Younghyun

2014-01-01

This book covers system-level design optimization and implementation of hybrid energy storage systems. The author introduces various techniques to improve the performance of hybrid energy storage systems, in the context of design optimization and automation. Various energy storage techniques are discussed, each with its own advantages and drawbacks, offering viable, hybrid approaches to building a high performance, low cost energy storage system. Novel design optimization techniques and energy-efficient operation schemes are introduced. The author also describes the technical details of an act

Hybrid renewable energy support policy in the power sector: The contracts for difference and capacity market case study

International Nuclear Information System (INIS)

Onifade, Temitope Tunbi

2016-01-01

The article employs qualitative methods in contextualizing and conceptualizing the hybrid renewable energy support policy. It claims that hybrid policies may combine distinct mechanisms to drive desirable objectives better than traditional policies. A policy cycle helps to frame the United Kingdom's Contracts for Difference and Capacity Market (CFD & CM) scheme as a case study. The CFD & CM policy emerged to address environmental and energy challenges through the deployment of renewable energy (RE) in a low-carbon economy, employing liberalization: Environmental protection is foremost in this scheme. The policy combines and improves on the elements of feed-in tariff (FIT) and quota obligation (QO), and strives to solve the problems of these traditional policies. It addresses regulatory uncertainty under FIT by employing private law mechanics to guarantee above-loss reward for low carbon generation, and addresses market uncertainty under QO by incentivizing the capacity to supply future low carbon energy based on projected demand, hence creating a predictable and stable market. It also accommodates other important commitments. Overall, the CFD & CM scheme is a hybrid policy that engages the energy market mainly for advancing the end goal of environmental protection. To thrive however, it needs to meet private sector interests substantially. - Highlights: •The hybrid support policy combines traditional support systems. •Hybrid policies may drive objectives better than traditional policies. •The UK's contract for difference and capacity market system is a hybrid policy. •Environmental protection is foremost in the UK's hybrid policy. •To thrive, the UK's hybrid policy should address private sector interests.

Bidirectional fiber-wireless and fiber-IVLLC integrated system based on polarization-orthogonal modulation scheme.

Science.gov (United States)

Lu, Hai-Han; Li, Chung-Yi; Chen, Hwan-Wei; Ho, Chun-Ming; Cheng, Ming-Te; Huang, Sheng-Jhe; Yang, Zih-Yi; Lin, Xin-Yao

2016-07-25

A bidirectional fiber-wireless and fiber-invisible laser light communication (IVLLC) integrated system that employs polarization-orthogonal modulation scheme for hybrid cable television (CATV)/microwave (MW)/millimeter-wave (MMW)/baseband (BB) signal transmission is proposed and demonstrated. To our knowledge, it is the first one that adopts a polarization-orthogonal modulation scheme in a bidirectional fiber-wireless and fiber-IVLLC integrated system with hybrid CATV/MW/MMW/BB signal. For downlink transmission, carrier-to-noise ratio (CNR), composite second-order (CSO), composite triple-beat (CTB), and bit error rate (BER) perform well over 40-km single-mode fiber (SMF) and 10-m RF/50-m optical wireless transport scenarios. For uplink transmission, good BER performance is obtained over 40-km SMF and 50-m optical wireless transport scenario. Such a bidirectional fiber-wireless and fiber-IVLLC integrated system for hybrid CATV/MW/MMW/BB signal transmission will be an attractive alternative for providing broadband integrated services, including CATV, Internet, and telecommunication services. It is shown to be a prominent one to present the advancements for the convergence of fiber backbone and RF/optical wireless feeder.

Structural classification and a binary structure model for superconductors