WorldWideScience

Sample records for classification schemes based

  1. 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.

  2. 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.

  3. A Classification Scheme for Production System Processes

    DEFF Research Database (Denmark)

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

    2018-01-01

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

  4. A 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

    Highlights: • PET, HPDE or PP types of plastics are considered. • An automated classification of plastic bottles based on the feature extraction and classification methods is performed. • The decision mechanism consists of PCA, Kernel PCA, FLDA, SVD and Laplacian Eigenmaps methods. • SVM is selected to achieve the classification task and majority voting technique is used. - Abstract: Since recycling of materials is widely assumed to be environmentally and economically beneficial, reliable sorting and processing of waste packaging materials such as plastics is very important for recycling with high efficiency. An automated system that can quickly categorize these materials is certainly needed for obtaining maximum classification while maintaining high throughput. In this paper, first of all, the photographs of the plastic bottles have been taken and several preprocessing steps were carried out. The first preprocessing step is to extract the plastic area of a bottle from the background. Then, the morphological image operations are implemented. These operations are edge detection, noise removal, hole removing, image enhancement, and image segmentation. These morphological operations can be generally defined in terms of the combinations of erosion and dilation. The effect of bottle color as well as label are eliminated using these operations. Secondly, the pixel-wise intensity values of the plastic bottle images have been used together with the most popular subspace and statistical feature extraction methods to construct the feature vectors in this study. Only three types of plastics are considered due to higher existence ratio of them than the other plastic types in the world. The decision mechanism consists of five different feature extraction methods including as Principal Component Analysis (PCA), Kernel PCA (KPCA), Fisher’s Linear Discriminant Analysis (FLDA), Singular Value Decomposition (SVD) and Laplacian Eigenmaps (LEMAP) and uses a simple

  5. 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

    Highlights: • PET, HPDE or PP types of plastics are considered. • An automated classification of plastic bottles based on the feature extraction and classification methods is performed. • The decision mechanism consists of PCA, Kernel PCA, FLDA, SVD and Laplacian Eigenmaps methods. • SVM is selected to achieve the classification task and majority voting technique is used. - Abstract: Since recycling of materials is widely assumed to be environmentally and economically beneficial, reliable sorting and processing of waste packaging materials such as plastics is very important for recycling with high efficiency. An automated system that can quickly categorize these materials is certainly needed for obtaining maximum classification while maintaining high throughput. In this paper, first of all, the photographs of the plastic bottles have been taken and several preprocessing steps were carried out. The first preprocessing step is to extract the plastic area of a bottle from the background. Then, the morphological image operations are implemented. These operations are edge detection, noise removal, hole removing, image enhancement, and image segmentation. These morphological operations can be generally defined in terms of the combinations of erosion and dilation. The effect of bottle color as well as label are eliminated using these operations. Secondly, the pixel-wise intensity values of the plastic bottle images have been used together with the most popular subspace and statistical feature extraction methods to construct the feature vectors in this study. Only three types of plastics are considered due to higher existence ratio of them than the other plastic types in the world. The decision mechanism consists of five different feature extraction methods including as Principal Component Analysis (PCA), Kernel PCA (KPCA), Fisher’s Linear Discriminant Analysis (FLDA), Singular Value Decomposition (SVD) and Laplacian Eigenmaps (LEMAP) and uses a simple

  6. 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.

  7. Small-scale classification schemes

    DEFF Research Database (Denmark)

    Hertzum, Morten

    2004-01-01

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

  8. 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.

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

    Science.gov (United States)

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

    2016-01-01

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

  10. 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.

  11. 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.

  12. 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.

  13. 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.

  14. 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.

  15. A classification scheme for LWR fuel assemblies

    Energy Technology Data Exchange (ETDEWEB)

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

    1988-11-01

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

  16. A classification scheme for LWR fuel assemblies

    International Nuclear Information System (INIS)

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

    1988-11-01

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

  17. A Classification Scheme for Literary Characters

    Directory of Open Access Journals (Sweden)

    Matthew Berry

    2017-10-01

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

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

    Science.gov (United States)

    Biehl, Michael; Hammer, Barbara; Villmann, Thomas

    2017-06-01

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

  19. A classification scheme for risk assessment methods.

    Energy Technology Data Exchange (ETDEWEB)

    Stamp, Jason Edwin; Campbell, Philip LaRoche

    2004-08-01

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

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

    International Nuclear Information System (INIS)

    Marklund, G.

    1983-06-01

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

  1. A hierarchical classification scheme of psoriasis images

    DEFF Research Database (Denmark)

    Maletti, Gabriela Mariel; Ersbøll, Bjarne Kjær

    2003-01-01

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

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

    International Nuclear Information System (INIS)

    Kim, Yochan; Park, Jinkyun; Jung, Wondea

    2017-01-01

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

  3. 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

  4. 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 ...

  5. 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

  6. 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.

  7. 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.

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

    Science.gov (United States)

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

    2017-12-06

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

  9. Proposal of a new classification scheme for periocular injuries

    Directory of Open Access Journals (Sweden)

    Devi Prasad Mohapatra

    2017-01-01

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

  10. 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.

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

    Science.gov (United States)

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

  12. 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.

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

    DEFF Research Database (Denmark)

    Rasmussen, Birgit

    2009-01-01

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

  14. 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

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

    International Nuclear Information System (INIS)

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

    1997-01-01

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

  16. 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.

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

    DEFF Research Database (Denmark)

    Gao, Qian; Pratico, Giulia; Scalbert, Augustin

    2017-01-01

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

  18. Supervised machine learning-based classification scheme to segment the brainstem on MRI in multicenter brain tumor treatment context.

    Science.gov (United States)

    Dolz, Jose; Laprie, Anne; Ken, Soléakhéna; Leroy, Henri-Arthur; Reyns, Nicolas; Massoptier, Laurent; Vermandel, Maximilien

    2016-01-01

    To constrain the risk of severe toxicity in radiotherapy and radiosurgery, precise volume delineation of organs at risk is required. This task is still manually performed, which is time-consuming and prone to observer variability. To address these issues, and as alternative to atlas-based segmentation methods, machine learning techniques, such as support vector machines (SVM), have been recently presented to segment subcortical structures on magnetic resonance images (MRI). SVM is proposed to segment the brainstem on MRI in multicenter brain cancer context. A dataset composed by 14 adult brain MRI scans is used to evaluate its performance. In addition to spatial and probabilistic information, five different image intensity values (IIVs) configurations are evaluated as features to train the SVM classifier. Segmentation accuracy is evaluated by computing the Dice similarity coefficient (DSC), absolute volumes difference (AVD) and percentage volume difference between automatic and manual contours. Mean DSC for all proposed IIVs configurations ranged from 0.89 to 0.90. Mean AVD values were below 1.5 cm(3), where the value for best performing IIVs configuration was 0.85 cm(3), representing an absolute mean difference of 3.99% with respect to the manual segmented volumes. Results suggest consistent volume estimation and high spatial similarity with respect to expert delineations. The proposed approach outperformed presented methods to segment the brainstem, not only in volume similarity metrics, but also in segmentation time. Preliminary results showed that the approach might be promising for adoption in clinical use.

  19. International proposal for an acoustic classification scheme for dwellings

    DEFF Research Database (Denmark)

    Rasmussen, Birgit

    2014-01-01

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

  20. 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.

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

    Science.gov (United States)

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

    2014-06-01

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

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

    Science.gov (United States)

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

    2017-12-14

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

  3. 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…

  4. 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…

  5. 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…

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

    Energy Technology Data Exchange (ETDEWEB)

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

    2017-04-15

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

  7. 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.

  8. 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

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

    Science.gov (United States)

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

    2015-01-01

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

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

    International Nuclear Information System (INIS)

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

    2003-12-01

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

  11. 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…

  12. Pitch Based Sound Classification

    DEFF Research Database (Denmark)

    Nielsen, Andreas Brinch; Hansen, Lars Kai; Kjems, U

    2006-01-01

    A sound classification model is presented that can classify signals into music, noise and speech. The model extracts the pitch of the signal using the harmonic product spectrum. Based on the pitch estimate and a pitch error measure, features are created and used in a probabilistic model with soft......-max output function. Both linear and quadratic inputs are used. The model is trained on 2 hours of sound and tested on publicly available data. A test classification error below 0.05 with 1 s classification windows is achieved. Further more it is shown that linear input performs as well as a quadratic......, and that even though classification gets marginally better, not much is achieved by increasing the window size beyond 1 s....

  13. 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.

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

    Science.gov (United States)

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

    2014-01-01

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

  15. Granular loess classification based

    International Nuclear Information System (INIS)

    Browzin, B.S.

    1985-01-01

    This paper discusses how loess might be identified by two index properties: the granulometric composition and the dry unit weight. These two indices are necessary but not always sufficient for identification of loess. On the basis of analyses of samples from three continents, it was concluded that the 0.01-0.5-mm fraction deserves the name loessial fraction. Based on the loessial fraction concept, a granulometric classification of loess is proposed. A triangular chart is used to classify loess

  16. 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

  17. 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.

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

    Science.gov (United States)

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

    2017-04-01

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

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

    Directory of Open Access Journals (Sweden)

    René Roland Colditz

    2015-07-01

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

  20. 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.

  1. 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...

  2. 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...

  3. 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.

  4. Inventory classification based on decoupling points

    Directory of Open Access Journals (Sweden)

    Joakim Wikner

    2015-01-01

    Full Text Available The ideal state of continuous one-piece flow may never be achieved. Still the logistics manager can improve the flow by carefully positioning inventory to buffer against variations. Strategies such as lean, postponement, mass customization, and outsourcing all rely on strategic positioning of decoupling points to separate forecast-driven from customer-order-driven flows. Planning and scheduling of the flow are also based on classification of decoupling points as master scheduled or not. A comprehensive classification scheme for these types of decoupling points is introduced. The approach rests on identification of flows as being either demand based or supply based. The demand or supply is then combined with exogenous factors, classified as independent, or endogenous factors, classified as dependent. As a result, eight types of strategic as well as tactical decoupling points are identified resulting in a process-based framework for inventory classification that can be used for flow design.

  5. Cluster Based Text Classification Model

    DEFF Research Database (Denmark)

    Nizamani, Sarwat; Memon, Nasrullah; Wiil, Uffe Kock

    2011-01-01

    We propose a cluster based classification model for suspicious email detection and other text classification tasks. The text classification tasks comprise many training examples that require a complex classification model. Using clusters for classification makes the model simpler and increases...... the accuracy at the same time. The test example is classified using simpler and smaller model. The training examples in a particular cluster share the common vocabulary. At the time of clustering, we do not take into account the labels of the training examples. After the clusters have been created......, the classifier is trained on each cluster having reduced dimensionality and less number of examples. The experimental results show that the proposed model outperforms the existing classification models for the task of suspicious email detection and topic categorization on the Reuters-21578 and 20 Newsgroups...

  6. The impact of FNAC in the management of salivary gland lesions: Institutional experiences leading to a risk-based classification scheme.

    Science.gov (United States)

    Rossi, Esther Diana; Wong, Lawrence Q; Bizzarro, Tommaso; Petrone, Gianluigi; Mule, Antonio; Fadda, Guido; Baloch, Zubair M

    2016-06-01

    Fine-needle aspiration cytology (FNAC) has proven its value as an essential step in the diagnosis of salivary gland lesions. Although the majority of salivary gland lesions, especially those that are common and benign, can be diagnosed with ease on FNAC, limited cellularity and morphologic lesion heterogeneity can pose diagnostic challenges and lead to false-positive and false-negative diagnoses. This study presents the institutional experience of FNAC of salivary gland lesions from 2 academic centers. A retrospective analysis was conducted on 1729 salivary gland FNAC specimens that were diagnosed over an 8-year period from January 2008 to March 2015. All samples were processed either with liquid-based cytology alone or in combination with air-dried, Diff-Quik-stained or alcohol-fixed, Papanicolaou-stained smears. Surgical excision was performed in 709 of 1749 FNACs (41%) that were diagnosed as nondiagnostic/inadequate (n = 29), benign (n = 111), neoplasm (n = 453), atypical (n = 15), suspicious for malignancy (n = 28), and malignant (n = 73). The overall concordance between cytologic and histologic diagnoses was 92.2%, with 91.8% concordance in the benign category and 89.5% concordance in cases diagnosed as suspicious for malignancy and malignant. The most frequent benign and malignant lesions were pleomorphic adenoma and squamous cell carcinoma, respectively. There were 46 false-negative and 13 false-positive results, leading to an overall specificity of 97.6% and diagnostic accuracy of 91.3%. FNAC is a reliable diagnostic modality for the diagnosis and management of salivary gland lesions based on its high specificity and diagnostic accuracy. Cancer Cytopathol 2016;124:388-96. © 2016 American Cancer Society. © 2016 American Cancer Society.

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

    DEFF Research Database (Denmark)

    Rasmussen, Birgit

    2010-01-01

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

  8. 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.

  9. 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...

  10. A New Classification Approach Based on Multiple Classification Rules

    OpenAIRE

    Zhongmei Zhou

    2014-01-01

    A good classifier can correctly predict new data for which the class label is unknown, so it is important to construct a high accuracy classifier. Hence, classification techniques are much useful in ubiquitous computing. Associative classification achieves higher classification accuracy than some traditional rule-based classification approaches. However, the approach also has two major deficiencies. First, it generates a very large number of association classification rules, especially when t...

  11. 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 ...

  12. 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

  13. 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, ...

  14. 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...

  15. 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%.

  16. Adaptive PCA based fault diagnosis scheme in imperial smelting process.

    Science.gov (United States)

    Hu, Zhikun; Chen, Zhiwen; Gui, Weihua; Jiang, Bin

    2014-09-01

    In this paper, an adaptive fault detection scheme based on a recursive principal component analysis (PCA) is proposed to deal with the problem of false alarm due to normal process changes in real process. Our further study is also dedicated to develop a fault isolation approach based on Generalized Likelihood Ratio (GLR) test and Singular Value Decomposition (SVD) which is one of general techniques of PCA, on which the off-set and scaling fault can be easily isolated with explicit off-set fault direction and scaling fault classification. The identification of off-set and scaling fault is also applied. The complete scheme of PCA-based fault diagnosis procedure is proposed. The proposed scheme is first applied to Imperial Smelting Process, and the results show that the proposed strategies can be able to mitigate false alarms and isolate faults efficiently. Copyright © 2013 ISA. Published by Elsevier Ltd. All rights reserved.

  17. 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...

  18. 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.

  19. Signature scheme based on bilinear pairs

    Science.gov (United States)

    Tong, Rui Y.; Geng, Yong J.

    2013-03-01

    An identity-based signature scheme is proposed by using bilinear pairs technology. The scheme uses user's identity information as public key such as email address, IP address, telephone number so that it erases the cost of forming and managing public key infrastructure and avoids the problem of user private generating center generating forgery signature by using CL-PKC framework to generate user's private key.

  20. 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.

  1. 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...

  2. 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.

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

    International Nuclear Information System (INIS)

    Hojreh, A.

    2002-04-01

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

  4. Quantum Watermarking Scheme Based on INEQR

    Science.gov (United States)

    Zhou, Ri-Gui; Zhou, Yang; Zhu, Changming; Wei, Lai; Zhang, Xiafen; Ian, Hou

    2018-04-01

    Quantum watermarking technology protects copyright by embedding invisible quantum signal in quantum multimedia data. In this paper, a watermarking scheme based on INEQR was presented. Firstly, the watermark image is extended to achieve the requirement of embedding carrier image. Secondly, the swap and XOR operation is used on the processed pixels. Since there is only one bit per pixel, XOR operation can achieve the effect of simple encryption. Thirdly, both the watermark image extraction and embedding operations are described, where the key image, swap operation and LSB algorithm are used. When the embedding is made, the binary image key is changed. It means that the watermark has been embedded. Of course, if the watermark image is extracted, the key's state need detected. When key's state is |1>, this extraction operation is carried out. Finally, for validation of the proposed scheme, both the Signal-to-noise ratio (PSNR) and the security of the scheme are analyzed.

  5. 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...

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

    Science.gov (United States)

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

    2005-01-01

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

  7. 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...

  8. Comparison of wavelet based denoising schemes for gear condition monitoring: An Artificial Neural Network based Approach

    Science.gov (United States)

    Ahmed, Rounaq; Srinivasa Pai, P.; Sriram, N. S.; Bhat, Vasudeva

    2018-02-01

    Vibration Analysis has been extensively used in recent past for gear fault diagnosis. The vibration signals extracted is usually contaminated with noise and may lead to wrong interpretation of results. The denoising of extracted vibration signals helps the fault diagnosis by giving meaningful results. Wavelet Transform (WT) increases signal to noise ratio (SNR), reduces root mean square error (RMSE) and is effective to denoise the gear vibration signals. The extracted signals have to be denoised by selecting a proper denoising scheme in order to prevent the loss of signal information along with noise. An approach has been made in this work to show the effectiveness of Principal Component Analysis (PCA) to denoise gear vibration signal. In this regard three selected wavelet based denoising schemes namely PCA, Empirical Mode Decomposition (EMD), Neighcoeff Coefficient (NC), has been compared with Adaptive Threshold (AT) an extensively used wavelet based denoising scheme for gear vibration signal. The vibration signals acquired from a customized gear test rig were denoised by above mentioned four denoising schemes. The fault identification capability as well as SNR, Kurtosis and RMSE for the four denoising schemes have been compared. Features extracted from the denoised signals have been used to train and test artificial neural network (ANN) models. The performances of the four denoising schemes have been evaluated based on the performance of the ANN models. The best denoising scheme has been identified, based on the classification accuracy results. PCA is effective in all the regards as a best denoising scheme.

  9. 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...

  10. 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.

  11. 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.

  12. 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.

  13. A novel secret image sharing scheme based on chaotic system

    Science.gov (United States)

    Li, Li; Abd El-Latif, Ahmed A.; Wang, Chuanjun; Li, Qiong; Niu, Xiamu

    2012-04-01

    In this paper, we propose a new secret image sharing scheme based on chaotic system and Shamir's method. The new scheme protects the shadow images with confidentiality and loss-tolerance simultaneously. In the new scheme, we generate the key sequence based on chaotic system and then encrypt the original image during the sharing phase. Experimental results and analysis of the proposed scheme demonstrate a better performance than other schemes and confirm a high probability to resist brute force attack.

  14. 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.

  15. 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

  16. 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.

  17. 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

  18. Password Authentication Based on Fractal Coding Scheme

    Directory of Open Access Journals (Sweden)

    Nadia M. G. Al-Saidi

    2012-01-01

    Full Text Available Password authentication is a mechanism used to authenticate user identity over insecure communication channel. In this paper, a new method to improve the security of password authentication is proposed. It is based on the compression capability of the fractal image coding to provide an authorized user a secure access to registration and login process. In the proposed scheme, a hashed password string is generated and encrypted to be captured together with the user identity using text to image mechanisms. The advantage of fractal image coding is to be used to securely send the compressed image data through a nonsecured communication channel to the server. The verification of client information with the database system is achieved in the server to authenticate the legal user. The encrypted hashed password in the decoded fractal image is recognized using optical character recognition. The authentication process is performed after a successful verification of the client identity by comparing the decrypted hashed password with those which was stored in the database system. The system is analyzed and discussed from the attacker’s viewpoint. A security comparison is performed to show that the proposed scheme provides an essential security requirement, while their efficiency makes it easier to be applied alone or in hybrid with other security methods. Computer simulation and statistical analysis are presented.

  19. CT-based injury classification

    International Nuclear Information System (INIS)

    Mirvis, S.E.; Whitley, N.O.; Vainright, J.; Gens, D.

    1988-01-01

    Review of preoperative abdominal CT scans obtained in adults after blunt trauma during a 2.5-year period demonstrated isolated or predominant liver injury in 35 patients and splenic injury in 33 patients. CT-based injury scores, consisting of five levels of hepatic injury and four levels of splenic injury, were correlated with clinical outcome and surgical findings. Hepatic injury grades I-III, present in 33 of 35 patients, were associated with successful nonsurgical management in 27 (82%) or with findings at celiotomy not requiring surgical intervention in four (12%). Higher grades of splenic injury generally required early operative intervention, but eight (36%) of 22 patients with initial grade III or IV injury were managed without surgery, while four (36%) of 11 patients with grade I or II injury required delayed celiotomy and splenectomy (three patients) or emergent rehospitalization (one patient). CT-based injury classification is useful in guiding the nonoperative management of blunt hepatic injury in hemodynamically stable adults but appears to be less reliable in predicting the outcome of blunt splenic injury

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

    Science.gov (United States)

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

    2014-01-01

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

  1. 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.

  2. 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)

  3. A malware detection scheme based on mining format information.

    Science.gov (United States)

    Bai, Jinrong; Wang, Junfeng; Zou, Guozhong

    2014-01-01

    Malware has become one of the most serious threats to computer information system and the current malware detection technology still has very significant limitations. In this paper, we proposed a malware detection approach by mining format information of PE (portable executable) files. Based on in-depth analysis of the static format information of the PE files, we extracted 197 features from format information of PE files and applied feature selection methods to reduce the dimensionality of the features and achieve acceptable high performance. When the selected features were trained using classification algorithms, the results of our experiments indicate that the accuracy of the top classification algorithm is 99.1% and the value of the AUC is 0.998. We designed three experiments to evaluate the performance of our detection scheme and the ability of detecting unknown and new malware. Although the experimental results of identifying new malware are not perfect, our method is still able to identify 97.6% of new malware with 1.3% false positive rates.

  4. Color encryption scheme based on adapted quantum logistic map

    Science.gov (United States)

    Zaghloul, Alaa; Zhang, Tiejun; Amin, Mohamed; Abd El-Latif, Ahmed A.

    2014-04-01

    This paper presents a new color image encryption scheme based on quantum chaotic system. In this scheme, a new encryption scheme is accomplished by generating an intermediate chaotic key stream with the help of quantum chaotic logistic map. Then, each pixel is encrypted by the cipher value of the previous pixel and the adapted quantum logistic map. The results show that the proposed scheme has adequate security for the confidentiality of color images.

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

    International Nuclear Information System (INIS)

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

    1986-01-01

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

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

    DEFF Research Database (Denmark)

    Rasmussen, Birgit

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

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

    Directory of Open Access Journals (Sweden)

    Chen Ling

    2005-01-01

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

  8. 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

  9. 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

  10. 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...

  11. The Performance-based Funding Scheme of Universities

    Directory of Open Access Journals (Sweden)

    Juha KETTUNEN

    2016-05-01

    Full Text Available The purpose of this study is to analyse the effectiveness of the performance-based funding scheme of the Finnish universities that was adopted at the beginning of 2013. The political decision-makers expect that the funding scheme will create incentives for the universities to improve performance, but these funding schemes have largely failed in many other countries, primarily because public funding is only a small share of the total funding of universities. This study is interesting because Finnish universities have no tuition fees, unlike in many other countries, and the state allocates funding based on the objectives achieved. The empirical evidence of the graduation rates indicates that graduation rates increased when a new scheme was adopted, especially among male students, who have more room for improvement than female students. The new performance-based funding scheme allocates the funding according to the output-based indicators and limits the scope of strategic planning and the autonomy of the university. The performance-based funding scheme is transformed to the strategy map of the balanced scorecard. The new funding scheme steers universities in many respects but leaves the research and teaching skills to the discretion of the universities. The new scheme has also diminished the importance of the performance agreements between the university and the Ministry. The scheme increases the incentives for universities to improve the processes and structures in order to attain as much public funding as possible. It is optimal for the central administration of the university to allocate resources to faculties and other organisational units following the criteria of the performance-based funding scheme. The new funding scheme has made the universities compete with each other, because the total funding to the universities is allocated to each university according to the funding scheme. There is a tendency that the funding schemes are occasionally

  12. 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.

  13. Adaptive Image Transmission Scheme over Wavelet-Based OFDM System

    Institute of Scientific and Technical Information of China (English)

    GAOXinying; YUANDongfeng; ZHANGHaixia

    2005-01-01

    In this paper an adaptive image transmission scheme is proposed over Wavelet-based OFDM (WOFDM) system with Unequal error protection (UEP) by the design of non-uniform signal constellation in MLC. Two different data division schemes: byte-based and bitbased, are analyzed and compared. Different bits are protected unequally according to their different contribution to the image quality in bit-based data division scheme, which causes UEP combined with this scheme more powerful than that with byte-based scheme. Simulation results demonstrate that image transmission by UEP with bit-based data division scheme presents much higher PSNR values and surprisingly better image quality. Furthermore, by considering the tradeoff of complexity and BER performance, Haar wavelet with the shortest compactly supported filter length is the most suitable one among orthogonal Daubechies wavelet series in our proposed system.

  14. 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

  15. Quantum election scheme based on anonymous quantum key distribution

    International Nuclear Information System (INIS)

    Zhou Rui-Rui; Yang Li

    2012-01-01

    An unconditionally secure authority-certified anonymous quantum key distribution scheme using conjugate coding is presented, based on which we construct a quantum election scheme without the help of an entanglement state. We show that this election scheme ensures the completeness, soundness, privacy, eligibility, unreusability, fairness, and verifiability of a large-scale election in which the administrator and counter are semi-honest. This election scheme can work even if there exist loss and errors in quantum channels. In addition, any irregularity in this scheme is sensible. (general)

  16. Design Scheme of Remote Monitoring System Based on Qt

    Directory of Open Access Journals (Sweden)

    Xu Dawei

    2015-01-01

    Full Text Available This paper introduces a design scheme of remote monitoring system based on Qt, the scheme of remote monitoring system based on S3C2410 and Qt, with the aid of cross platform development tools Qt and powerful ARM platform design and implementation. The development of remote video surveillance system based on embedded terminal has practical significance and value.

  17. Cloud field classification based on textural features

    Science.gov (United States)

    Sengupta, Sailes Kumar

    1989-01-01

    An essential component in global climate research is accurate cloud cover and type determination. Of the two approaches to texture-based classification (statistical and textural), only the former is effective in the classification of natural scenes such as land, ocean, and atmosphere. In the statistical approach that was adopted, parameters characterizing the stochastic properties of the spatial distribution of grey levels in an image are estimated and then used as features for cloud classification. Two types of textural measures were used. One is based on the distribution of the grey level difference vector (GLDV), and the other on a set of textural features derived from the MaxMin cooccurrence matrix (MMCM). The GLDV method looks at the difference D of grey levels at pixels separated by a horizontal distance d and computes several statistics based on this distribution. These are then used as features in subsequent classification. The MaxMin tectural features on the other hand are based on the MMCM, a matrix whose (I,J)th entry give the relative frequency of occurrences of the grey level pair (I,J) that are consecutive and thresholded local extremes separated by a given pixel distance d. Textural measures are then computed based on this matrix in much the same manner as is done in texture computation using the grey level cooccurrence matrix. The database consists of 37 cloud field scenes from LANDSAT imagery using a near IR visible channel. The classification algorithm used is the well known Stepwise Discriminant Analysis. The overall accuracy was estimated by the percentage or correct classifications in each case. It turns out that both types of classifiers, at their best combination of features, and at any given spatial resolution give approximately the same classification accuracy. A neural network based classifier with a feed forward architecture and a back propagation training algorithm is used to increase the classification accuracy, using these two classes

  18. Error function attack of chaos synchronization based encryption schemes.

    Science.gov (United States)

    Wang, Xingang; Zhan, Meng; Lai, C-H; Gang, Hu

    2004-03-01

    Different chaos synchronization based encryption schemes are reviewed and compared from the practical point of view. As an efficient cryptanalysis tool for chaos encryption, a proposal based on the error function attack is presented systematically and used to evaluate system security. We define a quantitative measure (quality factor) of the effective applicability of a chaos encryption scheme, which takes into account the security, the encryption speed, and the robustness against channel noise. A comparison is made of several encryption schemes and it is found that a scheme based on one-way coupled chaotic map lattices performs outstandingly well, as judged from quality factor. Copyright 2004 American Institute of Physics.

  19. 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.

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

    Science.gov (United States)

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

    2017-01-01

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

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

    Science.gov (United States)

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

    2017-01-01

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

  2. A Classification-based Review Recommender

    Science.gov (United States)

    O'Mahony, Michael P.; Smyth, Barry

    Many online stores encourage their users to submit product/service reviews in order to guide future purchasing decisions. These reviews are often listed alongside product recommendations but, to date, limited attention has been paid as to how best to present these reviews to the end-user. In this paper, we describe a supervised classification approach that is designed to identify and recommend the most helpful product reviews. Using the TripAdvisor service as a case study, we compare the performance of several classification techniques using a range of features derived from hotel reviews. We then describe how these classifiers can be used as the basis for a practical recommender that automatically suggests the mosthelpful contrasting reviews to end-users. We present an empirical evaluation which shows that our approach achieves a statistically significant improvement over alternative review ranking schemes.

  3. An Efficient Homomorphic Aggregate Signature Scheme Based on Lattice

    Directory of Open Access Journals (Sweden)

    Zhengjun Jing

    2014-01-01

    Full Text Available Homomorphic aggregate signature (HAS is a linearly homomorphic signature (LHS for multiple users, which can be applied for a variety of purposes, such as multi-source network coding and sensor data aggregation. In order to design an efficient postquantum secure HAS scheme, we borrow the idea of the lattice-based LHS scheme over binary field in the single-user case, and develop it into a new lattice-based HAS scheme in this paper. The security of the proposed scheme is proved by showing a reduction to the single-user case and the signature length remains invariant. Compared with the existing lattice-based homomorphic aggregate signature scheme, our new scheme enjoys shorter signature length and high efficiency.

  4. A Digital Signature Scheme Based on MST3 Cryptosystems

    Directory of Open Access Journals (Sweden)

    Haibo Hong

    2014-01-01

    Full Text Available As special types of factorization of finite groups, logarithmic signature and cover have been used as the main components of cryptographic keys for secret key cryptosystems such as PGM and public key cryptosystems like MST1, MST2, and MST3. Recently, Svaba et. al proposed a revised MST3 encryption scheme with greater security. Meanwhile, they put forward an idea of constructing signature schemes on the basis of logarithmic signatures and random covers. In this paper, we firstly design a secure digital signature scheme based on logarithmic signatures and random covers. In order to complete the task, we devise a new encryption scheme based on MST3 cryptosystems.

  5. An Authentication Technique Based on Classification

    Institute of Scientific and Technical Information of China (English)

    李钢; 杨杰

    2004-01-01

    We present a novel watermarking approach based on classification for authentication, in which a watermark is embedded into the host image. When the marked image is modified, the extracted watermark is also different to the original watermark, and different kinds of modification lead to different extracted watermarks. In this paper, different kinds of modification are considered as classes, and we used classification algorithm to recognize the modifications with high probability. Simulation results show that the proposed method is potential and effective.

  6. Energy-efficiency based classification of the manufacturing workstation

    Science.gov (United States)

    Frumuşanu, G.; Afteni, C.; Badea, N.; Epureanu, A.

    2017-08-01

    EU Directive 92/75/EC established for the first time an energy consumption labelling scheme, further implemented by several other directives. As consequence, nowadays many products (e.g. home appliances, tyres, light bulbs, houses) have an EU Energy Label when offered for sale or rent. Several energy consumption models of manufacturing equipments have been also developed. This paper proposes an energy efficiency - based classification of the manufacturing workstation, aiming to characterize its energetic behaviour. The concept of energy efficiency of the manufacturing workstation is defined. On this base, a classification methodology has been developed. It refers to specific criteria and their evaluation modalities, together to the definition & delimitation of energy efficiency classes. The energy class position is defined after the amount of energy needed by the workstation in the middle point of its operating domain, while its extension is determined by the value of the first coefficient from the Taylor series that approximates the dependence between the energy consume and the chosen parameter of the working regime. The main domain of interest for this classification looks to be the optimization of the manufacturing activities planning and programming. A case-study regarding an actual lathe classification from energy efficiency point of view, based on two different approaches (analytical and numerical) is also included.

  7. Quantum signature scheme based on a quantum search algorithm

    International Nuclear Information System (INIS)

    Yoon, Chun Seok; Kang, Min Sung; Lim, Jong In; Yang, Hyung Jin

    2015-01-01

    We present a quantum signature scheme based on a two-qubit quantum search algorithm. For secure transmission of signatures, we use a quantum search algorithm that has not been used in previous quantum signature schemes. A two-step protocol secures the quantum channel, and a trusted center guarantees non-repudiation that is similar to other quantum signature schemes. We discuss the security of our protocol. (paper)

  8. Atmospheric circulation classification comparison based on wildfires in Portugal

    Science.gov (United States)

    Pereira, M. G.; Trigo, R. M.

    2009-04-01

    Atmospheric circulation classifications are not a simple description of atmospheric states but a tool to understand and interpret the atmospheric processes and to model the relation between atmospheric circulation and surface climate and other related variables (Radan Huth et al., 2008). Classifications were initially developed with weather forecasting purposes, however with the progress in computer processing capability, new and more robust objective methods were developed and applied to large datasets prompting atmospheric circulation classification methods to one of the most important fields in synoptic and statistical climatology. Classification studies have been extensively used in climate change studies (e.g. reconstructed past climates, recent observed changes and future climates), in bioclimatological research (e.g. relating human mortality to climatic factors) and in a wide variety of synoptic climatological applications (e.g. comparison between datasets, air pollution, snow avalanches, wine quality, fish captures and forest fires). Likewise, atmospheric circulation classifications are important for the study of the role of weather in wildfire occurrence in Portugal because the daily synoptic variability is the most important driver of local weather conditions (Pereira et al., 2005). In particular, the objective classification scheme developed by Trigo and DaCamara (2000) to classify the atmospheric circulation affecting Portugal have proved to be quite useful in discriminating the occurrence and development of wildfires as well as the distribution over Portugal of surface climatic variables with impact in wildfire activity such as maximum and minimum temperature and precipitation. This work aims to present: (i) an overview the existing circulation classification for the Iberian Peninsula, and (ii) the results of a comparison study between these atmospheric circulation classifications based on its relation with wildfires and relevant meteorological

  9. EMG finger movement classification based on ANFIS

    Science.gov (United States)

    Caesarendra, W.; Tjahjowidodo, T.; Nico, Y.; Wahyudati, S.; Nurhasanah, L.

    2018-04-01

    An increase number of people suffering from stroke has impact to the rapid development of finger hand exoskeleton to enable an automatic physical therapy. Prior to the development of finger exoskeleton, a research topic yet important i.e. machine learning of finger gestures classification is conducted. This paper presents a study on EMG signal classification of 5 finger gestures as a preliminary study toward the finger exoskeleton design and development in Indonesia. The EMG signals of 5 finger gestures were acquired using Myo EMG sensor. The EMG signal features were extracted and reduced using PCA. The ANFIS based learning is used to classify reduced features of 5 finger gestures. The result shows that the classification of finger gestures is less than the classification of 7 hand gestures.

  10. 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.

  11. Distance tracking scheme for seamless handover in IMS-based ...

    African Journals Online (AJOL)

    This paper proposes a fast and seamless handover scheme for systems based on IP Multimedia Subsystem (IMS) architectural framework with Universal Mobile Telecommunications System (UMTS) access network. In the scheme the location, direction and movement pattern of a Mobile Node (MN) in a network cell are ...

  12. Comprehensive Evaluation of Car-Body Light-Weighting Scheme Based on LCC Theory

    Directory of Open Access Journals (Sweden)

    Han Qing-lan

    2016-01-01

    Full Text Available In this paper, a comprehensive evaluation model of light-weighting scheme is established, which is based on three dimensions, including the life cycle costs of the resource consumed by the designed objects (LCC, willingness to pay for the environmental effect of resource consumption (WTP and performance (P. Firstly, cost of each stage is determined. Then, based on the resource classification, which is based on cost elements, determine the material list needed, and apply WTP weight coefficient to monetize life cycle environmental impact and obtain the life cycle comprehensive cost of designed scheme (TCC. In the next step Performance (P index is calculated to measure the value of the life cycle costs by applying AHP and SAW method, integrated (TCC and (P to achieve comprehensive evaluation of light-weighting scheme. Finally, the effectiveness of the evaluation model is verified by the example of car engine hood.

  13. 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

  14. 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.

  15. Cost-based droop scheme for DC microgrid

    DEFF Research Database (Denmark)

    Nutkani, Inam Ullah; Wang, Peng; Loh, Poh Chiang

    2014-01-01

    voltage level, less on optimized operation and control of generation sources. The latter theme is perused in this paper, where cost-based droop scheme is proposed for distributed generators (DGs) in DC microgrids. Unlike traditional proportional power sharing based droop scheme, the proposed scheme......-connected operation. Most importantly, the proposed scheme can reduce overall total generation cost in DC microgrids without centralized controller and communication links. The performance of the proposed scheme has been verified under different load conditions.......DC microgrids are gaining interest due to higher efficiencies of DC distribution compared with AC. The benefits of DC systems have been widely researched for data centers, IT facilities and residential applications. The research focus, however, has been more on system architecture and optimal...

  16. Task Classification Based Energy-Aware Consolidation in Clouds

    Directory of Open Access Journals (Sweden)

    HeeSeok Choi

    2016-01-01

    Full Text Available We consider a cloud data center, in which the service provider supplies virtual machines (VMs on hosts or physical machines (PMs to its subscribers for computation in an on-demand fashion. For the cloud data center, we propose a task consolidation algorithm based on task classification (i.e., computation-intensive and data-intensive and resource utilization (e.g., CPU and RAM. Furthermore, we design a VM consolidation algorithm to balance task execution time and energy consumption without violating a predefined service level agreement (SLA. Unlike the existing research on VM consolidation or scheduling that applies none or single threshold schemes, we focus on a double threshold (upper and lower scheme, which is used for VM consolidation. More specifically, when a host operates with resource utilization below the lower threshold, all the VMs on the host will be scheduled to be migrated to other hosts and then the host will be powered down, while when a host operates with resource utilization above the upper threshold, a VM will be migrated to avoid using 100% of resource utilization. Based on experimental performance evaluations with real-world traces, we prove that our task classification based energy-aware consolidation algorithm (TCEA achieves a significant energy reduction without incurring predefined SLA violations.

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

    Science.gov (United States)

    Dill, Harald G.; Weber, Berthold

    2013-12-01

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

  18. Voice based gender classification using machine learning

    Science.gov (United States)

    Raahul, A.; Sapthagiri, R.; Pankaj, K.; Vijayarajan, V.

    2017-11-01

    Gender identification is one of the major problem speech analysis today. Tracing the gender from acoustic data i.e., pitch, median, frequency etc. Machine learning gives promising results for classification problem in all the research domains. There are several performance metrics to evaluate algorithms of an area. Our Comparative model algorithm for evaluating 5 different machine learning algorithms based on eight different metrics in gender classification from acoustic data. Agenda is to identify gender, with five different algorithms: Linear Discriminant Analysis (LDA), K-Nearest Neighbour (KNN), Classification and Regression Trees (CART), Random Forest (RF), and Support Vector Machine (SVM) on basis of eight different metrics. The main parameter in evaluating any algorithms is its performance. Misclassification rate must be less in classification problems, which says that the accuracy rate must be high. Location and gender of the person have become very crucial in economic markets in the form of AdSense. Here with this comparative model algorithm, we are trying to assess the different ML algorithms and find the best fit for gender classification of acoustic data.

  19. Rough set classification based on quantum logic

    Science.gov (United States)

    Hassan, Yasser F.

    2017-11-01

    By combining the advantages of quantum computing and soft computing, the paper shows that rough sets can be used with quantum logic for classification and recognition systems. We suggest the new definition of rough set theory as quantum logic theory. Rough approximations are essential elements in rough set theory, the quantum rough set model for set-valued data directly construct set approximation based on a kind of quantum similarity relation which is presented here. Theoretical analyses demonstrate that the new model for quantum rough sets has new type of decision rule with less redundancy which can be used to give accurate classification using principles of quantum superposition and non-linear quantum relations. To our knowledge, this is the first attempt aiming to define rough sets in representation of a quantum rather than logic or sets. The experiments on data-sets have demonstrated that the proposed model is more accuracy than the traditional rough sets in terms of finding optimal classifications.

  20. Time-and-ID-Based Proxy Reencryption Scheme

    Directory of Open Access Journals (Sweden)

    Kambombo Mtonga

    2014-01-01

    Full Text Available Time- and ID-based proxy reencryption scheme is proposed in this paper in which a type-based proxy reencryption enables the delegator to implement fine-grained policies with one key pair without any additional trust on the proxy. However, in some applications, the time within which the data was sampled or collected is very critical. In such applications, for example, healthcare and criminal investigations, the delegatee may be interested in only some of the messages with some types sampled within some time bound instead of the entire subset. Hence, in order to carter for such situations, in this paper, we propose a time-and-identity-based proxy reencryption scheme that takes into account the time within which the data was collected as a factor to consider when categorizing data in addition to its type. Our scheme is based on Boneh and Boyen identity-based scheme (BB-IBE and Matsuo’s proxy reencryption scheme for identity-based encryption (IBE to IBE. We prove that our scheme is semantically secure in the standard model.

  1. A digital memories based user authentication scheme with privacy preservation.

    Directory of Open Access Journals (Sweden)

    JunLiang Liu

    Full Text Available The traditional username/password or PIN based authentication scheme, which still remains the most popular form of authentication, has been proved insecure, unmemorable and vulnerable to guessing, dictionary attack, key-logger, shoulder-surfing and social engineering. Based on this, a large number of new alternative methods have recently been proposed. However, most of them rely on users being able to accurately recall complex and unmemorable information or using extra hardware (such as a USB Key, which makes authentication more difficult and confusing. In this paper, we propose a Digital Memories based user authentication scheme adopting homomorphic encryption and a public key encryption design which can protect users' privacy effectively, prevent tracking and provide multi-level security in an Internet & IoT environment. Also, we prove the superior reliability and security of our scheme compared to other schemes and present a performance analysis and promising evaluation results.

  2. 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

  3. Investigation into Text Classification With Kernel Based Schemes

    Science.gov (United States)

    2010-03-01

    Document Matrix TDMs Term-Document Matrices TMG Text to Matrix Generator TN True Negative TP True Positive VSM Vector Space Model xxii THIS PAGE...are represented as a term-document matrix, common evaluation metrics, and the software package Text to Matrix Generator ( TMG ). The classifier...AND METRICS This chapter introduces the indexing capabilities of the Text to Matrix Generator ( TMG ) Toolbox. Specific attention is placed on the

  4. Analysis of composition-based metagenomic classification.

    Science.gov (United States)

    Higashi, Susan; Barreto, André da Motta Salles; Cantão, Maurício Egidio; de Vasconcelos, Ana Tereza Ribeiro

    2012-01-01

    An essential step of a metagenomic study is the taxonomic classification, that is, the identification of the taxonomic lineage of the organisms in a given sample. The taxonomic classification process involves a series of decisions. Currently, in the context of metagenomics, such decisions are usually based on empirical studies that consider one specific type of classifier. In this study we propose a general framework for analyzing the impact that several decisions can have on the classification problem. Instead of focusing on any specific classifier, we define a generic score function that provides a measure of the difficulty of the classification task. Using this framework, we analyze the impact of the following parameters on the taxonomic classification problem: (i) the length of n-mers used to encode the metagenomic sequences, (ii) the similarity measure used to compare sequences, and (iii) the type of taxonomic classification, which can be conventional or hierarchical, depending on whether the classification process occurs in a single shot or in several steps according to the taxonomic tree. We defined a score function that measures the degree of separability of the taxonomic classes under a given configuration induced by the parameters above. We conducted an extensive computational experiment and found out that reasonable values for the parameters of interest could be (i) intermediate values of n, the length of the n-mers; (ii) any similarity measure, because all of them resulted in similar scores; and (iii) the hierarchical strategy, which performed better in all of the cases. As expected, short n-mers generate lower configuration scores because they give rise to frequency vectors that represent distinct sequences in a similar way. On the other hand, large values for n result in sparse frequency vectors that represent differently metagenomic fragments that are in fact similar, also leading to low configuration scores. Regarding the similarity measure, in

  5. Mechanism-based drug exposure classification in pharmacoepidemiological studies

    NARCIS (Netherlands)

    Verdel, B.M.

    2010-01-01

    Mechanism-based classification of drug exposure in pharmacoepidemiological studies In pharmacoepidemiology and pharmacovigilance, the relation between drug exposure and clinical outcomes is crucial. Exposure classification in pharmacoepidemiological studies is traditionally based on

  6. 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.

  7. 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.

  8. A novel grain cluster-based homogenization scheme

    International Nuclear Information System (INIS)

    Tjahjanto, D D; Eisenlohr, P; Roters, F

    2010-01-01

    An efficient homogenization scheme, termed the relaxed grain cluster (RGC), for elasto-plastic deformations of polycrystals is presented. The scheme is based on a generalization of the grain cluster concept. A volume element consisting of eight (= 2 × 2 × 2) hexahedral grains is considered. The kinematics of the RGC scheme is formulated within a finite deformation framework, where the relaxation of the local deformation gradient of each individual grain is connected to the overall deformation gradient by the, so-called, interface relaxation vectors. The set of relaxation vectors is determined by the minimization of the constitutive energy (or work) density of the overall cluster. An additional energy density associated with the mismatch at the grain boundaries due to relaxations is incorporated as a penalty term into the energy minimization formulation. Effectively, this penalty term represents the kinematical condition of deformation compatibility at the grain boundaries. Simulations have been performed for a dual-phase grain cluster loaded in uniaxial tension. The results of the simulations are presented and discussed in terms of the effective stress–strain response and the overall deformation anisotropy as functions of the penalty energy parameters. In addition, the prediction of the RGC scheme is compared with predictions using other averaging schemes, as well as to the result of direct finite element (FE) simulation. The comparison indicates that the present RGC scheme is able to approximate FE simulation results of relatively fine discretization at about three orders of magnitude lower computational cost

  9. Application of Bayesian Classification to Content-Based Data Management

    Science.gov (United States)

    Lynnes, Christopher; Berrick, S.; Gopalan, A.; Hua, X.; Shen, S.; Smith, P.; Yang, K-Y.; Wheeler, K.; Curry, C.

    2004-01-01

    The high volume of Earth Observing System data has proven to be challenging to manage for data centers and users alike. At the Goddard Earth Sciences Distributed Active Archive Center (GES DAAC), about 1 TB of new data are archived each day. Distribution to users is also about 1 TB/day. A substantial portion of this distribution is MODIS calibrated radiance data, which has a wide variety of uses. However, much of the data is not useful for a particular user's needs: for example, ocean color users typically need oceanic pixels that are free of cloud and sun-glint. The GES DAAC is using a simple Bayesian classification scheme to rapidly classify each pixel in the scene in order to support several experimental content-based data services for near-real-time MODIS calibrated radiance products (from Direct Readout stations). Content-based subsetting would allow distribution of, say, only clear pixels to the user if desired. Content-based subscriptions would distribute data to users only when they fit the user's usability criteria in their area of interest within the scene. Content-based cache management would retain more useful data on disk for easy online access. The classification may even be exploited in an automated quality assessment of the geolocation product. Though initially to be demonstrated at the GES DAAC, these techniques have applicability in other resource-limited environments, such as spaceborne data systems.

  10. SQL based cardiovascular ultrasound image classification.

    Science.gov (United States)

    Nandagopalan, S; Suryanarayana, Adiga B; Sudarshan, T S B; Chandrashekar, Dhanalakshmi; Manjunath, C N

    2013-01-01

    This paper proposes a novel method to analyze and classify the cardiovascular ultrasound echocardiographic images using Naïve-Bayesian model via database OLAP-SQL. Efficient data mining algorithms based on tightly-coupled model is used to extract features. Three algorithms are proposed for classification namely Naïve-Bayesian Classifier for Discrete variables (NBCD) with SQL, NBCD with OLAP-SQL, and Naïve-Bayesian Classifier for Continuous variables (NBCC) using OLAP-SQL. The proposed model is trained with 207 patient images containing normal and abnormal categories. Out of the three proposed algorithms, a high classification accuracy of 96.59% was achieved from NBCC which is better than the earlier methods.

  11. 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.

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

    Science.gov (United States)

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

    2014-11-01

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

  13. 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

  14. Judgement of Design Scheme Based on Flexible Constraint in ICAD

    Institute of Scientific and Technical Information of China (English)

    2000-01-01

    The conception of flexible constraint is proposed in the paper. The solution of flexible constraint is in special range, and maybe different in different instances of same design scheme. The paper emphasis on how to evaluate and optimize a design scheme with flexible constraints based on the satisfaction degree function defined on flexible constraints. The conception of flexible constraint is used to solve constraint conflict and design optimization in complicated constraint-based assembly design by the PFM parametrization assembly design system. An instance of gear-box design is used for verifying optimization method.

  15. 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.

  16. 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...

  17. Design of a polynomial ring based symmetric homomorphic encryption scheme

    Directory of Open Access Journals (Sweden)

    Smaranika Dasgupta

    2016-09-01

    Full Text Available Security of data, especially in clouds, has become immensely essential for present-day applications. Fully homomorphic encryption (FHE is a great way to secure data which is used and manipulated by untrusted applications or systems. In this paper, we propose a symmetric FHE scheme based on polynomial over ring of integers. This scheme is somewhat homomorphic due to accumulation of noise after few operations, which is made fully homomorphic using a refresh procedure. After certain amount of homomorphic computations, large ciphertexts are refreshed for proper decryption. The hardness of the scheme is based on the difficulty of factorizing large integers. Also, it requires polynomial addition which is computationally cost effective. Experimental results are shown to support our claim.

  18. Integrated optical 3D digital imaging based on DSP scheme

    Science.gov (United States)

    Wang, Xiaodong; Peng, Xiang; Gao, Bruce Z.

    2008-03-01

    We present a scheme of integrated optical 3-D digital imaging (IO3DI) based on digital signal processor (DSP), which can acquire range images independently without PC support. This scheme is based on a parallel hardware structure with aid of DSP and field programmable gate array (FPGA) to realize 3-D imaging. In this integrated scheme of 3-D imaging, the phase measurement profilometry is adopted. To realize the pipeline processing of the fringe projection, image acquisition and fringe pattern analysis, we present a multi-threads application program that is developed under the environment of DSP/BIOS RTOS (real-time operating system). Since RTOS provides a preemptive kernel and powerful configuration tool, with which we are able to achieve a real-time scheduling and synchronization. To accelerate automatic fringe analysis and phase unwrapping, we make use of the technique of software optimization. The proposed scheme can reach a performance of 39.5 f/s (frames per second), so it may well fit into real-time fringe-pattern analysis and can implement fast 3-D imaging. Experiment results are also presented to show the validity of proposed scheme.

  19. Security problems with a chaos-based deniable authentication scheme

    International Nuclear Information System (INIS)

    Alvarez, Gonzalo

    2005-01-01

    Recently, a new scheme was proposed for deniable authentication. Its main originality lied on applying a chaos-based encryption-hash parallel algorithm and the semi-group property of the Chebyshev chaotic map. Although original and practicable, its insecurity and inefficiency are shown in this paper, thus rendering it inadequate for adoption in e-commerce

  20. Community Based Health Insurance Schemes and Protection of the ...

    African Journals Online (AJOL)

    The objectives of this study are two folds: firstly to explore the magnitude of catastrophic expenditure, and secondly to determine its contributing factor,s including the protective impact of the voluntary community based health insurance schemes in Tanzania. The study covered 274 respondents. Study findings have shown ...

  1. Security problems with a chaos-based deniable authentication scheme

    Energy Technology Data Exchange (ETDEWEB)

    Alvarez, Gonzalo [Instituto de Fisica Aplicada, Consejo Superior de Investigaciones Cientificas, Serrano 144, 28006 Madrid (Spain)] e-mail: gonzalo@iec.csic.es

    2005-10-01

    Recently, a new scheme was proposed for deniable authentication. Its main originality lied on applying a chaos-based encryption-hash parallel algorithm and the semi-group property of the Chebyshev chaotic map. Although original and practicable, its insecurity and inefficiency are shown in this paper, thus rendering it inadequate for adoption in e-commerce.

  2. A Muon Collider scheme based on Frictional Cooling

    Energy Technology Data Exchange (ETDEWEB)

    Abramowicz, H. [Tel Aviv University, Tel Aviv (Israel); Caldwell, A. [Max-Planck-Institut fuer Physik, Munich (Germany); Galea, R. [Nevis Laboratories, Columbia University, Irvington, NY (United States)]. E-mail: galea@nevis.columbia.edu; Schlenstedt, S. [DESY, Zeuthen (Germany)

    2005-07-11

    Muon Colliders would usher in a new era of scientific investigation in the field of high-energy particle physics. The cooling of muon beams is proving to be the greatest obstacle in the realization of a Muon Collider. Monte Carlo simulations of a muon cooling scheme based on Frictional Cooling were performed. Critical issues, which require further study, relating to the technical feasibility of such a scheme are identified. Frictional Cooling, as outlined in this paper, provides sufficient six-dimensional emittance to make luminous collisions possible. It holds exciting potential in solving the problem of Muon Cooling.

  3. A Muon Collider scheme based on Frictional Cooling

    International Nuclear Information System (INIS)

    Abramowicz, H.; Caldwell, A.; Galea, R.; Schlenstedt, S.

    2005-01-01

    Muon Colliders would usher in a new era of scientific investigation in the field of high-energy particle physics. The cooling of muon beams is proving to be the greatest obstacle in the realization of a Muon Collider. Monte Carlo simulations of a muon cooling scheme based on Frictional Cooling were performed. Critical issues, which require further study, relating to the technical feasibility of such a scheme are identified. Frictional Cooling, as outlined in this paper, provides sufficient six-dimensional emittance to make luminous collisions possible. It holds exciting potential in solving the problem of Muon Cooling

  4. A DFIG Islanding Detection Scheme Based on Reactive Power Infusion

    Science.gov (United States)

    Wang, M.; Liu, C.; He, G. Q.; Li, G. H.; Feng, K. H.; Sun, W. W.

    2017-07-01

    A lot of research has been done on photovoltaic (the “PV”) power system islanding detection in recent years. As a comparison, much less attention has been paid to islanding in wind turbines. Meanwhile, wind turbines can work in islanding conditions for quite a long period, which can be harmful to equipments and cause safety hazards. This paper presents and examines a double fed introduction generation (the “DFIG”) islanding detection scheme based on feedback of reactive power and frequency and uses a trigger signal of reactive power infusion which can be obtained by dividing the voltage total harmonic distortion (the "THD") by the voltage THD of last cycle to avoid the deterioration of power quality. This DFIG islanding detection scheme uses feedback of reactive power current loop to amplify the frequency differences in islanding and normal conditions. Simulation results show that the DFIG islanding detection scheme is effective.

  5. Breaking a chaos-noise-based secure communication scheme

    Science.gov (United States)

    Li, Shujun; Álvarez, Gonzalo; Chen, Guanrong; Mou, Xuanqin

    2005-03-01

    This paper studies the security of a secure communication scheme based on two discrete-time intermittently chaotic systems synchronized via a common random driving signal. Some security defects of the scheme are revealed: 1) The key space can be remarkably reduced; 2) the decryption is insensitive to the mismatch of the secret key; 3) the key-generation process is insecure against known/chosen-plaintext attacks. The first two defects mean that the scheme is not secure enough against brute-force attacks, and the third one means that an attacker can easily break the cryptosystem by approximately estimating the secret key once he has a chance to access a fragment of the generated keystream. Yet it remains to be clarified if intermittent chaos could be used for designing secure chaotic cryptosystems.

  6. A Novel Quantum Image Steganography Scheme Based on LSB

    Science.gov (United States)

    Zhou, Ri-Gui; Luo, Jia; Liu, XingAo; Zhu, Changming; Wei, Lai; Zhang, Xiafen

    2018-06-01

    Based on the NEQR representation of quantum images and least significant bit (LSB) scheme, a novel quantum image steganography scheme is proposed. The sizes of the cover image and the original information image are assumed to be 4 n × 4 n and n × n, respectively. Firstly, the bit-plane scrambling method is used to scramble the original information image. Then the scrambled information image is expanded to the same size of the cover image by using the key only known to the operator. The expanded image is scrambled to be a meaningless image with the Arnold scrambling. The embedding procedure and extracting procedure are carried out by K 1 and K 2 which are under control of the operator. For validation of the presented scheme, the peak-signal-to-noise ratio (PSNR), the capacity, the security of the images and the circuit complexity are analyzed.

  7. A privacy authentication scheme based on cloud for medical environment.

    Science.gov (United States)

    Chen, Chin-Ling; Yang, Tsai-Tung; Chiang, Mao-Lun; Shih, Tzay-Farn

    2014-11-01

    With the rapid development of the information technology, the health care technologies already became matured. Such as electronic medical records that can be easily stored. However, how to get medical resources more convenient is currently concerning issue. In spite of many literatures discussed about medical systems, these literatures should face many security challenges. The most important issue is patients' privacy. Therefore, we propose a privacy authentication scheme based on cloud environment. In our scheme, we use mobile device's characteristics, allowing peoples to use medical resources on the cloud environment to find medical advice conveniently. The digital signature is used to ensure the security of the medical information that is certified by the medical department in our proposed scheme.

  8. 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.

  9. 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

  10. 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.

  11. 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

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

    Science.gov (United States)

    Mackinejad, Kioumars; Sharifi, Vandad

    2006-01-01

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

  13. Research on Classification of Chinese Text Data Based on SVM

    Science.gov (United States)

    Lin, Yuan; Yu, Hongzhi; Wan, Fucheng; Xu, Tao

    2017-09-01

    Data Mining has important application value in today’s industry and academia. Text classification is a very important technology in data mining. At present, there are many mature algorithms for text classification. KNN, NB, AB, SVM, decision tree and other classification methods all show good classification performance. Support Vector Machine’ (SVM) classification method is a good classifier in machine learning research. This paper will study the classification effect based on the SVM method in the Chinese text data, and use the support vector machine method in the chinese text to achieve the classify chinese text, and to able to combination of academia and practical application.

  14. 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

  15. Time-and-ID-Based Proxy Reencryption Scheme

    OpenAIRE

    Mtonga, Kambombo; Paul, Anand; Rho, Seungmin

    2014-01-01

    Time- and ID-based proxy reencryption scheme is proposed in this paper in which a type-based proxy reencryption enables the delegator to implement fine-grained policies with one key pair without any additional trust on the proxy. However, in some applications, the time within which the data was sampled or collected is very critical. In such applications, for example, healthcare and criminal investigations, the delegatee may be interested in only some of the messages with some types sampled wi...

  16. Biometrics based authentication scheme for session initiation protocol

    OpenAIRE

    Xie, Qi; Tang, Zhixiong

    2016-01-01

    Many two-factor challenge-response based session initiation protocol (SIP) has been proposed, but most of them are vulnerable to smart card stolen attacks and password guessing attacks. In this paper, we propose a novel three-factor SIP authentication scheme using biometrics, password and smart card, and utilize the pi calculus-based formal verification tool ProVerif to prove that the proposed protocol achieves security and authentication. Furthermore, our protocol is highly efficient when co...

  17. A vegetation-based hierarchical classification for seasonally pulsed ...

    African Journals Online (AJOL)

    A classification scheme is presented for seasonal floodplains of the Boro-Xudum distributary of the Okavango Delta, Botswana. This distributary is subject to an annual flood-pulse, the inundated area varying from a mean low of 3 600 km2 to a mean high of 5 400 km2 between 2000 and 2006. A stratified random sample of ...

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

    Science.gov (United States)

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

    2012-05-18

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

  19. Threshold secret sharing scheme based on phase-shifting interferometry.

    Science.gov (United States)

    Deng, Xiaopeng; Shi, Zhengang; Wen, Wei

    2016-11-01

    We propose a new method for secret image sharing with the (3,N) threshold scheme based on phase-shifting interferometry. The secret image, which is multiplied with an encryption key in advance, is first encrypted by using Fourier transformation. Then, the encoded image is shared into N shadow images based on the recording principle of phase-shifting interferometry. Based on the reconstruction principle of phase-shifting interferometry, any three or more shadow images can retrieve the secret image, while any two or fewer shadow images cannot obtain any information of the secret image. Thus, a (3,N) threshold secret sharing scheme can be implemented. Compared with our previously reported method, the algorithm of this paper is suited for not only a binary image but also a gray-scale image. Moreover, the proposed algorithm can obtain a larger threshold value t. Simulation results are presented to demonstrate the feasibility of the proposed method.

  20. Contextual segment-based classification of airborne laser scanner data

    NARCIS (Netherlands)

    Vosselman, George; Coenen, Maximilian; Rottensteiner, Franz

    2017-01-01

    Classification of point clouds is needed as a first step in the extraction of various types of geo-information from point clouds. We present a new approach to contextual classification of segmented airborne laser scanning data. Potential advantages of segment-based classification are easily offset

  1. A New Wavelet-Based Document Image Segmentation Scheme

    Institute of Scientific and Technical Information of China (English)

    赵健; 李道京; 俞卞章; 耿军平

    2002-01-01

    The document image segmentation is very useful for printing, faxing and data processing. An algorithm is developed for segmenting and classifying document image. Feature used for classification is based on the histogram distribution pattern of different image classes. The important attribute of the algorithm is using wavelet correlation image to enhance raw image's pattern, so the classification accuracy is improved. In this paper document image is divided into four types: background, photo, text and graph. Firstly, the document image background has been distingusished easily by former normally method; secondly, three image types will be distinguished by their typical histograms, in order to make histograms feature clearer, each resolution' s HH wavelet subimage is used to add to the raw image at their resolution. At last, the photo, text and praph have been devided according to how the feature fit to the Laplacian distrbution by -X2 and L. Simulations show that classification accuracy is significantly improved. The comparison with related shows that our algorithm provides both lower classification error rates and better visual results.

  2. Enhancing Community Detection By Affinity-based Edge Weighting Scheme

    Energy Technology Data Exchange (ETDEWEB)

    Yoo, Andy [Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States); Sanders, Geoffrey [Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States); Henson, Van [Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States); Vassilevski, Panayot [Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States)

    2015-10-05

    Community detection refers to an important graph analytics problem of finding a set of densely-connected subgraphs in a graph and has gained a great deal of interest recently. The performance of current community detection algorithms is limited by an inherent constraint of unweighted graphs that offer very little information on their internal community structures. In this paper, we propose a new scheme to address this issue that weights the edges in a given graph based on recently proposed vertex affinity. The vertex affinity quantifies the proximity between two vertices in terms of their clustering strength, and therefore, it is ideal for graph analytics applications such as community detection. We also demonstrate that the affinity-based edge weighting scheme can improve the performance of community detection algorithms significantly.

  3. Functions and Design Scheme of Tibet High Altitude Test Base

    Institute of Scientific and Technical Information of China (English)

    Yu Yongqing; Guo Jian; Yin Yu; Mao Yan; Li Guangfan; Fan Jianbin; Lu Jiayu; Su Zhiyi; Li Peng; Li Qingfeng; Liao Weiming; Zhou Jun

    2010-01-01

    @@ The functional orientation of the Tibet High Altitude Test Base, subordinated to the State Grid Corporation of China (SGCC), is to serve power transmission projects in high altitude areas, especially to provide technical support for southwestern hydropower delivery projects by UHVDC transmission and Qinghai-Tibet grid interconnection project. This paper presents the matters concerned during siting and planning, functions,design scheme, the main performances and parameters of the test facilities, as well as the tests and research tasks already carried out.

  4. Multi-biometrics based cryptographic key regeneration scheme

    OpenAIRE

    Kanade , Sanjay Ganesh; Petrovska-Delacrétaz , Dijana; Dorizzi , Bernadette

    2009-01-01

    International audience; Biometrics lack revocability and privacy while cryptography cannot detect the user's identity. By obtaining cryptographic keys using biometrics, one can achieve the properties such as revocability, assurance about user's identity, and privacy. In this paper, we propose a multi-biometric based cryptographic key regeneration scheme. Since left and right irises of a person are uncorrelated, we treat them as two independent biometrics and combine in our system. We propose ...

  5. Image-Based Airborne Sensors: A Combined Approach for Spectral Signatures Classification through Deterministic Simulated Annealing

    Science.gov (United States)

    Guijarro, María; Pajares, Gonzalo; Herrera, P. Javier

    2009-01-01

    The increasing technology of high-resolution image airborne sensors, including those on board Unmanned Aerial Vehicles, demands automatic solutions for processing, either on-line or off-line, the huge amountds of image data sensed during the flights. The classification of natural spectral signatures in images is one potential application. The actual tendency in classification is oriented towards the combination of simple classifiers. In this paper we propose a combined strategy based on the Deterministic Simulated Annealing (DSA) framework. The simple classifiers used are the well tested supervised parametric Bayesian estimator and the Fuzzy Clustering. The DSA is an optimization approach, which minimizes an energy function. The main contribution of DSA is its ability to avoid local minima during the optimization process thanks to the annealing scheme. It outperforms simple classifiers used for the combination and some combined strategies, including a scheme based on the fuzzy cognitive maps and an optimization approach based on the Hopfield neural network paradigm. PMID:22399989

  6. 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.

  7. Hyperspectral Image Classification Based on the Combination of Spatial-spectral Feature and Sparse Representation

    Directory of Open Access Journals (Sweden)

    YANG Zhaoxia

    2015-07-01

    Full Text Available In order to avoid the problem of being over-dependent on high-dimensional spectral feature in the traditional hyperspectral image classification, a novel approach based on the combination of spatial-spectral feature and sparse representation is proposed in this paper. Firstly, we extract the spatial-spectral feature by reorganizing the local image patch with the first d principal components(PCs into a vector representation, followed by a sorting scheme to make the vector invariant to local image rotation. Secondly, we learn the dictionary through a supervised method, and use it to code the features from test samples afterwards. Finally, we embed the resulting sparse feature coding into the support vector machine(SVM for hyperspectral image classification. Experiments using three hyperspectral data show that the proposed method can effectively improve the classification accuracy comparing with traditional classification methods.

  8. 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.

  9. Density Based Support Vector Machines for Classification

    OpenAIRE

    Zahra Nazari; Dongshik Kang

    2015-01-01

    Support Vector Machines (SVM) is the most successful algorithm for classification problems. SVM learns the decision boundary from two classes (for Binary Classification) of training points. However, sometimes there are some less meaningful samples amongst training points, which are corrupted by noises or misplaced in wrong side, called outliers. These outliers are affecting on margin and classification performance, and machine should better to discard them. SVM as a popular and widely used cl...

  10. Correlation-based motion vector processing with adaptive interpolation scheme for motion-compensated frame interpolation.

    Science.gov (United States)

    Huang, Ai-Mei; Nguyen, Truong

    2009-04-01

    In this paper, we address the problems of unreliable motion vectors that cause visual artifacts but cannot be detected by high residual energy or bidirectional prediction difference in motion-compensated frame interpolation. A correlation-based motion vector processing method is proposed to detect and correct those unreliable motion vectors by explicitly considering motion vector correlation in the motion vector reliability classification, motion vector correction, and frame interpolation stages. Since our method gradually corrects unreliable motion vectors based on their reliability, we can effectively discover the areas where no motion is reliable to be used, such as occlusions and deformed structures. We also propose an adaptive frame interpolation scheme for the occlusion areas based on the analysis of their surrounding motion distribution. As a result, the interpolated frames using the proposed scheme have clearer structure edges and ghost artifacts are also greatly reduced. Experimental results show that our interpolated results have better visual quality than other methods. In addition, the proposed scheme is robust even for those video sequences that contain multiple and fast motions.

  11. Intelligent Aggregation Based on Content Routing Scheme for Cloud Computing

    Directory of Open Access Journals (Sweden)

    Jiachen Xu

    2017-10-01

    Full Text Available Cloud computing has emerged as today’s most exciting computing paradigm for providing services using a shared framework, which opens a new door for solving the problems of the explosive growth of digital resource demands and their corresponding convenience. With the exponential growth of the number of data types and data size in so-called big data work, the backbone network is under great pressure due to its transmission capacity, which is lower than the growth of the data size and would seriously hinder the development of the network without an effective approach to solve this problem. In this paper, an Intelligent Aggregation based on a Content Routing (IACR scheme for cloud computing, which could reduce the amount of data in the network effectively and play a basic supporting role in the development of cloud computing, is first put forward. All in all, the main innovations in this paper are: (1 A framework for intelligent aggregation based on content routing is proposed, which can support aggregation based content routing; (2 The proposed IACR scheme could effectively route the high aggregation ratio data to the data center through the same routing path so as to effectively reduce the amount of data that the network transmits. The theoretical analyses experiments and results show that, compared with the previous original routing scheme, the IACR scheme can balance the load of the whole network, reduce the amount of data transmitted in the network by 41.8%, and reduce the transmission time by 31.6% in the same network with a more balanced network load.

  12. 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)...

  13. Classification of research reactors and discussion of thinking of safety regulation based on the classification

    International Nuclear Information System (INIS)

    Song Chenxiu; Zhu Lixin

    2013-01-01

    Research reactors have different characteristics in the fields of reactor type, use, power level, design principle, operation model and safety performance, etc, and also have significant discrepancy in the aspect of nuclear safety regulation. This paper introduces classification of research reactors and discusses thinking of safety regulation based on the classification of research reactors. (authors)

  14. Management initiatives in a community-based health insurance scheme.

    Science.gov (United States)

    Sinha, Tara; Ranson, M Kent; Chatterjee, Mirai; Mills, Anne

    2007-01-01

    Community-based health insurance (CBHI) schemes have developed in response to inadequacies of alternate systems for protecting the poor against health care expenditures. Some of these schemes have arisen within community-based organizations (CBOs), which have strong links with poor communities, and are therefore well situated to offer CBHI. However, the managerial capacities of many such CBOs are limited. This paper describes management initiatives undertaken in a CBHI scheme in India, in the course of an action-research project. The existing structures and systems at the CBHI had several strengths, but fell short on some counts, which became apparent in the course of planning for two interventions under the research project. Management initiatives were introduced that addressed four features of the CBHI, viz. human resources, organizational structure, implementation systems, and data management. Trained personnel were hired and given clear roles and responsibilities. Lines of reporting and accountability were spelt out, and supportive supervision was provided to team members. The data resources of the organization were strengthened for greater utilization of this information. While the changes that were introduced took some time to be accepted by team members, the commitment of the CBHI's leadership to these initiatives was critical to their success. Copyright (c) 2007 John Wiley & Sons, Ltd.

  15. Prediction-based association control scheme in dense femtocell networks

    Science.gov (United States)

    Pham, Ngoc-Thai; Huynh, Thong; Hwang, Won-Joo; You, Ilsun; Choo, Kim-Kwang Raymond

    2017-01-01

    The deployment of large number of femtocell base stations allows us to extend the coverage and efficiently utilize resources in a low cost manner. However, the small cell size of femtocell networks can result in frequent handovers to the mobile user, and consequently throughput degradation. Thus, in this paper, we propose predictive association control schemes to improve the system’s effective throughput. Our design focuses on reducing handover frequency without impacting on throughput. The proposed schemes determine handover decisions that contribute most to the network throughput and are proper for distributed implementations. The simulation results show significant gains compared with existing methods in terms of handover frequency and network throughput perspective. PMID:28328992

  16. Sentiment classification technology based on Markov logic networks

    Science.gov (United States)

    He, Hui; Li, Zhigang; Yao, Chongchong; Zhang, Weizhe

    2016-07-01

    With diverse online media emerging, there is a growing concern of sentiment classification problem. At present, text sentiment classification mainly utilizes supervised machine learning methods, which feature certain domain dependency. On the basis of Markov logic networks (MLNs), this study proposed a cross-domain multi-task text sentiment classification method rooted in transfer learning. Through many-to-one knowledge transfer, labeled text sentiment classification, knowledge was successfully transferred into other domains, and the precision of the sentiment classification analysis in the text tendency domain was improved. The experimental results revealed the following: (1) the model based on a MLN demonstrated higher precision than the single individual learning plan model. (2) Multi-task transfer learning based on Markov logical networks could acquire more knowledge than self-domain learning. The cross-domain text sentiment classification model could significantly improve the precision and efficiency of text sentiment classification.

  17. An improved biometrics-based remote user authentication scheme with user anonymity.

    Science.gov (United States)

    Khan, Muhammad Khurram; Kumari, Saru

    2013-01-01

    The authors review the biometrics-based user authentication scheme proposed by An in 2012. The authors show that there exist loopholes in the scheme which are detrimental for its security. Therefore the authors propose an improved scheme eradicating the flaws of An's scheme. Then a detailed security analysis of the proposed scheme is presented followed by its efficiency comparison. The proposed scheme not only withstands security problems found in An's scheme but also provides some extra features with mere addition of only two hash operations. The proposed scheme allows user to freely change his password and also provides user anonymity with untraceability.

  18. An Improved Biometrics-Based Remote User Authentication Scheme with User Anonymity

    Directory of Open Access Journals (Sweden)

    Muhammad Khurram Khan

    2013-01-01

    Full Text Available The authors review the biometrics-based user authentication scheme proposed by An in 2012. The authors show that there exist loopholes in the scheme which are detrimental for its security. Therefore the authors propose an improved scheme eradicating the flaws of An’s scheme. Then a detailed security analysis of the proposed scheme is presented followed by its efficiency comparison. The proposed scheme not only withstands security problems found in An’s scheme but also provides some extra features with mere addition of only two hash operations. The proposed scheme allows user to freely change his password and also provides user anonymity with untraceability.

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

    Science.gov (United States)

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

    2016-01-01

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

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

    Directory of Open Access Journals (Sweden)

    Christopher Beckham

    2016-08-01

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

  1. Biometrics based authentication scheme for session initiation protocol.

    Science.gov (United States)

    Xie, Qi; Tang, Zhixiong

    2016-01-01

    Many two-factor challenge-response based session initiation protocol (SIP) has been proposed, but most of them are vulnerable to smart card stolen attacks and password guessing attacks. In this paper, we propose a novel three-factor SIP authentication scheme using biometrics, password and smart card, and utilize the pi calculus-based formal verification tool ProVerif to prove that the proposed protocol achieves security and authentication. Furthermore, our protocol is highly efficient when compared to other related protocols.

  2. Demand response scheme based on lottery-like rebates

    KAUST Repository

    Schwartz, Galina A.; Tembine, Hamidou; Amin, Saurabh; Sastry, S. Shankar

    2014-01-01

    In this paper, we develop a novel mechanism for reducing volatility of residential demand for electricity. We construct a reward-based (rebate) mechanism that provides consumers with incentives to shift their demand to off-peak time. In contrast to most other mechanisms proposed in the literature, the key feature of our mechanism is its modest requirements on user preferences, i.e., it does not require exact knowledge of user responsiveness to rewards for shifting their demand from the peak to the off-peak time. Specifically, our mechanism utilizes a probabilistic reward structure for users who shift their demand to the off-peak time, and is robust to incomplete information about user demand and/or risk preferences. We approach the problem from the public good perspective, and demonstrate that the mechanism can be implemented via lottery-like schemes. Our mechanism permits to reduce the distribution losses, and thus improve efficiency of electricity distribution. Finally, the mechanism can be readily incorporated into the emerging demand response schemes (e.g., the time-of-day pricing, and critical peak pricing schemes), and has security and privacy-preserving properties.

  3. Demand response scheme based on lottery-like rebates

    KAUST Repository

    Schwartz, Galina A.

    2014-08-24

    In this paper, we develop a novel mechanism for reducing volatility of residential demand for electricity. We construct a reward-based (rebate) mechanism that provides consumers with incentives to shift their demand to off-peak time. In contrast to most other mechanisms proposed in the literature, the key feature of our mechanism is its modest requirements on user preferences, i.e., it does not require exact knowledge of user responsiveness to rewards for shifting their demand from the peak to the off-peak time. Specifically, our mechanism utilizes a probabilistic reward structure for users who shift their demand to the off-peak time, and is robust to incomplete information about user demand and/or risk preferences. We approach the problem from the public good perspective, and demonstrate that the mechanism can be implemented via lottery-like schemes. Our mechanism permits to reduce the distribution losses, and thus improve efficiency of electricity distribution. Finally, the mechanism can be readily incorporated into the emerging demand response schemes (e.g., the time-of-day pricing, and critical peak pricing schemes), and has security and privacy-preserving properties.

  4. Dynamic Symmetric Key Mobile Commerce Scheme Based on Self-Verified Mechanism

    Directory of Open Access Journals (Sweden)

    Jiachen Yang

    2014-01-01

    Full Text Available In terms of the security and efficiency of mobile e-commerce, the authors summarized the advantages and disadvantages of several related schemes, especially the self-verified mobile payment scheme based on the elliptic curve cryptosystem (ECC and then proposed a new type of dynamic symmetric key mobile commerce scheme based on self-verified mechanism. The authors analyzed the basic algorithm based on self-verified mechanisms and detailed the complete transaction process of the proposed scheme. The authors analyzed the payment scheme based on the security and high efficiency index. The analysis shows that the proposed scheme not only meets the high efficiency of mobile electronic payment premise, but also takes the security into account. The user confirmation mechanism at the end of the proposed scheme further strengthens the security of the proposed scheme. In brief, the proposed scheme is more efficient and practical than most of the existing schemes.

  5. Risk-based classification system of nanomaterials

    International Nuclear Information System (INIS)

    Tervonen, Tommi; Linkov, Igor; Figueira, Jose Rui; Steevens, Jeffery; Chappell, Mark; Merad, Myriam

    2009-01-01

    Various stakeholders are increasingly interested in the potential toxicity and other risks associated with nanomaterials throughout the different stages of a product's life cycle (e.g., development, production, use, disposal). Risk assessment methods and tools developed and applied to chemical and biological materials may not be readily adaptable for nanomaterials because of the current uncertainty in identifying the relevant physico-chemical and biological properties that adequately describe the materials. Such uncertainty is further driven by the substantial variations in the properties of the original material due to variable manufacturing processes employed in nanomaterial production. To guide scientists and engineers in nanomaterial research and application as well as to promote the safe handling and use of these materials, we propose a decision support system for classifying nanomaterials into different risk categories. The classification system is based on a set of performance metrics that measure both the toxicity and physico-chemical characteristics of the original materials, as well as the expected environmental impacts through the product life cycle. Stochastic multicriteria acceptability analysis (SMAA-TRI), a formal decision analysis method, was used as the foundation for this task. This method allowed us to cluster various nanomaterials in different ecological risk categories based on our current knowledge of nanomaterial physico-chemical characteristics, variation in produced material, and best professional judgments. SMAA-TRI uses Monte Carlo simulations to explore all feasible values for weights, criteria measurements, and other model parameters to assess the robustness of nanomaterial grouping for risk management purposes.

  6. Structure-Based Algorithms for Microvessel Classification

    KAUST Repository

    Smith, Amy F.

    2015-02-01

    © 2014 The Authors. Microcirculation published by John Wiley & Sons Ltd. Objective: Recent developments in high-resolution imaging techniques have enabled digital reconstruction of three-dimensional sections of microvascular networks down to the capillary scale. To better interpret these large data sets, our goal is to distinguish branching trees of arterioles and venules from capillaries. Methods: Two novel algorithms are presented for classifying vessels in microvascular anatomical data sets without requiring flow information. The algorithms are compared with a classification based on observed flow directions (considered the gold standard), and with an existing resistance-based method that relies only on structural data. Results: The first algorithm, developed for networks with one arteriolar and one venular tree, performs well in identifying arterioles and venules and is robust to parameter changes, but incorrectly labels a significant number of capillaries as arterioles or venules. The second algorithm, developed for networks with multiple inlets and outlets, correctly identifies more arterioles and venules, but is more sensitive to parameter changes. Conclusions: The algorithms presented here can be used to classify microvessels in large microvascular data sets lacking flow information. This provides a basis for analyzing the distinct geometrical properties and modelling the functional behavior of arterioles, capillaries, and venules.

  7. Risk-based classification system of nanomaterials

    Energy Technology Data Exchange (ETDEWEB)

    Tervonen, Tommi, E-mail: t.p.tervonen@rug.n [University of Groningen, Faculty of Economics and Business (Netherlands); Linkov, Igor, E-mail: igor.linkov@usace.army.mi [US Army Research and Development Center (United States); Figueira, Jose Rui, E-mail: figueira@ist.utl.p [Technical University of Lisbon, CEG-IST, Centre for Management Studies, Instituto Superior Tecnico (Portugal); Steevens, Jeffery, E-mail: jeffery.a.steevens@usace.army.mil; Chappell, Mark, E-mail: mark.a.chappell@usace.army.mi [US Army Research and Development Center (United States); Merad, Myriam, E-mail: myriam.merad@ineris.f [INERIS BP 2, Societal Management of Risks Unit/Accidental Risks Division (France)

    2009-05-15

    Various stakeholders are increasingly interested in the potential toxicity and other risks associated with nanomaterials throughout the different stages of a product's life cycle (e.g., development, production, use, disposal). Risk assessment methods and tools developed and applied to chemical and biological materials may not be readily adaptable for nanomaterials because of the current uncertainty in identifying the relevant physico-chemical and biological properties that adequately describe the materials. Such uncertainty is further driven by the substantial variations in the properties of the original material due to variable manufacturing processes employed in nanomaterial production. To guide scientists and engineers in nanomaterial research and application as well as to promote the safe handling and use of these materials, we propose a decision support system for classifying nanomaterials into different risk categories. The classification system is based on a set of performance metrics that measure both the toxicity and physico-chemical characteristics of the original materials, as well as the expected environmental impacts through the product life cycle. Stochastic multicriteria acceptability analysis (SMAA-TRI), a formal decision analysis method, was used as the foundation for this task. This method allowed us to cluster various nanomaterials in different ecological risk categories based on our current knowledge of nanomaterial physico-chemical characteristics, variation in produced material, and best professional judgments. SMAA-TRI uses Monte Carlo simulations to explore all feasible values for weights, criteria measurements, and other model parameters to assess the robustness of nanomaterial grouping for risk management purposes.

  8. An Industrial Model Based Disturbance Feedback Control Scheme

    DEFF Research Database (Denmark)

    Kawai, Fukiko; Nakazawa, Chikashi; Vinther, Kasper

    2014-01-01

    This paper presents a model based disturbance feedback control scheme. Industrial process systems have been traditionally controlled by using relay and PID controller. However these controllers are affected by disturbances and model errors and these effects degrade control performance. The authors...... propose a new control method that can decrease the negative impact of disturbance and model errors. The control method is motivated by industrial practice by Fuji Electric. Simulation tests are examined with a conventional PID controller and the disturbance feedback control. The simulation results...

  9. A New Images Hiding Scheme Based on Chaotic Sequences

    Institute of Scientific and Technical Information of China (English)

    LIU Nian-sheng; GUO Dong-hui; WU Bo-xi; Parr G

    2005-01-01

    We propose a data hidding technique in a still image. This technique is based on chaotic sequence in the transform domain of covert image. We use different chaotic random sequences multiplied by multiple sensitive images, respectively, to spread the spectrum of sensitive images. Multiple sensitive images are hidden in a covert image as a form of noise. The results of theoretical analysis and computer simulation show the new hiding technique have better properties with high security, imperceptibility and capacity for hidden information in comparison with the conventional scheme such as LSB (Least Significance Bit).

  10. Information Security Scheme Based on Computational Temporal Ghost Imaging.

    Science.gov (United States)

    Jiang, Shan; Wang, Yurong; Long, Tao; Meng, Xiangfeng; Yang, Xiulun; Shu, Rong; Sun, Baoqing

    2017-08-09

    An information security scheme based on computational temporal ghost imaging is proposed. A sequence of independent 2D random binary patterns are used as encryption key to multiply with the 1D data stream. The cipher text is obtained by summing the weighted encryption key. The decryption process can be realized by correlation measurement between the encrypted information and the encryption key. Due to the instinct high-level randomness of the key, the security of this method is greatly guaranteed. The feasibility of this method and robustness against both occlusion and additional noise attacks are discussed with simulation, respectively.

  11. Image Interpolation Scheme based on SVM and Improved PSO

    Science.gov (United States)

    Jia, X. F.; Zhao, B. T.; Liu, X. X.; Song, H. P.

    2018-01-01

    In order to obtain visually pleasing images, a support vector machines (SVM) based interpolation scheme is proposed, in which the improved particle swarm optimization is applied to support vector machine parameters optimization. Training samples are constructed by the pixels around the pixel to be interpolated. Then the support vector machine with optimal parameters is trained using training samples. After the training, we can get the interpolation model, which can be employed to estimate the unknown pixel. Experimental result show that the interpolated images get improvement PNSR compared with traditional interpolation methods, which is agrees with the subjective quality.

  12. A rational function based scheme for solving advection equation

    International Nuclear Information System (INIS)

    Xiao, Feng; Yabe, Takashi.

    1995-07-01

    A numerical scheme for solving advection equations is presented. The scheme is derived from a rational interpolation function. Some properties of the scheme with respect to convex-concave preserving and monotone preserving are discussed. We find that the scheme is attractive in surpressinging overshoots and undershoots even in the vicinities of discontinuity. The scheme can also be easily swicthed as the CIP (Cubic interpolated Pseudo-Particle) method to get a third-order accuracy in smooth region. Numbers of numerical tests are carried out to show the non-oscillatory and less diffusive nature of the scheme. (author)

  13. Classification of types of stuttering symptoms based on brain activity.

    Directory of Open Access Journals (Sweden)

    Jing Jiang

    Full Text Available Among the non-fluencies seen in speech, some are more typical (MT of stuttering speakers, whereas others are less typical (LT and are common to both stuttering and fluent speakers. No neuroimaging work has evaluated the neural basis for grouping these symptom types. Another long-debated issue is which type (LT, MT whole-word repetitions (WWR should be placed in. In this study, a sentence completion task was performed by twenty stuttering patients who were scanned using an event-related design. This task elicited stuttering in these patients. Each stuttered trial from each patient was sorted into the MT or LT types with WWR put aside. Pattern classification was employed to train a patient-specific single trial model to automatically classify each trial as MT or LT using the corresponding fMRI data. This model was then validated by using test data that were independent of the training data. In a subsequent analysis, the classification model, just established, was used to determine which type the WWR should be placed in. The results showed that the LT and the MT could be separated with high accuracy based on their brain activity. The brain regions that made most contribution to the separation of the types were: the left inferior frontal cortex and bilateral precuneus, both of which showed higher activity in the MT than in the LT; and the left putamen and right cerebellum which showed the opposite activity pattern. The results also showed that the brain activity for WWR was more similar to that of the LT and fluent speech than to that of the MT. These findings provide a neurological basis for separating the MT and the LT types, and support the widely-used MT/LT symptom grouping scheme. In addition, WWR play a similar role as the LT, and thus should be placed in the LT type.

  14. Classification of Types of Stuttering Symptoms Based on Brain Activity

    Science.gov (United States)

    Jiang, Jing; Lu, Chunming; Peng, Danling; Zhu, Chaozhe; Howell, Peter

    2012-01-01

    Among the non-fluencies seen in speech, some are more typical (MT) of stuttering speakers, whereas others are less typical (LT) and are common to both stuttering and fluent speakers. No neuroimaging work has evaluated the neural basis for grouping these symptom types. Another long-debated issue is which type (LT, MT) whole-word repetitions (WWR) should be placed in. In this study, a sentence completion task was performed by twenty stuttering patients who were scanned using an event-related design. This task elicited stuttering in these patients. Each stuttered trial from each patient was sorted into the MT or LT types with WWR put aside. Pattern classification was employed to train a patient-specific single trial model to automatically classify each trial as MT or LT using the corresponding fMRI data. This model was then validated by using test data that were independent of the training data. In a subsequent analysis, the classification model, just established, was used to determine which type the WWR should be placed in. The results showed that the LT and the MT could be separated with high accuracy based on their brain activity. The brain regions that made most contribution to the separation of the types were: the left inferior frontal cortex and bilateral precuneus, both of which showed higher activity in the MT than in the LT; and the left putamen and right cerebellum which showed the opposite activity pattern. The results also showed that the brain activity for WWR was more similar to that of the LT and fluent speech than to that of the MT. These findings provide a neurological basis for separating the MT and the LT types, and support the widely-used MT/LT symptom grouping scheme. In addition, WWR play a similar role as the LT, and thus should be placed in the LT type. PMID:22761887

  15. Use of Ecohydraulic-Based Mesohabitat Classification and Fish Species Traits for Stream Restoration Design

    Directory of Open Access Journals (Sweden)

    John S. Schwartz

    2016-11-01

    Full Text Available Stream restoration practice typically relies on a geomorphological design approach in which the integration of ecological criteria is limited and generally qualitative, although the most commonly stated project objective is to restore biological integrity by enhancing habitat and water quality. Restoration has achieved mixed results in terms of ecological successes and it is evident that improved methodologies for assessment and design are needed. A design approach is suggested for mesohabitat restoration based on a review and integration of fundamental processes associated with: (1 lotic ecological concepts; (2 applied geomorphic processes for mesohabitat self-maintenance; (3 multidimensional hydraulics and habitat suitability modeling; (4 species functional traits correlated with fish mesohabitat use; and (5 multi-stage ecohydraulics-based mesohabitat classification. Classification of mesohabitat units demonstrated in this article were based on fish preferences specifically linked to functional trait strategies (i.e., feeding resting, evasion, spawning, and flow refugia, recognizing that habitat preferences shift by season and flow stage. A multi-stage classification scheme developed under this premise provides the basic “building blocks” for ecological design criteria for stream restoration. The scheme was developed for Midwest US prairie streams, but the conceptual framework for mesohabitat classification and functional traits analysis can be applied to other ecoregions.

  16. Integrating Globality and Locality for Robust Representation Based Classification

    Directory of Open Access Journals (Sweden)

    Zheng Zhang

    2014-01-01

    Full Text Available The representation based classification method (RBCM has shown huge potential for face recognition since it first emerged. Linear regression classification (LRC method and collaborative representation classification (CRC method are two well-known RBCMs. LRC and CRC exploit training samples of each class and all the training samples to represent the testing sample, respectively, and subsequently conduct classification on the basis of the representation residual. LRC method can be viewed as a “locality representation” method because it just uses the training samples of each class to represent the testing sample and it cannot embody the effectiveness of the “globality representation.” On the contrary, it seems that CRC method cannot own the benefit of locality of the general RBCM. Thus we propose to integrate CRC and LRC to perform more robust representation based classification. The experimental results on benchmark face databases substantially demonstrate that the proposed method achieves high classification accuracy.

  17. Novel Schemes for Measurement-Based Quantum Computation

    International Nuclear Information System (INIS)

    Gross, D.; Eisert, J.

    2007-01-01

    We establish a framework which allows one to construct novel schemes for measurement-based quantum computation. The technique develops tools from many-body physics--based on finitely correlated or projected entangled pair states--to go beyond the cluster-state based one-way computer. We identify resource states radically different from the cluster state, in that they exhibit nonvanishing correlations, can be prepared using nonmaximally entangling gates, or have very different local entanglement properties. In the computational models, randomness is compensated in a different manner. It is shown that there exist resource states which are locally arbitrarily close to a pure state. We comment on the possibility of tailoring computational models to specific physical systems

  18. Novel schemes for measurement-based quantum computation.

    Science.gov (United States)

    Gross, D; Eisert, J

    2007-06-01

    We establish a framework which allows one to construct novel schemes for measurement-based quantum computation. The technique develops tools from many-body physics-based on finitely correlated or projected entangled pair states-to go beyond the cluster-state based one-way computer. We identify resource states radically different from the cluster state, in that they exhibit nonvanishing correlations, can be prepared using nonmaximally entangling gates, or have very different local entanglement properties. In the computational models, randomness is compensated in a different manner. It is shown that there exist resource states which are locally arbitrarily close to a pure state. We comment on the possibility of tailoring computational models to specific physical systems.

  19. Generating unstable resonances for extraction schemes based on transverse splitting

    Directory of Open Access Journals (Sweden)

    M. Giovannozzi

    2009-02-01

    Full Text Available A few years ago, a novel multiturn extraction scheme was proposed, based on particle trapping inside stable resonances. Numerical simulations and experimental tests have confirmed the feasibility of such a scheme for low order resonances. While the third-order resonance is generically unstable and those higher than fourth order are generically stable, the fourth-order resonance can be either stable or unstable depending on the specifics of the system under consideration. By means of the normal form, a general approach to control the stability of the fourth-order resonance has been derived. This approach is based on the control of the amplitude detuning and the general form for a lattice with an arbitrary number of sextupole and octupole families is derived in this paper. Numerical simulations have confirmed the analytical results and have shown that, when crossing the unstable fourth-order resonance, the region around the center of the phase space is depleted and particles are trapped in only the four stable islands. A four-turn extraction could be designed using this technique.

  20. Generating Unstable Resonances for Extraction Schemes Based on Transverse Splitting

    CERN Document Server

    Giovannozzi, M; Turchetti, G

    2009-01-01

    A few years ago, a novel multi-turn extraction scheme was proposed, based on particle trapping inside stable resonances. Numerical simulations and experimental tests have confirmed the feasibility of such a scheme for low order resonances. While the third-order resonance is generically unstable and those higher than fourth-order are generically stable, the fourth-order resonance can be either stable or unstable depending on the specifics of the system under consideration. By means of the Normal Form a general approach to control the stability of the fourth-order resonance has been derived. This approach is based on the control of the amplitude detuning and the general form for a lattice with an arbitrary number of sextupole and octupole families is derived in this paper. Numerical simulations have confirmed the analytical results and have shown that, when crossing the unstable fourth-order resonance, the region around the centre of the phase space is depleted and particles are trapped in only the four stable ...

  1. 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...

  2. Radar-Derived Quantitative Precipitation Estimation Based on Precipitation Classification

    Directory of Open Access Journals (Sweden)

    Lili Yang

    2016-01-01

    Full Text Available A method for improving radar-derived quantitative precipitation estimation is proposed. Tropical vertical profiles of reflectivity (VPRs are first determined from multiple VPRs. Upon identifying a tropical VPR, the event can be further classified as either tropical-stratiform or tropical-convective rainfall by a fuzzy logic (FL algorithm. Based on the precipitation-type fields, the reflectivity values are converted into rainfall rate using a Z-R relationship. In order to evaluate the performance of this rainfall classification scheme, three experiments were conducted using three months of data and two study cases. In Experiment I, the Weather Surveillance Radar-1988 Doppler (WSR-88D default Z-R relationship was applied. In Experiment II, the precipitation regime was separated into convective and stratiform rainfall using the FL algorithm, and corresponding Z-R relationships were used. In Experiment III, the precipitation regime was separated into convective, stratiform, and tropical rainfall, and the corresponding Z-R relationships were applied. The results show that the rainfall rates obtained from all three experiments match closely with the gauge observations, although Experiment II could solve the underestimation, when compared to Experiment I. Experiment III significantly reduced this underestimation and generated the most accurate radar estimates of rain rate among the three experiments.

  3. A novel transferable individual tree crown delineation model based on Fishing Net Dragging and boundary classification

    Science.gov (United States)

    Liu, Tao; Im, Jungho; Quackenbush, Lindi J.

    2015-12-01

    This study provides a novel approach to individual tree crown delineation (ITCD) using airborne Light Detection and Ranging (LiDAR) data in dense natural forests using two main steps: crown boundary refinement based on a proposed Fishing Net Dragging (FiND) method, and segment merging based on boundary classification. FiND starts with approximate tree crown boundaries derived using a traditional watershed method with Gaussian filtering and refines these boundaries using an algorithm that mimics how a fisherman drags a fishing net. Random forest machine learning is then used to classify boundary segments into two classes: boundaries between trees and boundaries between branches that belong to a single tree. Three groups of LiDAR-derived features-two from the pseudo waveform generated along with crown boundaries and one from a canopy height model (CHM)-were used in the classification. The proposed ITCD approach was tested using LiDAR data collected over a mountainous region in the Adirondack Park, NY, USA. Overall accuracy of boundary classification was 82.4%. Features derived from the CHM were generally more important in the classification than the features extracted from the pseudo waveform. A comprehensive accuracy assessment scheme for ITCD was also introduced by considering both area of crown overlap and crown centroids. Accuracy assessment using this new scheme shows the proposed ITCD achieved 74% and 78% as overall accuracy, respectively, for deciduous and mixed forest.

  4. A Lattice-Based Identity-Based Proxy Blind Signature Scheme in the Standard Model

    Directory of Open Access Journals (Sweden)

    Lili Zhang

    2014-01-01

    Full Text Available A proxy blind signature scheme is a special form of blind signature which allowed a designated person called proxy signer to sign on behalf of original signers without knowing the content of the message. It combines the advantages of proxy signature and blind signature. Up to date, most proxy blind signature schemes rely on hard number theory problems, discrete logarithm, and bilinear pairings. Unfortunately, the above underlying number theory problems will be solvable in the postquantum era. Lattice-based cryptography is enjoying great interest these days, due to implementation simplicity and provable security reductions. Moreover, lattice-based cryptography is believed to be hard even for quantum computers. In this paper, we present a new identity-based proxy blind signature scheme from lattices without random oracles. The new scheme is proven to be strongly unforgeable under the standard hardness assumption of the short integer solution problem (SIS and the inhomogeneous small integer solution problem (ISIS. Furthermore, the secret key size and the signature length of our scheme are invariant and much shorter than those of the previous lattice-based proxy blind signature schemes. To the best of our knowledge, our construction is the first short lattice-based identity-based proxy blind signature scheme in the standard model.

  5. Quantum Ensemble Classification: A Sampling-Based Learning Control Approach.

    Science.gov (United States)

    Chen, Chunlin; Dong, Daoyi; Qi, Bo; Petersen, Ian R; Rabitz, Herschel

    2017-06-01

    Quantum ensemble classification (QEC) has significant applications in discrimination of atoms (or molecules), separation of isotopes, and quantum information extraction. However, quantum mechanics forbids deterministic discrimination among nonorthogonal states. The classification of inhomogeneous quantum ensembles is very challenging, since there exist variations in the parameters characterizing the members within different classes. In this paper, we recast QEC as a supervised quantum learning problem. A systematic classification methodology is presented by using a sampling-based learning control (SLC) approach for quantum discrimination. The classification task is accomplished via simultaneously steering members belonging to different classes to their corresponding target states (e.g., mutually orthogonal states). First, a new discrimination method is proposed for two similar quantum systems. Then, an SLC method is presented for QEC. Numerical results demonstrate the effectiveness of the proposed approach for the binary classification of two-level quantum ensembles and the multiclass classification of multilevel quantum ensembles.

  6. A group signature scheme based on quantum teleportation

    International Nuclear Information System (INIS)

    Wen Xiaojun; Tian Yuan; Ji Liping; Niu Xiamu

    2010-01-01

    In this paper, we present a group signature scheme using quantum teleportation. Different from classical group signature and current quantum signature schemes, which could only deliver either group signature or unconditional security, our scheme guarantees both by adopting quantum key preparation, quantum encryption algorithm and quantum teleportation. Security analysis proved that our scheme has the characteristics of group signature, non-counterfeit, non-disavowal, blindness and traceability. Our quantum group signature scheme has a foreseeable application in the e-payment system, e-government, e-business, etc.

  7. A group signature scheme based on quantum teleportation

    Energy Technology Data Exchange (ETDEWEB)

    Wen Xiaojun; Tian Yuan; Ji Liping; Niu Xiamu, E-mail: wxjun36@gmail.co [Information Countermeasure Technique Research Institute, Harbin Institute of Technology, Harbin 150001 (China)

    2010-05-01

    In this paper, we present a group signature scheme using quantum teleportation. Different from classical group signature and current quantum signature schemes, which could only deliver either group signature or unconditional security, our scheme guarantees both by adopting quantum key preparation, quantum encryption algorithm and quantum teleportation. Security analysis proved that our scheme has the characteristics of group signature, non-counterfeit, non-disavowal, blindness and traceability. Our quantum group signature scheme has a foreseeable application in the e-payment system, e-government, e-business, etc.

  8. Preliminary Research on Grassland Fine-classification Based on MODIS

    International Nuclear Information System (INIS)

    Hu, Z W; Zhang, S; Yu, X Y; Wang, X S

    2014-01-01

    Grassland ecosystem is important for climatic regulation, maintaining the soil and water. Research on the grassland monitoring method could provide effective reference for grassland resource investigation. In this study, we used the vegetation index method for grassland classification. There are several types of climate in China. Therefore, we need to use China's Main Climate Zone Maps and divide the study region into four climate zones. Based on grassland classification system of the first nation-wide grass resource survey in China, we established a new grassland classification system which is only suitable for this research. We used MODIS images as the basic data resources, and use the expert classifier method to perform grassland classification. Based on the 1:1,000,000 Grassland Resource Map of China, we obtained the basic distribution of all the grassland types and selected 20 samples evenly distributed in each type, then used NDVI/EVI product to summarize different spectral features of different grassland types. Finally, we introduced other classification auxiliary data, such as elevation, accumulate temperature (AT), humidity index (HI) and rainfall. China's nation-wide grassland classification map is resulted by merging the grassland in different climate zone. The overall classification accuracy is 60.4%. The result indicated that expert classifier is proper for national wide grassland classification, but the classification accuracy need to be improved

  9. Saturation Detection-Based Blocking Scheme for Transformer Differential Protection

    Directory of Open Access Journals (Sweden)

    Byung Eun Lee

    2014-07-01

    Full Text Available This paper describes a current differential relay for transformer protection that operates in conjunction with a core saturation detection-based blocking algorithm. The differential current for the magnetic inrush or over-excitation has a point of inflection at the start and end of each saturation period of the transformer core. At these instants, discontinuities arise in the first-difference function of the differential current. The second- and third-difference functions convert the points of inflection into pulses, the magnitudes of which are large enough to detect core saturation. The blocking signal is activated if the third-difference of the differential current is larger than the threshold and is maintained for one cycle. In addition, a method to discriminate between transformer saturation and current transformer (CT saturation is included. The performance of the proposed blocking scheme was compared with that of a conventional harmonic blocking method. The test results indicate that the proposed scheme successfully discriminates internal faults even with CT saturation from the magnetic inrush, over-excitation, and external faults with CT saturation, and can significantly reduce the operating time delay of the relay.

  10. Energy Aware Cluster Based Routing Scheme For Wireless Sensor Network

    Directory of Open Access Journals (Sweden)

    Roy Sohini

    2015-09-01

    Full Text Available Wireless Sensor Network (WSN has emerged as an important supplement to the modern wireless communication systems due to its wide range of applications. The recent researches are facing the various challenges of the sensor network more gracefully. However, energy efficiency has still remained a matter of concern for the researches. Meeting the countless security needs, timely data delivery and taking a quick action, efficient route selection and multi-path routing etc. can only be achieved at the cost of energy. Hierarchical routing is more useful in this regard. The proposed algorithm Energy Aware Cluster Based Routing Scheme (EACBRS aims at conserving energy with the help of hierarchical routing by calculating the optimum number of cluster heads for the network, selecting energy-efficient route to the sink and by offering congestion control. Simulation results prove that EACBRS performs better than existing hierarchical routing algorithms like Distributed Energy-Efficient Clustering (DEEC algorithm for heterogeneous wireless sensor networks and Energy Efficient Heterogeneous Clustered scheme for Wireless Sensor Network (EEHC.

  11. CLAS: A Novel Communications Latency Based Authentication Scheme

    Directory of Open Access Journals (Sweden)

    Zuochao Dou

    2017-01-01

    Full Text Available We design and implement a novel communications latency based authentication scheme, dubbed CLAS, that strengthens the security of state-of-the-art web authentication approaches by leveraging the round trip network communications latency (RTL between clients and authenticators. In addition to the traditional credentials, CLAS profiles RTL values of clients and uses them to defend against password compromise. The key challenges are (i to prevent RTL manipulation, (ii to alleviate network instabilities, and (iii to address mobile clients. CLAS addresses the first challenge by introducing a novel network architecture, which makes it extremely difficult for attackers to simulate legitimate RTL values. The second challenge is addressed by outlier removal and multiple temporal profiling, while the last challenge is addressed by augmenting CLAS with out-of-band-channels or other authentication schemes. CLAS restricts login to profiled locations while demanding additional information for nonprofiled ones, which highly reduces the attack surface even when the legitimate credentials are compromised. Additionally, unlike many state-of-the-art authentication mechanisms, CLAS is resilient to phishing, pharming, man-in-the-middle, and social engineering attacks. Furthermore, CLAS is transparent to users and incurs negligible overhead. The experimental results show that CLAS can achieve very low false positive and false negative rates.

  12. A proposed data base system for detection, classification and ...

    African Journals Online (AJOL)

    A proposed data base system for detection, classification and location of fault on electricity company of Ghana electrical distribution system. Isaac Owusu-Nyarko, Mensah-Ananoo Eugine. Abstract. No Abstract. Keywords: database, classification of fault, power, distribution system, SCADA, ECG. Full Text: EMAIL FULL TEXT ...

  13. AN OBJECT-BASED METHOD FOR CHINESE LANDFORM TYPES CLASSIFICATION

    Directory of Open Access Journals (Sweden)

    H. Ding

    2016-06-01

    Full Text Available Landform classification is a necessary task for various fields of landscape and regional planning, for example for landscape evaluation, erosion studies, hazard prediction, et al. This study proposes an improved object-based classification for Chinese landform types using the factor importance analysis of random forest and the gray-level co-occurrence matrix (GLCM. In this research, based on 1km DEM of China, the combination of the terrain factors extracted from DEM are selected by correlation analysis and Sheffield's entropy method. Random forest classification tree is applied to evaluate the importance of the terrain factors, which are used as multi-scale segmentation thresholds. Then the GLCM is conducted for the knowledge base of classification. The classification result was checked by using the 1:4,000,000 Chinese Geomorphological Map as reference. And the overall classification accuracy of the proposed method is 5.7% higher than ISODATA unsupervised classification, and 15.7% higher than the traditional object-based classification method.

  14. The nature of pseudo-twinning modes on the basis of a twin classification scheme

    International Nuclear Information System (INIS)

    Singh, Jung B.; Sundararaman, M.; Krishnan, M.

    2011-01-01

    Pseudo-twins can form in ordered structures under high stress conditions. These twins are defined by lattice sites that are at twin positions but are incorrectly occupied by different species of atoms. The present note discusses if it is possible to further classify pseudo-twins into different modes based on the nature of associated twinning elements.

  15. Fuzzy-Wavelet Based Double Line Transmission System Protection Scheme in the Presence of SVC

    Science.gov (United States)

    Goli, Ravikumar; Shaik, Abdul Gafoor; Tulasi Ram, Sankara S.

    2015-06-01

    Increasing the power transfer capability and efficient utilization of available transmission lines, improving the power system controllability and stability, power oscillation damping and voltage compensation have made strides and created Flexible AC Transmission (FACTS) devices in recent decades. Shunt FACTS devices can have adverse effects on distance protection both in steady state and transient periods. Severe under reaching is the most important problem of relay which is caused by current injection at the point of connection to the system. Current absorption of compensator leads to overreach of relay. This work presents an efficient method based on wavelet transforms, fault detection, classification and location using Fuzzy logic technique which is almost independent of fault impedance, fault distance and fault inception angle. The proposed protection scheme is found to be fast, reliable and accurate for various types of faults on transmission lines with and without Static Var compensator at different locations and with various incidence angles.

  16. Iris image recognition wavelet filter-banks based iris feature extraction schemes

    CERN Document Server

    Rahulkar, Amol D

    2014-01-01

    This book provides the new results in wavelet filter banks based feature extraction, and the classifier in the field of iris image recognition. It provides the broad treatment on the design of separable, non-separable wavelets filter banks, and the classifier. The design techniques presented in the book are applied on iris image analysis for person authentication. This book also brings together the three strands of research (wavelets, iris image analysis, and classifier). It compares the performance of the presented techniques with state-of-the-art available schemes. This book contains the compilation of basic material on the design of wavelets that avoids reading many different books. Therefore, it provide an easier path for the new-comers, researchers to master the contents. In addition, the designed filter banks and classifier can also be effectively used than existing filter-banks in many signal processing applications like pattern classification, data-compression, watermarking, denoising etc.  that will...

  17. Cryptanalysis and Improvement of a Biometric-Based Multi-Server Authentication and Key Agreement Scheme.

    Directory of Open Access Journals (Sweden)

    Chengqi Wang

    Full Text Available With the security requirements of networks, biometrics authenticated schemes which are applied in the multi-server environment come to be more crucial and widely deployed. In this paper, we propose a novel biometric-based multi-server authentication and key agreement scheme which is based on the cryptanalysis of Mishra et al.'s scheme. The informal and formal security analysis of our scheme are given, which demonstrate that our scheme satisfies the desirable security requirements. The presented scheme provides a variety of significant functionalities, in which some features are not considered in the most of existing authentication schemes, such as, user revocation or re-registration and biometric information protection. Compared with several related schemes, our scheme has more secure properties and lower computation cost. It is obviously more appropriate for practical applications in the remote distributed networks.

  18. Cryptanalysis and Improvement of a Biometric-Based Multi-Server Authentication and Key Agreement Scheme

    Science.gov (United States)

    Wang, Chengqi; Zhang, Xiao; Zheng, Zhiming

    2016-01-01

    With the security requirements of networks, biometrics authenticated schemes which are applied in the multi-server environment come to be more crucial and widely deployed. In this paper, we propose a novel biometric-based multi-server authentication and key agreement scheme which is based on the cryptanalysis of Mishra et al.’s scheme. The informal and formal security analysis of our scheme are given, which demonstrate that our scheme satisfies the desirable security requirements. The presented scheme provides a variety of significant functionalities, in which some features are not considered in the most of existing authentication schemes, such as, user revocation or re-registration and biometric information protection. Compared with several related schemes, our scheme has more secure properties and lower computation cost. It is obviously more appropriate for practical applications in the remote distributed networks. PMID:26866606

  19. A secure smart-card based authentication and key agreement scheme for telecare medicine information systems.

    Science.gov (United States)

    Lee, Tian-Fu; Liu, Chuan-Ming

    2013-06-01

    A smart-card based authentication scheme for telecare medicine information systems enables patients, doctors, nurses, health visitors and the medicine information systems to establish a secure communication platform through public networks. Zhu recently presented an improved authentication scheme in order to solve the weakness of the authentication scheme of Wei et al., where the off-line password guessing attacks cannot be resisted. This investigation indicates that the improved scheme of Zhu has some faults such that the authentication scheme cannot execute correctly and is vulnerable to the attack of parallel sessions. Additionally, an enhanced authentication scheme based on the scheme of Zhu is proposed. The enhanced scheme not only avoids the weakness in the original scheme, but also provides users' anonymity and authenticated key agreements for secure data communications.

  20. Cryptanalysis and Improvement of a Biometric-Based Multi-Server Authentication and Key Agreement Scheme.

    Science.gov (United States)

    Wang, Chengqi; Zhang, Xiao; Zheng, Zhiming

    2016-01-01

    With the security requirements of networks, biometrics authenticated schemes which are applied in the multi-server environment come to be more crucial and widely deployed. In this paper, we propose a novel biometric-based multi-server authentication and key agreement scheme which is based on the cryptanalysis of Mishra et al.'s scheme. The informal and formal security analysis of our scheme are given, which demonstrate that our scheme satisfies the desirable security requirements. The presented scheme provides a variety of significant functionalities, in which some features are not considered in the most of existing authentication schemes, such as, user revocation or re-registration and biometric information protection. Compared with several related schemes, our scheme has more secure properties and lower computation cost. It is obviously more appropriate for practical applications in the remote distributed networks.

  1. MIMO transmit scheme based on morphological perceptron with competitive learning.

    Science.gov (United States)

    Valente, Raul Ambrozio; Abrão, Taufik

    2016-08-01

    This paper proposes a new multi-input multi-output (MIMO) transmit scheme aided by artificial neural network (ANN). The morphological perceptron with competitive learning (MP/CL) concept is deployed as a decision rule in the MIMO detection stage. The proposed MIMO transmission scheme is able to achieve double spectral efficiency; hence, in each time-slot the receiver decodes two symbols at a time instead one as Alamouti scheme. Other advantage of the proposed transmit scheme with MP/CL-aided detector is its polynomial complexity according to modulation order, while it becomes linear when the data stream length is greater than modulation order. The performance of the proposed scheme is compared to the traditional MIMO schemes, namely Alamouti scheme and maximum-likelihood MIMO (ML-MIMO) detector. Also, the proposed scheme is evaluated in a scenario with variable channel information along the frame. Numerical results have shown that the diversity gain under space-time coding Alamouti scheme is partially lost, which slightly reduces the bit-error rate (BER) performance of the proposed MP/CL-NN MIMO scheme. Copyright © 2016 Elsevier Ltd. All rights reserved.

  2. Establishment on the classification scheme for the Evaluation System of the Decommissioning Information and Data

    International Nuclear Information System (INIS)

    Park, S. K.; Ji, Y. H.; Chung, U. S.

    2010-01-01

    According to the requirement, the items for the evaluation system were distinguished with the understanding of the code and it's value, the relation of the technology and it's problems, the relation with the systematical structure of the DECOMMIS-I and its' advantages and disadvantages. The detailed data model (the connection with entities) was structured as of the Information and data on the evaluation items. The ERD(Entity Relationship Diagram) on the characterization was set up. The conceptual modeling (the prototyping) which be on the base of these all result was established

  3. Interference mitigation enhancement of switched-based scheme in over-loaded femtocells

    KAUST Repository

    Gaaloul, Fakhreddine; Radaydeh, Redha Mahmoud Mesleh; Alouini, Mohamed-Slim

    2012-01-01

    -based scheme by minimum interference channel selection or adopt different interference thresholds on available channels, while aiming to reduce the channels examination load. The performance of the proposed schemes is quantified and then compared with those

  4. A Machine Learning Based Intrusion Impact Analysis Scheme for Clouds

    Directory of Open Access Journals (Sweden)

    Junaid Arshad

    2012-01-01

    Full Text Available Clouds represent a major paradigm shift, inspiring the contemporary approach to computing. They present fascinating opportunities to address dynamic user requirements with the provision of on demand expandable computing infrastructures. However, Clouds introduce novel security challenges which need to be addressed to facilitate widespread adoption. This paper is focused on one such challenge - intrusion impact analysis. In particular, we highlight the significance of intrusion impact analysis for the overall security of Clouds. Additionally, we present a machine learning based scheme to address this challenge in accordance with the specific requirements of Clouds for intrusion impact analysis. We also present rigorous evaluation performed to assess the effectiveness and feasibility of the proposed method to address this challenge for Clouds. The evaluation results demonstrate high degree of effectiveness to correctly determine the impact of an intrusion along with significant reduction with respect to the intrusion response time.

  5. From plastic to gold: a unified classification scheme for reference standards in medical image processing

    Science.gov (United States)

    Lehmann, Thomas M.

    2002-05-01

    Reliable evaluation of medical image processing is of major importance for routine applications. Nonetheless, evaluation is often omitted or methodically defective when novel approaches or algorithms are introduced. Adopted from medical diagnosis, we define the following criteria to classify reference standards: 1. Reliance, if the generation or capturing of test images for evaluation follows an exactly determined and reproducible protocol. 2. Equivalence, if the image material or relationships considered within an algorithmic reference standard equal real-life data with respect to structure, noise, or other parameters of importance. 3. Independence, if any reference standard relies on a different procedure than that to be evaluated, or on other images or image modalities than that used routinely. This criterion bans the simultaneous use of one image for both, training and test phase. 4. Relevance, if the algorithm to be evaluated is self-reproducible. If random parameters or optimization strategies are applied, reliability of the algorithm must be shown before the reference standard is applied for evaluation. 5. Significance, if the number of reference standard images that are used for evaluation is sufficient large to enable statistically founded analysis. We demand that a true gold standard must satisfy the Criteria 1 to 3. Any standard only satisfying two criteria, i.e., Criterion 1 and Criterion 2 or Criterion 1 and Criterion 3, is referred to as silver standard. Other standards are termed to be from plastic. Before exhaustive evaluation based on gold or silver standards is performed, its relevance must be shown (Criterion 4) and sufficient tests must be carried out to found statistical analysis (Criterion 5). In this paper, examples are given for each class of reference standards.

  6. A robust anonymous biometric-based remote user authentication scheme using smart cards

    Directory of Open Access Journals (Sweden)

    Ashok Kumar Das

    2015-04-01

    Full Text Available Several biometric-based remote user authentication schemes using smart cards have been proposed in the literature in order to improve the security weaknesses in user authentication system. In 2012, An proposed an enhanced biometric-based remote user authentication scheme using smart cards. It was claimed that the proposed scheme is secure against the user impersonation attack, the server masquerading attack, the password guessing attack, and the insider attack and provides mutual authentication between the user and the server. In this paper, we first analyze the security of An’s scheme and we show that this scheme has three serious security flaws in the design of the scheme: (i flaw in user’s biometric verification during the login phase, (ii flaw in user’s password verification during the login and authentication phases, and (iii flaw in user’s password change locally at any time by the user. Due to these security flaws, An’s scheme cannot support mutual authentication between the user and the server. Further, we show that An’s scheme cannot prevent insider attack. In order to remedy the security weaknesses found in An’s scheme, we propose a new robust and secure anonymous biometric-based remote user authentication scheme using smart cards. Through the informal and formal security analysis, we show that our scheme is secure against all possible known attacks including the attacks found in An’s scheme. The simulation results of our scheme using the widely-accepted AVISPA (Automated Validation of Internet Security Protocols and Applications tool ensure that our scheme is secure against passive and active attacks. In addition, our scheme is also comparable in terms of the communication and computational overheads with An’s scheme and other related existing schemes. As a result, our scheme is more appropriate for practical applications compared to other approaches.

  7. Text document classification based on mixture models

    Czech Academy of Sciences Publication Activity Database

    Novovičová, Jana; Malík, Antonín

    2004-01-01

    Roč. 40, č. 3 (2004), s. 293-304 ISSN 0023-5954 R&D Projects: GA AV ČR IAA2075302; GA ČR GA102/03/0049; GA AV ČR KSK1019101 Institutional research plan: CEZ:AV0Z1075907 Keywords : text classification * text categorization * multinomial mixture model Subject RIV: BB - Applied Statistics, Operational Research Impact factor: 0.224, year: 2004

  8. Classification

    Science.gov (United States)

    Clary, Renee; Wandersee, James

    2013-01-01

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

  9. A Region-Based GeneSIS Segmentation Algorithm for the Classification of Remotely Sensed Images

    Directory of Open Access Journals (Sweden)

    Stelios K. Mylonas

    2015-03-01

    Full Text Available This paper proposes an object-based segmentation/classification scheme for remotely sensed images, based on a novel variant of the recently proposed Genetic Sequential Image Segmentation (GeneSIS algorithm. GeneSIS segments the image in an iterative manner, whereby at each iteration a single object is extracted via a genetic-based object extraction algorithm. Contrary to the previous pixel-based GeneSIS where the candidate objects to be extracted were evaluated through the fuzzy content of their included pixels, in the newly developed region-based GeneSIS algorithm, a watershed-driven fine segmentation map is initially obtained from the original image, which serves as the basis for the forthcoming GeneSIS segmentation. Furthermore, in order to enhance the spatial search capabilities, we introduce a more descriptive encoding scheme in the object extraction algorithm, where the structural search modules are represented by polygonal shapes. Our objectives in the new framework are posed as follows: enhance the flexibility of the algorithm in extracting more flexible object shapes, assure high level classification accuracies, and reduce the execution time of the segmentation, while at the same time preserving all the inherent attributes of the GeneSIS approach. Finally, exploiting the inherent attribute of GeneSIS to produce multiple segmentations, we also propose two segmentation fusion schemes that operate on the ensemble of segmentations generated by GeneSIS. Our approaches are tested on an urban and two agricultural images. The results show that region-based GeneSIS has considerably lower computational demands compared to the pixel-based one. Furthermore, the suggested methods achieve higher classification accuracies and good segmentation maps compared to a series of existing algorithms.

  10. Enhanced ID-Based Authentication Scheme Using OTP in Smart Grid AMI Environment

    Directory of Open Access Journals (Sweden)

    Sang-Soo Yeo

    2014-01-01

    Full Text Available This paper presents the vulnerabilities analyses of KL scheme which is an ID-based authentication scheme for AMI network attached SCADA in smart grid and proposes a security-enhanced authentication scheme which satisfies forward secrecy as well as security requirements introduced in KL scheme and also other existing schemes. The proposed scheme uses MDMS which is the supervising system located in an electrical company as a time-synchronizing server in order to synchronize smart devices at home and conducts authentication between smart meter and smart devices using a new secret value generated by an OTP generator every session. The proposed scheme has forward secrecy, so it increases overall security, but its communication and computation overhead reduce its performance slightly, comparing the existing schemes. Nonetheless, hardware specification and communication bandwidth of smart devices will have better conditions continuously, so the proposed scheme would be a good choice for secure AMI environment.

  11. TENSOR MODELING BASED FOR AIRBORNE LiDAR DATA CLASSIFICATION

    Directory of Open Access Journals (Sweden)

    N. Li

    2016-06-01

    Full Text Available Feature selection and description is a key factor in classification of Earth observation data. In this paper a classification method based on tensor decomposition is proposed. First, multiple features are extracted from raw LiDAR point cloud, and raster LiDAR images are derived by accumulating features or the “raw” data attributes. Then, the feature rasters of LiDAR data are stored as a tensor, and tensor decomposition is used to select component features. This tensor representation could keep the initial spatial structure and insure the consideration of the neighborhood. Based on a small number of component features a k nearest neighborhood classification is applied.

  12. Object-Based Crop Species Classification Based on the Combination of Airborne Hyperspectral Images and LiDAR Data

    Directory of Open Access Journals (Sweden)

    Xiaolong Liu

    2015-01-01

    Full Text Available Identification of crop species is an important issue in agricultural management. In recent years, many studies have explored this topic using multi-spectral and hyperspectral remote sensing data. In this study, we perform dedicated research to propose a framework for mapping crop species by combining hyperspectral and Light Detection and Ranging (LiDAR data in an object-based image analysis (OBIA paradigm. The aims of this work were the following: (i to understand the performances of different spectral dimension-reduced features from hyperspectral data and their combination with LiDAR derived height information in image segmentation; (ii to understand what classification accuracies of crop species can be achieved by combining hyperspectral and LiDAR data in an OBIA paradigm, especially in regions that have fragmented agricultural landscape and complicated crop planting structure; and (iii to understand the contributions of the crop height that is derived from LiDAR data, as well as the geometric and textural features of image objects, to the crop species’ separabilities. The study region was an irrigated agricultural area in the central Heihe river basin, which is characterized by many crop species, complicated crop planting structures, and fragmented landscape. The airborne hyperspectral data acquired by the Compact Airborne Spectrographic Imager (CASI with a 1 m spatial resolution and the Canopy Height Model (CHM data derived from the LiDAR data acquired by the airborne Leica ALS70 LiDAR system were used for this study. The image segmentation accuracies of different feature combination schemes (very high-resolution imagery (VHR, VHR/CHM, and minimum noise fractional transformed data (MNF/CHM were evaluated and analyzed. The results showed that VHR/CHM outperformed the other two combination schemes with a segmentation accuracy of 84.8%. The object-based crop species classification results of different feature integrations indicated that

  13. An efficient entire chaos-based scheme for deniable authentication

    International Nuclear Information System (INIS)

    Xiao Di; Liao Xiaofeng; Wong, K.W.

    2005-01-01

    By using a chaotic encryption-hash parallel algorithm and the semi-group property of Chebyshev chaotic map, we propose a secure and efficient scheme for the deniable authentication. The scheme is efficient, practicable and reliable, with high potential to be adopted for e-commerce

  14. An efficient entire chaos-based scheme for deniable authentication

    Energy Technology Data Exchange (ETDEWEB)

    Xiao Di [College of Computer Science and Engineering, Chongqing University, Chongqing, 400044 (China) and College of Mechanical Engineering, Chongqing University, Chongqing, 400044 (China)]. E-mail: xiaodi_cqu@hotmail.com; Liao Xiaofeng [College of Computer Science and Engineering, Chongqing University, Chongqing, 400044 (China); Wong, K.W. [Department of Computer Engineering and Information Technology, City University of Hong Kong, Hong Kong (China)

    2005-02-01

    By using a chaotic encryption-hash parallel algorithm and the semi-group property of Chebyshev chaotic map, we propose a secure and efficient scheme for the deniable authentication. The scheme is efficient, practicable and reliable, with high potential to be adopted for e-commerce.

  15. A novel chaotic encryption scheme based on arithmetic coding

    International Nuclear Information System (INIS)

    Mi Bo; Liao Xiaofeng; Chen Yong

    2008-01-01

    In this paper, under the combination of arithmetic coding and logistic map, a novel chaotic encryption scheme is presented. The plaintexts are encrypted and compressed by using an arithmetic coder whose mapping intervals are changed irregularly according to a keystream derived from chaotic map and plaintext. Performance and security of the scheme are also studied experimentally and theoretically in detail

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

    Science.gov (United States)

    Kaufung, Eva; Winkler, Stefan

    2014-05-01

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

  17. Iris Image Classification Based on Hierarchical Visual Codebook.

    Science.gov (United States)

    Zhenan Sun; Hui Zhang; Tieniu Tan; Jianyu Wang

    2014-06-01

    Iris recognition as a reliable method for personal identification has been well-studied with the objective to assign the class label of each iris image to a unique subject. In contrast, iris image classification aims to classify an iris image to an application specific category, e.g., iris liveness detection (classification of genuine and fake iris images), race classification (e.g., classification of iris images of Asian and non-Asian subjects), coarse-to-fine iris identification (classification of all iris images in the central database into multiple categories). This paper proposes a general framework for iris image classification based on texture analysis. A novel texture pattern representation method called Hierarchical Visual Codebook (HVC) is proposed to encode the texture primitives of iris images. The proposed HVC method is an integration of two existing Bag-of-Words models, namely Vocabulary Tree (VT), and Locality-constrained Linear Coding (LLC). The HVC adopts a coarse-to-fine visual coding strategy and takes advantages of both VT and LLC for accurate and sparse representation of iris texture. Extensive experimental results demonstrate that the proposed iris image classification method achieves state-of-the-art performance for iris liveness detection, race classification, and coarse-to-fine iris identification. A comprehensive fake iris image database simulating four types of iris spoof attacks is developed as the benchmark for research of iris liveness detection.

  18. Classification

    DEFF Research Database (Denmark)

    Hjørland, Birger

    2017-01-01

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

  19. Novel Quantum Secret Sharing and Controlled Communication Schemes Based on Einstein–Podolsky–Rosen Correlations

    International Nuclear Information System (INIS)

    Yuan, Li; Gui-Hua, Zeng

    2009-01-01

    Employing quantum registers, we first proposed a novel (2, 3) quantum threshold scheme based on Einstein–Podolsky–Rosen (EPR) correlations in this letter. Motivated by the present threshold scheme, we also propose a controlled communication scheme to transmit the secret message with a controller. In the communication protocol, the encoded quantum message carried by particles sequence, is transmitted by legitimate communicators

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

    Science.gov (United States)

    Friedel, Michael; Buscema, Massimo

    2016-04-01

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

  1. Scalable cavity-QED-based scheme of generating entanglement of atoms and of cavity fields

    OpenAIRE

    Lee, Jaehak; Park, Jiyong; Lee, Sang Min; Lee, Hai-Woong; Khosa, Ashfaq H.

    2008-01-01

    We propose a cavity-QED-based scheme of generating entanglement between atoms. The scheme is scalable to an arbitrary number of atoms, and can be used to generate a variety of multipartite entangled states such as the Greenberger-Horne-Zeilinger, W, and cluster states. Furthermore, with a role switching of atoms with photons, the scheme can be used to generate entanglement between cavity fields. We also introduce a scheme that can generate an arbitrary multipartite field graph state.

  2. Ebolavirus Classification Based on Natural Vectors

    Science.gov (United States)

    Zheng, Hui; Yin, Changchuan; Hoang, Tung; He, Rong Lucy; Yang, Jie

    2015-01-01

    According to the WHO, ebolaviruses have resulted in 8818 human deaths in West Africa as of January 2015. To better understand the evolutionary relationship of the ebolaviruses and infer virulence from the relationship, we applied the alignment-free natural vector method to classify the newest ebolaviruses. The dataset includes three new Guinea viruses as well as 99 viruses from Sierra Leone. For the viruses of the family of Filoviridae, both genus label classification and species label classification achieve an accuracy rate of 100%. We represented the relationships among Filoviridae viruses by Unweighted Pair Group Method with Arithmetic Mean (UPGMA) phylogenetic trees and found that the filoviruses can be separated well by three genera. We performed the phylogenetic analysis on the relationship among different species of Ebolavirus by their coding-complete genomes and seven viral protein genes (glycoprotein [GP], nucleoprotein [NP], VP24, VP30, VP35, VP40, and RNA polymerase [L]). The topology of the phylogenetic tree by the viral protein VP24 shows consistency with the variations of virulence of ebolaviruses. The result suggests that VP24 be a pharmaceutical target for treating or preventing ebolaviruses. PMID:25803489

  3. Hot complaint intelligent classification based on text mining

    Directory of Open Access Journals (Sweden)

    XIA Haifeng

    2013-10-01

    Full Text Available The complaint recognizer system plays an important role in making sure the correct classification of the hot complaint,improving the service quantity of telecommunications industry.The customers’ complaint in telecommunications industry has its special particularity which should be done in limited time,which cause the error in classification of hot complaint.The paper presents a model of complaint hot intelligent classification based on text mining,which can classify the hot complaint in the correct level of the complaint navigation.The examples show that the model can be efficient to classify the text of the complaint.

  4. Radar Target Classification using Recursive Knowledge-Based Methods

    DEFF Research Database (Denmark)

    Jochumsen, Lars Wurtz

    The topic of this thesis is target classification of radar tracks from a 2D mechanically scanning coastal surveillance radar. The measurements provided by the radar are position data and therefore the classification is mainly based on kinematic data, which is deduced from the position. The target...... been terminated. Therefore, an update of the classification results must be made for each measurement of the target. The data for this work are collected throughout the PhD and are both collected from radars and other sensors such as GPS....

  5. Key-phrase based classification of public health web pages.

    Science.gov (United States)

    Dolamic, Ljiljana; Boyer, Célia

    2013-01-01

    This paper describes and evaluates the public health web pages classification model based on key phrase extraction and matching. Easily extendible both in terms of new classes as well as the new language this method proves to be a good solution for text classification faced with the total lack of training data. To evaluate the proposed solution we have used a small collection of public health related web pages created by a double blind manual classification. Our experiments have shown that by choosing the adequate threshold value the desired value for either precision or recall can be achieved.

  6. Analysis on Target Detection and Classification in LTE Based Passive Forward Scattering Radar

    Directory of Open Access Journals (Sweden)

    Raja Syamsul Azmir Raja Abdullah

    2016-09-01

    Full Text Available The passive bistatic radar (PBR system can utilize the illuminator of opportunity to enhance radar capability. By utilizing the forward scattering technique and procedure into the specific mode of PBR can provide an improvement in target detection and classification. The system is known as passive Forward Scattering Radar (FSR. The passive FSR system can exploit the peculiar advantage of the enhancement in forward scatter radar cross section (FSRCS for target detection. Thus, the aim of this paper is to show the feasibility of passive FSR for moving target detection and classification by experimental analysis and results. The signal source is coming from the latest technology of 4G Long-Term Evolution (LTE base station. A detailed explanation on the passive FSR receiver circuit, the detection scheme and the classification algorithm are given. In addition, the proposed passive FSR circuit employs the self-mixing technique at the receiver; hence the synchronization signal from the transmitter is not required. The experimental results confirm the passive FSR system’s capability for ground target detection and classification. Furthermore, this paper illustrates the first classification result in the passive FSR system. The great potential in the passive FSR system provides a new research area in passive radar that can be used for diverse remote monitoring applications.

  7. Analysis on Target Detection and Classification in LTE Based Passive Forward Scattering Radar.

    Science.gov (United States)

    Raja Abdullah, Raja Syamsul Azmir; Abdul Aziz, Noor Hafizah; Abdul Rashid, Nur Emileen; Ahmad Salah, Asem; Hashim, Fazirulhisyam

    2016-09-29

    The passive bistatic radar (PBR) system can utilize the illuminator of opportunity to enhance radar capability. By utilizing the forward scattering technique and procedure into the specific mode of PBR can provide an improvement in target detection and classification. The system is known as passive Forward Scattering Radar (FSR). The passive FSR system can exploit the peculiar advantage of the enhancement in forward scatter radar cross section (FSRCS) for target detection. Thus, the aim of this paper is to show the feasibility of passive FSR for moving target detection and classification by experimental analysis and results. The signal source is coming from the latest technology of 4G Long-Term Evolution (LTE) base station. A detailed explanation on the passive FSR receiver circuit, the detection scheme and the classification algorithm are given. In addition, the proposed passive FSR circuit employs the self-mixing technique at the receiver; hence the synchronization signal from the transmitter is not required. The experimental results confirm the passive FSR system's capability for ground target detection and classification. Furthermore, this paper illustrates the first classification result in the passive FSR system. The great potential in the passive FSR system provides a new research area in passive radar that can be used for diverse remote monitoring applications.

  8. SoFoCles: feature filtering for microarray classification based on gene ontology.

    Science.gov (United States)

    Papachristoudis, Georgios; Diplaris, Sotiris; Mitkas, Pericles A

    2010-02-01

    Marker gene selection has been an important research topic in the classification analysis of gene expression data. Current methods try to reduce the "curse of dimensionality" by using statistical intra-feature set calculations, or classifiers that are based on the given dataset. In this paper, we present SoFoCles, an interactive tool that enables semantic feature filtering in microarray classification problems with the use of external, well-defined knowledge retrieved from the Gene Ontology. The notion of semantic similarity is used to derive genes that are involved in the same biological path during the microarray experiment, by enriching a feature set that has been initially produced with legacy methods. Among its other functionalities, SoFoCles offers a large repository of semantic similarity methods that are used in order to derive feature sets and marker genes. The structure and functionality of the tool are discussed in detail, as well as its ability to improve classification accuracy. Through experimental evaluation, SoFoCles is shown to outperform other classification schemes in terms of classification accuracy in two real datasets using different semantic similarity computation approaches.

  9. An enhanced dynamic ID-based authentication scheme for telecare medical information systems

    Directory of Open Access Journals (Sweden)

    Ankita Chaturvedi

    2017-01-01

    Full Text Available The authentication schemes for telecare medical information systems (TMIS try to ensure secure and authorized access. ID-based authentication schemes address secure communication, but privacy is not properly addressed. In recent times, dynamic ID-based remote user authentication schemes for TMIS have been presented to protect user’s privacy. The dynamic ID-based authentication schemes efficiently protect the user’s privacy. Unfortunately, most of the existing dynamic ID-based authentication schemes for TMIS ignore the input verifying condition. This makes login and password change phases inefficient. Inefficiency of the password change phase may lead to denial of service attack in the case of incorrect input in the password change phase. To overcome these weaknesses, we proposed a new dynamic ID-based authentication scheme using a smart card. The proposed scheme can quickly detect incorrect inputs which makes the login and password change phase efficient. We adopt the approach with the aim to protect privacy, and efficient login and password change phases. The proposed scheme also resists off-line password guessing attack and denial of service attack. We also demonstrate the validity of the proposed scheme by utilizing the widely-accepted BAN (Burrows, Abadi, and Needham logic. In addition, our scheme is comparable in terms of the communication and computational overheads with relevant schemes for TMIS.

  10. A dynamic identity based authentication scheme using chaotic maps for telecare medicine information systems.

    Science.gov (United States)

    Wang, Zhiheng; Huo, Zhanqiang; Shi, Wenbo

    2015-01-01

    With rapid development of computer technology and wide use of mobile devices, the telecare medicine information system has become universal in the field of medical care. To protect patients' privacy and medial data's security, many authentication schemes for the telecare medicine information system have been proposed. Due to its better performance, chaotic maps have been used in the design of authentication schemes for the telecare medicine information system. However, most of them cannot provide user's anonymity. Recently, Lin proposed a dynamic identity based authentication scheme using chaotic maps for the telecare medicine information system and claimed that their scheme was secure against existential active attacks. In this paper, we will demonstrate that their scheme cannot provide user anonymity and is vulnerable to the impersonation attack. Further, we propose an improved scheme to fix security flaws in Lin's scheme and demonstrate the proposed scheme could withstand various attacks.

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

    International Nuclear Information System (INIS)

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

    2009-01-01

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

  12. An efficient and provable secure revocable identity-based encryption scheme.

    Directory of Open Access Journals (Sweden)

    Changji Wang

    Full Text Available Revocation functionality is necessary and crucial to identity-based cryptosystems. Revocable identity-based encryption (RIBE has attracted a lot of attention in recent years, many RIBE schemes have been proposed in the literature but shown to be either insecure or inefficient. In this paper, we propose a new scalable RIBE scheme with decryption key exposure resilience by combining Lewko and Waters' identity-based encryption scheme and complete subtree method, and prove our RIBE scheme to be semantically secure using dual system encryption methodology. Compared to existing scalable and semantically secure RIBE schemes, our proposed RIBE scheme is more efficient in term of ciphertext size, public parameters size and decryption cost at price of a little looser security reduction. To the best of our knowledge, this is the first construction of scalable and semantically secure RIBE scheme with constant size public system parameters.

  13. A Rhythm-Based Authentication Scheme for Smart Media Devices

    Directory of Open Access Journals (Sweden)

    Jae Dong Lee

    2014-01-01

    Full Text Available In recent years, ubiquitous computing has been rapidly emerged in our lives and extensive studies have been conducted in a variety of areas related to smart devices, such as tablets, smartphones, smart TVs, smart refrigerators, and smart media devices, as a measure for realizing the ubiquitous computing. In particular, smartphones have significantly evolved from the traditional feature phones. Increasingly higher-end smartphone models that can perform a range of functions are now available. Smart devices have become widely popular since they provide high efficiency and great convenience for not only private daily activities but also business endeavors. Rapid advancements have been achieved in smart device technologies to improve the end users’ convenience. Consequently, many people increasingly rely on smart devices to store their valuable and important data. With this increasing dependence, an important aspect that must be addressed is security issues. Leaking of private information or sensitive business data due to loss or theft of smart devices could result in exorbitant damage. To mitigate these security threats, basic embedded locking features are provided in smart devices. However, these locking features are vulnerable. In this paper, an original security-locking scheme using a rhythm-based locking system (RLS is proposed to overcome the existing security problems of smart devices. RLS is a user-authenticated system that addresses vulnerability issues in the existing locking features and provides secure confidentiality in addition to convenience.

  14. A rhythm-based authentication scheme for smart media devices.

    Science.gov (United States)

    Lee, Jae Dong; Jeong, Young-Sik; Park, Jong Hyuk

    2014-01-01

    In recent years, ubiquitous computing has been rapidly emerged in our lives and extensive studies have been conducted in a variety of areas related to smart devices, such as tablets, smartphones, smart TVs, smart refrigerators, and smart media devices, as a measure for realizing the ubiquitous computing. In particular, smartphones have significantly evolved from the traditional feature phones. Increasingly higher-end smartphone models that can perform a range of functions are now available. Smart devices have become widely popular since they provide high efficiency and great convenience for not only private daily activities but also business endeavors. Rapid advancements have been achieved in smart device technologies to improve the end users' convenience. Consequently, many people increasingly rely on smart devices to store their valuable and important data. With this increasing dependence, an important aspect that must be addressed is security issues. Leaking of private information or sensitive business data due to loss or theft of smart devices could result in exorbitant damage. To mitigate these security threats, basic embedded locking features are provided in smart devices. However, these locking features are vulnerable. In this paper, an original security-locking scheme using a rhythm-based locking system (RLS) is proposed to overcome the existing security problems of smart devices. RLS is a user-authenticated system that addresses vulnerability issues in the existing locking features and provides secure confidentiality in addition to convenience.

  15. Noninvasive blood pressure measurement scheme based on optical fiber sensor

    Science.gov (United States)

    Liu, Xianxuan; Yuan, Xueguang; Zhang, Yangan

    2016-10-01

    Optical fiber sensing has many advantages, such as volume small, light quality, low loss, strong in anti-jamming. Since the invention of the optical fiber sensing technology in 1977, optical fiber sensing technology has been applied in the military, national defense, aerospace, industrial, medical and other fields in recent years, and made a great contribution to parameter measurement in the environment under the limited condition .With the rapid development of computer, network system, the intelligent optical fiber sensing technology, the sensor technology, the combination of computer and communication technology , the detection, diagnosis and analysis can be automatically and efficiently completed. In this work, we proposed a noninvasive blood pressure detection and analysis scheme which uses optical fiber sensor. Optical fiber sensing system mainly includes the light source, optical fiber, optical detector, optical modulator, the signal processing module and so on. wavelength optical signals were led into the optical fiber sensor and the signals reflected by the human body surface were detected. By comparing actual testing data with the data got by traditional way to measure the blood pressure we can establish models for predicting the blood pressure and achieve noninvasive blood pressure measurement by using spectrum analysis technology. Blood pressure measurement method based on optical fiber sensing system is faster and more convenient than traditional way, and it can get accurate analysis results in a shorter period of time than before, so it can efficiently reduce the time cost and manpower cost.

  16. Novel communication scheme based on chaotic Roessler circuits

    International Nuclear Information System (INIS)

    GarcIa-Lopez, J H; Jaimes-Reategui, R; Pisarchik, A N; MurguIa-Hernandez, A; Medina-Gutierrez, C; Valdivia-Hernadez, R; Villafana-Rauda, E

    2005-01-01

    We present a novel synchronization scheme for secure communication with two chaotic unidirectionally coupled Roessler circuits. The circuits are synchronized via one of the variables, while a signal is transmitted through another variable. We show that this scheme allows more stable communications. The system dynamics is studied numerically and experimentally in a wide range of a control parameter. The possibility of secure communications with an audio signal is demonstrated

  17. Empirical Studies On Machine Learning Based Text Classification Algorithms

    OpenAIRE

    Shweta C. Dharmadhikari; Maya Ingle; Parag Kulkarni

    2011-01-01

    Automatic classification of text documents has become an important research issue now days. Properclassification of text documents requires information retrieval, machine learning and Natural languageprocessing (NLP) techniques. Our aim is to focus on important approaches to automatic textclassification based on machine learning techniques viz. supervised, unsupervised and semi supervised.In this paper we present a review of various text classification approaches under machine learningparadig...

  18. Novel Threshold Changeable Secret Sharing Schemes Based on Polynomial Interpolation.

    Science.gov (United States)

    Yuan, Lifeng; Li, Mingchu; Guo, Cheng; Choo, Kim-Kwang Raymond; Ren, Yizhi

    2016-01-01

    After any distribution of secret sharing shadows in a threshold changeable secret sharing scheme, the threshold may need to be adjusted to deal with changes in the security policy and adversary structure. For example, when employees leave the organization, it is not realistic to expect departing employees to ensure the security of their secret shadows. Therefore, in 2012, Zhang et al. proposed (t → t', n) and ({t1, t2,⋯, tN}, n) threshold changeable secret sharing schemes. However, their schemes suffer from a number of limitations such as strict limit on the threshold values, large storage space requirement for secret shadows, and significant computation for constructing and recovering polynomials. To address these limitations, we propose two improved dealer-free threshold changeable secret sharing schemes. In our schemes, we construct polynomials to update secret shadows, and use two-variable one-way function to resist collusion attacks and secure the information stored by the combiner. We then demonstrate our schemes can adjust the threshold safely.

  19. Index-based reactive power compensation scheme for voltage regulation

    Science.gov (United States)

    Dike, Damian Obioma

    2008-10-01

    Increasing demand for electrical power arising from deregulation and the restrictions posed to the construction of new transmission lines by environment, socioeconomic, and political issues had led to higher grid loading. Consequently, voltage instability has become a major concern, and reactive power support is vital to enhance transmission grid performance. Improved reactive power support to distressed grid is possible through the application of relatively unfamiliar emerging technologies of "Flexible AC Transmission Systems (FACTS)" devices and "Distributed Energy Resources (DERS)." In addition to these infrastructure issues, a lack of situational awareness by system operators can cause major power outages as evidenced by the August 14, 2003 widespread North American blackout. This and many other recent major outages have highlighted the inadequacies of existing power system indexes. In this work, a novel "Index-based reactive compensation scheme" appropriate for both on-line and off-line computation of grid status has been developed. A new voltage stability index (Ls-index) suitable for long transmission lines was developed, simulated, and compared to the existing two-machine modeled L-index. This showed the effect of long distance power wheeling amongst regional transmission organizations. The dissertation further provided models for index modulated voltage source converters (VSC) and index-based load flow analysis of both FACTS and microgrid interconnected power systems using the Newton-Raphson's load flow model incorporated with multi-FACTS devices. The developed package has been made user-friendly through the embodiment of interactive graphical user interface and implemented on the IEEE 14, 30, and 300 bus systems. The results showed reactive compensation has system wide-effect, provided readily accessible system status indicators, ensured seamless DERs interconnection through new islanding modes and enhanced VSC utilization. These outcomes may contribute

  20. SAR Imagery Simulation of Ship Based on Electromagnetic Calculations and Sea Clutter Modelling for Classification Applications

    International Nuclear Information System (INIS)

    Ji, K F; Zhao, Z; Xing, X W; Zou, H X; Zhou, S L

    2014-01-01

    Ship detection and classification with space-borne SAR has many potential applications within the maritime surveillance, fishery activity management, monitoring ship traffic, and military security. While ship detection techniques with SAR imagery are well established, ship classification is still an open issue. One of the main reasons may be ascribed to the difficulties on acquiring the required quantities of real data of vessels under different observation and environmental conditions with precise ground truth. Therefore, simulation of SAR images with high scenario flexibility and reasonable computation costs is compulsory for ship classification algorithms development. However, the simulation of SAR imagery of ship over sea surface is challenging. Though great efforts have been devoted to tackle this difficult problem, it is far from being conquered. This paper proposes a novel scheme for SAR imagery simulation of ship over sea surface. The simulation is implemented based on high frequency electromagnetic calculations methods of PO, MEC, PTD and GO. SAR imagery of sea clutter is modelled by the representative K-distribution clutter model. Then, the simulated SAR imagery of ship can be produced by inserting the simulated SAR imagery chips of ship into the SAR imagery of sea clutter. The proposed scheme has been validated with canonical and complex ship targets over a typical sea scene

  1. Entropy-based gene ranking without selection bias for the predictive classification of microarray data

    Directory of Open Access Journals (Sweden)

    Serafini Maria

    2003-11-01

    Full Text Available Abstract Background We describe the E-RFE method for gene ranking, which is useful for the identification of markers in the predictive classification of array data. The method supports a practical modeling scheme designed to avoid the construction of classification rules based on the selection of too small gene subsets (an effect known as the selection bias, in which the estimated predictive errors are too optimistic due to testing on samples already considered in the feature selection process. Results With E-RFE, we speed up the recursive feature elimination (RFE with SVM classifiers by eliminating chunks of uninteresting genes using an entropy measure of the SVM weights distribution. An optimal subset of genes is selected according to a two-strata model evaluation procedure: modeling is replicated by an external stratified-partition resampling scheme, and, within each run, an internal K-fold cross-validation is used for E-RFE ranking. Also, the optimal number of genes can be estimated according to the saturation of Zipf's law profiles. Conclusions Without a decrease of classification accuracy, E-RFE allows a speed-up factor of 100 with respect to standard RFE, while improving on alternative parametric RFE reduction strategies. Thus, a process for gene selection and error estimation is made practical, ensuring control of the selection bias, and providing additional diagnostic indicators of gene importance.

  2. An improved biometrics-based authentication scheme for telecare medical information systems.

    Science.gov (United States)

    Guo, Dianli; Wen, Qiaoyan; Li, Wenmin; Zhang, Hua; Jin, Zhengping

    2015-03-01

    Telecare medical information system (TMIS) offers healthcare delivery services and patients can acquire their desired medical services conveniently through public networks. The protection of patients' privacy and data confidentiality are significant. Very recently, Mishra et al. proposed a biometrics-based authentication scheme for telecare medical information system. Their scheme can protect user privacy and is believed to resist a range of network attacks. In this paper, we analyze Mishra et al.'s scheme and identify that their scheme is insecure to against known session key attack and impersonation attack. Thereby, we present a modified biometrics-based authentication scheme for TMIS to eliminate the aforementioned faults. Besides, we demonstrate the completeness of the proposed scheme through BAN-logic. Compared to the related schemes, our protocol can provide stronger security and it is more practical.

  3. Polarimetric SAR image classification based on discriminative dictionary learning model

    Science.gov (United States)

    Sang, Cheng Wei; Sun, Hong

    2018-03-01

    Polarimetric SAR (PolSAR) image classification is one of the important applications of PolSAR remote sensing. It is a difficult high-dimension nonlinear mapping problem, the sparse representations based on learning overcomplete dictionary have shown great potential to solve such problem. The overcomplete dictionary plays an important role in PolSAR image classification, however for PolSAR image complex scenes, features shared by different classes will weaken the discrimination of learned dictionary, so as to degrade classification performance. In this paper, we propose a novel overcomplete dictionary learning model to enhance the discrimination of dictionary. The learned overcomplete dictionary by the proposed model is more discriminative and very suitable for PolSAR classification.

  4. Semantic Document Image Classification Based on Valuable Text Pattern

    Directory of Open Access Journals (Sweden)

    Hossein Pourghassem

    2011-01-01

    Full Text Available Knowledge extraction from detected document image is a complex problem in the field of information technology. This problem becomes more intricate when we know, a negligible percentage of the detected document images are valuable. In this paper, a segmentation-based classification algorithm is used to analysis the document image. In this algorithm, using a two-stage segmentation approach, regions of the image are detected, and then classified to document and non-document (pure region regions in the hierarchical classification. In this paper, a novel valuable definition is proposed to classify document image in to valuable or invaluable categories. The proposed algorithm is evaluated on a database consisting of the document and non-document image that provide from Internet. Experimental results show the efficiency of the proposed algorithm in the semantic document image classification. The proposed algorithm provides accuracy rate of 98.8% for valuable and invaluable document image classification problem.

  5. Video based object representation and classification using multiple covariance matrices.

    Science.gov (United States)

    Zhang, Yurong; Liu, Quan

    2017-01-01

    Video based object recognition and classification has been widely studied in computer vision and image processing area. One main issue of this task is to develop an effective representation for video. This problem can generally be formulated as image set representation. In this paper, we present a new method called Multiple Covariance Discriminative Learning (MCDL) for image set representation and classification problem. The core idea of MCDL is to represent an image set using multiple covariance matrices with each covariance matrix representing one cluster of images. Firstly, we use the Nonnegative Matrix Factorization (NMF) method to do image clustering within each image set, and then adopt Covariance Discriminative Learning on each cluster (subset) of images. At last, we adopt KLDA and nearest neighborhood classification method for image set classification. Promising experimental results on several datasets show the effectiveness of our MCDL method.

  6. Pathological Bases for a Robust Application of Cancer Molecular Classification

    Directory of Open Access Journals (Sweden)

    Salvador J. Diaz-Cano

    2015-04-01

    Full Text Available Any robust classification system depends on its purpose and must refer to accepted standards, its strength relying on predictive values and a careful consideration of known factors that can affect its reliability. In this context, a molecular classification of human cancer must refer to the current gold standard (histological classification and try to improve it with key prognosticators for metastatic potential, staging and grading. Although organ-specific examples have been published based on proteomics, transcriptomics and genomics evaluations, the most popular approach uses gene expression analysis as a direct correlate of cellular differentiation, which represents the key feature of the histological classification. RNA is a labile molecule that varies significantly according with the preservation protocol, its transcription reflect the adaptation of the tumor cells to the microenvironment, it can be passed through mechanisms of intercellular transference of genetic information (exosomes, and it is exposed to epigenetic modifications. More robust classifications should be based on stable molecules, at the genetic level represented by DNA to improve reliability, and its analysis must deal with the concept of intratumoral heterogeneity, which is at the origin of tumor progression and is the byproduct of the selection process during the clonal expansion and progression of neoplasms. The simultaneous analysis of multiple DNA targets and next generation sequencing offer the best practical approach for an analytical genomic classification of tumors.

  7. Classification of BCI Users Based on Cognition

    Directory of Open Access Journals (Sweden)

    N. Firat Ozkan

    2018-01-01

    Full Text Available Brain-Computer Interfaces (BCI are systems originally developed to assist paralyzed patients allowing for commands to the computer with brain activities. This study aims to examine cognitive state with an objective, easy-to-use, and easy-to-interpret method utilizing Brain-Computer Interface systems. Seventy healthy participants completed six tasks using a Brain-Computer Interface system and participants’ pupil dilation, blink rate, and Galvanic Skin Response (GSR data were collected simultaneously. Participants filled Nasa-TLX forms following each task and task performances of participants were also measured. Cognitive state clusters were created from the data collected using the K-means method. Taking these clusters and task performances into account, the general cognitive state of each participant was classified as low risk or high risk. Logistic Regression, Decision Tree, and Neural Networks were also used to classify the same data in order to measure the consistency of this classification with other techniques and the method provided a consistency between 87.1% and 100% with other techniques.

  8. AN ENSEMBLE TEMPLATE MATCHING AND CONTENT-BASED IMAGE RETRIEVAL SCHEME TOWARDS EARLY STAGE DETECTION OF MELANOMA

    Directory of Open Access Journals (Sweden)

    Spiros Kostopoulos

    2016-12-01

    Full Text Available Malignant melanoma represents the most dangerous type of skin cancer. In this study we present an ensemble classification scheme, employing the mutual information, the cross-correlation and the clustering based on proximity of image features methods, for early stage assessment of melanomas on plain photography images. The proposed scheme performs two main operations. First, it retrieves the most similar, to the unknown case, image samples from an available image database with verified benign moles and malignant melanoma cases. Second, it provides an automated estimation regarding the nature of the unknown image sample based on the majority of the most similar images retrieved from the available database. Clinical material comprised 75 melanoma and 75 benign plain photography images collected from publicly available dermatological atlases. Results showed that the ensemble scheme outperformed all other methods tested in terms of accuracy with 94.9±1.5%, following an external cross-validation evaluation methodology. The proposed scheme may benefit patients by providing a second opinion consultation during the self-skin examination process and the physician by providing a second opinion estimation regarding the nature of suspicious moles that may assist towards decision making especially for ambiguous cases, safeguarding, in this way from potential diagnostic misinterpretations.

  9. The Study of Land Use Classification Based on SPOT6 High Resolution Data

    OpenAIRE

    Wu Song; Jiang Qigang

    2016-01-01

    A method is carried out to quick classification extract of the type of land use in agricultural areas, which is based on the spot6 high resolution remote sensing classification data and used of the good nonlinear classification ability of support vector machine. The results show that the spot6 high resolution remote sensing classification data can realize land classification efficiently, the overall classification accuracy reached 88.79% and Kappa factor is 0.8632 which means that the classif...

  10. A secure quantum group signature scheme based on Bell states

    International Nuclear Information System (INIS)

    Zhang Kejia; Song Tingting; Zuo Huijuan; Zhang Weiwei

    2013-01-01

    In this paper, we propose a new secure quantum group signature with Bell states, which may have applications in e-payment system, e-government, e-business, etc. Compared with the recent quantum group signature protocols, our scheme is focused on the most general situation in practice, i.e. only the arbitrator is trusted and no intermediate information needs to be stored in the signing phase to ensure the security. Furthermore, our scheme has achieved all the characteristics of group signature—anonymity, verifiability, traceability, unforgetability and undeniability, by using some current developed quantum and classical technologies. Finally, a feasible security analysis model for quantum group signature is presented. (paper)

  11. A vertical handoff scheme based on adaptive period

    Directory of Open Access Journals (Sweden)

    Li Yang

    2017-08-01

    Full Text Available This paper presents a periodic adaptive vertical handoff scheme.In the phase of handoff initiation,the mobile terminal will adjust the interfaces activating interval to scan the potential new wireless signals according to the Received Signals Strength.In the phase of handoff decision,multiple attribute judgment method are adopted to judge the comprehensive perfomance of each network.The simulation shows that the proposed scheme can discover new wireless networks access the network that has the best comprehensive performance saving consumed power.

  12. A Novel Basis Splitting Eavesdropping Scheme in Quantum Cryptography Based on the BB84 Protocol

    International Nuclear Information System (INIS)

    Zhao Nan; Zhu Chang-Hua; Quan Dong-Xiao

    2015-01-01

    We propose a novel strategy named basis-splitting scheme to split the intercepted quanta into several portions based on different bases, for eavesdropping in the process of quantum cryptography. Compared with intercept-resend strategy, our simulation results of the basis-splitting scheme under the non-ideal condition show a greater performance, especially with the increase of the length of shifted bits. Consequently our scheme can aid eavesdropper to gather much more useful information. (paper)

  13. A new circulation type classification based upon Lagrangian air trajectories

    Directory of Open Access Journals (Sweden)

    Alexandre M. Ramos

    2014-10-01

    Full Text Available A new classification method of the large-scale circulation characteristic for a specific target area (NW Iberian Peninsula is presented, based on the analysis of 90-h backward trajectories arriving in this area calculated with the 3-D Lagrangian particle dispersion model FLEXPART. A cluster analysis is applied to separate the backward trajectories in up to five representative air streams for each day. Specific measures are then used to characterise the distinct air streams (e.g., curvature of the trajectories, cyclonic or anticyclonic flow, moisture evolution, origin and length of the trajectories. The robustness of the presented method is demonstrated in comparison with the Eulerian Lamb weather type classification.A case study of the 2003 heatwave is discussed in terms of the new Lagrangian circulation and the Lamb weather type classifications. It is shown that the new classification method adds valuable information about the pertinent meteorological conditions, which are missing in an Eulerian approach. The new method is climatologically evaluated for the five-year time period from December 1999 to November 2004. The ability of the method to capture the inter-seasonal circulation variability in the target region is shown. Furthermore, the multi-dimensional character of the classification is shortly discussed, in particular with respect to inter-seasonal differences. Finally, the relationship between the new Lagrangian classification and the precipitation in the target area is studied.

  14. A spatiotemporal-based scheme for efficient registration-based segmentation of thoracic 4-D MRI.

    Science.gov (United States)

    Yang, Y; Van Reeth, E; Poh, C L; Tan, C H; Tham, I W K

    2014-05-01

    Dynamic three-dimensional (3-D) (four-dimensional, 4-D) magnetic resonance (MR) imaging is gaining importance in the study of pulmonary motion for respiratory diseases and pulmonary tumor motion for radiotherapy. To perform quantitative analysis using 4-D MR images, segmentation of anatomical structures such as the lung and pulmonary tumor is required. Manual segmentation of entire thoracic 4-D MRI data that typically contains many 3-D volumes acquired over several breathing cycles is extremely tedious, time consuming, and suffers high user variability. This requires the development of new automated segmentation schemes for 4-D MRI data segmentation. Registration-based segmentation technique that uses automatic registration methods for segmentation has been shown to be an accurate method to segment structures for 4-D data series. However, directly applying registration-based segmentation to segment 4-D MRI series lacks efficiency. Here we propose an automated 4-D registration-based segmentation scheme that is based on spatiotemporal information for the segmentation of thoracic 4-D MR lung images. The proposed scheme saved up to 95% of computation amount while achieving comparable accurate segmentations compared to directly applying registration-based segmentation to 4-D dataset. The scheme facilitates rapid 3-D/4-D visualization of the lung and tumor motion and potentially the tracking of tumor during radiation delivery.

  15. An adjoint-based scheme for eigenvalue error improvement

    International Nuclear Information System (INIS)

    Merton, S.R.; Smedley-Stevenson, R.P.; Pain, C.C.; El-Sheikh, A.H.; Buchan, A.G.

    2011-01-01

    A scheme for improving the accuracy and reducing the error in eigenvalue calculations is presented. Using a rst order Taylor series expansion of both the eigenvalue solution and the residual of the governing equation, an approximation to the error in the eigenvalue is derived. This is done using a convolution of the equation residual and adjoint solution, which is calculated in-line with the primal solution. A defect correction on the solution is then performed in which the approximation to the error is used to apply a correction to the eigenvalue. The method is shown to dramatically improve convergence of the eigenvalue. The equation for the eigenvalue is shown to simplify when certain normalizations are applied to the eigenvector. Two such normalizations are considered; the rst of these is a fission-source type of normalisation and the second is an eigenvector normalisation. Results are demonstrated on a number of demanding elliptic problems using continuous Galerkin weighted nite elements. Moreover, the correction scheme may also be applied to hyperbolic problems and arbitrary discretization. This is not limited to spatial corrections and may be used throughout the phase space of the discrete equation. The applied correction not only improves fidelity of the calculation, it allows assessment of the reliability of numerical schemes to be made and could be used to guide mesh adaption algorithms or to automate mesh generation schemes. (author)

  16. Deflection routing scheme for GMPLS-based OBS networks

    DEFF Research Database (Denmark)

    Eid, Arafat; Mahmood, Waqar; Alomar, Anwar

    2010-01-01

    Integrating the Generalized Multi-Protocol Label Switching (GMPLS) framework into an Optical Burst Switching (OBS) Control Plane is a promising solution to alleviating most of OBS performance and design issues. However, implementing the already proposed OBS deflection routing schemes is not appli...

  17. Assessment of irrigation schemes in Turkey based on management ...

    African Journals Online (AJOL)

    This suggests that the WUAs-operated schemes are not optimally managed, possibly due to factors such as inappropriate crop pattern and intensity, irrigation infrastructure, lack of an effective monitoring and evaluation system, insufficient awareness among managers and farmers, or unstable administrative structure.

  18. Market-based support schemes for renewable energy sources

    NARCIS (Netherlands)

    Fagiani, R.

    2014-01-01

    The European Union set ambitious goals regarding the production of electricity from renewable energy sources and the majority of European governments have implemented policies stimulating investments in such technologies. Support schemes differ in many aspects, not only in their effectivity and

  19. Failure diagnosis using deep belief learning based health state classification

    International Nuclear Information System (INIS)

    Tamilselvan, Prasanna; Wang, Pingfeng

    2013-01-01

    Effective health diagnosis provides multifarious benefits such as improved safety, improved reliability and reduced costs for operation and maintenance of complex engineered systems. This paper presents a novel multi-sensor health diagnosis method using deep belief network (DBN). DBN has recently become a popular approach in machine learning for its promised advantages such as fast inference and the ability to encode richer and higher order network structures. The DBN employs a hierarchical structure with multiple stacked restricted Boltzmann machines and works through a layer by layer successive learning process. The proposed multi-sensor health diagnosis methodology using DBN based state classification can be structured in three consecutive stages: first, defining health states and preprocessing sensory data for DBN training and testing; second, developing DBN based classification models for diagnosis of predefined health states; third, validating DBN classification models with testing sensory dataset. Health diagnosis using DBN based health state classification technique is compared with four existing diagnosis techniques. Benchmark classification problems and two engineering health diagnosis applications: aircraft engine health diagnosis and electric power transformer health diagnosis are employed to demonstrate the efficacy of the proposed approach

  20. A provably-secure ECC-based authentication scheme for wireless sensor networks.

    Science.gov (United States)

    Nam, Junghyun; Kim, Moonseong; Paik, Juryon; Lee, Youngsook; Won, Dongho

    2014-11-06

    A smart-card-based user authentication scheme for wireless sensor networks (in short, a SUA-WSN scheme) is designed to restrict access to the sensor data only to users who are in possession of both a smart card and the corresponding password. While a significant number of SUA-WSN schemes have been suggested in recent years, their intended security properties lack formal definitions and proofs in a widely-accepted model. One consequence is that SUA-WSN schemes insecure against various attacks have proliferated. In this paper, we devise a security model for the analysis of SUA-WSN schemes by extending the widely-accepted model of Bellare, Pointcheval and Rogaway (2000). Our model provides formal definitions of authenticated key exchange and user anonymity while capturing side-channel attacks, as well as other common attacks. We also propose a new SUA-WSN scheme based on elliptic curve cryptography (ECC), and prove its security properties in our extended model. To the best of our knowledge, our proposed scheme is the first SUA-WSN scheme that provably achieves both authenticated key exchange and user anonymity. Our scheme is also computationally competitive with other ECC-based (non-provably secure) schemes.

  1. A Provably-Secure ECC-Based Authentication Scheme for Wireless Sensor Networks

    Science.gov (United States)

    Nam, Junghyun; Kim, Moonseong; Paik, Juryon; Lee, Youngsook; Won, Dongho

    2014-01-01

    A smart-card-based user authentication scheme for wireless sensor networks (in short, a SUA-WSN scheme) is designed to restrict access to the sensor data only to users who are in possession of both a smart card and the corresponding password. While a significant number of SUA-WSN schemes have been suggested in recent years, their intended security properties lack formal definitions and proofs in a widely-accepted model. One consequence is that SUA-WSN schemes insecure against various attacks have proliferated. In this paper, we devise a security model for the analysis of SUA-WSN schemes by extending the widely-accepted model of Bellare, Pointcheval and Rogaway (2000). Our model provides formal definitions of authenticated key exchange and user anonymity while capturing side-channel attacks, as well as other common attacks. We also propose a new SUA-WSN scheme based on elliptic curve cryptography (ECC), and prove its security properties in our extended model. To the best of our knowledge, our proposed scheme is the first SUA-WSN scheme that provably achieves both authenticated key exchange and user anonymity. Our scheme is also computationally competitive with other ECC-based (non-provably secure) schemes. PMID:25384009

  2. A Provably-Secure ECC-Based Authentication Scheme for Wireless Sensor Networks

    Directory of Open Access Journals (Sweden)

    Junghyun Nam

    2014-11-01

    Full Text Available A smart-card-based user authentication scheme for wireless sensor networks (in short, a SUA-WSN scheme is designed to restrict access to the sensor data only to users who are in possession of both a smart card and the corresponding password. While a significant number of SUA-WSN schemes have been suggested in recent years, their intended security properties lack formal definitions and proofs in a widely-accepted model. One consequence is that SUA-WSN schemes insecure against various attacks have proliferated. In this paper, we devise a security model for the analysis of SUA-WSN schemes by extending the widely-accepted model of Bellare, Pointcheval and Rogaway (2000. Our model provides formal definitions of authenticated key exchange and user anonymity while capturing side-channel attacks, as well as other common attacks. We also propose a new SUA-WSN scheme based on elliptic curve cryptography (ECC, and prove its security properties in our extended model. To the best of our knowledge, our proposed scheme is the first SUA-WSN scheme that provably achieves both authenticated key exchange and user anonymity. Our scheme is also computationally competitive with other ECC-based (non-provably secure schemes.

  3. [Object-oriented stand type classification based on the combination of multi-source remote sen-sing data].

    Science.gov (United States)

    Mao, Xue Gang; Wei, Jing Yu

    2017-11-01

    The recognition of forest type is one of the key problems in forest resource monitoring. The Radarsat-2 data and QuickBird remote sensing image were used for object-based classification to study the object-based forest type classification and recognition based on the combination of multi-source remote sensing data. In the process of object-based classification, three segmentation schemes (segmentation with QuickBird remote sensing image only, segmentation with Radarsat-2 data only, segmentation with combination of QuickBird and Radarsat-2) were adopted. For the three segmentation schemes, ten segmentation scale parameters were adopted (25-250, step 25), and modified Euclidean distance 3 index was further used to evaluate the segmented results to determine the optimal segmentation scheme and segmentation scale. Based on the optimal segmented result, three forest types of Chinese fir, Masson pine and broad-leaved forest were classified and recognized using Support Vector Machine (SVM) classifier with Radial Basis Foundation (RBF) kernel according to different feature combinations of topography, height, spectrum and common features. The results showed that the combination of Radarsat-2 data and QuickBird remote sensing image had its advantages of object-based forest type classification over using Radarsat-2 data or QuickBird remote sensing image only. The optimal scale parameter for QuickBirdRadarsat-2 segmentation was 100, and at the optimal scale, the accuracy of object-based forest type classification was the highest (OA=86%, Kappa=0.86), when using all features which were extracted from two kinds of data resources. This study could not only provide a reference for forest type recognition using multi-source remote sensing data, but also had a practical significance for forest resource investigation and monitoring.

  4. Point Based Emotion Classification Using SVM

    OpenAIRE

    Swinkels, Wout

    2016-01-01

    The detection of emotions is a hot topic in the area of computer vision. Emotions are based on subtle changes in the face that are intuitively detected and interpreted by humans. Detecting these subtle changes, based on mathematical models, is a great challenge in the area of computer vision. In this thesis a new method is proposed to achieve state-of-the-art emotion detection performance. This method is based on facial feature points to monitor subtle changes in the face. Therefore the c...

  5. Deep-learning-based classification of FDG-PET data for Alzheimer's disease categories

    Science.gov (United States)

    Singh, Shibani; Srivastava, Anant; Mi, Liang; Caselli, Richard J.; Chen, Kewei; Goradia, Dhruman; Reiman, Eric M.; Wang, Yalin

    2017-11-01

    Fluorodeoxyglucose (FDG) positron emission tomography (PET) measures the decline in the regional cerebral metabolic rate for glucose, offering a reliable metabolic biomarker even on presymptomatic Alzheimer's disease (AD) patients. PET scans provide functional information that is unique and unavailable using other types of imaging. However, the computational efficacy of FDG-PET data alone, for the classification of various Alzheimers Diagnostic categories, has not been well studied. This motivates us to correctly discriminate various AD Diagnostic categories using FDG-PET data. Deep learning has improved state-of-the-art classification accuracies in the areas of speech, signal, image, video, text mining and recognition. We propose novel methods that involve probabilistic principal component analysis on max-pooled data and mean-pooled data for dimensionality reduction, and multilayer feed forward neural network which performs binary classification. Our experimental dataset consists of baseline data of subjects including 186 cognitively unimpaired (CU) subjects, 336 mild cognitive impairment (MCI) subjects with 158 Late MCI and 178 Early MCI, and 146 AD patients from Alzheimer's Disease Neuroimaging Initiative (ADNI) dataset. We measured F1-measure, precision, recall, negative and positive predictive values with a 10-fold cross validation scheme. Our results indicate that our designed classifiers achieve competitive results while max pooling achieves better classification performance compared to mean-pooled features. Our deep model based research may advance FDG-PET analysis by demonstrating their potential as an effective imaging biomarker of AD.

  6. Cost-Based Droop Schemes for Economic Dispatch in Islanded Microgrids

    DEFF Research Database (Denmark)

    Chen, Feixiong; Chen, Minyou; Li, Qiang

    2017-01-01

    In this paper, cost based droop schemes are proposed, to minimize the total active power generation cost in an islanded microgrid (MG), while the simplicity and decentralized nature of the droop control are retained. In cost based droop schemes, the incremental costs of distributed generators (DGs...

  7. Performance analysis of switch-based multiuser scheduling schemes with adaptive modulation in spectrum sharing systems

    KAUST Repository

    Qaraqe, Marwa; Abdallah, Mohamed M.; Serpedin, Erchin; Alouini, Mohamed-Slim

    2014-01-01

    the average spectral efficiency by selecting the user that reports the best channel quality. In order to alleviate the relatively high feedback required by the first scheme, a second scheme based on the concept of switched diversity is proposed, where the base

  8. Performance Analysis of Virtual MIMO Relaying Schemes Based on Detect–Split–Forward

    KAUST Repository

    Al-Basit, Suhaib M.; Al-Ghadhban, Samir; Zummo, Salam A.

    2014-01-01

    © 2014, Springer Science+Business Media New York. Virtual multi-input multi-output (vMIMO) schemes in wireless communication systems improve coverage, throughput, capacity, and quality of service. In this paper, we propose three uplink vMIMO relaying schemes based on detect–split–forward (DSF). In addition, we investigate the effect of several physical parameters such as distance, modulation type and number of relays. Furthermore, an adaptive vMIMO DSF scheme based on VBLAST and STBC is proposed. In order to do that, we provide analytical tools to evaluate the performance of the propose vMIMO relaying scheme.

  9. Performance Analysis of Virtual MIMO Relaying Schemes Based on Detect–Split–Forward

    KAUST Repository

    Al-Basit, Suhaib M.

    2014-10-29

    © 2014, Springer Science+Business Media New York. Virtual multi-input multi-output (vMIMO) schemes in wireless communication systems improve coverage, throughput, capacity, and quality of service. In this paper, we propose three uplink vMIMO relaying schemes based on detect–split–forward (DSF). In addition, we investigate the effect of several physical parameters such as distance, modulation type and number of relays. Furthermore, an adaptive vMIMO DSF scheme based on VBLAST and STBC is proposed. In order to do that, we provide analytical tools to evaluate the performance of the propose vMIMO relaying scheme.

  10. ICF-based classification and measurement of functioning.

    Science.gov (United States)

    Stucki, G; Kostanjsek, N; Ustün, B; Cieza, A

    2008-09-01

    If we aim towards a comprehensive understanding of human functioning and the development of comprehensive programs to optimize functioning of individuals and populations we need to develop suitable measures. The approval of the International Classification, Disability and Health (ICF) in 2001 by the 54th World Health Assembly as the first universally shared model and classification of functioning, disability and health marks, therefore an important step in the development of measurement instruments and ultimately for our understanding of functioning, disability and health. The acceptance and use of the ICF as a reference framework and classification has been facilitated by its development in a worldwide, comprehensive consensus process and the increasing evidence regarding its validity. However, the broad acceptance and use of the ICF as a reference framework and classification will also depend on the resolution of conceptual and methodological challenges relevant for the classification and measurement of functioning. This paper therefore describes first how the ICF categories can serve as building blocks for the measurement of functioning and then the current state of the development of ICF based practical tools and international standards such as the ICF Core Sets. Finally it illustrates how to map the world of measures to the ICF and vice versa and the methodological principles relevant for the transformation of information obtained with a clinical test or a patient-oriented instrument to the ICF as well as the development of ICF-based clinical and self-reported measurement instruments.

  11. Chinese Sentence Classification Based on Convolutional Neural Network

    Science.gov (United States)

    Gu, Chengwei; Wu, Ming; Zhang, Chuang

    2017-10-01

    Sentence classification is one of the significant issues in Natural Language Processing (NLP). Feature extraction is often regarded as the key point for natural language processing. Traditional ways based on machine learning can not take high level features into consideration, such as Naive Bayesian Model. The neural network for sentence classification can make use of contextual information to achieve greater results in sentence classification tasks. In this paper, we focus on classifying Chinese sentences. And the most important is that we post a novel architecture of Convolutional Neural Network (CNN) to apply on Chinese sentence classification. In particular, most of the previous methods often use softmax classifier for prediction, we embed a linear support vector machine to substitute softmax in the deep neural network model, minimizing a margin-based loss to get a better result. And we use tanh as an activation function, instead of ReLU. The CNN model improve the result of Chinese sentence classification tasks. Experimental results on the Chinese news title database validate the effectiveness of our model.

  12. Universal block diagram based modeling and simulation schemes for fractional-order control systems.

    Science.gov (United States)

    Bai, Lu; Xue, Dingyü

    2017-05-08

    Universal block diagram based schemes are proposed for modeling and simulating the fractional-order control systems in this paper. A fractional operator block in Simulink is designed to evaluate the fractional-order derivative and integral. Based on the block, the fractional-order control systems with zero initial conditions can be modeled conveniently. For modeling the system with nonzero initial conditions, the auxiliary signal is constructed in the compensation scheme. Since the compensation scheme is very complicated, therefore the integrator chain scheme is further proposed to simplify the modeling procedures. The accuracy and effectiveness of the schemes are assessed in the examples, the computation results testify the block diagram scheme is efficient for all Caputo fractional-order ordinary differential equations (FODEs) of any complexity, including the implicit Caputo FODEs. Copyright © 2017 ISA. Published by Elsevier Ltd. All rights reserved.

  13. Identity based Encryption and Biometric Authentication Scheme for Secure Data Access in Cloud Computing

    DEFF Research Database (Denmark)

    Cheng, Hongbing; Rong, Chunming; Tan, Zheng-Hua

    2012-01-01

    Cloud computing will be a main information infrastructure in the future; it consists of many large datacenters which are usually geographically distributed and heterogeneous. How to design a secure data access for cloud computing platform is a big challenge. In this paper, we propose a secure data...... access scheme based on identity-based encryption and biometric authentication for cloud computing. Firstly, we describe the security concern of cloud computing and then propose an integrated data access scheme for cloud computing, the procedure of the proposed scheme include parameter setup, key...... distribution, feature template creation, cloud data processing and secure data access control. Finally, we compare the proposed scheme with other schemes through comprehensive analysis and simulation. The results show that the proposed data access scheme is feasible and secure for cloud computing....

  14. A keyword searchable attribute-based encryption scheme with attribute update for cloud storage.

    Science.gov (United States)

    Wang, Shangping; Ye, Jian; Zhang, Yaling

    2018-01-01

    Ciphertext-policy attribute-based encryption (CP-ABE) scheme is a new type of data encryption primitive, which is very suitable for data cloud storage for its fine-grained access control. Keyword-based searchable encryption scheme enables users to quickly find interesting data stored in the cloud server without revealing any information of the searched keywords. In this work, we provide a keyword searchable attribute-based encryption scheme with attribute update for cloud storage, which is a combination of attribute-based encryption scheme and keyword searchable encryption scheme. The new scheme supports the user's attribute update, especially in our new scheme when a user's attribute need to be updated, only the user's secret key related with the attribute need to be updated, while other user's secret key and the ciphertexts related with this attribute need not to be updated with the help of the cloud server. In addition, we outsource the operation with high computation cost to cloud server to reduce the user's computational burden. Moreover, our scheme is proven to be semantic security against chosen ciphertext-policy and chosen plaintext attack in the general bilinear group model. And our scheme is also proven to be semantic security against chosen keyword attack under bilinear Diffie-Hellman (BDH) assumption.

  15. Distributed Group-Based Mobility Management Scheme in Wireless Body Area Networks

    Directory of Open Access Journals (Sweden)

    Moneeb Gohar

    2017-01-01

    Full Text Available For group-based mobility management in 6LoWPAN-based wireless body area networks (WBAN, some schemes using the Proxy Mobile IPv6 (PMIP have been proposed. However, the existing PMIP-based mobility schemes tend to induce large registration delay and handover delay. To overcome such limitations, we propose a new distributed group-based mobility management scheme, in which the Local Mobility Anchor (LMA function is implemented by each Mobile Access Gateway (MAG and the handover operation is performed between two neighboring MAGs without the help of LMA. Besides, each MAG maintains the information of the group of mobile sensors and aggregates the Authentication-Authorization-Accounting (AAA query messages for a group of mobile sensors as a “single” message to decrease the control overhead. By numerical analysis, it is shown that the proposed scheme can reduce the registration and handover delays, compared to the existing PMIP-based mobility schemes.

  16. NIM: A Node Influence Based Method for Cancer Classification

    Directory of Open Access Journals (Sweden)

    Yiwen Wang

    2014-01-01

    Full Text Available The classification of different cancer types owns great significance in the medical field. However, the great majority of existing cancer classification methods are clinical-based and have relatively weak diagnostic ability. With the rapid development of gene expression technology, it is able to classify different kinds of cancers using DNA microarray. Our main idea is to confront the problem of cancer classification using gene expression data from a graph-based view. Based on a new node influence model we proposed, this paper presents a novel high accuracy method for cancer classification, which is composed of four parts: the first is to calculate the similarity matrix of all samples, the second is to compute the node influence of training samples, the third is to obtain the similarity between every test sample and each class using weighted sum of node influence and similarity matrix, and the last is to classify each test sample based on its similarity between every class. The data sets used in our experiments are breast cancer, central nervous system, colon tumor, prostate cancer, acute lymphoblastic leukemia, and lung cancer. experimental results showed that our node influence based method (NIM is more efficient and robust than the support vector machine, K-nearest neighbor, C4.5, naive Bayes, and CART.

  17. Optimization bitumen-based upgrading and refining schemes

    Energy Technology Data Exchange (ETDEWEB)

    Munteanu, M.; Chen, J. [National Centre for Upgrading Technology, Devon, AB (Canada); Natural Resources Canada, Devon, AB (Canada). CanmetENERGY

    2009-07-01

    This poster highlighted the results of a study in which the entire refining scheme for Canadian bitumen as feedstocks was modelled and simulated under different process configurations, operating conditions and product structures. The aim of the study was to optimize the economic benefits, product quality and energy use under a range of operational scenarios. Optimal refining schemes were proposed along with process conditions for existing refinery configurations and objectives. The goal was to provide guidelines and information for upgrading and refining process design and retrofitting. Critical steps were identified with regards to the upgrading process. It was concluded that the information obtained from this study would lead to significant improvement in process performance and operations, and in reducing the capital cost for building new upgraders and refineries. The simulation results provided valuable information for increasing the marketability of bitumen, reducing greenhouse gas emissions and other environmental impacts associated with bitumen upgrading and refining. tabs., figs.

  18. 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.

  19. A continuous and prognostic convection scheme based on buoyancy, PCMT

    Science.gov (United States)

    Guérémy, Jean-François; Piriou, Jean-Marcel

    2016-04-01

    A new and consistent convection scheme (PCMT: Prognostic Condensates Microphysics and Transport), providing a continuous and prognostic treatment of this atmospheric process, is described. The main concept ensuring the consistency of the whole system is the buoyancy, key element of any vertical motion. The buoyancy constitutes the forcing term of the convective vertical velocity, which is then used to define the triggering condition, the mass flux, and the rates of entrainment-detrainment. The buoyancy is also used in its vertically integrated form (CAPE) to determine the closure condition. The continuous treatment of convection, from dry thermals to deep precipitating convection, is achieved with the help of a continuous formulation of the entrainment-detrainment rates (depending on the convective vertical velocity) and of the CAPE relaxation time (depending on the convective over-turning time). The convective tendencies are directly expressed in terms of condensation and transport. Finally, the convective vertical velocity and condensates are fully prognostic, the latter being treated using the same microphysics scheme as for the resolved condensates but considering the convective environment. A Single Column Model (SCM) validation of this scheme is shown, allowing detailed comparisons with observed and explicitly simulated data. Four cases covering the convective spectrum are considered: over ocean, sensitivity to environmental moisture (S. Derbyshire) non precipitating shallow convection to deep precipitating convection, trade wind shallow convection (BOMEX) and strato-cumulus (FIRE), together with an entire continental diurnal cycle of convection (ARM). The emphasis is put on the characteristics of the scheme which enable a continuous treatment of convection. Then, a 3D LAM validation is presented considering an AMMA case with both observations and a CRM simulation using the same initial and lateral conditions as for the parameterized one. Finally, global

  20. A Quantum Proxy Weak Blind Signature Scheme Based on Controlled Quantum Teleportation

    Science.gov (United States)

    Cao, Hai-Jing; Yu, Yao-Feng; Song, Qin; Gao, Lan-Xiang

    2015-04-01

    Proxy blind signature is applied to the electronic paying system, electronic voting system, mobile agent system, security of internet, etc. A quantum proxy weak blind signature scheme is proposed in this paper. It is based on controlled quantum teleportation. Five-qubit entangled state functions as quantum channel. The scheme uses the physical characteristics of quantum mechanics to implement message blinding, so it could guarantee not only the unconditional security of the scheme but also the anonymity of the messages owner.

  1. MULTIMEDIA DATA TRANSMISSION THROUGH TCP/IP USING HASH BASED FEC WITH AUTO-XOR SCHEME

    OpenAIRE

    R. Shalin; D. Kesavaraja

    2012-01-01

    The most preferred mode for communication of multimedia data is through the TCP/IP protocol. But on the other hand the TCP/IP protocol produces huge packet loss unavoidable due to network traffic and congestion. In order to provide a efficient communication it is necessary to recover the loss of packets. The proposed scheme implements Hash based FEC with auto XOR scheme for this purpose. The scheme is implemented through Forward error correction, MD5 and XOR for providing efficient transmissi...

  2. Systems-based decomposition schemes for the approximate solution of multi-term fractional differential equations

    Science.gov (United States)

    Ford, Neville J.; Connolly, Joseph A.

    2009-07-01

    We give a comparison of the efficiency of three alternative decomposition schemes for the approximate solution of multi-term fractional differential equations using the Caputo form of the fractional derivative. The schemes we compare are based on conversion of the original problem into a system of equations. We review alternative approaches and consider how the most appropriate numerical scheme may be chosen to solve a particular equation.

  3. Voting-based Classification for E-mail Spam Detection

    Directory of Open Access Journals (Sweden)

    Bashar Awad Al-Shboul

    2016-06-01

    Full Text Available The problem of spam e-mail has gained a tremendous amount of attention. Although entities tend to use e-mail spam filter applications to filter out received spam e-mails, marketing companies still tend to send unsolicited e-mails in bulk and users still receive a reasonable amount of spam e-mail despite those filtering applications. This work proposes a new method for classifying e-mails into spam and non-spam. First, several e-mail content features are extracted and then those features are used for classifying each e-mail individually. The classification results of three different classifiers (i.e. Decision Trees, Random Forests and k-Nearest Neighbor are combined in various voting schemes (i.e. majority vote, average probability, product of probabilities, minimum probability and maximum probability for making the final decision. To validate our method, two different spam e-mail collections were used.

  4. Movie Popularity Classification based on Inherent Movie Attributes using C4.5, PART and Correlation Coefficient

    DEFF Research Database (Denmark)

    Ibnal Asad, Khalid; Ahmed, Tanvir; Rahman, Md. Saiedur

    2012-01-01

    Abundance of movie data across the internet makes it an obvious candidate for machine learning and knowledge discovery. But most researches are directed towards bi-polar classification of movie or generation of a movie recommendation system based on reviews given by viewers on various internet...... sites. Classification of movie popularity based solely on attributes of a movie i.e. actor, actress, director rating, language, country and budget etc. has been less highlighted due to large number of attributes that are associated with each movie and their differences in dimensions. In this paper, we...... propose classification scheme of pre-release movie popularity based on inherent attributes using C4.S and PART classifier algorithm and define the relation between attributes of post release movies using correlation coefficient....

  5. A Topic Space Oriented User Group Discovering Scheme in Social Network: A Trust Chain Based Interest Measuring Perspective

    Directory of Open Access Journals (Sweden)

    Wang Dong

    2016-01-01

    Full Text Available Currently, user group has become an effective platform for information sharing and communicating among users in social network sites. In present work, we propose a single topic user group discovering scheme, which includes three phases: topic impact evaluation, interest degree measurement, and trust chain based discovering, to enable selecting influential topic and discovering users into a topic oriented group. Our main works include (1 an overview of proposed scheme and its related definitions; (2 topic space construction method based on topic relatedness clustering and its impact (influence degree and popularity degree evaluation; (3 a trust chain model to take user relation network topological information into account with a strength classification perspective; (4 an interest degree (user explicit and implicit interest degree evaluation method based on trust chain among users; and (5 a topic space oriented user group discovering method to group core users according to their explicit interest degrees and to predict ordinary users under implicit interest and user trust chain. Finally, experimental results are given to explain effectiveness and feasibility of our scheme.

  6. Some improved classification-based ridge parameter of Hoerl and ...

    African Journals Online (AJOL)

    Some improved classification-based ridge parameter of Hoerl and Kennard estimation techniques. ... This assumption is often violated and Ridge Regression estimator introduced by [2]has been identified to be more efficient than ordinary least square (OLS) in handling it. However, it requires a ridge parameter, K, of which ...

  7. Classification and Target Group Selection Based Upon Frequent Patterns

    NARCIS (Netherlands)

    W.H.L.M. Pijls (Wim); R. Potharst (Rob)

    2000-01-01

    textabstractIn this technical report , two new algorithms based upon frequent patterns are proposed. One algorithm is a classification method. The other one is an algorithm for target group selection. In both algorithms, first of all, the collection of frequent patterns in the training set is

  8. 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)

  9. Searchable attribute-based encryption scheme with attribute revocation in cloud storage.

    Science.gov (United States)

    Wang, Shangping; Zhao, Duqiao; Zhang, Yaling

    2017-01-01

    Attribute based encryption (ABE) is a good way to achieve flexible and secure access control to data, and attribute revocation is the extension of the attribute-based encryption, and the keyword search is an indispensable part for cloud storage. The combination of both has an important application in the cloud storage. In this paper, we construct a searchable attribute-based encryption scheme with attribute revocation in cloud storage, the keyword search in our scheme is attribute based with access control, when the search succeeds, the cloud server returns the corresponding cipher text to user and the user can decrypt the cipher text definitely. Besides, our scheme supports multiple keywords search, which makes the scheme more practical. Under the assumption of decisional bilinear Diffie-Hellman exponent (q-BDHE) and decisional Diffie-Hellman (DDH) in the selective security model, we prove that our scheme is secure.

  10. Torrent classification - Base of rational management of erosive regions

    International Nuclear Information System (INIS)

    Gavrilovic, Zoran; Stefanovic, Milutin; Milovanovic, Irina; Cotric, Jelena; Milojevic, Mileta

    2008-01-01

    A complex methodology for torrents and erosion and the associated calculations was developed during the second half of the twentieth century in Serbia. It was the 'Erosion Potential Method'. One of the modules of that complex method was focused on torrent classification. The module enables the identification of hydro graphic, climate and erosion characteristics. The method makes it possible for each torrent, regardless of its magnitude, to be simply and recognizably described by the 'Formula of torrentially'. The above torrent classification is the base on which a set of optimisation calculations is developed for the required scope of erosion-control works and measures, the application of which enables the management of significantly larger erosion and torrential regions compared to the previous period. This paper will present the procedure and the method of torrent classification.

  11. Classification of scintigrams on the base of an automatic analysis

    International Nuclear Information System (INIS)

    Vidyukov, V.I.; Kasatkin, Yu.N.; Kal'nitskaya, E.F.; Mironov, S.P.; Rotenberg, E.M.

    1980-01-01

    The stages of drawing a discriminative system based on self-education for an automatic analysis of scintigrams have been considered. The results of the classification of 240 scintigrams of the liver into ''normal'', ''diffuse lesions'', ''focal lesions'' have been evaluated by medical experts and computer. The accuracy of the computerized classification was 91.7%, that of the experts-85%. The automatic analysis methods of scintigrams of the liver have been realized using the specialized MDS system of data processing. The quality of the discriminative system has been assessed on 125 scintigrams. The accuracy of the classification is equal to 89.6%. The employment of the self-education; methods permitted one to single out two subclasses depending on the severity of diffuse lesions

  12. Hyperspectral image classification based on local binary patterns and PCANet

    Science.gov (United States)

    Yang, Huizhen; Gao, Feng; Dong, Junyu; Yang, Yang

    2018-04-01

    Hyperspectral image classification has been well acknowledged as one of the challenging tasks of hyperspectral data processing. In this paper, we propose a novel hyperspectral image classification framework based on local binary pattern (LBP) features and PCANet. In the proposed method, linear prediction error (LPE) is first employed to select a subset of informative bands, and LBP is utilized to extract texture features. Then, spectral and texture features are stacked into a high dimensional vectors. Next, the extracted features of a specified position are transformed to a 2-D image. The obtained images of all pixels are fed into PCANet for classification. Experimental results on real hyperspectral dataset demonstrate the effectiveness of the proposed method.

  13. Remote Sensing Image Classification Based on Stacked Denoising Autoencoder

    Directory of Open Access Journals (Sweden)

    Peng Liang

    2017-12-01

    Full Text Available Focused on the issue that conventional remote sensing image classification methods have run into the bottlenecks in accuracy, a new remote sensing image classification method inspired by deep learning is proposed, which is based on Stacked Denoising Autoencoder. First, the deep network model is built through the stacked layers of Denoising Autoencoder. Then, with noised input, the unsupervised Greedy layer-wise training algorithm is used to train each layer in turn for more robust expressing, characteristics are obtained in supervised learning by Back Propagation (BP neural network, and the whole network is optimized by error back propagation. Finally, Gaofen-1 satellite (GF-1 remote sensing data are used for evaluation, and the total accuracy and kappa accuracy reach 95.7% and 0.955, respectively, which are higher than that of the Support Vector Machine and Back Propagation neural network. The experiment results show that the proposed method can effectively improve the accuracy of remote sensing image classification.

  14. Torrent classification - Base of rational management of erosive regions

    Energy Technology Data Exchange (ETDEWEB)

    Gavrilovic, Zoran; Stefanovic, Milutin; Milovanovic, Irina; Cotric, Jelena; Milojevic, Mileta [Institute for the Development of Water Resources ' Jaroslav Cerni' , 11226 Beograd (Pinosava), Jaroslava Cernog 80 (Serbia)], E-mail: gavrilovicz@sbb.rs

    2008-11-01

    A complex methodology for torrents and erosion and the associated calculations was developed during the second half of the twentieth century in Serbia. It was the 'Erosion Potential Method'. One of the modules of that complex method was focused on torrent classification. The module enables the identification of hydro graphic, climate and erosion characteristics. The method makes it possible for each torrent, regardless of its magnitude, to be simply and recognizably described by the 'Formula of torrentially'. The above torrent classification is the base on which a set of optimisation calculations is developed for the required scope of erosion-control works and measures, the application of which enables the management of significantly larger erosion and torrential regions compared to the previous period. This paper will present the procedure and the method of torrent classification.

  15. A Data Gathering Scheme in Wireless Sensor Networks Based on Synchronization of Chaotic Spiking Oscillator Networks

    International Nuclear Information System (INIS)

    Nakano, Hidehiro; Utani, Akihide; Miyauchi, Arata; Yamamoto, Hisao

    2011-01-01

    This paper studies chaos-based data gathering scheme in multiple sink wireless sensor networks. In the proposed scheme, each wireless sensor node has a simple chaotic oscillator. The oscillators generate spike signals with chaotic interspike intervals, and are impulsively coupled by the signals via wireless communication. Each wireless sensor node transmits and receives sensor information only in the timing of the couplings. The proposed scheme can exhibit various chaos synchronous phenomena and their breakdown phenomena, and can effectively gather sensor information with the significantly small number of transmissions and receptions compared with the conventional scheme. Also, the proposed scheme can flexibly adapt various wireless sensor networks not only with a single sink node but also with multiple sink nodes. This paper introduces our previous works. Through simulation experiments, we show effectiveness of the proposed scheme and discuss its development potential.

  16. A User Authentication Scheme Based on Elliptic Curves Cryptography for Wireless Ad Hoc Networks.

    Science.gov (United States)

    Chen, Huifang; Ge, Linlin; Xie, Lei

    2015-07-14

    The feature of non-infrastructure support in a wireless ad hoc network (WANET) makes it suffer from various attacks. Moreover, user authentication is the first safety barrier in a network. A mutual trust is achieved by a protocol which enables communicating parties to authenticate each other at the same time and to exchange session keys. For the resource-constrained WANET, an efficient and lightweight user authentication scheme is necessary. In this paper, we propose a user authentication scheme based on the self-certified public key system and elliptic curves cryptography for a WANET. Using the proposed scheme, an efficient two-way user authentication and secure session key agreement can be achieved. Security analysis shows that our proposed scheme is resilient to common known attacks. In addition, the performance analysis shows that our proposed scheme performs similar or better compared with some existing user authentication schemes.

  17. MULTIMEDIA DATA TRANSMISSION THROUGH TCP/IP USING HASH BASED FEC WITH AUTO-XOR SCHEME

    Directory of Open Access Journals (Sweden)

    R. Shalin

    2012-09-01

    Full Text Available The most preferred mode for communication of multimedia data is through the TCP/IP protocol. But on the other hand the TCP/IP protocol produces huge packet loss unavoidable due to network traffic and congestion. In order to provide a efficient communication it is necessary to recover the loss of packets. The proposed scheme implements Hash based FEC with auto XOR scheme for this purpose. The scheme is implemented through Forward error correction, MD5 and XOR for providing efficient transmission of multimedia data. The proposed scheme provides transmission high accuracy, throughput and low latency and loss.

  18. Cost-based droop scheme with lower generation costs for microgrids

    DEFF Research Database (Denmark)

    Nutkani, I. U.; Loh, Poh Chiang; Blaabjerg, Frede

    2013-01-01

    on the DG kVA ratings. Other operating characteristics like generation costs, efficiencies and emission penalties at different loadings have not been considered. This makes existing droop schemes not too well-suited for standalone microgrids without central management system, where different types of DGs...... usually exist. As an alternative, this paper proposes a cost-based droop scheme, whose objective is to reduce a generation cost realized with various DG operating characteristics taken into consideration. The proposed droop scheme therefore retains all advantages of the traditional droop schemes, while...... at the same time keep its generation cost low. These findings have been validated through simulation and scaled down lab experiment....

  19. Deep learning for EEG-Based preference classification

    Science.gov (United States)

    Teo, Jason; Hou, Chew Lin; Mountstephens, James

    2017-10-01

    Electroencephalogram (EEG)-based emotion classification is rapidly becoming one of the most intensely studied areas of brain-computer interfacing (BCI). The ability to passively identify yet accurately correlate brainwaves with our immediate emotions opens up truly meaningful and previously unattainable human-computer interactions such as in forensic neuroscience, rehabilitative medicine, affective entertainment and neuro-marketing. One particularly useful yet rarely explored areas of EEG-based emotion classification is preference recognition [1], which is simply the detection of like versus dislike. Within the limited investigations into preference classification, all reported studies were based on musically-induced stimuli except for a single study which used 2D images. The main objective of this study is to apply deep learning, which has been shown to produce state-of-the-art results in diverse hard problems such as in computer vision, natural language processing and audio recognition, to 3D object preference classification over a larger group of test subjects. A cohort of 16 users was shown 60 bracelet-like objects as rotating visual stimuli on a computer display while their preferences and EEGs were recorded. After training a variety of machine learning approaches which included deep neural networks, we then attempted to classify the users' preferences for the 3D visual stimuli based on their EEGs. Here, we show that that deep learning outperforms a variety of other machine learning classifiers for this EEG-based preference classification task particularly in a highly challenging dataset with large inter- and intra-subject variability.

  20. Performance Analysis of a Threshold-Based Parallel Multiple Beam Selection Scheme for WDM FSO Systems

    KAUST Repository

    Nam, Sung Sik; Alouini, Mohamed-Slim; Ko, Young-Chai

    2018-01-01

    In this paper, we statistically analyze the performance of a threshold-based parallel multiple beam selection scheme for a free-space optical (FSO) based system with wavelength division multiplexing (WDM) in cases where a pointing error has occurred

  1. Hardware Accelerators Targeting a Novel Group Based Packet Classification Algorithm

    Directory of Open Access Journals (Sweden)

    O. Ahmed

    2013-01-01

    Full Text Available Packet classification is a ubiquitous and key building block for many critical network devices. However, it remains as one of the main bottlenecks faced when designing fast network devices. In this paper, we propose a novel Group Based Search packet classification Algorithm (GBSA that is scalable, fast, and efficient. GBSA consumes an average of 0.4 megabytes of memory for a 10 k rule set. The worst-case classification time per packet is 2 microseconds, and the preprocessing speed is 3 M rules/second based on an Xeon processor operating at 3.4 GHz. When compared with other state-of-the-art classification techniques, the results showed that GBSA outperforms the competition with respect to speed, memory usage, and processing time. Moreover, GBSA is amenable to implementation in hardware. Three different hardware implementations are also presented in this paper including an Application Specific Instruction Set Processor (ASIP implementation and two pure Register-Transfer Level (RTL implementations based on Impulse-C and Handel-C flows, respectively. Speedups achieved with these hardware accelerators ranged from 9x to 18x compared with a pure software implementation running on an Xeon processor.

  2. Sparse Representation Based Binary Hypothesis Model for Hyperspectral Image Classification

    Directory of Open Access Journals (Sweden)

    Yidong Tang

    2016-01-01

    Full Text Available The sparse representation based classifier (SRC and its kernel version (KSRC have been employed for hyperspectral image (HSI classification. However, the state-of-the-art SRC often aims at extended surface objects with linear mixture in smooth scene and assumes that the number of classes is given. Considering the small target with complex background, a sparse representation based binary hypothesis (SRBBH model is established in this paper. In this model, a query pixel is represented in two ways, which are, respectively, by background dictionary and by union dictionary. The background dictionary is composed of samples selected from the local dual concentric window centered at the query pixel. Thus, for each pixel the classification issue becomes an adaptive multiclass classification problem, where only the number of desired classes is required. Furthermore, the kernel method is employed to improve the interclass separability. In kernel space, the coding vector is obtained by using kernel-based orthogonal matching pursuit (KOMP algorithm. Then the query pixel can be labeled by the characteristics of the coding vectors. Instead of directly using the reconstruction residuals, the different impacts the background dictionary and union dictionary have on reconstruction are used for validation and classification. It enhances the discrimination and hence improves the performance.

  3. Knowledge-based approach to video content classification

    Science.gov (United States)

    Chen, Yu; Wong, Edward K.

    2001-01-01

    A framework for video content classification using a knowledge-based approach is herein proposed. This approach is motivated by the fact that videos are rich in semantic contents, which can best be interpreted and analyzed by human experts. We demonstrate the concept by implementing a prototype video classification system using the rule-based programming language CLIPS 6.05. Knowledge for video classification is encoded as a set of rules in the rule base. The left-hand-sides of rules contain high level and low level features, while the right-hand-sides of rules contain intermediate results or conclusions. Our current implementation includes features computed from motion, color, and text extracted from video frames. Our current rule set allows us to classify input video into one of five classes: news, weather, reporting, commercial, basketball and football. We use MYCIN's inexact reasoning method for combining evidences, and to handle the uncertainties in the features and in the classification results. We obtained good results in a preliminary experiment, and it demonstrated the validity of the proposed approach.

  4. Secure and Efficient User Authentication Scheme Based on Password and Smart Card for Multiserver Environment

    Directory of Open Access Journals (Sweden)

    Yan Zhao

    2018-01-01

    Full Text Available The rapid development of information and network technologies motivates the emergence of various new computing paradigms, such as distributed computing, cloud computing, and edge computing. This also enables more and more network enterprises to provide multiple different services simultaneously. To ensure these services can only be accessed conveniently by authorized users, many password and smart card based authentication schemes for multiserver architecture have been proposed. Recently, Truong et al. introduced an identity based user authentication scheme on elliptic curve cryptography in multiserver environment and claimed that their scheme is secure against popular attacks. However, in this paper, we point out that their scheme suffers from offline password guessing and impersonation attack and fails to achieve security requirements of this kind of authentication scheme. Moreover, we put forward a new scheme to conquer security pitfalls in the above scheme. Security analysis indicates that the proposed scheme can be free from well-known attacks. Performance discussion demonstrates that our scheme has advantages in terms of both security property and computation efficiency and thus is more desirable for practical applications in multiserver environment.

  5. Improving Biometric-Based Authentication Schemes with Smart Card Revocation/Reissue for Wireless Sensor Networks.

    Science.gov (United States)

    Moon, Jongho; Lee, Donghoon; Lee, Youngsook; Won, Dongho

    2017-04-25

    User authentication in wireless sensor networks is more difficult than in traditional networks owing to sensor network characteristics such as unreliable communication, limited resources, and unattended operation. For these reasons, various authentication schemes have been proposed to provide secure and efficient communication. In 2016, Park et al. proposed a secure biometric-based authentication scheme with smart card revocation/reissue for wireless sensor networks. However, we found that their scheme was still insecure against impersonation attack, and had a problem in the smart card revocation/reissue phase. In this paper, we show how an adversary can impersonate a legitimate user or sensor node, illegal smart card revocation/reissue and prove that Park et al.'s scheme fails to provide revocation/reissue. In addition, we propose an enhanced scheme that provides efficiency, as well as anonymity and security. Finally, we provide security and performance analysis between previous schemes and the proposed scheme, and provide formal analysis based on the random oracle model. The results prove that the proposed scheme can solve the weaknesses of impersonation attack and other security flaws in the security analysis section. Furthermore, performance analysis shows that the computational cost is lower than the previous scheme.

  6. Scheme of adaptive polarization filtering based on Kalman model

    Institute of Scientific and Technical Information of China (English)

    Song Lizhong; Qi Haiming; Qiao Xiaolin; Meng Xiande

    2006-01-01

    A new kind of adaptive polarization filtering algorithm in order to suppress the angle cheating interference for the active guidance radar is presented. The polarization characteristic of the interference is dynamically tracked by using Kalman estimator under variable environments with time. The polarization filter parameters are designed according to the polarization characteristic of the interference, and the polarization filtering is finished in the target cell. The system scheme of adaptive polarization filter is studied and the tracking performance of polarization filter and improvement of angle measurement precision are simulated. The research results demonstrate this technology can effectively suppress the angle cheating interference in guidance radar and is feasible in engineering.

  7. Adaptation of failure scenario based resilience schemes toward availability guarantees

    Science.gov (United States)

    Scheffel, Matthias

    2006-07-01

    Various resilience schemes have been proposed to allow for fault-tolerant transport networks. Their common aim is to survive certain failure patterns such as node or span failures by providing alternative transmission paths. However, network operators guarantee the resulting network reliability in terms of service availability to their business customers. A maximum duration of service disruption per year must not be exceeded. We investigate an optimal design of resilient network configurations that adapts to end-to-end availability requirements. We formulate an integer linear program that minimizes the resource utilization and investigate a case study.

  8. Bayesian outcome-based strategy classification.

    Science.gov (United States)

    Lee, Michael D

    2016-03-01

    Hilbig and Moshagen (Psychonomic Bulletin & Review, 21, 1431-1443, 2014) recently developed a method for making inferences about the decision processes people use in multi-attribute forced choice tasks. Their paper makes a number of worthwhile theoretical and methodological contributions. Theoretically, they provide an insightful psychological motivation for a probabilistic extension of the widely-used "weighted additive" (WADD) model, and show how this model, as well as other important models like "take-the-best" (TTB), can and should be expressed in terms of meaningful priors. Methodologically, they develop an inference approach based on the Minimum Description Length (MDL) principles that balances both the goodness-of-fit and complexity of the decision models they consider. This paper aims to preserve these useful contributions, but provide a complementary Bayesian approach with some theoretical and methodological advantages. We develop a simple graphical model, implemented in JAGS, that allows for fully Bayesian inferences about which models people use to make decisions. To demonstrate the Bayesian approach, we apply it to the models and data considered by Hilbig and Moshagen (Psychonomic Bulletin & Review, 21, 1431-1443, 2014), showing how a prior predictive analysis of the models, and posterior inferences about which models people use and the parameter settings at which they use them, can contribute to our understanding of human decision making.

  9. An Improved Dynamic ID-Based Remote User Authentication with Key Agreement Scheme

    Directory of Open Access Journals (Sweden)

    Juan Qu

    2013-01-01

    Full Text Available In recent years, several dynamic ID-based remote user authentication schemes have been proposed. In 2012, Wen and Li proposed a dynamic ID-based remote user authentication with key agreement scheme. They claimed that their scheme can resist impersonation attack and insider attack and provide anonymity for the users. However, we will show that Wen and Li's scheme cannot withstand insider attack and forward secrecy, does not provide anonymity for the users, and inefficiency for error password login. In this paper, we propose a novel ECC-based remote user authentication scheme which is immune to various known types of attack and is more secure and practical for mobile clients.

  10. Renewing membership in three community-based health insurance schemes in rural India

    NARCIS (Netherlands)

    P. Panda (Pradeep); A. Chakraborty (Arpita); W.A. Raza (Wameq); A.S. Bedi (Arjun Singh)

    2015-01-01

    textabstractLow renewal rate is a key challenge facing the sustainability of Community-based Health Insurance (CBHI) schemes. While there is a large literature on initial enrolment into such schemes, there is limited evidence on the factors that impede renewal. This paper uses longitudinal data to

  11. A new Identity Based Encryption (IBE) scheme using extended Chebyshev polynomial over finite fields Zp

    International Nuclear Information System (INIS)

    Benasser Algehawi, Mohammed; Samsudin, Azman

    2010-01-01

    We present a method to extract key pairs needed for the Identity Based Encryption (IBE) scheme from extended Chebyshev polynomial over finite fields Z p . Our proposed scheme relies on the hard problem and the bilinear property of the extended Chebyshev polynomial over Z p . The proposed system is applicable, secure, and reliable.

  12. An Ultra-Low-Latency Geo-Routing Scheme for Team-Based Unmanned Vehicular Applications

    KAUST Repository

    Bader, Ahmed; Alouini, Mohamed-Slim

    2016-01-01

    Results and lessons learned from the implementation of a novel ultra low-latency geo-routing scheme are presented in this paper. The geo-routing scheme is intended for team-based mobile systems whereby a cluster of unmanned autonomous vehicles

  13. Dropping out of Ethiopia’s Community Based Health Insurance scheme

    NARCIS (Netherlands)

    A.D. Mebratie (Anagaw); R.A. Sparrow (Robert); Z.Y. Debebe (Zelalem); G. Alemu (Getnet ); A.S. Bedi (Arjun Singh)

    2014-01-01

    textabstractLow contract renewal rates have been identified as one of the challenges facing the development of community based health insurance schemes (CBHI). This paper uses longitudinal household survey data to examine dropout in the case of Ethiopia’s pilot CBHI scheme, which saw enrolment

  14. XMSS : a practical forward secure signature scheme based on minimal security assumptions

    NARCIS (Netherlands)

    Buchmann, Johannes; Dahmen, Erik; Hülsing, Andreas; Yang, B.-Y.

    2011-01-01

    We present the hash-based signature scheme XMSS. It is the first provably (forward) secure and practical signature scheme with minimal security requirements: a pseudorandom and a second preimage resistant (hash) function family. Its signature size is reduced to less than 25% compared to the best

  15. Optical beam classification using deep learning: a comparison with rule- and feature-based classification

    Science.gov (United States)

    Alom, Md. Zahangir; Awwal, Abdul A. S.; Lowe-Webb, Roger; Taha, Tarek M.

    2017-08-01

    Vector Machine (SVM). The experimental results show around 96% classification accuracy using CNN; the CNN approach also provides comparable recognition results compared to the present feature-based off-normal detection. The feature-based solution was developed to capture the expertise of a human expert in classifying the images. The misclassified results are further studied to explain the differences and discover any discrepancies or inconsistencies in current classification.

  16. 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

  17. System for Anonymous Data Collection Based on Group Signature Scheme

    Directory of Open Access Journals (Sweden)

    David Troják

    2016-01-01

    Full Text Available This paper deals with an anonymous data collection in the Internet of Things (IoT. the privacy and anonymity of the data source is important for many IoT applications, such as in agriculture, health, and automotive. the proposed data‑collection system provides anonymity for the data sources by applying a cooperation group scheme. the group scheme also provides a low power consumption. the system is built upon the Tor (The Onion Router anonymous network, which is a part of the Internet darknet. the proposed system was designed for the Android devices on the client side and for Java environment on the server side. We evaluated the anonymous data collection in a real‑use scenario that covers selected data acquisition (e.g. signal strength from smartphones triggered by their geographical location change. the results show that the proposed system provides the sufficient data source anonymity, an effective revocation, a low computational cost and a low overhead.

  18. A Chinese text classification system based on Naive Bayes algorithm

    Directory of Open Access Journals (Sweden)

    Cui Wei

    2016-01-01

    Full Text Available In this paper, aiming at the characteristics of Chinese text classification, using the ICTCLAS(Chinese lexical analysis system of Chinese academy of sciences for document segmentation, and for data cleaning and filtering the Stop words, using the information gain and document frequency feature selection algorithm to document feature selection. Based on this, based on the Naive Bayesian algorithm implemented text classifier , and use Chinese corpus of Fudan University has carried on the experiment and analysis on the system.

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

    Science.gov (United States)

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

    2015-03-01

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

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

    Directory of Open Access Journals (Sweden)

    Muhammad Usman

    2015-05-01

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

  1. Emotional textile image classification based on cross-domain convolutional sparse autoencoders with feature selection

    Science.gov (United States)

    Li, Zuhe; Fan, Yangyu; Liu, Weihua; Yu, Zeqi; Wang, Fengqin

    2017-01-01

    We aim to apply sparse autoencoder-based unsupervised feature learning to emotional semantic analysis for textile images. To tackle the problem of limited training data, we present a cross-domain feature learning scheme for emotional textile image classification using convolutional autoencoders. We further propose a correlation-analysis-based feature selection method for the weights learned by sparse autoencoders to reduce the number of features extracted from large size images. First, we randomly collect image patches on an unlabeled image dataset in the source domain and learn local features with a sparse autoencoder. We then conduct feature selection according to the correlation between different weight vectors corresponding to the autoencoder's hidden units. We finally adopt a convolutional neural network including a pooling layer to obtain global feature activations of textile images in the target domain and send these global feature vectors into logistic regression models for emotional image classification. The cross-domain unsupervised feature learning method achieves 65% to 78% average accuracy in the cross-validation experiments corresponding to eight emotional categories and performs better than conventional methods. Feature selection can reduce the computational cost of global feature extraction by about 50% while improving classification performance.

  2. An Efficient Code-Based Threshold Ring Signature Scheme with a Leader-Participant Model

    Directory of Open Access Journals (Sweden)

    Guomin Zhou

    2017-01-01

    Full Text Available Digital signature schemes with additional properties have broad applications, such as in protecting the identity of signers allowing a signer to anonymously sign a message in a group of signers (also known as a ring. While these number-theoretic problems are still secure at the time of this research, the situation could change with advances in quantum computing. There is a pressing need to design PKC schemes that are secure against quantum attacks. In this paper, we propose a novel code-based threshold ring signature scheme with a leader-participant model. A leader is appointed, who chooses some shared parameters for other signers to participate in the signing process. This leader-participant model enhances the performance because every participant including the leader could execute the decoding algorithm (as a part of signing process upon receiving the shared parameters from the leader. The time complexity of our scheme is close to Courtois et al.’s (2001 scheme. The latter is often used as a basis to construct other types of code-based signature schemes. Moreover, as a threshold ring signature scheme, our scheme is as efficient as the normal code-based ring signature.

  3. 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

  4. Security enhancement of a biometric based authentication scheme for telecare medicine information systems with nonce.

    Science.gov (United States)

    Mishra, Dheerendra; Mukhopadhyay, Sourav; Kumari, Saru; Khan, Muhammad Khurram; Chaturvedi, Ankita

    2014-05-01

    Telecare medicine information systems (TMIS) present the platform to deliver clinical service door to door. The technological advances in mobile computing are enhancing the quality of healthcare and a user can access these services using its mobile device. However, user and Telecare system communicate via public channels in these online services which increase the security risk. Therefore, it is required to ensure that only authorized user is accessing the system and user is interacting with the correct system. The mutual authentication provides the way to achieve this. Although existing schemes are either vulnerable to attacks or they have higher computational cost while an scalable authentication scheme for mobile devices should be secure and efficient. Recently, Awasthi and Srivastava presented a biometric based authentication scheme for TMIS with nonce. Their scheme only requires the computation of the hash and XOR functions.pagebreak Thus, this scheme fits for TMIS. However, we observe that Awasthi and Srivastava's scheme does not achieve efficient password change phase. Moreover, their scheme does not resist off-line password guessing attack. Further, we propose an improvement of Awasthi and Srivastava's scheme with the aim to remove the drawbacks of their scheme.

  5. A multihop key agreement scheme for wireless ad hoc networks based on channel characteristics.

    Science.gov (United States)

    Hao, Zhuo; Zhong, Sheng; Yu, Nenghai

    2013-01-01

    A number of key agreement schemes based on wireless channel characteristics have been proposed recently. However, previous key agreement schemes require that two nodes which need to agree on a key are within the communication range of each other. Hence, they are not suitable for multihop wireless networks, in which nodes do not always have direct connections with each other. In this paper, we first propose a basic multihop key agreement scheme for wireless ad hoc networks. The proposed basic scheme is resistant to external eavesdroppers. Nevertheless, this basic scheme is not secure when there exist internal eavesdroppers or Man-in-the-Middle (MITM) adversaries. In order to cope with these adversaries, we propose an improved multihop key agreement scheme. We show that the improved scheme is secure against internal eavesdroppers and MITM adversaries in a single path. Both performance analysis and simulation results demonstrate that the improved scheme is efficient. Consequently, the improved key agreement scheme is suitable for multihop wireless ad hoc networks.

  6. Group-Based Active Learning of Classification Models.

    Science.gov (United States)

    Luo, Zhipeng; Hauskrecht, Milos

    2017-05-01

    Learning of classification models from real-world data often requires additional human expert effort to annotate the data. However, this process can be rather costly and finding ways of reducing the human annotation effort is critical for this task. The objective of this paper is to develop and study new ways of providing human feedback for efficient learning of classification models by labeling groups of examples. Briefly, unlike traditional active learning methods that seek feedback on individual examples, we develop a new group-based active learning framework that solicits label information on groups of multiple examples. In order to describe groups in a user-friendly way, conjunctive patterns are used to compactly represent groups. Our empirical study on 12 UCI data sets demonstrates the advantages and superiority of our approach over both classic instance-based active learning work, as well as existing group-based active-learning methods.

  7. Chaotic Dynamical State Variables Selection Procedure Based Image Encryption Scheme

    Directory of Open Access Journals (Sweden)

    Zia Bashir

    2017-12-01

    Full Text Available Nowadays, in the modern digital era, the use of computer technologies such as smartphones, tablets and the Internet, as well as the enormous quantity of confidential information being converted into digital form have resulted in raised security issues. This, in turn, has led to rapid developments in cryptography, due to the imminent need for system security. Low-dimensional chaotic systems have low complexity and key space, yet they achieve high encryption speed. An image encryption scheme is proposed that, without compromising the security, uses reasonable resources. We introduced a chaotic dynamic state variables selection procedure (CDSVSP to use all state variables of a hyper-chaotic four-dimensional dynamical system. As a result, less iterations of the dynamical system are required, and resources are saved, thus making the algorithm fast and suitable for practical use. The simulation results of security and other miscellaneous tests demonstrate that the suggested algorithm excels at robustness, security and high speed encryption.

  8. AN AGENT BASED TRANSACTION PROCESSING SCHEME FOR DISCONNECTED MOBILE NODES

    Directory of Open Access Journals (Sweden)

    J.L. Walter Jeyakumar

    2010-12-01

    Full Text Available We present a mobile transaction framework in which mobile users can share data which is stored in the cache of a mobile agent. This mobile agent is a special mobile node which coordinates the sharing process. The proposed framework allows mobile affiliation work groups to be formed dynamically with a mobile agent and mobile hosts. Using short range wireless communication technology, mobile users can simultaneously access the data from the cache of the mobile agent. The data Access Manager module at the mobile agent enforces concurrency control using cache invalidation technique. This model supports disconnected mobile computing allowing mobile agent to move along with the Mobile Hosts. The proposed Transaction frame work has been simulated in Java 2 and performance of this scheme is compared with existing frame works.

  9. Sparse Parallel MRI Based on Accelerated Operator Splitting Schemes.

    Science.gov (United States)

    Cai, Nian; Xie, Weisi; Su, Zhenghang; Wang, Shanshan; Liang, Dong

    2016-01-01

    Recently, the sparsity which is implicit in MR images has been successfully exploited for fast MR imaging with incomplete acquisitions. In this paper, two novel algorithms are proposed to solve the sparse parallel MR imaging problem, which consists of l 1 regularization and fidelity terms. The two algorithms combine forward-backward operator splitting and Barzilai-Borwein schemes. Theoretically, the presented algorithms overcome the nondifferentiable property in l 1 regularization term. Meanwhile, they are able to treat a general matrix operator that may not be diagonalized by fast Fourier transform and to ensure that a well-conditioned optimization system of equations is simply solved. In addition, we build connections between the proposed algorithms and the state-of-the-art existing methods and prove their convergence with a constant stepsize in Appendix. Numerical results and comparisons with the advanced methods demonstrate the efficiency of proposed algorithms.

  10. Network-based Arbitrated Quantum Signature Scheme with Graph State

    Science.gov (United States)

    Ma, Hongling; Li, Fei; Mao, Ningyi; Wang, Yijun; Guo, Ying

    2017-08-01

    Implementing an arbitrated quantum signature(QAS) through complex networks is an interesting cryptography technology in the literature. In this paper, we propose an arbitrated quantum signature for the multi-user-involved networks, whose topological structures are established by the encoded graph state. The determinative transmission of the shared keys, is enabled by the appropriate stabilizers performed on the graph state. The implementation of this scheme depends on the deterministic distribution of the multi-user-shared graph state on which the encoded message can be processed in signing and verifying phases. There are four parties involved, the signatory Alice, the verifier Bob, the arbitrator Trent and Dealer who assists the legal participants in the signature generation and verification. The security is guaranteed by the entanglement of the encoded graph state which is cooperatively prepared by legal participants in complex quantum networks.

  11. 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

  12. Classification of Hearing Loss Disorders Using Teoae-Based Descriptors

    Science.gov (United States)

    Hatzopoulos, Stavros Dimitris

    Transiently Evoked Otoacoustic Emissions (TEOAE) are signals produced by the cochlea upon stimulation by an acoustic click. Within the context of this dissertation, it was hypothesized that the relationship between the TEOAEs and the functional status of the OHCs provided an opportunity for designing a TEOAE-based clinical procedure that could be used to assess cochlear function. To understand the nature of the TEOAE signals in the time and the frequency domain several different analyses were performed. Using normative Input-Output (IO) curves, short-time FFT analyses and cochlear computer simulations, it was found that for optimization of the hearing loss classification it is necessary to use a complete 20 ms TEOAE segment. It was also determined that various 2-D filtering methods (median and averaging filtering masks, LP-FFT) used to enhance of the TEOAE S/N offered minimal improvement (less than 6 dB per stimulus level). Higher S/N improvements resulted in TEOAE sequences that were over-smoothed. The final classification algorithm was based on a statistical analysis of raw FFT data and when applied to a sample set of clinically obtained TEOAE recordings (from 56 normal and 66 hearing-loss subjects) correctly identified 94.3% of the normal and 90% of the hearing loss subjects, at the 80 dB SPL stimulus level. To enhance the discrimination between the conductive and the sensorineural populations, data from the 68 dB SPL stimulus level were used, which yielded a normal classification of 90.2%, a hearing loss classification of 87.5% and a conductive-sensorineural classification of 87%. Among the hearing-loss populations the best discrimination was obtained in the group of otosclerosis and the worst in the group of acute acoustic trauma.

  13. Comparative Study between Two Schemes of Active-Control-Based Mechatronic Inerter

    Directory of Open Access Journals (Sweden)

    He Lingduo

    2017-01-01

    Full Text Available Based on force-current analogy and velocity-voltage analogy in the theory of electromechanical analogy, the inerter is a device that corresponded to the capacitor completely where conquers the nature restriction of mass, what’s more, it is significant to improve the ratio of the inerter’s inertance to its mass for mechanical networks synthesis. And according to the principle of active-control-based mechatronic inerter, we present two implementation schemes. One was based on linear motor, and the other was based on the ball screw and rotary motor. We introduced the implementation methods and established theoretical model of the two schemes, then compared the ratio of the inerter’s inertance to its mass for the two schemes. Finally, we consider the scheme is better which was based on the ball screw and rotary motor.

  14. Comparison Of Power Quality Disturbances Classification Based On Neural Network

    Directory of Open Access Journals (Sweden)

    Nway Nway Kyaw Win

    2015-07-01

    Full Text Available Abstract Power quality disturbances PQDs result serious problems in the reliability safety and economy of power system network. In order to improve electric power quality events the detection and classification of PQDs must be made type of transient fault. Software analysis of wavelet transform with multiresolution analysis MRA algorithm and feed forward neural network probabilistic and multilayer feed forward neural network based methodology for automatic classification of eight types of PQ signals flicker harmonics sag swell impulse fluctuation notch and oscillatory will be presented. The wavelet family Db4 is chosen in this system to calculate the values of detailed energy distributions as input features for classification because it can perform well in detecting and localizing various types of PQ disturbances. This technique classifies the types of PQDs problem sevents.The classifiers classify and identify the disturbance type according to the energy distribution. The results show that the PNN can analyze different power disturbance types efficiently. Therefore it can be seen that PNN has better classification accuracy than MLFF.

  15. An enhanced biometric-based authentication scheme for telecare medicine information systems using elliptic curve cryptosystem.

    Science.gov (United States)

    Lu, Yanrong; Li, Lixiang; Peng, Haipeng; Yang, Yixian

    2015-03-01

    The telecare medical information systems (TMISs) enable patients to conveniently enjoy telecare services at home. The protection of patient's privacy is a key issue due to the openness of communication environment. Authentication as a typical approach is adopted to guarantee confidential and authorized interaction between the patient and remote server. In order to achieve the goals, numerous remote authentication schemes based on cryptography have been presented. Recently, Arshad et al. (J Med Syst 38(12): 2014) presented a secure and efficient three-factor authenticated key exchange scheme to remedy the weaknesses of Tan et al.'s scheme (J Med Syst 38(3): 2014). In this paper, we found that once a successful off-line password attack that results in an adversary could impersonate any user of the system in Arshad et al.'s scheme. In order to thwart these security attacks, an enhanced biometric and smart card based remote authentication scheme for TMISs is proposed. In addition, the BAN logic is applied to demonstrate the completeness of the enhanced scheme. Security and performance analyses show that our enhanced scheme satisfies more security properties and less computational cost compared with previously proposed schemes.

  16. Structure-based classification and ontology in chemistry

    Directory of Open Access Journals (Sweden)

    Hastings Janna

    2012-04-01

    Full Text Available Abstract Background Recent years have seen an explosion in the availability of data in the chemistry domain. With this information explosion, however, retrieving relevant results from the available information, and organising those results, become even harder problems. Computational processing is essential to filter and organise the available resources so as to better facilitate the work of scientists. Ontologies encode expert domain knowledge in a hierarchically organised machine-processable format. One such ontology for the chemical domain is ChEBI. ChEBI provides a classification of chemicals based on their structural features and a role or activity-based classification. An example of a structure-based class is 'pentacyclic compound' (compounds containing five-ring structures, while an example of a role-based class is 'analgesic', since many different chemicals can act as analgesics without sharing structural features. Structure-based classification in chemistry exploits elegant regularities and symmetries in the underlying chemical domain. As yet, there has been neither a systematic analysis of the types of structural classification in use in chemistry nor a comparison to the capabilities of available technologies. Results We analyze the different categories of structural classes in chemistry, presenting a list of patterns for features found in class definitions. We compare these patterns of class definition to tools which allow for automation of hierarchy construction within cheminformatics and within logic-based ontology technology, going into detail in the latter case with respect to the expressive capabilities of the Web Ontology Language and recent extensions for modelling structured objects. Finally we discuss the relationships and interactions between cheminformatics approaches and logic-based approaches. Conclusion Systems that perform intelligent reasoning tasks on chemistry data require a diverse set of underlying computational

  17. 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

  18. 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.

  19. 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.

  20. SPITZER IRS SPECTRA OF LUMINOUS 8 μm SOURCES IN THE LARGE MAGELLANIC CLOUD: TESTING COLOR-BASED CLASSIFICATIONS

    International Nuclear Information System (INIS)

    Buchanan, Catherine L.; Kastner, Joel H.; Hrivnak, Bruce J.; Sahai, Raghvendra

    2009-01-01

    We present archival Spitzer Infrared Spectrograph (IRS) spectra of 19 luminous 8 μm selected sources in the Large Magellanic Cloud (LMC). The object classes derived from these spectra and from an additional 24 spectra in the literature are compared with classifications based on Two Micron All Sky Survey (2MASS)/MSX (J, H, K, and 8 μm) colors in order to test the 'JHK8' (Kastner et al.) classification scheme. The IRS spectra confirm the classifications of 22 of the 31 sources that can be classified under the JHK8 system. The spectroscopic classification of 12 objects that were unclassifiable in the JHK8 scheme allow us to characterize regions of the color-color diagrams that previously lacked spectroscopic verification, enabling refinements to the JHK8 classification system. The results of these new classifications are consistent with previous results concerning the identification of the most infrared-luminous objects in the LMC. In particular, while the IRS spectra reveal several new examples of asymptotic giant branch (AGB) stars with O-rich envelopes, such objects are still far outnumbered by carbon stars (C-rich AGB stars). We show that Spitzer IRAC/MIPS color-color diagrams provide improved discrimination between red supergiants and oxygen-rich and carbon-rich AGB stars relative to those based on 2MASS/MSX colors. These diagrams will enable the most luminous IR sources in Local Group galaxies to be classified with high confidence based on their Spitzer colors. Such characterizations of stellar populations will continue to be possible during Spitzer's warm mission through the use of IRAC [3.6]-[4.5] and 2MASS colors.

  1. Knowledge-Based Trajectory Error Pattern Method Applied to an Active Force Control Scheme

    Directory of Open Access Journals (Sweden)

    Endra Pitowarno, Musa Mailah, Hishamuddin Jamaluddin

    2012-08-01

    Full Text Available The active force control (AFC method is known as a robust control scheme that dramatically enhances the performance of a robot arm particularly in compensating the disturbance effects. The main task of the AFC method is to estimate the inertia matrix in the feedback loop to provide the correct (motor torque required to cancel out these disturbances. Several intelligent control schemes have already been introduced to enhance the estimation methods of acquiring the inertia matrix such as those using neural network, iterative learning and fuzzy logic. In this paper, we propose an alternative scheme called Knowledge-Based Trajectory Error Pattern Method (KBTEPM to suppress the trajectory track error of the AFC scheme. The knowledge is developed from the trajectory track error characteristic based on the previous experimental results of the crude approximation method. It produces a unique, new and desirable error pattern when a trajectory command is forced. An experimental study was performed using simulation work on the AFC scheme with KBTEPM applied to a two-planar manipulator in which a set of rule-based algorithm is derived. A number of previous AFC schemes are also reviewed as benchmark. The simulation results show that the AFC-KBTEPM scheme successfully reduces the trajectory track error significantly even in the presence of the introduced disturbances.Key Words:  Active force control, estimated inertia matrix, robot arm, trajectory error pattern, knowledge-based.

  2. Gradient Evolution-based Support Vector Machine Algorithm for Classification

    Science.gov (United States)

    Zulvia, Ferani E.; Kuo, R. J.

    2018-03-01

    This paper proposes a classification algorithm based on a support vector machine (SVM) and gradient evolution (GE) algorithms. SVM algorithm has been widely used in classification. However, its result is significantly influenced by the parameters. Therefore, this paper aims to propose an improvement of SVM algorithm which can find the best SVMs’ parameters automatically. The proposed algorithm employs a GE algorithm to automatically determine the SVMs’ parameters. The GE algorithm takes a role as a global optimizer in finding the best parameter which will be used by SVM algorithm. The proposed GE-SVM algorithm is verified using some benchmark datasets and compared with other metaheuristic-based SVM algorithms. The experimental results show that the proposed GE-SVM algorithm obtains better results than other algorithms tested in this paper.

  3. A strategy learning model for autonomous agents based on classification

    Directory of Open Access Journals (Sweden)

    Śnieżyński Bartłomiej

    2015-09-01

    Full Text Available In this paper we propose a strategy learning model for autonomous agents based on classification. In the literature, the most commonly used learning method in agent-based systems is reinforcement learning. In our opinion, classification can be considered a good alternative. This type of supervised learning can be used to generate a classifier that allows the agent to choose an appropriate action for execution. Experimental results show that this model can be successfully applied for strategy generation even if rewards are delayed. We compare the efficiency of the proposed model and reinforcement learning using the farmer-pest domain and configurations of various complexity. In complex environments, supervised learning can improve the performance of agents much faster that reinforcement learning. If an appropriate knowledge representation is used, the learned knowledge may be analyzed by humans, which allows tracking the learning process

  4. Vessel-guided airway segmentation based on voxel classification

    DEFF Research Database (Denmark)

    Lo, Pechin Chien Pau; Sporring, Jon; Ashraf, Haseem

    2008-01-01

    This paper presents a method for improving airway tree segmentation using vessel orientation information. We use the fact that an airway branch is always accompanied by an artery, with both structures having similar orientations. This work is based on a  voxel classification airway segmentation...... method proposed previously. The probability of a voxel belonging to the airway, from the voxel classification method, is augmented with an orientation similarity measure as a criterion for region growing. The orientation similarity measure of a voxel indicates how similar is the orientation...... of the surroundings of a voxel, estimated based on a tube model, is to that of a neighboring vessel. The proposed method is tested on 20 CT images from different subjects selected randomly from a lung cancer screening study. Length of the airway branches from the results of the proposed method are significantly...

  5. A Sieving ANN for Emotion-Based Movie Clip Classification

    Science.gov (United States)

    Watanapa, Saowaluk C.; Thipakorn, Bundit; Charoenkitkarn, Nipon

    Effective classification and analysis of semantic contents are very important for the content-based indexing and retrieval of video database. Our research attempts to classify movie clips into three groups of commonly elicited emotions, namely excitement, joy and sadness, based on a set of abstract-level semantic features extracted from the film sequence. In particular, these features consist of six visual and audio measures grounded on the artistic film theories. A unique sieving-structured neural network is proposed to be the classifying model due to its robustness. The performance of the proposed model is tested with 101 movie clips excerpted from 24 award-winning and well-known Hollywood feature films. The experimental result of 97.8% correct classification rate, measured against the collected human-judges, indicates the great potential of using abstract-level semantic features as an engineered tool for the application of video-content retrieval/indexing.

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

    International Nuclear Information System (INIS)

    Karnop, G.

    1975-01-01

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

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

    Energy Technology Data Exchange (ETDEWEB)

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

    1975-04-01

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

  8. Micro-Doppler Based Classification of Human Aquatic Activities via Transfer Learning of Convolutional Neural Networks

    Directory of Open Access Journals (Sweden)

    Jinhee Park

    2016-11-01

    Full Text Available Accurate classification of human aquatic activities using radar has a variety of potential applications such as rescue operations and border patrols. Nevertheless, the classification of activities on water using radar has not been extensively studied, unlike the case on dry ground, due to its unique challenge. Namely, not only is the radar cross section of a human on water small, but the micro-Doppler signatures are much noisier due to water drops and waves. In this paper, we first investigate whether discriminative signatures could be obtained for activities on water through a simulation study. Then, we show how we can effectively achieve high classification accuracy by applying deep convolutional neural networks (DCNN directly to the spectrogram of real measurement data. From the five-fold cross-validation on our dataset, which consists of five aquatic activities, we report that the conventional feature-based scheme only achieves an accuracy of 45.1%. In contrast, the DCNN trained using only the collected data attains 66.7%, and the transfer learned DCNN, which takes a DCNN pre-trained on a RGB image dataset and fine-tunes the parameters using the collected data, achieves a much higher 80.3%, which is a significant performance boost.

  9. Video event classification and image segmentation based on noncausal multidimensional hidden Markov models.

    Science.gov (United States)

    Ma, Xiang; Schonfeld, Dan; Khokhar, Ashfaq A

    2009-06-01

    In this paper, we propose a novel solution to an arbitrary noncausal, multidimensional hidden Markov model (HMM) for image and video classification. First, we show that the noncausal model can be solved by splitting it into multiple causal HMMs and simultaneously solving each causal HMM using a fully synchronous distributed computing framework, therefore referred to as distributed HMMs. Next we present an approximate solution to the multiple causal HMMs that is based on an alternating updating scheme and assumes a realistic sequential computing framework. The parameters of the distributed causal HMMs are estimated by extending the classical 1-D training and classification algorithms to multiple dimensions. The proposed extension to arbitrary causal, multidimensional HMMs allows state transitions that are dependent on all causal neighbors. We, thus, extend three fundamental algorithms to multidimensional causal systems, i.e., 1) expectation-maximization (EM), 2) general forward-backward (GFB), and 3) Viterbi algorithms. In the simulations, we choose to limit ourselves to a noncausal 2-D model whose noncausality is along a single dimension, in order to significantly reduce the computational complexity. Simulation results demonstrate the superior performance, higher accuracy rate, and applicability of the proposed noncausal HMM framework to image and video classification.

  10. Land Cover and Land Use Classification with TWOPAC: towards Automated Processing for Pixel- and Object-Based Image Classification

    Directory of Open Access Journals (Sweden)

    Stefan Dech

    2012-09-01

    Full Text Available We present a novel and innovative automated processing environment for the derivation of land cover (LC and land use (LU information. This processing framework named TWOPAC (TWinned Object and Pixel based Automated classification Chain enables the standardized, independent, user-friendly, and comparable derivation of LC and LU information, with minimized manual classification labor. TWOPAC allows classification of multi-spectral and multi-temporal remote sensing imagery from different sensor types. TWOPAC enables not only pixel-based classification, but also allows classification based on object-based characteristics. Classification is based on a Decision Tree approach (DT for which the well-known C5.0 code has been implemented, which builds decision trees based on the concept of information entropy. TWOPAC enables automatic generation of the decision tree classifier based on a C5.0-retrieved ascii-file, as well as fully automatic validation of the classification output via sample based accuracy assessment.Envisaging the automated generation of standardized land cover products, as well as area-wide classification of large amounts of data in preferably a short processing time, standardized interfaces for process control, Web Processing Services (WPS, as introduced by the Open Geospatial Consortium (OGC, are utilized. TWOPAC’s functionality to process geospatial raster or vector data via web resources (server, network enables TWOPAC’s usability independent of any commercial client or desktop software and allows for large scale data processing on servers. Furthermore, the components of TWOPAC were built-up using open source code components and are implemented as a plug-in for Quantum GIS software for easy handling of the classification process from the user’s perspective.

  11. A unified classification of alien species based on the magnitude of their environmental impacts.

    Directory of Open Access Journals (Sweden)

    Tim M Blackburn

    2014-05-01

    Full Text Available Species moved by human activities beyond the limits of their native geographic ranges into areas in which they do not naturally occur (termed aliens can cause a broad range of significant changes to recipient ecosystems; however, their impacts vary greatly across species and the ecosystems into which they are introduced. There is therefore a critical need for a standardised method to evaluate, compare, and eventually predict the magnitudes of these different impacts. Here, we propose a straightforward system for classifying alien species according to the magnitude of their environmental impacts, based on the mechanisms of impact used to code species in the International Union for Conservation of Nature (IUCN Global Invasive Species Database, which are presented here for the first time. The classification system uses five semi-quantitative scenarios describing impacts under each mechanism to assign species to different levels of impact-ranging from Minimal to Massive-with assignment corresponding to the highest level of deleterious impact associated with any of the mechanisms. The scheme also includes categories for species that are Not Evaluated, have No Alien Population, or are Data Deficient, and a method for assigning uncertainty to all the classifications. We show how this classification system is applicable at different levels of ecological complexity and different spatial and temporal scales, and embraces existing impact metrics. In fact, the scheme is analogous to the already widely adopted and accepted Red List approach to categorising extinction risk, and so could conceivably be readily integrated with existing practices and policies in many regions.

  12. An encryption scheme based on phase-shifting digital holography and amplitude-phase disturbance

    International Nuclear Information System (INIS)

    Hua Li-Li; Xu Ning; Yang Geng

    2014-01-01

    In this paper, we propose an encryption scheme based on phase-shifting digital interferometry. According to the original system framework, we add a random amplitude mask and replace the Fourier transform by the Fresnel transform. We develop a mathematical model and give a discrete formula based on the scheme, which makes it easy to implement the scheme in computer programming. The experimental results show that the improved system has a better performance in security than the original encryption method. Moreover, it demonstrates a good capability of anti-noise and anti-shear robustness

  13. Cryptanalysis of a computer cryptography scheme based on a filter bank

    International Nuclear Information System (INIS)

    Arroyo, David; Li Chengqing; Li Shujun; Alvarez, Gonzalo

    2009-01-01

    This paper analyzes the security of a recently-proposed signal encryption scheme based on a filter bank. A very critical weakness of this new signal encryption procedure is exploited in order to successfully recover the associated secret key.

  14. Asynchronous error-correcting secure communication scheme based on fractional-order shifting chaotic system

    Science.gov (United States)

    Chao, Luo

    2015-11-01

    In this paper, a novel digital secure communication scheme is firstly proposed. Different from the usual secure communication schemes based on chaotic synchronization, the proposed scheme employs asynchronous communication which avoids the weakness of synchronous systems and is susceptible to environmental interference. Moreover, as to the transmission errors and data loss in the process of communication, the proposed scheme has the ability to be error-checking and error-correcting in real time. In order to guarantee security, the fractional-order complex chaotic system with the shifting of order is utilized to modulate the transmitted signal, which has high nonlinearity and complexity in both frequency and time domains. The corresponding numerical simulations demonstrate the effectiveness and feasibility of the scheme.

  15. A light weight secure image encryption scheme based on chaos & DNA computing

    Directory of Open Access Journals (Sweden)

    Bhaskar Mondal

    2017-10-01

    Full Text Available This paper proposed a new light weight secure cryptographic scheme for secure image communication. In this scheme the plain image is permuted first using a sequence of pseudo random number (PRN and encrypted by DeoxyriboNucleic Acid (DNA computation. Two PRN sequences are generated by a Pseudo Random Number Generator (PRNG based on cross coupled chaotic logistic map using two sets of keys. The first PRN sequence is used for permuting the plain image whereas the second PRN sequence is used for generating random DNA sequence. The number of rounds of permutation and encryption may be variable to increase security. The scheme is proposed for gray label images but the scheme may be extended for color images and text data. Simulation results exhibit that the proposed scheme can defy any kind of attack.

  16. A Sentiment Delivering Estimate Scheme Based on Trust Chain in Mobile Social Network

    Directory of Open Access Journals (Sweden)

    Meizi Li

    2015-01-01

    Full Text Available User sentiment analysis has become a flourishing frontier in data mining mobile social network platform since the mobile social network plays a significant role in users’ daily communication and sentiment interaction. This study studies the scheme of sentiment estimate by using the users’ trustworthy relationships for evaluating sentiment delivering. First, we address an overview of sentiment delivering estimate scheme and propose its related definitions, that is, trust chain among users, sentiment semantics, and sentiment ontology. Second, this study proposes the trust chain model and its evaluation method, which is composed of evaluation of atomic, serial, parallel, and combined trust chains. Then, we propose sentiment modeling method by presenting its modeling rules. Further, we propose the sentiment delivering estimate scheme from two aspects: explicit and implicit sentiment delivering estimate schemes, based on trust chain and sentiment modeling method. Finally, examinations and results are given to further explain effectiveness and feasibility of our scheme.

  17. Optimal Scheme Selection of Agricultural Production Structure Adjustment - Based on DEA Model; Punjab (Pakistan)

    Institute of Scientific and Technical Information of China (English)

    Zeeshan Ahmad; Meng Jun; Muhammad Abdullah; Mazhar Nadeem Ishaq; Majid Lateef; Imran Khan

    2015-01-01

    This paper used the modern evaluation method of DEA (Data Envelopment Analysis) to assess the comparative efficiency and then on the basis of this among multiple schemes chose the optimal scheme of agricultural production structure adjustment. Based on the results of DEA model, we dissected scale advantages of each discretionary scheme or plan. We examined scale advantages of each discretionary scheme, tested profoundly a definitive purpose behind not-DEA efficient, which elucidated the system and methodology to enhance these discretionary plans. At the end, another method had been proposed to rank and select the optimal scheme. The research was important to guide the practice if the modification of agricultural production industrial structure was carried on.

  18. A Non-symmetric Digital Image Secure Communication Scheme Based on Generalized Chaos Synchronization System

    International Nuclear Information System (INIS)

    Zhang Xiaohong; Min Lequan

    2005-01-01

    Based on a generalized chaos synchronization system and a discrete Sinai map, a non-symmetric true color (RGB) digital image secure communication scheme is proposed. The scheme first changes an ordinary RGB digital image with 8 bits into unrecognizable disorder codes and then transforms the disorder codes into an RGB digital image with 16 bits for transmitting. A receiver uses a non-symmetric key to verify the authentication of the received data origin, and decrypts the ciphertext. The scheme can encrypt and decrypt most formatted digital RGB images recognized by computers, and recover the plaintext almost without any errors. The scheme is suitable to be applied in network image communications. The analysis of the key space, sensitivity of key parameters, and correlation of encrypted images imply that this scheme has sound security.

  19. Handover Based IMS Registration Scheme for Next Generation Mobile Networks

    Directory of Open Access Journals (Sweden)

    Shireen Tahira

    2017-01-01

    Full Text Available Next generation mobile networks aim to provide faster speed and more capacity along with energy efficiency to support video streaming and massive data sharing in social and communication networks. In these networks, user equipment has to register with IP Multimedia Subsystem (IMS which promises quality of service to the mobile users that frequently move across different access networks. After each handover caused due to mobility, IMS provides IPSec Security Association establishment and authentication phases. The main issue is that unnecessary reregistration after every handover results in latency and communication overhead. To tackle these issues, this paper presents a lightweight Fast IMS Mobility (FIM registration scheme that avoids unnecessary conventional registration phases such as security associations, authentication, and authorization. FIM maintains a flag to avoid deregistration and sends a subsequent message to provide necessary parameters to IMS servers after mobility. It also handles the change of IP address for user equipment and transferring the security associations from old to new servers. We have validated the performance of FIM by developing a testbed consisting of IMS servers and user equipment. The experimental results demonstrate the performance supremacy of FIM. It reduces media disruption time, number of messages, and packet loss up to 67%, 100%, and 61%, respectively, as compared to preliminaries.

  20. Communication-based fault handling scheme for ungrounded distribution systems

    International Nuclear Information System (INIS)

    Yang, X.; Lim, S.I.; Lee, S.J.; Choi, M.S.

    2006-01-01

    The requirement for high quality and highly reliable power supplies has been increasing as a result of increasing demand for power. At the time of a fault occurrence in a distribution system, some protection method would be dedicated to fault section isolation and service restoration. However, if there are many outage areas when the protection method is performed, it is an inconvenience to the customer. A conventional method to determine a fault section in ungrounded systems requires many successive outage invocations. This paper proposed an efficient fault section isolation method and service restoration method for single line-to-ground fault in an ungrounded distribution system that was faster than the conventional one using the information exchange between connected feeders. The proposed algorithm could be performed without any power supply interruption and could decrease the number of switching operations, so that customers would not experience outages very frequently. The method involved the use of an intelligent communication method and a sequential switching control scheme. The proposed algorithm was also applied in both a single-tie and multi-tie distribution system. This proposed algorithm has been verified through fault simulations in a simple model of ungrounded multi-tie distribution system. The method proposed in this paper was proven to offer more efficient fault identification and much less outage time than the conventional method. The proposed method could contribute to a system design since it is valid in multi-tie systems. 5 refs., 2 tabs., 8 figs

  1. A new gammagraphic and functional-based classification for hyperthyroidism

    International Nuclear Information System (INIS)

    Sanchez, J.; Lamata, F.; Cerdan, R.; Agilella, V.; Gastaminza, R.; Abusada, R.; Gonzales, M.; Martinez, M.

    2000-01-01

    The absence of an universal classification for hyperthyroidism's (HT), give rise to inadequate interpretation of series and trials, and prevents decision making. We offer a tentative classification based on gammagraphic and functional findings. Clinical records from patients who underwent thyroidectomy in our Department since 1967 to 1997 were reviewed. Those with functional measurements of hyperthyroidism were considered. All were managed according to the same preestablished guidelines. HT was the surgical indication in 694 (27,1%) of the 2559 thyroidectomy. Based on gammagraphic studies, we classified HTs in: parenchymatous increased-uptake, which could be diffuse, diffuse with cold nodules or diffuse with at least one nodule, and nodular increased-uptake (Autonomous Functioning Thyroid Nodes-AFTN), divided into solitary AFTN or toxic adenoma and multiple AFTN o toxic multi-nodular goiter. This gammagraphic-based classification in useful and has high sensitivity to detect these nodules assessing their activity, allowing us to make therapeutic decision making and, in some cases, to choose surgical technique. (authors)

  2. An Improved Timestamp-Based Password Authentication Scheme Using Smart Cards

    OpenAIRE

    Pathan, Al-Sakib Khan; Hong, Choong Seon

    2007-01-01

    With the recent proliferation of distributed systems and networking, remote authentication has become a crucial task in many networking applications. Various schemes have been proposed so far for the two-party remote authentication; however, some of them have been proved to be insecure. In this paper, we propose an efficient timestamp-based password authentication scheme using smart cards. We show various types of forgery attacks against a previously proposed timestamp-based password authenti...

  3. An efficient and secure dynamic ID-based authentication scheme for telecare medical information systems.

    Science.gov (United States)

    Chen, Hung-Ming; Lo, Jung-Wen; Yeh, Chang-Kuo

    2012-12-01

    The rapidly increased availability of always-on broadband telecommunication environments and lower-cost vital signs monitoring devices bring the advantages of telemedicine directly into the patient's home. Hence, the control of access to remote medical servers' resources has become a crucial challenge. A secure authentication scheme between the medical server and remote users is therefore needed to safeguard data integrity, confidentiality and to ensure availability. Recently, many authentication schemes that use low-cost mobile devices have been proposed to meet these requirements. In contrast to previous schemes, Khan et al. proposed a dynamic ID-based remote user authentication scheme that reduces computational complexity and includes features such as a provision for the revocation of lost or stolen smart cards and a time expiry check for the authentication process. However, Khan et al.'s scheme has some security drawbacks. To remedy theses, this study proposes an enhanced authentication scheme that overcomes the weaknesses inherent in Khan et al.'s scheme and demonstrated this scheme is more secure and robust for use in a telecare medical information system.

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

    DEFF Research Database (Denmark)

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

    2013-01-01

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

  5. Feature extraction based on extended multi-attribute profiles and sparse autoencoder for remote sensing image classification

    Science.gov (United States)

    Teffahi, Hanane; Yao, Hongxun; Belabid, Nasreddine; Chaib, Souleyman

    2018-02-01

    The satellite images with very high spatial resolution have been recently widely used in image classification topic as it has become challenging task in remote sensing field. Due to a number of limitations such as the redundancy of features and the high dimensionality of the data, different classification methods have been proposed for remote sensing images classification particularly the methods using feature extraction techniques. This paper propose a simple efficient method exploiting the capability of extended multi-attribute profiles (EMAP) with sparse autoencoder (SAE) for remote sensing image classification. The proposed method is used to classify various remote sensing datasets including hyperspectral and multispectral images by extracting spatial and spectral features based on the combination of EMAP and SAE by linking them to kernel support vector machine (SVM) for classification. Experiments on new hyperspectral image "Huston data" and multispectral image "Washington DC data" shows that this new scheme can achieve better performance of feature learning than the primitive features, traditional classifiers and ordinary autoencoder and has huge potential to achieve higher accuracy for classification in short running time.

  6. GIS/RS-based Rapid Reassessment for Slope Land Capability Classification

    Science.gov (United States)

    Chang, T. Y.; Chompuchan, C.

    2014-12-01

    Farmland resources in Taiwan are limited because about 73% is mountainous and slope land. Moreover, the rapid urbanization and dense population resulted in the highly developed flat area. Therefore, the utilization of slope land for agriculture is more needed. In 1976, "Slope Land Conservation and Utilization Act" was promulgated to regulate the slope land utilization. Consequently, slope land capability was categorized into Class I-IV according to 4 criteria, i.e., average land slope, effective soil depth, degree of soil erosion, and parent rock. The slope land capability Class I-VI are suitable for cultivation and pasture. Whereas, Class V should be used for forestry purpose and Class VI should be the conservation land which requires intensive conservation practices. The field survey was conducted to categorize each land unit as the classification scheme. The landowners may not allow to overuse land capability limitation. In the last decade, typhoons and landslides frequently devastated in Taiwan. The rapid post-disaster reassessment of the slope land capability classification is necessary. However, the large-scale disaster on slope land is the constraint of field investigation. This study focused on using satellite remote sensing and GIS as the rapid re-evaluation method. Chenyulan watershed in Nantou County, Taiwan was selected to be a case study area. Grid-based slope derivation, topographic wetness index (TWI) and USLE soil loss calculation were used to classify slope land capability. The results showed that GIS-based classification give an overall accuracy of 68.32%. In addition, the post-disaster areas of Typhoon Morakot in 2009, which interpreted by SPOT satellite imageries, were suggested to classify as the conservation lands. These tools perform better in the large coverage post-disaster update for slope land capability classification and reduce time-consuming, manpower and material resources to the field investigation.

  7. Changing Histopathological Diagnostics by Genome-Based Tumor Classification

    Directory of Open Access Journals (Sweden)

    Michael Kloth

    2014-05-01

    Full Text Available Traditionally, tumors are classified by histopathological criteria, i.e., based on their specific morphological appearances. Consequently, current therapeutic decisions in oncology are strongly influenced by histology rather than underlying molecular or genomic aberrations. The increase of information on molecular changes however, enabled by the Human Genome Project and the International Cancer Genome Consortium as well as the manifold advances in molecular biology and high-throughput sequencing techniques, inaugurated the integration of genomic information into disease classification. Furthermore, in some cases it became evident that former classifications needed major revision and adaption. Such adaptations are often required by understanding the pathogenesis of a disease from a specific molecular alteration, using this molecular driver for targeted and highly effective therapies. Altogether, reclassifications should lead to higher information content of the underlying diagnoses, reflecting their molecular pathogenesis and resulting in optimized and individual therapeutic decisions. The objective of this article is to summarize some particularly important examples of genome-based classification approaches and associated therapeutic concepts. In addition to reviewing disease specific markers, we focus on potentially therapeutic or predictive markers and the relevance of molecular diagnostics in disease monitoring.

  8. G0-WISHART Distribution Based Classification from Polarimetric SAR Images

    Science.gov (United States)

    Hu, G. C.; Zhao, Q. H.

    2017-09-01

    Enormous scientific and technical developments have been carried out to further improve the remote sensing for decades, particularly Polarimetric Synthetic Aperture Radar(PolSAR) technique, so classification method based on PolSAR images has getted much more attention from scholars and related department around the world. The multilook polarmetric G0-Wishart model is a more flexible model which describe homogeneous, heterogeneous and extremely heterogeneous regions in the image. Moreover, the polarmetric G0-Wishart distribution dose not include the modified Bessel function of the second kind. It is a kind of simple statistical distribution model with less parameter. To prove its feasibility, a process of classification has been tested with the full-polarized Synthetic Aperture Radar (SAR) image by the method. First, apply multilook polarimetric SAR data process and speckle filter to reduce speckle influence for classification result. Initially classify the image into sixteen classes by H/A/α decomposition. Using the ICM algorithm to classify feature based on the G0-Wshart distance. Qualitative and quantitative results show that the proposed method can classify polaimetric SAR data effectively and efficiently.

  9. Histological image classification using biologically interpretable shape-based features

    International Nuclear Information System (INIS)

    Kothari, Sonal; Phan, John H; Young, Andrew N; Wang, May D

    2013-01-01

    Automatic cancer diagnostic systems based on histological image classification are important for improving therapeutic decisions. Previous studies propose textural and morphological features for such systems. These features capture patterns in histological images that are useful for both cancer grading and subtyping. However, because many of these features lack a clear biological interpretation, pathologists may be reluctant to adopt these features for clinical diagnosis. We examine the utility of biologically interpretable shape-based features for classification of histological renal tumor images. Using Fourier shape descriptors, we extract shape-based features that capture the distribution of stain-enhanced cellular and tissue structures in each image and evaluate these features using a multi-class prediction model. We compare the predictive performance of the shape-based diagnostic model to that of traditional models, i.e., using textural, morphological and topological features. The shape-based model, with an average accuracy of 77%, outperforms or complements traditional models. We identify the most informative shapes for each renal tumor subtype from the top-selected features. Results suggest that these shapes are not only accurate diagnostic features, but also correlate with known biological characteristics of renal tumors. Shape-based analysis of histological renal tumor images accurately classifies disease subtypes and reveals biologically insightful discriminatory features. This method for shape-based analysis can be extended to other histological datasets to aid pathologists in diagnostic and therapeutic decisions

  10. On the security flaws in ID-based password authentication schemes for telecare medical information systems.

    Science.gov (United States)

    Mishra, Dheerendra

    2015-01-01

    Telecare medical information systems (TMIS) enable healthcare delivery services. However, access of these services via public channel raises security and privacy issues. In recent years, several smart card based authentication schemes have been introduced to ensure secure and authorized communication between remote entities over the public channel for the (TMIS). We analyze the security of some of the recently proposed authentication schemes of Lin, Xie et al., Cao and Zhai, and Wu and Xu's for TMIS. Unfortunately, we identify that these schemes failed to satisfy desirable security attributes. In this article we briefly discuss four dynamic ID-based authentication schemes and demonstrate their failure to satisfy desirable security attributes. The study is aimed to demonstrate how inefficient password change phase can lead to denial of server scenario for an authorized user, and how an inefficient login phase causes the communication and computational overhead and decrease the performance of the system. Moreover, we show the vulnerability of Cao and Zhai's scheme to known session specific temporary information attack, vulnerability of Wu and Xu's scheme to off-line password guessing attack, and vulnerability of Xie et al.'s scheme to untraceable on-line password guessing attack.

  11. Novel neural networks-based fault tolerant control scheme with fault alarm.

    Science.gov (United States)

    Shen, Qikun; Jiang, Bin; Shi, Peng; Lim, Cheng-Chew

    2014-11-01

    In this paper, the problem of adaptive active fault-tolerant control for a class of nonlinear systems with unknown actuator fault is investigated. The actuator fault is assumed to have no traditional affine appearance of the system state variables and control input. The useful property of the basis function of the radial basis function neural network (NN), which will be used in the design of the fault tolerant controller, is explored. Based on the analysis of the design of normal and passive fault tolerant controllers, by using the implicit function theorem, a novel NN-based active fault-tolerant control scheme with fault alarm is proposed. Comparing with results in the literature, the fault-tolerant control scheme can minimize the time delay between fault occurrence and accommodation that is called the time delay due to fault diagnosis, and reduce the adverse effect on system performance. In addition, the FTC scheme has the advantages of a passive fault-tolerant control scheme as well as the traditional active fault-tolerant control scheme's properties. Furthermore, the fault-tolerant control scheme requires no additional fault detection and isolation model which is necessary in the traditional active fault-tolerant control scheme. Finally, simulation results are presented to demonstrate the efficiency of the developed techniques.

  12. Design and implementation based on the classification protection vulnerability scanning system

    International Nuclear Information System (INIS)

    Wang Chao; Lu Zhigang; Liu Baoxu

    2010-01-01

    With the application and spread of the classification protection, Network Security Vulnerability Scanning should consider the efficiency and the function expansion. It proposes a kind of a system vulnerability from classification protection, and elaborates the design and implementation of a vulnerability scanning system based on vulnerability classification plug-in technology and oriented classification protection. According to the experiment, the application of classification protection has good adaptability and salability with the system, and it also approves the efficiency of scanning. (authors)

  13. Soil classification basing on the spectral characteristics of topsoil samples

    Science.gov (United States)

    Liu, Huanjun; Zhang, Xiaokang; Zhang, Xinle

    2016-04-01

    Soil taxonomy plays an important role in soil utility and management, but China has only course soil map created based on 1980s data. New technology, e.g. spectroscopy, could simplify soil classification. The study try to classify soils basing on the spectral characteristics of topsoil samples. 148 topsoil samples of typical soils, including Black soil, Chernozem, Blown soil and Meadow soil, were collected from Songnen plain, Northeast China, and the room spectral reflectance in the visible and near infrared region (400-2500 nm) were processed with weighted moving average, resampling technique, and continuum removal. Spectral indices were extracted from soil spectral characteristics, including the second absorption positions of spectral curve, the first absorption vale's area, and slope of spectral curve at 500-600 nm and 1340-1360 nm. Then K-means clustering and decision tree were used respectively to build soil classification model. The results indicated that 1) the second absorption positions of Black soil and Chernozem were located at 610 nm and 650 nm respectively; 2) the spectral curve of the meadow is similar to its adjacent soil, which could be due to soil erosion; 3) decision tree model showed higher classification accuracy, and accuracy of Black soil, Chernozem, Blown soil and Meadow are 100%, 88%, 97%, 50% respectively, and the accuracy of Blown soil could be increased to 100% by adding one more spectral index (the first two vole's area) to the model, which showed that the model could be used for soil classification and soil map in near future.

  14. A Fingerprint Encryption Scheme Based on Irreversible Function and Secure Authentication

    Directory of Open Access Journals (Sweden)

    Yijun Yang

    2015-01-01

    Full Text Available A fingerprint encryption scheme based on irreversible function has been designed in this paper. Since the fingerprint template includes almost the entire information of users’ fingerprints, the personal authentication can be determined only by the fingerprint features. This paper proposes an irreversible transforming function (using the improved SHA1 algorithm to transform the original minutiae which are extracted from the thinned fingerprint image. Then, Chinese remainder theorem is used to obtain the biokey from the integration of the transformed minutiae and the private key. The result shows that the scheme has better performance on security and efficiency comparing with other irreversible function schemes.

  15. An image encryption scheme based on the MLNCML system using DNA sequences

    Science.gov (United States)

    Zhang, Ying-Qian; Wang, Xing-Yuan; Liu, Jia; Chi, Ze-Lin

    2016-07-01

    We propose a new image scheme based on the spatiotemporal chaos of the Mixed Linear-Nonlinear Coupled Map Lattices (MLNCML). This spatiotemporal chaotic system has more cryptographic features in dynamics than the system of Coupled Map Lattices (CML). In the proposed scheme, we employ the strategy of DNA computing and one time pad encryption policy, which can enhance the sensitivity to the plaintext and resist differential attack, brute-force attack, statistical attack and plaintext attack. Simulation results and theoretical analysis indicate that the proposed scheme has superior high security.

  16. An Ultra-Low-Latency Geo-Routing Scheme for Team-Based Unmanned Vehicular Applications

    KAUST Repository

    Bader, Ahmed

    2016-02-26

    Results and lessons learned from the implementation of a novel ultra low-latency geo-routing scheme are presented in this paper. The geo-routing scheme is intended for team-based mobile systems whereby a cluster of unmanned autonomous vehicles are deployed to accomplish a critical mission under human supervision. The contention-free nature of the developed scheme lends itself to jointly achieve lower latency and higher throughput. Implementation challenges are presented and corresponding resolutions are discussed herewith. © 2015 IEEE.

  17. Self-match based on polling scheme for passive optical network monitoring

    Science.gov (United States)

    Zhang, Xuan; Guo, Hao; Jia, Xinhong; Liao, Qinghua

    2018-06-01

    We propose a self-match based on polling scheme for passive optical network monitoring. Each end-user is equipped with an optical matcher that exploits only the specific length patchcord and two different fiber Bragg gratings with 100% reflectivity. The simple and low-cost scheme can greatly simplify the final recognition processing of the network link status and reduce the sensitivity of the photodetector. We analyze the time-domain relation between reflected pulses and establish the calculation model to evaluate the false alarm rate. The feasibility of the proposed scheme and the validity of the time-domain relation analysis are experimentally demonstrated.

  18. An efficient deterministic secure quantum communication scheme based on cluster states and identity authentication

    International Nuclear Information System (INIS)

    Wen-Jie, Liu; Han-Wu, Chen; Zhi-Qiang, Li; Zhi-Hao, Liu; Wen-Bo, Hu; Ting-Huai, Ma

    2009-01-01

    A novel efficient deterministic secure quantum communication scheme based on four-qubit cluster states and single-photon identity authentication is proposed. In this scheme, the two authenticated users can transmit two bits of classical information per cluster state, and its efficiency of the quantum communication is 1/3, which is approximately 1.67 times that of the previous protocol presented by Wang et al [Chin. Phys. Lett. 23 (2006) 2658]. Security analysis shows the present scheme is secure against intercept-resend attack and the impersonator's attack. Furthermore, it is more economic with present-day techniques and easily processed by a one-way quantum computer. (general)

  19. Operation Modes and Control Schemes for Internet-Based Teleoperation System with Time Delay

    Institute of Scientific and Technical Information of China (English)

    曾庆军; 宋爱国

    2003-01-01

    Teleoperation system plays an important role in executing task under hazard environment. As the computer networks such as the Internet are being used as the communication channel of teleoperation system, varying time delay causes the overall system unstable and reduces the performance of transparency. This paper proposed twelve operation modes with different control schemes for teleoperation on the Internet with time delay. And an optimal operation mode with control scheme was specified for teleoperation with time delay, based on the tradeoff between passivity and transparency properties. It experimentally confirmed the validity of the proposed optimal mode and control scheme by using a simple one DOF master-slave manipulator system.

  20. Immunophenotype Discovery, Hierarchical Organization, and Template-based Classification of Flow Cytometry Samples

    Directory of Open Access Journals (Sweden)

    Ariful Azad

    2016-08-01

    Full Text Available We describe algorithms for discovering immunophenotypes from large collections of flow cytometry (FC samples, and using them to organize the samples into a hierarchy based on phenotypic similarity. The hierarchical organization is helpful for effective and robust cytometry data mining, including the creation of collections of cell populations characteristic of different classes of samples, robust classification, and anomaly detection. We summarize a set of samples belonging to a biological class or category with a statistically derived template for the class. Whereas individual samples are represented in terms of their cell populations (clusters, a template consists of generic meta-populations (a group of homogeneous cell populations obtained from the samples in a class that describe key phenotypes shared among all those samples. We organize an FC data collection in a hierarchical data structure that supports the identification of immunophenotypes relevant to clinical diagnosis. A robust template-based classification scheme is also developed, but our primary focus is in the discovery of phenotypic signatures and inter-sample relationships in an FC data collection. This collective analysis approach is more efficient and robust since templates describe phenotypic signatures common to cell populations in several samples, while ignoring noise and small sample-specific variations.We have applied the template-base scheme to analyze several data setsincluding one representing a healthy immune system, and one of Acute Myeloid Leukemia (AMLsamples. The last task is challenging due to the phenotypic heterogeneity of the severalsubtypes of AML. However, we identified thirteen immunophenotypes corresponding to subtypes of AML, and were able to distinguish Acute Promyelocytic Leukemia from other subtypes of AML.

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

    Science.gov (United States)

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

    2011-01-01

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

  2. A Generalized Weight-Based Particle-In-Cell Simulation Scheme

    International Nuclear Information System (INIS)

    Lee, W.W.; Jenkins, T.G.; Ethier, S.

    2010-01-01

    A generalized weight-based particle simulation scheme suitable for simulating magnetized plasmas, where the zeroth-order inhomogeneity is important, is presented. The scheme is an extension of the perturbative simulation schemes developed earlier for particle-in-cell (PIC) simulations. The new scheme is designed to simulate both the perturbed distribution ((delta)f) and the full distribution (full-F) within the same code. The development is based on the concept of multiscale expansion, which separates the scale lengths of the background inhomogeneity from those associated with the perturbed distributions. The potential advantage for such an arrangement is to minimize the particle noise by using (delta)f in the linear stage stage of the simulation, while retaining the flexibility of a full-F capability in the fully nonlinear stage of the development when signals associated with plasma turbulence are at a much higher level than those from the intrinsic particle noise.

  3. A scheme of hidden-structure attribute-based encryption with multiple authorities

    Science.gov (United States)

    Ling, J.; Weng, A. X.

    2018-05-01

    In the most of the CP-ABE schemes with hidden access structure, both all the user attributes and the key generation are managed by only one authority. The key generation efficiency will decrease as the number of user increases, and the data will encounter security issues as the only authority is attacked. We proposed a scheme of hidden-structure attribute-based encryption with multiple authorities, which introduces multiple semi-trusted attribute authorities, avoiding the threat even though one or more authorities are attacked. We also realized user revocation by managing a revocation list. Based on DBDH assumption, we proved that our scheme is of IND-CMA security. The analysis shows that our scheme improves the key generation efficiency.

  4. Multiple image encryption scheme based on pixel exchange operation and vector decomposition

    Science.gov (United States)

    Xiong, Y.; Quan, C.; Tay, C. J.

    2018-02-01

    We propose a new multiple image encryption scheme based on a pixel exchange operation and a basic vector decomposition in Fourier domain. In this algorithm, original images are imported via a pixel exchange operator, from which scrambled images and pixel position matrices are obtained. Scrambled images encrypted into phase information are imported using the proposed algorithm and phase keys are obtained from the difference between scrambled images and synthesized vectors in a charge-coupled device (CCD) plane. The final synthesized vector is used as an input in a random phase encoding (DRPE) scheme. In the proposed encryption scheme, pixel position matrices and phase keys serve as additional private keys to enhance the security of the cryptosystem which is based on a 4-f system. Numerical simulations are presented to demonstrate the feasibility and robustness of the proposed encryption scheme.

  5. Cost-based droop scheme with lower generation costs for microgrids

    DEFF Research Database (Denmark)

    Nutkani, Inam Ullah; Loh, Poh Chiang; Blaabjerg, Frede

    2014-01-01

    -based droop scheme, whose objective is to reduce a generation cost function realised with various DG operating characteristics taken into consideration. Where desired, proportional power sharing based on the DG kVA ratings can also be included, whose disadvantage is a slightly higher generation cost, which...... on the DG kilovolts ampere (kVA) ratings. Other factors like generation costs, efficiencies and emission penalties at different load demands have not been considered. This omission might not be appropriate if different types of DGs are present in the microgrids. As an alternative, this study proposes a cost...... is still lower than that produced by the traditional droop schemes. The proposed droop scheme therefore retains all advantages of the traditional droop schemes, whereas at the same time, keeps its generation cost low. These findings have been validated in experiments....

  6. Radiographic classification for fractures of the fifth metatarsal base

    International Nuclear Information System (INIS)

    Mehlhorn, Alexander T.; Zwingmann, Joern; Hirschmueller, Anja; Suedkamp, Norbert P.; Schmal, Hagen

    2014-01-01

    Avulsion fractures of the fifth metatarsal base (MTB5) are common fore foot injuries. Based on a radiomorphometric analysis reflecting the risk for a secondary displacement, a new classification was developed. A cohort of 95 healthy, sportive, and young patients (age ≤ 50 years) with avulsion fractures of the MTB5 was included in the study and divided into groups with non-displaced, primary-displaced, and secondary-displaced fractures. Radiomorphometric data obtained using standard oblique and dorso-plantar views were analyzed in association with secondary displacement. Based on this, a classification was developed and checked for reproducibility. Fractures with a longer distance between the lateral edge of the styloid process and the lateral fracture step-off and fractures with a more medial joint entry of the fracture line at the MTB5 are at higher risk to displace secondarily. Based on these findings, all fractures were divided into three types: type I with a fracture entry in the lateral third; type II in the middle third; and type III in the medial third of the MTB5. Additionally, the three types were subdivided into an A-type with a fracture displacement <2 mm and a B-type with a fracture displacement ≥ 2 mm. A substantial level of interobserver agreement was found in the assignment of all 95 fractures to the six fracture types (κ = 0.72). The secondary displacement of fractures was confirmed by all examiners in 100 %. Radiomorphometric data may identify fractures at risk for secondary displacement of the MTB5. Based on this, a reliable classification was developed. (orig.)

  7. Radiographic classification for fractures of the fifth metatarsal base

    Energy Technology Data Exchange (ETDEWEB)

    Mehlhorn, Alexander T.; Zwingmann, Joern; Hirschmueller, Anja; Suedkamp, Norbert P.; Schmal, Hagen [University of Freiburg Medical Center, Department of Orthopaedic Surgery, Freiburg (Germany)

    2014-04-15

    Avulsion fractures of the fifth metatarsal base (MTB5) are common fore foot injuries. Based on a radiomorphometric analysis reflecting the risk for a secondary displacement, a new classification was developed. A cohort of 95 healthy, sportive, and young patients (age ≤ 50 years) with avulsion fractures of the MTB5 was included in the study and divided into groups with non-displaced, primary-displaced, and secondary-displaced fractures. Radiomorphometric data obtained using standard oblique and dorso-plantar views were analyzed in association with secondary displacement. Based on this, a classification was developed and checked for reproducibility. Fractures with a longer distance between the lateral edge of the styloid process and the lateral fracture step-off and fractures with a more medial joint entry of the fracture line at the MTB5 are at higher risk to displace secondarily. Based on these findings, all fractures were divided into three types: type I with a fracture entry in the lateral third; type II in the middle third; and type III in the medial third of the MTB5. Additionally, the three types were subdivided into an A-type with a fracture displacement <2 mm and a B-type with a fracture displacement ≥ 2 mm. A substantial level of interobserver agreement was found in the assignment of all 95 fractures to the six fracture types (κ = 0.72). The secondary displacement of fractures was confirmed by all examiners in 100 %. Radiomorphometric data may identify fractures at risk for secondary displacement of the MTB5. Based on this, a reliable classification was developed. (orig.)

  8. Risk Classification and Risk-based Safety and Mission Assurance

    Science.gov (United States)

    Leitner, Jesse A.

    2014-01-01

    Recent activities to revamp and emphasize the need to streamline processes and activities for Class D missions across the agency have led to various interpretations of Class D, including the lumping of a variety of low-cost projects into Class D. Sometimes terms such as Class D minus are used. In this presentation, mission risk classifications will be traced to official requirements and definitions as a measure to ensure that projects and programs align with the guidance and requirements that are commensurate for their defined risk posture. As part of this, the full suite of risk classifications, formal and informal will be defined, followed by an introduction to the new GPR 8705.4 that is currently under review.GPR 8705.4 lays out guidance for the mission success activities performed at the Classes A-D for NPR 7120.5 projects as well as for projects not under NPR 7120.5. Furthermore, the trends in stepping from Class A into higher risk posture classifications will be discussed. The talk will conclude with a discussion about risk-based safety and mission assuranceat GSFC.

  9. Overfitting Reduction of Text Classification Based on AdaBELM

    Directory of Open Access Journals (Sweden)

    Xiaoyue Feng

    2017-07-01

    Full Text Available Overfitting is an important problem in machine learning. Several algorithms, such as the extreme learning machine (ELM, suffer from this issue when facing high-dimensional sparse data, e.g., in text classification. One common issue is that the extent of overfitting is not well quantified. In this paper, we propose a quantitative measure of overfitting referred to as the rate of overfitting (RO and a novel model, named AdaBELM, to reduce the overfitting. With RO, the overfitting problem can be quantitatively measured and identified. The newly proposed model can achieve high performance on multi-class text classification. To evaluate the generalizability of the new model, we designed experiments based on three datasets, i.e., the 20 Newsgroups, Reuters-21578, and BioMed corpora, which represent balanced, unbalanced, and real application data, respectively. Experiment results demonstrate that AdaBELM can reduce overfitting and outperform classical ELM, decision tree, random forests, and AdaBoost on all three text-classification datasets; for example, it can achieve 62.2% higher accuracy than ELM. Therefore, the proposed model has a good generalizability.

  10. Image Classification Based on Convolutional Denoising Sparse Autoencoder

    Directory of Open Access Journals (Sweden)

    Shuangshuang Chen

    2017-01-01

    Full Text Available Image classification aims to group images into corresponding semantic categories. Due to the difficulties of interclass similarity and intraclass variability, it is a challenging issue in computer vision. In this paper, an unsupervised feature learning approach called convolutional denoising sparse autoencoder (CDSAE is proposed based on the theory of visual attention mechanism and deep learning methods. Firstly, saliency detection method is utilized to get training samples for unsupervised feature learning. Next, these samples are sent to the denoising sparse autoencoder (DSAE, followed by convolutional layer and local contrast normalization layer. Generally, prior in a specific task is helpful for the task solution. Therefore, a new pooling strategy—spatial pyramid pooling (SPP fused with center-bias prior—is introduced into our approach. Experimental results on the common two image datasets (STL-10 and CIFAR-10 demonstrate that our approach is effective in image classification. They also demonstrate that none of these three components: local contrast normalization, SPP fused with center-prior, and l2 vector normalization can be excluded from our proposed approach. They jointly improve image representation and classification performance.

  11. Tongue Images Classification Based on Constrained High Dispersal Network

    Directory of Open Access Journals (Sweden)

    Dan Meng

    2017-01-01

    Full Text Available Computer aided tongue diagnosis has a great potential to play important roles in traditional Chinese medicine (TCM. However, the majority of the existing tongue image analyses and classification methods are based on the low-level features, which may not provide a holistic view of the tongue. Inspired by deep convolutional neural network (CNN, we propose a novel feature extraction framework called constrained high dispersal neural networks (CHDNet to extract unbiased features and reduce human labor for tongue diagnosis in TCM. Previous CNN models have mostly focused on learning convolutional filters and adapting weights between them, but these models have two major issues: redundancy and insufficient capability in handling unbalanced sample distribution. We introduce high dispersal and local response normalization operation to address the issue of redundancy. We also add multiscale feature analysis to avoid the problem of sensitivity to deformation. Our proposed CHDNet learns high-level features and provides more classification information during training time, which may result in higher accuracy when predicting testing samples. We tested the proposed method on a set of 267 gastritis patients and a control group of 48 healthy volunteers. Test results show that CHDNet is a promising method in tongue image classification for the TCM study.

  12. An ID-based Blind Signature Scheme from Bilinear Pairings

    OpenAIRE

    B.Umaprasada Rao; K.A.Ajmath

    2010-01-01

    Blind signatures, introduced by Chaum, allow a user to obtain a signature on a message without revealing any thing about the message to the signer. Blind signatures play on important role in plenty of applications such as e-voting, e-cash system where anonymity is of great concern. Identity based(ID-based) public key cryptography can be a good alternative for certified based public key setting, especially when efficient key management and moderate security are required. In this paper, we prop...

  13. Breaking an encryption scheme based on chaotic baker map

    International Nuclear Information System (INIS)

    Alvarez, Gonzalo; Li, Shujun

    2006-01-01

    In recent years, a growing number of cryptosystems based on chaos have been proposed, many of them fundamentally flawed by a lack of robustness and security. This Letter describes the security weaknesses of a recently proposed cryptographic algorithm with chaos at the physical level based on the baker map. It is shown that the security is trivially compromised for practical implementations of the cryptosystem with finite computing precision and for the use of the iteration number n as the secret key. Some possible countermeasures to enhance the security of the chaos-based cryptographic algorithm are also discussed

  14. Land Cover - Minnesota Land Cover Classification System

    Data.gov (United States)

    Minnesota Department of Natural Resources — Land cover data set based on the Minnesota Land Cover Classification System (MLCCS) coding scheme. This data was produced using a combination of aerial photograph...

  15. Efficient demodulation scheme for rolling-shutter-patterning of CMOS image sensor based visible light communications.

    Science.gov (United States)

    Chen, Chia-Wei; Chow, Chi-Wai; Liu, Yang; Yeh, Chien-Hung

    2017-10-02

    Recently even the low-end mobile-phones are equipped with a high-resolution complementary-metal-oxide-semiconductor (CMOS) image sensor. This motivates using a CMOS image sensor for visible light communication (VLC). Here we propose and demonstrate an efficient demodulation scheme to synchronize and demodulate the rolling shutter pattern in image sensor based VLC. The implementation algorithm is discussed. The bit-error-rate (BER) performance and processing latency are evaluated and compared with other thresholding schemes.

  16. Real-time-service-based Distributed Scheduling Scheme for IEEE 802.16j Networks

    OpenAIRE

    Kuo-Feng Huang; Shih-Jung Wu

    2013-01-01

    Supporting Quality of Service (QoS) guarantees for diverse multimedia services is the primary concern for IEEE802.16j networks. A scheduling scheme that satisfies the QoS requirements has become more important for wireless communications. We proposed an adaptive nontransparent-based distributed scheduling scheme (ANDS) for IEEE 802.16j networks. ANDS comprises three major components: Priority Assignment, Resource Allocation, Preserved Bandwidth Adjustment. Different service-type connections p...

  17. An Approach for Leukemia Classification Based on Cooperative Game Theory

    Directory of Open Access Journals (Sweden)

    Atefeh Torkaman

    2011-01-01

    Full Text Available Hematological malignancies are the types of cancer that affect blood, bone marrow and lymph nodes. As these tissues are naturally connected through the immune system, a disease affecting one of them will often affect the others as well. The hematological malignancies include; Leukemia, Lymphoma, Multiple myeloma. Among them, leukemia is a serious malignancy that starts in blood tissues especially the bone marrow, where the blood is made. Researches show, leukemia is one of the common cancers in the world. So, the emphasis on diagnostic techniques and best treatments would be able to provide better prognosis and survival for patients. In this paper, an automatic diagnosis recommender system for classifying leukemia based on cooperative game is presented. Through out this research, we analyze the flow cytometry data toward the classification of leukemia into eight classes. We work on real data set from different types of leukemia that have been collected at Iran Blood Transfusion Organization (IBTO. Generally, the data set contains 400 samples taken from human leukemic bone marrow. This study deals with cooperative game used for classification according to different weights assigned to the markers. The proposed method is versatile as there are no constraints to what the input or output represent. This means that it can be used to classify a population according to their contributions. In other words, it applies equally to other groups of data. The experimental results show the accuracy rate of 93.12%, for classification and compared to decision tree (C4.5 with (90.16% in accuracy. The result demonstrates that cooperative game is very promising to be used directly for classification of leukemia as a part of Active Medical decision support system for interpretation of flow cytometry readout. This system could assist clinical hematologists to properly recognize different kinds of leukemia by preparing suggestions and this could improve the treatment

  18. An approach for leukemia classification based on cooperative game theory.

    Science.gov (United States)

    Torkaman, Atefeh; Charkari, Nasrollah Moghaddam; Aghaeipour, Mahnaz

    2011-01-01

    Hematological malignancies are the types of cancer that affect blood, bone marrow and lymph nodes. As these tissues are naturally connected through the immune system, a disease affecting one of them will often affect the others as well. The hematological malignancies include; Leukemia, Lymphoma, Multiple myeloma. Among them, leukemia is a serious malignancy that starts in blood tissues especially the bone marrow, where the blood is made. Researches show, leukemia is one of the common cancers in the world. So, the emphasis on diagnostic techniques and best treatments would be able to provide better prognosis and survival for patients. In this paper, an automatic diagnosis recommender system for classifying leukemia based on cooperative game is presented. Through out this research, we analyze the flow cytometry data toward the classification of leukemia into eight classes. We work on real data set from different types of leukemia that have been collected at Iran Blood Transfusion Organization (IBTO). Generally, the data set contains 400 samples taken from human leukemic bone marrow. This study deals with cooperative game used for classification according to different weights assigned to the markers. The proposed method is versatile as there are no constraints to what the input or output represent. This means that it can be used to classify a population according to their contributions. In other words, it applies equally to other groups of data. The experimental results show the accuracy rate of 93.12%, for classification and compared to decision tree (C4.5) with (90.16%) in accuracy. The result demonstrates that cooperative game is very promising to be used directly for classification of leukemia as a part of Active Medical decision support system for interpretation of flow cytometry readout. This system could assist clinical hematologists to properly recognize different kinds of leukemia by preparing suggestions and this could improve the treatment of leukemic

  19. PLS-based memory control scheme for enhanced process monitoring

    KAUST Repository

    Harrou, Fouzi

    2017-01-20

    Fault detection is important for safe operation of various modern engineering systems. Partial least square (PLS) has been widely used in monitoring highly correlated process variables. Conventional PLS-based methods, nevertheless, often fail to detect incipient faults. In this paper, we develop new PLS-based monitoring chart, combining PLS with multivariate memory control chart, the multivariate exponentially weighted moving average (MEWMA) monitoring chart. The MEWMA are sensitive to incipient faults in the process mean, which significantly improves the performance of PLS methods and widen their applicability in practice. Using simulated distillation column data, we demonstrate that the proposed PLS-based MEWMA control chart is more effective in detecting incipient fault in the mean of the multivariate process variables, and outperform the conventional PLS-based monitoring charts.

  20. PLS-based memory control scheme for enhanced process monitoring

    KAUST Repository

    Harrou, Fouzi; Sun, Ying

    2017-01-01

    Fault detection is important for safe operation of various modern engineering systems. Partial least square (PLS) has been widely used in monitoring highly correlated process variables. Conventional PLS-based methods, nevertheless, often fail

  1. Automatic classification for mammogram backgrounds based on bi-rads complexity definition and on a multi content analysis framework

    Science.gov (United States)

    Wu, Jie; Besnehard, Quentin; Marchessoux, Cédric

    2011-03-01

    Clinical studies for the validation of new medical imaging devices require hundreds of images. An important step in creating and tuning the study protocol is the classification of images into "difficult" and "easy" cases. This consists of classifying the image based on features like the complexity of the background, the visibility of the disease (lesions). Therefore, an automatic medical background classification tool for mammograms would help for such clinical studies. This classification tool is based on a multi-content analysis framework (MCA) which was firstly developed to recognize image content of computer screen shots. With the implementation of new texture features and a defined breast density scale, the MCA framework is able to automatically classify digital mammograms with a satisfying accuracy. BI-RADS (Breast Imaging Reporting Data System) density scale is used for grouping the mammograms, which standardizes the mammography reporting terminology and assessment and recommendation categories. Selected features are input into a decision tree classification scheme in MCA framework, which is the so called "weak classifier" (any classifier with a global error rate below 50%). With the AdaBoost iteration algorithm, these "weak classifiers" are combined into a "strong classifier" (a classifier with a low global error rate) for classifying one category. The results of classification for one "strong classifier" show the good accuracy with the high true positive rates. For the four categories the results are: TP=90.38%, TN=67.88%, FP=32.12% and FN =9.62%.

  2. Security analysis of a chaotic map-based authentication scheme for telecare medicine information systems.

    Science.gov (United States)

    Yau, Wei-Chuen; Phan, Raphael C-W

    2013-12-01

    Many authentication schemes have been proposed for telecare medicine information systems (TMIS) to ensure the privacy, integrity, and availability of patient records. These schemes are crucial for TMIS systems because otherwise patients' medical records become susceptible to tampering thus hampering diagnosis or private medical conditions of patients could be disclosed to parties who do not have a right to access such information. Very recently, Hao et al. proposed a chaotic map-based authentication scheme for telecare medicine information systems in a recent issue of Journal of Medical Systems. They claimed that the authentication scheme can withstand various attacks and it is secure to be used in TMIS. In this paper, we show that this authentication scheme is vulnerable to key-compromise impersonation attacks, off-line password guessing attacks upon compromising of a smart card, and parallel session attacks. We also exploit weaknesses in the password change phase of the scheme to mount a denial-of-service attack. Our results show that this scheme cannot be used to provide security in a telecare medicine information system.

  3. An Interference Cancellation Scheme for High Reliability Based on MIMO Systems

    Directory of Open Access Journals (Sweden)

    Jae-Hyun Ro

    2018-03-01

    Full Text Available This article proposes a new interference cancellation scheme in a half-duplex based two-path relay system. In the conventional two-path relay system, inter-relay-interference (IRI which severely degrades the error performances at a destination occurs because a source and a relay transmit signals simultaneously at a specific time. The proposed scheme removes the IRI at a relay for higher signal-to-interference plus noise ratio (SINR to receive interference free signal at a destination, unlike the conventional relay system, which removes IRI at a destination. To handle the IRI, the proposed scheme uses multiple-input multiple-output (MIMO signal detection at the relays and it makes low-complexity signal processing at a destination which is a usually mobile user. At the relays, the proposed scheme uses the low-complexity QR decomposition-M algorithm (QRD-M to optimally remove the IRI. Also, for obtaining diversity gain, the proposed scheme uses cyclic delay diversity (CDD to transmit the signals at a source and the relays. In simulation results, the error performance for the proposed scheme is better when the distance between one relay and another relay is low unlike the conventional scheme because the QRD-M detects received signal in order of higher post signal-to-noise ratio (SNR.

  4. SDN-Based Mobile Data Offloading Scheme Using a Femtocell and WiFi Networks

    Directory of Open Access Journals (Sweden)

    Chang-Woo Ahn

    2017-01-01

    Full Text Available Because of the many applications running on smartphones, the load of mobile data traffic on cellular networks is increasing rapidly. A femtocell is a solution to increase the cellular network capacity and coverage. However, because it uses the same frequency bands as a macrocell, interference problems have prevented its widespread adoption. In this paper, we propose a scheme for traffic offloading between femtocells and WiFi networks utilizing software-defined networking (SDN technology. In the proposed offloading scheme, the SDN technology allows a terminal to maintain existing sessions after offloading through a centralized control of the SDN-based equipment. We also propose an offloading target selection scheme based on available bandwidth estimation and an association control mechanism to reduce the femtocell load while ensuring quality of service (QoS in terms of throughput. Experimental results on an actual testbed showed that the proposed offloading scheme provides seamless connectivity and reduces the femtocell load by up to 46% with the aid of the proposed target selection scheme, while ensuring QoS after offloading. We also observed that the proposed target selection scheme offloads 28% more traffic to WiFi networks compared to received signal strength indicator-based target selection in a low background traffic environment.

  5. Threshold-Based Multiple Optical Signal Selection Scheme for Free-Space Optical Wavelength Division Multiplexing Systems

    KAUST Repository

    Nam, Sung Sik; Alouini, Mohamed-Slim; Zhang, Lin; Ko, Young-Chai

    2017-01-01

    We propose a threshold-based multiple optical signal selection scheme (TMOS) for free-space optical wavelength division multiplexing systems. With this scheme, we can obtain higher spectral efficiency while reducing the possible complexity

  6. Classification of Noisy Data: An Approach Based on Genetic Algorithms and Voronoi Tessellation

    DEFF Research Database (Denmark)

    Khan, Abdul Rauf; Schiøler, Henrik; Knudsen, Torben

    Classification is one of the major constituents of the data-mining toolkit. The well-known methods for classification are built on either the principle of logic or statistical/mathematical reasoning for classification. In this article we propose: (1) a different strategy, which is based on the po......Classification is one of the major constituents of the data-mining toolkit. The well-known methods for classification are built on either the principle of logic or statistical/mathematical reasoning for classification. In this article we propose: (1) a different strategy, which is based...

  7. Contaminant classification using cosine distances based on multiple conventional sensors.

    Science.gov (United States)

    Liu, Shuming; Che, Han; Smith, Kate; Chang, Tian

    2015-02-01

    Emergent contamination events have a significant impact on water systems. After contamination detection, it is important to classify the type of contaminant quickly to provide support for remediation attempts. Conventional methods generally either rely on laboratory-based analysis, which requires a long analysis time, or on multivariable-based geometry analysis and sequence analysis, which is prone to being affected by the contaminant concentration. This paper proposes a new contaminant classification method, which discriminates contaminants in a real time manner independent of the contaminant concentration. The proposed method quantifies the similarities or dissimilarities between sensors' responses to different types of contaminants. The performance of the proposed method was evaluated using data from contaminant injection experiments in a laboratory and compared with a Euclidean distance-based method. The robustness of the proposed method was evaluated using an uncertainty analysis. The results show that the proposed method performed better in identifying the type of contaminant than the Euclidean distance based method and that it could classify the type of contaminant in minutes without significantly compromising the correct classification rate (CCR).

  8. Control charts for location based on different sampling schemes

    NARCIS (Netherlands)

    Mehmood, R.; Riaz, M.; Does, R.J.M.M.

    2013-01-01

    Control charts are the most important statistical process control tool for monitoring variations in a process. A number of articles are available in the literature for the X̄ control chart based on simple random sampling, ranked set sampling, median-ranked set sampling (MRSS), extreme-ranked set

  9. Object-based Dimensionality Reduction in Land Surface Phenology Classification

    Directory of Open Access Journals (Sweden)

    Brian E. Bunker

    2016-11-01

    Full Text Available Unsupervised classification or clustering of multi-decadal land surface phenology provides a spatio-temporal synopsis of natural and agricultural vegetation response to environmental variability and anthropogenic activities. Notwithstanding the detailed temporal information available in calibrated bi-monthly normalized difference vegetation index (NDVI and comparable time series, typical pre-classification workflows average a pixel’s bi-monthly index within the larger multi-decadal time series. While this process is one practical way to reduce the dimensionality of time series with many hundreds of image epochs, it effectively dampens temporal variation from both intra and inter-annual observations related to land surface phenology. Through a novel application of object-based segmentation aimed at spatial (not temporal dimensionality reduction, all 294 image epochs from a Moderate Resolution Imaging Spectroradiometer (MODIS bi-monthly NDVI time series covering the northern Fertile Crescent were retained (in homogenous landscape units as unsupervised classification inputs. Given the inherent challenges of in situ or manual image interpretation of land surface phenology classes, a cluster validation approach based on transformed divergence enabled comparison between traditional and novel techniques. Improved intra-annual contrast was clearly manifest in rain-fed agriculture and inter-annual trajectories showed increased cluster cohesion, reducing the overall number of classes identified in the Fertile Crescent study area from 24 to 10. Given careful segmentation parameters, this spatial dimensionality reduction technique augments the value of unsupervised learning to generate homogeneous land surface phenology units. By combining recent scalable computational approaches to image segmentation, future work can pursue new global land surface phenology products based on the high temporal resolution signatures of vegetation index time series.

  10. Improving Cross-Day EEG-Based Emotion Classification Using Robust Principal Component Analysis

    Directory of Open Access Journals (Sweden)

    Yuan-Pin Lin

    2017-07-01

    Full Text Available Constructing a robust emotion-aware analytical framework using non-invasively recorded electroencephalogram (EEG signals has gained intensive attentions nowadays. However, as deploying a laboratory-oriented proof-of-concept study toward real-world applications, researchers are now facing an ecological challenge that the EEG patterns recorded in real life substantially change across days (i.e., day-to-day variability, arguably making the pre-defined predictive model vulnerable to the given EEG signals of a separate day. The present work addressed how to mitigate the inter-day EEG variability of emotional responses with an attempt to facilitate cross-day emotion classification, which was less concerned in the literature. This study proposed a robust principal component analysis (RPCA-based signal filtering strategy and validated its neurophysiological validity and machine-learning practicability on a binary emotion classification task (happiness vs. sadness using a five-day EEG dataset of 12 subjects when participated in a music-listening task. The empirical results showed that the RPCA-decomposed sparse signals (RPCA-S enabled filtering off the background EEG activity that contributed more to the inter-day variability, and predominately captured the EEG oscillations of emotional responses that behaved relatively consistent along days. Through applying a realistic add-day-in classification validation scheme, the RPCA-S progressively exploited more informative features (from 12.67 ± 5.99 to 20.83 ± 7.18 and improved the cross-day binary emotion-classification accuracy (from 58.31 ± 12.33% to 64.03 ± 8.40% as trained the EEG signals from one to four recording days and tested against one unseen subsequent day. The original EEG features (prior to RPCA processing neither achieved the cross-day classification (the accuracy was around chance level nor replicated the encouraging improvement due to the inter-day EEG variability. This result

  11. Distributed Classification of Localization Attacks in Sensor Networks Using Exchange-Based Feature Extraction and Classifier

    Directory of Open Access Journals (Sweden)

    Su-Zhe Wang

    2016-01-01

    Full Text Available Secure localization under different forms of attack has become an essential task in wireless sensor networks. Despite the significant research efforts in detecting the malicious nodes, the problem of localization attack type recognition has not yet been well addressed. Motivated by this concern, we propose a novel exchange-based attack classification algorithm. This is achieved by a distributed expectation maximization extractor integrated with the PECPR-MKSVM classifier. First, the mixed distribution features based on the probabilistic modeling are extracted using a distributed expectation maximization algorithm. After feature extraction, by introducing the theory from support vector machine, an extensive contractive Peaceman-Rachford splitting method is derived to build the distributed classifier that diffuses the iteration calculation among neighbor sensors. To verify the efficiency of the distributed recognition scheme, four groups of experiments were carried out under various conditions. The average success rate of the proposed classification algorithm obtained in the presented experiments for external attacks is excellent and has achieved about 93.9% in some cases. These testing results demonstrate that the proposed algorithm can produce much greater recognition rate, and it can be also more robust and efficient even in the presence of excessive malicious scenario.

  12. Novel UEP LT Coding Scheme with Feedback Based on Different Degree Distributions

    Directory of Open Access Journals (Sweden)

    Li Ya-Fang

    2016-01-01

    Full Text Available Traditional unequal error protection (UEP schemes have some limitations and problems, such as the poor UEP performance of high priority data and the seriously sacrifice of low priority data in decoding property. Based on the reasonable applications of different degree distributions in LT codes, this paper puts forward a novel UEP LT coding scheme with a simple feedback to compile these data packets separately. Simulation results show that the proposed scheme can effectively protect high priority data, and improve the transmission efficiency of low priority data from 2.9% to 22.3%. Furthermore, it is fairly suitable to apply this novel scheme to multicast and broadcast environments since only a simple feedback introduced.

  13. A Quantum Multi-Proxy Weak Blind Signature Scheme Based on Entanglement Swapping

    Science.gov (United States)

    Yan, LiLi; Chang, Yan; Zhang, ShiBin; Han, GuiHua; Sheng, ZhiWei

    2017-02-01

    In this paper, we present a multi-proxy weak blind signature scheme based on quantum entanglement swapping of Bell states. In the scheme, proxy signers can finish the signature instead of original singer with his/her authority. It can be applied to the electronic voting system, electronic paying system, etc. The scheme uses the physical characteristics of quantum mechanics to implement delegation, signature and verification. It could guarantee not only the unconditionally security but also the anonymity of the message owner. The security analysis shows the scheme satisfies the security features of multi-proxy weak signature, singers cannot disavowal his/her signature while the signature cannot be forged by others, and the message owner can be traced.

  14. Advanced neural network-based computational schemes for robust fault diagnosis

    CERN Document Server

    Mrugalski, Marcin

    2014-01-01

    The present book is devoted to problems of adaptation of artificial neural networks to robust fault diagnosis schemes. It presents neural networks-based modelling and estimation techniques used for designing robust fault diagnosis schemes for non-linear dynamic systems. A part of the book focuses on fundamental issues such as architectures of dynamic neural networks, methods for designing of neural networks and fault diagnosis schemes as well as the importance of robustness. The book is of a tutorial value and can be perceived as a good starting point for the new-comers to this field. The book is also devoted to advanced schemes of description of neural model uncertainty. In particular, the methods of computation of neural networks uncertainty with robust parameter estimation are presented. Moreover, a novel approach for system identification with the state-space GMDH neural network is delivered. All the concepts described in this book are illustrated by both simple academic illustrative examples and practica...

  15. A modified chaos-based communication scheme using Hamiltonian forms and observer

    International Nuclear Information System (INIS)

    Lopez-Mancilla, D; Cruz-Hernandez, C; Posadas-Castillo, C

    2005-01-01

    In this work, a modified chaos-based communication scheme is presented. In particular, we use the modified scheme proposed by Lopez-Mancilla and Cruz-Hernandez (2005), that improves the basic scheme for chaotic masking using a single transmission channel proposed by Cuomo and coworkers (1993). It is extended for a special class of Generalized Hamiltonian systems. Substantial differences that significantly affect the reception quality of the sent message, with or without considering noise effect in the transmission channel are given. We use two Hamiltonian Lorenz systems unidirectionally coupled, the first like a master/transmitter system and the other like a slave/receiver system in order to illustrate with numerical simulations the effectiveness of the modified scheme, using chaos synchronization with Hamiltonian forms and observer

  16. A modified chaos-based communication scheme using Hamiltonian forms and observer

    Energy Technology Data Exchange (ETDEWEB)

    Lopez-Mancilla, D [Engineering Faculty, Baja California Autonomous University (UABC), Km. 103, Carretera Tijuana-Ensenada, 22860, Ensenada, B.C. (Mexico); Cruz-Hernandez, C [Telematics Direction, Scientific Research and Advanced Studies of Ensenada (CICESE), Km. 107 Carretera Tijuana-Ensenada, 22860 Ensenada, B.C. (Mexico); Posadas-Castillo, C [Engineering Faculty, Baja California Autonomous University (UABC), Km. 103, Carretera Tijuana-Ensenada, 22860, Ensenada, B.C. (Mexico); Faculty of Engineering Mechanic and Electrical (FIME), Nuevo Leon Autonomous University (UANL), Pedro de alba s/n Cd. Universitaria San Nicolas de los Garza N.L. (Mexico)

    2005-01-01

    In this work, a modified chaos-based communication scheme is presented. In particular, we use the modified scheme proposed by Lopez-Mancilla and Cruz-Hernandez (2005), that improves the basic scheme for chaotic masking using a single transmission channel proposed by Cuomo and coworkers (1993). It is extended for a special class of Generalized Hamiltonian systems. Substantial differences that significantly affect the reception quality of the sent message, with or without considering noise effect in the transmission channel are given. We use two Hamiltonian Lorenz systems unidirectionally coupled, the first like a master/transmitter system and the other like a slave/receiver system in order to illustrate with numerical simulations the effectiveness of the modified scheme, using chaos synchronization with Hamiltonian forms and observer.

  17. Experimental Investigation of Cooperative Schemes on a Real-Time DSP-Based Testbed

    Directory of Open Access Journals (Sweden)

    Mavrokefalidis Christos

    2009-01-01

    Full Text Available Experimental results on the well-known cooperating relaying schemes, amplify-and-forward (AF, detect-and-forward (DF, cooperative maximum ratio combining (CMRC, and distributed space-time coding (DSTC, are presented in this paper. A novel relaying scheme named "selection relaying" (SR, in which one of two relays are selected base on path-loss, is also tested. For all schemes except AF receive antenna diversity is as an option which can be switched on or off. For DF and DSTC a feature "selective" where the relay only forwards frames with a receive SNR above 6 dB is introduced. In our measurements, all cooperative relaying schemes above increase the coverage area as compared with direct transmission. The features "antenna diversity" and "selective" improve the performance. Good performance is obtained with CMRC, DSTC, and SR.

  18. Evaluation of frame aggregation schemes for the p-persistent based next generation WLANS

    Science.gov (United States)

    Ahmad, Ashar; Anna, Kiran; Bassiouni, Mostafa A.

    2010-04-01

    The next Generation IEEE 802.11n is designed to improve the throughput of the existing standard 802.11. It aims to achieve this by increasing the data rate from 54 Mbps to 600 Mbps with the help of physical layer enhancements. Therefore, the Medium Access Layer (MAC) requires improvements to fully utilize the capabilities of the enhanced 802.11n physical layer. In this paper, we present the performance evaluation results of two frame aggregation schemes viz., MAC Protocol Data Unit Aggregation (A-MPDU) and MAC Service Data Unit Aggregation (A-MSDU) and study their performance impact when the two schemes are incorporated in a p-persistent based 802.11n. The simulation results have shown that the two schemes achieve consistent performance improvement over the standard non-aggregation scheme.

  19. An Improved Wavelet‐Based Multivariable Fault Detection Scheme

    KAUST Repository

    Harrou, Fouzi

    2017-07-06

    Data observed from environmental and engineering processes are usually noisy and correlated in time, which makes the fault detection more difficult as the presence of noise degrades fault detection quality. Multiscale representation of data using wavelets is a powerful feature extraction tool that is well suited to denoising and decorrelating time series data. In this chapter, we combine the advantages of multiscale partial least squares (MSPLSs) modeling with those of the univariate EWMA (exponentially weighted moving average) monitoring chart, which results in an improved fault detection system, especially for detecting small faults in highly correlated, multivariate data. Toward this end, we applied EWMA chart to the output residuals obtained from MSPLS model. It is shown through simulated distillation column data the significant improvement in fault detection can be obtained by using the proposed methods as compared to the use of the conventional partial least square (PLS)‐based Q and EWMA methods and MSPLS‐based Q method.

  20. Hamming Code Based Watermarking Scheme for 3D Model Verification

    Directory of Open Access Journals (Sweden)

    Jen-Tse Wang

    2014-01-01

    Full Text Available Due to the explosive growth of the Internet and maturing of 3D hardware techniques, protecting 3D objects becomes a more and more important issue. In this paper, a public hamming code based fragile watermarking technique is proposed for 3D objects verification. An adaptive watermark is generated from each cover model by using the hamming code technique. A simple least significant bit (LSB substitution technique is employed for watermark embedding. In the extraction stage, the hamming code based watermark can be verified by using the hamming code checking without embedding any verification information. Experimental results shows that 100% vertices of the cover model can be watermarked, extracted, and verified. It also shows that the proposed method can improve security and achieve low distortion of stego object.

  1. Password-based authenticated key exchange scheme using smart card

    Science.gov (United States)

    Liu, Hui; Zhong, Shaojun

    2013-03-01

    A protocol that allows any two entities to negotiate a shared session key is commonly called a key exchange protocol. If the protocol provides a function to authenticate each other, we call the protocol authenticated key exchange protocol (AKE). Password authentication key exchange (PAKE) is the AKE protocol in which the two entities share a humanmemorable password. Most of current PAKE relies on the existence of a public key infrastructure, which sometime is impossible for a certain environments such as low computational device due to the computation overhead. In this paper, we propose password-based authenticated key exchange using smart card. Compared to previous PAKE, our protocol is more efficient because our protocol is based on ECC. Thereby, the proposed protocol can be well applied to low computation device.

  2. FPGA-based network data transmission scheme for CSNS

    International Nuclear Information System (INIS)

    Wang Xiuku; Zhang Hongyu; Gu Minhao; Xiao Liang

    2012-01-01

    This paper presents the FPGA-based network data transmission solutions for the Data Acquisition System of China Spallation Neutron Source (CSNS). The board with FPGA as the core is used as the hardware platform to realize the transmission of network data. A SOPC system is built and an embedded Linux is transplanted on PowerPC Core. An application program based on Linux has been finished to realize the data transmission via embedded Gigabit Ethernet. The relationship between network transfer performance and packet size was obtained by a test program. In addition, the paper also tried to realize some other ways to transfer data: transplanting PetaLinux on Microblaze, transplanting Lwip protocol stack on PowerPC Core and Microblaze. Their advantages and disadvantages are analyzed and compared in this paper, so that different options and recommendations can be given to meet the actual needs of different projects in the future. (authors)

  3. A new iterative speech enhancement scheme based on Kalman filtering

    DEFF Research Database (Denmark)

    Li, Chunjian; Andersen, Søren Vang

    2005-01-01

    for a high temporal resolution estimation of this variance. A Local Variance Estimator based on a Prediction Error Kalman Filter is designed for this high temporal resolution variance estimation. To achieve fast convergence and avoid local maxima of the likelihood function, a Weighted Power Spectral....... Performance comparison shows significant improvement over the baseline EM algorithm in terms of three objective measures. Listening test indicates an improvement in subjective quality due to a significant reduction of musical noise compared to the baseline EM algorithm....

  4. Hydrophobicity classification of polymeric materials based on fractal dimension

    Directory of Open Access Journals (Sweden)

    Daniel Thomazini

    2008-12-01

    Full Text Available This study proposes a new method to obtain hydrophobicity classification (HC in high voltage polymer insulators. In the method mentioned, the HC was analyzed by fractal dimension (fd and its processing time was evaluated having as a goal the application in mobile devices. Texture images were created from spraying solutions produced of mixtures of isopropyl alcohol and distilled water in proportions, which ranged from 0 to 100% volume of alcohol (%AIA. Based on these solutions, the contact angles of the drops were measured and the textures were used as patterns for fractal dimension calculations.

  5. Parametric classification of handvein patterns based on texture features

    Science.gov (United States)

    Al Mahafzah, Harbi; Imran, Mohammad; Supreetha Gowda H., D.

    2018-04-01

    In this paper, we have developed Biometric recognition system adopting hand based modality Handvein,which has the unique pattern for each individual and it is impossible to counterfeit and fabricate as it is an internal feature. We have opted in choosing feature extraction algorithms such as LBP-visual descriptor, LPQ-blur insensitive texture operator, Log-Gabor-Texture descriptor. We have chosen well known classifiers such as KNN and SVM for classification. We have experimented and tabulated results of single algorithm recognition rate for Handvein under different distance measures and kernel options. The feature level fusion is carried out which increased the performance level.

  6. MODEL-BASED CLUSTERING FOR CLASSIFICATION OF AQUATIC SYSTEMS AND DIAGNOSIS OF ECOLOGICAL STRESS

    Science.gov (United States)

    Clustering approaches were developed using the classification likelihood, the mixture likelihood, and also using a randomization approach with a model index. Using a clustering approach based on the mixture and classification likelihoods, we have developed an algorithm that...

  7. Design, Implementation, and Performance Evaluation of Efficient PMIPv6 Based Mobile Multicast Sender Support Schemes

    Directory of Open Access Journals (Sweden)

    Lili Wang

    2015-01-01

    Full Text Available Proxy Mobile IPv6 (PMIPv6 is proposed as a promising network-based mobility management protocol, which does not need any participation of mobile nodes. PMIPv6 does not support the multicast well and most of the current research concentrates on the mobile multicast receiver. However, the mobile multicast sender is also very important and challenging, which has not been addressed well. Therefore, in this paper we propose two efficient PMIPv6 based mobile multicast sender support schemes which are PMIP bidirectional tunneling (PMIP-BT and PMIP direct routing (PMIP-DR. In the PMIP-BT, the multicast traffic can be delivered through the PMIPv6 bidirectional tunnel, while, in the PMIP-DR, the multicast data can be transmitted via an optimized direct multicast routing. Both of them can support the multicast sender mobility transparently enabled in the PMIPv6 networks. We evaluate the performance of the proposed schemes by theoretical analysis, and the numerical results show that the proposed schemes have a better performance in terms of the signaling cost than the current schemes. Meanwhile, the proposed schemes are also implemented on the test bed, and the experimental results not only verify the validity and feasibility of our proposed schemes, but also conclude the different scenarios to which they are applicable.

  8. Connection Setup Signaling Scheme with Flooding-Based Path Searching for Diverse-Metric Network

    Science.gov (United States)

    Kikuta, Ko; Ishii, Daisuke; Okamoto, Satoru; Oki, Eiji; Yamanaka, Naoaki

    Connection setup on various computer networks is now achieved by GMPLS. This technology is based on the source-routing approach, which requires the source node to store metric information of the entire network prior to computing a route. Thus all metric information must be distributed to all network nodes and kept up-to-date. However, as metric information become more diverse and generalized, it is hard to update all information due to the huge update overhead. Emerging network services and applications require the network to support diverse metrics for achieving various communication qualities. Increasing the number of metrics supported by the network causes excessive processing of metric update messages. To reduce the number of metric update messages, another scheme is required. This paper proposes a connection setup scheme that uses flooding-based signaling rather than the distribution of metric information. The proposed scheme requires only flooding of signaling messages with requested metric information, no routing protocol is required. Evaluations confirm that the proposed scheme achieves connection establishment without excessive overhead. Our analysis shows that the proposed scheme greatly reduces the number of control messages compared to the conventional scheme, while their blocking probabilities are comparable.

  9. East Asian winter monsoon forecasting schemes based on the NCEP's climate forecast system

    Science.gov (United States)

    Tian, Baoqiang; Fan, Ke; Yang, Hongqing

    2017-12-01

    The East Asian winter monsoon (EAWM) is the major climate system in the Northern Hemisphere during boreal winter. In this study, we developed two schemes to improve the forecasting skill of the interannual variability of the EAWM index (EAWMI) using the interannual increment prediction method, also known as the DY method. First, we found that version 2 of the NCEP's Climate Forecast System (CFSv2) showed higher skill in predicting the EAWMI in DY form than not. So, based on the advantage of the DY method, Scheme-I was obtained by adding the EAWMI DY predicted by CFSv2 to the observed EAWMI in the previous year. This scheme showed higher forecasting skill than CFSv2. Specifically, during 1983-2016, the temporal correlation coefficient between the Scheme-I-predicted and observed EAWMI was 0.47, exceeding the 99% significance level, with the root-mean-square error (RMSE) decreased by 12%. The autumn Arctic sea ice and North Pacific sea surface temperature (SST) are two important external forcing factors for the interannual variability of the EAWM. Therefore, a second (hybrid) prediction scheme, Scheme-II, was also developed. This scheme not only involved the EAWMI DY of CFSv2, but also the sea-ice concentration (SIC) observed the previous autumn in the Laptev and East Siberian seas and the temporal coefficients of the third mode of the North Pacific SST in DY form. We found that a negative SIC anomaly in the preceding autumn over the Laptev and the East Siberian seas could lead to a significant enhancement of the Aleutian low and East Asian westerly jet in the following winter. However, the intensity of the winter Siberian high was mainly affected by the third mode of the North Pacific autumn SST. Scheme-I and Scheme-II also showed higher predictive ability for the EAWMI in negative anomaly years compared to CFSv2. More importantly, the improvement in the prediction skill of the EAWMI by the new schemes, especially for Scheme-II, could enhance the forecasting skill of

  10. A Secure and Privacy-Preserving Navigation Scheme Using Spatial Crowdsourcing in Fog-Based VANETs

    Science.gov (United States)

    Wang, Lingling; Liu, Guozhu; Sun, Lijun

    2017-01-01

    Fog-based VANETs (Vehicular ad hoc networks) is a new paradigm of vehicular ad hoc networks with the advantages of both vehicular cloud and fog computing. Real-time navigation schemes based on fog-based VANETs can promote the scheme performance efficiently. In this paper, we propose a secure and privacy-preserving navigation scheme by using vehicular spatial crowdsourcing based on fog-based VANETs. Fog nodes are used to generate and release the crowdsourcing tasks, and cooperatively find the optimal route according to the real-time traffic information collected by vehicles in their coverage areas. Meanwhile, the vehicle performing the crowdsourcing task can get a reasonable reward. The querying vehicle can retrieve the navigation results from each fog node successively when entering its coverage area, and follow the optimal route to the next fog node until it reaches the desired destination. Our scheme fulfills the security and privacy requirements of authentication, confidentiality and conditional privacy preservation. Some cryptographic primitives, including the Elgamal encryption algorithm, AES, randomized anonymous credentials and group signatures, are adopted to achieve this goal. Finally, we analyze the security and the efficiency of the proposed scheme. PMID:28338620

  11. A Secure and Privacy-Preserving Navigation Scheme Using Spatial Crowdsourcing in Fog-Based VANETs.

    Science.gov (United States)

    Wang, Lingling; Liu, Guozhu; Sun, Lijun

    2017-03-24

    Fog-based VANETs (Vehicular ad hoc networks) is a new paradigm of vehicular ad hoc networks with the advantages of both vehicular cloud and fog computing. Real-time navigation schemes based on fog-based VANETs can promote the scheme performance efficiently. In this paper, we propose a secure and privacy-preserving navigation scheme by using vehicular spatial crowdsourcing based on fog-based VANETs. Fog nodes are used to generate and release the crowdsourcing tasks, and cooperatively find the optimal route according to the real-time traffic information collected by vehicles in their coverage areas. Meanwhile, the vehicle performing the crowdsourcing task can get a reasonable reward. The querying vehicle can retrieve the navigation results from each fog node successively when entering its coverage area, and follow the optimal route to the next fog node until it reaches the desired destination. Our scheme fulfills the security and privacy requirements of authentication, confidentiality and conditional privacy preservation. Some cryptographic primitives, including the Elgamal encryption algorithm, AES, randomized anonymous credentials and group signatures, are adopted to achieve this goal. Finally, we analyze the security and the efficiency of the proposed scheme.

  12. Predictors of Availing Maternal Health Schemes: A community based study in Gujarat, India

    Directory of Open Access Journals (Sweden)

    Kranti Suresh Vora

    2014-06-01

    Full Text Available Background: India continues to face challenges in improving key maternal health indicators with about 1/3rd of global maternal deaths happening in India. Utilization of health care services is an important issue in India with significant proportion of home deliveries and majority of mothers not receiving adequate antenatal care. Mortality among poor rural women is the highest with lowest utilization. To make maternal healthcare more equitable, numerous schemes such as Janani Suraksha Yojana, Chiranjeevi Yojana, Kasturba Poshan Sahay Yojana have been introduced. Studies suggest that utilization of such schemes by target population is low and there is a need to understand factors affecting maternal health care utilization in the context of these schemes. Current community based study was done in rural Gujarat to understand characteristics of women who utilize such schemes and predictors of utilization. Methodology: Data collection was done in two districts of Gujarat from June to August, 2013 as a pilot phase of MATIND project. Community based cross-sectional study included 827 households and socio-demographic details of 1454 women of 15-49 years age groups were collected. 265 mothers, who had delivered after 1st January, 2013 are included in the regression analyses. The data analysis carried out with R version 3.0.1 software.  Results: The analysis indicates socioeconomic variables such as caste, maternal variables such as education and health system variables such as use of government facility are important predictors of maternal health scheme utilization. Results suggest that socioeconomic and health system factors are the best predictors for availing scheme. Conclusion: Health system variables along with individual level variables are important predictors for availing maternal health schemes. The study indicates the need to examine all levels of predictors for utilizing government health schemes to maximize the benefit for underserved

  13. A novel lost packets recovery scheme based on visual secret sharing

    Science.gov (United States)

    Lu, Kun; Shan, Hong; Li, Zhi; Niu, Zhao

    2017-08-01

    In this paper, a novel lost packets recovery scheme which encrypts the effective parts of an original packet into two shadow packets based on (2, 2)-threshold XOR-based visual Secret Sharing (VSS) is proposed. The two shadow packets used as watermarks would be embedded into two normal data packets with digital watermarking embedding technology and then sent from one sensor node to another. Each shadow packet would reveal no information of the original packet, which can improve the security of original packet delivery greatly. The two shadow packets which can be extracted from the received two normal data packets delivered from a sensor node can recover the original packet lossless based on XOR-based VSS. The Performance analysis present that the proposed scheme provides essential services as long as possible in the presence of selective forwarding attack. The proposed scheme would not increase the amount of additional traffic, namely, lower energy consumption, which is suitable for Wireless Sensor Network (WSN).

  14. [Extension of health coverage and community based health insurance schemes in Africa: Myths and realities].

    Science.gov (United States)

    Boidin, B

    2015-02-01

    This article tackles the perspectives and limits of the extension of health coverage based on community based health insurance schemes in Africa. Despite their strong potential contribution to the extension of health coverage, their weaknesses challenge their ability to play an important role in this extension. Three limits are distinguished: financial fragility; insufficient adaptation to characteristics and needs of poor people; organizational and institutional failures. Therefore lessons can be learnt from the limits of the institutionalization of community based health insurance schemes. At first, community based health insurance schemes are to be considered as a transitional but insufficient solution. There is also a stronger role to be played by public actors in improving financial support, strengthening health services and coordinating coverage programs.

  15. Forest Classification Based on Forest texture in Northwest Yunnan Province

    Science.gov (United States)

    Wang, Jinliang; Gao, Yan; Wang, Xiaohua; Fu, Lei

    2014-03-01

    Forest texture is an intrinsic characteristic and an important visual feature of a forest ecological system. Full utilization of forest texture will be a great help in increasing the accuracy of forest classification based on remote sensed data. Taking Shangri-La as a study area, forest classification has been based on the texture. The results show that: (1) From the texture abundance, texture boundary, entropy as well as visual interpretation, the combination of Grayscale-gradient co-occurrence matrix and wavelet transformation is much better than either one of both ways of forest texture information extraction; (2) During the forest texture information extraction, the size of the texture-suitable window determined by the semi-variogram method depends on the forest type (evergreen broadleaf forest is 3×3, deciduous broadleaf forest is 5×5, etc.). (3)While classifying forest based on forest texture information, the texture factor assembly differs among forests: Variance Heterogeneity and Correlation should be selected when the window is between 3×3 and 5×5 Mean, Correlation, and Entropy should be used when the window in the range of 7×7 to 19×19 and Correlation, Second Moment, and Variance should be used when the range is larger than 21×21.

  16. Forest Classification Based on Forest texture in Northwest Yunnan Province

    International Nuclear Information System (INIS)

    Wang, Jinliang; Gao, Yan; Fu, Lei; Wang, Xiaohua

    2014-01-01

    Forest texture is an intrinsic characteristic and an important visual feature of a forest ecological system. Full utilization of forest texture will be a great help in increasing the accuracy of forest classification based on remote sensed data. Taking Shangri-La as a study area, forest classification has been based on the texture. The results show that: (1) From the texture abundance, texture boundary, entropy as well as visual interpretation, the combination of Grayscale-gradient co-occurrence matrix and wavelet transformation is much better than either one of both ways of forest texture information extraction; (2) During the forest texture information extraction, the size of the texture-suitable window determined by the semi-variogram method depends on the forest type (evergreen broadleaf forest is 3×3, deciduous broadleaf forest is 5×5, etc.). (3)While classifying forest based on forest texture information, the texture factor assembly differs among forests: Variance Heterogeneity and Correlation should be selected when the window is between 3×3 and 5×5; Mean, Correlation, and Entropy should be used when the window in the range of 7×7 to 19×19; and Correlation, Second Moment, and Variance should be used when the range is larger than 21×21

  17. Feature selection gait-based gender classification under different circumstances

    Science.gov (United States)

    Sabir, Azhin; Al-Jawad, Naseer; Jassim, Sabah

    2014-05-01

    This paper proposes a gender classification based on human gait features and investigates the problem of two variations: clothing (wearing coats) and carrying bag condition as addition to the normal gait sequence. The feature vectors in the proposed system are constructed after applying wavelet transform. Three different sets of feature are proposed in this method. First, Spatio-temporal distance that is dealing with the distance of different parts of the human body (like feet, knees, hand, Human Height and shoulder) during one gait cycle. The second and third feature sets are constructed from approximation and non-approximation coefficient of human body respectively. To extract these two sets of feature we divided the human body into two parts, upper and lower body part, based on the golden ratio proportion. In this paper, we have adopted a statistical method for constructing the feature vector from the above sets. The dimension of the constructed feature vector is reduced based on the Fisher score as a feature selection method to optimize their discriminating significance. Finally k-Nearest Neighbor is applied as a classification method. Experimental results demonstrate that our approach is providing more realistic scenario and relatively better performance compared with the existing approaches.

  18. An Indexing Scheme for Case-Based Manufacturing Vision Development

    DEFF Research Database (Denmark)

    Wang, Chengbo; Johansen, John; Luxhøj, James T.

    2004-01-01

    with the competence improvement of an enterprises manufacturing system. There are two types of cases within the CBRM – an event case (EC) and a general supportive case (GSC). We designed one set of indexing vocabulary for the two types of cases, but a different indexing representation structure for each of them......This paper focuses on one critical element, indexing – retaining and representing knowledge in an applied case-based reasoning (CBR) model for supporting strategic manufacturing vision development (CBRM). Manufacturing vision (MV) is a kind of knowledge management concept and process concerned...

  19. Joint Probability-Based Neuronal Spike Train Classification

    Directory of Open Access Journals (Sweden)

    Yan Chen

    2009-01-01

    Full Text Available Neuronal spike trains are used by the nervous system to encode and transmit information. Euclidean distance-based methods (EDBMs have been applied to quantify the similarity between temporally-discretized spike trains and model responses. In this study, using the same discretization procedure, we developed and applied a joint probability-based method (JPBM to classify individual spike trains of slowly adapting pulmonary stretch receptors (SARs. The activity of individual SARs was recorded in anaesthetized, paralysed adult male rabbits, which were artificially-ventilated at constant rate and one of three different volumes. Two-thirds of the responses to the 600 stimuli presented at each volume were used to construct three response models (one for each stimulus volume consisting of a series of time bins, each with spike probabilities. The remaining one-third of the responses where used as test responses to be classified into one of the three model responses. This was done by computing the joint probability of observing the same series of events (spikes or no spikes, dictated by the test response in a given model and determining which probability of the three was highest. The JPBM generally produced better classification accuracy than the EDBM, and both performed well above chance. Both methods were similarly affected by variations in discretization parameters, response epoch duration, and two different response alignment strategies. Increasing bin widths increased classification accuracy, which also improved with increased observation time, but primarily during periods of increasing lung inflation. Thus, the JPBM is a simple and effective method performing spike train classification.

  20. Modeling and performance analysis of an improved movement-based location management scheme for packet-switched mobile communication systems.

    Science.gov (United States)

    Chung, Yun Won; Kwon, Jae Kyun; Park, Suwon

    2014-01-01

    One of the key technologies to support mobility of mobile station (MS) in mobile communication systems is location management which consists of location update and paging. In this paper, an improved movement-based location management scheme with two movement thresholds is proposed, considering bursty data traffic characteristics of packet-switched (PS) services. The analytical modeling for location update and paging signaling loads of the proposed scheme is developed thoroughly and the performance of the proposed scheme is compared with that of the conventional scheme. We show that the proposed scheme outperforms the conventional scheme in terms of total signaling load with an appropriate selection of movement thresholds.

  1. A Dynamic Reallocation Based Window Access Scheme for Enhancing QoS of Vehicular Ad-hoc Networks (VANETs

    Directory of Open Access Journals (Sweden)

    Md. Amirul Islam

    2018-01-01

    Full Text Available This article proposes a new MAC scheme for Vehicle-to-Infrastructure (V2I communications that dynamically reallocates unused TDMA slots. By maintaining a balanced waiting time, the proposed TDMA based scheduling scheme allocates TDMA slots in a rational way to minimize merging and one-hop neighboring collision. The proposed scheme ensures dynamic reallocation of unused slots by using “time slot reassignment” mechanism. The scheme has been simulated in VEINS framework of OMNET++ network simulator and its performance has been compared with other conventional protocols. Experimental results show that our scheme performs better than existing schemes in terms of successfully transmitted data packets.

  2. A novel image encryption scheme based on spatial chaos map

    International Nuclear Information System (INIS)

    Sun Fuyan; Liu Shutang; Li Zhongqin; Lue Zongwang

    2008-01-01

    In recent years, the chaos-based cryptographic algorithms have suggested some new and efficient ways to develop secure image encryption techniques, but the drawbacks of small key space and weak security in one-dimensional chaotic cryptosystems are obvious. In this paper, spatial chaos system are used for high degree security image encryption while its speed is acceptable. The proposed algorithm is described in detail. The basic idea is to encrypt the image in space with spatial chaos map pixel by pixel, and then the pixels are confused in multiple directions of space. Using this method one cycle, the image becomes indistinguishable in space due to inherent properties of spatial chaotic systems. Several experimental results, key sensitivity tests, key space analysis, and statistical analysis show that the approach for image cryptosystems provides an efficient and secure way for real time image encryption and transmission from the cryptographic viewpoint

  3. Counter-Based Broadcast Scheme Considering Reachability, Network Density, and Energy Efficiency for Wireless Sensor Networks.

    Science.gov (United States)

    Jung, Ji-Young; Seo, Dong-Yoon; Lee, Jung-Ryun

    2018-01-04

    A wireless sensor network (WSN) is emerging as an innovative method for gathering information that will significantly improve the reliability and efficiency of infrastructure systems. Broadcast is a common method to disseminate information in WSNs. A variety of counter-based broadcast schemes have been proposed to mitigate the broadcast-storm problems, using the count threshold value and a random access delay. However, because of the limited propagation of the broadcast-message, there exists a trade-off in a sense that redundant retransmissions of the broadcast-message become low and energy efficiency of a node is enhanced, but reachability become low. Therefore, it is necessary to study an efficient counter-based broadcast scheme that can dynamically adjust the random access delay and count threshold value to ensure high reachability, low redundant of broadcast-messages, and low energy consumption of nodes. Thus, in this paper, we first measure the additional coverage provided by a node that receives the same broadcast-message from two neighbor nodes, in order to achieve high reachability with low redundant retransmissions of broadcast-messages. Second, we propose a new counter-based broadcast scheme considering the size of the additional coverage area, distance between the node and the broadcasting node, remaining battery of the node, and variations of the node density. Finally, we evaluate performance of the proposed scheme compared with the existing counter-based broadcast schemes. Simulation results show that the proposed scheme outperforms the existing schemes in terms of saved rebroadcasts, reachability, and total energy consumption.

  4. Breaking a chaos-based secure communication scheme designed by an improved modulation method

    International Nuclear Information System (INIS)

    Li Shujun; Alvarez, Gonzalo; Chen Guanrong

    2005-01-01

    Recently Bu and Wang [Bu S, Wang B-H. Chaos, Solitons and Fractals 2004;19(4):919-24] proposed a simple modulation method aiming to improve the security of chaos-based secure communications against return-map-based attacks. Soon this modulation method was independently cryptanalyzed by Chee et al. [Chee CY, Xu D, Bishop SR. Chaos, Solitons and Fractals 2004;21(5):1129-34], Wu et al. [Wu X, Hu H, Zhang B. Chaos, Solitons and Fractals 2004;22(2):367-73], and Alvarez et al. [Alvarez G, Montoya F, Romera M, Pastor G. Chaos, Solitons and Fractals, in press, arXiv:nlin/0406065] via different attacks. As an enhancement to the Bu-Wang method, an improving scheme was suggested by Wu et al. by removing the relationship between the modulating function and the zero-points. The present paper points out that the improved scheme proposed by Wu et al. is still insecure against a new attack. Compared with the existing attacks, the proposed attack is more powerful and can also break the original Bu-Wang scheme. Furthermore, it is pointed out that the security of the modulation-based schemes proposed by Wu et al. is not so satisfactory from a pure cryptographical point of view. The synchronization performance of this class of modulation-based schemes is also discussed

  5. Efficient and Provable Secure Pairing-Free Security-Mediated Identity-Based Identification Schemes

    Directory of Open Access Journals (Sweden)

    Ji-Jian Chin

    2014-01-01

    Full Text Available Security-mediated cryptography was first introduced by Boneh et al. in 2001. The main motivation behind security-mediated cryptography was the capability to allow instant revocation of a user’s secret key by necessitating the cooperation of a security mediator in any given transaction. Subsequently in 2003, Boneh et al. showed how to convert a RSA-based security-mediated encryption scheme from a traditional public key setting to an identity-based one, where certificates would no longer be required. Following these two pioneering papers, other cryptographic primitives that utilize a security-mediated approach began to surface. However, the security-mediated identity-based identification scheme (SM-IBI was not introduced until Chin et al. in 2013 with a scheme built on bilinear pairings. In this paper, we improve on the efficiency results for SM-IBI schemes by proposing two schemes that are pairing-free and are based on well-studied complexity assumptions: the RSA and discrete logarithm assumptions.

  6. Efficient and provable secure pairing-free security-mediated identity-based identification schemes.

    Science.gov (United States)

    Chin, Ji-Jian; Tan, Syh-Yuan; Heng, Swee-Huay; Phan, Raphael C-W

    2014-01-01

    Security-mediated cryptography was first introduced by Boneh et al. in 2001. The main motivation behind security-mediated cryptography was the capability to allow instant revocation of a user's secret key by necessitating the cooperation of a security mediator in any given transaction. Subsequently in 2003, Boneh et al. showed how to convert a RSA-based security-mediated encryption scheme from a traditional public key setting to an identity-based one, where certificates would no longer be required. Following these two pioneering papers, other cryptographic primitives that utilize a security-mediated approach began to surface. However, the security-mediated identity-based identification scheme (SM-IBI) was not introduced until Chin et al. in 2013 with a scheme built on bilinear pairings. In this paper, we improve on the efficiency results for SM-IBI schemes by proposing two schemes that are pairing-free and are based on well-studied complexity assumptions: the RSA and discrete logarithm assumptions.

  7. Breaking a chaos-based secure communication scheme designed by an improved modulation method

    Energy Technology Data Exchange (ETDEWEB)

    Li Shujun [Department of Electronic Engineering, City University of Hong Kong, Kowloon, Hong Kong (China)]. E-mail: hooklee@mail.com; Alvarez, Gonzalo [Instituto de Fisica Aplicada, Consejo Superior de Investigaciones Cientificas, Serrano 144-28006 Madrid (Spain); Chen Guanrong [Department of Electronic Engineering, City University of Hong Kong, Kowloon, Hong Kong (China)

    2005-07-01

    Recently Bu and Wang [Bu S, Wang B-H. Chaos, Solitons and Fractals 2004;19(4):919-24] proposed a simple modulation method aiming to improve the security of chaos-based secure communications against return-map-based attacks. Soon this modulation method was independently cryptanalyzed by Chee et al. [Chee CY, Xu D, Bishop SR. Chaos, Solitons and Fractals 2004;21(5):1129-34], Wu et al. [Wu X, Hu H, Zhang B. Chaos, Solitons and Fractals 2004;22(2):367-73], and Alvarez et al. [Alvarez G, Montoya F, Romera M, Pastor G. Chaos, Solitons and Fractals, in press, arXiv:nlin/0406065] via different attacks. As an enhancement to the Bu-Wang method, an improving scheme was suggested by Wu et al. by removing the relationship between the modulating function and the zero-points. The present paper points out that the improved scheme proposed by Wu et al. is still insecure against a new attack. Compared with the existing attacks, the proposed attack is more powerful and can also break the original Bu-Wang scheme. Furthermore, it is pointed out that the security of the modulation-based schemes proposed by Wu et al. is not so satisfactory from a pure cryptographical point of view. The synchronization performance of this class of modulation-based schemes is also discussed.

  8. [Part-time Work and Men's Health : Results based on Routine Data of a Statutory Health Insurance Scheme].

    Science.gov (United States)

    Grobe, Thomas G

    2016-08-01

    With the introduction of a new occupational classification at the end of 2011, employment characteristics are reported by employees to social insurance agencies in Germany in more detail than in previous years. In addition to other changes, the new classification allows a distinction between full- and part-time work to be made. This provided a reason to consider the health-related aspects of part-time work on the basis of data from a statutory health insurance scheme. Our analysis is based on the data of 3.8 million employees insured with the Techniker Krankenkasse (TK), a statutory health insurance scheme, in 2012. In addition to daily information on employment situations, details of periods and diagnoses of sick leave and the drugs prescribed were available. Although approximately 50 % of women of middle to higher working age worked part-time in 2012, the corresponding percentage of men employed in part-time work was less than 10 %. Overall, part-time employees were on sick leave for fewer days than full-time employees, but among men, sick leave due to mental disorders was longer for part-time employees than for full-time employees, whereas women working part time were affected to a lesser extent by corresponding periods of absence than those working full time. The results provide indications for the assertion that men in gender-specifically atypical employment situations are more frequently affected by mental disorders. Further evidence supports this assertion. With the long-term availability of these new employment characteristics, longitudinal analyses could help to clarify this cause-effect relationship.

  9. GIS coupled Multiple Criteria based Decision Support for Classification of Urban Coastal Areas in India

    Science.gov (United States)

    Dhiman, R.; Kalbar, P.; Inamdar, A. B.

    2017-12-01

    Coastal area classification in India is a challenge for federal and state government agencies due to fragile institutional framework, unclear directions in implementation of costal regulations and violations happening at private and government level. This work is an attempt to improvise the objectivity of existing classification methods to synergies the ecological systems and socioeconomic development in coastal cities. We developed a Geographic information system coupled Multi-criteria Decision Making (GIS-MCDM) approach to classify urban coastal areas where utility functions are used to transform the costal features into quantitative membership values after assessing the sensitivity of urban coastal ecosystem. Furthermore, these membership values for costal features are applied in different weighting schemes to derive Coastal Area Index (CAI) which classifies the coastal areas in four distinct categories viz. 1) No Development Zone, 2) Highly Sensitive Zone, 3) Moderately Sensitive Zone and 4) Low Sensitive Zone based on the sensitivity of urban coastal ecosystem. Mumbai, a coastal megacity in India is used as case study for demonstration of proposed method. Finally, uncertainty analysis using Monte Carlo approach to validate the sensitivity of CAI under specific multiple scenarios is carried out. Results of CAI method shows the clear demarcation of coastal areas in GIS environment based on the ecological sensitivity. CAI provides better decision support for federal and state level agencies to classify urban coastal areas according to the regional requirement of coastal resources considering resilience and sustainable development. CAI method will strengthen the existing institutional framework for decision making in classification of urban coastal areas where most effective coastal management options can be proposed.

  10. A physiologically-inspired model of numerical classification based on graded stimulus coding

    Directory of Open Access Journals (Sweden)

    John Pearson

    2010-01-01

    Full Text Available In most natural decision contexts, the process of selecting among competing actions takes place in the presence of informative, but potentially ambiguous, stimuli. Decisions about magnitudes—quantities like time, length, and brightness that are linearly ordered—constitute an important subclass of such decisions. It has long been known that perceptual judgments about such quantities obey Weber’s Law, wherein the just-noticeable difference in a magnitude is proportional to the magnitude itself. Current physiologically inspired models of numerical classification assume discriminations are made via a labeled line code of neurons selectively tuned for numerosity, a pattern observed in the firing rates of neurons in the ventral intraparietal area (VIP of the macaque. By contrast, neurons in the contiguous lateral intraparietal area (LIP signal numerosity in a graded fashion, suggesting the possibility that numerical classification could be achieved in the absence of neurons tuned for number. Here, we consider the performance of a decision model based on this analog coding scheme in a paradigmatic discrimination task—numerosity bisection. We demonstrate that a basic two-neuron classifier model, derived from experimentally measured monotonic responses of LIP neurons, is sufficient to reproduce the numerosity bisection behavior of monkeys, and that the threshold of the classifier can be set by reward maximization via a simple learning rule. In addition, our model predicts deviations from Weber Law scaling of choice behavior at high numerosity. Together, these results suggest both a generic neuronal framework for magnitude-based decisions and a role for reward contingency in the classification of such stimuli.

  11. Soft computing based feature selection for environmental sound classification

    NARCIS (Netherlands)

    Shakoor, A.; May, T.M.; Van Schijndel, N.H.

    2010-01-01

    Environmental sound classification has a wide range of applications,like hearing aids, mobile communication devices, portable media players, and auditory protection devices. Sound classification systemstypically extract features from the input sound. Using too many features increases complexity

  12. Chemometric classification of casework arson samples based on gasoline content.

    Science.gov (United States)

    Sinkov, Nikolai A; Sandercock, P Mark L; Harynuk, James J

    2014-02-01

    Detection and identification of ignitable liquids (ILs) in arson debris is a critical part of arson investigations. The challenge of this task is due to the complex and unpredictable chemical nature of arson debris, which also contains pyrolysis products from the fire. ILs, most commonly gasoline, are complex chemical mixtures containing hundreds of compounds that will be consumed or otherwise weathered by the fire to varying extents depending on factors such as temperature, air flow, the surface on which IL was placed, etc. While methods such as ASTM E-1618 are effective, data interpretation can be a costly bottleneck in the analytical process for some laboratories. In this study, we address this issue through the application of chemometric tools. Prior to the application of chemometric tools such as PLS-DA and SIMCA, issues of chromatographic alignment and variable selection need to be addressed. Here we use an alignment strategy based on a ladder consisting of perdeuterated n-alkanes. Variable selection and model optimization was automated using a hybrid backward elimination (BE) and forward selection (FS) approach guided by the cluster resolution (CR) metric. In this work, we demonstrate the automated construction, optimization, and application of chemometric tools to casework arson data. The resulting PLS-DA and SIMCA classification models, trained with 165 training set samples, have provided classification of 55 validation set samples based on gasoline content with 100% specificity and sensitivity. Copyright © 2013 Elsevier Ireland Ltd. All rights reserved.

  13. Interactive classification and content-based retrieval of tissue images

    Science.gov (United States)

    Aksoy, Selim; Marchisio, Giovanni B.; Tusk, Carsten; Koperski, Krzysztof

    2002-11-01

    We describe a system for interactive classification and retrieval of microscopic tissue images. Our system models tissues in pixel, region and image levels. Pixel level features are generated using unsupervised clustering of color and texture values. Region level features include shape information and statistics of pixel level feature values. Image level features include statistics and spatial relationships of regions. To reduce the gap between low-level features and high-level expert knowledge, we define the concept of prototype regions. The system learns the prototype regions in an image collection using model-based clustering and density estimation. Different tissue types are modeled using spatial relationships of these regions. Spatial relationships are represented by fuzzy membership functions. The system automatically selects significant relationships from training data and builds models which can also be updated using user relevance feedback. A Bayesian framework is used to classify tissues based on these models. Preliminary experiments show that the spatial relationship models we developed provide a flexible and powerful framework for classification and retrieval of tissue images.

  14. Drunk driving detection based on classification of multivariate time series.

    Science.gov (United States)

    Li, Zhenlong; Jin, Xue; Zhao, Xiaohua

    2015-09-01

    This paper addresses the problem of detecting drunk driving based on classification of multivariate time series. First, driving performance measures were collected from a test in a driving simulator located in the Traffic Research Center, Beijing University of Technology. Lateral position and steering angle were used to detect drunk driving. Second, multivariate time series analysis was performed to extract the features. A piecewise linear representation was used to represent multivariate time series. A bottom-up algorithm was then employed to separate multivariate time series. The slope and time interval of each segment were extracted as the features for classification. Third, a support vector machine classifier was used to classify driver's state into two classes (normal or drunk) according to the extracted features. The proposed approach achieved an accuracy of 80.0%. Drunk driving detection based on the analysis of multivariate time series is feasible and effective. The approach has implications for drunk driving detection. Copyright © 2015 Elsevier Ltd and National Safety Council. All rights reserved.

  15. Multiple kernel boosting framework based on information measure for classification

    International Nuclear Information System (INIS)

    Qi, Chengming; Wang, Yuping; Tian, Wenjie; Wang, Qun

    2016-01-01

    The performance of kernel-based method, such as support vector machine (SVM), is greatly affected by the choice of kernel function. Multiple kernel learning (MKL) is a promising family of machine learning algorithms and has attracted many attentions in recent years. MKL combines multiple sub-kernels to seek better results compared to single kernel learning. In order to improve the efficiency of SVM and MKL, in this paper, the Kullback–Leibler kernel function is derived to develop SVM. The proposed method employs an improved ensemble learning framework, named KLMKB, which applies Adaboost to learning multiple kernel-based classifier. In the experiment for hyperspectral remote sensing image classification, we employ feature selected through Optional Index Factor (OIF) to classify the satellite image. We extensively examine the performance of our approach in comparison to some relevant and state-of-the-art algorithms on a number of benchmark classification data sets and hyperspectral remote sensing image data set. Experimental results show that our method has a stable behavior and a noticeable accuracy for different data set.

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

    Science.gov (United States)

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

    2011-09-01

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

  17. Robust Pedestrian Classification Based on Hierarchical Kernel Sparse Representation

    Directory of Open Access Journals (Sweden)

    Rui Sun

    2016-08-01

    Full Text Available Vision-based pedestrian detection has become an active topic in computer vision and autonomous vehicles. It aims at detecting pedestrians appearing ahead of the vehicle using a camera so that autonomous vehicles can assess the danger and take action. Due to varied illumination and appearance, complex background and occlusion pedestrian detection in outdoor environments is a difficult problem. In this paper, we propose a novel hierarchical feature extraction and weighted kernel sparse representation model for pedestrian classification. Initially, hierarchical feature extraction based on a CENTRIST descriptor is used to capture discriminative structures. A max pooling operation is used to enhance the invariance of varying appearance. Then, a kernel sparse representation model is proposed to fully exploit the discrimination information embedded in the hierarchical local features, and a Gaussian weight function as the measure to effectively handle the occlusion in pedestrian images. Extensive experiments are conducted on benchmark databases, including INRIA, Daimler, an artificially generated dataset and a real occluded dataset, demonstrating the more robust performance of the proposed method compared to state-of-the-art pedestrian classification methods.

  18. Style-based classification of Chinese ink and wash paintings

    Science.gov (United States)

    Sheng, Jiachuan; Jiang, Jianmin

    2013-09-01

    Following the fact that a large collection of ink and wash paintings (IWP) is being digitized and made available on the Internet, their automated content description, analysis, and management are attracting attention across research communities. While existing research in relevant areas is primarily focused on image processing approaches, a style-based algorithm is proposed to classify IWPs automatically by their authors. As IWPs do not have colors or even tones, the proposed algorithm applies edge detection to locate the local region and detect painting strokes to enable histogram-based feature extraction and capture of important cues to reflect the styles of different artists. Such features are then applied to drive a number of neural networks in parallel to complete the classification, and an information entropy balanced fusion is proposed to make an integrated decision for the multiple neural network classification results in which the entropy is used as a pointer to combine the global and local features. Evaluations via experiments support that the proposed algorithm achieves good performances, providing excellent potential for computerized analysis and management of IWPs.

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

    Science.gov (United States)

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

    2017-07-01

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

  20. A Simple K-Map Based Variable Selection Scheme in the Direct ...

    African Journals Online (AJOL)

    A multiplexer with (n-l) data select inputs can realise directly a function of n variables. In this paper, a simple k-map based variable selection scheme is proposed such that an n variable logic function can be synthesised using a multiplexer with (n-q) data input variables and q data select variables. The procedure is based on ...