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Sample records for hybrid feature set

  1. A Relation Extraction Framework for Biomedical Text Using Hybrid Feature Set

    Directory of Open Access Journals (Sweden)

    Abdul Wahab Muzaffar

    2015-01-01

    Full Text Available The information extraction from unstructured text segments is a complex task. Although manual information extraction often produces the best results, it is harder to manage biomedical data extraction manually because of the exponential increase in data size. Thus, there is a need for automatic tools and techniques for information extraction in biomedical text mining. Relation extraction is a significant area under biomedical information extraction that has gained much importance in the last two decades. A lot of work has been done on biomedical relation extraction focusing on rule-based and machine learning techniques. In the last decade, the focus has changed to hybrid approaches showing better results. This research presents a hybrid feature set for classification of relations between biomedical entities. The main contribution of this research is done in the semantic feature set where verb phrases are ranked using Unified Medical Language System (UMLS and a ranking algorithm. Support Vector Machine and Naïve Bayes, the two effective machine learning techniques, are used to classify these relations. Our approach has been validated on the standard biomedical text corpus obtained from MEDLINE 2001. Conclusively, it can be articulated that our framework outperforms all state-of-the-art approaches used for relation extraction on the same corpus.

  2. Compact and Hybrid Feature Description for Building Extraction

    Science.gov (United States)

    Li, Z.; Liu, Y.; Hu, Y.; Li, P.; Ding, Y.

    2017-05-01

    Building extraction in aerial orthophotos is crucial for various applications. Currently, deep learning has been shown to be successful in addressing building extraction with high accuracy and high robustness. However, quite a large number of samples is required in training a classifier when using deep learning model. In order to realize accurate and semi-interactive labelling, the performance of feature description is crucial, as it has significant effect on the accuracy of classification. In this paper, we bring forward a compact and hybrid feature description method, in order to guarantees desirable classification accuracy of the corners on the building roof contours. The proposed descriptor is a hybrid description of an image patch constructed from 4 sets of binary intensity tests. Experiments show that benefiting from binary description and making full use of color channels, this descriptor is not only computationally frugal, but also accurate than SURF for building extraction.

  3. Hybrid feature selection for supporting lightweight intrusion detection systems

    Science.gov (United States)

    Song, Jianglong; Zhao, Wentao; Liu, Qiang; Wang, Xin

    2017-08-01

    Redundant and irrelevant features not only cause high resource consumption but also degrade the performance of Intrusion Detection Systems (IDS), especially when coping with big data. These features slow down the process of training and testing in network traffic classification. Therefore, a hybrid feature selection approach in combination with wrapper and filter selection is designed in this paper to build a lightweight intrusion detection system. Two main phases are involved in this method. The first phase conducts a preliminary search for an optimal subset of features, in which the chi-square feature selection is utilized. The selected set of features from the previous phase is further refined in the second phase in a wrapper manner, in which the Random Forest(RF) is used to guide the selection process and retain an optimized set of features. After that, we build an RF-based detection model and make a fair comparison with other approaches. The experimental results on NSL-KDD datasets show that our approach results are in higher detection accuracy as well as faster training and testing processes.

  4. Breast Cancer Detection with Reduced Feature Set

    Directory of Open Access Journals (Sweden)

    Ahmet Mert

    2015-01-01

    Full Text Available This paper explores feature reduction properties of independent component analysis (ICA on breast cancer decision support system. Wisconsin diagnostic breast cancer (WDBC dataset is reduced to one-dimensional feature vector computing an independent component (IC. The original data with 30 features and reduced one feature (IC are used to evaluate diagnostic accuracy of the classifiers such as k-nearest neighbor (k-NN, artificial neural network (ANN, radial basis function neural network (RBFNN, and support vector machine (SVM. The comparison of the proposed classification using the IC with original feature set is also tested on different validation (5/10-fold cross-validations and partitioning (20%–40% methods. These classifiers are evaluated how to effectively categorize tumors as benign and malignant in terms of specificity, sensitivity, accuracy, F-score, Youden’s index, discriminant power, and the receiver operating characteristic (ROC curve with its criterion values including area under curve (AUC and 95% confidential interval (CI. This represents an improvement in diagnostic decision support system, while reducing computational complexity.

  5. Generalized rough sets hybrid structure and applications

    CERN Document Server

    Mukherjee, Anjan

    2015-01-01

    The book introduces the concept of “generalized interval valued intuitionistic fuzzy soft sets”. It presents the basic properties of these sets and also, investigates an application of generalized interval valued intuitionistic fuzzy soft sets in decision making with respect to interval of degree of preference. The concept of “interval valued intuitionistic fuzzy soft rough sets” is discussed and interval valued intuitionistic fuzzy soft rough set based multi criteria group decision making scheme is presented, which refines the primary evaluation of the whole expert group and enables us to select the optimal object in a most reliable manner. The book also details concept of interval valued intuitionistic fuzzy sets of type 2. It presents the basic properties of these sets. The book also introduces the concept of “interval valued intuitionistic fuzzy soft topological space (IVIFS topological space)” together with intuitionistic fuzzy soft open sets (IVIFS open sets) and intuitionistic fuzzy soft cl...

  6. Discovering highly informative feature set over high dimensions

    KAUST Repository

    Zhang, Chongsheng; Masseglia, Florent; Zhang, Xiangliang

    2012-01-01

    For many textual collections, the number of features is often overly large. These features can be very redundant, it is therefore desirable to have a small, succinct, yet highly informative collection of features that describes the key characteristics of a dataset. Information theory is one such tool for us to obtain this feature collection. With this paper, we mainly contribute to the improvement of efficiency for the process of selecting the most informative feature set over high-dimensional unlabeled data. We propose a heuristic theory for informative feature set selection from high dimensional data. Moreover, we design data structures that enable us to compute the entropies of the candidate feature sets efficiently. We also develop a simple pruning strategy that eliminates the hopeless candidates at each forward selection step. We test our method through experiments on real-world data sets, showing that our proposal is very efficient. © 2012 IEEE.

  7. Discovering highly informative feature set over high dimensions

    KAUST Repository

    Zhang, Chongsheng

    2012-11-01

    For many textual collections, the number of features is often overly large. These features can be very redundant, it is therefore desirable to have a small, succinct, yet highly informative collection of features that describes the key characteristics of a dataset. Information theory is one such tool for us to obtain this feature collection. With this paper, we mainly contribute to the improvement of efficiency for the process of selecting the most informative feature set over high-dimensional unlabeled data. We propose a heuristic theory for informative feature set selection from high dimensional data. Moreover, we design data structures that enable us to compute the entropies of the candidate feature sets efficiently. We also develop a simple pruning strategy that eliminates the hopeless candidates at each forward selection step. We test our method through experiments on real-world data sets, showing that our proposal is very efficient. © 2012 IEEE.

  8. Performance Evaluation of Feature Sets of Minutiae Quadruplets ...

    African Journals Online (AJOL)

    The features proposed in this paper are derived from minutiae quadruplets and are applicable in matching and indexing ngerprint images. In this work nineteen different possibilities of features were explored for indexing and the performances of some of the feature sets were mixed: some giving good performances on ...

  9. Multithreaded hybrid feature tracking for markerless augmented reality.

    Science.gov (United States)

    Lee, Taehee; Höllerer, Tobias

    2009-01-01

    We describe a novel markerless camera tracking approach and user interaction methodology for augmented reality (AR) on unprepared tabletop environments. We propose a real-time system architecture that combines two types of feature tracking. Distinctive image features of the scene are detected and tracked frame-to-frame by computing optical flow. In order to achieve real-time performance, multiple operations are processed in a synchronized multi-threaded manner: capturing a video frame, tracking features using optical flow, detecting distinctive invariant features, and rendering an output frame. We also introduce user interaction methodology for establishing a global coordinate system and for placing virtual objects in the AR environment by tracking a user's outstretched hand and estimating a camera pose relative to it. We evaluate the speed and accuracy of our hybrid feature tracking approach, and demonstrate a proof-of-concept application for enabling AR in unprepared tabletop environments, using bare hands for interaction.

  10. Design features of HTMR-Hybrid Toroidal Magnet Tokamak Reactor

    International Nuclear Information System (INIS)

    Rosatelli, F.; Avanzini, P.G.; Brunelli, B.; Derchi, D.; Magnasco, M.; Grattarola, M.; Peluffo, M.; Raia, G.; Zampaglione, V.

    1985-01-01

    The HTMR (Hybrid Toroidal Magnet Tokamak Reactor) conceptual design is aimed to demonstrate the feasibility of a Tokamak reactor which could fulfill the scientific and technological objectives expected from next generation devices (e.g. INTOR-NET) with size and costs as small as possible. An hybrid toroidal field magnet, made up by copper and superconducting coils, seems to be a promising solution, allowing a considerable flexibility in machine performances, so as to gain useful margins in front of the uncertainties in confinement time scaling laws and beta and plasma density limits. In this paper the authors describe the optimization procedure for the hybrid magnet configuration, the main design features of HTMR and the preliminary mechanical calculations of the superconducting toroidal coils

  11. Design features of HTMR-hybrid toroidal magnet tokamak reactor

    International Nuclear Information System (INIS)

    Rosatelli, F.; Avanzini, P.G.; Derchi, D.; Magnasco, M.; Grattarola, M.; Peluffo, M.; Raia, G.; Brunelli, B.; Zampaglione, V.

    1984-01-01

    The HTMR (Hybrid Toroidal Magnet Tokamak Reactor) conceptual design is aimed to demonstrate the feasibility of a Tokamak reactor which could fulfil the scientific and technological objectives expected from next generation devices with size and costs as small as possible. A hybrid toroidal field magnet, made up by copper and superconducting coils, seems to be a promising solution, allowing a considerable flexibility in machine performances, so as to gain useful margins in front of the uncertainties in confinement time scaling laws and beta and plasma density limits. The optimization procedure for the hybrid magnet, configuration, the main design features of HTMR and the preliminary mechanical calculations of the superconducting toroidal coils are described. (author)

  12. HybridGO-Loc: mining hybrid features on gene ontology for predicting subcellular localization of multi-location proteins.

    Science.gov (United States)

    Wan, Shibiao; Mak, Man-Wai; Kung, Sun-Yuan

    2014-01-01

    Protein subcellular localization prediction, as an essential step to elucidate the functions in vivo of proteins and identify drugs targets, has been extensively studied in previous decades. Instead of only determining subcellular localization of single-label proteins, recent studies have focused on predicting both single- and multi-location proteins. Computational methods based on Gene Ontology (GO) have been demonstrated to be superior to methods based on other features. However, existing GO-based methods focus on the occurrences of GO terms and disregard their relationships. This paper proposes a multi-label subcellular-localization predictor, namely HybridGO-Loc, that leverages not only the GO term occurrences but also the inter-term relationships. This is achieved by hybridizing the GO frequencies of occurrences and the semantic similarity between GO terms. Given a protein, a set of GO terms are retrieved by searching against the gene ontology database, using the accession numbers of homologous proteins obtained via BLAST search as the keys. The frequency of GO occurrences and semantic similarity (SS) between GO terms are used to formulate frequency vectors and semantic similarity vectors, respectively, which are subsequently hybridized to construct fusion vectors. An adaptive-decision based multi-label support vector machine (SVM) classifier is proposed to classify the fusion vectors. Experimental results based on recent benchmark datasets and a new dataset containing novel proteins show that the proposed hybrid-feature predictor significantly outperforms predictors based on individual GO features as well as other state-of-the-art predictors. For readers' convenience, the HybridGO-Loc server, which is for predicting virus or plant proteins, is available online at http://bioinfo.eie.polyu.edu.hk/HybridGoServer/.

  13. A Hybrid Feature Selection Approach for Arabic Documents Classification

    NARCIS (Netherlands)

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

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

  14. Level Sets and Voronoi based Feature Extraction from any Imagery

    DEFF Research Database (Denmark)

    Sharma, O.; Anton, François; Mioc, Darka

    2012-01-01

    Polygon features are of interest in many GEOProcessing applications like shoreline mapping, boundary delineation, change detection, etc. This paper presents a unique new GPU-based methodology to automate feature extraction combining level sets, or mean shift based segmentation together with Voron...

  15. Relevant test set using feature selection algorithm for early detection ...

    African Journals Online (AJOL)

    The objective of feature selection is to find the most relevant features for classification. Thus, the dimensionality of the information will be reduced and may improve classification's accuracy. This paper proposed a minimum set of relevant questions that can be used for early detection of dyslexia. In this research, we ...

  16. Annotation-based feature extraction from sets of SBML models.

    Science.gov (United States)

    Alm, Rebekka; Waltemath, Dagmar; Wolfien, Markus; Wolkenhauer, Olaf; Henkel, Ron

    2015-01-01

    Model repositories such as BioModels Database provide computational models of biological systems for the scientific community. These models contain rich semantic annotations that link model entities to concepts in well-established bio-ontologies such as Gene Ontology. Consequently, thematically similar models are likely to share similar annotations. Based on this assumption, we argue that semantic annotations are a suitable tool to characterize sets of models. These characteristics improve model classification, allow to identify additional features for model retrieval tasks, and enable the comparison of sets of models. In this paper we discuss four methods for annotation-based feature extraction from model sets. We tested all methods on sets of models in SBML format which were composed from BioModels Database. To characterize each of these sets, we analyzed and extracted concepts from three frequently used ontologies, namely Gene Ontology, ChEBI and SBO. We find that three out of the methods are suitable to determine characteristic features for arbitrary sets of models: The selected features vary depending on the underlying model set, and they are also specific to the chosen model set. We show that the identified features map on concepts that are higher up in the hierarchy of the ontologies than the concepts used for model annotations. Our analysis also reveals that the information content of concepts in ontologies and their usage for model annotation do not correlate. Annotation-based feature extraction enables the comparison of model sets, as opposed to existing methods for model-to-keyword comparison, or model-to-model comparison.

  17. Hybrid Electric Energy Storages: Their Specific Features and Application (Review)

    Science.gov (United States)

    Popel', O. S.; Tarasenko, A. B.

    2018-05-01

    The article presents a review of various aspects related to development and practical use of hybrid electric energy storages (i.e., those uniting different energy storage technologies and devices in an integrated system) in transport and conventional and renewable power engineering applications. Such devices, which were initially developed for transport power installations, are increasingly being used by other consumers characterized by pronounced nonuniformities of their load schedule. A range of tasks solved using such energy storages is considered. It is shown that, owing to the advent of new types of energy storages and the extended spectrum of their performance characteristics, new possibilities for combining different types of energy storages and for developing hybrid systems have become available. This, in turn, opens up the possibility of making energy storages with better mass and dimension characteristics and achieving essentially lower operational costs. The possibility to secure more comfortable (base) operating modes of primary sources of energy (heat engines and renewable energy source based power installations) and to achieve a higher capacity utilization factor are unquestionable merits of hybrid energy storages. Development of optimal process circuit solutions, as well as energy conversion and control devices facilitating the fullest utilization of the properties of each individual energy storage included in the hybrid system, is among the important lines of research carried out in this field in Russia and abroad. Our review of existing developments has shown that there are no universal technical solutions in this field (the specific features of a consumer have an essential effect on the process circuit solutions and on the composition of a hybrid energy storage), a circumstance that dictates the need to extend the scope of investigations in this promising field.

  18. performance evaluation of feature sets of minutiae quadruplets

    African Journals Online (AJOL)

    databases. This shows that the evaluation of algorithms on just one or two databases is not sufficient to confirm the performance of tech- niques as they may be database-dependent. Much work was done to find a feature-set that would have a good performance across three. FVC databases of the FVC 2000, 2002 and. 2004 ...

  19. A linear-time algorithm for Euclidean feature transform sets

    NARCIS (Netherlands)

    Hesselink, Wim H.

    2007-01-01

    The Euclidean distance transform of a binary image is the function that assigns to every pixel the Euclidean distance to the background. The Euclidean feature transform is the function that assigns to every pixel the set of background pixels with this distance. We present an algorithm to compute the

  20. Hybrid Histogram Descriptor: A Fusion Feature Representation for Image Retrieval.

    Science.gov (United States)

    Feng, Qinghe; Hao, Qiaohong; Chen, Yuqi; Yi, Yugen; Wei, Ying; Dai, Jiangyan

    2018-06-15

    Currently, visual sensors are becoming increasingly affordable and fashionable, acceleratingly the increasing number of image data. Image retrieval has attracted increasing interest due to space exploration, industrial, and biomedical applications. Nevertheless, designing effective feature representation is acknowledged as a hard yet fundamental issue. This paper presents a fusion feature representation called a hybrid histogram descriptor (HHD) for image retrieval. The proposed descriptor comprises two histograms jointly: a perceptually uniform histogram which is extracted by exploiting the color and edge orientation information in perceptually uniform regions; and a motif co-occurrence histogram which is acquired by calculating the probability of a pair of motif patterns. To evaluate the performance, we benchmarked the proposed descriptor on RSSCN7, AID, Outex-00013, Outex-00014 and ETHZ-53 datasets. Experimental results suggest that the proposed descriptor is more effective and robust than ten recent fusion-based descriptors under the content-based image retrieval framework. The computational complexity was also analyzed to give an in-depth evaluation. Furthermore, compared with the state-of-the-art convolutional neural network (CNN)-based descriptors, the proposed descriptor also achieves comparable performance, but does not require any training process.

  1. Electricity market price spike analysis by a hybrid data model and feature selection technique

    International Nuclear Information System (INIS)

    Amjady, Nima; Keynia, Farshid

    2010-01-01

    In a competitive electricity market, energy price forecasting is an important activity for both suppliers and consumers. For this reason, many techniques have been proposed to predict electricity market prices in the recent years. However, electricity price is a complex volatile signal owning many spikes. Most of electricity price forecast techniques focus on the normal price prediction, while price spike forecast is a different and more complex prediction process. Price spike forecasting has two main aspects: prediction of price spike occurrence and value. In this paper, a novel technique for price spike occurrence prediction is presented composed of a new hybrid data model, a novel feature selection technique and an efficient forecast engine. The hybrid data model includes both wavelet and time domain variables as well as calendar indicators, comprising a large candidate input set. The set is refined by the proposed feature selection technique evaluating both relevancy and redundancy of the candidate inputs. The forecast engine is a probabilistic neural network, which are fed by the selected candidate inputs of the feature selection technique and predict price spike occurrence. The efficiency of the whole proposed method for price spike occurrence forecasting is evaluated by means of real data from the Queensland and PJM electricity markets. (author)

  2. Skull defect reconstruction based on a new hybrid level set.

    Science.gov (United States)

    Zhang, Ziqun; Zhang, Ran; Song, Zhijian

    2014-01-01

    Skull defect reconstruction is an important aspect of surgical repair. Historically, a skull defect prosthesis was created by the mirroring technique, surface fitting, or formed templates. These methods are not based on the anatomy of the individual patient's skull, and therefore, the prosthesis cannot precisely correct the defect. This study presented a new hybrid level set model, taking into account both the global optimization region information and the local accuracy edge information, while avoiding re-initialization during the evolution of the level set function. Based on the new method, a skull defect was reconstructed, and the skull prosthesis was produced by rapid prototyping technology. This resulted in a skull defect prosthesis that well matched the skull defect with excellent individual adaptation.

  3. Comparing sociocultural features of cholera in three endemic African settings

    Science.gov (United States)

    2013-01-01

    Background Cholera mainly affects developing countries where safe water supply and sanitation infrastructure are often rudimentary. Sub-Saharan Africa is a cholera hotspot. Effective cholera control requires not only a professional assessment, but also consideration of community-based priorities. The present work compares local sociocultural features of endemic cholera in urban and rural sites from three field studies in southeastern Democratic Republic of Congo (SE-DRC), western Kenya and Zanzibar. Methods A vignette-based semistructured interview was used in 2008 in Zanzibar to study sociocultural features of cholera-related illness among 356 men and women from urban and rural communities. Similar cross-sectional surveys were performed in western Kenya (n = 379) and in SE-DRC (n = 360) in 2010. Systematic comparison across all settings considered the following domains: illness identification; perceived seriousness, potential fatality and past household episodes; illness-related experience; meaning; knowledge of prevention; help-seeking behavior; and perceived vulnerability. Results Cholera is well known in all three settings and is understood to have a significant impact on people’s lives. Its social impact was mainly characterized by financial concerns. Problems with unsafe water, sanitation and dirty environments were the most common perceived causes across settings; nonetheless, non-biomedical explanations were widespread in rural areas of SE-DRC and Zanzibar. Safe food and water and vaccines were prioritized for prevention in SE-DRC. Safe water was prioritized in western Kenya along with sanitation and health education. The latter two were also prioritized in Zanzibar. Use of oral rehydration solutions and rehydration was a top priority everywhere; healthcare facilities were universally reported as a primary source of help. Respondents in SE-DRC and Zanzibar reported cholera as affecting almost everybody without differentiating much for gender, age

  4. A Hybrid Feature Subset Selection Algorithm for Analysis of High Correlation Proteomic Data

    Science.gov (United States)

    Kordy, Hussain Montazery; Baygi, Mohammad Hossein Miran; Moradi, Mohammad Hassan

    2012-01-01

    Pathological changes within an organ can be reflected as proteomic patterns in biological fluids such as plasma, serum, and urine. The surface-enhanced laser desorption and ionization time-of-flight mass spectrometry (SELDI-TOF MS) has been used to generate proteomic profiles from biological fluids. Mass spectrometry yields redundant noisy data that the most data points are irrelevant features for differentiating between cancer and normal cases. In this paper, we have proposed a hybrid feature subset selection algorithm based on maximum-discrimination and minimum-correlation coupled with peak scoring criteria. Our algorithm has been applied to two independent SELDI-TOF MS datasets of ovarian cancer obtained from the NCI-FDA clinical proteomics databank. The proposed algorithm has used to extract a set of proteins as potential biomarkers in each dataset. We applied the linear discriminate analysis to identify the important biomarkers. The selected biomarkers have been able to successfully diagnose the ovarian cancer patients from the noncancer control group with an accuracy of 100%, a sensitivity of 100%, and a specificity of 100% in the two datasets. The hybrid algorithm has the advantage that increases reproducibility of selected biomarkers and able to find a small set of proteins with high discrimination power. PMID:23717808

  5. Features of standardized nursing terminology sets in Japan.

    Science.gov (United States)

    Sagara, Kaoru; Abe, Akinori; Ozaku, Hiromi Itoh; Kuwahara, Noriaki; Kogure, Kiyoshi

    2006-01-01

    This paper reports the features and relationships between standardizes nursing terminology sets used in Japan. First, we analyzed the common parts in five standardized nursing terminology sets: the Japan Nursing Practice Standard Master (JNPSM) that includes the names of nursing activities and is built by the Medical Information Center Development Center (MEDIS-DC); the labels of the Japan Classification of Nursing Practice (JCNP), built by the term advisory committee in the Japan Academy of Nursing Science; the labels of the International Classification for Nursing Practice (ICNP) translated to Japanese; the labels, domain names, and class names of the North American Nursing Diagnosis Association (NANDA) Nursing Diagnoses 2003-2004 translated to Japanese; and the terms included in the labels of Nursing Interventions Classification (NIC) translated to Japanese. Then we compared them with terms in a thesaurus dictionary, the Bunrui Goihyo, that contains general Japanese words and is built by the National Institute for Japanese Language. 1) the level of interchangeability between four standardized nursing terminology sets is quite low; 2) abbreviations and katakana words are frequently used to express nursing activities; 3) general Japanese words are usually used to express the status or situation of patients.

  6. Specific features of goal setting in road traffic safety

    Science.gov (United States)

    Kolesov, V. I.; Danilov, O. F.; Petrov, A. I.

    2017-10-01

    Road traffic safety (RTS) management is inherently a branch of cybernetics and therefore requires clear formalization of the task. The paper aims at identification of the specific features of goal setting in RTS management under the system approach. The paper presents the results of cybernetic modeling of the cause-to-effect mechanism of a road traffic accident (RTA); in here, the mechanism itself is viewed as a complex system. A designed management goal function is focused on minimizing the difficulty in achieving the target goal. Optimization of the target goal has been performed using the Lagrange principle. The created working algorithms have passed the soft testing. The key role of the obtained solution in the tactical and strategic RTS management is considered. The dynamics of the management effectiveness indicator has been analyzed based on the ten-year statistics for Russia.

  7. Set of Frequent Word Item sets as Feature Representation for Text with Indonesian Slang

    Science.gov (United States)

    Sa'adillah Maylawati, Dian; Putri Saptawati, G. A.

    2017-01-01

    Indonesian slang are commonly used in social media. Due to their unstructured syntax, it is difficult to extract their features based on Indonesian grammar for text mining. To do so, we propose Set of Frequent Word Item sets (SFWI) as text representation which is considered match for Indonesian slang. Besides, SFWI is able to keep the meaning of Indonesian slang with regard to the order of appearance sentence. We use FP-Growth algorithm with adding separation sentence function into the algorithm to extract the feature of SFWI. The experiments is done with text data from social media such as Facebook, Twitter, and personal website. The result of experiments shows that Indonesian slang were more correctly interpreted based on SFWI.

  8. Space – An Essential Feature of the Hybrid War

    Directory of Open Access Journals (Sweden)

    Ioniţă Dorin

    2017-03-01

    Full Text Available Hybrid Warfare is an unofficial intellectual construct to describe the combination or integration of conventional and non-conventional approaches used by adversaries to avoid conventional military strengths, often times occurring below the threshold that would trigger a conventional military.

  9. Diffusion tensor image registration using hybrid connectivity and tensor features.

    Science.gov (United States)

    Wang, Qian; Yap, Pew-Thian; Wu, Guorong; Shen, Dinggang

    2014-07-01

    Most existing diffusion tensor imaging (DTI) registration methods estimate structural correspondences based on voxelwise matching of tensors. The rich connectivity information that is given by DTI, however, is often neglected. In this article, we propose to integrate complementary information given by connectivity features and tensor features for improved registration accuracy. To utilize connectivity information, we place multiple anchors representing different brain anatomies in the image space, and define the connectivity features for each voxel as the geodesic distances from all anchors to the voxel under consideration. The geodesic distance, which is computed in relation to the tensor field, encapsulates information of brain connectivity. We also extract tensor features for every voxel to reflect the local statistics of tensors in its neighborhood. We then combine both connectivity features and tensor features for registration of tensor images. From the images, landmarks are selected automatically and their correspondences are determined based on their connectivity and tensor feature vectors. The deformation field that deforms one tensor image to the other is iteratively estimated and optimized according to the landmarks and their associated correspondences. Experimental results show that, by using connectivity features and tensor features simultaneously, registration accuracy is increased substantially compared with the cases using either type of features alone. Copyright © 2013 Wiley Periodicals, Inc.

  10. A novel approach for fire recognition using hybrid features and manifold learning-based classifier

    Science.gov (United States)

    Zhu, Rong; Hu, Xueying; Tang, Jiajun; Hu, Sheng

    2018-03-01

    Although image/video based fire recognition has received growing attention, an efficient and robust fire detection strategy is rarely explored. In this paper, we propose a novel approach to automatically identify the flame or smoke regions in an image. It is composed to three stages: (1) a block processing is applied to divide an image into several nonoverlapping image blocks, and these image blocks are identified as suspicious fire regions or not by using two color models and a color histogram-based similarity matching method in the HSV color space, (2) considering that compared to other information, the flame and smoke regions have significant visual characteristics, so that two kinds of image features are extracted for fire recognition, where local features are obtained based on the Scale Invariant Feature Transform (SIFT) descriptor and the Bags of Keypoints (BOK) technique, and texture features are extracted based on the Gray Level Co-occurrence Matrices (GLCM) and the Wavelet-based Analysis (WA) methods, and (3) a manifold learning-based classifier is constructed based on two image manifolds, which is designed via an improve Globular Neighborhood Locally Linear Embedding (GNLLE) algorithm, and the extracted hybrid features are used as input feature vectors to train the classifier, which is used to make decision for fire images or non fire images. Experiments and comparative analyses with four approaches are conducted on the collected image sets. The results show that the proposed approach is superior to the other ones in detecting fire and achieving a high recognition accuracy and a low error rate.

  11. Feature Selection using Multi-objective Genetic Algorith m: A Hybrid Approach

    OpenAIRE

    Ahuja, Jyoti; GJUST - Guru Jambheshwar University of Sciecne and Technology; Ratnoo, Saroj Dahiya; GJUST - Guru Jambheshwar University of Sciecne and Technology

    2015-01-01

    Feature selection is an important pre-processing task for building accurate and comprehensible classification models. Several researchers have applied filter, wrapper or hybrid approaches using genetic algorithms which are good candidates for optimization problems that involve large search spaces like in the case of feature selection. Moreover, feature selection is an inherently multi-objective problem with many competing objectives involving size, predictive power and redundancy of the featu...

  12. ANALYSIS DATA SETS USING HYBRID TECHNIQUES APPLIED ARTIFICIAL INTELLIGENCE BASED PRODUCTION SYSTEMS INTEGRATED DESIGN

    Directory of Open Access Journals (Sweden)

    Daniel-Petru GHENCEA

    2017-06-01

    Full Text Available The paper proposes a prediction model of behavior spindle from the point of view of the thermal deformations and the level of the vibrations by highlighting and processing the characteristic equations. This is a model analysis for the shaft with similar electro-mechanical characteristics can be achieved using a hybrid analysis based on artificial intelligence (genetic algorithms - artificial neural networks - fuzzy logic. The paper presents a prediction mode obtaining valid range of values for spindles with similar characteristics based on measured data sets from a few spindles test without additional measures being required. Extracting polynomial functions of graphs resulting from simultaneous measurements and predict the dynamics of the two features with multi-objective criterion is the main advantage of this method.

  13. MIL-STD-1553 dynamic bus controller/remote terminal hybrid set

    Science.gov (United States)

    Friedman, S. N.

    This paper describes the performance, physical and electrical requirements of a Dual Redundant BUS Interface Unit (BIU) acting as a BUS Controller Interface Unit (BCIU) or Remote Terminal Unit (RTU) between a Motorola 68000 VME BUS and MIL-STD-1553B Multiplex Data Bus. A discussion of how the BIU Hybrid set is programmed, and operates as a BCIU or RTU, will be included. This paper will review Dynamic Bus Control and other Mode Code capabilities. The BIU Hybrid Set interfaces to a 68000 Microprocessor with a VME Bus using programmed I/O transfers. This special interface will be discussed along with the internal Dual Access Memory (4K x 16) used to support the data exchanges between the CPU and the BIU Hybrid Set. The hybrid set's physical size and power requirements will be covered. This includes the present Double Eurocard the BIU function is presently being offered on.

  14. Hybrid Compensatory-Noncompensatory Choice Sets in Semicompensatory Models

    DEFF Research Database (Denmark)

    Kaplan, Sigal; Bekhor, Shlomo; Shiftan, Yoram

    2013-01-01

    Semicompensatory models represent a choice process consisting of an elimination-based choice set formation on satisfaction of criterion thresholds and a utility-based choice. Current semicompensatory models assume a purely noncompensatory choice set formation and therefore do not support multinom...

  15. Influence of Familiar Features on Diagnosis: Instantiated Features in an Applied Setting

    Science.gov (United States)

    Dore, Kelly L.; Brooks, Lee R.; Weaver, Bruce; Norman, Geoffrey R.

    2012-01-01

    Medical diagnosis can be viewed as a categorization task. There are two mechanisms whereby humans make categorical judgments: "analytical reasoning," based on explicit consideration of features and "nonanalytical reasoning," an unconscious holistic process of matching against prior exemplars. However, there is evidence that prior experience can…

  16. An Improved Iris Recognition Algorithm Based on Hybrid Feature and ELM

    Science.gov (United States)

    Wang, Juan

    2018-03-01

    The iris image is easily polluted by noise and uneven light. This paper proposed an improved extreme learning machine (ELM) based iris recognition algorithm with hybrid feature. 2D-Gabor filters and GLCM is employed to generate a multi-granularity hybrid feature vector. 2D-Gabor filter and GLCM feature work for capturing low-intermediate frequency and high frequency texture information, respectively. Finally, we utilize extreme learning machine for iris recognition. Experimental results reveal our proposed ELM based multi-granularity iris recognition algorithm (ELM-MGIR) has higher accuracy of 99.86%, and lower EER of 0.12% under the premise of real-time performance. The proposed ELM-MGIR algorithm outperforms other mainstream iris recognition algorithms.

  17. Finite-Control-Set Model Predictive Control (FCS-MPC) for Islanded Hybrid Microgrids

    OpenAIRE

    Yi, Zhehan; Babqi, Abdulrahman J.; Wang, Yishen; Shi, Di; Etemadi, Amir H.; Wang, Zhiwei; Huang, Bibin

    2018-01-01

    Microgrids consisting of multiple distributed energy resources (DERs) provide a promising solution to integrate renewable energies, e.g., solar photovoltaic (PV) systems. Hybrid AC/DC microgrids leverage the merits of both AC and DC power systems. In this paper, a control strategy for islanded multi-bus hybrid microgrids is proposed based on the Finite-Control-Set Model Predictive Control (FCS-MPC) technologies. The control loops are expedited by predicting the future states and determining t...

  18. Finding an optimum immuno-histochemical feature set to distinguish benign phyllodes from fibroadenoma.

    Science.gov (United States)

    Maity, Priti Prasanna; Chatterjee, Subhamoy; Das, Raunak Kumar; Mukhopadhyay, Subhalaxmi; Maity, Ashok; Maulik, Dhrubajyoti; Ray, Ajoy Kumar; Dhara, Santanu; Chatterjee, Jyotirmoy

    2013-05-01

    Benign phyllodes and fibroadenoma are two well-known breast tumors with remarkable diagnostic ambiguity. The present study is aimed at determining an optimum set of immuno-histochemical features to distinguish them by analyzing important observations on expressions of important genes in fibro-glandular tissue. Immuno-histochemically, the expressions of p63 and α-SMA in myoepithelial cells and collagen I, III and CD105 in stroma of tumors and their normal counterpart were studied. Semi-quantified features were analyzed primarily by ANOVA and ranked through F-scores for understanding relative importance of group of features in discriminating three classes followed by reduction in F-score arranged feature space dimension and application of inter-class Bhattacharyya distances to distinguish tumors with an optimum set of features. Among thirteen studied features except one all differed significantly in three study classes. F-Ranking of features revealed highest discriminative potential of collagen III (initial region). F-Score arranged feature space dimension and application of Bhattacharyya distance gave rise to a feature set of lower dimension which can discriminate benign phyllodes and fibroadenoma effectively. The work definitely separated normal breast, fibroadenoma and benign phyllodes, through an optimal set of immuno-histochemical features which are not only useful to address diagnostic ambiguity of the tumors but also to spell about malignant potentiality. Copyright © 2013 Elsevier Ltd. All rights reserved.

  19. Prediction of hot spots in protein interfaces using a random forest model with hybrid features.

    Science.gov (United States)

    Wang, Lin; Liu, Zhi-Ping; Zhang, Xiang-Sun; Chen, Luonan

    2012-03-01

    Prediction of hot spots in protein interfaces provides crucial information for the research on protein-protein interaction and drug design. Existing machine learning methods generally judge whether a given residue is likely to be a hot spot by extracting features only from the target residue. However, hot spots usually form a small cluster of residues which are tightly packed together at the center of protein interface. With this in mind, we present a novel method to extract hybrid features which incorporate a wide range of information of the target residue and its spatially neighboring residues, i.e. the nearest contact residue in the other face (mirror-contact residue) and the nearest contact residue in the same face (intra-contact residue). We provide a novel random forest (RF) model to effectively integrate these hybrid features for predicting hot spots in protein interfaces. Our method can achieve accuracy (ACC) of 82.4% and Matthew's correlation coefficient (MCC) of 0.482 in Alanine Scanning Energetics Database, and ACC of 77.6% and MCC of 0.429 in Binding Interface Database. In a comparison study, performance of our RF model exceeds other existing methods, such as Robetta, FOLDEF, KFC, KFC2, MINERVA and HotPoint. Of our hybrid features, three physicochemical features of target residues (mass, polarizability and isoelectric point), the relative side-chain accessible surface area and the average depth index of mirror-contact residues are found to be the main discriminative features in hot spots prediction. We also confirm that hot spots tend to form large contact surface areas between two interacting proteins. Source data and code are available at: http://www.aporc.org/doc/wiki/HotSpot.

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

    Science.gov (United States)

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

    2015-01-01

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

  1. Conceptual Design of Hybrid Safety Features for NPP by Utilizing Solar Updraft Tower

    Energy Technology Data Exchange (ETDEWEB)

    Song, Sub Lee [Handong Global University, Pohang (Korea, Republic of); Choi, Young Jae; Kim, Yong Jin [KAIST, Daejeon (Korea, Republic of); Park, Hyo Chan; Park, Youn Won [BEES, Daejeon (Korea, Republic of)

    2016-05-15

    In this study, hybrid safety features for NPP with solar updraft tower (SUT) is conceptually suggested to cope with loss of ultimate heat sink accident. The hybrid safety features utilizing SUT target NPPs in seashore of Arabian Gulf. Usually NPPs are constructed near seashore to utilize sea water as an ultimate heat sink. Residual heat or decay heat of nuclear reactor will diffuse into the ocean through the condenser. NPPs in Middle East are expected to be placed in seashore of Arabian Gulf. The NPP site of Barakah is an actual example. For NPPs in seashore of Arabian Gulf, an additional safety concern should be considered. Arabian Gulf is the largest oil transporting route in the world. The oil spill risk in Arabian Gulf will be the largest simultaneously. Unfortunately, not like other oceans, Arabian Gulf is a kind of closed ocean which does not have strong ocean currents connected to out of the gulf. If once oil spill is occurred, its influence can be propagated more than our expectation. The spilled oil also can affect to NPPs in seashore by covering surfaces of condenser. It will directly cause loss of ultimate heat sink. The hybrid safety features of SUT system are expected to aid normal operation of safety system and mitigate consequence of severe accident. Detail analysis and technology development is ongoing now.

  2. Conceptual Design of Hybrid Safety Features for NPP by Utilizing Solar Updraft Tower

    International Nuclear Information System (INIS)

    Song, Sub Lee; Choi, Young Jae; Kim, Yong Jin; Park, Hyo Chan; Park, Youn Won

    2016-01-01

    In this study, hybrid safety features for NPP with solar updraft tower (SUT) is conceptually suggested to cope with loss of ultimate heat sink accident. The hybrid safety features utilizing SUT target NPPs in seashore of Arabian Gulf. Usually NPPs are constructed near seashore to utilize sea water as an ultimate heat sink. Residual heat or decay heat of nuclear reactor will diffuse into the ocean through the condenser. NPPs in Middle East are expected to be placed in seashore of Arabian Gulf. The NPP site of Barakah is an actual example. For NPPs in seashore of Arabian Gulf, an additional safety concern should be considered. Arabian Gulf is the largest oil transporting route in the world. The oil spill risk in Arabian Gulf will be the largest simultaneously. Unfortunately, not like other oceans, Arabian Gulf is a kind of closed ocean which does not have strong ocean currents connected to out of the gulf. If once oil spill is occurred, its influence can be propagated more than our expectation. The spilled oil also can affect to NPPs in seashore by covering surfaces of condenser. It will directly cause loss of ultimate heat sink. The hybrid safety features of SUT system are expected to aid normal operation of safety system and mitigate consequence of severe accident. Detail analysis and technology development is ongoing now

  3. Feature Set Evaluation for Offline Handwriting Recognition Systems: Application to the Recurrent Neural Network Model.

    Science.gov (United States)

    Chherawala, Youssouf; Roy, Partha Pratim; Cheriet, Mohamed

    2016-12-01

    The performance of handwriting recognition systems is dependent on the features extracted from the word image. A large body of features exists in the literature, but no method has yet been proposed to identify the most promising of these, other than a straightforward comparison based on the recognition rate. In this paper, we propose a framework for feature set evaluation based on a collaborative setting. We use a weighted vote combination of recurrent neural network (RNN) classifiers, each trained with a particular feature set. This combination is modeled in a probabilistic framework as a mixture model and two methods for weight estimation are described. The main contribution of this paper is to quantify the importance of feature sets through the combination weights, which reflect their strength and complementarity. We chose the RNN classifier because of its state-of-the-art performance. Also, we provide the first feature set benchmark for this classifier. We evaluated several feature sets on the IFN/ENIT and RIMES databases of Arabic and Latin script, respectively. The resulting combination model is competitive with state-of-the-art systems.

  4. Intelligent fault diagnosis of rolling bearing based on kernel neighborhood rough sets and statistical features

    Energy Technology Data Exchange (ETDEWEB)

    Zhu, Xiao Ran; Zhang, You Yun; Zhu, Yong Sheng [Xi' an Jiaotong Univ., Xi' an (China)

    2012-09-15

    Intelligent fault diagnosis benefits from efficient feature selection. Neighborhood rough sets are effective in feature selection. However, determining the neighborhood value accurately remains a challenge. The wrapper feature selection algorithm is designed by combining the kernel method and neighborhood rough sets to self-adaptively select sensitive features. The combination effectively solves the shortcomings in selecting the neighborhood value in the previous application process. The statistical features of time and frequency domains are used to describe the characteristic of the rolling bearing to make the intelligent fault diagnosis approach work. Three classification algorithms, namely, classification and regression tree (CART), commercial version 4.5 (C4.5), and radial basis function support vector machines (RBFSVM), are used to test UCI datasets and 10 fault datasets of rolling bearing. The results indicate that the diagnostic approach presented could effectively select the sensitive fault features and simultaneously identify the type and degree of the fault.

  5. Intelligent fault diagnosis of rolling bearing based on kernel neighborhood rough sets and statistical features

    International Nuclear Information System (INIS)

    Zhu, Xiao Ran; Zhang, You Yun; Zhu, Yong Sheng

    2012-01-01

    Intelligent fault diagnosis benefits from efficient feature selection. Neighborhood rough sets are effective in feature selection. However, determining the neighborhood value accurately remains a challenge. The wrapper feature selection algorithm is designed by combining the kernel method and neighborhood rough sets to self-adaptively select sensitive features. The combination effectively solves the shortcomings in selecting the neighborhood value in the previous application process. The statistical features of time and frequency domains are used to describe the characteristic of the rolling bearing to make the intelligent fault diagnosis approach work. Three classification algorithms, namely, classification and regression tree (CART), commercial version 4.5 (C4.5), and radial basis function support vector machines (RBFSVM), are used to test UCI datasets and 10 fault datasets of rolling bearing. The results indicate that the diagnostic approach presented could effectively select the sensitive fault features and simultaneously identify the type and degree of the fault

  6. A NEW STRATEGY FOR IMPROVING FEATURE SETS IN A DISCRETE HMM­BASED HANDWRITING RECOGNITION SYSTEM

    NARCIS (Netherlands)

    Grandidier, F.; Sabourin, R.; Suen, C.Y.; Gilloux, M.

    2004-01-01

    In this paper we introduce a new strategy for improving a discrete HMM­based handwriting recognition system, by integrating several information sources from specialized feature sets. For a given system, the basic idea is to keep the most discriminative features, and to replace the others with new

  7. Spatially hybrid computations for streamer discharges with generic features of pulled fronts: I. Planar fronts

    International Nuclear Information System (INIS)

    Li Chao; Ebert, Ute; Hundsdorfer, Willem

    2010-01-01

    Streamers are the first stage of sparks and lightning; they grow due to a strongly enhanced electric field at their tips; this field is created by a thin curved space charge layer. These multiple scales are already challenging when the electrons are approximated by densities. However, electron density fluctuations in the leading edge of the front and non-thermal stretched tails of the electron energy distribution (as a cause of X-ray emissions) require a particle model to follow the electron motion. But present computers cannot deal with all electrons in a fully developed streamer. Therefore, super-particle have to be introduced, which leads to wrong statistics and numerical artifacts. The method of choice is a hybrid computation in space where individual electrons are followed in the region of high electric field and low density while the bulk of the electrons is approximated by densities (or fluids). We here develop the hybrid coupling for planar fronts. First, to obtain a consistent flux at the interface between particle and fluid model in the hybrid computation, the widely used classical fluid model is replaced by an extended fluid model. Then the coupling algorithm and the numerical implementation of the spatially hybrid model are presented in detail, in particular, the position of the model interface and the construction of the buffer region. The method carries generic features of pulled fronts that can be applied to similar problems like large deviations in the leading edge of population fronts, etc.

  8. Complementary Self-Biased Logics Based on Single-Electron Transistor (SET)/CMOS Hybrid Process

    Science.gov (United States)

    Song, Ki-Whan; Lee, Yong Kyu; Sim, Jae Sung; Kim, Kyung Rok; Lee, Jong Duk; Park, Byung-Gook; You, Young Sub; Park, Joo-On; Jin, You Seung; Kim, Young-Wug

    2005-04-01

    We propose a complementary self-biasing method which enables the single-electron transistor (SET)/complementary metal-oxide semiconductor (CMOS) hybrid multi-valued logics (MVLs) to operate well at high temperatures, where the peak-to-valley current ratio (PVCR) of the Coulomb oscillation markedly decreases. The new architecture is implemented with a few transistors by utilizing the phase control capability of the sidewall depletion gates in dual-gate single-electron transistors (DGSETs). The suggested scheme is evaluated by a SPICE simulation with an analytical DGSET model. Furthermore, we have developed a new process technology for the SET/CMOS hybrid systems. We have confirmed that both of the fabricated devices, namely, SET and CMOS transistors, exhibit the ideal characteristics for the complementary self-biasing scheme: the SET shows clear Coulomb oscillations with a 100 mV period and the CMOS transistors show a high voltage gain.

  9. Fast detection of vascular plaque in optical coherence tomography images using a reduced feature set

    Science.gov (United States)

    Prakash, Ammu; Ocana Macias, Mariano; Hewko, Mark; Sowa, Michael; Sherif, Sherif

    2018-03-01

    Optical coherence tomography (OCT) images are capable of detecting vascular plaque by using the full set of 26 Haralick textural features and a standard K-means clustering algorithm. However, the use of the full set of 26 textural features is computationally expensive and may not be feasible for real time implementation. In this work, we identified a reduced set of 3 textural feature which characterizes vascular plaque and used a generalized Fuzzy C-means clustering algorithm. Our work involves three steps: 1) the reduction of a full set 26 textural feature to a reduced set of 3 textural features by using genetic algorithm (GA) optimization method 2) the implementation of an unsupervised generalized clustering algorithm (Fuzzy C-means) on the reduced feature space, and 3) the validation of our results using histology and actual photographic images of vascular plaque. Our results show an excellent match with histology and actual photographic images of vascular tissue. Therefore, our results could provide an efficient pre-clinical tool for the detection of vascular plaque in real time OCT imaging.

  10. Selecting Optimal Feature Set in High-Dimensional Data by Swarm Search

    Directory of Open Access Journals (Sweden)

    Simon Fong

    2013-01-01

    Full Text Available Selecting the right set of features from data of high dimensionality for inducing an accurate classification model is a tough computational challenge. It is almost a NP-hard problem as the combinations of features escalate exponentially as the number of features increases. Unfortunately in data mining, as well as other engineering applications and bioinformatics, some data are described by a long array of features. Many feature subset selection algorithms have been proposed in the past, but not all of them are effective. Since it takes seemingly forever to use brute force in exhaustively trying every possible combination of features, stochastic optimization may be a solution. In this paper, we propose a new feature selection scheme called Swarm Search to find an optimal feature set by using metaheuristics. The advantage of Swarm Search is its flexibility in integrating any classifier into its fitness function and plugging in any metaheuristic algorithm to facilitate heuristic search. Simulation experiments are carried out by testing the Swarm Search over some high-dimensional datasets, with different classification algorithms and various metaheuristic algorithms. The comparative experiment results show that Swarm Search is able to attain relatively low error rates in classification without shrinking the size of the feature subset to its minimum.

  11. Joint Markov Blankets in Feature Sets Extracted from Wavelet Packet Decompositions

    Directory of Open Access Journals (Sweden)

    Gert Van Dijck

    2011-07-01

    Full Text Available Since two decades, wavelet packet decompositions have been shown effective as a generic approach to feature extraction from time series and images for the prediction of a target variable. Redundancies exist between the wavelet coefficients and between the energy features that are derived from the wavelet coefficients. We assess these redundancies in wavelet packet decompositions by means of the Markov blanket filtering theory. We introduce the concept of joint Markov blankets. It is shown that joint Markov blankets are a natural extension of Markov blankets, which are defined for single features, to a set of features. We show that these joint Markov blankets exist in feature sets consisting of the wavelet coefficients. Furthermore, we prove that wavelet energy features from the highest frequency resolution level form a joint Markov blanket for all other wavelet energy features. The joint Markov blanket theory indicates that one can expect an increase of classification accuracy with the increase of the frequency resolution level of the energy features.

  12. A hybrid model for dissolved oxygen prediction in aquaculture based on multi-scale features

    Directory of Open Access Journals (Sweden)

    Chen Li

    2018-03-01

    Full Text Available To increase prediction accuracy of dissolved oxygen (DO in aquaculture, a hybrid model based on multi-scale features using ensemble empirical mode decomposition (EEMD is proposed. Firstly, original DO datasets are decomposed by EEMD and we get several components. Secondly, these components are used to reconstruct four terms including high frequency term, intermediate frequency term, low frequency term and trend term. Thirdly, according to the characteristics of high and intermediate frequency terms, which fluctuate violently, the least squares support vector machine (LSSVR is used to predict the two terms. The fluctuation of low frequency term is gentle and periodic, so it can be modeled by BP neural network with an optimal mind evolutionary computation (MEC-BP. Then, the trend term is predicted using grey model (GM because it is nearly linear. Finally, the prediction values of DO datasets are calculated by the sum of the forecasting values of all terms. The experimental results demonstrate that our hybrid model outperforms EEMD-ELM (extreme learning machine based on EEMD, EEMD-BP and MEC-BP models based on the mean absolute error (MAE, mean absolute percentage error (MAPE, mean square error (MSE and root mean square error (RMSE. Our hybrid model is proven to be an effective approach to predict aquaculture DO.

  13. Design and control of a hybrid mount featuring a magnetorheological fluid and a piezostack

    International Nuclear Information System (INIS)

    Han, Young-Min; Choi, Sang-Min; Choi, Seung-Bok; Lee, Ho-Guen

    2011-01-01

    In this study, a hybrid mount featuring a magnetorheological (MR) fluid and a piezostack is devised to reduce vibrations occuring in dynamic systems which are operated in a wide frequency range. An MR fluid is adopted to improve isolation performance at resonant low frequencies, whereas a piezostack actuator is adopted for performance improvement at non-resonant high frequencies. As a first step, a passive rubber part is manufactured and its dynamic characteristics are experimentally evaluated. By adopting the MR fluid and the piezostack, semi-active and active actuating mechanisms are devised and their mathematical models are derived. In particular, the magnetic circuit for MR operation is optimally designed via finite element analysis. After evaluating the dynamic characteristics of the manufactured MR device and inertial piezostack actuator, the proposed hybrid mount is then established by integrating them with the rubber part. Subsequently, a vibration control system is constructed using the proposed hybrid mount, and a sliding mode controller (SMC) is designed to attenuate the vibrations transmitted from the base excitation. Control performances of the proposed mount are experimentally evaluated in time and frequency domains

  14. A hybrid approach to select features and classify diseases based on medical data

    Science.gov (United States)

    AbdelLatif, Hisham; Luo, Jiawei

    2018-03-01

    Feature selection is popular problem in the classification of diseases in clinical medicine. Here, we developing a hybrid methodology to classify diseases, based on three medical datasets, Arrhythmia, Breast cancer, and Hepatitis datasets. This methodology called k-means ANOVA Support Vector Machine (K-ANOVA-SVM) uses K-means cluster with ANOVA statistical to preprocessing data and selection the significant features, and Support Vector Machines in the classification process. To compare and evaluate the performance, we choice three classification algorithms, decision tree Naïve Bayes, Support Vector Machines and applied the medical datasets direct to these algorithms. Our methodology was a much better classification accuracy is given of 98% in Arrhythmia datasets, 92% in Breast cancer datasets and 88% in Hepatitis datasets, Compare to use the medical data directly with decision tree Naïve Bayes, and Support Vector Machines. Also, the ROC curve and precision with (K-ANOVA-SVM) Achieved best results than other algorithms

  15. A Hybrid Feature Model and Deep-Learning-Based Bearing Fault Diagnosis

    Directory of Open Access Journals (Sweden)

    Muhammad Sohaib

    2017-12-01

    Full Text Available Bearing fault diagnosis is imperative for the maintenance, reliability, and durability of rotary machines. It can reduce economical losses by eliminating unexpected downtime in industry due to failure of rotary machines. Though widely investigated in the past couple of decades, continued advancement is still desirable to improve upon existing fault diagnosis techniques. Vibration acceleration signals collected from machine bearings exhibit nonstationary behavior due to variable working conditions and multiple fault severities. In the current work, a two-layered bearing fault diagnosis scheme is proposed for the identification of fault pattern and crack size for a given fault type. A hybrid feature pool is used in combination with sparse stacked autoencoder (SAE-based deep neural networks (DNNs to perform effective diagnosis of bearing faults of multiple severities. The hybrid feature pool can extract more discriminating information from the raw vibration signals, to overcome the nonstationary behavior of the signals caused by multiple crack sizes. More discriminating information helps the subsequent classifier to effectively classify data into the respective classes. The results indicate that the proposed scheme provides satisfactory performance in diagnosing bearing defects of multiple severities. Moreover, the results also demonstrate that the proposed model outperforms other state-of-the-art algorithms, i.e., support vector machines (SVMs and backpropagation neural networks (BPNNs.

  16. A Hybrid Feature Model and Deep-Learning-Based Bearing Fault Diagnosis.

    Science.gov (United States)

    Sohaib, Muhammad; Kim, Cheol-Hong; Kim, Jong-Myon

    2017-12-11

    Bearing fault diagnosis is imperative for the maintenance, reliability, and durability of rotary machines. It can reduce economical losses by eliminating unexpected downtime in industry due to failure of rotary machines. Though widely investigated in the past couple of decades, continued advancement is still desirable to improve upon existing fault diagnosis techniques. Vibration acceleration signals collected from machine bearings exhibit nonstationary behavior due to variable working conditions and multiple fault severities. In the current work, a two-layered bearing fault diagnosis scheme is proposed for the identification of fault pattern and crack size for a given fault type. A hybrid feature pool is used in combination with sparse stacked autoencoder (SAE)-based deep neural networks (DNNs) to perform effective diagnosis of bearing faults of multiple severities. The hybrid feature pool can extract more discriminating information from the raw vibration signals, to overcome the nonstationary behavior of the signals caused by multiple crack sizes. More discriminating information helps the subsequent classifier to effectively classify data into the respective classes. The results indicate that the proposed scheme provides satisfactory performance in diagnosing bearing defects of multiple severities. Moreover, the results also demonstrate that the proposed model outperforms other state-of-the-art algorithms, i.e., support vector machines (SVMs) and backpropagation neural networks (BPNNs).

  17. EEG-based recognition of video-induced emotions: selecting subject-independent feature set.

    Science.gov (United States)

    Kortelainen, Jukka; Seppänen, Tapio

    2013-01-01

    Emotions are fundamental for everyday life affecting our communication, learning, perception, and decision making. Including emotions into the human-computer interaction (HCI) could be seen as a significant step forward offering a great potential for developing advanced future technologies. While the electrical activity of the brain is affected by emotions, offers electroencephalogram (EEG) an interesting channel to improve the HCI. In this paper, the selection of subject-independent feature set for EEG-based emotion recognition is studied. We investigate the effect of different feature sets in classifying person's arousal and valence while watching videos with emotional content. The classification performance is optimized by applying a sequential forward floating search algorithm for feature selection. The best classification rate (65.1% for arousal and 63.0% for valence) is obtained with a feature set containing power spectral features from the frequency band of 1-32 Hz. The proposed approach substantially improves the classification rate reported in the literature. In future, further analysis of the video-induced EEG changes including the topographical differences in the spectral features is needed.

  18. A hybrid fault diagnosis approach based on mixed-domain state features for rotating machinery.

    Science.gov (United States)

    Xue, Xiaoming; Zhou, Jianzhong

    2017-01-01

    To make further improvement in the diagnosis accuracy and efficiency, a mixed-domain state features data based hybrid fault diagnosis approach, which systematically blends both the statistical analysis approach and the artificial intelligence technology, is proposed in this work for rolling element bearings. For simplifying the fault diagnosis problems, the execution of the proposed method is divided into three steps, i.e., fault preliminary detection, fault type recognition and fault degree identification. In the first step, a preliminary judgment about the health status of the equipment can be evaluated by the statistical analysis method based on the permutation entropy theory. If fault exists, the following two processes based on the artificial intelligence approach are performed to further recognize the fault type and then identify the fault degree. For the two subsequent steps, mixed-domain state features containing time-domain, frequency-domain and multi-scale features are extracted to represent the fault peculiarity under different working conditions. As a powerful time-frequency analysis method, the fast EEMD method was employed to obtain multi-scale features. Furthermore, due to the information redundancy and the submergence of original feature space, a novel manifold learning method (modified LGPCA) is introduced to realize the low-dimensional representations for high-dimensional feature space. Finally, two cases with 12 working conditions respectively have been employed to evaluate the performance of the proposed method, where vibration signals were measured from an experimental bench of rolling element bearing. The analysis results showed the effectiveness and the superiority of the proposed method of which the diagnosis thought is more suitable for practical application. Copyright © 2016 ISA. Published by Elsevier Ltd. All rights reserved.

  19. Use of a New Set of Linguistic Features to Improve Automatic Assessment of Text Readability

    Science.gov (United States)

    Yoshimi, Takehiko; Kotani, Katsunori; Isahara, Hitoshi

    2012-01-01

    The present paper proposes and evaluates a readability assessment method designed for Japanese learners of EFL (English as a foreign language). The proposed readability assessment method is constructed by a regression algorithm using a new set of linguistic features that were employed separately in previous studies. The results showed that the…

  20. Management and performance features of cancer centers in Europe: A fuzzy-set analysis

    NARCIS (Netherlands)

    Wind, Anke; Lobo, Mariana Fernandes; van Dijk, Joris; Lepage-Nefkens, Isabelle; Laranja-Pontes, Jose; da Conceicao Goncalves, Vitor; van Harten, Willem H.; Rocha-Goncalves, Francisco Nuno

    2016-01-01

    The specific aim of this study is to identify the performance features of cancer centers in the European Union by using a fuzzy-set qualitative comparative analysis (fsQCA). The fsQCA method represents cases (cancer centers) as a combination of explanatory and outcome conditions. This study uses

  1. Generalizations of the subject-independent feature set for music-induced emotion recognition.

    Science.gov (United States)

    Lin, Yuan-Pin; Chen, Jyh-Horng; Duann, Jeng-Ren; Lin, Chin-Teng; Jung, Tzyy-Ping

    2011-01-01

    Electroencephalogram (EEG)-based emotion recognition has been an intensely growing field. Yet, how to achieve acceptable accuracy on a practical system with as fewer electrodes as possible is less concerned. This study evaluates a set of subject-independent features, based on differential power asymmetry of symmetric electrode pairs [1], with emphasis on its applicability to subject variability in music-induced emotion classification problem. Results of this study have evidently validated the feasibility of using subject-independent EEG features to classify four emotional states with acceptable accuracy in second-scale temporal resolution. These features could be generalized across subjects to detect emotion induced by music excerpts not limited to the music database that was used to derive the emotion-specific features.

  2. New Hybrid Features Selection Method: A Case Study on Websites Phishing

    Directory of Open Access Journals (Sweden)

    Khairan D. Rajab

    2017-01-01

    Full Text Available Phishing is one of the serious web threats that involves mimicking authenticated websites to deceive users in order to obtain their financial information. Phishing has caused financial damage to the different online stakeholders. It is massive in the magnitude of hundreds of millions; hence it is essential to minimize this risk. Classifying websites into “phishy” and legitimate types is a primary task in data mining that security experts and decision makers are hoping to improve particularly with respect to the detection rate and reliability of the results. One way to ensure the reliability of the results and to enhance performance is to identify a set of related features early on so the data dimensionality reduces and irrelevant features are discarded. To increase reliability of preprocessing, this article proposes a new feature selection method that combines the scores of multiple known methods to minimize discrepancies in feature selection results. The proposed method has been applied to the problem of website phishing classification to show its pros and cons in identifying relevant features. Results against a security dataset reveal that the proposed preprocessing method was able to derive new features datasets which when mined generate high competitive classifiers with reference to detection rate when compared to results obtained from other features selection methods.

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

    Directory of Open Access Journals (Sweden)

    Jaison Bennet

    2014-01-01

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

  4. A Hybrid Swarm Intelligence Algorithm for Intrusion Detection Using Significant Features

    Directory of Open Access Journals (Sweden)

    P. Amudha

    2015-01-01

    Full Text Available Intrusion detection has become a main part of network security due to the huge number of attacks which affects the computers. This is due to the extensive growth of internet connectivity and accessibility to information systems worldwide. To deal with this problem, in this paper a hybrid algorithm is proposed to integrate Modified Artificial Bee Colony (MABC with Enhanced Particle Swarm Optimization (EPSO to predict the intrusion detection problem. The algorithms are combined together to find out better optimization results and the classification accuracies are obtained by 10-fold cross-validation method. The purpose of this paper is to select the most relevant features that can represent the pattern of the network traffic and test its effect on the success of the proposed hybrid classification algorithm. To investigate the performance of the proposed method, intrusion detection KDDCup’99 benchmark dataset from the UCI Machine Learning repository is used. The performance of the proposed method is compared with the other machine learning algorithms and found to be significantly different.

  5. Effects of silicon on seed setting rate of rice intersubspecific hybrids.

    Science.gov (United States)

    Li, W-C; Zhang, L; Wang, J; Wang, D; Wang, T-X; Duan, C-X

    2015-09-01

    The present study found semi-sterility in rice intersubspecific hybrids of 'Taichung 65' x 'Guangluai 4' and 'Ludao' x 'Qiuguang'. Embryo sac fertility was evaluated using the overall staining transparent method. The results showed that the embryo sac contained a normal egg cell, normal synergid cells, polar nuclei cells, and antipodal cells, indicating that semi-sterility was caused mainly by pollen semi-sterility. In the pot experiment, the effects of silicon on the seed-setting rate of the two intersubspecific hybrids were examined. The results showed that the rate of anther dehiscence, number of pollen per stigma of Fl plants, potential of pollen grain germination, and fertility of the spikelet were significantly improved by the utilization of silicon fertilizer.

  6. Feature Reduction Based on Genetic Algorithm and Hybrid Model for Opinion Mining

    Directory of Open Access Journals (Sweden)

    P. Kalaivani

    2015-01-01

    Full Text Available With the rapid growth of websites and web form the number of product reviews is available on the sites. An opinion mining system is needed to help the people to evaluate emotions, opinions, attitude, and behavior of others, which is used to make decisions based on the user preference. In this paper, we proposed an optimized feature reduction that incorporates an ensemble method of machine learning approaches that uses information gain and genetic algorithm as feature reduction techniques. We conducted comparative study experiments on multidomain review dataset and movie review dataset in opinion mining. The effectiveness of single classifiers Naïve Bayes, logistic regression, support vector machine, and ensemble technique for opinion mining are compared on five datasets. The proposed hybrid method is evaluated and experimental results using information gain and genetic algorithm with ensemble technique perform better in terms of various measures for multidomain review and movie reviews. Classification algorithms are evaluated using McNemar’s test to compare the level of significance of the classifiers.

  7. Credit scoring using ensemble of various classifiers on reduced feature set

    Directory of Open Access Journals (Sweden)

    Dahiya Shashi

    2015-01-01

    Full Text Available Credit scoring methods are widely used for evaluating loan applications in financial and banking institutions. Credit score identifies if applicant customers belong to good risk applicant group or a bad risk applicant group. These decisions are based on the demographic data of the customers, overall business by the customer with bank, and loan payment history of the loan applicants. The advantages of using credit scoring models include reducing the cost of credit analysis, enabling faster credit decisions and diminishing possible risk. Many statistical and machine learning techniques such as Logistic Regression, Support Vector Machines, Neural Networks and Decision tree algorithms have been used independently and as hybrid credit scoring models. This paper proposes an ensemble based technique combining seven individual models to increase the classification accuracy. Feature selection has also been used for selecting important attributes for classification. Cross classification was conducted using three data partitions. German credit dataset having 1000 instances and 21 attributes is used in the present study. The results of the experiments revealed that the ensemble model yielded a very good accuracy when compared to individual models. In all three different partitions, the ensemble model was able to classify more than 80% of the loan customers as good creditors correctly. Also, for 70:30 partition there was a good impact of feature selection on the accuracy of classifiers. The results were improved for almost all individual models including the ensemble model.

  8. Fusion-fission hybrid design with analysis of direct enrichment and non-proliferation features (the SOLASE-H study)

    International Nuclear Information System (INIS)

    Conn, R.W.; Abdel-Khalik, S.I.; Moses, G.A.; Kulcinski, G.L.; Larsen, E.; Maynard, C.W.; Magheb, M.M.H.; Sviatolslavsky, I.N.; Vogelsang, W.F.; Wolfer, W.G.

    1981-01-01

    The role of a fusion-fission hybrid in the context of a nuclear economy with and without reprocessing is examined. An inertial confinement fusion driver is assumed and a consistent set of reactor parameters are developed. The form of the driver is not critical, however, to the general concepts. The use of the hybrid as a fuel factory within a secured fuel production and reprocessing center is considered. Either the hybrid or a low power fission reactor can be used to mildly irradiate fuel prior to shipment to offsite reactors thereby rendering the fuel resistant to diversion. A simplified economic analysis indicates a hybrid providing fuel to 10 fission reactors of equal thermal power is insensitive to the recirculating power fraction provided reprocessing is permitted. If reprocessing is not allowed, the hybrid can be used to directly enrich light water reactor fuel bundles fabricated initially from fertile fuel (either ThO 2 or 238 UO 2 ). A detailed neutronic analysis indicates such direct enrichments is feasible but the support ratio for 233 U or 239 Pu production is only 2, making such an approach highly sensitive to the hybrid cost. The hybrid would have to produce considerable net power for economic feasibility in this case. Inertial confinement fusion performance requirements for hybrid application are also examined and an integrated design, SOLASE-H, is described based upon the direct enrichment concept. (orig.)

  9. Characterization of mammographic masses based on level set segmentation with new image features and patient information

    International Nuclear Information System (INIS)

    Shi Jiazheng; Sahiner, Berkman; Chan Heangping; Ge Jun; Hadjiiski, Lubomir; Helvie, Mark A.; Nees, Alexis; Wu Yita; Wei Jun; Zhou Chuan; Zhang Yiheng; Cui Jing

    2008-01-01

    Computer-aided diagnosis (CAD) for characterization of mammographic masses as malignant or benign has the potential to assist radiologists in reducing the biopsy rate without increasing false negatives. The purpose of this study was to develop an automated method for mammographic mass segmentation and explore new image based features in combination with patient information in order to improve the performance of mass characterization. The authors' previous CAD system, which used the active contour segmentation, and morphological, textural, and spiculation features, has achieved promising results in mass characterization. The new CAD system is based on the level set method and includes two new types of image features related to the presence of microcalcifications with the mass and abruptness of the mass margin, and patient age. A linear discriminant analysis (LDA) classifier with stepwise feature selection was used to merge the extracted features into a classification score. The classification accuracy was evaluated using the area under the receiver operating characteristic curve. The authors' primary data set consisted of 427 biopsy-proven masses (200 malignant and 227 benign) in 909 regions of interest (ROIs) (451 malignant and 458 benign) from multiple mammographic views. Leave-one-case-out resampling was used for training and testing. The new CAD system based on the level set segmentation and the new mammographic feature space achieved a view-based A z value of 0.83±0.01. The improvement compared to the previous CAD system was statistically significant (p=0.02). When patient age was included in the new CAD system, view-based and case-based A z values were 0.85±0.01 and 0.87±0.02, respectively. The study also demonstrated the consistency of the newly developed CAD system by evaluating the statistics of the weights of the LDA classifiers in leave-one-case-out classification. Finally, an independent test on the publicly available digital database for screening

  10. Mental sets in conduct problem youth with psychopathic features: entity versus incremental theories of intelligence.

    Science.gov (United States)

    Salekin, Randall T; Lester, Whitney S; Sellers, Mary-Kate

    2012-08-01

    The purpose of the current study was to examine the effect of a motivational intervention on conduct problem youth with psychopathic features. Specifically, the current study examined conduct problem youths' mental set (or theory) regarding intelligence (entity vs. incremental) upon task performance. We assessed 36 juvenile offenders with psychopathic features and tested whether providing them with two different messages regarding intelligence would affect their functioning on a task related to academic performance. The study employed a MANOVA design with two motivational conditions and three outcomes including fluency, flexibility, and originality. Results showed that youth with psychopathic features who were given a message that intelligence grows over time, were more fluent and flexible than youth who were informed that intelligence is static. There were no significant differences between the groups in terms of originality. The implications of these findings are discussed including the possible benefits of interventions for adolescent offenders with conduct problems and psychopathic features. (PsycINFO Database Record (c) 2012 APA, all rights reserved).

  11. Inherent Safety Feature of Hybrid Low Power Research Reactor during Reactivity Induced Accident

    Energy Technology Data Exchange (ETDEWEB)

    Kim, DongHyun; Yum, Soo Been; Hong, Sung Teak; Lim, In-Cheol [Korea Atomic Energy Research Institute, Daejeon (Korea, Republic of)

    2016-10-15

    Hybrid low power research reactor(H-LPRR) is the new design concept of low power research reactor for critical facility as well as education and training. In the case of typical low power research reactor, the purposes of utilization are the experiments for education of nuclear engineering students, Neutron Activation Analysis(NAA) and radio-isotope production for research purpose. H-LPRR is a light-water cooled and moderated research reactor that uses rod-type LEU UO{sub 2} fuels same as those for commercial power plants. The maximum core thermal power is 70kW and, the core is placed in the bottom of open pool. There are 1 control rod and 2 shutdown rods in the core. It is designed to cool the core by natural convection, retain negative feedback coefficient for entire fuel periods and operate for 20 years without refueling. Inherent safety in H-LPRR is achieved by passive design features such as negative temperature feedback coefficient and core cooling by natural convection during normal and emergency conditions. The purpose of this study is to find out that the inherent safety characteristics of H-LPRR is able to control the power and protect the reactor from the RIA(Reactivity induced accident). RIA analysis was performed to investigate the inherent safety feature of H-LPRR. As a result, it was found that the reactor controls its power without fuel damage in the event and that the reactor remains safe states inherently. Therefore, it is believed that high degree of safety inheres in H-LPRR.

  12. A Power Supply System with ZVS and Current-Doubler Features for Hybrid Renewable Energy Conversion

    Directory of Open Access Journals (Sweden)

    Jye-Chau Su

    2013-09-01

    Full Text Available In this paper, a power supply system for hybrid renewable energy conversion is proposed, which can process PV (photovoltaic power and wind-turbine energy simultaneously for step-down voltage and high current applications. It is a dual-input converter and mainly contains a PV energy source, a wind turbine energy source, a zero-voltage-switching (ZVS forward converter, and a current-doubler rectifier. The proposed power supply system has the following advantages: (1 PV-arrays and wind-energy sources can alternatively deliver power to the load during climate or season alteration; (2 maximum power point tracking (MPPT can be accomplished for both different kinds of renewable-energy sources; (3 ZVS and synchronous rectification techniques for the active switches of the forward converter are embedded so as to reduce switching and conducting losses; and (4 electricity isolation is naturally obtained. To achieve an optimally dynamic response and to increase control flexibility, a digital signal processor (DSP is investigated and presented to implement MPPT algorithm and power regulating scheme. Finally, a 240 W prototype power supply system with ZVS and current-doubler features to deal with PV power and wind energy is built and implemented. Experimental results are presented to verify the performance and the feasibility of the proposed power supply system.

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

    Directory of Open Access Journals (Sweden)

    Soumya Banerjee

    2011-03-01

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

  14. Development of a set of SSR markers for genetic polymorphism detection and interspecific hybrid jute breeding

    Directory of Open Access Journals (Sweden)

    Dipnarayan Saha

    2017-10-01

    Full Text Available Corchorus capsularis (white jute and C. olitorius (dark jute are the two principal cultivated species of jute that produce natural bast fiber of commercial importance. We have identified 4509 simple sequence repeat (SSR loci from 34,163 unigene sequences of C. capsularis to develop a non-redundant set of 2079 flanking primer pairs. Among the SSRs, trinucleotide repeats were most frequent (60% followed by dinucleotide repeats (37.6%. Annotation of the SSR-containing unigenes revealed their putative functions in various biological and molecular processes, including responses to biotic and abiotic signals. Eighteen expressed gene-derived SSR (eSSR markers were successfully mapped to the existing single-nucleotide polymorphism (SNP linkage map of jute, providing additional anchor points. Amplification of 72% of the 74 randomly selected primer pairs was successful in a panel of 24 jute accessions, comprising five and twelve accessions of C. capsularis and C. olitorius, respectively, and seven wild jute species. Forty-three primer pairs produced an average of 2.7 alleles and 58.1% polymorphism in a panel of 24 jute accessions. The mean PIC value was 0.34 but some markers showed PIC values higher than 0.5, suggesting that these markers can efficiently measure genetic diversity and serve for mapping of quantitative trait loci (QTLs in jute. A primer polymorphism survey with parents of a wide-hybridized population between a cultivated jute and its wild relative revealed their efficacy for interspecific hybrid identification. For ready accessibility of jute eSSR primers, we compiled all information in a user-friendly web database, JuteMarkerdb (http://jutemarkerdb.icar.gov.in/ for the first time in jute. This eSSR resource in jute is expected to be of use in characterization of germplasm, interspecific hybrid and variety identification, and marker-assisted breeding of superior-quality jute.

  15. Generation of New Genotypic and Phenotypic Features in Artificial and Natural Yeast Hybrids

    Directory of Open Access Journals (Sweden)

    Walter P. Pfliegler

    2014-01-01

    Full Text Available Evolution and genome stabilization have mostly been studied on the Saccharomyces hybrids isolated from natural and alcoholic fermentation environments. Genetic and phenotypic properties have usually been compared to the laboratory and reference strains, as the true ancestors of the natural hybrid yeasts are unknown. In this way the exact impact of different parental fractions on the genome organization or metabolic activity of the hybrid yeasts is difficult to resolve completely. In the present work the evolution of geno- and phenotypic properties is studied in the interspecies hybrids created by the cross-breeding of S. cerevisiae with S. uvarum or S. kudriavzevii auxotrophic mutants. We hypothesized that the extent of genomic alterations in S. cerevisiae × S. uvarum and S. cerevisiae × S. kudriavzevii should affect the physiology of their F1 offspring in different ways. Our results, obtained by amplified fragment length polymorphism (AFLP genotyping and karyotyping analyses, showed that both subgenomes of the S. cerevisiae x S. uvarum and of S. cerevisiae × S. kudriavzevii hybrids experienced various modifications. However, the S. cerevisiae × S. kudriavzevii F1 hybrids underwent more severe genomic alterations than the S. cerevisiae × S. uvarum ones. Generation of the new genotypes also influenced the physiological performances of the hybrids and the occurrence of novel phenotypes. Significant differences in carbohydrate utilization and distinct growth dynamics at increasing concentrations of sodium chloride, urea and miconazole were observed within and between the S. cerevisiae × S. uvarum and S. cerevisiae × S. kudriavzevii hybrids. Parental strains also demonstrated different contributions to the final metabolic outcomes of the hybrid yeasts. A comparison of the genotypic properties of the artificial hybrids with several hybrid isolates from the wine-related environments and wastewater demonstrated a greater genetic variability of

  16. kmer-SVM: a web server for identifying predictive regulatory sequence features in genomic data sets

    Science.gov (United States)

    Fletez-Brant, Christopher; Lee, Dongwon; McCallion, Andrew S.; Beer, Michael A.

    2013-01-01

    Massively parallel sequencing technologies have made the generation of genomic data sets a routine component of many biological investigations. For example, Chromatin immunoprecipitation followed by sequence assays detect genomic regions bound (directly or indirectly) by specific factors, and DNase-seq identifies regions of open chromatin. A major bottleneck in the interpretation of these data is the identification of the underlying DNA sequence code that defines, and ultimately facilitates prediction of, these transcription factor (TF) bound or open chromatin regions. We have recently developed a novel computational methodology, which uses a support vector machine (SVM) with kmer sequence features (kmer-SVM) to identify predictive combinations of short transcription factor-binding sites, which determine the tissue specificity of these genomic assays (Lee, Karchin and Beer, Discriminative prediction of mammalian enhancers from DNA sequence. Genome Res. 2011; 21:2167–80). This regulatory information can (i) give confidence in genomic experiments by recovering previously known binding sites, and (ii) reveal novel sequence features for subsequent experimental testing of cooperative mechanisms. Here, we describe the development and implementation of a web server to allow the broader research community to independently apply our kmer-SVM to analyze and interpret their genomic datasets. We analyze five recently published data sets and demonstrate how this tool identifies accessory factors and repressive sequence elements. kmer-SVM is available at http://kmersvm.beerlab.org. PMID:23771147

  17. Study of Machine-Learning Classifier and Feature Set Selection for Intent Classification of Korean Tweets about Food Safety

    Directory of Open Access Journals (Sweden)

    Yeom, Ha-Neul

    2014-09-01

    Full Text Available In recent years, several studies have proposed making use of the Twitter micro-blogging service to track various trends in online media and discussion. In this study, we specifically examine the use of Twitter to track discussions of food safety in the Korean language. Given the irregularity of keyword use in most tweets, we focus on optimistic machine-learning and feature set selection to classify collected tweets. We build the classifier model using Naive Bayes & Naive Bayes Multinomial, Support Vector Machine, and Decision Tree Algorithms, all of which show good performance. To select an optimum feature set, we construct a basic feature set as a standard for performance comparison, so that further test feature sets can be evaluated. Experiments show that precision and F-measure performance are best when using a Naive Bayes Multinomial classifier model with a test feature set defined by extracting Substantive, Predicate, Modifier, and Interjection parts of speech.

  18. A comparative study of different feature sets for recognition of handwritten Arabic numerals using a Multi Layer Perceptron

    OpenAIRE

    Das, Nibaran; Mollah, Ayatullah Faruk; Sarkar, Ram; Basu, Subhadip

    2010-01-01

    The work presents a comparative assessment of seven different feature sets for recognition of handwritten Arabic numerals using a Multi Layer Perceptron (MLP) based classifier. The seven feature sets employed here consist of shadow features, octant centroids, longest runs, angular distances, effective spans, dynamic centers of gravity, and some of their combinations. On experimentation with a database of 3000 samples, the maximum recognition rate of 95.80% is observed with both of two separat...

  19. Application of Microarray-Based Comparative Genomic Hybridization in Prenatal and Postnatal Settings: Three Case Reports

    Directory of Open Access Journals (Sweden)

    Jing Liu

    2011-01-01

    Full Text Available Microarray-based comparative genomic hybridization (array CGH is a newly emerged molecular cytogenetic technique for rapid evaluation of the entire genome with sub-megabase resolution. It allows for the comprehensive investigation of thousands and millions of genomic loci at once and therefore enables the efficient detection of DNA copy number variations (a.k.a, cryptic genomic imbalances. The development and the clinical application of array CGH have revolutionized the diagnostic process in patients and has provided a clue to many unidentified or unexplained diseases which are suspected to have a genetic cause. In this paper, we present three clinical cases in both prenatal and postnatal settings. Among all, array CGH played a major discovery role to reveal the cryptic and/or complex nature of chromosome arrangements. By identifying the genetic causes responsible for the clinical observation in patients, array CGH has provided accurate diagnosis and appropriate clinical management in a timely and efficient manner.

  20. Hybrid Feature Selection Approach Based on GRASP for Cancer Microarray Data

    Directory of Open Access Journals (Sweden)

    Arpita Nagpal

    2017-01-01

    Full Text Available Microarray data usually contain a large number of genes, but a small number of samples. Feature subset selection for microarray data aims at reducing the number of genes so that useful information can be extracted from the samples. Reducing the dimension of data sets further helps in improving the computational efficiency of the learning model. In this paper, we propose a modified algorithm based on the tabu search as local search procedures to a Greedy Randomized Adaptive Search Procedure (GRASP for high dimensional microarray data sets. The proposed Tabu based Greedy Randomized Adaptive Search Procedure algorithm is named as TGRASP. In TGRASP, a new parameter has been introduced named as Tabu Tenure and the existing parameters, NumIter and size have been modified. We observed that different parameter settings affect the quality of the optimum. The second proposed algorithm known as FFGRASP (Firefly Greedy Randomized Adaptive Search Procedure uses a firefly optimization algorithm in the local search optimzation phase of the greedy randomized adaptive search procedure (GRASP. Firefly algorithm is one of the powerful algorithms for optimization of multimodal applications. Experimental results show that the proposed TGRASP and FFGRASP algorithms are much better than existing algorithm with respect to three performance parameters viz. accuracy, run time, number of a selected subset of features. We have also compared both the approaches with a unified metric (Extended Adjusted Ratio of Ratios which has shown that TGRASP approach outperforms existing approach for six out of nine cancer microarray datasets and FFGRASP performs better on seven out of nine datasets.

  1. Indirect Effects of Field Management on Pollination Service and Seed Set in Hybrid Onion Seed Production.

    Science.gov (United States)

    Gillespie, Sandra; Long, Rachael; Williams, Neal

    2015-12-01

    Pollination in crops, as in native ecosystems, is a stepwise process that can be disrupted at any stage. Healthy pollinator populations are critical for adequate visitation, but pollination still might fail if crop management interferes with the attraction and retention of pollinators. Farmers must balance the direct benefits of applying insecticide and managing irrigation rates against their potential to indirectly interfere with the pollination process. We investigated these issues in hybrid onion seed production, where previous research has shown that high insecticide use reduces pollinator attraction. We conducted field surveys of soil moisture, nectar production, pollinator visitation, pollen-stigma interactions, and seed set at multiple commercial fields across 2 yr. We then examined how management actions, such as irrigation rate (approximated by soil moisture), or insecticide use could affect the pollination process. Onions produced maximum nectar at intermediate soil moisture, and high nectar production attracted more pollinators. Insecticide use weakly affected pollinator visitation, but when applied close to bloom reduced pollen germination and pollen tube growth. Ultimately, neither soil moisture nor insecticide use directly affected seed set, but the high correlation between pollinator visitation and seed set suggests that crop management will ultimately affect yields via indirect effects on the pollination process. © The Authors 2015. Published by Oxford University Press on behalf of Entomological Society of America. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

  2. An optimal set of features for predicting type IV secretion system effector proteins for a subset of species based on a multi-level feature selection approach.

    Directory of Open Access Journals (Sweden)

    Zhila Esna Ashari

    Full Text Available Type IV secretion systems (T4SS are multi-protein complexes in a number of bacterial pathogens that can translocate proteins and DNA to the host. Most T4SSs function in conjugation and translocate DNA; however, approximately 13% function to secrete proteins, delivering effector proteins into the cytosol of eukaryotic host cells. Upon entry, these effectors manipulate the host cell's machinery for their own benefit, which can result in serious illness or death of the host. For this reason recognition of T4SS effectors has become an important subject. Much previous work has focused on verifying effectors experimentally, a costly endeavor in terms of money, time, and effort. Having good predictions for effectors will help to focus experimental validations and decrease testing costs. In recent years, several scoring and machine learning-based methods have been suggested for the purpose of predicting T4SS effector proteins. These methods have used different sets of features for prediction, and their predictions have been inconsistent. In this paper, an optimal set of features is presented for predicting T4SS effector proteins using a statistical approach. A thorough literature search was performed to find features that have been proposed. Feature values were calculated for datasets of known effectors and non-effectors for T4SS-containing pathogens for four genera with a sufficient number of known effectors, Legionella pneumophila, Coxiella burnetii, Brucella spp, and Bartonella spp. The features were ranked, and less important features were filtered out. Correlations between remaining features were removed, and dimensional reduction was accomplished using principal component analysis and factor analysis. Finally, the optimal features for each pathogen were chosen by building logistic regression models and evaluating each model. The results based on evaluation of our logistic regression models confirm the effectiveness of our four optimal sets of

  3. Combination of Biorthogonal Wavelet Hybrid Kernel OCSVM with Feature Weighted Approach Based on EVA and GRA in Financial Distress Prediction

    Directory of Open Access Journals (Sweden)

    Chao Huang

    2014-01-01

    Full Text Available Financial distress prediction plays an important role in the survival of companies. In this paper, a novel biorthogonal wavelet hybrid kernel function is constructed by combining linear kernel function with biorthogonal wavelet kernel function. Besides, a new feature weighted approach is presented based on economic value added (EVA and grey relational analysis (GRA. Considering the imbalance between financially distressed companies and normal ones, the feature weighted one-class support vector machine based on biorthogonal wavelet hybrid kernel (BWH-FWOCSVM is further put forward for financial distress prediction. The empirical study with real data from the listed companies on Growth Enterprise Market (GEM in China shows that the proposed approach has good performance.

  4. 3D variational brain tumor segmentation using Dirichlet priors on a clustered feature set.

    Science.gov (United States)

    Popuri, Karteek; Cobzas, Dana; Murtha, Albert; Jägersand, Martin

    2012-07-01

    Brain tumor segmentation is a required step before any radiation treatment or surgery. When performed manually, segmentation is time consuming and prone to human errors. Therefore, there have been significant efforts to automate the process. But, automatic tumor segmentation from MRI data is a particularly challenging task. Tumors have a large diversity in shape and appearance with intensities overlapping the normal brain tissues. In addition, an expanding tumor can also deflect and deform nearby tissue. In our work, we propose an automatic brain tumor segmentation method that addresses these last two difficult problems. We use the available MRI modalities (T1, T1c, T2) and their texture characteristics to construct a multidimensional feature set. Then, we extract clusters which provide a compact representation of the essential information in these features. The main idea in this work is to incorporate these clustered features into the 3D variational segmentation framework. In contrast to previous variational approaches, we propose a segmentation method that evolves the contour in a supervised fashion. The segmentation boundary is driven by the learned region statistics in the cluster space. We incorporate prior knowledge about the normal brain tissue appearance during the estimation of these region statistics. In particular, we use a Dirichlet prior that discourages the clusters from the normal brain region to be in the tumor region. This leads to a better disambiguation of the tumor from brain tissue. We evaluated the performance of our automatic segmentation method on 15 real MRI scans of brain tumor patients, with tumors that are inhomogeneous in appearance, small in size and in proximity to the major structures in the brain. Validation with the expert segmentation labels yielded encouraging results: Jaccard (58%), Precision (81%), Recall (67%), Hausdorff distance (24 mm). Using priors on the brain/tumor appearance, our proposed automatic 3D variational

  5. Chemical name extraction based on automatic training data generation and rich feature set.

    Science.gov (United States)

    Yan, Su; Spangler, W Scott; Chen, Ying

    2013-01-01

    The automation of extracting chemical names from text has significant value to biomedical and life science research. A major barrier in this task is the difficulty of getting a sizable and good quality data to train a reliable entity extraction model. Another difficulty is the selection of informative features of chemical names, since comprehensive domain knowledge on chemistry nomenclature is required. Leveraging random text generation techniques, we explore the idea of automatically creating training sets for the task of chemical name extraction. Assuming the availability of an incomplete list of chemical names, called a dictionary, we are able to generate well-controlled, random, yet realistic chemical-like training documents. We statistically analyze the construction of chemical names based on the incomplete dictionary, and propose a series of new features, without relying on any domain knowledge. Compared to state-of-the-art models learned from manually labeled data and domain knowledge, our solution shows better or comparable results in annotating real-world data with less human effort. Moreover, we report an interesting observation about the language for chemical names. That is, both the structural and semantic components of chemical names follow a Zipfian distribution, which resembles many natural languages.

  6. Multimodal Discrimination of Schizophrenia Using Hybrid Weighted Feature Concatenation of Brain Functional Connectivity and Anatomical Features with an Extreme Learning Machine

    Directory of Open Access Journals (Sweden)

    Muhammad Naveed Iqbal Qureshi

    2017-09-01

    Full Text Available Multimodal features of structural and functional magnetic resonance imaging (MRI of the human brain can assist in the diagnosis of schizophrenia. We performed a classification study on age, sex, and handedness-matched subjects. The dataset we used is publicly available from the Center for Biomedical Research Excellence (COBRE and it consists of two groups: patients with schizophrenia and healthy controls. We performed an independent component analysis and calculated global averaged functional connectivity-based features from the resting-state functional MRI data for all the cortical and subcortical anatomical parcellation. Cortical thickness along with standard deviation, surface area, volume, curvature, white matter volume, and intensity measures from the cortical parcellation, as well as volume and intensity from sub-cortical parcellation and overall volume of cortex features were extracted from the structural MRI data. A novel hybrid weighted feature concatenation method was used to acquire maximal 99.29% (P < 0.0001 accuracy which preserves high discriminatory power through the weight of the individual feature type. The classification was performed by an extreme learning machine, and its efficiency was compared to linear and non-linear (radial basis function support vector machines, linear discriminant analysis, and random forest bagged tree ensemble algorithms. This article reports the predictive accuracy of both unimodal and multimodal features after 10-by-10-fold nested cross-validation. A permutation test followed the classification experiment to assess the statistical significance of the classification results. It was concluded that, from a clinical perspective, this feature concatenation approach may assist the clinicians in schizophrenia diagnosis.

  7. Local analysis of hybrid systems on polyhedral sets with state-dependent switching

    Directory of Open Access Journals (Sweden)

    Leth John

    2014-06-01

    Full Text Available This paper deals with stability analysis of hybrid systems. Various stability concepts related to hybrid systems are introduced. The paper advocates a local analysis. It involves the equivalence relation generated by reset maps of a hybrid system. To establish a tangible method for stability analysis, we introduce the notion of a chart, which locally reduces the complexity of the hybrid system. In a chart, a hybrid system is particularly simple and can be analyzed with the use of methods borrowed from the theory of differential inclusions. Thus, the main contribution of this paper is to show how stability of a hybrid system can be reduced to a specialization of the well established stability theory of differential inclusions. A number of examples illustrate the concepts introduced in the paper.

  8. ClusTrack: feature extraction and similarity measures for clustering of genome-wide data sets.

    Directory of Open Access Journals (Sweden)

    Halfdan Rydbeck

    Full Text Available Clustering is a popular technique for explorative analysis of data, as it can reveal subgroupings and similarities between data in an unsupervised manner. While clustering is routinely applied to gene expression data, there is a lack of appropriate general methodology for clustering of sequence-level genomic and epigenomic data, e.g. ChIP-based data. We here introduce a general methodology for clustering data sets of coordinates relative to a genome assembly, i.e. genomic tracks. By defining appropriate feature extraction approaches and similarity measures, we allow biologically meaningful clustering to be performed for genomic tracks using standard clustering algorithms. An implementation of the methodology is provided through a tool, ClusTrack, which allows fine-tuned clustering analyses to be specified through a web-based interface. We apply our methods to the clustering of occupancy of the H3K4me1 histone modification in samples from a range of different cell types. The majority of samples form meaningful subclusters, confirming that the definitions of features and similarity capture biological, rather than technical, variation between the genomic tracks. Input data and results are available, and can be reproduced, through a Galaxy Pages document at http://hyperbrowser.uio.no/hb/u/hb-superuser/p/clustrack. The clustering functionality is available as a Galaxy tool, under the menu option "Specialized analyzis of tracks", and the submenu option "Cluster tracks based on genome level similarity", at the Genomic HyperBrowser server: http://hyperbrowser.uio.no/hb/.

  9. A Novel Evaluation Model for Hybrid Power System Based on Vague Set and Dempster-Shafer Evidence Theory

    Directory of Open Access Journals (Sweden)

    Dongxiao Niu

    2012-01-01

    Full Text Available Because clean energy and traditional energy have different advantages and disadvantages, it is of great significance to evaluate comprehensive benefits for hybrid power systems. Based on thorough analysis of important characters on hybrid power systems, an index system including security, economic benefit, environmental benefit, and social benefit is established in this paper. Due to advantages of processing abundant uncertain and fuzzy information, vague set is used to determine the decision matrix. Convert vague decision matrix to real one by vague combination ruleand determine uncertain degrees of different indexes by grey incidence analysis, then the mass functions of different comment set in different indexes are obtained. Information can be fused in accordance with Dempster-Shafer (D-S combination rule and the evaluation result is got by vague set and D-S evidence theory. A simulation of hybrid power system including thermal power, wind power, and photovoltaic power in China is provided to demonstrate the effectiveness and potential of the proposed design scheme. It can be clearly seen that the uncertainties in decision making can be dramatically decreased compared with existing methods in the literature. The actual implementation results illustrate that the proposed index system and evaluation model based on vague set and D-S evidence theory are effective and practical to evaluate comprehensive benefit of hybrid power system.

  10. A hybrid interface tracking - level set technique for multiphase flow with soluble surfactant

    Science.gov (United States)

    Shin, Seungwon; Chergui, Jalel; Juric, Damir; Kahouadji, Lyes; Matar, Omar K.; Craster, Richard V.

    2018-04-01

    A formulation for soluble surfactant transport in multiphase flows recently presented by Muradoglu and Tryggvason (JCP 274 (2014) 737-757) [17] is adapted to the context of the Level Contour Reconstruction Method, LCRM, (Shin et al. IJNMF 60 (2009) 753-778, [8]) which is a hybrid method that combines the advantages of the Front-tracking and Level Set methods. Particularly close attention is paid to the formulation and numerical implementation of the surface gradients of surfactant concentration and surface tension. Various benchmark tests are performed to demonstrate the accuracy of different elements of the algorithm. To verify surfactant mass conservation, values for surfactant diffusion along the interface are compared with the exact solution for the problem of uniform expansion of a sphere. The numerical implementation of the discontinuous boundary condition for the source term in the bulk concentration is compared with the approximate solution. Surface tension forces are tested for Marangoni drop translation. Our numerical results for drop deformation in simple shear are compared with experiments and results from previous simulations. All benchmarking tests compare well with existing data thus providing confidence that the adapted LCRM formulation for surfactant advection and diffusion is accurate and effective in three-dimensional multiphase flows with a structured mesh. We also demonstrate that this approach applies easily to massively parallel simulations.

  11. Design and Implementation of a Set-Top Box-Based Homecare System Using Hybrid Cloud.

    Science.gov (United States)

    Lin, Bor-Shing; Hsiao, Pei-Chi; Cheng, Po-Hsun; Lee, I-Jung; Jan, Gene Eu

    2015-11-01

    Telemedicine has become a prevalent topic in recent years, and several telemedicine systems have been proposed; however, such systems are an unsuitable fit for the daily requirements of users. The system proposed in this study was developed as a set-top box integrated with the Android™ (Google, Mountain View, CA) operating system to provide a convenient and user-friendly interface. The proposed system can assist with family healthcare management, telemedicine service delivery, and information exchange among hospitals. To manage the system, a novel type of hybrid cloud architecture was also developed. Updated information is stored on a public cloud, enabling medical staff members to rapidly access information when diagnosing patients. In the long term, the stored data can be reduced to improve the efficiency of the database. The proposed design offers a robust architecture for storing data in a homecare system and can thus resolve network overload and congestion resulting from accumulating data, which are inherent problems in centralized architectures, thereby improving system efficiency.

  12. H2RM: A Hybrid Rough Set Reasoning Model for Prediction and Management of Diabetes Mellitus

    Directory of Open Access Journals (Sweden)

    Rahman Ali

    2015-07-01

    Full Text Available Diabetes is a chronic disease characterized by high blood glucose level that results either from a deficiency of insulin produced by the body, or the body’s resistance to the effects of insulin. Accurate and precise reasoning and prediction models greatly help physicians to improve diagnosis, prognosis and treatment procedures of different diseases. Though numerous models have been proposed to solve issues of diagnosis and management of diabetes, they have the following drawbacks: (1 restricted one type of diabetes; (2 lack understandability and explanatory power of the techniques and decision; (3 limited either to prediction purpose or management over the structured contents; and (4 lack competence for dimensionality and vagueness of patient’s data. To overcome these issues, this paper proposes a novel hybrid rough set reasoning model (H2RM that resolves problems of inaccurate prediction and management of type-1 diabetes mellitus (T1DM and type-2 diabetes mellitus (T2DM. For verification of the proposed model, experimental data from fifty patients, acquired from a local hospital in semi-structured format, is used. First, the data is transformed into structured format and then used for mining prediction rules. Rough set theory (RST based techniques and algorithms are used to mine the prediction rules. During the online execution phase of the model, these rules are used to predict T1DM and T2DM for new patients. Furthermore, the proposed model assists physicians to manage diabetes using knowledge extracted from online diabetes guidelines. Correlation-based trend analysis techniques are used to manage diabetic observations. Experimental results demonstrate that the proposed model outperforms the existing methods with 95.9% average and balanced accuracies.

  13. H2RM: A Hybrid Rough Set Reasoning Model for Prediction and Management of Diabetes Mellitus.

    Science.gov (United States)

    Ali, Rahman; Hussain, Jamil; Siddiqi, Muhammad Hameed; Hussain, Maqbool; Lee, Sungyoung

    2015-07-03

    Diabetes is a chronic disease characterized by high blood glucose level that results either from a deficiency of insulin produced by the body, or the body's resistance to the effects of insulin. Accurate and precise reasoning and prediction models greatly help physicians to improve diagnosis, prognosis and treatment procedures of different diseases. Though numerous models have been proposed to solve issues of diagnosis and management of diabetes, they have the following drawbacks: (1) restricted one type of diabetes; (2) lack understandability and explanatory power of the techniques and decision; (3) limited either to prediction purpose or management over the structured contents; and (4) lack competence for dimensionality and vagueness of patient's data. To overcome these issues, this paper proposes a novel hybrid rough set reasoning model (H2RM) that resolves problems of inaccurate prediction and management of type-1 diabetes mellitus (T1DM) and type-2 diabetes mellitus (T2DM). For verification of the proposed model, experimental data from fifty patients, acquired from a local hospital in semi-structured format, is used. First, the data is transformed into structured format and then used for mining prediction rules. Rough set theory (RST) based techniques and algorithms are used to mine the prediction rules. During the online execution phase of the model, these rules are used to predict T1DM and T2DM for new patients. Furthermore, the proposed model assists physicians to manage diabetes using knowledge extracted from online diabetes guidelines. Correlation-based trend analysis techniques are used to manage diabetic observations. Experimental results demonstrate that the proposed model outperforms the existing methods with 95.9% average and balanced accuracies.

  14. Definition and verification of a set of reusable reference architectures for hybrid vehicle development

    OpenAIRE

    Harrington, Cian

    2012-01-01

    Current concerns regarding climate change and energy security have resulted in an increasing demand for low carbon vehicles, including: more efficient internal combustion engine vehicles, alternative fuel vehicles, electric vehicles and hybrid vehicles. Unlike traditional internal combustion engine vehicles and electric vehicles, hybrid vehicles contain a m...

  15. Oral cancer prognosis based on clinicopathologic and genomic markers using a hybrid of feature selection and machine learning methods

    Science.gov (United States)

    2013-01-01

    Background Machine learning techniques are becoming useful as an alternative approach to conventional medical diagnosis or prognosis as they are good for handling noisy and incomplete data, and significant results can be attained despite a small sample size. Traditionally, clinicians make prognostic decisions based on clinicopathologic markers. However, it is not easy for the most skilful clinician to come out with an accurate prognosis by using these markers alone. Thus, there is a need to use genomic markers to improve the accuracy of prognosis. The main aim of this research is to apply a hybrid of feature selection and machine learning methods in oral cancer prognosis based on the parameters of the correlation of clinicopathologic and genomic markers. Results In the first stage of this research, five feature selection methods have been proposed and experimented on the oral cancer prognosis dataset. In the second stage, the model with the features selected from each feature selection methods are tested on the proposed classifiers. Four types of classifiers are chosen; these are namely, ANFIS, artificial neural network, support vector machine and logistic regression. A k-fold cross-validation is implemented on all types of classifiers due to the small sample size. The hybrid model of ReliefF-GA-ANFIS with 3-input features of drink, invasion and p63 achieved the best accuracy (accuracy = 93.81%; AUC = 0.90) for the oral cancer prognosis. Conclusions The results revealed that the prognosis is superior with the presence of both clinicopathologic and genomic markers. The selected features can be investigated further to validate the potential of becoming as significant prognostic signature in the oral cancer studies. PMID:23725313

  16. Evaluating the influence of goal setting on intravenous catheterization skill acquisition and transfer in a hybrid simulation training context.

    Science.gov (United States)

    Brydges, Ryan; Mallette, Claire; Pollex, Heather; Carnahan, Heather; Dubrowski, Adam

    2012-08-01

    Educators often simplify complex tasks by setting learning objectives that focus trainees on isolated skills rather than the holistic task. We designed 2 sets of learning objectives for intravenous catheterization using goal setting theory. We hypothesized that setting holistic goals related to technical, cognitive, and communication skills would result in superior holistic performance, whereas setting isolated goals related to technical skills would result in superior technical performance. We randomly assigned practicing health care professionals to set holistic (n = 14) or isolated (n = 15) goals. All watched an instructional video and studied a list of 9 goals specific to their group. Participants practiced independently in a hybrid simulation (standardized patient combined with an arm simulator). The first and the last practice trials were videotaped for analysis. One-week later, participants completed a transfer test in another hybrid simulation scenario. Blinded experts evaluated performance on all 3 trials using the Direct Observation of Procedural Skills tool. The holistic group scored higher than the isolated group on the holistic Direct Observation of Procedural Skills score for all 3 trials [mean (SD), 45.0 (9.16) vs. 38.4 (9.17); P = 0.01]. The isolated group did not perform better than the holistic group on the technical skills score [10.3 (2.73) vs. 11.6 (3.01); P = 0.11]. Our results suggest that asking learners to set holistic goals did not interfere with their attaining competent holistic and technical skills during hybrid simulation training. This exploratory trial provides preliminary evidence for how to consider integrating hybrid simulation into medical curricula and for the design of learning goals in simulation-based education.

  17. A Hybrid FPGA/Coarse Parallel Processing Architecture for Multi-modal Visual Feature Descriptors

    DEFF Research Database (Denmark)

    Jensen, Lars Baunegaard With; Kjær-Nielsen, Anders; Alonso, Javier Díaz

    2008-01-01

    This paper describes the hybrid architecture developed for speeding up the processing of so-called multi-modal visual primitives which are sparse image descriptors extracted along contours. In the system, the first stages of visual processing are implemented on FPGAs due to their highly parallel...

  18. On the use of wavelet for extracting feature patterns from Multitemporal google earth satellite data sets

    Science.gov (United States)

    Lasaponara, R.

    2012-04-01

    The great amount of multispectral VHR satellite images, even available free of charge in Google earth has opened new strategic challenges in the field of remote sensing for archaeological studies. These challenges substantially deal with: (i) the strategic exploitation of satellite data as much as possible, (ii) the setting up of effective and reliable automatic and/or semiautomatic data processing strategies and (iii) the integration with other data sources from documentary resources to the traditional ground survey, historical documentation, geophysical prospection, etc. VHR satellites provide high resolution data which can improve knowledge on past human activities providing precious qualitative and quantitative information developed to such an extent that currently they share many of the physical characteristics of aerial imagery. This makes them ideal for investigations ranging from a local to a regional scale (see. for example, Lasaponara and Masini 2006a,b, 2007a, 2011; Masini and Lasaponara 2006, 2007, Sparavigna, 2010). Moreover, satellite data are still the only data source for research performed in areas where aerial photography is restricted because of military or political reasons. Among the main advantages of using satellite remote sensing compared to traditional field archaeology herein we briefly focalize on the use of wavelet data processing for enhancing google earth satellite data with particular reference to multitemporal datasets. Study areas selected from Southern Italy, Middle East and South America are presented and discussed. Results obtained point out the use of automatic image enhancement can successfully applied as first step of supervised classification and intelligent data analysis for semiautomatic identification of features of archaeological interest. Reference Lasaponara R, Masini N (2006a) On the potential of panchromatic and multispectral Quickbird data for archaeological prospection. Int J Remote Sens 27: 3607-3614. Lasaponara R

  19. Hybrid Control of a Two-Wheeled Automatic-Balancing Robot with Backlash Feature

    DEFF Research Database (Denmark)

    Løhndorf, Petar Durdevic; Yang, Zhenyu

    2013-01-01

    This paper investigates the application of hybrid control for an automatic balancing robot system subject to backlash effect. The developed controller is a type of sliding mode controller, refereed to as a switching controller, with respect to different situations i.e., whether the backlash is pr...... and comparisons with other solutions show the proposed solution can lead to a very satisfactory anti-backlash performance, with an easy and cost-effective implementation....

  20. The actor set-up of TV advertising. A new process for hybrid formats

    OpenAIRE

    von Rimscha, M Bjørn; Rademacher, Patrick

    2008-01-01

    The paper introduces a basic description of the advertising process in TV advertising and discusses how this process might be altered when 30 second spots are replaced by hybrid advertising formats such as sponsoring and placements. For each actor in the process the potential benefit of hybrid advertising is identified and the respective interest in changing the process is deduced. A qualitative interview study with representatives from each actor in the process is used to illustrate that con...

  1. A large set of newly created interspecific Saccharomyces hybrids increases aromatic diversity in lager beers.

    Science.gov (United States)

    Mertens, Stijn; Steensels, Jan; Saels, Veerle; De Rouck, Gert; Aerts, Guido; Verstrepen, Kevin J

    2015-12-01

    Lager beer is the most consumed alcoholic beverage in the world. Its production process is marked by a fermentation conducted at low (8 to 15°C) temperatures and by the use of Saccharomyces pastorianus, an interspecific hybrid between Saccharomyces cerevisiae and the cold-tolerant Saccharomyces eubayanus. Recent whole-genome-sequencing efforts revealed that the currently available lager yeasts belong to one of only two archetypes, "Saaz" and "Frohberg." This limited genetic variation likely reflects that all lager yeasts descend from only two separate interspecific hybridization events, which may also explain the relatively limited aromatic diversity between the available lager beer yeasts compared to, for example, wine and ale beer yeasts. In this study, 31 novel interspecific yeast hybrids were developed, resulting from large-scale robot-assisted selection and breeding between carefully selected strains of S. cerevisiae (six strains) and S. eubayanus (two strains). Interestingly, many of the resulting hybrids showed a broader temperature tolerance than their parental strains and reference S. pastorianus yeasts. Moreover, they combined a high fermentation capacity with a desirable aroma profile in laboratory-scale lager beer fermentations, thereby successfully enriching the currently available lager yeast biodiversity. Pilot-scale trials further confirmed the industrial potential of these hybrids and identified one strain, hybrid H29, which combines a fast fermentation, high attenuation, and the production of a complex, desirable fruity aroma. Copyright © 2015, American Society for Microbiology. All Rights Reserved.

  2. A HYBRID FILTER AND WRAPPER FEATURE SELECTION APPROACH FOR DETECTING CONTAMINATION IN DRINKING WATER MANAGEMENT SYSTEM

    Directory of Open Access Journals (Sweden)

    S. VISALAKSHI

    2017-07-01

    Full Text Available Feature selection is an important task in predictive models which helps to identify the irrelevant features in the high - dimensional dataset. In this case of water contamination detection dataset, the standard wrapper algorithm alone cannot be applied because of the complexity. To overcome this computational complexity problem and making it lighter, filter-wrapper based algorithm has been proposed. In this work, reducing the feature space is a significant component of water contamination. The main findings are as follows: (1 The main goal is speeding up the feature selection process, so the proposed filter - based feature pre-selection is applied and guarantees that useful data are improbable to be detached in the initial stage which discussed briefly in this paper. (2 The resulting features are again filtered by using the Genetic Algorithm coded with Support Vector Machine method, where it facilitates to nutshell the subset of features with high accuracy and decreases the expense. Experimental results show that the proposed methods trim down redundant features effectively and achieved better classification accuracy.

  3. Obscene Video Recognition Using Fuzzy SVM and New Sets of Features

    Directory of Open Access Journals (Sweden)

    Alireza Behrad

    2013-02-01

    Full Text Available In this paper, a novel approach for identifying normal and obscene videos is proposed. In order to classify different episodes of a video independently and discard the need to process all frames, first, key frames are extracted and skin regions are detected for groups of video frames starting with key frames. In the second step, three different features including 1- structural features based on single frame information, 2- features based on spatiotemporal volume and 3-motion-based features, are extracted for each episode of video. The PCA-LDA method is then applied to reduce the size of structural features and select more distinctive features. For the final step, we use fuzzy or a Weighted Support Vector Machine (WSVM classifier to identify video episodes. We also employ a multilayer Kohonen network as an initial clustering algorithm to increase the ability to discriminate between the extracted features into two classes of videos. Features based on motion and periodicity characteristics increase the efficiency of the proposed algorithm in videos with bad illumination and skin colour variation. The proposed method is evaluated using 1100 videos in different environmental and illumination conditions. The experimental results show a correct recognition rate of 94.2% for the proposed algorithm.

  4. Organizational contextual features that influence the implementation of evidence-based practices across healthcare settings: a systematic integrative review.

    Science.gov (United States)

    Li, Shelly-Anne; Jeffs, Lianne; Barwick, Melanie; Stevens, Bonnie

    2018-05-05

    Organizational contextual features have been recognized as important determinants for implementing evidence-based practices across healthcare settings for over a decade. However, implementation scientists have not reached consensus on which features are most important for implementing evidence-based practices. The aims of this review were to identify the most commonly reported organizational contextual features that influence the implementation of evidence-based practices across healthcare settings, and to describe how these features affect implementation. An integrative review was undertaken following literature searches in CINAHL, MEDLINE, PsycINFO, EMBASE, Web of Science, and Cochrane databases from January 2005 to June 2017. English language, peer-reviewed empirical studies exploring organizational context in at least one implementation initiative within a healthcare setting were included. Quality appraisal of the included studies was performed using the Mixed Methods Appraisal Tool. Inductive content analysis informed data extraction and reduction. The search generated 5152 citations. After removing duplicates and applying eligibility criteria, 36 journal articles were included. The majority (n = 20) of the study designs were qualitative, 11 were quantitative, and 5 used a mixed methods approach. Six main organizational contextual features (organizational culture; leadership; networks and communication; resources; evaluation, monitoring and feedback; and champions) were most commonly reported to influence implementation outcomes in the selected studies across a wide range of healthcare settings. We identified six organizational contextual features that appear to be interrelated and work synergistically to influence the implementation of evidence-based practices within an organization. Organizational contextual features did not influence implementation efforts independently from other features. Rather, features were interrelated and often influenced each

  5. Comparison of the effectiveness of alternative feature sets in shape retrieval of multicomponent images

    Science.gov (United States)

    Eakins, John P.; Edwards, Jonathan D.; Riley, K. Jonathan; Rosin, Paul L.

    2001-01-01

    Many different kinds of features have been used as the basis for shape retrieval from image databases. This paper investigates the relative effectiveness of several types of global shape feature, both singly and in combination. The features compared include well-established descriptors such as Fourier coefficients and moment invariants, as well as recently-proposed measures of triangularity and ellipticity. Experiments were conducted within the framework of the ARTISAN shape retrieval system, and retrieval effectiveness assessed on a database of over 10,000 images, using 24 queries and associated ground truth supplied by the UK Patent Office . Our experiments revealed only minor differences in retrieval effectiveness between different measures, suggesting that a wide variety of shape feature combinations can provide adequate discriminating power for effective shape retrieval in multi-component image collections such as trademark registries. Marked differences between measures were observed for some individual queries, suggesting that there could be considerable scope for improving retrieval effectiveness by providing users with an improved framework for searching multi-dimensional feature space.

  6. Toward accurate tooth segmentation from computed tomography images using a hybrid level set model

    Energy Technology Data Exchange (ETDEWEB)

    Gan, Yangzhou; Zhao, Qunfei [Department of Automation, Shanghai Jiao Tong University, and Key Laboratory of System Control and Information Processing, Ministry of Education of China, Shanghai 200240 (China); Xia, Zeyang, E-mail: zy.xia@siat.ac.cn, E-mail: jing.xiong@siat.ac.cn; Hu, Ying [Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, and The Chinese University of Hong Kong, Shenzhen 518055 (China); Xiong, Jing, E-mail: zy.xia@siat.ac.cn, E-mail: jing.xiong@siat.ac.cn [Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, Shenzhen 510855 (China); Zhang, Jianwei [TAMS, Department of Informatics, University of Hamburg, Hamburg 22527 (Germany)

    2015-01-15

    Purpose: A three-dimensional (3D) model of the teeth provides important information for orthodontic diagnosis and treatment planning. Tooth segmentation is an essential step in generating the 3D digital model from computed tomography (CT) images. The aim of this study is to develop an accurate and efficient tooth segmentation method from CT images. Methods: The 3D dental CT volumetric images are segmented slice by slice in a two-dimensional (2D) transverse plane. The 2D segmentation is composed of a manual initialization step and an automatic slice by slice segmentation step. In the manual initialization step, the user manually picks a starting slice and selects a seed point for each tooth in this slice. In the automatic slice segmentation step, a developed hybrid level set model is applied to segment tooth contours from each slice. Tooth contour propagation strategy is employed to initialize the level set function automatically. Cone beam CT (CBCT) images of two subjects were used to tune the parameters. Images of 16 additional subjects were used to validate the performance of the method. Volume overlap metrics and surface distance metrics were adopted to assess the segmentation accuracy quantitatively. The volume overlap metrics were volume difference (VD, mm{sup 3}) and Dice similarity coefficient (DSC, %). The surface distance metrics were average symmetric surface distance (ASSD, mm), RMS (root mean square) symmetric surface distance (RMSSSD, mm), and maximum symmetric surface distance (MSSD, mm). Computation time was recorded to assess the efficiency. The performance of the proposed method has been compared with two state-of-the-art methods. Results: For the tested CBCT images, the VD, DSC, ASSD, RMSSSD, and MSSD for the incisor were 38.16 ± 12.94 mm{sup 3}, 88.82 ± 2.14%, 0.29 ± 0.03 mm, 0.32 ± 0.08 mm, and 1.25 ± 0.58 mm, respectively; the VD, DSC, ASSD, RMSSSD, and MSSD for the canine were 49.12 ± 9.33 mm{sup 3}, 91.57 ± 0.82%, 0.27 ± 0.02 mm, 0

  7. Toward accurate tooth segmentation from computed tomography images using a hybrid level set model

    International Nuclear Information System (INIS)

    Gan, Yangzhou; Zhao, Qunfei; Xia, Zeyang; Hu, Ying; Xiong, Jing; Zhang, Jianwei

    2015-01-01

    Purpose: A three-dimensional (3D) model of the teeth provides important information for orthodontic diagnosis and treatment planning. Tooth segmentation is an essential step in generating the 3D digital model from computed tomography (CT) images. The aim of this study is to develop an accurate and efficient tooth segmentation method from CT images. Methods: The 3D dental CT volumetric images are segmented slice by slice in a two-dimensional (2D) transverse plane. The 2D segmentation is composed of a manual initialization step and an automatic slice by slice segmentation step. In the manual initialization step, the user manually picks a starting slice and selects a seed point for each tooth in this slice. In the automatic slice segmentation step, a developed hybrid level set model is applied to segment tooth contours from each slice. Tooth contour propagation strategy is employed to initialize the level set function automatically. Cone beam CT (CBCT) images of two subjects were used to tune the parameters. Images of 16 additional subjects were used to validate the performance of the method. Volume overlap metrics and surface distance metrics were adopted to assess the segmentation accuracy quantitatively. The volume overlap metrics were volume difference (VD, mm 3 ) and Dice similarity coefficient (DSC, %). The surface distance metrics were average symmetric surface distance (ASSD, mm), RMS (root mean square) symmetric surface distance (RMSSSD, mm), and maximum symmetric surface distance (MSSD, mm). Computation time was recorded to assess the efficiency. The performance of the proposed method has been compared with two state-of-the-art methods. Results: For the tested CBCT images, the VD, DSC, ASSD, RMSSSD, and MSSD for the incisor were 38.16 ± 12.94 mm 3 , 88.82 ± 2.14%, 0.29 ± 0.03 mm, 0.32 ± 0.08 mm, and 1.25 ± 0.58 mm, respectively; the VD, DSC, ASSD, RMSSSD, and MSSD for the canine were 49.12 ± 9.33 mm 3 , 91.57 ± 0.82%, 0.27 ± 0.02 mm, 0.28 ± 0.03 mm

  8. Homogeneity analysis with k sets of variables: An alternating least squares method with optimal scaling features

    NARCIS (Netherlands)

    van der Burg, Eeke; de Leeuw, Jan; Verdegaal, Renée

    1988-01-01

    Homogeneity analysis, or multiple correspondence analysis, is usually applied tok separate variables. In this paper we apply it to sets of variables by using sums within sets. The resulting technique is called OVERALS. It uses the notion of optimal scaling, with transformations that can be multiple

  9. An Optimized Set of Fluorescence In Situ Hybridization Probes for Detection of Pancreatobiliary Tract Cancer in Cytology Brush Samples.

    Science.gov (United States)

    Barr Fritcher, Emily G; Voss, Jesse S; Brankley, Shannon M; Campion, Michael B; Jenkins, Sarah M; Keeney, Matthew E; Henry, Michael R; Kerr, Sarah M; Chaiteerakij, Roongruedee; Pestova, Ekaterina V; Clayton, Amy C; Zhang, Jun; Roberts, Lewis R; Gores, Gregory J; Halling, Kevin C; Kipp, Benjamin R

    2015-12-01

    Pancreatobiliary cancer is detected by fluorescence in situ hybridization (FISH) of pancreatobiliary brush samples with UroVysion probes, originally designed to detect bladder cancer. We designed a set of new probes to detect pancreatobiliary cancer and compared its performance with that of UroVysion and routine cytology analysis. We tested a set of FISH probes on tumor tissues (cholangiocarcinoma or pancreatic carcinoma) and non-tumor tissues from 29 patients. We identified 4 probes that had high specificity for tumor vs non-tumor tissues; we called this set of probes pancreatobiliary FISH. We performed a retrospective analysis of brush samples from 272 patients who underwent endoscopic retrograde cholangiopancreatography for evaluation of malignancy at the Mayo Clinic; results were available from routine cytology and FISH with UroVysion probes. Archived residual specimens were retrieved and used to evaluate the pancreatobiliary FISH probes. Cutoff values for FISH with the pancreatobiliary probes were determined using 89 samples and validated in the remaining 183 samples. Clinical and pathologic evidence of malignancy in the pancreatobiliary tract within 2 years of brush sample collection was used as the standard; samples from patients without malignancies were used as negative controls. The validation cohort included 85 patients with malignancies (46.4%) and 114 patients with primary sclerosing cholangitis (62.3%). Samples containing cells above the cutoff for polysomy (copy number gain of ≥2 probes) were classified as positive in FISH with the UroVysion and pancreatobiliary probes. Multivariable logistic regression was used to estimate associations between clinical and pathology findings and results from FISH. The combination of FISH probes 1q21, 7p12, 8q24, and 9p21 identified cancer cells with 93% sensitivity and 100% specificity in pancreatobiliary tissue samples and were therefore included in the pancreatobiliary probe set. In the validation cohort of

  10. A proposed framework on hybrid feature selection techniques for handling high dimensional educational data

    Science.gov (United States)

    Shahiri, Amirah Mohamed; Husain, Wahidah; Rashid, Nur'Aini Abd

    2017-10-01

    Huge amounts of data in educational datasets may cause the problem in producing quality data. Recently, data mining approach are increasingly used by educational data mining researchers for analyzing the data patterns. However, many research studies have concentrated on selecting suitable learning algorithms instead of performing feature selection process. As a result, these data has problem with computational complexity and spend longer computational time for classification. The main objective of this research is to provide an overview of feature selection techniques that have been used to analyze the most significant features. Then, this research will propose a framework to improve the quality of students' dataset. The proposed framework uses filter and wrapper based technique to support prediction process in future study.

  11. Hybrid image representation learning model with invariant features for basal cell carcinoma detection

    Science.gov (United States)

    Arevalo, John; Cruz-Roa, Angel; González, Fabio A.

    2013-11-01

    This paper presents a novel method for basal-cell carcinoma detection, which combines state-of-the-art methods for unsupervised feature learning (UFL) and bag of features (BOF) representation. BOF, which is a form of representation learning, has shown a good performance in automatic histopathology image classi cation. In BOF, patches are usually represented using descriptors such as SIFT and DCT. We propose to use UFL to learn the patch representation itself. This is accomplished by applying a topographic UFL method (T-RICA), which automatically learns visual invariance properties of color, scale and rotation from an image collection. These learned features also reveals these visual properties associated to cancerous and healthy tissues and improves carcinoma detection results by 7% with respect to traditional autoencoders, and 6% with respect to standard DCT representations obtaining in average 92% in terms of F-score and 93% of balanced accuracy.

  12. The Roles of Feature-Specific Task Set and Bottom-Up Salience in Attentional Capture: An ERP Study

    Science.gov (United States)

    Eimer, Martin; Kiss, Monika; Press, Clare; Sauter, Disa

    2009-01-01

    We investigated the roles of top-down task set and bottom-up stimulus salience for feature-specific attentional capture. Spatially nonpredictive cues preceded search arrays that included a color-defined target. For target-color singleton cues, behavioral spatial cueing effects were accompanied by cue-induced N2pc components, indicative of…

  13. Simultaneous and Sequential Feature Negative Discriminations: Elemental Learning and Occasion Setting in Human Pavlovian Conditioning

    Science.gov (United States)

    Baeyens, Frank; Vervliet, Bram; Vansteenwegen, Debora; Beckers, Tom; Hermans, Dirk; Eelen, Paul

    2004-01-01

    Using a conditioned suppression task, we investigated simultaneous (XA-/A+) vs. sequential (X [right arrow] A-/A+) Feature Negative (FN) discrimination learning in humans. We expected the simultaneous discrimination to result in X (or alternatively the XA configuration) becoming an inhibitor acting directly on the US, and the sequential…

  14. Credible Set Estimation, Analysis, and Applications in Synthetic Aperture Radar Canonical Feature Extraction

    Science.gov (United States)

    2015-03-26

    83 5.1 Marginal PMFs for the cylinder scene at coarse zoom. . . . . . . . . . . . . . . 85 5.2 SAR image of a Nissan Sentra with canonical...of a Nissan Sentra with canonical features extracted by the SPLIT algorithm. 5.2.4 Experiment Summary. A notional algorithm is presented in Figure 5.3

  15. Setting and changing feature priorities in visual short-term memory.

    Science.gov (United States)

    Kalogeropoulou, Zampeta; Jagadeesh, Akshay V; Ohl, Sven; Rolfs, Martin

    2017-04-01

    Many everyday tasks require prioritizing some visual features over competing ones, both during the selection from the rich sensory input and while maintaining information in visual short-term memory (VSTM). Here, we show that observers can change priorities in VSTM when, initially, they attended to a different feature. Observers reported from memory the orientation of one of two spatially interspersed groups of black and white gratings. Using colored pre-cues (presented before stimulus onset) and retro-cues (presented after stimulus offset) predicting the to-be-reported group, we manipulated observers' feature priorities independently during stimulus encoding and maintenance, respectively. Valid pre-cues reliably increased observers' performance (reduced guessing, increased report precision) as compared to neutral ones; invalid pre-cues had the opposite effect. Valid retro-cues also consistently improved performance (by reducing random guesses), even if the unexpected group suddenly became relevant (invalid-valid condition). Thus, feature-based attention can reshape priorities in VSTM protecting information that would otherwise be forgotten.

  16. A hybrid approach of gene sets and single genes for the prediction of survival risks with gene expression data.

    Science.gov (United States)

    Seok, Junhee; Davis, Ronald W; Xiao, Wenzhong

    2015-01-01

    Accumulated biological knowledge is often encoded as gene sets, collections of genes associated with similar biological functions or pathways. The use of gene sets in the analyses of high-throughput gene expression data has been intensively studied and applied in clinical research. However, the main interest remains in finding modules of biological knowledge, or corresponding gene sets, significantly associated with disease conditions. Risk prediction from censored survival times using gene sets hasn't been well studied. In this work, we propose a hybrid method that uses both single gene and gene set information together to predict patient survival risks from gene expression profiles. In the proposed method, gene sets provide context-level information that is poorly reflected by single genes. Complementarily, single genes help to supplement incomplete information of gene sets due to our imperfect biomedical knowledge. Through the tests over multiple data sets of cancer and trauma injury, the proposed method showed robust and improved performance compared with the conventional approaches with only single genes or gene sets solely. Additionally, we examined the prediction result in the trauma injury data, and showed that the modules of biological knowledge used in the prediction by the proposed method were highly interpretable in biology. A wide range of survival prediction problems in clinical genomics is expected to benefit from the use of biological knowledge.

  17. Comparative analysis of different process simulation settings of a micro injection molded part featuring conformal cooling

    DEFF Research Database (Denmark)

    Marhöfer, David Maximilian; Tosello, Guido; Islam, Aminul

    2015-01-01

    . In the reported work, process simulations using Autodesk Moldflow Insight 2015® are applied to a micro mechanical part to be fabricated by micro injection molding and with over-all dimensions of 12.0 × 3.0 × 0.8 mm³ and micro features (micro hole, diameter of 580 μm, and sharp radii down to 100 μm). Three...

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

    Science.gov (United States)

    Zhang, Bin; Deng, Congying; Zhang, Yi

    2018-03-01

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

  19. Large scale features and energetics of the hybrid subtropical low `Duck' over the Tasman Sea

    Science.gov (United States)

    Pezza, Alexandre Bernardes; Garde, Luke Andrew; Veiga, José Augusto Paixão; Simmonds, Ian

    2014-01-01

    New aspects of the genesis and partial tropical transition of a rare hybrid subtropical cyclone on the eastern Australian coast are presented. The `Duck' (March 2001) attracted more recent attention due to its underlying genesis mechanisms being remarkably similar to the first South Atlantic hurricane (March 2004). Here we put this cyclone in climate perspective, showing that it belongs to a class within the 1 % lowest frequency percentile in the Southern Hemisphere as a function of its thermal evolution. A large scale analysis reveals a combined influence from an existing tropical cyclone and a persistent mid-latitude block. A Lagrangian tracer showed that the upper level air parcels arriving at the cyclone's center had been modified by the blocking. Lorenz energetics is used to identify connections with both tropical and extratropical processes, and reveal how these create the large scale environment conducive to the development of the vortex. The results reveal that the blocking exerted the most important influence, with a strong peak in barotropic generation of kinetic energy over a large area traversed by the air parcels just before genesis. A secondary peak also coincided with the first time the cyclone developed an upper level warm core, but with insufficient amplitude to allow for a full tropical transition. The applications of this technique are numerous and promising, particularly on the use of global climate models to infer changes in environmental parameters associated with severe storms.

  20. ANALYSIS DATA SETS USING HYBRID TECHNIQUES APPLIED ARTIFICIAL INTELLIGENCE BASED PRODUCTION SYSTEMS INTEGRATED DESIGN

    OpenAIRE

    Daniel-Petru GHENCEA; Miron ZAPCIU; Claudiu-Florinel BISU; Elena-Iuliana BOTEANU; Elena-Luminiţa OLTEANU

    2017-01-01

    The paper proposes a prediction model of behavior spindle from the point of view of the thermal deformations and the level of the vibrations by highlighting and processing the characteristic equations. This is a model analysis for the shaft with similar electro-mechanical characteristics can be achieved using a hybrid analysis based on artificial intelligence (genetic algorithms - artificial neural networks - fuzzy logic). The paper presents a prediction mode obtaining valid range of values f...

  1. Fast evaluation of patient set-up during radiotherapy by aligning features in portal and simulator images

    International Nuclear Information System (INIS)

    Bijhold, J.; Herk, M. van; Vijlbrief, R.; Lebesque, J.V.

    1991-01-01

    A new fast method is presented for the quantification of patient set-up errors during radiotherapy with external photon beams. The set-up errors are described as deviations in relative position and orientation of specified anatomical structures relative to specified field shaping devices. These deviations are determined from parameters of the image transformations that make their features in a portal image align with the corresponding features in a simulator image. Knowledge of some set-up parameters during treatment simulation is required. The method does not require accurate knowledge about the position of the portal imaging device as long as the positions of some of the field shaping devices are verified independently during treatment. By applying this method, deviations in a pelvic phantom set-up can be measured with a precision of 2 mm within 1 minute. Theoretical considerations and experiments have shown that the method is not applicable when there are out-of-plane rotations larger than 2 degrees or translations larger than 1 cm. Inter-observer variability proved to be a source of large systematic errors, which could be reduced by offering a precise protocol for the feature alignment. (author)

  2. Entropy Based Feature Selection for Fuzzy Set-Valued Information Systems

    Science.gov (United States)

    Ahmed, Waseem; Sufyan Beg, M. M.; Ahmad, Tanvir

    2018-06-01

    In Set-valued Information Systems (SIS), several objects contain more than one value for some attributes. Tolerance relation used for handling SIS sometimes leads to loss of certain information. To surmount this problem, fuzzy rough model was introduced. However, in some cases, SIS may contain some real or continuous set-values. Therefore, the existing fuzzy rough model for handling Information system with fuzzy set-values needs some changes. In this paper, Fuzzy Set-valued Information System (FSIS) is proposed and fuzzy similarity relation for FSIS is defined. Yager's relative conditional entropy was studied to find the significance measure of a candidate attribute of FSIS. Later, using these significance values, three greedy forward algorithms are discussed for finding the reduct and relative reduct for the proposed FSIS. An experiment was conducted on a sample population of the real dataset and a comparison of classification accuracies of the proposed FSIS with the existing SIS and single-valued Fuzzy Information Systems was made, which demonstrated the effectiveness of proposed FSIS.

  3. HCRS: A hybrid clothes recommender system based on user ratings and product features

    OpenAIRE

    Hu, Xiaosong; Zhu, Wen; Li, Qing

    2014-01-01

    Nowadays, online clothes-selling business has become popular and extremely attractive because of its convenience and cheap-and-fine price. Good examples of these successful Web sites include Yintai.com, Vancl.com and Shop.vipshop.com which provide thousands of clothes for online shoppers. The challenge for online shoppers lies on how to find a good product from lots of options. In this article, we propose a collaborative clothes recommender for easy shopping. One of the unique features of thi...

  4. Automated oral cancer identification using histopathological images: a hybrid feature extraction paradigm.

    Science.gov (United States)

    Krishnan, M Muthu Rama; Venkatraghavan, Vikram; Acharya, U Rajendra; Pal, Mousumi; Paul, Ranjan Rashmi; Min, Lim Choo; Ray, Ajoy Kumar; Chatterjee, Jyotirmoy; Chakraborty, Chandan

    2012-02-01

    Oral cancer (OC) is the sixth most common cancer in the world. In India it is the most common malignant neoplasm. Histopathological images have widely been used in the differential diagnosis of normal, oral precancerous (oral sub-mucous fibrosis (OSF)) and cancer lesions. However, this technique is limited by subjective interpretations and less accurate diagnosis. The objective of this work is to improve the classification accuracy based on textural features in the development of a computer assisted screening of OSF. The approach introduced here is to grade the histopathological tissue sections into normal, OSF without Dysplasia (OSFWD) and OSF with Dysplasia (OSFD), which would help the oral onco-pathologists to screen the subjects rapidly. The biopsy sections are stained with H&E. The optical density of the pixels in the light microscopic images is recorded and represented as matrix quantized as integers from 0 to 255 for each fundamental color (Red, Green, Blue), resulting in a M×N×3 matrix of integers. Depending on either normal or OSF condition, the image has various granular structures which are self similar patterns at different scales termed "texture". We have extracted these textural changes using Higher Order Spectra (HOS), Local Binary Pattern (LBP), and Laws Texture Energy (LTE) from the histopathological images (normal, OSFWD and OSFD). These feature vectors were fed to five different classifiers: Decision Tree (DT), Sugeno Fuzzy, Gaussian Mixture Model (GMM), K-Nearest Neighbor (K-NN), Radial Basis Probabilistic Neural Network (RBPNN) to select the best classifier. Our results show that combination of texture and HOS features coupled with Fuzzy classifier resulted in 95.7% accuracy, sensitivity and specificity of 94.5% and 98.8% respectively. Finally, we have proposed a novel integrated index called Oral Malignancy Index (OMI) using the HOS, LBP, LTE features, to diagnose benign or malignant tissues using just one number. We hope that this OMI can

  5. Advanced Hybrid Spacesuit Concept Featuring Integrated Open Loop and Closed Loop Ventilation Systems

    Science.gov (United States)

    Daniel, Brian A.; Fitzpatrick, Garret R.; Gohmert, Dustin M.; Ybarra, Rick M.; Dub, Mark O.

    2013-01-01

    A document discusses the design and prototype of an advanced spacesuit concept that integrates the capability to function seamlessly with multiple ventilation system approaches. Traditionally, spacesuits are designed to operate both dependently and independently of a host vehicle environment control and life support system (ECLSS). Spacesuits that operate independent of vehicle-provided ECLSS services must do so with equipment selfcontained within or on the spacesuit. Suits that are dependent on vehicle-provided consumables must remain physically connected to and integrated with the vehicle to operate properly. This innovation is the design and prototype of a hybrid spacesuit approach that configures the spacesuit to seamlessly interface and integrate with either type of vehicular systems, while still maintaining the ability to function completely independent of the vehicle. An existing Advanced Crew Escape Suit (ACES) was utilized as the platform from which to develop the innovation. The ACES was retrofitted with selected components and one-off items to achieve the objective. The ventilation system concept was developed and prototyped/retrofitted to an existing ACES. Components were selected to provide suit connectors, hoses/umbilicals, internal breathing system ducting/ conduits, etc. The concept utilizes a lowpressure- drop, high-flow ventilation system that serves as a conduit from the vehicle supply into the suit, up through a neck seal, into the breathing helmet cavity, back down through the neck seal, out of the suit, and returned to the vehicle. The concept also utilizes a modified demand-based breathing system configured to function seamlessly with the low-pressure-drop closed-loop ventilation system.

  6. The Role of Interaction Patterns with Hybrid Electric Vehicle Eco-Features for Drivers' Eco-Driving Performance.

    Science.gov (United States)

    Arend, Matthias G; Franke, Thomas

    2017-03-01

    The objective of the present research was to understand drivers' interaction patterns with hybrid electric vehicles' (HEV) eco-features (electric propulsion, regenerative braking, neutral mode) and their relationship to fuel efficiency and driver characteristics (technical system knowledge, eco-driving motivation). Eco-driving (driving behaviors performed to achieve higher fuel efficiency) has the potential to reduce CO 2 emissions caused by road vehicles. Eco-driving in HEVs is particularly challenging due to the systems' dynamic energy flows. As a result, drivers are likely to show diverse eco-driving behaviors, depending on factors like knowledge and motivation. The eco-features represent an interface for the control of the systems' energy flows. A sample of 121 HEV drivers who had constantly logged their fuel consumption prior to the study participated in an online questionnaire. Drivers' interaction patterns with the eco-features were related to fuel efficiency. A common factor was identified in an exploratory factor analysis, characterizing the intensity of actively dealing with electric energy, which was also related to fuel efficiency. Driver characteristics were not related to this factor, yet they were significant predictors of fuel efficiency. From the perspective of user-energy interaction, the relationship of the aggregated factor to fuel efficiency emphasizes the central role of drivers' perception of and interaction with energy conversions in determining HEV eco-driving success. To arrive at an in-depth understanding of drivers' eco-driving behaviors that can guide interface design, authors of future research should be concerned with the psychological processes that underlie drivers' interaction patterns with eco-features.

  7. Predicting DNA binding proteins using support vector machine with hybrid fractal features.

    Science.gov (United States)

    Niu, Xiao-Hui; Hu, Xue-Hai; Shi, Feng; Xia, Jing-Bo

    2014-02-21

    DNA-binding proteins play a vitally important role in many biological processes. Prediction of DNA-binding proteins from amino acid sequence is a significant but not fairly resolved scientific problem. Chaos game representation (CGR) investigates the patterns hidden in protein sequences, and visually reveals previously unknown structure. Fractal dimensions (FD) are good tools to measure sizes of complex, highly irregular geometric objects. In order to extract the intrinsic correlation with DNA-binding property from protein sequences, CGR algorithm, fractal dimension and amino acid composition are applied to formulate the numerical features of protein samples in this paper. Seven groups of features are extracted, which can be computed directly from the primary sequence, and each group is evaluated by the 10-fold cross-validation test and Jackknife test. Comparing the results of numerical experiments, the group of amino acid composition and fractal dimension (21-dimension vector) gets the best result, the average accuracy is 81.82% and average Matthew's correlation coefficient (MCC) is 0.6017. This resulting predictor is also compared with existing method DNA-Prot and shows better performances. © 2013 The Authors. Published by Elsevier Ltd All rights reserved.

  8. Tech-Assisted Language Learning Tasks in an EFL Setting: Use of Hand phone Recording Feature

    Directory of Open Access Journals (Sweden)

    Alireza Shakarami

    2014-09-01

    Full Text Available Technology with its speedy great leaps forward has undeniable impact on every aspect of our life in the new millennium. It has supplied us with different affordances almost daily or more precisely in a matter of hours. Technology and Computer seems to be a break through as for their roles in the Twenty-First century educational system. Examples are numerous, among which CALL, CMC, and Virtual learning spaces come to mind instantly. Amongst the newly developed gadgets of today are the sophisticated smart Hand phones which are far more ahead of a communication tool once designed for. Development of Hand phone as a wide-spread multi-tasking gadget has urged researchers to investigate its effect on every aspect of learning process including language learning. This study attempts to explore the effects of using cell phone audio recording feature, by Iranian EFL learners, on the development of their speaking skills. Thirty-five sophomore students were enrolled in a pre-posttest designed study. Data on their English speaking experience using audio–recording features of their Hand phones were collected. At the end of the semester, the performance of both groups, treatment and control, were observed, evaluated, and analyzed; thereafter procured qualitatively at the next phase. The quantitative outcome lent support to integrating Hand phones as part of the language learning curriculum. Keywords:

  9. Hybrid feature selection algorithm using symmetrical uncertainty and a harmony search algorithm

    Science.gov (United States)

    Salameh Shreem, Salam; Abdullah, Salwani; Nazri, Mohd Zakree Ahmad

    2016-04-01

    Microarray technology can be used as an efficient diagnostic system to recognise diseases such as tumours or to discriminate between different types of cancers in normal tissues. This technology has received increasing attention from the bioinformatics community because of its potential in designing powerful decision-making tools for cancer diagnosis. However, the presence of thousands or tens of thousands of genes affects the predictive accuracy of this technology from the perspective of classification. Thus, a key issue in microarray data is identifying or selecting the smallest possible set of genes from the input data that can achieve good predictive accuracy for classification. In this work, we propose a two-stage selection algorithm for gene selection problems in microarray data-sets called the symmetrical uncertainty filter and harmony search algorithm wrapper (SU-HSA). Experimental results show that the SU-HSA is better than HSA in isolation for all data-sets in terms of the accuracy and achieves a lower number of genes on 6 out of 10 instances. Furthermore, the comparison with state-of-the-art methods shows that our proposed approach is able to obtain 5 (out of 10) new best results in terms of the number of selected genes and competitive results in terms of the classification accuracy.

  10. Hybrid Wavelet De-noising and Rank-Set Pair Analysis approach for forecasting hydro-meteorological time series

    Science.gov (United States)

    WANG, D.; Wang, Y.; Zeng, X.

    2017-12-01

    Accurate, fast forecasting of hydro-meteorological time series is presently a major challenge in drought and flood mitigation. This paper proposes a hybrid approach, Wavelet De-noising (WD) and Rank-Set Pair Analysis (RSPA), that takes full advantage of a combination of the two approaches to improve forecasts of hydro-meteorological time series. WD allows decomposition and reconstruction of a time series by the wavelet transform, and hence separation of the noise from the original series. RSPA, a more reliable and efficient version of Set Pair Analysis, is integrated with WD to form the hybrid WD-RSPA approach. Two types of hydro-meteorological data sets with different characteristics and different levels of human influences at some representative stations are used to illustrate the WD-RSPA approach. The approach is also compared to three other generic methods: the conventional Auto Regressive Integrated Moving Average (ARIMA) method, Artificial Neural Networks (ANNs) (BP-error Back Propagation, MLP-Multilayer Perceptron and RBF-Radial Basis Function), and RSPA alone. Nine error metrics are used to evaluate the model performance. The results show that WD-RSPA is accurate, feasible, and effective. In particular, WD-RSPA is found to be the best among the various generic methods compared in this paper, even when the extreme events are included within a time series.

  11. Human body as a set of biometric features identified by means of optoelectronics

    Science.gov (United States)

    Podbielska, Halina; Bauer, Joanna

    2005-09-01

    Human body posses many unique, singular features that are impossible to copy or forge. Nowadays, to establish and to ensure the public security requires specially designed devices and systems. Biometrics is a field of science and technology, exploiting human body characteristics for people recognition. It identifies the most characteristic and unique ones in order to design and construct systems capable to recognize people. In this paper some overview is given, presenting the achievements in biometrics. The verification and identification process is explained, along with the way of evaluation of biometric recognition systems. The most frequently human biometrics used in practice are shortly presented, including fingerprints, facial imaging (including thermal characteristic), hand geometry and iris patterns.

  12. Systems-Level Annotation of a Metabolomics Data Set Reduces 25 000 Features to Fewer than 1000 Unique Metabolites.

    Science.gov (United States)

    Mahieu, Nathaniel G; Patti, Gary J

    2017-10-03

    When using liquid chromatography/mass spectrometry (LC/MS) to perform untargeted metabolomics, it is now routine to detect tens of thousands of features from biological samples. Poor understanding of the data, however, has complicated interpretation and masked the number of unique metabolites actually being measured in an experiment. Here we place an upper bound on the number of unique metabolites detected in Escherichia coli samples analyzed with one untargeted metabolomics method. We first group multiple features arising from the same analyte, which we call "degenerate features", using a context-driven annotation approach. Surprisingly, this analysis revealed thousands of previously unreported degeneracies that reduced the number of unique analytes to ∼2961. We then applied an orthogonal approach to remove nonbiological features from the data using the 13 C-based credentialing technology. This further reduced the number of unique analytes to less than 1000. Our 90% reduction in data is 5-fold greater than previously published studies. On the basis of the results, we propose an alternative approach to untargeted metabolomics that relies on thoroughly annotated reference data sets. To this end, we introduce the creDBle database ( http://creDBle.wustl.edu ), which contains accurate mass, retention time, and MS/MS fragmentation data as well as annotations of all credentialed features.

  13. Fast hybrid fractal image compression using an image feature and neural network

    International Nuclear Information System (INIS)

    Zhou Yiming; Zhang Chao; Zhang Zengke

    2008-01-01

    Since fractal image compression could maintain high-resolution reconstructed images at very high compression ratio, it has great potential to improve the efficiency of image storage and image transmission. On the other hand, fractal image encoding is time consuming for the best matching search between range blocks and domain blocks, which limits the algorithm to practical application greatly. In order to solve this problem, two strategies are adopted to improve the fractal image encoding algorithm in this paper. Firstly, based on the definition of an image feature, a necessary condition of the best matching search and FFC algorithm are proposed, and it could reduce the search space observably and exclude most inappropriate domain blocks according to each range block before the best matching search. Secondly, on the basis of FFC algorithm, in order to reduce the mapping error during the best matching search, a special neural network is constructed to modify the mapping scheme for the subblocks, in which the pixel values fluctuate greatly (FNFC algorithm). Experimental results show that the proposed algorithms could obtain good quality of the reconstructed images and need much less time than the baseline encoding algorithm

  14. Hybrid approach for detection of dental caries based on the methods FCM and level sets

    Science.gov (United States)

    Chaabene, Marwa; Ben Ali, Ramzi; Ejbali, Ridha; Zaied, Mourad

    2017-03-01

    This paper presents a new technique for detection of dental caries that is a bacterial disease that destroys the tooth structure. In our approach, we have achieved a new segmentation method that combines the advantages of fuzzy C mean algorithm and level set method. The results obtained by the FCM algorithm will be used by Level sets algorithm to reduce the influence of the noise effect on the working of each of these algorithms, to facilitate level sets manipulation and to lead to more robust segmentation. The sensitivity and specificity confirm the effectiveness of proposed method for caries detection.

  15. Sensitivity Analysis of features in tolerancing based on constraint function level sets

    International Nuclear Information System (INIS)

    Ziegler, Philipp; Wartzack, Sandro

    2015-01-01

    Usually, the geometry of the manufactured product inherently varies from the nominal geometry. This may negatively affect the product functions and properties (such as quality and reliability), as well as the assemblability of the single components. In order to avoid this, the geometric variation of these component surfaces and associated geometry elements (like hole axes) are restricted by tolerances. Since tighter tolerances lead to significant higher manufacturing costs, tolerances should be specified carefully. Therefore, the impact of deviating component surfaces on functions, properties and assemblability of the product has to be analyzed. As physical experiments are expensive, methods of statistical tolerance analysis tools are widely used in engineering design. Current tolerance simulation tools lack of an appropriate indicator for the impact of deviating component surfaces. In the adoption of Sensitivity Analysis methods, there are several challenges, which arise from the specific framework in tolerancing. This paper presents an approach to adopt Sensitivity Analysis methods on current tolerance simulations with an interface module, which bases on level sets of constraint functions for parameters of the simulation model. The paper is an extension and generalization of Ziegler and Wartzack [1]. Mathematical properties of the constraint functions (convexity, homogeneity), which are important for the computational costs of the Sensitivity Analysis, are shown. The practical use of the method is illustrated in a case study of a plain bearing. - Highlights: • Alternative definition of Deviation Domains. • Proof of mathematical properties of the Deviation Domains. • Definition of the interface between Deviation Domains and Sensitivity Analysis. • Sensitivity analysis of a gearbox to show the methods practical use

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

    Directory of Open Access Journals (Sweden)

    Abdullah M. Iliyasu

    2017-12-01

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

  17. Feature selection in wind speed prediction systems based on a hybrid coral reefs optimization – Extreme learning machine approach

    International Nuclear Information System (INIS)

    Salcedo-Sanz, S.; Pastor-Sánchez, A.; Prieto, L.; Blanco-Aguilera, A.; García-Herrera, R.

    2014-01-01

    Highlights: • A novel approach for short-term wind speed prediction is presented. • The system is formed by a coral reefs optimization algorithm and an extreme learning machine. • Feature selection is carried out with the CRO to improve the ELM performance. • The method is tested in real wind farm data in USA, for the period 2007–2008. - Abstract: This paper presents a novel approach for short-term wind speed prediction based on a Coral Reefs Optimization algorithm (CRO) and an Extreme Learning Machine (ELM), using meteorological predictive variables from a physical model (the Weather Research and Forecast model, WRF). The approach is based on a Feature Selection Problem (FSP) carried out with the CRO, that must obtain a reduced number of predictive variables out of the total available from the WRF. This set of features will be the input of an ELM, that finally provides the wind speed prediction. The CRO is a novel bio-inspired approach, based on the simulation of reef formation and coral reproduction, able to obtain excellent results in optimization problems. On the other hand, the ELM is a new paradigm in neural networks’ training, that provides a robust and extremely fast training of the network. Together, these algorithms are able to successfully solve this problem of feature selection in short-term wind speed prediction. Experiments in a real wind farm in the USA show the excellent performance of the CRO–ELM approach in this FSP wind speed prediction problem

  18. Features of the reproductive setting of men and women which are patients of the programs of assisted reproductive technologies (ARTs

    Directory of Open Access Journals (Sweden)

    A. V. Kaminsky

    2017-10-01

    Full Text Available Infertility refers to those states that significantly affect the psycho-emotional status of a person, causing the state of chronic stress. In turn, chronic stress can lead to the development of stress-induced infertility. The aim of the study was to identify features of the reproductive setting of men and women who are patients of assisted reproductive technology (ART programs in connection with reproductive behavior. Material and methods. Under supervision, there were 233 women and men who needed infertility treatment using ART methods, and 142 fertile women and men who had already had births, and applied for pre-gestational preparation before planning another pregnancy. Methods of psychological testing are used. Results. It has been established that the reproductive setting of infertile men and women is uncertain (contradictory; in it there is a discrepancy and ambivalence in the content of affective, cognitive and conative components. Reproductive testing of individuals having children is definite (harmonious; there is consistency in the content of affective, cognitive and conative components. There are gender differences in the components of the reproductive setting, both infertile and those with children. There is a connection between the type of reproductive setting and the personality characteristics, the relation to the spouse, the motives for the birth of the child. Conclusions. The reproductive settings of infertile men and women who are patients of the ART are different from those of mothers and fathers with newborn babies and require psychological correction.

  19. A new set of wavelet- and fractals-based features for Gleason grading of prostate cancer histopathology images

    Science.gov (United States)

    Mosquera Lopez, Clara; Agaian, Sos

    2013-02-01

    Prostate cancer detection and staging is an important step towards patient treatment selection. Advancements in digital pathology allow the application of new quantitative image analysis algorithms for computer-assisted diagnosis (CAD) on digitized histopathology images. In this paper, we introduce a new set of features to automatically grade pathological images using the well-known Gleason grading system. The goal of this study is to classify biopsy images belonging to Gleason patterns 3, 4, and 5 by using a combination of wavelet and fractal features. For image classification we use pairwise coupling Support Vector Machine (SVM) classifiers. The accuracy of the system, which is close to 97%, is estimated through three different cross-validation schemes. The proposed system offers the potential for automating classification of histological images and supporting prostate cancer diagnosis.

  20. A hybrid wavelet de-noising and Rank-Set Pair Analysis approach for forecasting hydro-meteorological time series.

    Science.gov (United States)

    Wang, Dong; Borthwick, Alistair G; He, Handan; Wang, Yuankun; Zhu, Jieyu; Lu, Yuan; Xu, Pengcheng; Zeng, Xiankui; Wu, Jichun; Wang, Lachun; Zou, Xinqing; Liu, Jiufu; Zou, Ying; He, Ruimin

    2018-01-01

    Accurate, fast forecasting of hydro-meteorological time series is presently a major challenge in drought and flood mitigation. This paper proposes a hybrid approach, wavelet de-noising (WD) and Rank-Set Pair Analysis (RSPA), that takes full advantage of a combination of the two approaches to improve forecasts of hydro-meteorological time series. WD allows decomposition and reconstruction of a time series by the wavelet transform, and hence separation of the noise from the original series. RSPA, a more reliable and efficient version of Set Pair Analysis, is integrated with WD to form the hybrid WD-RSPA approach. Two types of hydro-meteorological data sets with different characteristics and different levels of human influences at some representative stations are used to illustrate the WD-RSPA approach. The approach is also compared to three other generic methods: the conventional Auto Regressive Integrated Moving Average (ARIMA) method, Artificial Neural Networks (ANNs) (BP-error Back Propagation, MLP-Multilayer Perceptron and RBF-Radial Basis Function), and RSPA alone. Nine error metrics are used to evaluate the model performance. Compared to three other generic methods, the results generated by WD-REPA model presented invariably smaller error measures which means the forecasting capability of the WD-REPA model is better than other models. The results show that WD-RSPA is accurate, feasible, and effective. In particular, WD-RSPA is found to be the best among the various generic methods compared in this paper, even when the extreme events are included within a time series. Copyright © 2017 Elsevier Inc. All rights reserved.

  1. Cycle killer... qu'est-ce que c'est? On the comparative approximability of hybridization number and directed feedback vertex set

    NARCIS (Netherlands)

    Kelk, S.M.; Iersel, van L.J.J.; Lekic, N.; Linz, S.; Scornavacca, C.; Stougie, L.

    2011-01-01

    We show that the problem of computing the hybridization number of two rooted binary phylogenetic trees on the same set of taxa X has a constant factor polynomial-time approximation if and only if the problem of computing a minimum-size feedback vertex set in a directed graph (DFVS) has a constant

  2. Molecular and polymeric uranyl and thorium hybrid materials featuring methyl substituted pyrazole dicarboxylates and heterocyclic 1,3-diketones

    Science.gov (United States)

    Carter, Korey P.; Kerr, Andrew T.; Taydakov, Ilya V.; Cahill, Christopher L.

    2018-02-01

    A series of seven novel f-element bearing hybrid materials have been prepared from either methyl substituted 3,4 and 4,5-pyrazoledicarboxylic acids, or heterocyclic 1,3- diketonate ligands using hydrothermal conditions. Compounds 1, [UO2(C6H4N2O4)2(H2O)], and 3, [Th(C6H4N2O4)4(H2O)5]·H2O feature 1-Methyl-1H-pyrazole-3,4-dicarboxylate ligands (SVI-COOH 3,4), whereas 2, [UO2(C6H4N2O4)2(H2O)], and 4, [Th(C6H5N2O4)(OH)(H2O)6]2·2(C6H5N2O4)·3H2O feature 1-Methyl-1H-pyrazole-4,5-dicarboxylate moieties (SVI-COOH 4,5). Compounds 5, [UO2(C13H15N4O2)2(H2O)]·2H2O and 6, [UO2(C11H11N4O2)2(H2O)]·4.5H2O feature 1,3-bis(4-N1-methyl-pyrazolyl)propane-1,3-dione and 1,3-bis(4-N1,3-dimethyl-pyrazolyl)propane-1,3-dione respectively, whereas the heterometallic 7, [UO2(C11H11N4O2)2(CuCl2)(H2O)]·2H2O is formed by using 6 as a metalloligand starting material. Single crystal X-ray diffraction indicates that all coordination to either [UO2]2+ or Th(IV) metal centers is through O-donation as anticipated. Room temperature, solid-state luminescence studies indicate characteristic uranyl emissive behavior for 1 and 2, whereas those for 5 and 6 are weak and poorly resolved.

  3. Numerical simulation of overflow at vertical weirs using a hybrid level set/VOF method

    Science.gov (United States)

    Lv, Xin; Zou, Qingping; Reeve, Dominic

    2011-10-01

    This paper presents the applications of a newly developed free surface flow model to the practical, while challenging overflow problems for weirs. Since the model takes advantage of the strengths of both the level set and volume of fluid methods and solves the Navier-Stokes equations on an unstructured mesh, it is capable of resolving the time evolution of very complex vortical motions, air entrainment and pressure variations due to violent deformations following overflow of the weir crest. In the present study, two different types of vertical weir, namely broad-crested and sharp-crested, are considered for validation purposes. The calculated overflow parameters such as pressure head distributions, velocity distributions, and water surface profiles are compared against experimental data as well as numerical results available in literature. A very good quantitative agreement has been obtained. The numerical model, thus, offers a good alternative to traditional experimental methods in the study of weir problems.

  4. Lost in the supermarket: Quantifying the cost of partitioning memory sets in hybrid search.

    Science.gov (United States)

    Boettcher, Sage E P; Drew, Trafton; Wolfe, Jeremy M

    2018-01-01

    The items on a memorized grocery list are not relevant in every aisle; for example, it is useless to search for the cabbage in the cereal aisle. It might be beneficial if one could mentally partition the list so only the relevant subset was active, so that vegetables would be activated in the produce section. In four experiments, we explored observers' abilities to partition memory searches. For example, if observers held 16 items in memory, but only eight of the items were relevant, would response times resemble a search through eight or 16 items? In Experiments 1a and 1b, observers were not faster for the partition set; however, they suffered relatively small deficits when "lures" (items from the irrelevant subset) were presented, indicating that they were aware of the partition. In Experiment 2 the partitions were based on semantic distinctions, and again, observers were unable to restrict search to the relevant items. In Experiments 3a and 3b, observers attempted to remove items from the list one trial at a time but did not speed up over the course of a block, indicating that they also could not limit their memory searches. Finally, Experiments 4a, 4b, 4c, and 4d showed that observers were able to limit their memory searches when a subset was relevant for a run of trials. Overall, observers appear to be unable or unwilling to partition memory sets from trial to trial, yet they are capable of restricting search to a memory subset that remains relevant for several trials. This pattern is consistent with a cost to switching between currently relevant memory items.

  5. New Hybrid Multiple Attribute Decision-Making Model for Improving Competence Sets: Enhancing a Company’s Core Competitiveness

    Directory of Open Access Journals (Sweden)

    Kuan-Wei Huang

    2016-02-01

    Full Text Available A company’s core competitiveness depends on the strategic allocation of its human resources in alignment with employee capabilities. Competency models can identify the range of capabilities at a company’s disposal, and this information can be used to develop internal or external education training policies for sustainable development. Such models can ensure the importation of a strategic orientation reflecting the growth of its employee competence set and enhancing human resource sustainably. This approach ensures that the most appropriate people are assigned to the most appropriate positions. In this study, we proposed a new hybrid multiple attributed decision-making model by using the Decision-making trial and Evaluation Laboratory Technique (DEMATEL to construct an influential network relation map (INRM and determined the influential weights by using the basic concept of the analytic network process (called DEMATEL-based ANP, DANP; the influential weights were then adopted with a modified Vise Kriterijumska Optimizacija I Kompromisno Resenje (VIKOR method. A simple forecasting technique as an iteration function was also proposed. The proposed model was effective. We expect that the proposed model can facilitate making timely revisions, reflecting the growth of employee competence sets, reducing the performance gap toward the aspiration level, and ensuring the sustainability of a company.

  6. Communication and well-being outcomes of a hybrid service delivery model of intensive impairment-based treatment for aphasia in the hospital setting: a pilot study.

    Science.gov (United States)

    Wenke, Rachel; Cardell, Elizabeth; Lawrie, Melissa; Gunning, Dana

    2018-06-01

    This pilot study aimed to evaluate the effects of an intensive hybrid service delivery model (i.e., combining face-to-face individual, computer and group therapy) on communication and well-being for people with aphasia (PWA) in the hospital setting. The study explored two different intensities of the hybrid model, 4 h/week (Hybrid-4) and 8 h/week (Hybrid-8) both for 8 weeks. Participants ranging from 1 month to 5 years post-onset were allocated using matched-pair randomisation to receive either Hybrid-4 (n = 5) or Hybrid-8 (n = 4) and assessed using a comprehensive language battery by a blinded assessor, as well as selected activity, participation and well-being measures before, immediately after and 4-week post-treatment. All participants in Hybrid-4 and three out of four participants in Hybrid-8 demonstrated clinically significant improvement to measures of language impairment immediately post-treatment, with the majority also demonstrating maintenance effects 4-week post-treatment. Clinically significant improvements to activity, participation and well-being measures were also observed across participants in both groups. Findings support the potential benefit of employing an intensive hybrid service model and suggest that both 4 and 8 h per week of impairment-based treatment for 8 weeks may result in improvements in communication and well-being for some PWA across different stages of recovery. Implications for rehabilitation The present findings help bridge the gap between what evidence suggests is effective intensity of rehabilitation for aphasia and what can be practically delivered in real-world hospital settings. Findings support the potential clinical value of employing a hybrid service model (using computer, group and individual therapy) to deliver intensive rehabilitation to people with aphasia in the hospital setting, and suggest that clinically significant improvements to communication and well-being can result when the model is

  7. Patterns of Limnohabitans Microdiversity across a Large Set of Freshwater Habitats as Revealed by Reverse Line Blot Hybridization

    Science.gov (United States)

    Jezbera, Jan; Jezberová, Jitka; Kasalický, Vojtěch; Šimek, Karel; Hahn, Martin W.

    2013-01-01

    Among abundant freshwater Betaproteobacteria, only few groups are considered to be of central ecological importance. One of them is the well-studied genus Limnohabitans and mainly its R-BT subcluster, investigated previously mainly by fluorescence in situ hybridization methods. We designed, based on sequences from a large Limnohabitans culture collection, 18 RLBH (Reverse Line Blot Hybridization) probes specific for different groups within the genus Limnohabitans by targeting diagnostic sequences on their 16 S–23 S rRNA ITS regions. The developed probes covered in sum 92% of the available isolates. This set of probes was applied to environmental DNA originating from 161 different European standing freshwater habitats to reveal the microdiversity (intra-genus) patterns of the Limnohabitans genus along a pH gradient. Investigated habitats differed in various physicochemical parameters, and represented a very broad range of standing freshwater habitats. The Limnohabitans microdiversity, assessed as number of RLBH-defined groups detected, increased significantly along the gradient of rising pH of habitats. 14 out of 18 probes returned detection signals that allowed predictions on the distribution of distinct Limnohabitans groups. Most probe-defined Limnohabitans groups showed preferences for alkaline habitats, one for acidic, and some seemed to lack preferences. Complete niche-separation was indicated for some of the probe-targeted groups. Moreover, bimodal distributions observed for some groups of Limnohabitans, suggested further niche separation between genotypes within the same probe-defined group. Statistical analyses suggested that different environmental parameters such as pH, conductivity, oxygen and altitude influenced the distribution of distinct groups. The results of our study do not support the hypothesis that the wide ecological distribution of Limnohabitans bacteria in standing freshwater habitats results from generalist adaptations of these bacteria

  8. Patterns of Limnohabitans microdiversity across a large set of freshwater habitats as revealed by Reverse Line Blot Hybridization.

    Directory of Open Access Journals (Sweden)

    Jan Jezbera

    Full Text Available Among abundant freshwater Betaproteobacteria, only few groups are considered to be of central ecological importance. One of them is the well-studied genus Limnohabitans and mainly its R-BT subcluster, investigated previously mainly by fluorescence in situ hybridization methods. We designed, based on sequences from a large Limnohabitans culture collection, 18 RLBH (Reverse Line Blot Hybridization probes specific for different groups within the genus Limnohabitans by targeting diagnostic sequences on their 16 S-23 S rRNA ITS regions. The developed probes covered in sum 92% of the available isolates. This set of probes was applied to environmental DNA originating from 161 different European standing freshwater habitats to reveal the microdiversity (intra-genus patterns of the Limnohabitans genus along a pH gradient. Investigated habitats differed in various physicochemical parameters, and represented a very broad range of standing freshwater habitats. The Limnohabitans microdiversity, assessed as number of RLBH-defined groups detected, increased significantly along the gradient of rising pH of habitats. 14 out of 18 probes returned detection signals that allowed predictions on the distribution of distinct Limnohabitans groups. Most probe-defined Limnohabitans groups showed preferences for alkaline habitats, one for acidic, and some seemed to lack preferences. Complete niche-separation was indicated for some of the probe-targeted groups. Moreover, bimodal distributions observed for some groups of Limnohabitans, suggested further niche separation between genotypes within the same probe-defined group. Statistical analyses suggested that different environmental parameters such as pH, conductivity, oxygen and altitude influenced the distribution of distinct groups. The results of our study do not support the hypothesis that the wide ecological distribution of Limnohabitans bacteria in standing freshwater habitats results from generalist adaptations of

  9. Fluorescence in situ hybridization (FISH screening for the 22q11.2 deletion in patients with clinical features of velocardiofacial syndrome but without cardiac anomalies

    Directory of Open Access Journals (Sweden)

    Paula Sandrin-Garcia

    2007-01-01

    Full Text Available The velocardiofacial syndrome (VCFS, a condition associated with 22q11.2 deletions, is characterized by a typical facies, palatal anomalies, learning disabilities, behavioral disturbances and cardiac defects. We investigated the frequency of these chromosomal deletions in 16 individuals with VCFS features who presented no cardiac anomalies, one of the main characteristics of VCFS. Fluorescent in situ hybridization (FISH with the N25 (D22S75; 22q11.2 probe revealed deletions in ten individuals (62%. Therefore, even in the absence of cardiac anomalies testing for the 22q11.2 microdeletions in individuals showing other clinical features of this syndrome is recommended.

  10. Election Districts and Precincts, PrecinctPoly-The data set is a polygon feature consisting of 220 segments representing voter precinct boundaries., Published in 1991, Davis County Government.

    Data.gov (United States)

    NSGIC Local Govt | GIS Inventory — Election Districts and Precincts dataset current as of 1991. PrecinctPoly-The data set is a polygon feature consisting of 220 segments representing voter precinct...

  11. Alveolar bone-loss area localization in periodontitis radiographs based on threshold segmentation with a hybrid feature fused of intensity and the H-value of fractional Brownian motion model.

    Science.gov (United States)

    Lin, P L; Huang, P W; Huang, P Y; Hsu, H C

    2015-10-01

    Periodontitis involves progressive loss of alveolar bone around the teeth. Hence, automatic alveolar bone-loss (ABL) measurement in periapical radiographs can assist dentists in diagnosing such disease. In this paper, we propose an effective method for ABL area localization and denote it as ABLIfBm. ABLIfBm is a threshold segmentation method that uses a hybrid feature fused of both intensity and texture measured by the H-value of fractional Brownian motion (fBm) model, where the H-value is the Hurst coefficient in the expectation function of a fBm curve (intensity change) and is directly related to the value of fractal dimension. Adopting leave-one-out cross validation training and testing mechanism, ABLIfBm trains weights for both features using Bayesian classifier and transforms the radiograph image into a feature image obtained from a weighted average of both features. Finally, by Otsu's thresholding, it segments the feature image into normal and bone-loss regions. Experimental results on 31 periodontitis radiograph images in terms of mean true positive fraction and false positive fraction are about 92.5% and 14.0%, respectively, where the ground truth is provided by a dentist. The results also demonstrate that ABLIfBm outperforms (a) the threshold segmentation method using either feature alone or a weighted average of the same two features but with weights trained differently; (b) a level set segmentation method presented earlier in literature; and (c) segmentation methods based on Bayesian, K-NN, or SVM classifier using the same two features. Our results suggest that the proposed method can effectively localize alveolar bone-loss areas in periodontitis radiograph images and hence would be useful for dentists in evaluating degree of bone-loss for periodontitis patients. Copyright © 2015 Elsevier Ireland Ltd. All rights reserved.

  12. Differential profiling of volatile organic compound biomarker signatures utilizing a logical statistical filter-set and novel hybrid evolutionary classifiers

    Science.gov (United States)

    Grigsby, Claude C.; Zmuda, Michael A.; Boone, Derek W.; Highlander, Tyler C.; Kramer, Ryan M.; Rizki, Mateen M.

    2012-06-01

    A growing body of discoveries in molecular signatures has revealed that volatile organic compounds (VOCs), the small molecules associated with an individual's odor and breath, can be monitored to reveal the identity and presence of a unique individual, as well their overall physiological status. Given the analysis requirements for differential VOC profiling via gas chromatography/mass spectrometry, our group has developed a novel informatics platform, Metabolite Differentiation and Discovery Lab (MeDDL). In its current version, MeDDL is a comprehensive tool for time-series spectral registration and alignment, visualization, comparative analysis, and machine learning to facilitate the efficient analysis of multiple, large-scale biomarker discovery studies. The MeDDL toolset can therefore identify a large differential subset of registered peaks, where their corresponding intensities can be used as features for classification. This initial screening of peaks yields results sets that are typically too large for incorporation into a portable, electronic nose based system in addition to including VOCs that are not amenable to classification; consequently, it is also important to identify an optimal subset of these peaks to increase classification accuracy and to decrease the cost of the final system. MeDDL's learning tools include a classifier similar to a K-nearest neighbor classifier used in conjunction with a genetic algorithm (GA) that simultaneously optimizes the classifier and subset of features. The GA uses ROC curves to produce classifiers having maximal area under their ROC curve. Experimental results on over a dozen recognition problems show many examples of classifiers and feature sets that produce perfect ROC curves.

  13. The impact of image reconstruction settings on 18F-FDG PET radiomic features. Multi-scanner phantom and patient studies

    International Nuclear Information System (INIS)

    Shiri, Isaac; Abdollahi, Hamid; Rahmim, Arman; Ghaffarian, Pardis; Geramifar, Parham; Bitarafan-Rajabi, Ahmad

    2017-01-01

    The purpose of this study was to investigate the robustness of different PET/CT image radiomic features over a wide range of different reconstruction settings. Phantom and patient studies were conducted, including two PET/CT scanners. Different reconstruction algorithms and parameters including number of sub-iterations, number of subsets, full width at half maximum (FWHM) of Gaussian filter, scan time per bed position and matrix size were studied. Lesions were delineated and one hundred radiomic features were extracted. All radiomics features were categorized based on coefficient of variation (COV). Forty seven percent features showed COV ≤ 5% and 10% of which showed COV > 20%. All geometry based, 44% and 41% of intensity based and texture based features were found as robust respectively. In regard to matrix size, 56% and 6% of all features were found non-robust (COV > 20%) and robust (COV ≤ 5%) respectively. Variability and robustness of PET/CT image radiomics in advanced reconstruction settings is feature-dependent, and different settings have different effects on different features. Radiomic features with low COV can be considered as good candidates for reproducible tumour quantification in multi-center studies. (orig.)

  14. The impact of image reconstruction settings on 18F-FDG PET radiomic features. Multi-scanner phantom and patient studies

    Energy Technology Data Exchange (ETDEWEB)

    Shiri, Isaac; Abdollahi, Hamid [Iran University of Medical Sciences, Department of Medical Physics, School of Medicine, Tehran (Iran, Islamic Republic of); Rahmim, Arman [Johns Hopkins University, Department of Radiology, Baltimore, MD (United States); Johns Hopkins University, Department of Electrical and Computer Engineering, Baltimore, MD (United States); Ghaffarian, Pardis [Shahid Beheshti University of Medical Sciences, Chronic Respiratory Diseases Research Center, National Research Institute of Tuberculosis and Lung Diseases (NRITLD), Tehran (Iran, Islamic Republic of); Shahid Beheshti University of Medical Sciences, PET/CT and Cyclotron Center, Masih Daneshvari Hospital, Tehran (Iran, Islamic Republic of); Geramifar, Parham [Tehran University of Medical Sciences, Research Center for Nuclear Medicine, Shariati Hospital, Tehran (Iran, Islamic Republic of); Bitarafan-Rajabi, Ahmad [Iran University of Medical Sciences, Department of Medical Physics, School of Medicine, Tehran (Iran, Islamic Republic of); Iran University of Medical Sciences, Department of Nuclear Medicine, Rajaei Cardiovascular, Medical and Research Center, Tehran (Iran, Islamic Republic of)

    2017-11-15

    The purpose of this study was to investigate the robustness of different PET/CT image radiomic features over a wide range of different reconstruction settings. Phantom and patient studies were conducted, including two PET/CT scanners. Different reconstruction algorithms and parameters including number of sub-iterations, number of subsets, full width at half maximum (FWHM) of Gaussian filter, scan time per bed position and matrix size were studied. Lesions were delineated and one hundred radiomic features were extracted. All radiomics features were categorized based on coefficient of variation (COV). Forty seven percent features showed COV ≤ 5% and 10% of which showed COV > 20%. All geometry based, 44% and 41% of intensity based and texture based features were found as robust respectively. In regard to matrix size, 56% and 6% of all features were found non-robust (COV > 20%) and robust (COV ≤ 5%) respectively. Variability and robustness of PET/CT image radiomics in advanced reconstruction settings is feature-dependent, and different settings have different effects on different features. Radiomic features with low COV can be considered as good candidates for reproducible tumour quantification in multi-center studies. (orig.)

  15. A compound structure of ELM based on feature selection and parameter optimization using hybrid backtracking search algorithm for wind speed forecasting

    International Nuclear Information System (INIS)

    Zhang, Chu; Zhou, Jianzhong; Li, Chaoshun; Fu, Wenlong; Peng, Tian

    2017-01-01

    Highlights: • A novel hybrid approach is proposed for wind speed forecasting. • The variational mode decomposition (VMD) is optimized to decompose the original wind speed series. • The input matrix and parameters of ELM are optimized simultaneously by using a hybrid BSA. • Results show that OVMD-HBSA-ELM achieves better performance in terms of prediction accuracy. - Abstract: Reliable wind speed forecasting is essential for wind power integration in wind power generation system. The purpose of paper is to develop a novel hybrid model for short-term wind speed forecasting and demonstrates its efficiency. In the proposed model, a compound structure of extreme learning machine (ELM) based on feature selection and parameter optimization using hybrid backtracking search algorithm (HBSA) is employed as the predictor. The real-valued BSA (RBSA) is exploited to search for the optimal combination of weights and bias of ELM while the binary-valued BSA (BBSA) is exploited as a feature selection method applying on the candidate inputs predefined by partial autocorrelation function (PACF) values to reconstruct the input-matrix. Due to the volatility and randomness of wind speed signal, an optimized variational mode decomposition (OVMD) is employed to eliminate the redundant noises. The parameters of the proposed OVMD are determined according to the center frequencies of the decomposed modes and the residual evaluation index (REI). The wind speed signal is decomposed into a few modes via OVMD. The aggregation of the forecasting results of these modes constructs the final forecasting result of the proposed model. The proposed hybrid model has been applied on the mean half-hour wind speed observation data from two wind farms in Inner Mongolia, China and 10-min wind speed data from the Sotavento Galicia wind farm are studied as an additional case. Parallel experiments have been designed to compare with the proposed model. Results obtained from this study indicate that the

  16. Classification of health webpages as expert and non expert with a reduced set of cross-language features.

    Science.gov (United States)

    Grabar, Natalia; Krivine, Sonia; Jaulent, Marie-Christine

    2007-10-11

    Making the distinction between expert and non expert health documents can help users to select the information which is more suitable for them, according to whether they are familiar or not with medical terminology. This issue is particularly important for the information retrieval area. In our work we address this purpose through stylistic corpus analysis and the application of machine learning algorithms. Our hypothesis is that this distinction can be performed on the basis of a small number of features and that such features can be language and domain independent. The used features were acquired in source corpus (Russian language, diabetes topic) and then tested on target (French language, pneumology topic) and source corpora. These cross-language features show 90% precision and 93% recall with non expert documents in source language; and 85% precision and 74% recall with expert documents in target language.

  17. Note: Easy-to-maintain electron cyclotron resonance (ECR) plasma sputtering apparatus featuring hybrid waveguide and coaxial cables for microwave delivery

    Energy Technology Data Exchange (ETDEWEB)

    Akazawa, Housei, E-mail: akazawa.housei@lab.ntt.co.jp [NTT Device Innovation Center, Morinosato Wakamiya, Atsugi, Kanagawa 243-0198 (Japan)

    2016-06-15

    The branched-waveguide electron cyclotron resonance plasma sputtering apparatus places quartz windows for transmitting microwaves into the plasma source not in the line of sight of the target. However, the quartz windows must be replaced after some time of operation. For maintenance, the loop waveguide branching from the T-junction must be dismounted and re-assembled accurately, which is a time-consuming job. We investigated substituting the waveguide branches with two sets of coaxial cables and waveguide/coaxial cable converters to simplify assembly as far as connection and disconnection go. The resulting hybrid system worked well for the purposes of plasma generation and film deposition.

  18. Note: Easy-to-maintain electron cyclotron resonance (ECR) plasma sputtering apparatus featuring hybrid waveguide and coaxial cables for microwave delivery

    Science.gov (United States)

    Akazawa, Housei

    2016-06-01

    The branched-waveguide electron cyclotron resonance plasma sputtering apparatus places quartz windows for transmitting microwaves into the plasma source not in the line of sight of the target. However, the quartz windows must be replaced after some time of operation. For maintenance, the loop waveguide branching from the T-junction must be dismounted and re-assembled accurately, which is a time-consuming job. We investigated substituting the waveguide branches with two sets of coaxial cables and waveguide/coaxial cable converters to simplify assembly as far as connection and disconnection go. The resulting hybrid system worked well for the purposes of plasma generation and film deposition.

  19. Patterns of Limnohabitans microdiversity across a large set of freshwater habitats as revealed by reverse line blot hybridization

    Czech Academy of Sciences Publication Activity Database

    Jezbera, Jan; Jezberová, Jitka; Kasalický, Vojtěch; Šimek, Karel; Hahn, M.W.

    2013-01-01

    Roč. 8, č. 3 (2013), e58527 E-ISSN 1932-6203 R&D Projects: GA ČR(CZ) GAP504/10/0566; GA ČR(CZ) GEEEF/10/E011 Institutional support: RVO:60077344 Keywords : Limnohabitans * microdiversity * habitats * hybridization Subject RIV: DA - Hydrology ; Limnology Impact factor: 3.534, year: 2013

  20. Multi-valued logic circuits using hybrid circuit consisting of three gates single-electron transistors (TG-SETs) and MOSFETs.

    Science.gov (United States)

    Shin, SeungJun; Yu, YunSeop; Choi, JungBum

    2008-10-01

    New multi-valued logic (MVL) families using the hybrid circuits consisting of three gates single-electron transistors (TG-SETs) and a metal-oxide-semiconductor field-effect transistor (MOSFET) are proposed. The use of SETs offers periodic literal characteristics due to Coulomb oscillation of SET, which allows a realization of binary logic (BL) circuits as well as multi-valued logic (MVL) circuits. The basic operations of the proposed MVL families are successfully confirmed through SPICE circuit simulation based on the physical device model of a TG-SET. The proposed MVL circuits are found to be much faster, but much larger power consumption than a previously reported MVL, and they have a trade-off between speed and power consumption. As an example to apply the newly developed MVL families, a half-adder is introduced.

  1. A Novel Rough Set Reduct Algorithm for Medical Domain Based on Bee Colony Optimization

    OpenAIRE

    Suguna, N.; Thanushkodi, K.

    2010-01-01

    Feature selection refers to the problem of selecting relevant features which produce the most predictive outcome. In particular, feature selection task is involved in datasets containing huge number of features. Rough set theory has been one of the most successful methods used for feature selection. However, this method is still not able to find optimal subsets. This paper proposes a new feature selection method based on Rough set theory hybrid with Bee Colony Optimization (BCO) in an attempt...

  2. Novel WRM-based architecture of hybrid PON featuring online access and full-fiber-fault protection for smart grid

    Science.gov (United States)

    Li, Xingfeng; Gan, Chaoqin; Liu, Zongkang; Yan, Yuqi; Qiao, HuBao

    2018-01-01

    In this paper, a novel architecture of hybrid PON for smart grid is proposed by introducing a wavelength-routing module (WRM). By using conventional optical passive components, a WRM with M ports is designed. The symmetry and passivity of the WRM makes it be easily integrated and very cheap in practice. Via the WRM, two types of network based on different ONU-interconnected manner can realize online access. Depending on optical switches and interconnecting fibers, full-fiber-fault protection and dynamic bandwidth allocation are realized in these networks. With the help of amplitude modulation, DPSK modulation and RSOA technology, wavelength triple-reuse is achieved. By means of injecting signals into left and right branches in access ring simultaneously, the transmission delay is decreased. Finally, the performance analysis and simulation of the network verifies the feasibility of the proposed architecture.

  3. Multicriteria analysis of the hybrid systems with biogas: fuzzy set and rules; Analise multicriterio de sistemas hibridos com biogas: conjuntos e regras fuzzy

    Energy Technology Data Exchange (ETDEWEB)

    Barin, A.; Canha, L.; Abaide, A.; Magnago, K. [Federal University of Santa Maria (UFSM), RS (Brazil)], E-mail: chbarin@gmail.com; Machado, R. [Universidade de Sao Paulo (EESC/USP), Sao Carlos, SP (Brazil). Escola de Engenharia], E-mail: rquadros@sel.eesc.usp.br

    2009-07-01

    A multicriteria analysis to manage de renewable sources of energy is presented, identifying the most appropriate hybrid system to be used as distributed generation of electric energy using biogas. In this methodology, fuzzy sets and rules are defined simulated in the software MATLAB, where the main characteristics of the operation and application of hybrid systems of electric power generation are considered. The main generation system, that can use the biogas, as micro turbines and fuel cells, are evaluated. Afterwards, the systems of energy storage are analyzed: flywheel, H{sub 2} storage and conventional and redox batteries. For the development of the proposed methodology, it was considered the following criteria: efficiency, costs, technological maturity, environmental impacts, the amplitude of the system action (power range), useful life, co-generation possibility and operation temperature. A classification, by priority order, for the use of the sources and storages associated to the environment and cost scenarios is also presented.

  4. Fixed versus mixed RSA: Explaining visual representations by fixed and mixed feature sets from shallow and deep computational models.

    Science.gov (United States)

    Khaligh-Razavi, Seyed-Mahdi; Henriksson, Linda; Kay, Kendrick; Kriegeskorte, Nikolaus

    2017-02-01

    Studies of the primate visual system have begun to test a wide range of complex computational object-vision models. Realistic models have many parameters, which in practice cannot be fitted using the limited amounts of brain-activity data typically available. Task performance optimization (e.g. using backpropagation to train neural networks) provides major constraints for fitting parameters and discovering nonlinear representational features appropriate for the task (e.g. object classification). Model representations can be compared to brain representations in terms of the representational dissimilarities they predict for an image set. This method, called representational similarity analysis (RSA), enables us to test the representational feature space as is (fixed RSA) or to fit a linear transformation that mixes the nonlinear model features so as to best explain a cortical area's representational space (mixed RSA). Like voxel/population-receptive-field modelling, mixed RSA uses a training set (different stimuli) to fit one weight per model feature and response channel (voxels here), so as to best predict the response profile across images for each response channel. We analysed response patterns elicited by natural images, which were measured with functional magnetic resonance imaging (fMRI). We found that early visual areas were best accounted for by shallow models, such as a Gabor wavelet pyramid (GWP). The GWP model performed similarly with and without mixing, suggesting that the original features already approximated the representational space, obviating the need for mixing. However, a higher ventral-stream visual representation (lateral occipital region) was best explained by the higher layers of a deep convolutional network and mixing of its feature set was essential for this model to explain the representation. We suspect that mixing was essential because the convolutional network had been trained to discriminate a set of 1000 categories, whose frequencies

  5. Unsupervised Feature Subset Selection

    DEFF Research Database (Denmark)

    Søndberg-Madsen, Nicolaj; Thomsen, C.; Pena, Jose

    2003-01-01

    This paper studies filter and hybrid filter-wrapper feature subset selection for unsupervised learning (data clustering). We constrain the search for the best feature subset by scoring the dependence of every feature on the rest of the features, conjecturing that these scores discriminate some ir...... irrelevant features. We report experimental results on artificial and real data for unsupervised learning of naive Bayes models. Both the filter and hybrid approaches perform satisfactorily....

  6. Impacts of battery characteristics, driver preferences and road network features on travel costs of a plug-in hybrid electric vehicle (PHEV) for long-distance trips

    International Nuclear Information System (INIS)

    Arslan, Okan; Yıldız, Barış; Ekin Karaşan, Oya

    2014-01-01

    In a road network with refueling and fast charging stations, the minimum-cost driving path of a plug-in hybrid electric vehicle (PHEV) depends on factors such as location and availability of refueling/fast charging stations, capacity and cost of PHEV batteries, and driver tolerance towards extra mileage or additional stopping. In this paper, our focus is long-distance trips of PHEVs. We analyze the impacts of battery characteristics, often-overlooked driver preferences and road network features on PHEV travel costs for long-distance trips and compare the results with hybrid electric and conventional vehicles. We investigate the significance of these factors and derive critical managerial insights for shaping the future investment decisions about PHEVs and their infrastructure. In particular, our findings suggest that with a certain level of deployment of fast charging stations, well established cost and emission benefits of PHEVs for the short range trips can be extended to long distance. Drivers' stopping intolerance may hamper these benefits; however, increasing battery capacity may help overcome the adverse effects of this intolerance. - Highlights: • We investigate the travel costs of CVs, HEVs and PHEVs for long-distance trips. • We analyze the impacts of battery, driver and road network characteristics on the costs. • We provide critical managerial insights to shape the investment decisions about PHEVs. • Drivers' stopping intolerance may hamper the cost and emission benefits of PHEVs. • Negative effect of intolerance on cost may be overcome by battery capacity expansion

  7. Estimation of minimum sample size for identification of the most important features: a case study providing a qualitative B2B sales data set

    Directory of Open Access Journals (Sweden)

    Marko Bohanec

    2017-01-01

    Full Text Available An important task in machine learning is to reduce data set dimensionality, which in turn contributes to reducing computational load and data collection costs, while improving human understanding and interpretation of models. We introduce an operational guideline for determining the minimum number of instances sufficient to identify correct ranks of features with the highest impact. We conduct tests based on qualitative B2B sales forecasting data. The results show that a relatively small instance subset is sufficient for identifying the most important features when rank is not important.

  8. COMPARISON OF A HEAD MOUNTED IMPACT MEASUREMENT DEVICE TO THE HYBRID III ANTHROPOMORPHIC TESTING DEVICE IN A CONTROLLED LABORATORY SETTING.

    Science.gov (United States)

    Schussler, Eric; Stark, David; Bolte, John H; Kang, Yun Seok; Onate, James A

    2017-08-01

    Reports estimate that 1.6 to 3.8 million cases of concussion occur in sports and recreation each year in the United States. Despite continued efforts to reduce the occurrence of concussion, the rate of diagnosis continues to increase. The mechanisms of concussion are thought to involve linear and rotational head accelerations and velocities. One method of quantifying the kinematics experienced during sport participation is to place measurement devices into the athlete's helmet or directly on the athlete's head. The purpose of this research to determine the accuracy of a head mounted device for measuring the head accelerations experienced by the wearer. This will be accomplished by identifying the error in Peak Linear Acceleration (PLA), Peak Rotational Acceleration (PRA) and Peak Rotational Velocity (PRV) of the device. Laboratory study. A helmeted Hybrid III 50th percentile male headform was impacted via a pneumatic ram from the front, side, rear, front oblique and rear oblique at speeds from 1.5 to 5 m/s. The X2 Biosystems xPatch® (Seattle, WA) sensor was placed on the headform's right side at the approximate location of the mastoid process. Measures of PLA, PRA, PRV from the xPatch ® and Hybrid III were analyzed for Root Mean Square Error (RMSE), and Absolute and Relative Error (AE, RE). Seventy-six impacts were analyzed. All measures of correlation, fixed through the origin, were found to be strong: PLA R 2 =0.967 pstandard yet above the average error of testing devices in both PLA and PRA, but a low error in PRV. PLA measures from the xPatch® system demonstrated a high level of correlation with the PLA data from the Hybrid III mounted data collection system. 3.

  9. Hybridization between multi-objective genetic algorithm and support vector machine for feature selection in walker-assisted gait.

    Science.gov (United States)

    Martins, Maria; Costa, Lino; Frizera, Anselmo; Ceres, Ramón; Santos, Cristina

    2014-03-01

    Walker devices are often prescribed incorrectly to patients, leading to the increase of dissatisfaction and occurrence of several problems, such as, discomfort and pain. Thus, it is necessary to objectively evaluate the effects that assisted gait can have on the gait patterns of walker users, comparatively to a non-assisted gait. A gait analysis, focusing on spatiotemporal and kinematics parameters, will be issued for this purpose. However, gait analysis yields redundant information that often is difficult to interpret. This study addresses the problem of selecting the most relevant gait features required to differentiate between assisted and non-assisted gait. For that purpose, it is presented an efficient approach that combines evolutionary techniques, based on genetic algorithms, and support vector machine algorithms, to discriminate differences between assisted and non-assisted gait with a walker with forearm supports. For comparison purposes, other classification algorithms are verified. Results with healthy subjects show that the main differences are characterized by balance and joints excursion in the sagittal plane. These results, confirmed by clinical evidence, allow concluding that this technique is an efficient feature selection approach. Copyright © 2013 Elsevier Ireland Ltd. All rights reserved.

  10. Estimation of minimum sample size for identification of the most important features: a case study providing a qualitative B2B sales data set

    OpenAIRE

    Marko Bohanec; Mirjana Kljajić Borštnar; Marko Robnik-Šikonja

    2017-01-01

    An important task in machine learning is to reduce data set dimensionality, which in turn contributes to reducing computational load and data collection costs, while improving human understanding and interpretation of models. We introduce an operational guideline for determining the minimum number of instances sufficient to identify correct ranks of features with the highest impact. We conduct tests based on qualitative B2B sales forecasting data. The results show that a relatively small inst...

  11. Research and Application of Hybrid Forecasting Model Based on an Optimal Feature Selection System—A Case Study on Electrical Load Forecasting

    Directory of Open Access Journals (Sweden)

    Yunxuan Dong

    2017-04-01

    Full Text Available The process of modernizing smart grid prominently increases the complexity and uncertainty in scheduling and operation of power systems, and, in order to develop a more reliable, flexible, efficient and resilient grid, electrical load forecasting is not only an important key but is still a difficult and challenging task as well. In this paper, a short-term electrical load forecasting model, with a unit for feature learning named Pyramid System and recurrent neural networks, has been developed and it can effectively promote the stability and security of the power grid. Nine types of methods for feature learning are compared in this work to select the best one for learning target, and two criteria have been employed to evaluate the accuracy of the prediction intervals. Furthermore, an electrical load forecasting method based on recurrent neural networks has been formed to achieve the relational diagram of historical data, and, to be specific, the proposed techniques are applied to electrical load forecasting using the data collected from New South Wales, Australia. The simulation results show that the proposed hybrid models can not only satisfactorily approximate the actual value but they are also able to be effective tools in the planning of smart grids.

  12. Hybrid reactors

    International Nuclear Information System (INIS)

    Moir, R.W.

    1980-01-01

    The rationale for hybrid fusion-fission reactors is the production of fissile fuel for fission reactors. A new class of reactor, the fission-suppressed hybrid promises unusually good safety features as well as the ability to support 25 light-water reactors of the same nuclear power rating, or even more high-conversion-ratio reactors such as the heavy-water type. One 4000-MW nuclear hybrid can produce 7200 kg of 233 U per year. To obtain good economics, injector efficiency times plasma gain (eta/sub i/Q) should be greater than 2, the wall load should be greater than 1 MW.m -2 , and the hybrid should cost less than 6 times the cost of a light-water reactor. Introduction rates for the fission-suppressed hybrid are usually rapid

  13. Predicting High or Low Transfer Efficiency of Photovoltaic Systems Using a Novel Hybrid Methodology Combining Rough Set Theory, Data Envelopment Analysis and Genetic Programming

    Directory of Open Access Journals (Sweden)

    Lee-Ing Tong

    2012-02-01

    Full Text Available Solar energy has become an important energy source in recent years as it generates less pollution than other energies. A photovoltaic (PV system, which typically has many components, converts solar energy into electrical energy. With the development of advanced engineering technologies, the transfer efficiency of a PV system has been increased from low to high. The combination of components in a PV system influences its transfer efficiency. Therefore, when predicting the transfer efficiency of a PV system, one must consider the relationship among system components. This work accurately predicts whether transfer efficiency of a PV system is high or low using a novel hybrid model that combines rough set theory (RST, data envelopment analysis (DEA, and genetic programming (GP. Finally, real data-set are utilized to demonstrate the accuracy of the proposed method.

  14. Structural features of the adsorption layer of pentacene on the graphite surface and the PMMA/graphite hybrid surface

    Science.gov (United States)

    Fadeeva, A. I.; Gorbunov, V. A.; Litunenko, T. A.

    2017-08-01

    Using the molecular dynamics and the Monte Carlo methods, we have studied the structural features and growth mechanism of the pentacene film on graphite and polymethylmethacrylate /graphite surfaces. Monolayer capacity and molecular area, optimal angles between the pentacene molecules and graphite and PMMA/graphite surfaces as well as the characteristic angles between the neighboring pentacene molecules in the adsorption layer were estimated. It is shown that the orientation of the pentacene molecules in the film is determined by a number of factors, including the surface concentration of the molecules, relief of the surface, presence or absence of the polymer layer and its thickness. The pentacene molecules adsorbed on the graphite surface keep a horizontal position relative to the long axis at any surface coverage/thickness of the film. In the presence of the PMMA layer on the graphite, the increase of the number of pentacene molecules as well as the thickness of the PMMA layer induce the change of molecular orientation from predominantly horizontal to vertical one. The reason for such behavior is supposed to be the roughness of the PMMA surface.

  15. Sigmoid stenosis caused by diverticulitis vs. carcinoma: usefulness of sonographic features for their differentiation in the emergency setting.

    Science.gov (United States)

    Ripollés, Tomás; Martínez-Pérez, María Jesús; Gómez Valencia, Diana Patricia; Vizuete, José; Martín, Gregorio

    2015-10-01

    To retrospectively evaluate the accuracy of ultrasound as a diagnostic method for differentiating acute diverticulitis from colon cancer in patients with sigmoid colon stenosis. Ultrasound examinations of 91 consecutive patients with sigmoid stenosis (50 diverticulitis and 41 colon cancers) were reviewed by two trained radiologists. Sixty-five (71%) patients presented with acute abdominal symptoms. Thirteen sonographic criteria retrieved from the literature were evaluated to differentiate benign from malignant strictures. A score including all parameters which showed significant differences between benign vs. malignant was built. Sensitivity, specificity, accuracy, and positive or negative predictive values of each sonographic sign, the overall diagnosis, and sonographic score were calculated. Loss of the bowel wall stratification was the most reliable criteria for the diagnosis of malignancy (92% and 94% of sensitivity and specificity, respectively), and the best inter-radiologist agreement (κ = 0.848). Adjacent lymph nodes were the most specific feature (98%) for colon cancer, but its sensitivity was low. Global assessment could differentiate both diseases with high sensitivity (92-94.9%) and specificity (98-100%). Sonographic score >3 enabled differentiation of carcinoma from diverticulitis with 95% sensitivity and 92-94% specificity, with an area under the ROC curve of 0.98-0.987. There were no significant differences in the results between patients with acute and nonacute abdominal symptoms. The combination of several morphological sonographic findings using a score can differentiate most cases of diverticulitis from colon carcinoma in sigmoid strictures.

  16. SPECIFIC FEATURES OF PSYCHOLOGICAL CARE FOR PATIENTS WITH PULMONARY TUBERCULOSIS DURING INTENSIVE CHEMOTHERAPY (IN THE HOSPITAL SETTING

    Directory of Open Access Journals (Sweden)

    V. V. Streltsov

    2014-01-01

    Full Text Available The psychological trauma of pulmonary tuberculosis and long-term treatment may cause the development and progression of different borderline neuropsychic disorders in patients, lower therapeutic effectiveness, and prematurely discontinue therapy. The main practical tasks of psychological rehabilitation during intensive treatment are to render care for a patient during his adaptation to the hospital setting, to correct inadequate attitude towards disease, and to motivate active cooperation with specialists. Competent psychological support of drug therapy promotes a reduction in the intensity of psychic and somatic experiences in the patient and an increase in his psychological resources. A respective microclimate in the tuberculosis control facility and a patient-centered doctorpatient model should be considered as the most important rehabilitation factors.

  17. Sets of RNA repeated tags and hybridization-sensitive fluorescent probes for distinct images of RNA in a living cell.

    Directory of Open Access Journals (Sweden)

    Takeshi Kubota

    Full Text Available BACKGROUND: Imaging the behavior of RNA in a living cell is a powerful means for understanding RNA functions and acquiring spatiotemporal information in a single cell. For more distinct RNA imaging in a living cell, a more effective chemical method to fluorescently label RNA is now required. In addition, development of the technology labeling with different colors for different RNA would make it easier to analyze plural RNA strands expressing in a cell. METHODOLOGY/PRINCIPAL FINDINGS: Tag technology for RNA imaging in a living cell has been developed based on the unique chemical functions of exciton-controlled hybridization-sensitive oligonucleotide (ECHO probes. Repetitions of selected 18-nucleotide RNA tags were incorporated into the mRNA 3'-UTR. Pairs with complementary ECHO probes exhibited hybridization-sensitive fluorescence emission for the mRNA expressed in a living cell. The mRNA in a nucleus was detected clearly as fluorescent puncta, and the images of the expression of two mRNAs were obtained independently and simultaneously with two orthogonal tag-probe pairs. CONCLUSIONS/SIGNIFICANCE: A compact and repeated label has been developed for RNA imaging in a living cell, based on the photochemistry of ECHO probes. The pairs of an 18-nt RNA tag and the complementary ECHO probes are highly thermostable, sequence-specifically emissive, and orthogonal to each other. The nucleotide length necessary for one tag sequence is much shorter compared with conventional tag technologies, resulting in easy preparation of the tag sequences with a larger number of repeats for more distinct RNA imaging.

  18. Calibration sets and the accuracy of vibrational scaling factors: A case study with the X3LYP hybrid functional

    Science.gov (United States)

    Teixeira, Filipe; Melo, André; Cordeiro, M. Natália D. S.

    2010-09-01

    A linear least-squares methodology was used to determine the vibrational scaling factors for the X3LYP density functional. Uncertainties for these scaling factors were calculated according to the method devised by Irikura et al. [J. Phys. Chem. A 109, 8430 (2005)]. The calibration set was systematically partitioned according to several of its descriptors and the scaling factors for X3LYP were recalculated for each subset. The results show that the scaling factors are only significant up to the second digit, irrespective of the calibration set used. Furthermore, multivariate statistical analysis allowed us to conclude that the scaling factors and the associated uncertainties are independent of the size of the calibration set and strongly suggest the practical impossibility of obtaining vibrational scaling factors with more than two significant digits.

  19. Modified CC-LR algorithm with three diverse feature sets for motor imagery tasks classification in EEG based brain-computer interface.

    Science.gov (United States)

    Siuly; Li, Yan; Paul Wen, Peng

    2014-03-01

    Motor imagery (MI) tasks classification provides an important basis for designing brain-computer interface (BCI) systems. If the MI tasks are reliably distinguished through identifying typical patterns in electroencephalography (EEG) data, a motor disabled people could communicate with a device by composing sequences of these mental states. In our earlier study, we developed a cross-correlation based logistic regression (CC-LR) algorithm for the classification of MI tasks for BCI applications, but its performance was not satisfactory. This study develops a modified version of the CC-LR algorithm exploring a suitable feature set that can improve the performance. The modified CC-LR algorithm uses the C3 electrode channel (in the international 10-20 system) as a reference channel for the cross-correlation (CC) technique and applies three diverse feature sets separately, as the input to the logistic regression (LR) classifier. The present algorithm investigates which feature set is the best to characterize the distribution of MI tasks based EEG data. This study also provides an insight into how to select a reference channel for the CC technique with EEG signals considering the anatomical structure of the human brain. The proposed algorithm is compared with eight of the most recently reported well-known methods including the BCI III Winner algorithm. The findings of this study indicate that the modified CC-LR algorithm has potential to improve the identification performance of MI tasks in BCI systems. The results demonstrate that the proposed technique provides a classification improvement over the existing methods tested. Copyright © 2014 Elsevier Ireland Ltd. All rights reserved.

  20. Angiofibroma of soft tissue with fibrohistiocytic features and intratumor genetic heterogeneity of NCOA2 gene rearrangement revealed by chromogenic in situ hybridization: a case report.

    Science.gov (United States)

    Fukuda, Yumiko; Motoi, Toru; Kato, Ikuma; Ikegami, Masachika; Funata, Nobuaki; Ohtomo, Rie; Horiguchi, Shinichiro; Goto, Takahiro; Hishima, Tsunekazu

    2014-05-01

    Angiofibroma of soft tissue is a recently described soft tissue tumor that is characterized by fibroblastic spindle tumor cells with arborizing capillary proliferation. Cytogenetically, it harbors a specific fusion gene involving the nuclear receptor coactivator 2 (NCOA2) gene. We report here additional new pathological and cytogenetic features. A soft tissue tumor in the left thigh of 73-year-old female was investigated. Microscopically, histiocytoid tumor cells were scattered in an edematous background with branching capillary proliferation. Immunohistochemically, we identified that the tumor cells were positive for histiocytic markers such as CD68 and CD163. Rearrangement of the NCOA2 gene was detected successfully by chromogenic in situ hybridization; however, abnormal signal patterns were observed in only a small subset of tumor cells. Unlike typical tumors with bland spindle cells, the present tumor needs to be distinguished from myxoid, dendritic and clear cell tumors. This case may suggest that angiofibroma of soft tissue is not in the center of the fibroblastic/myofibroblastic tumor group, but rather shows a fibrohistiocytic nature. We also found intratumor genetic heterogeneity, which is uncommon for a translocation-associated tumor. Therefore, careful evaluation is required to detect the gene rearrangement in this tumor entity. © 2014 The Authors. Pathology International © 2014 Japanese Society of Pathology and Wiley Publishing Asia Pty Ltd.

  1. A Calibrated Test-Set for Measurement of Access-Point Time Specifications in Hybrid Wired/Wireless Industrial Communication †

    Directory of Open Access Journals (Sweden)

    Federico Tramarin

    2018-05-01

    Full Text Available In factory automation and process control systems, hybrid wired/wireless networks are often deployed to connect devices of difficult reachability such as those mounted on mobile equipment. A widespread implementation of these networks makes use of Access Points (APs to implement wireless extensions of Real-Time Ethernet (RTE networks via the IEEE 802.11 Wireless LAN (WLAN. Unfortunately, APs may introduce random delays in frame forwarding, mainly related to their internal behavior (e.g., queue management, processing times, that clearly impact the overall worst case execution time of real-time tasks involved in industrial process control systems. As a consequence, the knowledge of such delays becomes a crucial design parameter, and their estimation is definitely of utter importance. In this scenario, the paper presents an original and effective method to measure the aforementioned delays introduced by APs, exploiting a hybrid loop-back link and a simple, yet accurate set-up with moderate instrumentation requirements. The proposed method, which requires an initial calibration phase by means of a reference AP, has been successfully tested on some commercial APs to prove its effectiveness. The proposed measurement procedure is proven to be general and, as such, can be profitably adopted in even different scenarios.

  2. Implementation and importance of fluorescence in situ hybridization (fish) in paraffin tissues for categorization of B-cell lymphoma unclassifiable, with features intermediate between Burkitt lymphoma and diffuse large B-cell lymphoma

    International Nuclear Information System (INIS)

    Carvajal Cuenca, Alejandra

    2011-01-01

    The diagnostic criteria have been defined based on the tools that the country has acquired and international guidelines for pure entities: the LB, LDCGB, and the new entity of B lymphoma unclassifiable with features intermediate LDCGB and LB. The fluorescence in situ hybridization for the translocation (8;14) has been implemented in paraffin tissues for proper categorization. A total of 21 cases have been studied: the characteristics of patients, morphology, immunohistochemistry and the presence or absence of the translocation (8;14). Twelve of the cases have been classified as B-cell lymphoma unclassifiable with features intermediate between LDCGB and LB. Furthermore, nine of the cases were classified in LB. Fluorescence in situ hybridization (FISH) has been negative in 5 of the 21 cases. The diagnosis of lymphoma with features bordering between the LB and the LDCGB has been imperative for the survival of the patient and the corresponding treatment [es

  3. Evaluation of Mayer-Rokitansky-Kuester-Hauser syndrome with magnetic resonance imaging: Three patterns of uterine remnants and related anatomical features and clinical settings

    Energy Technology Data Exchange (ETDEWEB)

    Wang, Yue; Lu, Jingjing; Jiang, Bo; Feng, Feng; Jin, Zhengyu [Peking Union Medical College, Chinese Academy of Medical Sciences, Department of Radiology, Peking Union Medical College Hospital, Beijing (China); Zhu, Lan; Sun, Zhijing [Chinese Academy of Medical Sciences, Department of Obstetrics and Gynaecology, Peking Union Medical College Hospital, Peking Union Medical College, Bejing (China)

    2017-12-15

    To characterize the anatomical features and clinical settings of Mayer-Rokitansky-Kuester-Hauser (MRKH) syndrome and correlate them with patterns of uterine involvement. Pelvic magnetic resonance images and medical records of 92 MRKH patients were retrospectively reviewed. Patients were subgrouped by uterine morphology: uterine agenesis, unilateral rudimentary uterus and bilateral rudimentary uteri. Uterine volume, presence of endometrium, location of ovary, endometriosis and pelvic pain were compared among groups. The mean uterine volume was 33.5 ml (17.5-90.0 ml) for unilateral uterine remnants, and 16.1 ml (3.5-21.5 ml) for bilateral uterine rudiments (p<0.01). The incidence of presence of endometrium (100% vs. 22%, p<0.001), haematometra (56% vs. 3%, p<0.001) and ovarian endometriosis (22% vs. 3%, p<0.01) was significantly increased in the group of unilateral rudimentary uteri as compared with the group of bilateral uterine remnants. Thirty-one patients (38%) showed ectopic ovaries. Pelvic pain was more common in individuals with unilateral rudimentary uterus than those who had no (56% vs. 5%, p<0.01) or bilateral uterine remnants (56% vs. 14%, p<0.05). MRKH patients with different patterns of uterine involvement may have differentiated anatomical features and clinical settings. (orig.)

  4. Classification of breast masses in ultrasound images using self-adaptive differential evolution extreme learning machine and rough set feature selection.

    Science.gov (United States)

    Prabusankarlal, Kadayanallur Mahadevan; Thirumoorthy, Palanisamy; Manavalan, Radhakrishnan

    2017-04-01

    A method using rough set feature selection and extreme learning machine (ELM) whose learning strategy and hidden node parameters are optimized by self-adaptive differential evolution (SaDE) algorithm for classification of breast masses is investigated. A pathologically proven database of 140 breast ultrasound images, including 80 benign and 60 malignant, is used for this study. A fast nonlocal means algorithm is applied for speckle noise removal, and multiresolution analysis of undecimated discrete wavelet transform is used for accurate segmentation of breast lesions. A total of 34 features, including 29 textural and five morphological, are applied to a [Formula: see text]-fold cross-validation scheme, in which more relevant features are selected by quick-reduct algorithm, and the breast masses are discriminated into benign or malignant using SaDE-ELM classifier. The diagnosis accuracy of the system is assessed using parameters, such as accuracy (Ac), sensitivity (Se), specificity (Sp), positive predictive value (PPV), negative predictive value (NPV), Matthew's correlation coefficient (MCC), and area ([Formula: see text]) under receiver operating characteristics curve. The performance of the proposed system is also compared with other classifiers, such as support vector machine and ELM. The results indicated that the proposed SaDE algorithm has superior performance with [Formula: see text], [Formula: see text], [Formula: see text], [Formula: see text], [Formula: see text], [Formula: see text], and [Formula: see text] compared to other classifiers.

  5. Feature Sets for Screenshot Detection

    Science.gov (United States)

    2013-06-01

    containing screenshots of computer programs as part of their instructions. Additionally, web browsers such as Firefox capture and cache screenshots of user...provide indications as to the class of image. At an even higher level, there is often distinguishing metadata associated with digital images. Mac’s OS X...mac os x malware discovered, takes screenshots and uploads them to unknown servers without user’s consent. [Online]. Available: http

  6. Development of Feature Set, Classification Implementation and Applications for Vowel Migration/Modification in Sung Filipino (Tagalog Texts and Perceived Intelligibility

    Directory of Open Access Journals (Sweden)

    Virginia B. Bustos

    2009-12-01

    Full Text Available With the emergence of research on real-time visual feedback to supplement vocal pedagogy, the utilization of technology in the world of music is now seen to accelerate skills learning and enhance cognitive development. The researchers of this project aim to further analyze vowel intelligibility and develop software applications intended to be used not only by professional singers but also by individuals who wish to improve their singing capability. Data in the form of sung vowels and song pieces were obtained from 46 singers. A Listening Test was then conducted on these samples to obtain the ground truth for vowel classification based on human perception. Simulation of the human auditory perception of sung Filipino vowels was performed using formant frequencies and Mel-frequency cepstral coefficients as feature vector inputs to a two-stage Discriminant Analysis classifier. The setup resulted in an over-all Training Set accuracy of 89.4% and an over-all Test Set accuracy of 90.9%. The accuracy of the classifier, measured in terms of the correspondence of vowel classifications obtained from the classifier with the results of the Listening Test, reached 92.3%. Using information obtained from the classifier, offline and online/real-time software applications were developed. The main application features include the display of the spectral envelope and spectrogram, pitch and vibrato analysis and direct feedback on the classification of the sung vowel. These features were recommended by singers who were surveyed and were incorporated in the applications to aid singers to adjust formant locations, directly determine listener’s perception of sung vowels, perform modeling effectively and carry out vowel migration.

  7. A level set methodology for predicting the effect of mask wear on surface evolution of features in abrasive jet micro-machining

    International Nuclear Information System (INIS)

    Burzynski, T; Papini, M

    2012-01-01

    A previous implementation of narrow-band level set methodology developed by the authors was extended to allow for the modelling of mask erosive wear in abrasive jet micro-machining (AJM). The model permits the prediction of the surface evolution of both the mask and the target simultaneously, by representing them as a hybrid and continuous mask–target surface. The model also accounts for the change in abrasive mass flux incident to both the target surface and, for the first time, the eroding mask edge, that is brought about by the presence of the mask edge itself. The predictions of the channel surface and eroded mask profiles were compared with measurements on channels machined in both glass and poly-methyl-methacrylate (PMMA) targets at both normal and oblique incidence, using tempered steel and elastomeric masks. A much better agreement between the predicted and measured profiles was found when mask wear was taken into account. Mask wear generally resulted in wider and deeper glass target profiles and wider PMMA target profiles, respectively, when compared to cases where no mask wear was present. This work has important implications for the AJM of complex MEMS and microfluidic devices that require longer machining times. (paper)

  8. An enhanced feature set for pattern recognition based contrast enhancement of contact-less captured latent fingerprints in digitized crime scene forensics

    Science.gov (United States)

    Hildebrandt, Mario; Kiltz, Stefan; Dittmann, Jana; Vielhauer, Claus

    2014-02-01

    In crime scene forensics latent fingerprints are found on various substrates. Nowadays primarily physical or chemical preprocessing techniques are applied for enhancing the visibility of the fingerprint trace. In order to avoid altering the trace it has been shown that contact-less sensors offer a non-destructive acquisition approach. Here, the exploitation of fingerprint or substrate properties and the utilization of signal processing techniques are an essential requirement to enhance the fingerprint visibility. However, especially the optimal sensory is often substrate-dependent. An enhanced generic pattern recognition based contrast enhancement approach for scans of a chromatic white light sensor is introduced in Hildebrandt et al.1 using statistical, structural and Benford's law2 features for blocks of 50 micron. This approach achieves very good results for latent fingerprints on cooperative, non-textured, smooth substrates. However, on textured and structured substrates the error rates are very high and the approach thus unsuitable for forensic use cases. We propose the extension of the feature set with semantic features derived from known Gabor filter based exemplar fingerprint enhancement techniques by suggesting an Epsilon-neighborhood of each block in order to achieve an improved accuracy (called fingerprint ridge orientation semantics). Furthermore, we use rotation invariant Hu moments as an extension of the structural features and two additional preprocessing methods (separate X- and Y Sobel operators). This results in a 408-dimensional feature space. In our experiments we investigate and report the recognition accuracy for eight substrates, each with ten latent fingerprints: white furniture surface, veneered plywood, brushed stainless steel, aluminum foil, "Golden-Oak" veneer, non-metallic matte car body finish, metallic car body finish and blued metal. In comparison to Hildebrandt et al.,1 our evaluation shows a significant reduction of the error rates

  9. Major difference in visible-light photocatalytic features between perfect and self-defective Ta3N5 materials: A screened coulomb hybrid dft investigation

    KAUST Repository

    Harb, Moussab

    2014-09-11

    Relevant properties to visible-light overall water splitting reactions of perfect and self-defective bulk Ta3N5 semiconductor photocatalysts are investigated using accurate first-principles quantum calculations on the basis of density functional theory (DFT, including the perturbation theory DFPT) within the screened coulomb hybrid (HSE06) exchange-correlation formalism. Among the various explored self-defective structures, a strong stabilization is obtained for the configuration displaying a direct interaction between the created N- and Ta-vacancies. In the lowest-energy structure, each of the three created Ta-vacancies and the five created N-vacancies is found to be in aggregated disposition, leading to the formation of cages into the lattice. Although the calculated structural, electronic, and optical properties of the two materials are found to be very similar and in good agreement with available experimental works, their photocatalytic features for visible-light overall water splitting reactions show completely different behaviors. On the basis of calculated band edge positions relative to water redox potentials, the perfect Ta3N5 (calculated band gap of 2.2 eV) is predicted by HSE06 to be a good candidate only for H+ reduction while the self-defective Ta3N5 (calculated band gap of 2.0 eV) reveals suitable band positions for both water oxidation and H+ reduction similar to the experimental data reported on Ta3N5 powders. Its ability to reduce H+ is predicted to be lower than the perfect one. However, the strongly localized electronic characters of the valence band (VB) and conduction band (CB) edge states of the self-defective material only on the N 2p and Ta 5d orbitals surrounding the aggregated N- and Ta-vacancies are expected to strongly limit the probability of photogenerated carrier mobility through its crystal structure.

  10. Characterization of mature maize (Zea mays L.) root system architecture and complexity in a diverse set of Ex-PVP inbreds and hybrids.

    Science.gov (United States)

    Hauck, Andrew L; Novais, Joana; Grift, Tony E; Bohn, Martin O

    2015-01-01

    The mature root system is a vital plant organ, which is critical to plant performance. Commercial maize (Zea mays L.) breeding has resulted in a steady increase in plant performance over time, along with noticeable changes in above ground vegetative traits, but the corresponding changes in the root system are not presently known. In this study, roughly 2500 core root systems from field trials of a set of 10 diverse elite inbreds formerly protected by Plant Variety Protection plus B73 and Mo17 and the 66 diallel intercrosses among them were evaluated for root traits using high throughput image-based phenotyping. Overall root architecture was modeled by root angle (RA) and stem diameter (SD), while root complexity, the amount of root branching, was quantified using fractal analysis to obtain values for fractal dimension (FD) and fractal abundance (FA). For each trait, per se line effects were highly significant and the most important contributor to trait performance. Mid-parent heterosis and specific combining ability was also highly significant for FD, FA, and RA, while none of the traits showed significant general combining ability. The interaction between the environment and the additive line effect was also significant for all traits. Within the inbred and hybrid generations, FD and FA were highly correlated (rp ≥ 0.74), SD was moderately correlated to FD and FA (0.69 ≥ rp ≥ 0.48), while the correlation between RA and other traits was low (0.13 ≥ rp ≥ -0.40). Inbreds with contrasting effects on complexity and architecture traits were observed, suggesting that root complexity and architecture traits are inherited independently. A more comprehensive understanding of the maize root system and the way it interacts with the environment will be useful for defining adaptation to nutrient acquisition and tolerance to stress from drought and high plant densities, critical factors in the yield gains of modern hybrids.

  11. Major difference in visible-light photocatalytic features between perfect and self-defective Ta3N5 materials: A screened coulomb hybrid dft investigation

    KAUST Repository

    Harb, Moussab; Cavallo, Luigi; Basset, Jean-Marie

    2014-01-01

    theory (DFT, including the perturbation theory DFPT) within the screened coulomb hybrid (HSE06) exchange-correlation formalism. Among the various explored self-defective structures, a strong stabilization is obtained for the configuration displaying a

  12. Hybrid quantum information processing

    Energy Technology Data Exchange (ETDEWEB)

    Furusawa, Akira [Department of Applied Physics, School of Engineering, The University of Tokyo (Japan)

    2014-12-04

    I will briefly explain the definition and advantage of hybrid quantum information processing, which is hybridization of qubit and continuous-variable technologies. The final goal would be realization of universal gate sets both for qubit and continuous-variable quantum information processing with the hybrid technologies. For that purpose, qubit teleportation with a continuousvariable teleporter is one of the most important ingredients.

  13. BREEDING OF F1 HYBRIDS OF PUMPKIN FOR CANNING INDUSTRY

    Directory of Open Access Journals (Sweden)

    A. M. Shantasov

    2016-01-01

    Full Text Available As a result of crossing with patty pan squash with male sterility, the new parent lines of Cucurbita реро L., «ANZH» and «ANZ», with the original set of morphological traits («kabakson» based on the gene of male sterility of functional type were developed. The F1 hybrids with economically valuable features were obtained. These hybrids are characterized by small fruits of pickling types, high yield and biochemical content.

  14. Road and Street Centerlines, Street-The data set is a line feature consisting of 13948 line segments representing streets. It was created to maintain the location of city and county based streets., Published in 1989, Davis County Government.

    Data.gov (United States)

    NSGIC Local Govt | GIS Inventory — Road and Street Centerlines dataset current as of 1989. Street-The data set is a line feature consisting of 13948 line segments representing streets. It was created...

  15. Techno-economic analysis of a wind-solar hybrid renewable energy system with rainwater collection feature for urban high-rise application

    International Nuclear Information System (INIS)

    Chong, W.T.; Naghavi, M.S.; Poh, S.C.; Mahlia, T.M.I.; Pan, K.C.

    2011-01-01

    Graphical abstract: This wind-solar hybrid renewable energy system is a new concept of the utilization, integration and optimization of existing renewable energy and rain water harvesting technologies. It is compact and can be built on the top of high rise buildings to provide on-site green power to that building or feed into the grid line. This system utilizes the advantages of Malaysian climate, i.e. high solar radiation and rainfall for green energy generation and free water supply. It also overcomes the inferior aspect on the low wind speed by guiding and increasing the speed of the high altitude free-stream wind from all directions radially through power-augmentation-guide-vane (PAGV) before entering the wind turbine at center portion. The PAGV is an innovative design used to guide and create venturi effect to increase the wind speed before the wind-stream enters wind turbine. The system must also be designed to provide optimum surface area for solar panel (solar thermal or photovoltaic or solar PV/T)) installation and battery compartment for power storage. In addition; rain water collection feature must be built-into the system design. The system is recommended to be sited on the top of high rise buildings or structures with its appearance or outer design can be blended into the building architecture without negative visual impact. With this system, the size of wind turbine can be reduced for a given power output and the noise is also reduced since it is contained in the PAGV. The design is also safer and suitable to be used in populated area. Mesh can be mounted at the entrance of the PAGV to prevent the bird-strike. This system can eliminate or minimize the current problems concerning public acceptance of wind energy, i.e. poor starting behavior in low wind speed, noise, visual impact, electromagnetic interference, safety and environmental factors. Highlights: → This wind, solar and rain harvester integrates existing renewable energy and rain water

  16. Assessment of topoisomerase II-alpha gene status by dual color chromogenic in situ hybridization in a set of Iraqi patients with invasive breast carcinoma

    Directory of Open Access Journals (Sweden)

    Rasha Abd Alraouf Neama

    2017-01-01

    Full Text Available Background: The human epidermal growth factor receptor 2(HER2 proto-oncogene is overexpressed or amplified in approximately 15%–25% of invasive breast cancers. Approximately 35% of HER2-amplified breast cancers have coamplification of the topoisomerase II-alpha (TOP2A gene encoding an enzyme that is a major target of anthracyclines. Hence, the determination of genetic alteration (amplification or deletion of both genes is considered as an important predictive factor that determines the response of breast cancer patients to treatment. The aims of this study are to determinate TOP2A status gene amplification in a set of Iraqi patients with breast cancer that have had an equivocal (2+ and positive HER2/neu by immunohistochemistry (IHC and to compare the results with estrogen receptor (ER and progesterone receptor (PR and HER2/neu status. Patients and Methods: A cross-sectional prospective study done on 53 patients with invasive breast carcinoma. Twenty-six out of total 53 cases were positive HER2/neu (3+, the remaining 27 equivocal HER2-IHC (2+ cases reanalyzed using dual-color chromogenic in situ hybridization (ZytoVision probe kit for further identification of HER2/neu gene amplification. Using chromogenic in situ hybridization (CISH, TOP2A gene status determination was done for all cases. Results: There is a direct significant correlation between TOP2A gene amplification and HER2/neu positivity, P < 0.05 in that 15 (39.4% out of 38 positive HER2/neu cases were associated with topoisomerase gene amplification. Regarding relation of topoisomerase gene to hormone receptor status (ER and PR, there was a significant negative relationship between the gene and ER receptor status. The higher level of gene amplification was noticed in ER and PR negative cases in about 13 (43.3% and 14 (48.2% for ER and PR, respectively. Conclusion: TOP2A gene status has a significantly positive correlation with HER2/neu status while it has a significantly negative

  17. Modélisation du procédé de soudage hybride Arc / Laser par une approche level set application aux toles d'aciers de fortes épaisseurs A level-set approach for the modelling of hybrid arc/laser welding process application for high thickness steel sheets joining

    Directory of Open Access Journals (Sweden)

    Desmaison Olivier

    2013-11-01

    Full Text Available Le procédé de soudage hybride Arc/Laser est une solution aux assemblages difficiles de tôles de fortes épaisseurs. Ce procédé innovant associe deux sources de chaleur : un arc électrique produit par une torche MIG et une source laser placée en amont. Ce couplage améliore le rendement du procédé, la qualité du cordon et les déformations finales. La modélisation de ce procédé par une approche Level Set permet une prédiction du développement du cordon et du champ de température associé. La simulation du soudage multi-passes d'une nuance d'acier 18MnNiMo5 est présentée ici et les résultats sont comparés aux observations expérimentales. The hybrid arc/laser welding process has been developed in order to overcome the difficulties encountered for joining high thickness steel sheets. This innovative process gathers two heat sources: an arc source developed by a MIG torch and a pre-located laser source. This coupling improves the efficiency of the process, the weld bead quality and the final deformations. The Level-Set approach for the modelling of this process enables the prediction of the weld bead development and the temperature field evolution. The simulation of the multi-passes welding of a 18MnNiMo5 steel grade is detailed and the results are compared to the experimental observations.

  18. [Features of interaction bacterial strains Micrococcus luteus LBK1 from plants varieties/hybrids cucumber and sweet pepper and with fungus Fusarium oxysporum Scelecht].

    Science.gov (United States)

    Parfeniuk, A; Sterlikova, O; Beznosko, I; Krut', V

    2014-01-01

    The article presents the results of studying the impact of bacterial strain M. luteus LBK1, stimulating the growth and development of plant varieties/hybrids of cucumber and sweet pepper on the intensity of sporulation of the fungus F. oxysporum Scelecht--fusariose rot pathogen.

  19. Hybride textuelle Strukturen und hybride textuelle Einheiten. Ein ...

    African Journals Online (AJOL)

    carrying set of all hybrid hierarchical structures are element-heterogeneous whilst the structure- carrying set of all ... grams of hierarchical hybrid article structures, the nodes for those text segments that establish the hybrid status of .... der; d ∈ ArtA ⊣ G|WAr (= Artikelangabe, anhand derer das Genus (= G) und zugleich die ...

  20. Computing all hybridization networks for multiple binary phylogenetic input trees.

    Science.gov (United States)

    Albrecht, Benjamin

    2015-07-30

    The computation of phylogenetic trees on the same set of species that are based on different orthologous genes can lead to incongruent trees. One possible explanation for this behavior are interspecific hybridization events recombining genes of different species. An important approach to analyze such events is the computation of hybridization networks. This work presents the first algorithm computing the hybridization number as well as a set of representative hybridization networks for multiple binary phylogenetic input trees on the same set of taxa. To improve its practical runtime, we show how this algorithm can be parallelized. Moreover, we demonstrate the efficiency of the software Hybroscale, containing an implementation of our algorithm, by comparing it to PIRNv2.0, which is so far the best available software computing the exact hybridization number for multiple binary phylogenetic trees on the same set of taxa. The algorithm is part of the software Hybroscale, which was developed specifically for the investigation of hybridization networks including their computation and visualization. Hybroscale is freely available(1) and runs on all three major operating systems. Our simulation study indicates that our approach is on average 100 times faster than PIRNv2.0. Moreover, we show how Hybroscale improves the interpretation of the reported hybridization networks by adding certain features to its graphical representation.

  1. Automated hybrid closed-loop control with a proportional-integral-derivative based system in adolescents and adults with type 1 diabetes: individualizing settings for optimal performance.

    Science.gov (United States)

    Ly, Trang T; Weinzimer, Stuart A; Maahs, David M; Sherr, Jennifer L; Roy, Anirban; Grosman, Benyamin; Cantwell, Martin; Kurtz, Natalie; Carria, Lori; Messer, Laurel; von Eyben, Rie; Buckingham, Bruce A

    2017-08-01

    Automated insulin delivery systems, utilizing a control algorithm to dose insulin based upon subcutaneous continuous glucose sensor values and insulin pump therapy, will soon be available for commercial use. The objective of this study was to determine the preliminary safety and efficacy of initialization parameters with the Medtronic hybrid closed-loop controller by comparing percentage of time in range, 70-180 mg/dL (3.9-10 mmol/L), mean glucose values, as well as percentage of time above and below target range between sensor-augmented pump therapy and hybrid closed-loop, in adults and adolescents with type 1 diabetes. We studied an initial cohort of 9 adults followed by a second cohort of 15 adolescents, using the Medtronic hybrid closed-loop system with the proportional-integral-derivative with insulin feed-back (PID-IFB) algorithm. Hybrid closed-loop was tested in supervised hotel-based studies over 4-5 days. The overall mean percentage of time in range (70-180 mg/dL, 3.9-10 mmol/L) during hybrid closed-loop was 71.8% in the adult cohort and 69.8% in the adolescent cohort. The overall percentage of time spent under 70 mg/dL (3.9 mmol/L) was 2.0% in the adult cohort and 2.5% in the adolescent cohort. Mean glucose values were 152 mg/dL (8.4 mmol/L) in the adult cohort and 153 mg/dL (8.5 mmol/L) in the adolescent cohort. Closed-loop control using the Medtronic hybrid closed-loop system enables adaptive, real-time basal rate modulation. Initializing hybrid closed-loop in clinical practice will involve individualizing initiation parameters to optimize overall glucose control. © 2016 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.

  2. Efficient design and simulation of an expandable hybrid (wind-photovoltaic) power system with MPPT and inverter input voltage regulation features in compliance with electric grid requirements

    Energy Technology Data Exchange (ETDEWEB)

    Skretas, Sotirios B.; Papadopoulos, Demetrios P. [Electrical Machines Laboratory, Department of Electrical and Computer Engineering, Democritos University of Thrace (DUTH), 12 V. Sofias, 67100 Xanthi (Greece)

    2009-09-15

    In this paper an efficient design along with modeling and simulation of a transformer-less small-scale centralized DC - bus Grid Connected Hybrid (Wind-PV) power system for supplying electric power to a single phase of a three phase low voltage (LV) strong distribution grid are proposed and presented. The main components of the hybrid system are: a PV generator (PVG); and an array of horizontal-axis, fixed-pitch, small-size, variable-speed wind turbines (WTs) with direct-driven permanent magnet synchronous generator (PMSG) having an embedded uncontrolled bridge rectifier. An overview of the basic theory of such systems along with their modeling and simulation via Simulink/MATLAB software package are presented. An intelligent control method is applied to the proposed configuration to simultaneously achieve three desired goals: to extract maximum power from each hybrid power system component (PVG and WTs); to guarantee DC voltage regulation/stabilization at the input of the inverter; to transfer the total produced electric power to the electric grid, while fulfilling all necessary interconnection requirements. Finally, a practical case study is conducted for the purpose of fully evaluating a possible installation in a city site of Xanthi/Greece, and the practical results of the simulations are presented. (author)

  3. PDMS-SiO{sub 2}-TiO{sub 2}-CaO hybrid materials – Cytocompatibility and nanoscale surface features

    Energy Technology Data Exchange (ETDEWEB)

    Almeida, J. Carlos [CICECO - Aveiro Institute of Materials, Department of Materials and Ceramic Engineering, University of Aveiro, 3810-193 Aveiro (Portugal); Wacha, András [Research Centre for Natural Sciences, Hungarian Academy of Sciences, Magyar Tudósok körútja 2, Budapest 1117 (Hungary); Gomes, Pedro S.; Fernandes, M. Helena R. [Laboratory for Bone Metabolism and Regeneration, Faculdade de Medicina Dentária, Universidade do Porto (Portugal); Fernandes, M. Helena Vaz [CICECO - Aveiro Institute of Materials, Department of Materials and Ceramic Engineering, University of Aveiro, 3810-193 Aveiro (Portugal); Salvado, Isabel M. Miranda, E-mail: isabelmsalvado@ua.pt [CICECO - Aveiro Institute of Materials, Department of Materials and Ceramic Engineering, University of Aveiro, 3810-193 Aveiro (Portugal)

    2016-07-01

    Two PDMS-SiO{sub 2}-TiO{sub 2}-CaO porous hybrid materials were prepared using the same base composition, precursors, and solvents, but following two different sol-gel procedures, based on the authors' previous works where for the first time, in this hybrid system, calcium acetate was used as calcium source. The two different procedures resulted in monolithic materials with different structures, microstructures, and surface wettability. Even though both are highly hydrophobic (contact angles of 127.2° and 150.6°), and present different filling regimes due to different surface topographies, they have demonstrated to be cytocompatible when tested with human osteoblastic cells, against the accepted idea that high-hydrophobic surfaces are not suitable to cell adhesion and proliferation. At the nanoscale, the existence of hydrophilic silica domains containing calcium, where water molecules are physisorbed, is assumed to support this capability, as discussed. - Highlights: • Two hybrid materials were prepared following two different sol-gel procedures. • Both are highly hydrophobic but demonstrated to be cytocompatible. • Different filling regimes were observed.

  4. Hybrid mimics and hybrid vigor in Arabidopsis

    Science.gov (United States)

    Wang, Li; Greaves, Ian K.; Groszmann, Michael; Wu, Li Min; Dennis, Elizabeth S.; Peacock, W. James

    2015-01-01

    F1 hybrids can outperform their parents in yield and vegetative biomass, features of hybrid vigor that form the basis of the hybrid seed industry. The yield advantage of the F1 is lost in the F2 and subsequent generations. In Arabidopsis, from F2 plants that have a F1-like phenotype, we have by recurrent selection produced pure breeding F5/F6 lines, hybrid mimics, in which the characteristics of the F1 hybrid are stabilized. These hybrid mimic lines, like the F1 hybrid, have larger leaves than the parent plant, and the leaves have increased photosynthetic cell numbers, and in some lines, increased size of cells, suggesting an increased supply of photosynthate. A comparison of the differentially expressed genes in the F1 hybrid with those of eight hybrid mimic lines identified metabolic pathways altered in both; these pathways include down-regulation of defense response pathways and altered abiotic response pathways. F6 hybrid mimic lines are mostly homozygous at each locus in the genome and yet retain the large F1-like phenotype. Many alleles in the F6 plants, when they are homozygous, have expression levels different to the level in the parent. We consider this altered expression to be a consequence of transregulation of genes from one parent by genes from the other parent. Transregulation could also arise from epigenetic modifications in the F1. The pure breeding hybrid mimics have been valuable in probing the mechanisms of hybrid vigor and may also prove to be useful hybrid vigor equivalents in agriculture. PMID:26283378

  5. Hybride textuelle Strukturen und hybride textuelle Einheiten. Ein Beitrag zur Theorie der Wörterbuchform

    Directory of Open Access Journals (Sweden)

    Herbert Ernst Wiegand

    2011-10-01

    Textsegmentklassen aufweisen (vgl. die Stichwörter.

    Stichwörter: ANGABERELATION, ELEMENTENHETEROGENE TRÄGERMENGE, FUNKTIONALER ANGABEZUSATZ, FUNKTIONAL-POSITIONALE SEGMENTATION, HIERARCHISCHE ARCHITEKTONISCH ANGEREICHERTE ARTIKELMIKROSTRUKTUR, HIERARCHISCHE HYBRIDE ANGABENKONSTITUENTENSTRUKTUR MIT GLOSSATBEDINGTER TEILSTRUKTUR, HIERARCHISCHE HYBRIDE ANGABENSTRUKTUR, HIERARCHISCHE HYBRIDE ARTIKELKONSTITUENTENSTRUKTUR, HIERARCHISCHE HYBRIDE ARTIKELMIKROSTRUKTUR, HIERARCHISCHE HYBRIDE EXHAUSTIVE ANGABENSTRUKTUR, HIERARCHISCHE HYBRIDE GLOSSATBEDINGTE ANGABESTRUKTUR, HIERARCHISCHE HYBRIDE FLACHE DOPPELGLOSSATBEDINGTE ANGABESTRUKTUR, HIERARCHISCHE HYBRIDE MINIMIERTE GLOSSATBEDINGTE ANGABESTRUKTUR, HIERARCHISCHE HYBRIDE TEXTKONSTITUENTENSTRUKTUR, HIERARCHISCHE HYBRIDE TIEFE DOPPELGLOSSATBEDINGTE ANGABESTRUKTUR, HIERARCHISCHE REINE TEXTKONSTITUENTENSTRUKTUR, HYBRIDE VERWEISKENNZEICHNUNG, NICHTFUNKTIONALE-POSITIONALE SEGMENTATION, ORDNUNGSRELATION, SEGMENTATIVE ISOLIERUNG, VERTIKALE ANGABEARCHITEKTUR

     

    ABSTRACT: Hybrid textual structures and hybrid textual units. A contribution to the theory of dictionary structures. In this contribution, the formation, presentation and performance of hybrid textual structures that display accessible entries are discussed by using examples from dictionary articles. The features of hybrid textual units are also explained. A dictionary article in a printed dictionary always displays both a hierarchical pure and a hierarchical hybrid text constituent structure, when it contains at least one functional item addition, e.g. an upward- or downward- or an internally-expanded one. Because functional item additions are text segments with an item function but without text constituent status, they are enabled by means of non-functional segmentation, so that both functional and non-functional text segments prevail. During the formation of structures they then enter the structure-carrying set so that the structurecarrying set of all hybrid

  6. Structure and weights optimisation of a modified Elman network emotion classifier using hybrid computational intelligence algorithms: a comparative study

    Science.gov (United States)

    Sheikhan, Mansour; Abbasnezhad Arabi, Mahdi; Gharavian, Davood

    2015-10-01

    Artificial neural networks are efficient models in pattern recognition applications, but their performance is dependent on employing suitable structure and connection weights. This study used a hybrid method for obtaining the optimal weight set and architecture of a recurrent neural emotion classifier based on gravitational search algorithm (GSA) and its binary version (BGSA), respectively. By considering the features of speech signal that were related to prosody, voice quality, and spectrum, a rich feature set was constructed. To select more efficient features, a fast feature selection method was employed. The performance of the proposed hybrid GSA-BGSA method was compared with similar hybrid methods based on particle swarm optimisation (PSO) algorithm and its binary version, PSO and discrete firefly algorithm, and hybrid of error back-propagation and genetic algorithm that were used for optimisation. Experimental tests on Berlin emotional database demonstrated the superior performance of the proposed method using a lighter network structure.

  7. Design Features of a Planar Hybrid/Permanent Magnet Strong Focusing Undulator for Free Electron Laser (FEL) And Synchrotron Radiation (SR) Applications

    Energy Technology Data Exchange (ETDEWEB)

    Tatchyn, Roman; /SLAC

    2011-09-09

    Insertion devices for Angstrom-wavelength Free Electron Laser (FEL) amplifiers driven by multi-GeV electron beams generally require distributed focusing substantially stronger than their own natural focusing fields. Over the last several years a wide variety of focusing schemes and configurations have been proposed for undulators of this class, ranging from conventional current-driven quadrupoles external to the undulator magnets to permanent magnet (PM) lattices inserted into the insertion device gap. In this paper we present design studies of a flexible high-field hybrid/PM undulator with strong superimposed planar PM focusing proposed for a 1.5 Angstrom Linac Coherent Light Source (LCLS) driven by an electron beam with a 1 mm-mr normalized emittance. Attainable field parameters, tuning modes, and potential applications of the proposed structure are discussed.

  8. The Hybrid Automobile and the Atkinson Cycle

    Science.gov (United States)

    Feldman, Bernard J.

    2008-01-01

    The hybrid automobile is a strikingly new automobile technology with a number of new technological features that dramatically improve energy efficiency. This paper will briefly describe how hybrid automobiles work; what are these new technological features; why the Toyota Prius hybrid internal combustion engine operates on the Atkinson cycle…

  9. Features of Creation and Operation of Electric and Hybrid Vehicles in Countries with Difficult Climatic Conditions, for Example, in the Russian Federation

    Science.gov (United States)

    Karpukhin, K.; Terenchenko, A.

    2016-11-01

    The trend of increasing fleet of electric or hybrid vehicles and determines the extension of the geographical areas of operation, including the Northern areas with cold winter weather. Practically in all territory of Russia the average winter temperature is negative. With the winter temperatures can be below in Moscow -30°C, in Krasnoyarsk -50°C. Battery system can operate in a wide temperature range, but there are extremes that should be remembered all the time, especially in cold climates like Russia. In the operating instructions of the electric car Tesla Model S indicate that to save the battery don't use at temperatures below -15°C. The paper presents the dependence of the cooling time and heating of the battery cell at different ambient temperatures and provides guidance on allowable cooling time while using and not thermally insulated thermally containers Suggests using the temperature control on the basis of thermoelectric converters Peltier connection from the onboard electrical network of the electric vehicle.

  10. An unusual hybrid fluoride featuring a [V7F27]6- chain motif based on a pyrochlore-like building unit

    International Nuclear Information System (INIS)

    Aldous, David W.; Slawin, Alexandra M.Z.; Lightfoot, Philip

    2008-01-01

    A new hybrid vanadium (III) fluoride [C 4 H 12 N 2 ] 3 [V 7 F 27 ] has been synthesised solvothermally. The crystal structure (trigonal, R3-bar c; a=17.367(2) A, c=19.604(2) A) reveals an unusual and novel chain motif consisting of pyrochlore-like heptameric units of corner-sharing octahedra, which are further linked into linear chains of alternating triple and single octahedral groups. The chains are separated by hydrogen-bonded piperazinium moieties. Magnetic susceptibility data show moderate antiferromagnetic interactions but no long-range order above 2 K, consistent with pronounced one-dimensional character, as well as frustration arising within the triangular units of magnetic ions in the chains. - Graphical abstract: A unique chain-structure vanadium(III) fluoride [C 4 H 12 N 2 ] 3 [V 7 F 27 ], based on a pyrochlore-like building unit, has been prepared solvothermally. Despite antiferromagnetic interactions, no long-range magnetic order occurs above 2 K, suggesting possible frustration

  11. Sequence based prediction of DNA-binding proteins based on hybrid feature selection using random forest and Gaussian naïve Bayes.

    Directory of Open Access Journals (Sweden)

    Wangchao Lou

    Full Text Available Developing an efficient method for determination of the DNA-binding proteins, due to their vital roles in gene regulation, is becoming highly desired since it would be invaluable to advance our understanding of protein functions. In this study, we proposed a new method for the prediction of the DNA-binding proteins, by performing the feature rank using random forest and the wrapper-based feature selection using forward best-first search strategy. The features comprise information from primary sequence, predicted secondary structure, predicted relative solvent accessibility, and position specific scoring matrix. The proposed method, called DBPPred, used Gaussian naïve Bayes as the underlying classifier since it outperformed five other classifiers, including decision tree, logistic regression, k-nearest neighbor, support vector machine with polynomial kernel, and support vector machine with radial basis function. As a result, the proposed DBPPred yields the highest average accuracy of 0.791 and average MCC of 0.583 according to the five-fold cross validation with ten runs on the training benchmark dataset PDB594. Subsequently, blind tests on the independent dataset PDB186 by the proposed model trained on the entire PDB594 dataset and by other five existing methods (including iDNA-Prot, DNA-Prot, DNAbinder, DNABIND and DBD-Threader were performed, resulting in that the proposed DBPPred yielded the highest accuracy of 0.769, MCC of 0.538, and AUC of 0.790. The independent tests performed by the proposed DBPPred on completely a large non-DNA binding protein dataset and two RNA binding protein datasets also showed improved or comparable quality when compared with the relevant prediction methods. Moreover, we observed that majority of the selected features by the proposed method are statistically significantly different between the mean feature values of the DNA-binding and the non DNA-binding proteins. All of the experimental results indicate that

  12. Successful Wide Hybridization and Introgression Breeding in a Diverse Set of Common Peppers (Capsicum annuum) Using Different Cultivated Ají (C. baccatum) Accessions as Donor Parents

    Science.gov (United States)

    2015-01-01

    Capsicum baccatum, commonly known as ají, has been reported as a source of variation for many different traits to improve common pepper (C. annuum), one of the most important vegetables in the world. However, strong interspecific hybridization barriers exist between them. A comparative study of two wide hybridization approaches for introgressing C. baccatum genes into C. annuum was performed: i) genetic bridge (GB) using C. chinense and C. frutescens as bridge species; and, ii) direct cross between C. annuum and C. baccatum combined with in vitro embryo rescue (ER). A diverse and representative collection of 18 accessions from four cultivated species of Capsicum was used, including C. annuum (12), C. baccatum (3), C. chinense (2), and C. frutescens (1). More than 5000 crosses were made and over 1000 embryos were rescued in the present study. C. chinense performed as a good bridge species between C. annuum and C. baccatum, with the best results being obtained with the cross combination [C. baccatum (♀) × C. chinense (♂)] (♀) × C. annuum (♂), while C. frutescens gave poor results as bridge species due to strong prezygotic and postzygotic barriers. Virus-like-syndrome or dwarfism was observed in F1 hybrids when both C. chinense and C. frutescens were used as female parents. Regarding the ER strategy, the best response was found in C. annuum (♀) × C. baccatum (♂) crosses. First backcrosses to C. annuum (BC1s) were obtained according to the crossing scheme [C. annuum (♀) × C. baccatum (♂)] (♀) × C. annuum (♂) using ER. Advantages and disadvantages of each strategy are discussed in relation to their application to breeding programmes. These results provide breeders with useful practical information for the regular utilization of the C. baccatum gene pool in C. annuum breeding. PMID:26642059

  13. Determination of the correlation relationship of pedagogical tests of general physical training with a set of parameters describing the morphological features and canoeists.

    Directory of Open Access Journals (Sweden)

    Flerchuk Viktor Viktorovich

    2011-09-01

    Full Text Available Correlation connections of tests are certain to on general physical preparation with indexes morphological possibilities of sportsmen. 15 sportsmen took part in research. Propensity of sportsmen is set to certain distances in competition activity. Directions of selection and orientation of sportsmen are recommended to work of different orientation.

  14. Marine Fish Hybridization

    KAUST Repository

    He, Song

    2017-04-01

    Natural hybridization is reproduction (without artificial influence) between two or more species/populations which are distinguishable from each other by heritable characters. Natural hybridizations among marine fishes were highly underappreciated due to limited research effort; it seems that this phenomenon occurs more often than is commonly recognized. As hybridization plays an important role in biodiversity processes in the marine environment, detecting hybridization events and investigating hybridization is important to understand and protect biodiversity. The first chapter sets the framework for this disseration study. The Cohesion Species Concept was selected as the working definition of a species for this study as it can handle marine fish hybridization events. The concept does not require restrictive species boundaries. A general history and background of natural hybridization in marine fishes is reviewed during in chapter as well. Four marine fish hybridization cases were examed and documented in Chapters 2 to 5. In each case study, at least one diagnostic nuclear marker, screened from among ~14 candidate markers, was found to discriminate the putative hybridizing parent species. To further investigate genetic evidence to support the hybrid status for each hybrid offspring in each case, haploweb analysis on diagnostic markers (nuclear and/or mitochondrial) and the DAPC/PCA analysis on microsatellite data were used. By combining the genetic evidences, morphological traits, and ecological observations together, the potential reasons that triggered each hybridization events and the potential genetic/ecology effects could be discussed. In the last chapter, sequences from 82 pairs of hybridizing parents species (for which COI barcoding sequences were available either on GenBank or in our lab) were collected. By comparing the COI fragment p-distance between each hybridizing parent species, some general questions about marine fish hybridization were discussed: Is

  15. An Efficient Framework for EEG Analysis with Application to Hybrid Brain Computer Interfaces Based on Motor Imagery and P300

    Directory of Open Access Journals (Sweden)

    Jinyi Long

    2017-01-01

    Full Text Available The hybrid brain computer interface (BCI based on motor imagery (MI and P300 has been a preferred strategy aiming to improve the detection performance through combining the features of each. However, current methods used for combining these two modalities optimize them separately, which does not result in optimal performance. Here, we present an efficient framework to optimize them together by concatenating the features of MI and P300 in a block diagonal form. Then a linear classifier under a dual spectral norm regularizer is applied to the combined features. Under this framework, the hybrid features of MI and P300 can be learned, selected, and combined together directly. Experimental results on the data set of hybrid BCI based on MI and P300 are provided to illustrate competitive performance of the proposed method against other conventional methods. This provides an evidence that the method used here contributes to the discrimination performance of the brain state in hybrid BCI.

  16. WALK 2.0: Examining the effectiveness of Web 2.0 features to increase physical activity in a ‘real world’ setting: an ecological trial

    Science.gov (United States)

    Caperchione, Cristina M; Kolt, Gregory S; Savage, Trevor N; Rosenkranz, Richard R; Maeder, Anthony J; Vandelanotte, Corneel; Duncan, Mitch J; Van Itallie, Anetta; Tague, Rhys; Mummery, W Kerry

    2014-01-01

    Introduction Low levels of health-enhancing physical activity require novel approaches that have the potential to reach broad populations. Web-based interventions are a popular approach for behaviour change given their wide reach and accessibility. However, challenges with participant engagement and retention reduce the long-term maintenance of behaviour change. Web 2.0 features present a new and innovative online environment supporting greater interactivity, with the potential to increase engagement and retention. In order to understand the applicability of these innovative interventions for the broader population, ‘real-world’ interventions implemented under ‘everyday conditions’ are required. The aim of this study is to investigate the difference in physical activity behaviour between individuals using a traditional Web 1.0 website with those using a novel Web 2.0 website. Methods and analysis In this study we will aim to recruit 2894 participants. Participants will be recruited from individuals who register with a pre-existing health promotion website that currently provides Web 1.0 features (http://www.10000steps.org.au). Eligible participants who provide informed consent will be randomly assigned to one of the two trial conditions: the pre-existing 10 000 Steps website (with Web 1.0 features) or the newly developed WALK 2.0 website (with Web 2.0 features). Primary and secondary outcome measures will be assessed by self-report at baseline, 3 months and 12 months, and include: physical activity behaviour, height and weight, Internet self-efficacy, website usability, website usage and quality of life. Ethics and dissemination This study has received ethics approval from the University of Western Sydney Human Research Ethics Committee (Reference Number H8767) and has been funded by the National Health and Medical Research Council (Reference Number 589903). Study findings will be disseminated widely through peer-reviewed publications, academic

  17. WALK 2.0: examining the effectiveness of Web 2.0 features to increase physical activity in a 'real world' setting: an ecological trial.

    Science.gov (United States)

    Caperchione, Cristina M; Kolt, Gregory S; Savage, Trevor N; Rosenkranz, Richard R; Maeder, Anthony J; Vandelanotte, Corneel; Duncan, Mitch J; Van Itallie, Anetta; Tague, Rhys; Mummery, W Kerry

    2014-10-10

    Low levels of health-enhancing physical activity require novel approaches that have the potential to reach broad populations. Web-based interventions are a popular approach for behaviour change given their wide reach and accessibility. However, challenges with participant engagement and retention reduce the long-term maintenance of behaviour change. Web 2.0 features present a new and innovative online environment supporting greater interactivity, with the potential to increase engagement and retention. In order to understand the applicability of these innovative interventions for the broader population, 'real-world' interventions implemented under 'everyday conditions' are required. The aim of this study is to investigate the difference in physical activity behaviour between individuals using a traditional Web 1.0 website with those using a novel Web 2.0 website. In this study we will aim to recruit 2894 participants. Participants will be recruited from individuals who register with a pre-existing health promotion website that currently provides Web 1.0 features (http://www.10000steps.org.au). Eligible participants who provide informed consent will be randomly assigned to one of the two trial conditions: the pre-existing 10 000 Steps website (with Web 1.0 features) or the newly developed WALK 2.0 website (with Web 2.0 features). Primary and secondary outcome measures will be assessed by self-report at baseline, 3 months and 12 months, and include: physical activity behaviour, height and weight, Internet self-efficacy, website usability, website usage and quality of life. This study has received ethics approval from the University of Western Sydney Human Research Ethics Committee (Reference Number H8767) and has been funded by the National Health and Medical Research Council (Reference Number 589903). Study findings will be disseminated widely through peer-reviewed publications, academic conferences and local community-based presentations. Australian New

  18. Synthesis, structural and spectroscopic features, and investigation of bioactive nature of a novel organic-inorganic hybrid material 1H-1,2,4-triazole-4-ium trioxonitrate

    Science.gov (United States)

    Gatfaoui, Sofian; Issaoui, Noureddine; Mezni, Ali; Bardak, Fehmi; Roisnel, Thierry; Atac, Ahmet; Marouani, Houda

    2017-12-01

    The novel inorganic-organic hybrid material 1H-1,2,4-triazole-4-ium trioxonitrate (TAN) have been elaborated and crystallized to the monoclinic system with space group P21/c and the lattice parameters obtained are a = 8.8517(15) Å, b = 8.3791(15) Å, c = 7.1060(11) Å, β = 103.776(7)°, V = 511.89(15) Å3 and Z = 4. In order to enhance (TAN) on the applied plan, biophysicochemical characterization of the title compound have been obtained with experimentally and theoretically. The crystal structure exposed substantial hydrogen bonding stuck between the protonated 1,2,4-triazole ring and the nitrate forming thus sheets parallel to the plans (-1 0 1). The three-dimensional supramolecular network is formed through the π … π interactions involving heterocyclic rings in these sheets. Assessment of intermolecular contacts in the crystal arrangement was quantified by Hirshfeld surface analysis and interactions were analyzed by orbital NBO and topological AIM approaches. This compound was also investigated by means of infrared spectroscopy, electrical conductivity, thermal analysis TG-DTA, and DSC. Moreover, the antioxidant properties of TAN were determined via the DPPH radical scavenging, the ABTS radical scavenging, hydroxyl radical scavenging, and ferric reducing power (FRP). Obtained results confirm the functionality of antioxidant potency of TAN. The molecular structure and vibrational spectral analysis of TAN have been reported by using density functional theory calculations at B3LYP/6-311++G(d,p) level of theory. Molecular docking behaviors of TAN along with well-known triazole antifungal agents (fluconazole, itraconazole, posaconazole, and voriconazole) with saccharomyces cerevisiae CYP51 (Lanosterol 14-alpha demethylase) were investigated. The potent of TAN as an inhibitor was discussed on the basis of noncovalent interaction profile. Furthermore, protonic conduction of this compound has been intentional in the temperature range of 295-373 K.

  19. Feature Importance for Human Epithelial (HEp-2 Cell Image Classification

    Directory of Open Access Journals (Sweden)

    Vibha Gupta

    2018-02-01

    Full Text Available Indirect Immuno-Fluorescence (IIF microscopy imaging of human epithelial (HEp-2 cells is a popular method for diagnosing autoimmune diseases. Considering large data volumes, computer-aided diagnosis (CAD systems, based on image-based classification, can help in terms of time, effort, and reliability of diagnosis. Such approaches are based on extracting some representative features from the images. This work explores the selection of the most distinctive features for HEp-2 cell images using various feature selection (FS methods. Considering that there is no single universally optimal feature selection technique, we also propose hybridization of one class of FS methods (filter methods. Furthermore, the notion of variable importance for ranking features, provided by another type of approaches (embedded methods such as Random forest, Random uniform forest is exploited to select a good subset of features from a large set, such that addition of new features does not increase classification accuracy. In this work, we have also, with great consideration, designed class-specific features to capture morphological visual traits of the cell patterns. We perform various experiments and discussions to demonstrate the effectiveness of FS methods along with proposed and a standard feature set. We achieve state-of-the-art performance even with small number of features, obtained after the feature selection.

  20. Analysis and design of hybrid control systems

    Energy Technology Data Exchange (ETDEWEB)

    Malmborg, J.

    1998-05-01

    Different aspects of hybrid control systems are treated: analysis, simulation, design and implementation. A systematic methodology using extended Lyapunov theory for design of hybrid systems is developed. The methodology is based on conventional control designs in separate regions together with a switching strategy. Dynamics are not well defined if the control design methods lead to fast mode switching. The dynamics depend on the salient features of the implementation of the mode switches. A theorem for the stability of second order switching together with the resulting dynamics is derived. The dynamics on an intersection of two sliding sets are defined for two relays working on different time scales. The current simulation packages have problems modeling and simulating hybrid systems. It is shown how fast mode switches can be found before or during simulation. The necessary analysis work is a very small overhead for a modern simulation tool. To get some experience from practical problems with hybrid control the switching strategy is implemented in two different software environments. In one of them a time-optimal controller is added to an existing PID controller on a commercial control system. Successful experiments with this hybrid controller shows the practical use of the method 78 refs, 51 figs, 2 tabs

  1. Molecular Testing of Nodules with a Suspicious or Malignant Cytologic Diagnosis in the Setting of Non-Invasive Follicular Thyroid Neoplasm with Papillary-Like Nuclear Features (NIFTP).

    Science.gov (United States)

    Strickland, Kyle C; Eszlinger, Markus; Paschke, Ralf; Angell, Trevor E; Alexander, Erik K; Marqusee, Ellen; Nehs, Matthew A; Jo, Vickie Y; Lowe, Alarice; Vivero, Marina; Hollowell, Monica; Qian, Xiaohua; Wieczorek, Tad; French, Christopher A; Teot, Lisa A; Cibas, Edmund S; Lindeman, Neal I; Krane, Jeffrey F; Barletta, Justine A

    2018-03-01

    Non-invasive follicular thyroid neoplasm with papillary-like nuclear features (NIFTP) is an indolent thyroid tumor characterized by frequent RAS mutations and an absence of the BRAF V600E mutation commonly seen in classical papillary thyroid carcinoma (cPTC). The ability to differentiate potential NIFTP/follicular variant of papillary thyroid carcinoma (FVPTC) from cPTC at the time of fine-needle aspiration (FNA) can facilitate conservative management of NIFTP. The aim of the current study was to investigate how molecular testing may add to cytologic assessment in the pre-operative differentiation of potential NIFTP/FVPTC and cPTC. We had previously evaluated cytologists' ability to prospectively distinguish potential NIFTP/FVPTC from cPTC in a cohort of 56 consecutive FNAs diagnosed as malignant or suspicious for malignancy. We utilized this cohort to perform molecular analysis. Detected molecular abnormalities were stratified into two groups: (1) those supporting malignancy and (2) those supporting a diagnosis of potential NIFTP/FVPTC. The cytologists' characterization of cases and the detected molecular alterations were correlated with the final histologic diagnoses. Molecular testing was performed in 52 (93%) of the 56 cases. For the 37 cases cytologists favored to be cPTC, 31 (84%) had a molecular result that supported malignancy (28 BRAF V600E mutations, 2 NTRK1 fusions, 1 AGK-BRAF fusion). For the 8 cases that were favored to be NIFTP/FVPTC by cytologists, 7 (88%) had a molecular result that supported conservative management (1 NRAS mutation, 6 wild-type result). Seven cases were designated as cytomorphologically indeterminate for NIFTP/FVPTC or cPTC, of which 6 (86%) had a molecular result that would have aided in the pre-operative assessment of potential NIFTP/FVPTC or cPTC/malignancy. These included 3 BRAF V600E mutations in nodules that were cPTC on resection, an HRAS mutation, and a wild-type result in the 2 nodules that were NIFTP, and a TERT promoter

  2. Online feature selection with streaming features.

    Science.gov (United States)

    Wu, Xindong; Yu, Kui; Ding, Wei; Wang, Hao; Zhu, Xingquan

    2013-05-01

    We propose a new online feature selection framework for applications with streaming features where the knowledge of the full feature space is unknown in advance. We define streaming features as features that flow in one by one over time whereas the number of training examples remains fixed. This is in contrast with traditional online learning methods that only deal with sequentially added observations, with little attention being paid to streaming features. The critical challenges for Online Streaming Feature Selection (OSFS) include 1) the continuous growth of feature volumes over time, 2) a large feature space, possibly of unknown or infinite size, and 3) the unavailability of the entire feature set before learning starts. In the paper, we present a novel Online Streaming Feature Selection method to select strongly relevant and nonredundant features on the fly. An efficient Fast-OSFS algorithm is proposed to improve feature selection performance. The proposed algorithms are evaluated extensively on high-dimensional datasets and also with a real-world case study on impact crater detection. Experimental results demonstrate that the algorithms achieve better compactness and higher prediction accuracy than existing streaming feature selection algorithms.

  3. Superior Rhythm Discrimination With the SmartShock Technology Algorithm - Results of the Implantable Defibrillator With Enhanced Features and Settings for Reduction of Inaccurate Detection (DEFENSE) Trial.

    Science.gov (United States)

    Oginosawa, Yasushi; Kohno, Ritsuko; Honda, Toshihiro; Kikuchi, Kan; Nozoe, Masatsugu; Uchida, Takayuki; Minamiguchi, Hitoshi; Sonoda, Koichiro; Ogawa, Masahiro; Ideguchi, Takeshi; Kizaki, Yoshihisa; Nakamura, Toshihiro; Oba, Kageyuki; Higa, Satoshi; Yoshida, Keiki; Tsunoda, Soichi; Fujino, Yoshihisa; Abe, Haruhiko

    2017-08-25

    Shocks delivered by implanted anti-tachyarrhythmia devices, even when appropriate, lower the quality of life and survival. The new SmartShock Technology ® (SST) discrimination algorithm was developed to prevent the delivery of inappropriate shock. This prospective, multicenter, observational study compared the rate of inaccurate detection of ventricular tachyarrhythmia using the SST vs. a conventional discrimination algorithm.Methods and Results:Recipients of implantable cardioverter defibrillators (ICD) or cardiac resynchronization therapy defibrillators (CRT-D) equipped with the SST algorithm were enrolled and followed up every 6 months. The tachycardia detection rate was set at ≥150 beats/min with the SST algorithm. The primary endpoint was the time to first inaccurate detection of ventricular tachycardia (VT) with conventional vs. the SST discrimination algorithm, up to 2 years of follow-up. Between March 2012 and September 2013, 185 patients (mean age, 64.0±14.9 years; men, 74%; secondary prevention indication, 49.5%) were enrolled at 14 Japanese medical centers. Inaccurate detection was observed in 32 patients (17.6%) with the conventional, vs. in 19 patients (10.4%) with the SST algorithm. SST significantly lowered the rate of inaccurate detection by dual chamber devices (HR, 0.50; 95% CI: 0.263-0.950; P=0.034). Compared with previous algorithms, the SST discrimination algorithm significantly lowered the rate of inaccurate detection of VT in recipients of dual-chamber ICD or CRT-D.

  4. RBiomirGS: an all-in-one miRNA gene set analysis solution featuring target mRNA mapping and expression profile integration

    Directory of Open Access Journals (Sweden)

    Jing Zhang

    2018-01-01

    Full Text Available Background With the continuous discovery of microRNA’s (miRNA association with a wide range of biological and cellular processes, expression profile-based functional characterization of such post-transcriptional regulation is crucial for revealing its significance behind particular phenotypes. Profound advancement in bioinformatics has been made to enable in depth investigation of miRNA’s role in regulating cellular and molecular events, resulting in a huge quantity of software packages covering different aspects of miRNA functional analysis. Therefore, an all-in-one software solution is in demand for a comprehensive yet highly efficient workflow. Here we present RBiomirGS, an R package for a miRNA gene set (GS analysis. Methods The package utilizes multiple databases for target mRNA mapping, estimates miRNA effect on the target mRNAs through miRNA expression profile and conducts a logistic regression-based GS enrichment. Additionally, human ortholog Entrez ID conversion functionality is included for target mRNAs. Results By incorporating all the core steps into one package, RBiomirGS eliminates the need for switching between different software packages. The modular structure of RBiomirGS enables various access points to the analysis, with which users can choose the most relevant functionalities for their workflow. Conclusions With RBiomirGS, users are able to assess the functional significance of the miRNA expression profile under the corresponding experimental condition by minimal input and intervention. Accordingly, RBiomirGS encompasses an all-in-one solution for miRNA GS analysis. RBiomirGS is available on GitHub (http://github.com/jzhangc/RBiomirGS. More information including instruction and examples can be found on website (http://kenstoreylab.com/?page_id=2865.

  5. Design Principles for Hybrid Ventilation

    DEFF Research Database (Denmark)

    Heiselberg, Per

    For many years mechanical and natural ventilation systems have developed separately. Naturally, the next step in this development is the development of ventilation concepts that utilize and combine the best features from each system to create a new type of ventilation system -Hybrid Ventilation. ....... The hybrid ventilation concepts, design challenges and - principles are discussed and illustrated by four building examples....

  6. Allelic interaction of F1 pollen sterility loci and abnormal chromosome behaviour caused pollen sterility in intersubspecific autotetraploid rice hybrids.

    Science.gov (United States)

    He, J H; Shahid, M Q; Li, Y J; Guo, H B; Cheng, X A; Liu, X D; Lu, Y G

    2011-08-01

    The intersubspecific hybrids of autotetraploid rice has many features that increase rice yield, but lower seed set is a major hindrance in its utilization. Pollen sterility is one of the most important factors which cause intersubspecific hybrid sterility. The hybrids with greater variation in seed set were used to study how the F(1) pollen sterile loci (S-a, S-b, and S-c) interact with each other and how abnormal chromosome behaviour and allelic interaction of F(1) sterility loci affect pollen fertility and seed set of intersubspecific autotetraploid rice hybrids. The results showed that interaction between pollen sterility loci have significant effects on the pollen fertility of autotetraploid hybrids, and pollen fertility further decreased with an increase in the allelic interaction of F(1) pollen sterility loci. Abnormal ultra-structure and microtubule distribution patterns during pollen mother cell (PMC) meiosis were found in the hybrids with low pollen fertility in interphase and leptotene, suggesting that the effect-time of pollen sterility loci interaction was very early. There were highly significant differences in the number of quadrivalents and bivalents, and in chromosome configuration among all the hybrids, and quadrivalents decreased with an increase in the seed set of autotetraploid hybrids. Many different kinds of chromosomal abnormalities, such as chromosome straggling, chromosome lagging, asynchrony of chromosome disjunction, and tri-fission were found during the various developmental stages of PMC meiosis. All these abnormalities were significantly higher in sterile hybrids than in fertile hybrids, suggesting that pollen sterility gene interactions tend to increase the chromosomal abnormalities which cause the partial abortion of male gametes and leads to the decline in the seed set of the autotetraploid rice hybrids. © 2011 The Author(s).

  7. Hybrid Logical Analyses of the Ambient Calculus

    DEFF Research Database (Denmark)

    Bolander, Thomas; Hansen, Rene Rydhof

    2010-01-01

    In this paper, hybrid logic is used to formulate three control flow analyses for Mobile Ambients, a process calculus designed for modelling mobility. We show that hybrid logic is very well-suited to express the semantic structure of the ambient calculus and how features of hybrid logic can...

  8. A Novel Hybrid Similarity Calculation Model

    Directory of Open Access Journals (Sweden)

    Xiaoping Fan

    2017-01-01

    Full Text Available This paper addresses the problems of similarity calculation in the traditional recommendation algorithms of nearest neighbor collaborative filtering, especially the failure in describing dynamic user preference. Proceeding from the perspective of solving the problem of user interest drift, a new hybrid similarity calculation model is proposed in this paper. This model consists of two parts, on the one hand the model uses the function fitting to describe users’ rating behaviors and their rating preferences, and on the other hand it employs the Random Forest algorithm to take user attribute features into account. Furthermore, the paper combines the two parts to build a new hybrid similarity calculation model for user recommendation. Experimental results show that, for data sets of different size, the model’s prediction precision is higher than the traditional recommendation algorithms.

  9. Feature Set Fusion for Spoof Iris Detection

    Directory of Open Access Journals (Sweden)

    P. V. L. Suvarchala

    2018-04-01

    Full Text Available Iris recognition is considered as one of the most promising noninvasive biometric systems providing automated human identification. Numerous programs, like unique ID program in India - Aadhar, include iris biometric to provide distinctive identity identification to citizens. The active area is usually captured under non ideal imaging conditions. It usually suffers from poor brightness, low contrast, blur due to camera or subject's relative movement and eyelid eyelash occlusions. Besides the technical challenges, iris recognition started facing sophisticated threats like spoof attacks. Therefore it is vital that the integrity of such large scale iris deployments must be preserved. This paper presents the development of a new spoof resistant approach which exploits the statistical dependencies of both general eye and localized iris regions in textural domain using spatial gray level dependence matrix (SGLDM, gray level run length matrix (GLRLM and contourlets in transform domain. We did experiments on publicly available fake and lens iris image databases. Correct classification rate obtained with ATVS-FIr iris database is 100% while it is 95.63% and 88.83% with IITD spoof iris databases respectively.

  10. Hybrid2 - The hybrid power system simulation model

    Energy Technology Data Exchange (ETDEWEB)

    Baring-Gould, E.I.; Green, H.J.; Dijk, V.A.P. van [National Renewable Energy Lab., Golden, CO (United States); Manwell, J.F. [Univ. of Massachusetts, Amherst, MA (United States)

    1996-12-31

    There is a large-scale need and desire for energy in remote communities, especially in the developing world; however the lack of a user friendly, flexible performance prediction model for hybrid power systems incorporating renewables hindered the analysis of hybrids as options to conventional solutions. A user friendly model was needed with the versatility to simulate the many system locations, widely varying hardware configurations, and differing control options for potential hybrid power systems. To meet these ends, researchers from the National Renewable Energy Laboratory (NREL) and the University of Massachusetts (UMass) developed the Hybrid2 software. This paper provides an overview of the capabilities, features, and functionality of the Hybrid2 code, discusses its validation and future plans. Model availability and technical support provided to Hybrid2 users are also discussed. 12 refs., 3 figs., 4 tabs.

  11. FEV's new parallel hybrid transmission with single dry clutch and electric torque support

    Energy Technology Data Exchange (ETDEWEB)

    Hellenbroich, Gereon [VKA, RWTH Aachen (Germany); Rosenburg, Volker [FEV Motorentechnik GmbH, Aachen (Germany)

    2009-07-01

    FEV is currently developing a new 7-speed hybrid transmission for transverse installation. The transmission with a design torque of 320 Nm is based on AMT (automated manual transmission) technology and uses a single electric motor. The innovative gear set layout combines the advantages of modern AMTs such as best efficiency, low costs and few components with full hybrid capabilities and electric torque support during all gear shifts. Furthermore, the gear set layout allows for very short-shift-times due to the favorable distribution of inertias. Other features include an A/C compressor being electrically driven by the electric motor of the transmission during start/stop phases. (orig.)

  12. Semiautomated hybrid algorithm for estimation of three-dimensional liver surface in CT using dynamic cellular automata and level-sets.

    Science.gov (United States)

    Dakua, Sarada Prasad; Abinahed, Julien; Al-Ansari, Abdulla

    2015-04-01

    Liver segmentation continues to remain a major challenge, largely due to its intense complexity with surrounding anatomical structures (stomach, kidney, and heart), high noise level and lack of contrast in pathological computed tomography (CT) data. We present an approach to reconstructing the liver surface in low contrast CT. The main contributions are: (1) a stochastic resonance-based methodology in discrete cosine transform domain is developed to enhance the contrast of pathological liver images, (2) a new formulation is proposed to prevent the object boundary, resulting from the cellular automata method, from leaking into the surrounding areas of similar intensity, and (3) a level-set method is suggested to generate intermediate segmentation contours from two segmented slices distantly located in a subject sequence. We have tested the algorithm on real datasets obtained from two sources, Hamad General Hospital and medical image computing and computer-assisted interventions grand challenge workshop. Various parameters in the algorithm, such as [Formula: see text], [Formula: see text], [Formula: see text], [Formula: see text], [Formula: see text], [Formula: see text], and [Formula: see text], play imperative roles, thus their values are precisely selected. Both qualitative and quantitative evaluation performed on liver data show promising segmentation accuracy when compared with ground truth data reflecting the potential of the proposed method.

  13. A hybrid method using the widely-used WIEN2k and VASP codes to calculate the complete set of XAS/EELS edges in a hundred-atoms system.

    Science.gov (United States)

    Donval, Gaël; Moreau, Philippe; Danet, Julien; Larbi, Séverine Jouanneau-Si; Bayle-Guillemaud, Pascale; Boucher, Florent

    2017-01-04

    Most of the recent developments in EELS modelling has been focused on getting a better agreement with measurements. Less work however has been dedicated to bringing EELS calculations to larger structures that can more realistically describe actual systems. The purpose of this paper is to present a hybrid approach well adapted to calculating the whole set of localised EELS core-loss edges (at the XAS level of theory) on larger systems using only standard tools, namely the WIEN2k and VASP codes. We illustrate the usefulness of this method by applying it to a set of amorphous silicon structures in order to explain the flattening of the silicon L 2,3 EELS edge peak at the onset. We show that the peak flattening is actually caused by the collective contribution of each of the atoms to the average spectrum, as opposed to a flattening occurring on each individual spectrum. This method allowed us to reduce the execution time by a factor of 3 compared to a usual-carefully optimised-WIEN2k calculation. It provided even greater speed-ups on more complex systems (interfaces, ∼300 atoms) that will be presented in a future paper. This method is suited to calculate all the localized edges of all the atoms of a structure in a single calculation for light atoms as long as the core-hole effects can be neglected.

  14. Understanding Legacy Features with Featureous

    DEFF Research Database (Denmark)

    Olszak, Andrzej; Jørgensen, Bo Nørregaard

    2011-01-01

    Java programs called Featureous that addresses this issue. Featureous allows a programmer to easily establish feature-code traceability links and to analyze their characteristics using a number of visualizations. Featureous is an extension to the NetBeans IDE, and can itself be extended by third...

  15. STRICT STABILITY OF IMPULSIVE SET VALUED DIFFERENTIAL EQUATIONS

    Institute of Scientific and Technical Information of China (English)

    2011-01-01

    In this paper, we develop strict stability concepts of ODE to impulsive hybrid set valued differential equations. By Lyapunov’s original method, we get some basic strict stability criteria of impulsive hybrid set valued equations.

  16. Energy Efficiency Comparison between Hydraulic Hybrid and Hybrid Electric Vehicles

    Directory of Open Access Journals (Sweden)

    Jia-Shiun Chen

    2015-05-01

    Full Text Available Conventional vehicles tend to consume considerable amounts of fuel, which generates exhaust gases and environmental pollution during intermittent driving cycles. Therefore, prospective vehicle designs favor improved exhaust emissions and energy consumption without compromising vehicle performance. Although pure electric vehicles feature high performance and low pollution characteristics, their limitations are their short driving range and high battery costs. Hybrid electric vehicles (HEVs are comparatively environmentally friendly and energy efficient, but cost substantially more compared with conventional vehicles. Hydraulic hybrid vehicles (HHVs are mainly operated using engines, or using alternate combinations of engine and hydraulic power sources while vehicles accelerate. When the hydraulic system accumulator is depleted, the conventional engine reengages; concurrently, brake-regenerated power is recycled and reused by employing hydraulic motor–pump modules in circulation patterns to conserve fuel and recycle brake energy. This study adopted MATLAB Simulink to construct complete HHV and HEV models for backward simulations. New European Driving Cycles were used to determine the changes in fuel economy. The output of power components and the state-of-charge of energy could be retrieved. Varying power component models, energy storage component models, and series or parallel configurations were combined into seven different vehicle configurations: the conventional manual transmission vehicle, series hybrid electric vehicle, series hydraulic hybrid vehicle, parallel hybrid electric vehicle, parallel hydraulic hybrid vehicle, purely electric vehicle, and hydraulic-electric hybrid vehicle. The simulation results show that fuel consumption was 21.80% lower in the series hydraulic hybrid vehicle compared to the series hybrid electric vehicle; additionally, fuel consumption was 3.80% lower in the parallel hybrid electric vehicle compared to the

  17. Hybrid materials science: a promised land for the integrative design of multifunctional materials.

    Science.gov (United States)

    Nicole, Lionel; Laberty-Robert, Christel; Rozes, Laurence; Sanchez, Clément

    2014-06-21

    For more than 5000 years, organic-inorganic composite materials created by men via skill and serendipity have been part of human culture and customs. The concept of "hybrid organic-inorganic" nanocomposites exploded in the second half of the 20th century with the expansion of the so-called "chimie douce" which led to many collaborations between a large set of chemists, physicists and biologists. Consequently, the scientific melting pot of these very different scientific communities created a new pluridisciplinary school of thought. Today, the tremendous effort of basic research performed in the last twenty years allows tailor-made multifunctional hybrid materials with perfect control over composition, structure and shape. Some of these hybrid materials have already entered the industrial market. Many tailor-made multiscale hybrids are increasingly impacting numerous fields of applications: optics, catalysis, energy, environment, nanomedicine, etc. In the present feature article, we emphasize several fundamental and applied aspects of the hybrid materials field: bioreplication, mesostructured thin films, Lego-like chemistry designed hybrid nanocomposites, and advanced hybrid materials for energy. Finally, a few commercial applications of hybrid materials will be presented.

  18. Hybrid materials science: a promised land for the integrative design of multifunctional materials

    Science.gov (United States)

    Nicole, Lionel; Laberty-Robert, Christel; Rozes, Laurence; Sanchez, Clément

    2014-05-01

    For more than 5000 years, organic-inorganic composite materials created by men via skill and serendipity have been part of human culture and customs. The concept of ``hybrid organic-inorganic'' nanocomposites exploded in the second half of the 20th century with the expansion of the so-called ``chimie douce'' which led to many collaborations between a large set of chemists, physicists and biologists. Consequently, the scientific melting pot of these very different scientific communities created a new pluridisciplinary school of thought. Today, the tremendous effort of basic research performed in the last twenty years allows tailor-made multifunctional hybrid materials with perfect control over composition, structure and shape. Some of these hybrid materials have already entered the industrial market. Many tailor-made multiscale hybrids are increasingly impacting numerous fields of applications: optics, catalysis, energy, environment, nanomedicine, etc. In the present feature article, we emphasize several fundamental and applied aspects of the hybrid materials field: bioreplication, mesostructured thin films, Lego-like chemistry designed hybrid nanocomposites, and advanced hybrid materials for energy. Finally, a few commercial applications of hybrid materials will be presented.

  19. Feature Article

    Indian Academy of Sciences (India)

    Home; Journals; Resonance – Journal of Science Education. Feature Article. Articles in Resonance – Journal of Science Education. Volume 1 Issue 1 January 1996 pp 80-85 Feature Article. What's New in Computers Windows 95 · Vijnan Shastri · More Details Fulltext PDF. Volume 1 Issue 1 January 1996 pp 86-89 Feature ...

  20. Hybrid undulator numerical optimization

    Energy Technology Data Exchange (ETDEWEB)

    Hairetdinov, A.H. [Kurchatov Institute, Moscow (Russian Federation); Zukov, A.A. [Solid State Physics Institute, Chernogolovka (Russian Federation)

    1995-12-31

    3D properties of the hybrid undulator scheme arc studied numerically using PANDIRA code. It is shown that there exist two well defined sets of undulator parameters which provide either maximum on-axis field amplitude or minimal higher harmonics amplitude of the basic undulator field. Thus the alternative between higher field amplitude or pure sinusoidal field exists. The behavior of the undulator field amplitude and harmonics structure for a large set of (undulator gap)/(undulator wavelength) values is demonstrated.

  1. Genetic characterization of early maturing maize hybrids (Zea mays L. obtained by protein and RAPD markers

    Directory of Open Access Journals (Sweden)

    Bauer Iva

    2005-01-01

    Full Text Available Knowledge of maize germplasm genetic diversity is important for planning breeding programmes, germplasm conservation per se etc. Genetic variability of maize hybrids grown in the fields is also very important because genetic uniformity implies risks of genetic vulnerability to stress factors and can cause great losts in yield. Early maturing maize hybrids are characterized by shorter vegetation period and they are grown in areas with shorter vegetation season. Because of different climatic conditions in these areas lines and hybrids are developed with different features in respect to drought resistance and disease resistance. The objective of our study was to characterize set of early maturing maize hybrids with protein and RAPD markers and to compare this clasification with their pedigree information. RAPD markers gave significantly higher rate of polymorphism than protein markers. Better corelation was found among pedigree information and protein markers.

  2. Patch layout generation by detecting feature networks

    KAUST Repository

    Cao, Yuanhao; Yan, Dongming; Wonka, Peter

    2015-01-01

    The patch layout of 3D surfaces reveals the high-level geometric and topological structures. In this paper, we study the patch layout computation by detecting and enclosing feature loops on surfaces. We present a hybrid framework which combines

  3. Road and Street Centerlines, StreetLabels-The data set is a text feature consisting of 6329 label points representing street names. It was created to show the names of city and county based streets., Published in 1989, Davis County Government.

    Data.gov (United States)

    NSGIC Local Govt | GIS Inventory — Road and Street Centerlines dataset current as of 1989. StreetLabels-The data set is a text feature consisting of 6329 label points representing street names. It was...

  4. Mirror hybrid reactors

    International Nuclear Information System (INIS)

    Moir, R.W.

    1978-01-01

    The fusion-fission hybrid is a combination of the fusion and fission processes, having features which are complementary. Fission energy is running out of readily available fuel, and fusion has extra neutrons which can be used to breed that fission fuel. Fusion would have to take on an extra burden of radioactivity, but this early application would give fusion, which does not work well enough now to make power, practical experience which may accelerate development of pure fusion

  5. Cytogenetics of Festulolium (Festuca x Lolium hybrids).

    Science.gov (United States)

    Kopecký, D; Lukaszewski, A J; Dolezel, J

    2008-01-01

    Grasses are the most important and widely cultivated crops. Among them, ryegrasses (Lolium spp.) and fescues (Festuca spp.) provide high quality fodder for livestock, are used for turf and amenity purposes, and play a fundamental role in environment protection. Species from the two genera display complementary agronomic characteristics and are often grown in mixtures. Breeding efforts to combine desired features in single entities culminated with the production of Festuca x Lolium hybrids. The so called Festuloliums enjoy a considerable commercial success with numerous cultivars registered all over the world. They are also very intriguing from a strictly cytogenetic point of view as the parental chromosomes recombine freely in hybrids. Until a decade ago this phenomenon was only known in general quantitative terms. The introduction of molecular cytogenetic tools such as FISH and GISH permitted detailed studies of intergeneric chromosome recombination and karyotyping of Festulolium cultivars. These tools were also invaluable in revealing the origin of polyploid fescues, and facilitated the development of chromosome substitution and introgression lines and physical mapping of traits of interest. Further progress in this area will require the development of a larger set of cytogenetic markers and high-resolution cytogenetic maps. It is expected that the Lolium-Festuca complex will continue providing opportunities for breeding superior grass cultivars and the complex will remain an attractive platform for fundamental research of the early steps of hybrid speciation and interaction of parental genomes, as well as the processes of chromosome pairing, elimination and recombination. 2008 S. Karger AG, Basel

  6. Personalizing Medicine Through Hybrid Imaging and Medical Big Data Analysis

    Directory of Open Access Journals (Sweden)

    Laszlo Papp

    2018-06-01

    Full Text Available Medical imaging has evolved from a pure visualization tool to representing a primary source of analytic approaches toward in vivo disease characterization. Hybrid imaging is an integral part of this approach, as it provides complementary visual and quantitative information in the form of morphological and functional insights into the living body. As such, non-invasive imaging modalities no longer provide images only, but data, as stated recently by pioneers in the field. Today, such information, together with other, non-imaging medical data creates highly heterogeneous data sets that underpin the concept of medical big data. While the exponential growth of medical big data challenges their processing, they inherently contain information that benefits a patient-centric personalized healthcare. Novel machine learning approaches combined with high-performance distributed cloud computing technologies help explore medical big data. Such exploration and subsequent generation of knowledge require a profound understanding of the technical challenges. These challenges increase in complexity when employing hybrid, aka dual- or even multi-modality image data as input to big data repositories. This paper provides a general insight into medical big data analysis in light of the use of hybrid imaging information. First, hybrid imaging is introduced (see further contributions to this special Research Topic, also in the context of medical big data, then the technological background of machine learning as well as state-of-the-art distributed cloud computing technologies are presented, followed by the discussion of data preservation and data sharing trends. Joint data exploration endeavors in the context of in vivo radiomics and hybrid imaging will be presented. Standardization challenges of imaging protocol, delineation, feature engineering, and machine learning evaluation will be detailed. Last, the paper will provide an outlook into the future role of hybrid

  7. Hybrid composites

    CSIR Research Space (South Africa)

    Jacob John, Maya

    2009-04-01

    Full Text Available mixed short sisal/glass hybrid fibre reinforced low density polyethylene composites was investigated by Kalaprasad et al [25].Chemical surface modifications such as alkali, acetic anhydride, stearic acid, permanganate, maleic anhydride, silane...

  8. Exogenous selection rather than cytonuclear incompatibilities shapes asymmetrical fitness of reciprocal Arabidopsis hybrids.

    Science.gov (United States)

    Muir, Graham; Ruiz-Duarte, Paola; Hohmann, Nora; Mable, Barbara K; Novikova, Polina; Schmickl, Roswitha; Guggisberg, Alessia; Koch, Marcus A

    2015-04-01

    Reciprocal crosses between species often display an asymmetry in the fitness of F1 hybrids. This pattern, referred to as isolation asymmetry or Darwin's corollary to Haldane's rule, is a general feature of reproductive isolation in plants, yet factors determining its magnitude and direction remain unclear. We evaluated reciprocal species crosses between two naturally hybridizing diploid species of Arabidopsis to assess the degree of isolation asymmetry at different postmating life stages. We found that pollen from Arabidopsis arenosa will usually fertilize ovules from Arabidopsis lyrata; the reverse receptivity being less complete. Maternal A. lyrata parents set more F1 hybrid seed, but germinate at lower frequency, reversing the asymmetry. As predicted by theory, A. lyrata (the maternal parent with lower seed viability in crosses) exhibited accelerated chloroplast evolution, indicating that cytonuclear incompatibilities may play a role in reproductive isolation. However, this direction of asymmetrical reproductive isolation is not replicated in natural suture zones, where delayed hybrid breakdown of fertility at later developmental stages, or later-acting selection against A. arenosa maternal hybrids (unrelated to hybrid fertility, e.g., substrate adaptation) may be responsible for an excess of A. lyrata maternal hybrids. Exogenous selection rather than cytonuclear incompatibilities thus shapes the asymmetrical postmating isolation in nature.

  9. Hybrid intermediaries

    OpenAIRE

    Cetorelli, Nicola

    2014-01-01

    I introduce the concept of hybrid intermediaries: financial conglomerates that control a multiplicity of entity types active in the "assembly line" process of modern financial intermediation, a system that has become known as shadow banking. The complex bank holding companies of today are the best example of hybrid intermediaries, but I argue that financial firms from the "nonbank" space can just as easily evolve into conglomerates with similar organizational structure, thus acquiring the cap...

  10. Feature Extraction

    CERN Document Server

    CERN. Geneva

    2015-01-01

    Feature selection and reduction are key to robust multivariate analyses. In this talk I will focus on pros and cons of various variable selection methods and focus on those that are most relevant in the context of HEP.

  11. Solar Features

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — Collection includes a variety of solar feature datasets contributed by a number of national and private solar observatories located worldwide.

  12. Site Features

    Data.gov (United States)

    U.S. Environmental Protection Agency — This dataset consists of various site features from multiple Superfund sites in U.S. EPA Region 8. These data were acquired from multiple sources at different times...

  13. Design Principles for Natural and Hybrid Ventilation

    OpenAIRE

    Heiselberg, Per

    2000-01-01

    For many years mechanical and natural ventilation systems have developed separately. Naturally, the next step in this development is the development of ventilation concepts that utilize and combine the best features from each system to create a new type of ventilation system- Hybrid Ventilation. The hybrid ventilation concepts, design challenges and principles are discussed and illustrated by four building examples.

  14. Optimizing Hybrid Spreading in Metapopulations.

    OpenAIRE

    Zhang, C.; Zhou, S.; Miller, J. C.; Cox, I. J.; Chain, B. M.

    2015-01-01

    Epidemic spreading phenomena are ubiquitous in nature and society. Examples include the spreading of diseases, information, and computer viruses. Epidemics can spread by local spreading, where infected nodes can only infect a limited set of direct target nodes and global spreading, where an infected node can infect every other node. In reality, many epidemics spread using a hybrid mixture of both types of spreading. In this study we develop a theoretical framework for studying hybrid epidemic...

  15. Optimizing Hybrid Spreading in Metapopulations

    OpenAIRE

    Zhang, Changwang; Zhou, Shi; Miller, Joel C.; Cox, Ingemar J.; Chain, Benjamin M.

    2014-01-01

    Epidemic spreading phenomena are ubiquitous in nature and society. Examples include the spreading of diseases, information, and computer viruses. Epidemics can spread by local spreading, where infected nodes can only infect a limited set of direct target nodes and global spreading, where an infected node can infect every other node. In reality, many epidemics spread using a hybrid mixture of both types of spreading. In this study we develop a theoretical framework for studying hybrid epidemic...

  16. Deducing hybrid performance from parental metabolic profiles of young primary roots of maize by using a multivariate diallel approach.

    Directory of Open Access Journals (Sweden)

    Kristen Feher

    Full Text Available Heterosis, the greater vigor of hybrids compared to their parents, has been exploited in maize breeding for more than 100 years to produce ever better performing elite hybrids of increased yield. Despite extensive research, the underlying mechanisms shaping the extent of heterosis are not well understood, rendering the process of selecting an optimal set of parental lines tedious. This study is based on a dataset consisting of 112 metabolite levels in young roots of four parental maize inbred lines and their corresponding twelve hybrids, along with the roots' biomass as a heterotic trait. Because the parental biomass is a poor predictor for hybrid biomass, we established a model framework to deduce the biomass of the hybrid from metabolite profiles of its parental lines. In the proposed framework, the hybrid metabolite levels are expressed relative to the parental levels by incorporating the standard concept of additivity/dominance, which we name the Combined Relative Level (CRL. Our modeling strategy includes a feature selection step on the parental levels which are demonstrated to be predictive of CRL across many hybrid metabolites. We demonstrate that these selected parental metabolites are further predictive of hybrid biomass. Our approach directly employs the diallel structure in a multivariate fashion, whereby we attempt to not only predict macroscopic phenotype (biomass, but also molecular phenotype (metabolite profiles. Therefore, our study provides the first steps for further investigations of the genetic determinants to metabolism and, ultimately, growth. Finally, our success on the small-scale experiments implies a valid strategy for large-scale experiments, where parental metabolite profiles may be used together with profiles of selected hybrids as a training set to predict biomass of all possible hybrids.

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

    Science.gov (United States)

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

    2017-06-01

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

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

    Directory of Open Access Journals (Sweden)

    G. Ciarelli

    2017-06-01

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

  19. Design Procedure for Hybrid Ventilation

    DEFF Research Database (Denmark)

    Heiselberg, Per; Tjelflaat, Per Olaf

    Mechanical and natural ventilation systems have developed separately during many years. The natural next step in this development is development of ventilation concepts that utilises and combines the best features from each system into a new type of ventilation system - Hybrid Ventilation....... Buildings with hybrid ventilation often include other sustainable technologies and an energy optimisation requires an integrated approach in the design of the building and its mechanical systems. Therefore, the hybrid ventilation design procedure differs from the design procedure for conventional HVAC....... The first ideas on a design procedure for hybrid ventilation is presented and the different types of design methods, that is needed in different phases of the design process, is discussed....

  20. Development and evaluation of a watershed-scale hybrid hydrologic model

    OpenAIRE

    Cho, Younghyun

    2016-01-01

    A watershed-scale hybrid hydrologic model (Distributed-Clark), which is a lumped conceptual and distributed feature model, was developed to predict spatially distributed short- and long-term rainfall runoff generation and routing using relatively simple methodologies and state-of-the-art spatial data in a GIS environment. In Distributed-Clark, spatially distributed excess rainfall estimated with the SCS curve number method and a GIS-based set of separated unit hydrographs (spatially distribut...

  1. Integration of micro milling highspeed spindle on a microEDM-milling machine set-up

    DEFF Research Database (Denmark)

    De Grave, Arnaud; Hansen, Hans Nørgaard; Andolfatto, Loic

    2009-01-01

    In order to cope with repositioning errors and to combine the fast removal rate of micro milling with the precision and small feature size achievable with micro EDM milling, a hybrid micro-milling and micro-EDM milling centre was built and tested. The aim was to build an affordable set-up, easy...... by micro milling. Examples of test parts are shown and used as an experimental validation....

  2. Hybrid cycles for micro generation

    International Nuclear Information System (INIS)

    Campanari, S.

    2000-01-01

    This paper deals with the main features of two emerging technologies in the field of small-scale power generation, micro turbines and Solid Oxide Fuel Cells, discussing the extremely high potential of their combination into hybrid cycles and their possible role for distributed cogeneration [it

  3. Feature selection model based on clustering and ranking in pipeline for microarray data

    Directory of Open Access Journals (Sweden)

    Barnali Sahu

    2017-01-01

    Full Text Available Most of the available feature selection techniques in the literature are classifier bound. It means a group of features tied to the performance of a specific classifier as applied in wrapper and hybrid approach. Our objective in this study is to select a set of generic features not tied to any classifier based on the proposed framework. This framework uses attribute clustering and feature ranking techniques in pipeline in order to remove redundant features. On each uncovered cluster, signal-to-noise ratio, t-statistics and significance analysis of microarray are independently applied to select the top ranked features. Both filter and evolutionary wrapper approaches have been considered for feature selection and the data set with selected features are given to ensemble of predefined statistically different classifiers. The class labels of the test data are determined using majority voting technique. Moreover, with the aforesaid objectives, this paper focuses on obtaining a stable result out of various classification models. Further, a comparative analysis has been performed to study the classification accuracy and computational time of the current approach and evolutionary wrapper techniques. It gives a better insight into the features and further enhancing the classification accuracy with less computational time.

  4. Hybrid stars

    Indian Academy of Sciences (India)

    Hybrid stars. AsHOK GOYAL. Department of Physics and Astrophysics, University of Delhi, Delhi 110 007, India. Abstract. Recently there have been important developments in the determination of neutron ... number and the electric charge. ... available to the system to rearrange concentration of charges for a given fraction of.

  5. Design Principles for Natural and Hybrid Ventilation

    DEFF Research Database (Denmark)

    Heiselberg, Per

    For many years mechanical and natural ventilation systems have developed separately. Naturally, the next step in this development is the development of ventilation concepts that utilize and combine the best features from each system to create a new type of ventilation system- Hybrid Ventilation. ....... The hybrid ventilation concepts, design challenges and principles are discussed and illustrated by four building examples.......For many years mechanical and natural ventilation systems have developed separately. Naturally, the next step in this development is the development of ventilation concepts that utilize and combine the best features from each system to create a new type of ventilation system- Hybrid Ventilation...

  6. Soft sets combined with interval valued intuitionistic fuzzy sets of type-2 and rough sets

    Directory of Open Access Journals (Sweden)

    Anjan Mukherjee

    2015-03-01

    Full Text Available Fuzzy set theory, rough set theory and soft set theory are all mathematical tools dealing with uncertainties. The concept of type-2 fuzzy sets was introduced by Zadeh in 1975 which was extended to interval valued intuitionistic fuzzy sets of type-2 by the authors.This paper is devoted to the discussions of the combinations of interval valued intuitionistic sets of type-2, soft sets and rough sets.Three different types of new hybrid models, namely-interval valued intuitionistic fuzzy soft sets of type-2, soft rough interval valued intuitionistic fuzzy sets of type-2 and soft interval valued intuitionistic fuzzy rough sets of type-2 are proposed and their properties are derived.

  7. Hybrid machine learning technique for forecasting Dhaka stock market timing decisions.

    Science.gov (United States)

    Banik, Shipra; Khodadad Khan, A F M; Anwer, Mohammad

    2014-01-01

    Forecasting stock market has been a difficult job for applied researchers owing to nature of facts which is very noisy and time varying. However, this hypothesis has been featured by several empirical experiential studies and a number of researchers have efficiently applied machine learning techniques to forecast stock market. This paper studied stock prediction for the use of investors. It is always true that investors typically obtain loss because of uncertain investment purposes and unsighted assets. This paper proposes a rough set model, a neural network model, and a hybrid neural network and rough set model to find optimal buy and sell of a share on Dhaka stock exchange. Investigational findings demonstrate that our proposed hybrid model has higher precision than the single rough set model and the neural network model. We believe this paper findings will help stock investors to decide about optimal buy and/or sell time on Dhaka stock exchange.

  8. INNOVATIVE HYBRID GAS/ELECTRIC CHILLER COGENERATION

    Energy Technology Data Exchange (ETDEWEB)

    Todd Kollross; Mike Connolly

    2004-06-30

    Engine-driven chillers are quickly gaining popularity in the market place (increased from 7,000 tons in 1994 to greater than 50,000 tons in 1998) due to their high efficiency, electric peak shaving capability, and overall low operating cost. The product offers attractive economics (5 year pay back or less) in many applications, based on areas cooling requirements and electric pricing structure. When heat is recovered and utilized from the engine, the energy resource efficiency of a natural gas engine-driven chiller is higher than all competing products. As deregulation proceeds, real time pricing rate structures promise high peak demand electric rates, but low off-peak electric rates. An emerging trend with commercial building owners and managers who require air conditioning today is to reduce their operating costs by installing hybrid chiller systems that combine gas and electric units. Hybrid systems not only reduce peak electric demand charges, but also allow customers to level their energy load profiles and select the most economical energy source, gas or electricity, from hour to hour. Until recently, however, all hybrid systems incorporated one or more gas-powered chillers (engine driven and/or absorption) and one or more conventional electric units. Typically, the cooling capacity of hybrid chiller plants ranges from the hundreds to thousands of refrigeration tons, with multiple chillers affording the user a choice of cooling systems. But this flexibility is less of an option for building operators who have limited room for equipment. To address this technology gap, a hybrid chiller was developed by Alturdyne that combines a gas engine, an electric motor and a refrigeration compressor within a single package. However, this product had not been designed to realize the full features and benefits possible by combining an engine, motor/generator and compressor. The purpose of this project is to develop a new hybrid chiller that can (1) reduce end-user energy

  9. Optimizing hybrid spreading in metapopulations.

    Science.gov (United States)

    Zhang, Changwang; Zhou, Shi; Miller, Joel C; Cox, Ingemar J; Chain, Benjamin M

    2015-04-29

    Epidemic spreading phenomena are ubiquitous in nature and society. Examples include the spreading of diseases, information, and computer viruses. Epidemics can spread by local spreading, where infected nodes can only infect a limited set of direct target nodes and global spreading, where an infected node can infect every other node. In reality, many epidemics spread using a hybrid mixture of both types of spreading. In this study we develop a theoretical framework for studying hybrid epidemics, and examine the optimum balance between spreading mechanisms in terms of achieving the maximum outbreak size. We show the existence of critically hybrid epidemics where neither spreading mechanism alone can cause a noticeable spread but a combination of the two spreading mechanisms would produce an enormous outbreak. Our results provide new strategies for maximising beneficial epidemics and estimating the worst outcome of damaging hybrid epidemics.

  10. Hybrid-secure MPC 

    DEFF Research Database (Denmark)

    Lucas, Christoph; Raub, Dominik; Maurer, Ueli

    2010-01-01

    of the adversary, without being aware of the actual adversarial setting. Thus, hybrid-secure MPC protocols allow for graceful degradation of security. We present a hybrid-secure MPC protocol that provides an optimal trade-off between IT robustness and computational privacy: For any robustness parameter ρ ... obtain one MPC protocol that is simultaneously IT secure with robustness for up to t ≤ ρ actively corrupted parties, IT secure with fairness (no robustness) for up to t ... in the universal composability (UC) framework (based on a network of secure channels, a broadcast channel, and a common reference string). It achieves the bound on the trade-off between robustness and privacy shown by Ishai et al. [CRYPTO'06] and Katz [STOC'07], the bound on fairness shown by Cleve [STOC'86...

  11. Patch layout generation by detecting feature networks

    KAUST Repository

    Cao, Yuanhao

    2015-02-01

    The patch layout of 3D surfaces reveals the high-level geometric and topological structures. In this paper, we study the patch layout computation by detecting and enclosing feature loops on surfaces. We present a hybrid framework which combines several key ingredients, including feature detection, feature filtering, feature curve extension, patch subdivision and boundary smoothing. Our framework is able to compute patch layouts through concave features as previous approaches, but also able to generate nice layouts through smoothing regions. We demonstrate the effectiveness of our framework by comparing with the state-of-the-art methods.

  12. Multi-Objective Particle Swarm Optimization Approach for Cost-Based Feature Selection in Classification.

    Science.gov (United States)

    Zhang, Yong; Gong, Dun-Wei; Cheng, Jian

    2017-01-01

    Feature selection is an important data-preprocessing technique in classification problems such as bioinformatics and signal processing. Generally, there are some situations where a user is interested in not only maximizing the classification performance but also minimizing the cost that may be associated with features. This kind of problem is called cost-based feature selection. However, most existing feature selection approaches treat this task as a single-objective optimization problem. This paper presents the first study of multi-objective particle swarm optimization (PSO) for cost-based feature selection problems. The task of this paper is to generate a Pareto front of nondominated solutions, that is, feature subsets, to meet different requirements of decision-makers in real-world applications. In order to enhance the search capability of the proposed algorithm, a probability-based encoding technology and an effective hybrid operator, together with the ideas of the crowding distance, the external archive, and the Pareto domination relationship, are applied to PSO. The proposed PSO-based multi-objective feature selection algorithm is compared with several multi-objective feature selection algorithms on five benchmark datasets. Experimental results show that the proposed algorithm can automatically evolve a set of nondominated solutions, and it is a highly competitive feature selection method for solving cost-based feature selection problems.

  13. Functional Abstraction of Stochastic Hybrid Systems

    NARCIS (Netherlands)

    Bujorianu, L.M.; Blom, Henk A.P.; Hermanns, H.

    2006-01-01

    The verification problem for stochastic hybrid systems is quite difficult. One method to verify these systems is stochastic reachability analysis. Concepts of abstractions for stochastic hybrid systems are needed to ease the stochastic reachability analysis. In this paper, we set up different ways

  14. Counting SET-free sets

    OpenAIRE

    Harman, Nate

    2016-01-01

    We consider the following counting problem related to the card game SET: How many $k$-element SET-free sets are there in an $n$-dimensional SET deck? Through a series of algebraic reformulations and reinterpretations, we show the answer to this question satisfies two polynomiality conditions.

  15. Hybrid Arrays for Chemical Sensing

    Science.gov (United States)

    Kramer, Kirsten E.; Rose-Pehrsson, Susan L.; Johnson, Kevin J.; Minor, Christian P.

    intelligence and robotics, all share the same essential data fusion challenges. The design of a hybrid sensor array should draw on this extended body of knowledge. In this chapter, various techniques for data preprocessing, feature extraction, feature selection, and modeling of sensor data will be introduced and illustrated with data fusion approaches that have been implemented in applications involving data from hybrid arrays. The example systems discussed in this chapter involve the development of prototype sensor networks for damage control event detection aboard US Navy vessels and the development of analysis algorithms to combine multiple sensing techniques for enhanced remote detection of unexploded ordnance (UXO) in both ground surveys and wide area assessments.

  16. Featuring animacy

    Directory of Open Access Journals (Sweden)

    Elizabeth Ritter

    2015-01-01

    Full Text Available Algonquian languages are famous for their animacy-based grammatical properties—an animacy based noun classification system and direct/inverse system which gives rise to animacy hierarchy effects in the determination of verb agreement. In this paper I provide new evidence for the proposal that the distinctive properties of these languages is due to the use of participant-based features, rather than spatio-temporal ones, for both nominal and verbal functional categories (Ritter & Wiltschko 2009, 2014. Building on Wiltschko (2012, I develop a formal treatment of the Blackfoot aspectual system that assumes a category Inner Aspect (cf. MacDonald 2008, Travis 1991, 2010. Focusing on lexical aspect in Blackfoot, I demonstrate that the classification of both nouns (Seinsarten and verbs (Aktionsarten is based on animacy, rather than boundedness, resulting in a strikingly different aspectual system for both categories. 

  17. Design comparison of single phase outer and inner-rotor hybrid excitation flux switching motor for hybrid electric vehicles

    Science.gov (United States)

    Mazlan, Mohamed Mubin Aizat; Sulaiman, Erwan; Husin, Zhafir Aizat; Othman, Syed Muhammad Naufal Syed; Khan, Faisal

    2015-05-01

    In hybrid excitation machines (HEMs), there are two main flux sources which are permanent magnet (PM) and field excitation coil (FEC). These HEMs have better features when compared with the interior permanent magnet synchronous machines (IPMSM) used in conventional hybrid electric vehicles (HEVs). Since all flux sources including PM, FEC and armature coils are located on the stator core, the rotor becomes a single piece structure similar with switch reluctance machine (SRM). The combined flux generated by PM and FEC established more excitation fluxes that are required to produce much higher torque of the motor. In addition, variable DC FEC can control the flux capabilities of the motor, thus the machine can be applied for high-speed motor drive system. In this paper, the comparisons of single-phase 8S-4P outer and inner rotor hybrid excitation flux switching machine (HEFSM) are presented. Initially, design procedures of the HEFSM including parts drawing, materials and conditions setting, and properties setting are explained. Flux comparisons analysis is performed to investigate the flux capabilities at various current densities. Then the flux linkages of PM with DC FEC of various DC FEC current densities are examined. Finally torque performances are analyzed at various armature and FEC current densities for both designs. As a result, the outer-rotor HEFSM has higher flux linkage of PM with DC FEC and higher average torque of approximately 10% when compared with inner-rotor HEFSM.

  18. Complex Topographic Feature Ontology Patterns

    Science.gov (United States)

    Varanka, Dalia E.; Jerris, Thomas J.

    2015-01-01

    Semantic ontologies are examined as effective data models for the representation of complex topographic feature types. Complex feature types are viewed as integrated relations between basic features for a basic purpose. In the context of topographic science, such component assemblages are supported by resource systems and found on the local landscape. Ontologies are organized within six thematic modules of a domain ontology called Topography that includes within its sphere basic feature types, resource systems, and landscape types. Context is constructed not only as a spatial and temporal setting, but a setting also based on environmental processes. Types of spatial relations that exist between components include location, generative processes, and description. An example is offered in a complex feature type ‘mine.’ The identification and extraction of complex feature types are an area for future research.

  19. Feature displacement interpolation

    DEFF Research Database (Denmark)

    Nielsen, Mads; Andresen, Per Rønsholt

    1998-01-01

    Given a sparse set of feature matches, we want to compute an interpolated dense displacement map. The application may be stereo disparity computation, flow computation, or non-rigid medical registration. Also estimation of missing image data, may be phrased in this framework. Since the features...... often are very sparse, the interpolation model becomes crucial. We show that a maximum likelihood estimation based on the covariance properties (Kriging) show properties more expedient than methods such as Gaussian interpolation or Tikhonov regularizations, also including scale......-selection. The computational complexities are identical. We apply the maximum likelihood interpolation to growth analysis of the mandibular bone. Here, the features used are the crest-lines of the object surface....

  20. Hybrid technology for regional railcars

    Energy Technology Data Exchange (ETDEWEB)

    Mueller, Christoph [DVV Eurailpress, Hamburg (Germany)

    2012-05-15

    It is possible to reduce the fuel consumed by diesel railcars operating short-distance regional services by making use of newly developed hybrid technology. Voith Turbo is setting out to produce evidence of that through two completely different projects. (orig.)

  1. Hybrid Qualifications

    DEFF Research Database (Denmark)

    Against the background of increasing qualification needs there is a growing awareness of the challenge to widen participation in processes of skill formation and competence development. At the same time, the issue of permeability between vocational education and training (VET) and general education...... has turned out as a major focus of European education and training policies and certainly is a crucial principle underlying the European Qualifications Framework (EQF). In this context, «hybrid qualifications» (HQ) may be seen as an interesting approach to tackle these challenges as they serve «two...

  2. Hybrid Gear

    Science.gov (United States)

    Handschuh, Robert F. (Inventor); Roberts, Gary D. (Inventor)

    2016-01-01

    A hybrid gear consisting of metallic outer rim with gear teeth and metallic hub in combination with a composite lay up between the shaft interface (hub) and gear tooth rim is described. The composite lay-up lightens the gear member while having similar torque carrying capability and it attenuates the impact loading driven noise/vibration that is typical in gear systems. The gear has the same operational capability with respect to shaft speed, torque, and temperature as an all-metallic gear as used in aerospace gear design.

  3. Intuitionistic hybrid logic

    DEFF Research Database (Denmark)

    Braüner, Torben

    2011-01-01

    Intuitionistic hybrid logic is hybrid modal logic over an intuitionistic logic basis instead of a classical logical basis. In this short paper we introduce intuitionistic hybrid logic and we give a survey of work in the area.......Intuitionistic hybrid logic is hybrid modal logic over an intuitionistic logic basis instead of a classical logical basis. In this short paper we introduce intuitionistic hybrid logic and we give a survey of work in the area....

  4. Automatic sets and Delone sets

    International Nuclear Information System (INIS)

    Barbe, A; Haeseler, F von

    2004-01-01

    Automatic sets D part of Z m are characterized by having a finite number of decimations. They are equivalently generated by fixed points of certain substitution systems, or by certain finite automata. As examples, two-dimensional versions of the Thue-Morse, Baum-Sweet, Rudin-Shapiro and paperfolding sequences are presented. We give a necessary and sufficient condition for an automatic set D part of Z m to be a Delone set in R m . The result is then extended to automatic sets that are defined as fixed points of certain substitutions. The morphology of automatic sets is discussed by means of examples

  5. Optimal Design for Hybrid Ratio of Carbon/Basalt Hybrid Fiber Reinforced Resin Matrix Composites

    Directory of Open Access Journals (Sweden)

    XU Hong

    2017-08-01

    Full Text Available The optimum hybrid ratio range of carbon/basalt hybrid fiber reinforced resin composites was studied. Hybrid fiber composites with nine different hybrid ratios were prepared before tensile test.According to the structural features of plain weave, the unit cell's performance parameters were calculated. Finite element model was established by using SHELL181 in ANSYS. The simulated values of the sample stiffness in the model were approximately similar to the experimental ones. The stress nephogram shows that there is a critical hybrid ratio which divides the failure mechanism of HFRP into single failure state and multiple failure state. The tensile modulus, strength and limit tensile strain of HFRP with 45% resin are simulated by finite element method. The result shows that the tensile modulus of HFRP with 60% hybrid ratio increases by 93.4% compared with basalt fiber composites (BFRP, and the limit tensile strain increases by 11.3% compared with carbon fiber composites(CFRP.

  6. A survey of hybrid Unmanned Aerial Vehicles

    Science.gov (United States)

    Saeed, Adnan S.; Younes, Ahmad Bani; Cai, Chenxiao; Cai, Guowei

    2018-04-01

    This article presents a comprehensive overview on the recent advances of miniature hybrid Unmanned Aerial Vehicles (UAVs). For now, two conventional types, i.e., fixed-wing UAV and Vertical Takeoff and Landing (VTOL) UAV, dominate the miniature UAVs. Each type has its own inherent limitations on flexibility, payload, flight range, cruising speed, takeoff and landing requirements and endurance. Enhanced popularity and interest are recently gained by the newer type, named hybrid UAV, that integrates the beneficial features of both conventional ones. In this survey paper, a systematic categorization method for the hybrid UAV's platform designs is introduced, first presenting the technical features and representative examples. Next, the hybrid UAV's flight dynamics model and flight control strategies are explained addressing several representative modeling and control work. In addition, key observations, existing challenges and conclusive remarks based on the conducted review are discussed accordingly.

  7. Hybrid nanostructures: synthesis, morphology and functional properties

    International Nuclear Information System (INIS)

    Povolotskaya, A V; Povolotskiy, A V; Manshina, A A

    2015-01-01

    Hybrid nanostructures representing combinations of different materials and possessing properties that are absent in separate components forming the hybrid are discussed. Particular attention is given to hybrid structures containing plasmonic and magnetic nanoparticles, methods of their synthesis and the relationship between the composition, structure and properties. The functional features of the hybrid nanomaterials of various morphology (with core–shell structures, with encapsulated metal nanoparticles and with metal nanoparticles on the surface) are considered. The unique properties of these hybrid materials are demonstrated, which are of interest for solving problems of catalysis and photocatalysis, detecting impurities in various media, in vivo visualization, bioanalysis, as well as for the design of optical labels and multifunctional diagnostic nanoplatforms. The bibliography includes 182 references

  8. Review of laser hybrid welding

    DEFF Research Database (Denmark)

    Bagger, Claus

    2004-01-01

    In this artucle an overview og the hybrid welding process is given. After a short historic overview, a review of the fundamental phenomenon taking place when a laser (CO2 or Nd:YAG) interacts in the same molten pool as a more conventional source of energy, e.g. tungsten in-active gas, plasma......, or metal inactive gas/metal active gas.This is followed by reports of how the many process parameters governing the hybrid welding process can be set and how the choice of secondary energy source, shielding gas, etc. can affect the overall welding process....

  9. Hybrid Odontogenic Lesion: A Rare Entity

    Directory of Open Access Journals (Sweden)

    Reza Imani

    2017-03-01

    Full Text Available Hybrid tumors are very rare tumors composed of two different tumor entities, each of which conforms to an exactly defined tumor category. A 14-year-old boy was referred for an intraosseous painless lesion with a histopathological feature of multiple odontogenic lesions including calcifying odontogenic cyst, complex odontoma and ameloblastic fibro-odontoma. The final diagnosis considered to be a hybrid odontogenic lesion.

  10. Multiple target sound quality balance for hybrid electric powertrain noise

    Science.gov (United States)

    Mosquera-Sánchez, J. A.; Sarrazin, M.; Janssens, K.; de Oliveira, L. P. R.; Desmet, W.

    2018-01-01

    The integration of the electric motor to the powertrain in hybrid electric vehicles (HEVs) presents acoustic stimuli that elicit new perceptions. The large number of spectral components, as well as the wider bandwidth of this sort of noises, pose new challenges to current noise, vibration and harshness (NVH) approaches. This paper presents a framework for enhancing the sound quality (SQ) of the hybrid electric powertrain noise perceived inside the passenger compartment. Compared with current active sound quality control (ASQC) schemes, where the SQ improvement is just an effect of the control actions, the proposed technique features an optimization stage, which enables the NVH specialist to actively implement the amplitude balance of the tones that better fits into the auditory expectations. Since Loudness, Roughness, Sharpness and Tonality are the most relevant SQ metrics for interior HEV noise, they are used as performance metrics in the concurrent optimization analysis, which, eventually, drives the control design method. Thus, multichannel active sound profiling systems that feature cross-channel compensation schemes are guided by the multi-objective optimization stage, by means of optimal sets of amplitude gain factors that can be implemented at each single sensor location, while minimizing cross-channel effects that can either degrade the original SQ condition, or even hinder the implementation of independent SQ targets. The proposed framework is verified experimentally, with realistic stationary hybrid electric powertrain noise, showing SQ enhancement for multiple locations within a scaled vehicle mock-up. The results show total success rates in excess of 90%, which indicate that the proposed method is promising, not only for the improvement of the SQ of HEV noise, but also for a variety of periodic disturbances with similar features.

  11. Hybridized Tetraquarks

    CERN Document Server

    Esposito, A.; Polosa, A.D.

    2016-01-01

    We propose a new interpretation of the neutral and charged X, Z exotic hadron resonances. Hybridized-tetraquarks are neither purely compact tetraquark states nor bound or loosely bound molecules. The latter would require a negative or zero binding energy whose counterpart in h-tetraquarks is a positive quantity. The formation mechanism of this new class of hadrons is inspired by that of Feshbach metastable states in atomic physics. The recent claim of an exotic resonance in the Bs pi+- channel by the D0 collaboration and the negative result presented subsequently by the LHCb collaboration are understood in this scheme, together with a considerable portion of available data on X, Z particles. Considerations on a state with the same quantum numbers as the X(5568) are also made.

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

    Directory of Open Access Journals (Sweden)

    Carlos Fernández

    2017-01-01

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

  13. Chemical sensors are hybrid-input memristors

    Science.gov (United States)

    Sysoev, V. I.; Arkhipov, V. E.; Okotrub, A. V.; Pershin, Y. V.

    2018-04-01

    Memristors are two-terminal electronic devices whose resistance depends on the history of input signal (voltage or current). Here we demonstrate that the chemical gas sensors can be considered as memristors with a generalized (hybrid) input, namely, with the input consisting of the voltage, analyte concentrations and applied temperature. The concept of hybrid-input memristors is demonstrated experimentally using a single-walled carbon nanotubes chemical sensor. It is shown that with respect to the hybrid input, the sensor exhibits some features common with memristors such as the hysteretic input-output characteristics. This different perspective on chemical gas sensors may open new possibilities for smart sensor applications.

  14. Hybrid Logical Analyses of the Ambient Calculus

    DEFF Research Database (Denmark)

    Bolander, Thomas; Hansen, René Rydhof

    2007-01-01

    In this paper, hybrid logic is used to formulate a rational reconstruction of a previously published control flow analysis for the mobile ambients calculus and we further show how a more precise flow-sensitive analysis, that takes the ordering of action sequences into account, can be formulated...... in a natural way. We show that hybrid logic is very well suited to express the semantic structure of the ambient calculus and how features of hybrid logic can be exploited to reduce the "administrative overhead" of the analysis specification and thus simplify it. Finally, we use HyLoTab, a fully automated...

  15. Hybrid Ceramic Matrix Fibrous Composites: an Overview

    Science.gov (United States)

    Naslain, R.

    2011-10-01

    Ceramic-Matrix Composites (CMCs) consist of a ceramic fiber architecture in a ceramic matrix, bonded together through a thin interphase. The present contribution is limited to non-oxide CMCs. Their constituents being oxidation-prone, they are protected by external coatings. We state here that CMCs display a hybrid feature, when at least one of their components is not homogeneous from a chemical or microstructural standpoint. Hybrid fiber architectures are used to tailor the mechanical or thermal CMC-properties whereas hybrid interphases, matrices and coatings to improve CMC resistance to aggressive environments.

  16. Hybrid Ceramic Matrix Fibrous Composites: an Overview

    International Nuclear Information System (INIS)

    Naslain, R

    2011-01-01

    Ceramic-Matrix Composites (CMCs) consist of a ceramic fiber architecture in a ceramic matrix, bonded together through a thin interphase. The present contribution is limited to non-oxide CMCs. Their constituents being oxidation-prone, they are protected by external coatings. We state here that CMCs display a hybrid feature, when at least one of their components is not homogeneous from a chemical or microstructural standpoint. Hybrid fiber architectures are used to tailor the mechanical or thermal CMC-properties whereas hybrid interphases, matrices and coatings to improve CMC resistance to aggressive environments.

  17. Identifying the distinct features of geometric structures for hole trapping to generate radicals on rutile TiO₂(110) in photooxidation using density functional theory calculations with hybrid functional.

    Science.gov (United States)

    Wang, Dong; Wang, Haifeng; Hu, P

    2015-01-21

    Using density functional theory calculations with HSE 06 functional, we obtained the structures of spin-polarized radicals on rutile TiO2(110), which is crucial to understand the photooxidation at the atomic level, and further calculate the thermodynamic stabilities of these radicals. By analyzing the results, we identify the structural features for hole trapping in the system, and reveal the mutual effects among the geometric structures, the energy levels of trapped hole states and their hole trapping capacities. Furthermore, the results from HSE 06 functional are compared to those from DFT + U and the stability trend of radicals against the number of slabs is tested. The effect of trapped holes on two important steps of the oxygen evolution reaction, i.e. water dissociation and the oxygen removal, is investigated and discussed.

  18. Hybrid spectral CT reconstruction.

    Directory of Open Access Journals (Sweden)

    Darin P Clark

    Full Text Available Current photon counting x-ray detector (PCD technology faces limitations associated with spectral fidelity and photon starvation. One strategy for addressing these limitations is to supplement PCD data with high-resolution, low-noise data acquired with an energy-integrating detector (EID. In this work, we propose an iterative, hybrid reconstruction technique which combines the spectral properties of PCD data with the resolution and signal-to-noise characteristics of EID data. Our hybrid reconstruction technique is based on an algebraic model of data fidelity which substitutes the EID data into the data fidelity term associated with the PCD reconstruction, resulting in a joint reconstruction problem. Within the split Bregman framework, these data fidelity constraints are minimized subject to additional constraints on spectral rank and on joint intensity-gradient sparsity measured between the reconstructions of the EID and PCD data. Following a derivation of the proposed technique, we apply it to the reconstruction of a digital phantom which contains realistic concentrations of iodine, barium, and calcium encountered in small-animal micro-CT. The results of this experiment suggest reliable separation and detection of iodine at concentrations ≥ 5 mg/ml and barium at concentrations ≥ 10 mg/ml in 2-mm features for EID and PCD data reconstructed with inherent spatial resolutions of 176 μm and 254 μm, respectively (point spread function, FWHM. Furthermore, hybrid reconstruction is demonstrated to enhance spatial resolution within material decomposition results and to improve low-contrast detectability by as much as 2.6 times relative to reconstruction with PCD data only. The parameters of the simulation experiment are based on an in vivo micro-CT experiment conducted in a mouse model of soft-tissue sarcoma. Material decomposition results produced from this in vivo data demonstrate the feasibility of distinguishing two K-edge contrast agents with

  19. Hybrid spectral CT reconstruction

    Science.gov (United States)

    Clark, Darin P.

    2017-01-01

    Current photon counting x-ray detector (PCD) technology faces limitations associated with spectral fidelity and photon starvation. One strategy for addressing these limitations is to supplement PCD data with high-resolution, low-noise data acquired with an energy-integrating detector (EID). In this work, we propose an iterative, hybrid reconstruction technique which combines the spectral properties of PCD data with the resolution and signal-to-noise characteristics of EID data. Our hybrid reconstruction technique is based on an algebraic model of data fidelity which substitutes the EID data into the data fidelity term associated with the PCD reconstruction, resulting in a joint reconstruction problem. Within the split Bregman framework, these data fidelity constraints are minimized subject to additional constraints on spectral rank and on joint intensity-gradient sparsity measured between the reconstructions of the EID and PCD data. Following a derivation of the proposed technique, we apply it to the reconstruction of a digital phantom which contains realistic concentrations of iodine, barium, and calcium encountered in small-animal micro-CT. The results of this experiment suggest reliable separation and detection of iodine at concentrations ≥ 5 mg/ml and barium at concentrations ≥ 10 mg/ml in 2-mm features for EID and PCD data reconstructed with inherent spatial resolutions of 176 μm and 254 μm, respectively (point spread function, FWHM). Furthermore, hybrid reconstruction is demonstrated to enhance spatial resolution within material decomposition results and to improve low-contrast detectability by as much as 2.6 times relative to reconstruction with PCD data only. The parameters of the simulation experiment are based on an in vivo micro-CT experiment conducted in a mouse model of soft-tissue sarcoma. Material decomposition results produced from this in vivo data demonstrate the feasibility of distinguishing two K-edge contrast agents with a spectral

  20. Temporal feature integration for music genre classification

    DEFF Research Database (Denmark)

    Meng, Anders; Ahrendt, Peter; Larsen, Jan

    2007-01-01

    , but they capture neither the temporal dynamics nor dependencies among the individual feature dimensions. Here, a multivariate autoregressive feature model is proposed to solve this problem for music genre classification. This model gives two different feature sets, the diagonal autoregressive (DAR......) and multivariate autoregressive (MAR) features which are compared against the baseline mean-variance as well as two other temporal feature integration techniques. Reproducibility in performance ranking of temporal feature integration methods were demonstrated using two data sets with five and eleven music genres...

  1. Continuity controlled Hybrid Automata

    NARCIS (Netherlands)

    Bergstra, J.A.; Middelburg, C.A.

    We investigate the connections between the process algebra for hybrid systems of Bergstra and Middelburg and the formalism of hybrid automata of Henzinger et al. We give interpretations of hybrid automata in the process algebra for hybrid systems and compare them with the standard interpretation

  2. Continuity Controlled Hybrid Automata

    NARCIS (Netherlands)

    Bergstra, J.A.; Middelburg, C.A.

    2004-01-01

    We investigate the connections between the process algebra for hybrid systems of Bergstra and Middelburg and the formalism of hybrid automata of Henzinger et al. We give interpretations of hybrid automata in the process algebra for hybrid systems and compare them with the standard interpretation of

  3. Continuity controlled hybrid automata

    NARCIS (Netherlands)

    Bergstra, J.A.; Middelburg, C.A.

    2004-01-01

    We investigate the connections between the process algebra for hybrid systems of Bergstra and Middelburg and the formalism of hybrid automata of Henzinger et al. We give interpretations of hybrid automata in the process algebra for hybrid systems and compare them with the standard interpretation of

  4. Continuity controlled hybrid automata

    NARCIS (Netherlands)

    Bergstra, J.A.; Middelburg, C.A.

    2006-01-01

    We investigate the connections between the process algebra for hybrid systems of Bergstra and Middelburg and the formalism of hybrid automata of Henzinger et al. We give interpretations of hybrid automata in the process algebra for hybrid systems and compare them with the standard interpretation of

  5. Hybrid reactors: Nuclear breeding or energy production?

    International Nuclear Information System (INIS)

    Piera, Mireia; Lafuente, Antonio; Abanades, Alberto; Martinez-Val, J.M.

    2010-01-01

    After reviewing the long-standing tradition on hybrid research, an assessment model is presented in order to characterize the hybrid performance under different objectives. In hybrids, neutron multiplication in the subcritical blanket plays a major role, not only for energy production and nuclear breeding, but also for tritium breeding, which is fundamental requirement in fusion-fission hybrids. All three objectives are better achieved with high values of the neutron multiplication factor (k-eff) with the obvious and fundamental limitation that it cannot reach criticality under any event, particularly, in the case of a loss of coolant accident. This limitation will be very important in the selection of the coolant. Some general considerations will be proposed, as guidelines for assessing the hybrid potential in a given scenario. Those guidelines point out that hybrids can be of great interest for the future of nuclear energy in a framework of Sustainable Development, because they can contribute to the efficient exploitation of nuclear fuels, with very high safety features. Additionally, a proposal is presented on a blanket specially suited for fusion-fission hybrids, although this reactor concept is still under review, and new work is needed for identifying the most suitable blanket composition, which can vary depending on the main objective of the hybrid.

  6. Hybrid pine for tough sites

    International Nuclear Information System (INIS)

    Davidson, W.H.

    1994-01-01

    A test planting of 30 first- and second-generation pitch x loblolly pine (pinus rigida x P. taeda) hybrids was established on a West Virginia minesoil in 1985. The site was considered orphaned because earlier attempts at revegetation were unsuccessful. The soil was acid (pH 4.6), lacking in nutrients, and compacted. Vegetation present at the time of planting consisted of a sparse cover of tall fescue (Festuca arundinacea) and poverty grass (Danthonia spicata) and a few sourwood (Oxydendrum arboreum) and mountain laurel (Kalmia latifolia) seedlings. In the planting trial, 30 different hybrids were set out in 4 tree linear plots replicated 5 times. The seedlings had been grown in containers for 1 yr before outplanting. Evaluations made after 6 growing seasons showed overall plantation survival was 93%; six hybrids and one open-pollinated cross survived 100%. Individual tree heights ranged from 50 to 425 cm with a plantation average of 235 cm (7.7 ft). Eleven of the hybrids had average heights that exceeded the plantation average. Another test planting of tree and shrub species on this site has very poor survival. Therefore, pitch x loblolly hybrid pine can be recommended for reclaiming this and similar sites

  7. Corporate Hybrid Bonds

    OpenAIRE

    Ahlberg, Johan; Jansson, Anton

    2016-01-01

    Hybrid securities do not constitute a new phenomenon in the Swedish capital markets. Most commonly, hybrids issued by Swedish real estate companies in recent years are preference shares. Corporate hybrid bonds on the other hand may be considered as somewhat of a new-born child in the family of hybrid instruments. These do, as all other hybrid securities, share some equity-like and some debt-like characteristics. Nevertheless, since 2013 the interest for the instrument has grown rapidly and ha...

  8. Parcels and Land Ownership, This data set consists of digital map files containing parcel-level cadastral information obtained from property descriptions. Cadastral features contained in the data set include real property boundary lines, rights-of-way boundaries, property dimensions, Published in Not Provided, 1:2400 (1in=200ft) scale, Racine County Government.

    Data.gov (United States)

    NSGIC Local Govt | GIS Inventory — Parcels and Land Ownership dataset current as of unknown. This data set consists of digital map files containing parcel-level cadastral information obtained from...

  9. Genomic networks of hybrid sterility.

    Directory of Open Access Journals (Sweden)

    Leslie M Turner

    2014-02-01

    Full Text Available Hybrid dysfunction, a common feature of reproductive barriers between species, is often caused by negative epistasis between loci ("Dobzhansky-Muller incompatibilities". The nature and complexity of hybrid incompatibilities remain poorly understood because identifying interacting loci that affect complex phenotypes is difficult. With subspecies in the early stages of speciation, an array of genetic tools, and detailed knowledge of reproductive biology, house mice (Mus musculus provide a model system for dissecting hybrid incompatibilities. Male hybrids between M. musculus subspecies often show reduced fertility. Previous studies identified loci and several X chromosome-autosome interactions that contribute to sterility. To characterize the genetic basis of hybrid sterility in detail, we used a systems genetics approach, integrating mapping of gene expression traits with sterility phenotypes and QTL. We measured genome-wide testis expression in 305 male F2s from a cross between wild-derived inbred strains of M. musculus musculus and M. m. domesticus. We identified several thousand cis- and trans-acting QTL contributing to expression variation (eQTL. Many trans eQTL cluster into eleven 'hotspots,' seven of which co-localize with QTL for sterility phenotypes identified in the cross. The number and clustering of trans eQTL-but not cis eQTL-were substantially lower when mapping was restricted to a 'fertile' subset of mice, providing evidence that trans eQTL hotspots are related to sterility. Functional annotation of transcripts with eQTL provides insights into the biological processes disrupted by sterility loci and guides prioritization of candidate genes. Using a conditional mapping approach, we identified eQTL dependent on interactions between loci, revealing a complex system of epistasis. Our results illuminate established patterns, including the role of the X chromosome in hybrid sterility. The integrated mapping approach we employed is

  10. Genomic networks of hybrid sterility.

    Science.gov (United States)

    Turner, Leslie M; White, Michael A; Tautz, Diethard; Payseur, Bret A

    2014-02-01

    Hybrid dysfunction, a common feature of reproductive barriers between species, is often caused by negative epistasis between loci ("Dobzhansky-Muller incompatibilities"). The nature and complexity of hybrid incompatibilities remain poorly understood because identifying interacting loci that affect complex phenotypes is difficult. With subspecies in the early stages of speciation, an array of genetic tools, and detailed knowledge of reproductive biology, house mice (Mus musculus) provide a model system for dissecting hybrid incompatibilities. Male hybrids between M. musculus subspecies often show reduced fertility. Previous studies identified loci and several X chromosome-autosome interactions that contribute to sterility. To characterize the genetic basis of hybrid sterility in detail, we used a systems genetics approach, integrating mapping of gene expression traits with sterility phenotypes and QTL. We measured genome-wide testis expression in 305 male F2s from a cross between wild-derived inbred strains of M. musculus musculus and M. m. domesticus. We identified several thousand cis- and trans-acting QTL contributing to expression variation (eQTL). Many trans eQTL cluster into eleven 'hotspots,' seven of which co-localize with QTL for sterility phenotypes identified in the cross. The number and clustering of trans eQTL-but not cis eQTL-were substantially lower when mapping was restricted to a 'fertile' subset of mice, providing evidence that trans eQTL hotspots are related to sterility. Functional annotation of transcripts with eQTL provides insights into the biological processes disrupted by sterility loci and guides prioritization of candidate genes. Using a conditional mapping approach, we identified eQTL dependent on interactions between loci, revealing a complex system of epistasis. Our results illuminate established patterns, including the role of the X chromosome in hybrid sterility. The integrated mapping approach we employed is applicable in a broad

  11. Hybrid XRF

    International Nuclear Information System (INIS)

    Heckel, J.

    2002-01-01

    Full text: In the last 10 years significant innovations of EDXRF, e.g. total reflection XRF or polarized beam XRF, were utilized in different industrial applications. The decrease of background within the spectra was the goal of these developments. Excellent detection limits and sensitivities demonstrate the success of these new techniques. Nevertheless, further improvements are possible by using Si drift detectors. These detectors allow the processing of input count rates up to 10 6 cps in comparison to 10 5 of Si(Li) detectors. New excitation optics are necessary to produce such count rates. One possibility is the use of doubly curved crystals between tube and sample. These crystals enable the reflection of the primary beam within the given solid angle (0.4π) of an end window tube to the sample. Using such brightness optics excellent sensitivities mainly for light elements are achievable. The combination of a BRAGG crystal as a wavelength dispersive component and a solid state detector as an energy dispersive component creates a new technique: hybrid XRF. Copyright (2002) Australian X-ray Analytical Association Inc. Copyright (2002) Australian X-ray Analytical Association Inc

  12. Shape Grammars for Innovative Hybrid Typological Design

    DEFF Research Database (Denmark)

    Al-kazzaz, Dhuha; Bridges, Alan; Chase, Scott Curland

    2010-01-01

    This paper describes a new methodology of deriving innovative hybrid designs using shape grammars of heterogeneous designs. The method is detailed within three phases of shape grammars: analysis, synthesis and evaluation. In the analysis phase, the research suggests that original rules of each...... design component are grouped in subclass rule sets to facilitate rule choices. Additionally, adding new hybrid rules to original rules expands the options available to the grammar user. In the synthesis phase, the research adopts state labels and markers to drive the design generation. The former...... is implemented with a user guide grammar to ensure hybridity in the generated design, while the latter aims to ensure feasible designs. Lastly evaluation criteria are added to measure the degree of innovation of the hybrid designs. This paper describes the derivation of hybrid minaret designs from a corpus...

  13. A Test Setup for Quality Assurance of Front End Hybrids

    CERN Document Server

    Axer, Markus; Camps, Clemens; Commichau, Volker; Flügge, Günter; Franke, Torsten; Hangarter, Klaus; Ilgin, Can; Mnich, Joachim; Niehusmann, Jan; Poettgens, Michael; Schorn, Peter; Schulte, Reiner; Struczinski, Wolfgang

    2001-01-01

    The APV Readout Control (ARC) Test Setup is a compact, cost efficient test and diagnostic tool which is suited for full operation and characterisation of FE hybrids and Si-Detector modules. This note gives an overview of the construction and the features of the test facility. Based on the ARC setup and the experience gained with one prototype FE hybrid, possible quality assurance scenarios for short and long term tests of FE hybrids are also presented.

  14. Hybrid logic on linear structures: expressivity and complexity

    NARCIS (Netherlands)

    Franceschet, M.; de Rijke, M.; Schlingoff, B.-H.

    2003-01-01

    We investigate expressivity and complexity of hybrid logics on linear structures. Hybrid logics are an enrichment of modal logics with certain first-order features which are algorithmically well behaved. Therefore, they are well suited for the specification of certain properties of computational

  15. Supermarket Refrigeration System - Benchmark for Hybrid System Control

    DEFF Research Database (Denmark)

    Sloth, Lars Finn; Izadi-Zamanabadi, Roozbeh; Wisniewski, Rafal

    2007-01-01

    This paper presents a supermarket refrigeration system as a benchmark for development of new ideas and a comparison of methods for hybrid systems' modeling and control. The benchmark features switch dynamics and discrete valued input making it a hybrid system, furthermore the outputs are subjected...

  16. A New Hybrid Method for Improving the Performance of Myocardial Infarction Prediction

    Directory of Open Access Journals (Sweden)

    Hojatollah Hamidi

    2016-06-01

    Full Text Available Abstract Introduction: Myocardial Infarction, also known as heart attack, normally occurs due to such causes as smoking, family history, diabetes, and so on. It is recognized as one of the leading causes of death in the world. Therefore, the present study aimed to evaluate the performance of classification models in order to predict Myocardial Infarction, using a feature selection method that includes Forward Selection and Genetic Algorithm. Materials & Methods: The Myocardial Infarction data set used in this study contains the information related to 519 visitors to Shahid Madani Specialized Hospital of Khorramabad, Iran. This data set includes 33 features. The proposed method includes a hybrid feature selection method in order to enhance the performance of classification algorithms. The first step of this method selects the features using Forward Selection. At the second step, the selected features were given to a genetic algorithm, in order to select the best features. Classification algorithms entail Ada Boost, Naïve Bayes, J48 decision tree and simpleCART are applied to the data set with selected features, for predicting Myocardial Infarction. Results: The best results have been achieved after applying the proposed feature selection method, which were obtained via simpleCART and J48 algorithms with the accuracies of 96.53% and 96.34%, respectively. Conclusion: Based on the results, the performances of classification algorithms are improved. So, applying the proposed feature selection method, along with classification algorithms seem to be considered as a confident method with respect to predicting the Myocardial Infarction.

  17. Using Leaf-level Hyperspectral Reflectance Data to Analyze Genetic Gain in CIMMYT Maize Hybrids

    Data.gov (United States)

    US Agency for International Development — A set of recent CIMMYT era hybrids - spanning from the early 1990s to the late 2000s - was analyzed. The hybrids were grown in four different environments in two...

  18. Textural features for image classification

    Science.gov (United States)

    Haralick, R. M.; Dinstein, I.; Shanmugam, K.

    1973-01-01

    Description of some easily computable textural features based on gray-tone spatial dependances, and illustration of their application in category-identification tasks of three different kinds of image data - namely, photomicrographs of five kinds of sandstones, 1:20,000 panchromatic aerial photographs of eight land-use categories, and ERTS multispectral imagery containing several land-use categories. Two kinds of decision rules are used - one for which the decision regions are convex polyhedra (a piecewise-linear decision rule), and one for which the decision regions are rectangular parallelpipeds (a min-max decision rule). In each experiment the data set was divided into two parts, a training set and a test set. Test set identification accuracy is 89% for the photomicrographs, 82% for the aerial photographic imagery, and 83% for the satellite imagery. These results indicate that the easily computable textural features probably have a general applicability for a wide variety of image-classification applications.

  19. Développement de la tomographie intra-vitale au K-edge avec la caméra à pixels hybrides XPAD3

    OpenAIRE

    Kronland-Martinet, C.

    2015-01-01

    The hybrid pixel camera XPAD3 integrated in the micro-CT PIXSCAN IIis a new devicedeveloped by the imXgam team at CPPM for which photon counting replaces charge integrationused in standard X-ray CT. This novel approach involves advantages, in particularthe absence of dark noise and the ability to set an energy threshold on each pixel of thedetected photons. This features has been exploited during this thesis work for standardsmall animal preclinical imaging and permitted to establish the fais...

  20. Identifying significant environmental features using feature recognition.

    Science.gov (United States)

    2015-10-01

    The Department of Environmental Analysis at the Kentucky Transportation Cabinet has expressed an interest in feature-recognition capability because it may help analysts identify environmentally sensitive features in the landscape, : including those r...

  1. Hybrid Management in Hospitals

    DEFF Research Database (Denmark)

    Byrkjeflot, Haldor; Jespersen, Peter Kragh

    2010-01-01

    Artiklen indeholder et litteraturbaseret studium af ledelsesformer i sygehuse, hvor sundhedsfaglig ledelse og generel ledelse mikses til hybride ledelsesformer......Artiklen indeholder et litteraturbaseret studium af ledelsesformer i sygehuse, hvor sundhedsfaglig ledelse og generel ledelse mikses til hybride ledelsesformer...

  2. Hydraulic Hybrid Vehicles

    Science.gov (United States)

    EPA and the United Parcel Service (UPS) have developed a hydraulic hybrid delivery vehicle to explore and demonstrate the environmental benefits of the hydraulic hybrid for urban pick-up and delivery fleets.

  3. Hybrid Filter Membrane

    Science.gov (United States)

    Laicer, Castro; Rasimick, Brian; Green, Zachary

    2012-01-01

    Cabin environmental control is an important issue for a successful Moon mission. Due to the unique environment of the Moon, lunar dust control is one of the main problems that significantly diminishes the air quality inside spacecraft cabins. Therefore, this innovation was motivated by NASA s need to minimize the negative health impact that air-suspended lunar dust particles have on astronauts in spacecraft cabins. It is based on fabrication of a hybrid filter comprising nanofiber nonwoven layers coated on porous polymer membranes with uniform cylindrical pores. This design results in a high-efficiency gas particulate filter with low pressure drop and the ability to be easily regenerated to restore filtration performance. A hybrid filter was developed consisting of a porous membrane with uniform, micron-sized, cylindrical pore channels coated with a thin nanofiber layer. Compared to conventional filter media such as a high-efficiency particulate air (HEPA) filter, this filter is designed to provide high particle efficiency, low pressure drop, and the ability to be regenerated. These membranes have well-defined micron-sized pores and can be used independently as air filters with discreet particle size cut-off, or coated with nanofiber layers for filtration of ultrafine nanoscale particles. The filter consists of a thin design intended to facilitate filter regeneration by localized air pulsing. The two main features of this invention are the concept of combining a micro-engineered straight-pore membrane with nanofibers. The micro-engineered straight pore membrane can be prepared with extremely high precision. Because the resulting membrane pores are straight and not tortuous like those found in conventional filters, the pressure drop across the filter is significantly reduced. The nanofiber layer is applied as a very thin coating to enhance filtration efficiency for fine nanoscale particles. Additionally, the thin nanofiber coating is designed to promote capture of

  4. Mesoscale hybrid calibration artifact

    Science.gov (United States)

    Tran, Hy D.; Claudet, Andre A.; Oliver, Andrew D.

    2010-09-07

    A mesoscale calibration artifact, also called a hybrid artifact, suitable for hybrid dimensional measurement and the method for make the artifact. The hybrid artifact has structural characteristics that make it suitable for dimensional measurement in both vision-based systems and touch-probe-based systems. The hybrid artifact employs the intersection of bulk-micromachined planes to fabricate edges that are sharp to the nanometer level and intersecting planes with crystal-lattice-defined angles.

  5. Hermes: Seamless delivery of containerized bioinformatics workflows in hybrid cloud (HTC environments

    Directory of Open Access Journals (Sweden)

    Athanassios M. Kintsakis

    2017-01-01

    Full Text Available Hermes introduces a new “describe once, run anywhere” paradigm for the execution of bioinformatics workflows in hybrid cloud environments. It combines the traditional features of parallelization-enabled workflow management systems and of distributed computing platforms in a container-based approach. It offers seamless deployment, overcoming the burden of setting up and configuring the software and network requirements. Most importantly, Hermes fosters the reproducibility of scientific workflows by supporting standardization of the software execution environment, thus leading to consistent scientific workflow results and accelerating scientific output.

  6. Hermes: Seamless delivery of containerized bioinformatics workflows in hybrid cloud (HTC) environments

    Science.gov (United States)

    Kintsakis, Athanassios M.; Psomopoulos, Fotis E.; Symeonidis, Andreas L.; Mitkas, Pericles A.

    Hermes introduces a new "describe once, run anywhere" paradigm for the execution of bioinformatics workflows in hybrid cloud environments. It combines the traditional features of parallelization-enabled workflow management systems and of distributed computing platforms in a container-based approach. It offers seamless deployment, overcoming the burden of setting up and configuring the software and network requirements. Most importantly, Hermes fosters the reproducibility of scientific workflows by supporting standardization of the software execution environment, thus leading to consistent scientific workflow results and accelerating scientific output.

  7. The high-voltage system for the LHCb RICH hybrid photon detectors

    International Nuclear Information System (INIS)

    Arnaboldi, C.; Bellunato, T.; De Lucia, A.; Fanchini, E.; Perego, D.L.; Pessina, G.

    2009-01-01

    We describe the characterization of the high-voltage (HV) distribution system designed and produced for the pixel hybrid photon detectors of the ring imaging Cherenkov counters of the LHCb experiment. The HV system consists of a series of printed circuit boards with a specific layout designed to prevent any discharge arising from high electric fields. The system has dedicated monitoring and control features to supervise HV set-up during data taking. The full production of the HV system has been now completed and all the boards have been fully characterized and installed in the detector, which is currently being commissioned.

  8. Design of Energy Efficient Hybrid Ventilation

    DEFF Research Database (Denmark)

    Heiselberg, Per

    The focus in the development has for both systems been to minimise energy consumption while maintaining a comfortable and healthy indoor environment. The natural next step in this development is to develop ventilation concepts that utilises and combines the best features from each system......[Mechanical and natural ventilation] into a new type of ventilation system- Hybrid Ventilation....

  9. Fitting PAC spectra with a hybrid algorithm

    Energy Technology Data Exchange (ETDEWEB)

    Alves, M. A., E-mail: mauro@sepn.org [Instituto de Aeronautica e Espaco (Brazil); Carbonari, A. W., E-mail: carbonar@ipen.br [Instituto de Pesquisas Energeticas e Nucleares (Brazil)

    2008-01-15

    A hybrid algorithm (HA) that blends features of genetic algorithms (GA) and simulated annealing (SA) was implemented for simultaneous fits of perturbed angular correlation (PAC) spectra. The main characteristic of the HA is the incorporation of a selection criterion based on SA into the basic structure of GA. The results obtained with the HA compare favorably with fits performed with conventional methods.

  10. Multifunctional hybrids for electromagnetic absorption

    International Nuclear Information System (INIS)

    Huynen, I.; Quievy, N.; Bailly, C.; Bollen, P.; Detrembleur, C.; Eggermont, S.; Molenberg, I.; Thomassin, J.M.; Urbanczyk, L.

    2011-01-01

    Highlights: → EM absorption requires low dielectric constant and ∼1 S/m electrical conductivity. → New hybrids were processed with CNT-filled polymer foam inserted in Al honeycomb. → The EM absorption in the GHz range is superior to any known material. → A closed form model is used to guide the design of the hybrid. → The architectured material is light with potential for thermal management. - Abstract: Electromagnetic (EM) interferences are ubiquitous in modern technologies and impact on the reliability of electronic devices and on living cells. Shielding by EM absorption, which is preferable over reflection in certain instances, requires combining a low dielectric constant with high electrical conductivity, which are antagonist properties in the world of materials. A novel class of hybrid materials for EM absorption in the gigahertz range has been developed based on a hierarchical architecture involving a metallic honeycomb filled with a carbon nanotube-reinforced polymer foam. The waveguide characteristics of the honeycomb combined with the performance of the foam lead to unexpectedly large EM power absorption over a wide frequency range, superior to any known material. The peak absorption frequency can be tuned by varying the shape of the honeycomb unit cell. A closed form model of the EM reflection and absorption provides a tool for the optimization of the hybrid. This designed material sets the stage for a new class of sandwich panels combining high EM absorption with mass efficiency, stiffness and thermal management.

  11. SEEDLING DISCRIMINATION USING SHAPE FEATURES DERIVED FROM A DISTANCE TRANSFORM

    DEFF Research Database (Denmark)

    Mosgaard Giselsson, Thomas; Jørgensen, Rasmus Nyholm; Midtiby, Henrik

    NN, Naive-Bayes, Linear SVM, Non-linear SVM). A set of well known features is used for comparison. This feature set will be referred to as Standard Feature Set (SFS). The used dataset consisted of 139 samples of Corn Flower (Centaura cyanus L.) and 63 samples of Night Shade (Solanum nigrum L.). The highest...

  12. Textural features for radar image analysis

    Science.gov (United States)

    Shanmugan, K. S.; Narayanan, V.; Frost, V. S.; Stiles, J. A.; Holtzman, J. C.

    1981-01-01

    Texture is seen as an important spatial feature useful for identifying objects or regions of interest in an image. While textural features have been widely used in analyzing a variety of photographic images, they have not been used in processing radar images. A procedure for extracting a set of textural features for characterizing small areas in radar images is presented, and it is shown that these features can be used in classifying segments of radar images corresponding to different geological formations.

  13. A Novel Hybrid Model for Drawing Trace Reconstruction from Multichannel Surface Electromyographic Activity.

    Science.gov (United States)

    Chen, Yumiao; Yang, Zhongliang

    2017-01-01

    Recently, several researchers have considered the problem of reconstruction of handwriting and other meaningful arm and hand movements from surface electromyography (sEMG). Although much progress has been made, several practical limitations may still affect the clinical applicability of sEMG-based techniques. In this paper, a novel three-step hybrid model of coordinate state transition, sEMG feature extraction and gene expression programming (GEP) prediction is proposed for reconstructing drawing traces of 12 basic one-stroke shapes from multichannel surface electromyography. Using a specially designed coordinate data acquisition system, we recorded the coordinate data of drawing traces collected in accordance with the time series while 7-channel EMG signals were recorded. As a widely-used time domain feature, Root Mean Square (RMS) was extracted with the analysis window. The preliminary reconstruction models can be established by GEP. Then, the original drawing traces can be approximated by a constructed prediction model. Applying the three-step hybrid model, we were able to convert seven channels of EMG activity recorded from the arm muscles into smooth reconstructions of drawing traces. The hybrid model can yield a mean accuracy of 74% in within-group design (one set of prediction models for all shapes) and 86% in between-group design (one separate set of prediction models for each shape), averaged for the reconstructed x and y coordinates. It can be concluded that it is feasible for the proposed three-step hybrid model to improve the reconstruction ability of drawing traces from sEMG.

  14. Graphene hybridization for energy storage applications.

    Science.gov (United States)

    Li, Xianglong; Zhi, Linjie

    2018-05-08

    Graphene has attracted considerable attention due to its unique two-dimensional structure, high electronic mobility, exceptional thermal conductivity, excellent optical transmittance, good mechanical strength, and ultrahigh surface area. To meet the ever increasing demand for portable electronic products, electric vehicles, smart grids, and renewable energy integrations, hybridizing graphene with various functions and components has been demonstrated to be a versatile and powerful strategy to significantly enhance the performance of various energy storage systems such as lithium-ion batteries, supercapacitors and beyond, because such hybridization can result in synergistic effects that combine the best merits of involved components and confer new functions and properties, thereby improving the charge/discharge efficiencies and capabilities, energy/power densities, and cycle life of these energy storage systems. This review will focus on diverse graphene hybridization principles and strategies for energy storage applications, and the proposed outline is as follows. First, graphene and its fundamental properties, followed by graphene hybrids and related hybridization motivation, are introduced. Second, the developed hybridization formulas of using graphene for lithium-ion batteries are systematically categorized from the viewpoint of material structure design, bulk electrode construction, and material/electrode collaborative engineering; the latest representative progress on anodes and cathodes of lithium-ion batteries will be reviewed following such classifications. Third, similar hybridization formulas for graphene-based supercapacitor electrodes will be summarized and discussed as well. Fourth, the recently emerging hybridization formulas for other graphene-based energy storage devices will be briefed in combination with typical examples. Finally, future prospects and directions on the exploration of graphene hybridization toward the design and construction of

  15. Spatial features register: toward standardization of spatial features

    Science.gov (United States)

    Cascio, Janette

    1994-01-01

    As the need to share spatial data increases, more than agreement on a common format is needed to ensure that the data is meaningful to both the importer and the exporter. Effective data transfer also requires common definitions of spatial features. To achieve this, part 2 of the Spatial Data Transfer Standard (SDTS) provides a model for a spatial features data content specification and a glossary of features and attributes that fit this model. The model provides a foundation for standardizing spatial features. The glossary now contains only a limited subset of hydrographic and topographic features. For it to be useful, terms and definitions must be included for other categories, such as base cartographic, bathymetric, cadastral, cultural and demographic, geodetic, geologic, ground transportation, international boundaries, soils, vegetation, water, and wetlands, and the set of hydrographic and topographic features must be expanded. This paper will review the philosophy of the SDTS part 2 and the current plans for creating a national spatial features register as one mechanism for maintaining part 2.

  16. dyspepsia management in a resource poor setting feature article

    African Journals Online (AJOL)

    Methods: Extensive internet literature search was made through. Google scholar, Pubmed ... tests for H. pylori are not available or not cost-effective. Conclusion: Considering the .... and cognitive-behavioral therapy but they cannot be generally ...

  17. Rule set transferability for object-based feature extraction

    NARCIS (Netherlands)

    Anders, N.S.; Seijmonsbergen, Arie C.; Bouten, Willem

    2015-01-01

    Cirques are complex landforms resulting from glacial erosion and can be used to estimate Equilibrium Line Altitudes and infer climate history. Automated extraction of cirques may help research on glacial geomorphology and climate change. Our objective was to test the transferability of an

  18. Hybrid Model of Content Extraction

    DEFF Research Database (Denmark)

    Qureshi, Pir Abdul Rasool; Memon, Nasrullah

    2012-01-01

    We present a hybrid model for content extraction from HTML documents. The model operates on Document Object Model (DOM) tree of the corresponding HTML document. It evaluates each tree node and associated statistical features like link density and text distribution across the node to predict...... significance of the node towards overall content provided by the document. Once significance of the nodes is determined, the formatting characteristics like fonts, styles and the position of the nodes are evaluated to identify the nodes with similar formatting as compared to the significant nodes. The proposed...

  19. Hybrid recreation by reverse breeding in Arabidopsis thaliana.

    Science.gov (United States)

    Wijnker, Erik; Deurhof, Laurens; van de Belt, Jose; de Snoo, C Bastiaan; Blankestijn, Hetty; Becker, Frank; Ravi, Maruthachalam; Chan, Simon W L; van Dun, Kees; Lelivelt, Cilia L C; de Jong, Hans; Dirks, Rob; Keurentjes, Joost J B

    2014-04-01

    Hybrid crop varieties are traditionally produced by selecting and crossing parental lines to evaluate hybrid performance. Reverse breeding allows doing the opposite: selecting uncharacterized heterozygotes and generating parental lines from them. With these, the selected heterozygotes can be recreated as F1 hybrids, greatly increasing the number of hybrids that can be screened in breeding programs. Key to reverse breeding is the suppression of meiotic crossovers in a hybrid plant to ensure the transmission of nonrecombinant chromosomes to haploid gametes. These gametes are subsequently regenerated as doubled-haploid (DH) offspring. Each DH carries combinations of its parental chromosomes, and complementing pairs can be crossed to reconstitute the initial hybrid. Achiasmatic meiosis and haploid generation result in uncommon phenotypes among offspring owing to chromosome number variation. We describe how these features can be dealt with during a reverse-breeding experiment, which can be completed in six generations (∼1 year).

  20. Collective Identity Formation in Hybrid Organizations

    DEFF Research Database (Denmark)

    Boulongne, Romain; Boxenbaum, Eva

    The present article examines the process of collective identity formation in the context of hybrid organizing. Empirically, we investigate hybrid organizing in a collaborative structure at the interface of two heterogeneous organizations in the domain of new renewable energies. We draw...... on the literature on knowledge sharing across organizational boundaries, particularly the notions of transfer, translation and transformation, to examine in real time how knowledge sharing in a hybrid setting contributes (or not) to the emergence of a new collective identity at the interface of two heterogeneous...... organizations. Our findings point to two factors that limit knowledge sharing and hence to new collective identity formation in a hybrid space: 1) ambiguous or multiple organizational roles and 2) strong identities of the collaborating organizations. These findings contribute to illuminating the initial...

  1. Towards an expansive hybrid psychology

    DEFF Research Database (Denmark)

    Brinkmann, Svend

    2011-01-01

    sources of mediators that are the brain, the body, social practices and technological artefacts. It is argued that the mind is normative in the sense that mental processes do not simply happen, but can be done more or less well, and thus are subject to normative appraisal. The expanded hybrid psychology......This article develops an integrative theory of the mind by examining how the mind, understood as a set of skills and dispositions, depends upon four sources of mediators. Harré’s hybrid psychology is taken as a meta-theoretical starting point, but is expanded significantly by including the four...... is meant to assist in integrating theoretical perspectives and research interests that are often thought of as incompatible, among them neuroscience, phenomenology of the body, social practice theory and technology studies. A main point of the article is that these perspectives each are necessary...

  2. Classification Influence of Features on Given Emotions and Its Application in Feature Selection

    Science.gov (United States)

    Xing, Yin; Chen, Chuang; Liu, Li-Long

    2018-04-01

    In order to solve the problem that there is a large amount of redundant data in high-dimensional speech emotion features, we analyze deeply the extracted speech emotion features and select better features. Firstly, a given emotion is classified by each feature. Secondly, the recognition rate is ranked in descending order. Then, the optimal threshold of features is determined by rate criterion. Finally, the better features are obtained. When applied in Berlin and Chinese emotional data set, the experimental results show that the feature selection method outperforms the other traditional methods.

  3. Hybrid methods for cybersecurity analysis :

    Energy Technology Data Exchange (ETDEWEB)

    Davis, Warren Leon,; Dunlavy, Daniel M.

    2014-01-01

    Early 2010 saw a signi cant change in adversarial techniques aimed at network intrusion: a shift from malware delivered via email attachments toward the use of hidden, embedded hyperlinks to initiate sequences of downloads and interactions with web sites and network servers containing malicious software. Enterprise security groups were well poised and experienced in defending the former attacks, but the new types of attacks were larger in number, more challenging to detect, dynamic in nature, and required the development of new technologies and analytic capabilities. The Hybrid LDRD project was aimed at delivering new capabilities in large-scale data modeling and analysis to enterprise security operators and analysts and understanding the challenges of detection and prevention of emerging cybersecurity threats. Leveraging previous LDRD research e orts and capabilities in large-scale relational data analysis, large-scale discrete data analysis and visualization, and streaming data analysis, new modeling and analysis capabilities were quickly brought to bear on the problems in email phishing and spear phishing attacks in the Sandia enterprise security operational groups at the onset of the Hybrid project. As part of this project, a software development and deployment framework was created within the security analyst work ow tool sets to facilitate the delivery and testing of new capabilities as they became available, and machine learning algorithms were developed to address the challenge of dynamic threats. Furthermore, researchers from the Hybrid project were embedded in the security analyst groups for almost a full year, engaged in daily operational activities and routines, creating an atmosphere of trust and collaboration between the researchers and security personnel. The Hybrid project has altered the way that research ideas can be incorporated into the production environments of Sandias enterprise security groups, reducing time to deployment from months and

  4. Vibration Isolation for Parallel Hydraulic Hybrid Vehicles

    Directory of Open Access Journals (Sweden)

    The M. Nguyen

    2008-01-01

    Full Text Available In recent decades, several types of hybrid vehicles have been developed in order to improve the fuel economy and to reduce the pollution. Hybrid electric vehicles (HEV have shown a significant improvement in fuel efficiency for small and medium-sized passenger vehicles and SUVs. HEV has several limitations when applied to heavy vehicles; one is that larger vehicles demand more power, which requires significantly larger battery capacities. As an alternative solution, hydraulic hybrid technology has been found effective for heavy duty vehicle because of its high power density. The mechanical batteries used in hydraulic hybrid vehicles (HHV can be charged and discharged remarkably faster than chemical batteries. This feature is essential for heavy vehicle hybridization. One of the main problems that should be solved for the successful commercialization of HHV is the excessive noise and vibration involving with the hydraulic systems. This study focuses on using magnetorheological (MR technology to reduce the noise and vibration transmissibility from the hydraulic system to the vehicle body. In order to study the noise and vibration of HHV, a hydraulic hybrid subsystem in parallel design is analyzed. This research shows that the MR elements play an important role in reducing the transmitted noise and vibration to the vehicle body. Additionally, locations and orientations of the isolation system also affect the efficiency of the noise and vibration mitigation. In simulations, a skyhook control algorithm is used to achieve the highest possible effectiveness of the MR isolation system.

  5. Feature Evaluation for Building Facade Images - AN Empirical Study

    Science.gov (United States)

    Yang, M. Y.; Förstner, W.; Chai, D.

    2012-08-01

    The classification of building facade images is a challenging problem that receives a great deal of attention in the photogrammetry community. Image classification is critically dependent on the features. In this paper, we perform an empirical feature evaluation task for building facade images. Feature sets we choose are basic features, color features, histogram features, Peucker features, texture features, and SIFT features. We present an approach for region-wise labeling using an efficient randomized decision forest classifier and local features. We conduct our experiments with building facade image classification on the eTRIMS dataset, where our focus is the object classes building, car, door, pavement, road, sky, vegetation, and window.

  6. A Hybrid Supervised/Unsupervised Machine Learning Approach to Solar Flare Prediction

    Science.gov (United States)

    Benvenuto, Federico; Piana, Michele; Campi, Cristina; Massone, Anna Maria

    2018-01-01

    This paper introduces a novel method for flare forecasting, combining prediction accuracy with the ability to identify the most relevant predictive variables. This result is obtained by means of a two-step approach: first, a supervised regularization method for regression, namely, LASSO is applied, where a sparsity-enhancing penalty term allows the identification of the significance with which each data feature contributes to the prediction; then, an unsupervised fuzzy clustering technique for classification, namely, Fuzzy C-Means, is applied, where the regression outcome is partitioned through the minimization of a cost function and without focusing on the optimization of a specific skill score. This approach is therefore hybrid, since it combines supervised and unsupervised learning; realizes classification in an automatic, skill-score-independent way; and provides effective prediction performances even in the case of imbalanced data sets. Its prediction power is verified against NOAA Space Weather Prediction Center data, using as a test set, data in the range between 1996 August and 2010 December and as training set, data in the range between 1988 December and 1996 June. To validate the method, we computed several skill scores typically utilized in flare prediction and compared the values provided by the hybrid approach with the ones provided by several standard (non-hybrid) machine learning methods. The results showed that the hybrid approach performs classification better than all other supervised methods and with an effectiveness comparable to the one of clustering methods; but, in addition, it provides a reliable ranking of the weights with which the data properties contribute to the forecast.

  7. Hybrid Genetic Algorithm Optimization for Case Based Reasoning Systems

    International Nuclear Information System (INIS)

    Mohamed, A.H.

    2008-01-01

    The success of a CBR system largely depen ds on an effective retrieval of useful prior case for the problem. Nearest neighbor and induction are the main CBR retrieval algorithms. Each of them can be more suitable in different situations. Integrated the two retrieval algorithms can catch the advantages of both of them. But, they still have some limitations facing the induction retrieval algorithm when dealing with a noisy data, a large number of irrelevant features, and different types of data. This research utilizes a hybrid approach using genetic algorithms (GAs) to case-based induction retrieval of the integrated nearest neighbor - induction algorithm in an attempt to overcome these limitations and increase the overall classification accuracy. GAs can be used to optimize the search space of all the possible subsets of the features set. It can deal with the irrelevant and noisy features while still achieving a significant improvement of the retrieval accuracy. Therefore, the proposed CBR-GA introduces an effective general purpose retrieval algorithm that can improve the performance of CBR systems. It can be applied in many application areas. CBR-GA has proven its success when applied for different problems in real-life

  8. Efficient Generation and Selection of Combined Features for Improved Classification

    KAUST Repository

    Shono, Ahmad N.

    2014-05-01

    This study contributes a methodology and associated toolkit developed to allow users to experiment with the use of combined features in classification problems. Methods are provided for efficiently generating combined features from an original feature set, for efficiently selecting the most discriminating of these generated combined features, and for efficiently performing a preliminary comparison of the classification results when using the original features exclusively against the results when using the selected combined features. The potential benefit of considering combined features in classification problems is demonstrated by applying the developed methodology and toolkit to three sample data sets where the discovery of combined features containing new discriminating information led to improved classification results.

  9. Robust emotion recognition using spectral and prosodic features

    CERN Document Server

    Rao, K Sreenivasa

    2013-01-01

    In this brief, the authors discuss recently explored spectral (sub-segmental and pitch synchronous) and prosodic (global and local features at word and syllable levels in different parts of the utterance) features for discerning emotions in a robust manner. The authors also delve into the complementary evidences obtained from excitation source, vocal tract system and prosodic features for the purpose of enhancing emotion recognition performance. Features based on speaking rate characteristics are explored with the help of multi-stage and hybrid models for further improving emotion recognition performance. Proposed spectral and prosodic features are evaluated on real life emotional speech corpus.

  10. Naive Bayes-Guided Bat Algorithm for Feature Selection

    Directory of Open Access Journals (Sweden)

    Ahmed Majid Taha

    2013-01-01

    Full Text Available When the amount of data and information is said to double in every 20 months or so, feature selection has become highly important and beneficial. Further improvements in feature selection will positively affect a wide array of applications in fields such as pattern recognition, machine learning, or signal processing. Bio-inspired method called Bat Algorithm hybridized with a Naive Bayes classifier has been presented in this work. The performance of the proposed feature selection algorithm was investigated using twelve benchmark datasets from different domains and was compared to three other well-known feature selection algorithms. Discussion focused on four perspectives: number of features, classification accuracy, stability, and feature generalization. The results showed that BANB significantly outperformed other algorithms in selecting lower number of features, hence removing irrelevant, redundant, or noisy features while maintaining the classification accuracy. BANB is also proven to be more stable than other methods and is capable of producing more general feature subsets.

  11. Naive Bayes-Guided Bat Algorithm for Feature Selection

    Science.gov (United States)

    Taha, Ahmed Majid; Mustapha, Aida; Chen, Soong-Der

    2013-01-01

    When the amount of data and information is said to double in every 20 months or so, feature selection has become highly important and beneficial. Further improvements in feature selection will positively affect a wide array of applications in fields such as pattern recognition, machine learning, or signal processing. Bio-inspired method called Bat Algorithm hybridized with a Naive Bayes classifier has been presented in this work. The performance of the proposed feature selection algorithm was investigated using twelve benchmark datasets from different domains and was compared to three other well-known feature selection algorithms. Discussion focused on four perspectives: number of features, classification accuracy, stability, and feature generalization. The results showed that BANB significantly outperformed other algorithms in selecting lower number of features, hence removing irrelevant, redundant, or noisy features while maintaining the classification accuracy. BANB is also proven to be more stable than other methods and is capable of producing more general feature subsets. PMID:24396295

  12. A hybrid system for solar irradiance specification

    Science.gov (United States)

    Tobiska, W.; Bouwer, S.

    2006-12-01

    Space environment research and space weather operations require solar irradiances in a variety of time scales and spectral formats. We describe the development of solar irradiance characterization using four models and systems that are also used for space weather operations. The four models/systems include SOLAR2000 (S2K), SOLARFLARE (SFLR), APEX, and IDAR, which are used by Space Environment Technologies (SET) to provide solar irradiances from the soft X-rays through the visible spectrum. SFLR uses the GOES 0.1 0.8 nm X-rays in combination with a Mewe model subroutine to provide 0.1 30.0 nm irradiances at 0.1 nm spectral resolution, at 1 minute time resolution, and in a 6-hour XUV EUV spectral solar flare evolution forecast with a 7 minute latency and a 2 minute cadence. These irradiances have been calibrated with the SORCE XPS observations and we report on the inclusion of these irradiances into the S2K model. The APEX system is a real-time data retrieval system developed in conjunction with the University of Southern California Space Sciences Center (SSC) to provide SOHO SEM data processing and distribution. SSC provides the updated SEM data to the research community and SET provides the operational data to the space operations community. We describe how the SOHO SEM data, and especially the new S10.7 index, is being integrated directly into the S2K model for space weather operations. The IDAR system has been developed by SET to extract coronal hole boundaries, streamers, coronal loops, active regions, plage, network, and background (internetwork) features from solar images for comparison with solar magnetic features. S2K, SFLR, APEX, and IDAR outputs are integrated through the S2K solar irradiance platform that has become a hybrid system, i.e., a system that is able to produce irradiances using different processes, including empirical and physics-based models combined with real-time data integration.

  13. Henkin and Hybrid Logic

    DEFF Research Database (Denmark)

    Blackburn, Patrick Rowan; Huertas, Antonia; Manzano, Maria

    2014-01-01

    Leon Henkin was not a modal logician, but there is a branch of modal logic that has been deeply influenced by his work. That branch is hybrid logic, a family of logics that extend orthodox modal logic with special proposition symbols (called nominals) that name worlds. This paper explains why...... Henkin’s techniques are so important in hybrid logic. We do so by proving a completeness result for a hybrid type theory called HTT, probably the strongest hybrid logic that has yet been explored. Our completeness result builds on earlier work with a system called BHTT, or basic hybrid type theory...... is due to the first-order perspective, which lies at the heart of Henin’s best known work and hybrid logic....

  14. Universal features underlying the magnetism in diluted magnetic semiconductors

    Science.gov (United States)

    Andriotis, Antonis N.; Menon, Madhu

    2018-04-01

    Investigation of a diverse variety of wide band gap semiconductors and metal oxides that exhibit magnetism on substitutional doping has revealed the existence of universal features that relate the magnetic moment of the dopant to a number of physical properties inherent to the dopants and the hosts. The investigated materials consist of ZnO, GaN, GaP, TiO2, SnO2, Sn3N4, MoS2, ZnS and CdS doped with 3d-transition metal atoms. The primary physical properties contributing to magnetism include the orbital hybridization and charge distribution, the d-band filling, d-band center, crystal field splitting, electron pairing energy and electronegativity. These features specify the strength of the spin-polarization induced by the dopants on their first nearest neighboring anions which in turn specify the long range magnetic coupling among the dopants through successively induced spin polarizations (SSP) on neighboring dopants. The proposed local SSP process for the establishment of the magnetic coupling among the TM-dopants appears as a competitor to other classical processes (superexchange, double exchange, etc). Furthermore, these properties can be used as a set of descriptors suitable for developing statistical predictive theories for a much larger class of magnetic materials.

  15. Universal features underlying the magnetism in diluted magnetic semiconductors.

    Science.gov (United States)

    Andriotis, Antonis N; Menon, Madhu

    2018-04-04

    Investigation of a diverse variety of wide band gap semiconductors and metal oxides that exhibit magnetism on substitutional doping has revealed the existence of universal features that relate the magnetic moment of the dopant to a number of physical properties inherent to the dopants and the hosts. The investigated materials consist of ZnO, GaN, GaP, TiO 2 , SnO 2 , Sn 3 N 4 , MoS 2 , ZnS and CdS doped with 3d-transition metal atoms. The primary physical properties contributing to magnetism include the orbital hybridization and charge distribution, the d-band filling, d-band center, crystal field splitting, electron pairing energy and electronegativity. These features specify the strength of the spin-polarization induced by the dopants on their first nearest neighboring anions which in turn specify the long range magnetic coupling among the dopants through successively induced spin polarizations (SSP) on neighboring dopants. The proposed local SSP process for the establishment of the magnetic coupling among the TM-dopants appears as a competitor to other classical processes (superexchange, double exchange, etc). Furthermore, these properties can be used as a set of descriptors suitable for developing statistical predictive theories for a much larger class of magnetic materials.

  16. Hypothesis testing for differentially correlated features.

    Science.gov (United States)

    Sheng, Elisa; Witten, Daniela; Zhou, Xiao-Hua

    2016-10-01

    In a multivariate setting, we consider the task of identifying features whose correlations with the other features differ across conditions. Such correlation shifts may occur independently of mean shifts, or differences in the means of the individual features across conditions. Previous approaches for detecting correlation shifts consider features simultaneously, by computing a correlation-based test statistic for each feature. However, since correlations involve two features, such approaches do not lend themselves to identifying which feature is the culprit. In this article, we instead consider a serial testing approach, by comparing columns of the sample correlation matrix across two conditions, and removing one feature at a time. Our method provides a novel perspective and favorable empirical results compared with competing approaches. © The Author 2016. Published by Oxford University Press. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

  17. Hybrid Action Systems

    DEFF Research Database (Denmark)

    Ronkko, Mauno; Ravn, Anders P.

    1997-01-01

    a differential action, which allows differential equations as primitive actions. The extension allows us to model hybrid systems with both continuous and discrete behaviour. The main result of this paper is an extension of such a hybrid action system with parallel composition. The extension does not change...... the original meaning of the parallel composition, and therefore also the ordinary action systems can be composed in parallel with the hybrid action systems....

  18. Nanoscale Organic Hybrid Electrolytes

    KAUST Repository

    Nugent, Jennifer L.

    2010-08-20

    Nanoscale organic hybrid electrolytes are composed of organic-inorganic hybrid nanostructures, each with a metal oxide or metallic nanoparticle core densely grafted with an ion-conducting polyethylene glycol corona - doped with lithium salt. These materials form novel solvent-free hybrid electrolytes that are particle-rich, soft glasses at room temperature; yet manifest high ionic conductivity and good electrochemical stability above 5V. © 2010 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

  19. Nanoscale Organic Hybrid Electrolytes

    KAUST Repository

    Nugent, Jennifer L.; Moganty, Surya S.; Archer, Lynden A.

    2010-01-01

    Nanoscale organic hybrid electrolytes are composed of organic-inorganic hybrid nanostructures, each with a metal oxide or metallic nanoparticle core densely grafted with an ion-conducting polyethylene glycol corona - doped with lithium salt. These materials form novel solvent-free hybrid electrolytes that are particle-rich, soft glasses at room temperature; yet manifest high ionic conductivity and good electrochemical stability above 5V. © 2010 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

  20. HYBRID VEHICLE CONTROL SYSTEM

    Directory of Open Access Journals (Sweden)

    V. Dvadnenko

    2016-06-01

    Full Text Available The hybrid vehicle control system includes a start–stop system for an internal combustion engine. The system works in a hybrid mode and normal vehicle operation. To simplify the start–stop system, there were user new possibilities of a hybrid car, which appeared after the conversion. Results of the circuit design of the proposed system of basic blocks are analyzed.

  1. Hybrid radiator cooling system

    Science.gov (United States)

    France, David M.; Smith, David S.; Yu, Wenhua; Routbort, Jules L.

    2016-03-15

    A method and hybrid radiator-cooling apparatus for implementing enhanced radiator-cooling are provided. The hybrid radiator-cooling apparatus includes an air-side finned surface for air cooling; an elongated vertically extending surface extending outwardly from the air-side finned surface on a downstream air-side of the hybrid radiator; and a water supply for selectively providing evaporative cooling with water flow by gravity on the elongated vertically extending surface.

  2. Character feature integration of Chinese calligraphy and font

    Science.gov (United States)

    Shi, Cao; Xiao, Jianguo; Jia, Wenhua; Xu, Canhui

    2013-01-01

    A framework is proposed in this paper to effectively generate a new hybrid character type by means of integrating local contour feature of Chinese calligraphy with structural feature of font in computer system. To explore traditional art manifestation of calligraphy, multi-directional spatial filter is applied for local contour feature extraction. Then the contour of character image is divided into sub-images. The sub-images in the identical position from various characters are estimated by Gaussian distribution. According to its probability distribution, the dilation operator and erosion operator are designed to adjust the boundary of font image. And then new Chinese character images are generated which possess both contour feature of artistical calligraphy and elaborate structural feature of font. Experimental results demonstrate the new characters are visually acceptable, and the proposed framework is an effective and efficient strategy to automatically generate the new hybrid character of calligraphy and font.

  3. Directional genomic hybridization for chromosomal inversion discovery and detection.

    Science.gov (United States)

    Ray, F Andrew; Zimmerman, Erin; Robinson, Bruce; Cornforth, Michael N; Bedford, Joel S; Goodwin, Edwin H; Bailey, Susan M

    2013-04-01

    Chromosomal rearrangements are a source of structural variation within the genome that figure prominently in human disease, where the importance of translocations and deletions is well recognized. In principle, inversions-reversals in the orientation of DNA sequences within a chromosome-should have similar detrimental potential. However, the study of inversions has been hampered by traditional approaches used for their detection, which are not particularly robust. Even with significant advances in whole genome approaches, changes in the absolute orientation of DNA remain difficult to detect routinely. Consequently, our understanding of inversions is still surprisingly limited, as is our appreciation for their frequency and involvement in human disease. Here, we introduce the directional genomic hybridization methodology of chromatid painting-a whole new way of looking at structural features of the genome-that can be employed with high resolution on a cell-by-cell basis, and demonstrate its basic capabilities for genome-wide discovery and targeted detection of inversions. Bioinformatics enabled development of sequence- and strand-specific directional probe sets, which when coupled with single-stranded hybridization, greatly improved the resolution and ease of inversion detection. We highlight examples of the far-ranging applicability of this cytogenomics-based approach, which include confirmation of the alignment of the human genome database and evidence that individuals themselves share similar sequence directionality, as well as use in comparative and evolutionary studies for any species whose genome has been sequenced. In addition to applications related to basic mechanistic studies, the information obtainable with strand-specific hybridization strategies may ultimately enable novel gene discovery, thereby benefitting the diagnosis and treatment of a variety of human disease states and disorders including cancer, autism, and idiopathic infertility.

  4. Toronto hybrid taxi pilot

    Energy Technology Data Exchange (ETDEWEB)

    Stevens, M. [CrossChasm Technologies, Cambridge, ON (Canada); Marans, B. [Toronto Atmospheric Fund, ON (Canada)

    2009-10-15

    This paper provided details of a hybrid taxi pilot program conducted to compare the on-road performance of Toyota Camry hybrid vehicles against conventional vehicles over a 1-year period in order to determine the business case and air emission reductions associated with the use of hybrid taxi cabs. Over 750,000 km worth of fuel consumption was captured from 10 Toyota Camry hybrids, a Toyota Prius, and 5 non-hybrid Camry vehicles over an 18-month period. The average real world fuel consumption for the taxis demonstrated that the Toyota Prius has the lowest cost of ownership, while the non-hybrid Camry has the highest cost of ownership. Carbon dioxide (CO{sub 2}) reductions associated with the 10 Camry hybrid taxis were calculated at 236 tonnes over a 7-year taxi service life. Results suggested that the conversion of Toronto's 5680 taxis would yield annual CO{sub 2} emission reductions of over 19,000 tonnes. All hybrid purchasers identified themselves as highly likely to purchase a hybrid again. 5 tabs., 9 figs.

  5. Managing hybrid marketing systems.

    Science.gov (United States)

    Moriarty, R T; Moran, U

    1990-01-01

    As competition increases and costs become critical, companies that once went to market only one way are adding new channels and using new methods - creating hybrid marketing systems. These hybrid marketing systems hold the promise of greater coverage and reduced costs. But they are also hard to manage; they inevitably raise questions of conflict and control: conflict because marketing units compete for customers; control because new indirect channels are less subject to management authority. Hard as they are to manage, however, hybrid marketing systems promise to become the dominant design, replacing the "purebred" channel strategy in all kinds of businesses. The trick to managing the hybrid is to analyze tasks and channels within and across a marketing system. A map - the hybrid grid - can help managers make sense of their hybrid system. What the chart reveals is that channels are not the basic building blocks of a marketing system; marketing tasks are. The hybrid grid forces managers to consider various combinations of channels and tasks that will optimize both cost and coverage. Managing conflict is also an important element of a successful hybrid system. Managers should first acknowledge the inevitability of conflict. Then they should move to bound it by creating guidelines that spell out which customers to serve through which methods. Finally, a marketing and sales productivity (MSP) system, consisting of a central marketing database, can act as the central nervous system of a hybrid marketing system, helping managers create customized channels and service for specific customer segments.

  6. Toronto hybrid taxi pilot

    International Nuclear Information System (INIS)

    Stevens, M.; Marans, B.

    2009-10-01

    This paper provided details of a hybrid taxi pilot program conducted to compare the on-road performance of Toyota Camry hybrid vehicles against conventional vehicles over a 1-year period in order to determine the business case and air emission reductions associated with the use of hybrid taxi cabs. Over 750,000 km worth of fuel consumption was captured from 10 Toyota Camry hybrids, a Toyota Prius, and 5 non-hybrid Camry vehicles over an 18-month period. The average real world fuel consumption for the taxis demonstrated that the Toyota Prius has the lowest cost of ownership, while the non-hybrid Camry has the highest cost of ownership. Carbon dioxide (CO 2 ) reductions associated with the 10 Camry hybrid taxis were calculated at 236 tonnes over a 7-year taxi service life. Results suggested that the conversion of Toronto's 5680 taxis would yield annual CO 2 emission reductions of over 19,000 tonnes. All hybrid purchasers identified themselves as highly likely to purchase a hybrid again. 5 tabs., 9 figs.

  7. Hybrid FOSS Project

    Data.gov (United States)

    National Aeronautics and Space Administration — Armstrong researchers are continuing their efforts to further develop FOSS technologies. A hybrid FOSS technique (HyFOSS) employs conventional continuous grating...

  8. 3p interstitial deletion including PRICKLE2 in identical twins with autistic features.

    Science.gov (United States)

    Okumura, Akihisa; Yamamoto, Toshiyuki; Miyajima, Masakazu; Shimojima, Keiko; Kondo, Satoshi; Abe, Shinpei; Ikeno, Mitsuru; Shimizu, Toshiaki

    2014-11-01

    Microdeletion and microduplication syndromes without characteristic dysmorphic features are difficult to diagnose without chromosomal microarrays. We describe the clinical course and genetic findings of monozygotic twins with intellectual disabilities and autistic features associated with mild facial dysmorphism and microdeletion of chromosome 3p14. The postnatal course of the second twin was complicated by intestinal malrotation, whereas that of the first twin was unremarkable. Both twins had several mild dysmorphic features including upswept frontal hair, low-set posterior rotated ears, arched down-slanting eyebrows, prominent forehead, epicanthic folds, micrognathia, hypertelorism, broad nasal bridge, short philtrum, and camptodactyly of the bilateral fifth fingers. They had autistic features such as poor eye contact and no social smile, stereotyped behaviors, and preference for solitary play. Array comparative genomic hybridization analysis revealed de novo 6.88-Mb deletions of 3p14 (chr3: 60,472,496-67,385,119) involving 17 genes in both twins. The deleted region contained 17 genes, five of which are known or presumed to be related to central nervous system disorders: FEZF2, SYNPR, ATXN7, PRICKLE2, and MAGI1. We consider that PRICKLE2 is the most likely causative gene for the autistic features exhibited by these individuals. Copyright © 2014 Elsevier Inc. All rights reserved.

  9. Elastic softness of hybrid lead halide perovskites

    KAUST Repository

    Ferreira, A. C.; Lé toublon, A.; Paofai, S.; Raymond, S.; Ecolivet, C.; Rufflé , B.; Cordier, S.; Katan, C.; Saidaminov, Makhsud I.; Zhumekenov, A. A.; Bakr, Osman; Even, J.; Bourges, Ph.

    2018-01-01

    scattering, low frequency acoustic phonons in four different hybrid perovskite single crystals: MAPbBr3, FAPbBr3, MAPbI3 and α-FAPbI3 (MA: methylammonium, FA: formamidinium). We report a complete set of elastic constants caracterized by a very soft shear

  10. Stochastic hybrid systems with renewal transitions

    NARCIS (Netherlands)

    Guerreiro Tome Antunes, D.J.; Hespanha, J.P.; Silvestre, C.J.

    2010-01-01

    We consider Stochastic Hybrid Systems (SHSs) for which the lengths of times that the system stays in each mode are independent random variables with given distributions. We propose an analysis framework based on a set of Volterra renewal-type equations, which allows us to compute any statistical

  11. Feature-level domain adaptation

    DEFF Research Database (Denmark)

    Kouw, Wouter M.; Van Der Maaten, Laurens J P; Krijthe, Jesse H.

    2016-01-01

    -level domain adaptation (flda), that models the dependence between the two domains by means of a feature-level transfer model that is trained to describe the transfer from source to target domain. Subsequently, we train a domain-adapted classifier by minimizing the expected loss under the resulting transfer...... modeled via a dropout distribution, which allows the classiffier to adapt to differences in the marginal probability of features in the source and the target domain. Our experiments on several real-world problems show that flda performs on par with state-of-the-art domainadaptation techniques.......Domain adaptation is the supervised learning setting in which the training and test data are sampled from different distributions: training data is sampled from a source domain, whilst test data is sampled from a target domain. This paper proposes and studies an approach, called feature...

  12. Regulatory Hybridization in the Transnational Sphere

    DEFF Research Database (Denmark)

    Kjær, Poul Fritz; Jurcys, Paulius; Yrakami, Ren

    Hybridization has become a defining feature of regulatory frameworks. The combined forces of globalization and privatization together with increased reliance on self-regulation have resulted in the emergence of a multitude of regulatory arrangements which combine elements from several legal orders....... This book offers a conceptual framework as well as numerous empirical explorations capable of increasing our understanding of regulatory hybridization. A number of central dichotomies are deconstructed: national vs. transnational law; international vs. transnational law; convergence vs. divergence; … read...... moresoft law vs. hard law; territorial vs. non-territorial, ‘top-down’ vs. ‘bottom-up’ globalization and national vs. global just as the implications of regulatory hybridization for the question of choice of court and conflict of laws are analyzed....

  13. From hybrid swarms to swarms of hybrids

    Science.gov (United States)

    Stohlgren, Thomas J.; Szalanski, Allen L; Gaskin, John F.; Young, Nicholas E.; West, Amanda; Jarnevich, Catherine S.; Tripodi, Amber

    2014-01-01

    Science has shown that the introgression or hybridization of modern humans (Homo sapiens) with Neanderthals up to 40,000 YBP may have led to the swarm of modern humans on earth. However, there is little doubt that modern trade and transportation in support of the humans has continued to introduce additional species, genotypes, and hybrids to every country on the globe. We assessed the utility of species distributions modeling of genotypes to assess the risk of current and future invaders. We evaluated 93 locations of the genus Tamarix for which genetic data were available. Maxent models of habitat suitability showed that the hybrid, T. ramosissima x T. chinensis, was slightly greater than the parent taxa (AUCs > 0.83). General linear models of Africanized honey bees, a hybrid cross of Tanzanian Apis mellifera scutellata and a variety of European honey bee including A. m. ligustica, showed that the Africanized bees (AUC = 0.81) may be displacing European honey bees (AUC > 0.76) over large areas of the southwestern U.S. More important, Maxent modeling of sub-populations (A1 and A26 mitotypes based on mDNA) could be accurately modeled (AUC > 0.9), and they responded differently to environmental drivers. This suggests that rapid evolutionary change may be underway in the Africanized bees, allowing the bees to spread into new areas and extending their total range. Protecting native species and ecosystems may benefit from risk maps of harmful invasive species, hybrids, and genotypes.

  14. ON THE STABILIZATION OF THE LINEAR HYBRID SYSTEM STRUCTURE

    Directory of Open Access Journals (Sweden)

    Kirillov

    2014-11-01

    Full Text Available The linear control hybrid system, consisting of a fi- nite set of subsystems (modes having different dimensions, is considered. The moments of reset time are determined by some complementary function – evolutionary time. This function satisfies the special complementary ordinary differential equation. The mode stabilization problem is solved for some class of piecewise linear controls. The method of stabilization relies on the set of invariant planes, the existence of which is due to the special form of the hybrid system.

  15. Design, analysis and modeling of a novel hybrid powertrain system based on hybridized automated manual transmission

    Science.gov (United States)

    Wu, Guang; Dong, Zuomin

    2017-09-01

    Hybrid electric vehicles are widely accepted as a promising short to mid-term technical solution due to noticeably improved efficiency and lower emissions at competitive costs. In recent years, various hybrid powertrain systems were proposed and implemented based on different types of conventional transmission. Power-split system, including Toyota Hybrid System and Ford Hybrid System, are well-known examples. However, their relatively low torque capacity, and the drive of alternative and more advanced designs encouraged other innovative hybrid system designs. In this work, a new type of hybrid powertrain system based hybridized automated manual transmission (HAMT) is proposed. By using the concept of torque gap filler (TGF), this new hybrid powertrain type has the potential to overcome issue of torque gap during gearshift. The HAMT design (patent pending) is described in details, from gear layout and design of gear ratios (EV mode and HEV mode) to torque paths at different gears. As an analytical tool, mutli-body model of vehicle equipped with this HAMT was built to analyze powertrain dynamics at various steady and transient modes. A gearshift was decomposed and analyzed based basic modes. Furthermore, a Simulink-SimDriveline hybrid vehicle model was built for the new transmission, driveline and vehicle modular. Control strategy has also been built to harmonically coordinate different powertrain components to realize TGF function. A vehicle launch simulation test has been completed under 30% of accelerator pedal position to reveal details during gearshift. Simulation results showed that this HAMT can eliminate most torque gap that has been persistent issue of traditional AMT, improving both drivability and performance. This work demonstrated a new type of transmission that features high torque capacity, high efficiency and improved drivability.

  16. Feature Selection by Reordering

    Czech Academy of Sciences Publication Activity Database

    Jiřina, Marcel; Jiřina jr., M.

    2005-01-01

    Roč. 2, č. 1 (2005), s. 155-161 ISSN 1738-6438 Institutional research plan: CEZ:AV0Z10300504 Keywords : feature selection * data reduction * ordering of features Subject RIV: BA - General Mathematics

  17. Hybridization in geese

    NARCIS (Netherlands)

    Ottenburghs, Jente; Hooft, van Pim; Wieren, van Sipke E.; Ydenberg, Ronald C.; Prins, Herbert H.T.

    2016-01-01

    The high incidence of hybridization in waterfowl (ducks, geese and swans) makes this bird group an excellent study system to answer questions related to the evolution and maintenance of species boundaries. However, knowledge on waterfowl hybridization is biased towards ducks, with a large

  18. Mirror hybrid reactor studies

    International Nuclear Information System (INIS)

    Bender, D.J.

    1978-01-01

    The hybrid reactor studies are reviewed. The optimization of the point design and work on a reference design are described. The status of the nuclear analysis of fast spectrum blankets, systems studies for fissile fuel producing hybrid reactor, and the mechanical design of the machine are reviewed

  19. Hybrid Universities in Malaysia

    Science.gov (United States)

    Lee, Molly; Wan, Chang Da; Sirat, Morshidi

    2017-01-01

    Are Asian universities different from those in Western countries? Premised on the hypothesis that Asian universities are different because of hybridization between Western academic models and local traditional cultures, this paper investigates the hybrid characteristics in Malaysian universities resulting from interaction between contemporary…

  20. Cardiac hybrid imaging

    Energy Technology Data Exchange (ETDEWEB)

    Gaemperli, Oliver [University Hospital Zurich, Cardiac Imaging, Zurich (Switzerland); University Hospital Zurich, Nuclear Cardiology, Cardiovascular Center, Zurich (Switzerland); Kaufmann, Philipp A. [University Hospital Zurich, Cardiac Imaging, Zurich (Switzerland); Alkadhi, Hatem [University Hospital Zurich, Institute of Diagnostic and Interventional Radiology, Zurich (Switzerland)

    2014-05-15

    Hybrid cardiac single photon emission computed tomography (SPECT)/CT imaging allows combined assessment of anatomical and functional aspects of cardiac disease. In coronary artery disease (CAD), hybrid SPECT/CT imaging allows detection of coronary artery stenosis and myocardial perfusion abnormalities. The clinical value of hybrid imaging has been documented in several subsets of patients. In selected groups of patients, hybrid imaging improves the diagnostic accuracy to detect CAD compared to the single imaging techniques. Additionally, this approach facilitates functional interrogation of coronary stenoses and guidance with regard to revascularization procedures. Moreover, the anatomical information obtained from CT coronary angiography or coronary artery calcium scores (CACS) adds prognostic information over perfusion data from SPECT. The use of cardiac hybrid imaging has been favoured by the dissemination of dedicated hybrid systems and the release of dedicated image fusion software, which allow simple patient throughput for hybrid SPECT/CT studies. Further technological improvements such as more efficient detector technology to allow for low-radiation protocols, ultra-fast image acquisition and improved low-noise image reconstruction algorithms will be instrumental to further promote hybrid SPECT/CT in research and clinical practice. (orig.)

  1. Hybrid job shop scheduling

    NARCIS (Netherlands)

    Schutten, Johannes M.J.

    1995-01-01

    We consider the problem of scheduling jobs in a hybrid job shop. We use the term 'hybrid' to indicate that we consider a lot of extensions of the classic job shop, such as transportation times, multiple resources, and setup times. The Shifting Bottleneck procedure can be generalized to deal with

  2. Hybrid Shipboard Microgrids

    DEFF Research Database (Denmark)

    Othman @ Marzuki, Muzaidi Bin; Anvari-Moghaddam, Amjad; Guerrero, Josep M.

    2017-01-01

    Strict regulation on emissions of air pollutants imposed by the maritime authorities has led to the introduction of hybrid microgrids to the shipboard power systems (SPSs) which acts toward energy efficient ships with less pollution. A hybrid energy system can include different means of generation...

  3. Hybrid intelligent engineering systems

    CERN Document Server

    Jain, L C; Adelaide, Australia University of

    1997-01-01

    This book on hybrid intelligent engineering systems is unique, in the sense that it presents the integration of expert systems, neural networks, fuzzy systems, genetic algorithms, and chaos engineering. It shows that these new techniques enhance the capabilities of one another. A number of hybrid systems for solving engineering problems are presented.

  4. Editorial: Hybrid Systems

    DEFF Research Database (Denmark)

    Olderog, Ernst-Rüdiger; Ravn, Anders Peter

    2007-01-01

    An introduction to three papers in a special issue on Hybrid Systems. These paper were first presented at an IFIP WG 2.2 meeting in Skagen 2005.......An introduction to three papers in a special issue on Hybrid Systems. These paper were first presented at an IFIP WG 2.2 meeting in Skagen 2005....

  5. Screening for Plant Features

    NARCIS (Netherlands)

    Heijden, van der G.W.A.M.; Polder, G.

    2015-01-01

    In this chapter, an overview of different plant features is given, from (sub)cellular to canopy level. A myriad of methods is available to measure these features using image analysis, and often, multiple methods can be used to measure the same feature. Several criteria are listed for choosing a

  6. Course on hybrid calculation

    International Nuclear Information System (INIS)

    Weill, J.; Tellier; Bonnemay; Craigne; Chareton; Di Falco

    1969-02-01

    After a definition of hybrid calculation (combination of analogue and digital calculation) with a distinction between series and parallel hybrid computing, and a description of a hybrid computer structure and of task sharing between computers, this course proposes a description of hybrid hardware used in Saclay and Cadarache computing centres, and of operations performed by these systems. The next part addresses issues related to programming languages and software. The fourth part describes how a problem is organised for its processing on these computers. Methods of hybrid analysis are then addressed: resolution of optimisation problems, of partial differential equations, and of integral equations by means of different methods (gradient, maximum principle, characteristics, functional approximation, time slicing, Monte Carlo, Neumann iteration, Fischer iteration)

  7. Hybrid functional pseudopotentials

    Science.gov (United States)

    Yang, Jing; Tan, Liang Z.; Rappe, Andrew M.

    2018-02-01

    The consistency between the exchange-correlation functional used in pseudopotential construction and in the actual density functional theory calculation is essential for the accurate prediction of fundamental properties of materials. However, routine hybrid density functional calculations at present still rely on generalized gradient approximation pseudopotentials due to the lack of hybrid functional pseudopotentials. Here, we present a scheme for generating hybrid functional pseudopotentials, and we analyze the importance of pseudopotential density functional consistency for hybrid functionals. For the PBE0 hybrid functional, we benchmark our pseudopotentials for structural parameters and fundamental electronic gaps of the Gaussian-2 (G2) molecular dataset and some simple solids. Our results show that using our PBE0 pseudopotentials in PBE0 calculations improves agreement with respect to all-electron calculations.

  8. A hybrid scanning force and light microscope for surface imaging and three-dimensional optical sectioning in differential interference contrast.

    Science.gov (United States)

    Stemmer, A

    1995-04-01

    The design of a scanned-cantilever-type force microscope is presented which is fully integrated into an inverted high-resolution video-enhanced light microscope. This set-up allows us to acquire thin optical sections in differential interference contrast (DIC) or polarization while the force microscope is in place. Such a hybrid microscope provides a unique platform to study how cell surface properties determine, or are affected by, the three-dimensional dynamic organization inside the living cell. The hybrid microscope presented in this paper has proven reliable and versatile for biological applications. It is the only instrument that can image a specimen by force microscopy and high-power DIC without having either to translate the specimen or to remove the force microscope. Adaptation of the design features could greatly enhance the suitability of other force microscopes for biological work.

  9. Host Adaptation and Speciation through Hybridization and Polyploidy in Phytophthora

    Science.gov (United States)

    Bertier, Lien; Leus, Leen; D’hondt, Liesbet; de Cock, Arthur W. A. M.; Höfte, Monica

    2013-01-01

    It is becoming increasingly evident that interspecific hybridization is a common event in phytophthora evolution. Yet, the fundamental processes underlying interspecific hybridization and the consequences for its ecological fitness and distribution are not well understood. We studied hybridization events in phytophthora clade 8b. This is a cold-tolerant group of plant pathogenic oomycetes in which six host-specific species have been described that mostly attack winter-grown vegetables. Hybrid characterization was done by sequencing and cloning of two nuclear (ITS and Ypt1) and two mitochondrial loci (Cox1 and Nadh1) combined with DNA content estimation using flow cytometry. Three different mtDNA haplotypes were recovered among the presumed hybrid isolates, dividing the hybrids into three types, with different parental species involved. In the nuclear genes, additivity, i.e. the presence of two alleles coming from different parents, was detected. Hybrid isolates showed large variations in DNA content, which was positively correlated with the additivity in nuclear loci, indicating allopolyploid hybridization followed by a process of diploidization. Moreover, indications of homeologous recombination were found in the hybrids by cloning ITS products. The hybrid isolates have been isolated from a range of hosts that have not been reported previously for clade 8b species, indicating that they have novel pathogenic potential. Next to this, DNA content measurements of the non-hybrid clade 8b species suggest that polyploidy is a common feature of this clade. We hypothesize that interspecific hybridization and polyploidy are two linked phenomena in phytophthora, and that these processes might play an important and ongoing role in the evolution of this genus. PMID:24386473

  10. Weather forecasting based on hybrid neural model

    Science.gov (United States)

    Saba, Tanzila; Rehman, Amjad; AlGhamdi, Jarallah S.

    2017-11-01

    Making deductions and expectations about climate has been a challenge all through mankind's history. Challenges with exact meteorological directions assist to foresee and handle problems well in time. Different strategies have been investigated using various machine learning techniques in reported forecasting systems. Current research investigates climate as a major challenge for machine information mining and deduction. Accordingly, this paper presents a hybrid neural model (MLP and RBF) to enhance the accuracy of weather forecasting. Proposed hybrid model ensure precise forecasting due to the specialty of climate anticipating frameworks. The study concentrates on the data representing Saudi Arabia weather forecasting. The main input features employed to train individual and hybrid neural networks that include average dew point, minimum temperature, maximum temperature, mean temperature, average relative moistness, precipitation, normal wind speed, high wind speed and average cloudiness. The output layer composed of two neurons to represent rainy and dry weathers. Moreover, trial and error approach is adopted to select an appropriate number of inputs to the hybrid neural network. Correlation coefficient, RMSE and scatter index are the standard yard sticks adopted for forecast accuracy measurement. On individual standing MLP forecasting results are better than RBF, however, the proposed simplified hybrid neural model comes out with better forecasting accuracy as compared to both individual networks. Additionally, results are better than reported in the state of art, using a simple neural structure that reduces training time and complexity.

  11. Hybrid fission-fusion nuclear reactors

    International Nuclear Information System (INIS)

    Zucchetti, Massimo

    2011-01-01

    A fusion-fission hybrid could contribute to all components of nuclear power - fuel supply, electricity production, and waste management. The idea of the fusion-fission hybrid is many decades old. Several ideas, both new and revisited, have been investigated by hybrid proponents. These ideas appear to have attractive features, but they require various levels of advances in plasma science and fusion and nuclear technology. As a first step towards the development of hybrid reactors, fusion neutron sources can be considered as an option. Compact high-field tokamaks can be a candidate for being the neutron source in a fission-fusion hybrid, essentially due to their design characteristics, such as compact dimensions, high magnetic field, flexibility of operation. This study presents the development of a tokamak neutron source for a material testing facility using an Ignitor-based concept. The computed values show the potential of this neutron-rich device for fusion materials testing. Some full-power months of operation are sufficient to obtain relevant radiation damage values in terms of dpa. (Author)

  12. Optimization of the fission--fusion hybrid concept

    International Nuclear Information System (INIS)

    Saltmarsh, M.J.; Grimes, W.R.; Santoro, R.T.

    1979-04-01

    One of the potentially attractive applications of controlled thermonuclear fusion is the fission--fusion hybrid concept. In this report we examine the possible role of the hybrid as a fissile fuel producer. We parameterize the advantages of the concept in terms of the performance of the fusion device and the breeding blanket and discuss some of the more troublesome features of existing design studies. The analysis suggests that hybrids based on deuterium--tritium (D--T) fusion devices are unlikely to be economically attractive and that they present formidable blanket technology problems. We suggest an alternative approach based on a semicatalyzed deuterium--deuterium (D--D) fusion reactor and a molten salt blanket. This concept is shown to emphasize the desirable features of the hybrid, to have considerably greater economic potential, and to mitigate many of the disadvantages of D--T-based systems

  13. A hybrid model for the computationally-efficient simulation of the cerebellar granular layer

    Directory of Open Access Journals (Sweden)

    Anna eCattani

    2016-04-01

    Full Text Available The aim of the present paper is to efficiently describe the membrane potential dynamics of neural populations formed by species having a high density difference in specific brain areas. We propose a hybrid model whose main ingredients are a conductance-based model (ODE system and its continuous counterpart (PDE system obtained through a limit process in which the number of neurons confined in a bounded region of the brain tissue is sent to infinity. Specifically, in the discrete model, each cell is described by a set of time-dependent variables, whereas in the continuum model, cells are grouped into populations that are described by a set of continuous variables.Communications between populations, which translate into interactions among the discrete and the continuous models, are the essence of the hybrid model we present here. The cerebellum and cerebellum-like structures show in their granular layer a large difference in the relative density of neuronal species making them a natural testing ground for our hybrid model. By reconstructing the ensemble activity of the cerebellar granular layer network and by comparing our results to a more realistic computational network, we demonstrate that our description of the network activity, even though it is not biophysically detailed, is still capable of reproducing salient features of neural network dynamics. Our modeling approach yields a significant computational cost reduction by increasing the simulation speed at least $270$ times. The hybrid model reproduces interesting dynamics such as local microcircuit synchronization, traveling waves, center-surround and time-windowing.

  14. Zebrafish Expression Ontology of Gene Sets (ZEOGS): a tool to analyze enrichment of zebrafish anatomical terms in large gene sets.

    Science.gov (United States)

    Prykhozhij, Sergey V; Marsico, Annalisa; Meijsing, Sebastiaan H

    2013-09-01

    The zebrafish (Danio rerio) is an established model organism for developmental and biomedical research. It is frequently used for high-throughput functional genomics experiments, such as genome-wide gene expression measurements, to systematically analyze molecular mechanisms. However, the use of whole embryos or larvae in such experiments leads to a loss of the spatial information. To address this problem, we have developed a tool called Zebrafish Expression Ontology of Gene Sets (ZEOGS) to assess the enrichment of anatomical terms in large gene sets. ZEOGS uses gene expression pattern data from several sources: first, in situ hybridization experiments from the Zebrafish Model Organism Database (ZFIN); second, it uses the Zebrafish Anatomical Ontology, a controlled vocabulary that describes connected anatomical structures; and third, the available connections between expression patterns and anatomical terms contained in ZFIN. Upon input of a gene set, ZEOGS determines which anatomical structures are overrepresented in the input gene set. ZEOGS allows one for the first time to look at groups of genes and to describe them in terms of shared anatomical structures. To establish ZEOGS, we first tested it on random gene selections and on two public microarray datasets with known tissue-specific gene expression changes. These tests showed that ZEOGS could reliably identify the tissues affected, whereas only very few enriched terms to none were found in the random gene sets. Next we applied ZEOGS to microarray datasets of 24 and 72 h postfertilization zebrafish embryos treated with beclomethasone, a potent glucocorticoid. This analysis resulted in the identification of several anatomical terms related to glucocorticoid-responsive tissues, some of which were stage-specific. Our studies highlight the ability of ZEOGS to extract spatial information from datasets derived from whole embryos, indicating that ZEOGS could be a useful tool to automatically analyze gene expression

  15. Zebrafish Expression Ontology of Gene Sets (ZEOGS): A Tool to Analyze Enrichment of Zebrafish Anatomical Terms in Large Gene Sets

    Science.gov (United States)

    Marsico, Annalisa

    2013-01-01

    Abstract The zebrafish (Danio rerio) is an established model organism for developmental and biomedical research. It is frequently used for high-throughput functional genomics experiments, such as genome-wide gene expression measurements, to systematically analyze molecular mechanisms. However, the use of whole embryos or larvae in such experiments leads to a loss of the spatial information. To address this problem, we have developed a tool called Zebrafish Expression Ontology of Gene Sets (ZEOGS) to assess the enrichment of anatomical terms in large gene sets. ZEOGS uses gene expression pattern data from several sources: first, in situ hybridization experiments from the Zebrafish Model Organism Database (ZFIN); second, it uses the Zebrafish Anatomical Ontology, a controlled vocabulary that describes connected anatomical structures; and third, the available connections between expression patterns and anatomical terms contained in ZFIN. Upon input of a gene set, ZEOGS determines which anatomical structures are overrepresented in the input gene set. ZEOGS allows one for the first time to look at groups of genes and to describe them in terms of shared anatomical structures. To establish ZEOGS, we first tested it on random gene selections and on two public microarray datasets with known tissue-specific gene expression changes. These tests showed that ZEOGS could reliably identify the tissues affected, whereas only very few enriched terms to none were found in the random gene sets. Next we applied ZEOGS to microarray datasets of 24 and 72 h postfertilization zebrafish embryos treated with beclomethasone, a potent glucocorticoid. This analysis resulted in the identification of several anatomical terms related to glucocorticoid-responsive tissues, some of which were stage-specific. Our studies highlight the ability of ZEOGS to extract spatial information from datasets derived from whole embryos, indicating that ZEOGS could be a useful tool to automatically analyze gene

  16. Exploring Human Capital and Hybrid Entrepreneurship

    DEFF Research Database (Denmark)

    Klyver, Kim; Lomberg, Carina; Steffens, Paul

    2016-01-01

    ’s human capital influences entrepreneurial pursuits as a two stage process, first shaping whether nascent entrepreneurship and/or employment enters an individual’s consideration set when they are facing a career transition and second influencing the outcomes of entrepreneurial pursuits. Using a novel...... longitudinal dataset of individuals facing career transition as nascent entrepreneurs, job seekers or both, we find that while hybrid nascent entrepreneurship (trying to start a business while being employed) has a positive influence on outcomes, hybrid search (concurrent job search while trying to start...

  17. Generalised Computability and Applications to Hybrid Systems

    DEFF Research Database (Denmark)

    Korovina, Margarita V.; Kudinov, Oleg V.

    2001-01-01

    We investigate the concept of generalised computability of operators and functionals defined on the set of continuous functions, firstly introduced in [9]. By working in the reals, with equality and without equality, we study properties of generalised computable operators and functionals. Also we...... propose an interesting application to formalisation of hybrid systems. We obtain some class of hybrid systems, which trajectories are computable in the sense of computable analysis. This research was supported in part by the RFBR (grants N 99-01-00485, N 00-01- 00810) and by the Siberian Branch of RAS (a...... grant for young researchers, 2000)...

  18. Electric and hydraulic hybrid actuator. Competing and complementary systems?; Elektrische und hydraulische Hybridantriebe. Konkurrierende oder komplementaere Systeme?

    Energy Technology Data Exchange (ETDEWEB)

    Dehnert, Klaus [Eaton Corporation, Rastatt (Germany)

    2011-07-01

    Hybrid drives for commercial vehicles and for mobile processing machines are evolving rapidly to a future-oriented technology. Hybrid drives significantly affect issues such as fuel efficiency, emissions, productivity and life cycle cost. For recovery and storage of kinetic energy, different technologies are used. Under this aspect, the author of the contribution under consideration reports on the key distinguishing features of some currently available hybrid concepts and their appropriate application. In the selection of suitable hydraulic hybrid drive systems, the essential features of different hybrid systems have to be considered.

  19. First-Class Object Sets

    DEFF Research Database (Denmark)

    Ernst, Erik

    Typically, objects are monolithic entities with a fixed interface. To increase the flexibility in this area, this paper presents first-class object sets as a language construct. An object set offers an interface which is a disjoint union of the interfaces of its member objects. It may also be used...... for a special kind of method invocation involving multiple objects in a dynamic lookup process. With support for feature access and late-bound method calls object sets are similar to ordinary objects, only more flexible. The approach is made precise by means of a small calculus, and the soundness of its type...

  20. Hybrid Wars: Israel’s experience

    Directory of Open Access Journals (Sweden)

    E. N. Grachikov

    2015-01-01

    Full Text Available The article attempts to summarize the experience of Israel in the fight against non-traditional threats, which escalated into a hybrid war. Feature of these wars lies in the fact that they are usually conducted between Western and non-Western countries in the border and poorly controlled space. West opponents favor alliances and associations of non-Western countries and non-state actors. In this case, to justify the war, the norms of international law are used.

  1. Feature singletons attract spatial attention independently of feature priming.

    Science.gov (United States)

    Yashar, Amit; White, Alex L; Fang, Wanghaoming; Carrasco, Marisa

    2017-08-01

    People perform better in visual search when the target feature repeats across trials (intertrial feature priming [IFP]). Here, we investigated whether repetition of a feature singleton's color modulates stimulus-driven shifts of spatial attention by presenting a probe stimulus immediately after each singleton display. The task alternated every two trials between a probe discrimination task and a singleton search task. We measured both stimulus-driven spatial attention (via the distance between the probe and singleton) and IFP (via repetition of the singleton's color). Color repetition facilitated search performance (IFP effect) when the set size was small. When the probe appeared at the singleton's location, performance was better than at the opposite location (stimulus-driven attention effect). The magnitude of this attention effect increased with the singleton's set size (which increases its saliency) but did not depend on whether the singleton's color repeated across trials, even when the previous singleton had been attended as a search target. Thus, our findings show that repetition of a salient singleton's color affects performance when the singleton is task relevant and voluntarily attended (as in search trials). However, color repetition does not affect performance when the singleton becomes irrelevant to the current task, even though the singleton does capture attention (as in probe trials). Therefore, color repetition per se does not make a singleton more salient for stimulus-driven attention. Rather, we suggest that IFP requires voluntary selection of color singletons in each consecutive trial.

  2. A new MCNP trademark test set

    International Nuclear Information System (INIS)

    Brockhoff, R.C.; Hendricks, J.S.

    1994-09-01

    The MCNP test set is used to test the MCNP code after installation on various computer platforms. For MCNP4 and MCNP4A this test set included 25 test problems designed to test as many features of the MCNP code as possible. A new and better test set has been devised to increase coverage of the code from 85% to 97% with 28 problems. The new test set is as fast as and shorter than the MCNP4A test set. The authors describe the methodology for devising the new test set, the features that were not covered in the MCNP4A test set, and the changes in the MCNP4A test set that have been made for MCNP4B and its developmental versions. Finally, new bugs uncovered by the new test set and a compilation of all known MCNP4A bugs are presented

  3. Genome-wide mapping in a house mouse hybrid zone reveals hybrid sterility loci and Dobzhansky-Muller interactions.

    Science.gov (United States)

    Turner, Leslie M; Harr, Bettina

    2014-12-09

    Mapping hybrid defects in contact zones between incipient species can identify genomic regions contributing to reproductive isolation and reveal genetic mechanisms of speciation. The house mouse features a rare combination of sophisticated genetic tools and natural hybrid zones between subspecies. Male hybrids often show reduced fertility, a common reproductive barrier between incipient species. Laboratory crosses have identified sterility loci, but each encompasses hundreds of genes. We map genetic determinants of testis weight and testis gene expression using offspring of mice captured in a hybrid zone between M. musculus musculus and M. m. domesticus. Many generations of admixture enables high-resolution mapping of loci contributing to these sterility-related phenotypes. We identify complex interactions among sterility loci, suggesting multiple, non-independent genetic incompatibilities contribute to barriers to gene flow in the hybrid zone.

  4. Artificial Neural Network and Genetic Algorithm Hybrid Intelligence for Predicting Thai Stock Price Index Trend

    Science.gov (United States)

    Boonjing, Veera; Intakosum, Sarun

    2016-01-01

    This study investigated the use of Artificial Neural Network (ANN) and Genetic Algorithm (GA) for prediction of Thailand's SET50 index trend. ANN is a widely accepted machine learning method that uses past data to predict future trend, while GA is an algorithm that can find better subsets of input variables for importing into ANN, hence enabling more accurate prediction by its efficient feature selection. The imported data were chosen technical indicators highly regarded by stock analysts, each represented by 4 input variables that were based on past time spans of 4 different lengths: 3-, 5-, 10-, and 15-day spans before the day of prediction. This import undertaking generated a big set of diverse input variables with an exponentially higher number of possible subsets that GA culled down to a manageable number of more effective ones. SET50 index data of the past 6 years, from 2009 to 2014, were used to evaluate this hybrid intelligence prediction accuracy, and the hybrid's prediction results were found to be more accurate than those made by a method using only one input variable for one fixed length of past time span. PMID:27974883

  5. A Hybrid System for Subjectivity Analysis

    Directory of Open Access Journals (Sweden)

    Samir Rustamov

    2018-01-01

    Full Text Available We suggested different structured hybrid systems for the sentence-level subjectivity analysis based on three supervised machine learning algorithms, namely, Hidden Markov Model, Fuzzy Control System, and Adaptive Neuro-Fuzzy Inference System. The suggested feature extraction algorithm in our experiment computes a feature vector using statistical textual terms frequencies in a training dataset not having the use of any lexical knowledge except tokenization. Taking into consideration this fact, the above-mentioned methods may be employed in other languages as these methods do not utilize the morphological, syntactical, and lexical analysis in the classification problems.

  6. Hybrid electric vehicles TOPTEC

    Energy Technology Data Exchange (ETDEWEB)

    NONE

    1994-06-21

    This one-day TOPTEC session began with an overview of hybrid electric vehicle technology. Updates were given on alternative types of energy storage, APU control for low emissions, simulation programs, and industry and government activities. The keynote speech was about battery technology, a key element to the success of hybrids. The TOPEC concluded with a panel discussion on the mission of hybrid electric vehicles, with a perspective from industry and government experts from United States and Canada on their view of the role of this technology.

  7. Hybrid systems with constraints

    CERN Document Server

    Daafouz, Jamal; Sigalotti, Mario

    2013-01-01

    Control theory is the main subject of this title, in particular analysis and control design for hybrid dynamic systems.The notion of hybrid systems offers a strong theoretical and unified framework to cope with the modeling, analysis and control design of systems where both continuous and discrete dynamics interact. The theory of hybrid systems has been the subject of intensive research over the last decade and a large number of diverse and challenging problems have been investigated. Nevertheless, many important mathematical problems remain open.This book is dedicated mainly to

  8. Towers of hybrid mesons

    International Nuclear Information System (INIS)

    Semay, Claude; Buisseret, Fabien; Silvestre-Brac, Bernard

    2009-01-01

    A hybrid meson is a quark-antiquark pair in which, contrary to ordinary mesons, the gluon field is in an excited state. In the framework of constituent models, the interaction potential is assumed to be the energy of an excited string. An approximate, but accurate, analytical solution of the Schroedinger equation with such a potential is presented. When applied to hybrid charmonia and bottomonia, towers of states are predicted in which the masses are a linear function of a harmonic oscillator band number for the quark-antiquark pair. Such a formula could be a reliable guide for the experimental detection of heavy hybrid mesons.

  9. Hybrid Bloch brane

    Energy Technology Data Exchange (ETDEWEB)

    Bazeia, D.; Lima, Elisama E.M.; Losano, L. [Universidade Federal da Paraiba, Departamento de Fisica, Joao Pessoa, PB (Brazil)

    2017-02-15

    This work reports on models described by two real scalar fields coupled with gravity in the five-dimensional spacetime, with a warped geometry involving one infinite extra dimension. Through a mechanism that smoothly changes a thick brane into a hybrid brane, one investigates the appearance of hybrid branes hosting internal structure, characterized by the splitting on the energy density and the volcano potential, induced by the parameter which controls interactions between the two scalar fields. In particular, we investigate distinct symmetric and asymmetric hybrid brane scenarios. (orig.)

  10. DYNAMIC FEATURE SELECTION FOR WEB USER IDENTIFICATION ON LINGUISTIC AND STYLISTIC FEATURES OF ONLINE TEXTS

    Directory of Open Access Journals (Sweden)

    A. A. Vorobeva

    2017-01-01

    Full Text Available The paper deals with identification and authentication of web users participating in the Internet information processes (based on features of online texts.In digital forensics web user identification based on various linguistic features can be used to discover identity of individuals, criminals or terrorists using the Internet to commit cybercrimes. Internet could be used as a tool in different types of cybercrimes (fraud and identity theft, harassment and anonymous threats, terrorist or extremist statements, distribution of illegal content and information warfare. Linguistic identification of web users is a kind of biometric identification, it can be used to narrow down the suspects, identify a criminal and prosecute him. Feature set includes various linguistic and stylistic features extracted from online texts. We propose dynamic feature selection for each web user identification task. Selection is based on calculating Manhattan distance to k-nearest neighbors (Relief-f algorithm. This approach improves the identification accuracy and minimizes the number of features. Experiments were carried out on several datasets with different level of class imbalance. Experiment results showed that features relevance varies in different set of web users (probable authors of some text; features selection for each set of web users improves identification accuracy by 4% at the average that is approximately 1% higher than with the use of static set of features. The proposed approach is most effective for a small number of training samples (messages per user.

  11. Destination bonding: Hybrid cognition using Instagram

    Directory of Open Access Journals (Sweden)

    Arup Kumar Baksi

    2015-01-01

    Full Text Available Empirical research has identified the phenomenon of destination bonding as a result of summated physical and emotional values associated with the destination. Physical values, namely natural landscape & other physical settings and emotional values, namely the enculturation processes, have a significant role to play in portraying visitors’ cognitive framework for destination preference. The physical values seemed to be the stimulator for bonding that embodies action or behavior tendencies in imagery. The emotional values were the conditions that lead to affective bonding and are reflected in attitudes for a place which were evident in text narratives. Social networking on virtual platforms offers the scope for hybrid cognitive expression using imagery and text to the visitors. Instagram has emerged as an application-window to capture these hybrid cognitions of visitors. This study focuses on assessing the relationship between hybrid cognition of visitors expressed via Instagram and their bond with the destination. Further to this, the study attempts to examine the impact of hybrid cognition of visitors on the behavioral pattern of prospective visitors to the destination. The study revealed that sharing of visual imageries and related text by the visitors is an expression of the physico-emotional bonding with the destination. It was further established that hybrid cognition strongly asserts destination bonding and has been also found to have moderating impact on the link between destination bonding and electronic-word-of-mouth.

  12. A hybrid mammalian cell cycle model

    Directory of Open Access Journals (Sweden)

    Vincent Noël

    2013-08-01

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

  13. Formula hybrid SAE.

    Science.gov (United States)

    2013-09-01

    User-friendly tools are needed for undergraduates to learn about component sizing, powertrain integration, and control : strategies for student competitions involving hybrid vehicles. A TK Solver tool was developed at the University of Idaho for : th...

  14. Hybrid adsorptive membrane reactor

    Science.gov (United States)

    Tsotsis, Theodore T [Huntington Beach, CA; Sahimi, Muhammad [Altadena, CA; Fayyaz-Najafi, Babak [Richmond, CA; Harale, Aadesh [Los Angeles, CA; Park, Byoung-Gi [Yeosu, KR; Liu, Paul K. T. [Lafayette Hill, PA

    2011-03-01

    A hybrid adsorbent-membrane reactor in which the chemical reaction, membrane separation, and product adsorption are coupled. Also disclosed are a dual-reactor apparatus and a process using the reactor or the apparatus.

  15. Hybrid plasmachemical reactor

    Energy Technology Data Exchange (ETDEWEB)

    Lelevkin, V. M., E-mail: lelevkin44@mail.ru; Smirnova, Yu. G.; Tokarev, A. V. [Kyrgyz-Russian Slavic University (Kyrgyzstan)

    2015-04-15

    A hybrid plasmachemical reactor on the basis of a dielectric barrier discharge in a transformer is developed. The characteristics of the reactor as functions of the dielectric barrier discharge parameters are determined.

  16. Marine Fish Hybridization

    KAUST Repository

    He, Song

    2017-01-01

    for each hybrid offspring in each case, haploweb analysis on diagnostic markers (nuclear and/or mitochondrial) and the DAPC/PCA analysis on microsatellite data were used. By combining the genetic evidences, morphological traits, and ecological observations

  17. PV-hybrid and mini-grid

    Energy Technology Data Exchange (ETDEWEB)

    NONE

    2010-07-01

    photovoltaic - fuel cell - direct storage - power supply units; (11) Djungle power - A more remote AC bus; (12) Quality control tools applied to a PV micro-grid in Ecuador; (13) Integral Evaluation of energy supply systems at Mountain Refuges; (14) Hyress project: Study case of Tunisia. Installation, set-up and first results; (15) PV hybrid systems on Mountain Huts: The experience with the project CAI ENERGIA 2000; (16) Process management in zero-emission communities: Adaptation of consumption and production; (17) TRNSYS simulation of a system consisted of PV panels and H{sub 2} production and storage to feed a Remote Telecom Application (HildrosolarH2); (18) Photovoltaic forecasting: A state of the art; (19) PV*SOL 5.0 standalone - Simulation of a stand-alone AC system; (20) Effect of wind speed and solar irradiation on the optimization of a PV wind battery system to supply a Telecommunications station; (21) Polysun: PV, wind and power-heat cogeneration in one design tool; (22) Comparative study between distributed and centralised PV generation in Island power systems under variable weather conditions; (23) Development of a test facility for PV-wind hybrid energy systems; (24) Evaluation of a micro PV-wind hybrid system in Nordic climate conditions; (25) Prismes: The INES micro-grid platform; (26) Estimation of statistical electric energy demand profiles of non electrified regions in Northern Brazil.

  18. Hybrid vertical cavity laser

    DEFF Research Database (Denmark)

    Chung, Il-Sug; Mørk, Jesper

    2010-01-01

    A new hybrid vertical cavity laser structure for silicon photonics is suggested and numerically investigated. It incorporates a silicon subwavelength grating as a mirror and a lateral output coupler to a silicon ridge waveguide.......A new hybrid vertical cavity laser structure for silicon photonics is suggested and numerically investigated. It incorporates a silicon subwavelength grating as a mirror and a lateral output coupler to a silicon ridge waveguide....

  19. FEATURES OF STUDENT PSYCHOLOGICAL COUNSELLING

    Directory of Open Access Journals (Sweden)

    Maria Dorina PASCA

    2013-10-01

    Full Text Available Student psychological counseling is one of the means to acknowledge student identity by employing counseling tools that allow the psychologist to make use of a set of skills essential in achieving envisaged outcomes. To act as counseling psychologist for students is to guide actions by the five wh- questions: who (the client is, why (the counselor is approached, who (the counselor talks to, what (problem the student has to tackle, how (the problem can be solved. Some of the most important features that contribute to solving student problems are the counselor’s deontology, trustworthiness and attitude that are to be relied on without impeding the client’s personality traits. Thus, developing awareness of the features underlying student psychological counseling and acting accordingly is the real test for any professional in the field. Therefore, the real challenge is not being in the lion’s den, but living with it.

  20. General unifying features of controlled quantum phenomena

    International Nuclear Information System (INIS)

    Pechen, Alexander; Brif, Constantin; Wu, Rebing; Chakrabarti, Raj; Rabitz, Herschel

    2010-01-01

    Many proposals have been put forth for controlling quantum phenomena, including open-loop, adaptive feedback, and real-time feedback control. Each of these approaches has been viewed as operationally, and even physically, distinct from the others. This work shows that all such scenarios inherently share the same fundamental control features residing in the topology of the landscape relating the target physical observable to the applied controls. This unified foundation may provide a basis for development of hybrid control schemes that would combine the advantages of the existing approaches to achieve the best overall performance.

  1. IMPULSE CONTROL HYBRID ELECTRICAL SYSTEM

    Directory of Open Access Journals (Sweden)

    A. A. Lobaty

    2016-01-01

    Full Text Available This paper extends the recently introduced approach for modeling and solving the optimal control problem of fixedswitched mode DC-DC power converter. DCDC converters are a class of electric power circuits that used extensively in regulated DC power supplies, DC motor drives of different types, in Photovoltaic Station energy conversion and other applications due to its advantageous features in terms of size, weight and reliable performance. The main problem in controlling this type converters is in their hybrid nature as the switched circuit topology entails different modes of operation, each of it with its own associated linear continuous-time dynamics.This paper analyses the modeling and controller synthesis of the fixed-frequency buck DC-DC converter, in which the transistor switch is operated by a pulse sequence with constant frequency. In this case the regulation of the DC component of the output voltage is via the duty cycle. The optimization of the control system is based on the formation of the control signal at the output.It is proposed to solve the problem of optimal control of a hybrid system based on the formation of the control signal at the output of the controller, which minimizes a given functional integral quality, which is regarded as a linear quadratic Letov-Kalman functional. Search method of optimal control depends on the type of mathematical model of control object. In this case, we consider a linear deterministic model of the control system, which is common for the majority of hybrid electrical systems. For this formulation of the optimal control problem of search is a problem of analytical design of optimal controller, which has the analytical solution.As an example of the hybrid system is considered a step-down switching DC-DC converter, which is widely used in various electrical systems: as an uninterruptible power supply, battery charger for electric vehicles, the inverter in solar photovoltaic power plants.. A

  2. Human hybrid hybridoma

    Energy Technology Data Exchange (ETDEWEB)

    Tiebout, R.F.; van Boxtel-Oosterhof, F.; Stricker, E.A.M.; Zeijlemaker, W.P.

    1987-11-15

    Hybrid hybridomas are obtained by fusion of two cells, each producing its own antibody. Several authors have reported the construction of murine hybrid hybridomas with the aim to obtain bispecific monoclonal antibodies. The authors have investigated, in a model system, the feasibility of constructing a human hybrid hybridoma. They fused two monoclonal cell lines: an ouabain-sensitive and azaserine/hypoxanthine-resistant Epstein-Barr virus-transformed human cell line that produces an IgG1kappa antibody directed against tetanus toxiod and an azaserine/hypoxanthine-sensitive and ouabain-resistant human-mouse xenohybrid cell line that produces a human IgG1lambda antibody directed against hepatitis-B surface antigen. Hybrid hybridoma cells were selected in culture medium containing azaserine/hypoxanthine and ouabain. The hybrid nature of the secreted antibodies was analyzed by means of two antigen-specific immunoassay. The results show that it is possible, with the combined use of transformation and xenohybridization techniques, to construct human hybrid hybridomas that produce bispecific antibodies. Bispecific antibodies activity was measured by means of two radioimmunoassays.

  3. Systems for hybrid cars

    Science.gov (United States)

    Bitsche, Otmar; Gutmann, Guenter

    Not only sharp competition but also legislation are pushing development of hybrid drive trains. Based on conventional internal combustion engine (ICE) vehicles, these drive trains offer a wide range of benefits from reduced fuel consumption and emission to multifaceted performance improvements. Hybrid electric drive trains may also facilitate the introduction of fuel cells (FC). The battery is the key component for all hybrid drive trains, as it dominates cost and performance issues. The selection of the right battery technology for the specific automotive application is an important task with an impact on costs of development and use. Safety, power, and high cycle life are a must for all hybrid applications. The greatest pressure to reduce cost is in soft hybrids, where lead-acid embedded in a considerate management presents the cheapest solution, with a considerable improvement in performance needed. From mild to full hybridization, an improvement in specific power makes higher costs more acceptable, provided that the battery's service life is equivalent to the vehicle's lifetime. Today, this is proven for the nickel-metal hydride system. Lithium ion batteries, which make use of a multiple safety concept, and with some development anticipated, provide even better prospects in terms of performance and costs. Also, their scalability permits their application in battery electric vehicles—the basis for better performance and enhanced user acceptance. Development targets for the batteries are discussed with a focus on system aspects such as electrical and thermal management and safety.

  4. Feature Selection for Chemical Sensor Arrays Using Mutual Information

    Science.gov (United States)

    Wang, X. Rosalind; Lizier, Joseph T.; Nowotny, Thomas; Berna, Amalia Z.; Prokopenko, Mikhail; Trowell, Stephen C.

    2014-01-01

    We address the problem of feature selection for classifying a diverse set of chemicals using an array of metal oxide sensors. Our aim is to evaluate a filter approach to feature selection with reference to previous work, which used a wrapper approach on the same data set, and established best features and upper bounds on classification performance. We selected feature sets that exhibit the maximal mutual information with the identity of the chemicals. The selected features closely match those found to perform well in the previous study using a wrapper approach to conduct an exhaustive search of all permitted feature combinations. By comparing the classification performance of support vector machines (using features selected by mutual information) with the performance observed in the previous study, we found that while our approach does not always give the maximum possible classification performance, it always selects features that achieve classification performance approaching the optimum obtained by exhaustive search. We performed further classification using the selected feature set with some common classifiers and found that, for the selected features, Bayesian Networks gave the best performance. Finally, we compared the observed classification performances with the performance of classifiers using randomly selected features. We found that the selected features consistently outperformed randomly selected features for all tested classifiers. The mutual information filter approach is therefore a computationally efficient method for selecting near optimal features for chemical sensor arrays. PMID:24595058

  5. A deep learning / neuroevolution hybrid for visual control

    DEFF Research Database (Denmark)

    Poulsen, Andreas Precht; Thorhauge, Mark; Funch, Mikkel Hvilshj

    2017-01-01

    This paper presents a deep learning / neuroevolution hybrid approach called DLNE, which allows FPS bots to learn to aim & shoot based only on high-dimensional raw pixel input. The deep learning component is responsible for visual recognition and translating raw pixels to compact feature...... representations, while the evolving network takes those features as inputs to infer actions. The results suggest that combining deep learning and neuroevolution in a hybrid approach is a promising research direction that could make complex visual domains directly accessible to networks trained through evolution....

  6. Causal Set Generator and Action Computer

    OpenAIRE

    Cunningham, William; Krioukov, Dmitri

    2017-01-01

    The causal set approach to quantum gravity has gained traction over the past three decades, but numerical experiments involving causal sets have been limited to relatively small scales. The software suite presented here provides a new framework for the generation and study of causal sets. Its efficiency surpasses previous implementations by several orders of magnitude. We highlight several important features of the code, including the compact data structures, the $O(N^2)$ causal set generatio...

  7. Volcanic features of Io

    International Nuclear Information System (INIS)

    Carr, M.H.; Masursky, H.; Strom, R.G.; Terrile, R.J.

    1979-01-01

    The volcanic features of Io as detected during the Voyager mission are discussed. The volcanic activity is apparently higher than on any other body in the Solar System. Its volcanic landforms are compared with features on Earth to indicate the type of volcanism present on Io. (U.K.)

  8. Improving Naive Bayes with Online Feature Selection for Quick Adaptation to Evolving Feature Usefulness

    Energy Technology Data Exchange (ETDEWEB)

    Pon, R K; Cardenas, A F; Buttler, D J

    2007-09-19

    The definition of what makes an article interesting varies from user to user and continually evolves even for a single user. As a result, for news recommendation systems, useless document features can not be determined a priori and all features are usually considered for interestingness classification. Consequently, the presence of currently useless features degrades classification performance [1], particularly over the initial set of news articles being classified. The initial set of document is critical for a user when considering which particular news recommendation system to adopt. To address these problems, we introduce an improved version of the naive Bayes classifier with online feature selection. We use correlation to determine the utility of each feature and take advantage of the conditional independence assumption used by naive Bayes for online feature selection and classification. The augmented naive Bayes classifier performs 28% better than the traditional naive Bayes classifier in recommending news articles from the Yahoo! RSS feeds.

  9. Social entrepreneurship in the Czech Republic: Current trends in research on hybridity

    OpenAIRE

    Vaceková, Gabriela; Soukopová, Jana; Křenková, Tereza

    2015-01-01

    The hybridity phenomenon has received increasing attention in the scientific literature worldwide. However, this is largely western literature, which is not perfectly suited to the transitional context of Central and Eastern Europe, respecting its specific features. The lack of relevant research on hybridity in the post-communist countries shows a considerable research gap that strongly indicates the need for deeper insight. The paper contributes to the conversation by rethinking hybridity in...

  10. An improved strategy for skin lesion detection and classification using uniform segmentation and feature selection based approach.

    Science.gov (United States)

    Nasir, Muhammad; Attique Khan, Muhammad; Sharif, Muhammad; Lali, Ikram Ullah; Saba, Tanzila; Iqbal, Tassawar

    2018-02-21

    Melanoma is the deadliest type of skin cancer with highest mortality rate. However, the annihilation in early stage implies a high survival rate therefore, it demands early diagnosis. The accustomed diagnosis methods are costly and cumbersome due to the involvement of experienced experts as well as the requirements for highly equipped environment. The recent advancements in computerized solutions for these diagnoses are highly promising with improved accuracy and efficiency. In this article, we proposed a method for the classification of melanoma and benign skin lesions. Our approach integrates preprocessing, lesion segmentation, features extraction, features selection, and classification. Preprocessing is executed in the context of hair removal by DullRazor, whereas lesion texture and color information are utilized to enhance the lesion contrast. In lesion segmentation, a hybrid technique has been implemented and results are fused using additive law of probability. Serial based method is applied subsequently that extracts and fuses the traits such as color, texture, and HOG (shape). The fused features are selected afterwards by implementing a novel Boltzman Entropy method. Finally, the selected features are classified by Support Vector Machine. The proposed method is evaluated on publically available data set PH2. Our approach has provided promising results of sensitivity 97.7%, specificity 96.7%, accuracy 97.5%, and F-score 97.5%, which are significantly better than the results of existing methods available on the same data set. The proposed method detects and classifies melanoma significantly good as compared to existing methods. © 2018 Wiley Periodicals, Inc.

  11. JCE Feature Columns

    Science.gov (United States)

    Holmes, Jon L.

    1999-05-01

    The Features area of JCE Online is now readily accessible through a single click from our home page. In the Features area each column is linked to its own home page. These column home pages also have links to them from the online Journal Table of Contents pages or from any article published as part of that feature column. Using these links you can easily find abstracts of additional articles that are related by topic. Of course, JCE Online+ subscribers are then just one click away from the entire article. Finding related articles is easy because each feature column "site" contains links to the online abstracts of all the articles that have appeared in the column. In addition, you can find the mission statement for the column and the email link to the column editor that I mentioned above. At the discretion of its editor, a feature column site may contain additional resources. As an example, the Chemical Information Instructor column edited by Arleen Somerville will have a periodically updated bibliography of resources for teaching and using chemical information. Due to the increase in the number of these resources available on the WWW, it only makes sense to publish this information online so that you can get to these resources with a simple click of the mouse. We expect that there will soon be additional information and resources at several other feature column sites. Following in the footsteps of the Chemical Information Instructor, up-to-date bibliographies and links to related online resources can be made available. We hope to extend the online component of our feature columns with moderated online discussion forums. If you have a suggestion for an online resource you would like to see included, let the feature editor or JCE Online (jceonline@chem.wisc.edu) know about it. JCE Internet Features JCE Internet also has several feature columns: Chemical Education Resource Shelf, Conceptual Questions and Challenge Problems, Equipment Buyers Guide, Hal's Picks, Mathcad

  12. Conversion of localized lower hybrid oscillations and fast magnetosonic waves at a plasma density cavity

    International Nuclear Information System (INIS)

    Hall, J.O.

    2004-01-01

    Analytic expressions are presented for conversion of localized lower hybrid oscillations and magnetosonic waves by scattering off a small scale density cavity. The governing equations are solved in slab geometry with wave vectors perpendicular to both the ambient magnetic field and the density gradient associated with density cavity using a scale length separation method. The theory predicts strong excitation of localized lower hybrid oscillations for a set of frequencies between the lower hybrid frequency of the ambient plasma and the minimum lower hybrid frequency inside the cavity. The theory is relevant for the lower hybrid solitary structures observed in space plasmas

  13. Hybrid Propulsion Demonstration Program 250K Hybrid Motor

    Science.gov (United States)

    Story, George; Zoladz, Tom; Arves, Joe; Kearney, Darren; Abel, Terry; Park, O.

    2003-01-01

    The Hybrid Propulsion Demonstration Program (HPDP) program was formed to mature hybrid propulsion technology to a readiness level sufficient to enable commercialization for various space launch applications. The goal of the HPDP was to develop and test a 250,000 pound vacuum thrust hybrid booster in order to demonstrate hybrid propulsion technology and enable manufacturing of large hybrid boosters for current and future space launch vehicles. The HPDP has successfully conducted four tests of the 250,000 pound thrust hybrid rocket motor at NASA's Stennis Space Center. This paper documents the test series.

  14. A Structural Model Decomposition Framework for Hybrid Systems Diagnosis

    Science.gov (United States)

    Daigle, Matthew; Bregon, Anibal; Roychoudhury, Indranil

    2015-01-01

    Nowadays, a large number of practical systems in aerospace and industrial environments are best represented as hybrid systems that consist of discrete modes of behavior, each defined by a set of continuous dynamics. These hybrid dynamics make the on-line fault diagnosis task very challenging. In this work, we present a new modeling and diagnosis framework for hybrid systems. Models are composed from sets of user-defined components using a compositional modeling approach. Submodels for residual generation are then generated for a given mode, and reconfigured efficiently when the mode changes. Efficient reconfiguration is established by exploiting causality information within the hybrid system models. The submodels can then be used for fault diagnosis based on residual generation and analysis. We demonstrate the efficient causality reassignment, submodel reconfiguration, and residual generation for fault diagnosis using an electrical circuit case study.

  15. Theory of the Quantum Dot Hybrid Qubit

    Science.gov (United States)

    Friesen, Mark

    2015-03-01

    The quantum dot hybrid qubit, formed from three electrons in two quantum dots, combines the desirable features of charge qubits (fast manipulation) and spin qubits (long coherence times). The hybridized spin and charge states yield a unique energy spectrum with several useful properties, including two different operating regimes that are relatively immune to charge noise due to the presence of optimal working points or ``sweet spots.'' In this talk, I will describe dc and ac-driven gate operations of the quantum dot hybrid qubit. I will analyze improvements in the dephasing that are enabled by the sweet spots, and I will discuss the outlook for quantum hybrid qubits in terms of scalability. This work was supported in part by ARO (W911NF-12-0607), NSF (PHY-1104660), the USDOD, and the Intelligence Community Postdoctoral Research Fellowship Program. The views and conclusions contained in this presentation are those of the authors and should not be interpreted as representing the official policies or endorsements, either expressed or implied, of the US government.

  16. Nitrous Oxide/Paraffin Hybrid Rocket Engines

    Science.gov (United States)

    Zubrin, Robert; Snyder, Gary

    2010-01-01

    Nitrous oxide/paraffin (N2OP) hybrid rocket engines have been invented as alternatives to other rocket engines especially those that burn granular, rubbery solid fuels consisting largely of hydroxyl- terminated polybutadiene (HTPB). Originally intended for use in launching spacecraft, these engines would also be suitable for terrestrial use in rocket-assisted takeoff of small airplanes. The main novel features of these engines are (1) the use of reinforced paraffin as the fuel and (2) the use of nitrous oxide as the oxidizer. Hybrid (solid-fuel/fluid-oxidizer) rocket engines offer advantages of safety and simplicity over fluid-bipropellant (fluid-fuel/fluid-oxidizer) rocket en - gines, but the thrusts of HTPB-based hybrid rocket engines are limited by the low regression rates of the fuel grains. Paraffin used as a solid fuel has a regression rate about 4 times that of HTPB, but pure paraffin fuel grains soften when heated; hence, paraffin fuel grains can, potentially, slump during firing. In a hybrid engine of the present type, the paraffin is molded into a 3-volume-percent graphite sponge or similar carbon matrix, which supports the paraffin against slumping during firing. In addition, because the carbon matrix material burns along with the paraffin, engine performance is not appreciably degraded by use of the matrix.

  17. Development of Premacy Hydrogen RE Hybrid

    Energy Technology Data Exchange (ETDEWEB)

    Wakayama, N. [Mazda Motor Corporation, Hiroshima (Japan)

    2010-07-01

    Hydrogen powered ICE (internal combustion engine) vehicles can play an important role as an automotive power source in the future, because of its higher reliability and cost performance than those of fuel cell vehicles. Combined with hydrogen, Mazda's unique rotary engine (RE) has merits such as a prevention of hydrogen pre-ignition. Mazda has been developing hydrogen vehicles with the hydrogen RE from the early 1990s. Premacy (Mazda5) Hydrogen RE Hybrid was developed and launched in 2009, following RX-8 Hydrogen RE delivered in 2006. A series hybrid system was adopted in Premacy Hydrogen RE Hybrid. A traction motor switches its windings while the vehicle is moving. This switching technology allows the motor to be small and high-efficient. The lithium-ion high voltage battery, which has excellent input-output characteristics, was installed. These features extend the hydrogen fuel driving range to 200 km and obtain excellent acceleration performance. The hydrogen RE can be also operated by gasoline (Dual Fuel System). The additional gasoline operation makes hydrogen vehicles possible to drive in non-hydrogen station area. With approval from the Japanese Ministry of Land Infrastructure and Transport, Mazda Premacy Hydrogen RE Hybrid was delivered successfully to the Japanese market in the form of leasing. (orig.)

  18. Fusion-fission hybrid reactors

    International Nuclear Information System (INIS)

    Greenspan, E.

    1984-01-01

    This chapter discusses the range of characteristics attainable from hybrid reactor blankets; blanket design considerations; hybrid reactor designs; alternative fuel hybrid reactors; multi-purpose hybrid reactors; and hybrid reactors and the energy economy. Hybrid reactors are driven by a fusion neutron source and include fertile and/or fissile material. The fusion component provides a copious source of fusion neutrons which interact with a subcritical fission component located adjacent to the plasma or pellet chamber. Fissile fuel and/or energy are the main products of hybrid reactors. Topics include high F/M blankets, the fissile (and tritium) breeding ratio, effects of composition on blanket properties, geometrical considerations, power density and first wall loading, variations of blanket properties with irradiation, thermal-hydraulic and mechanical design considerations, safety considerations, tokamak hybrid reactors, tandem-mirror hybrid reactors, inertial confinement hybrid reactors, fusion neutron sources, fissile-fuel and energy production ability, simultaneous production of combustible and fissile fuels, fusion reactors for waste transmutation and fissile breeding, nuclear pumped laser hybrid reactors, Hybrid Fuel Factories (HFFs), and scenarios for hybrid contribution. The appendix offers hybrid reactor fundamentals. Numerous references are provided

  19. New features in MEDM

    International Nuclear Information System (INIS)

    Evans, K. Jr.

    1999-01-01

    MEDM, which is derived from Motif Editor and Display Manager, is the primary graphical interface to the EPICS control system. This paper describes new features that have been added to MEDM in the last two years. These features include new editing capabilities, a PV Info dialog box, a means of specifying limits and precision, a new implementation of the Cartesian Plot, new features for several objects, new capability for the Related Display, help, a user-configurable Execute Menu, reconfigured start-up options, and availability for Windows 95/98/NT. Over one hundred bugs have been fixed, and the program is quite stable and in extensive use

  20. Tissue culture-induced genetic and epigenetic alterations in rice pure-lines, F1 hybrids and polyploids.

    Science.gov (United States)

    Wang, Xiaoran; Wu, Rui; Lin, Xiuyun; Bai, Yan; Song, Congdi; Yu, Xiaoming; Xu, Chunming; Zhao, Na; Dong, Yuzhu; Liu, Bao

    2013-05-05

    Genetic and epigenetic alterations can be invoked by plant tissue culture, which may result in heritable changes in phenotypes, a phenomenon collectively termed somaclonal variation. Although extensive studies have been conducted on the molecular nature and spectrum of tissue culture-induced genomic alterations, the issue of whether and to what extent distinct plant genotypes, e.g., pure-lines, hybrids and polyploids, may respond differentially to the tissue culture condition remains poorly understood. We investigated tissue culture-induced genetic and epigenetic alterations in a set of rice genotypes including two pure-lines (different subspecies), a pair of reciprocal F1 hybrids parented by the two pure-lines, and a pair of reciprocal tetraploids resulted from the hybrids. Using two molecular markers, amplified fragment length polymorphism (AFLP) and methylation-sensitive amplified polymorphism (MSAP), both genetic and DNA methylation alterations were detected in calli and regenerants from all six genotypes, but genetic alteration is more prominent than epigenetic alteration. While significant genotypic difference was observed in frequencies of both types of alterations, only genetic alteration showed distinctive features among the three types of genomes, with one hybrid (N/9) being exceptionally labile. Surprisingly, difference in genetic alteration frequencies between the pair of reciprocal F1 hybrids is much greater than that between the two pure-line subspecies. Difference also exists in the pair of reciprocal tetraploids, but is to a less extent than that between the hybrids. The steady-state transcript abundance of genes involved in DNA repair and DNA methylation was significantly altered in both calli and regenerants, and some of which were correlated with the genetic and/or epigenetic alterations. Our results, based on molecular marker analysis of ca. 1,000 genomic loci, document that genetic alteration is the major cause of somaclonal variation in rice

  1. Local hybrid functionals: An assessment for thermochemical kinetics

    International Nuclear Information System (INIS)

    Kaupp, Martin; Bahmann, Hilke; Arbuznikov, Alexei V.

    2007-01-01

    Local hybrid functionals with position-dependent exact-exchange admixture are a new class of exchange-correlation functionals in density functional theory that promise to advance the available accuracy in many areas of application. Local hybrids with different local mixing functions (LMFs) governing the position dependence are validated for the heats of formation of the extended G3/99 set, and for two sets of barriers of hydrogen-transfer and heavy-atom transfer reactions (HTBH38 and NHTBH38 databases). A simple local hybrid Lh-SVWN with only Slater and exact exchange plus local correlation and a one-parameter LMF, g(r)=b(τ W (r)/τ(r)), performs best and provides overall mean absolute errors for thermochemistry and kinetics that are a significant improvement over standard state-of-the-art global hybrid functionals. In particular, this local hybrid functional does not suffer from the systematic deterioration that standard functionals exhibit for larger molecules. In contrast, local hybrids based on generalized gradient approximation exchange tend to give rise to nonintuitive LMFs, and no improved functionals have been obtained along this route. The LMF is a real-space function and thus can be analyzed in detail. We use, in particular, graphical analyses to rationalize the performance of different local hybrids for thermochemistry and reaction barriers

  2. Grammar-based feature generation for time-series prediction

    CERN Document Server

    De Silva, Anthony Mihirana

    2015-01-01

    This book proposes a novel approach for time-series prediction using machine learning techniques with automatic feature generation. Application of machine learning techniques to predict time-series continues to attract considerable attention due to the difficulty of the prediction problems compounded by the non-linear and non-stationary nature of the real world time-series. The performance of machine learning techniques, among other things, depends on suitable engineering of features. This book proposes a systematic way for generating suitable features using context-free grammar. A number of feature selection criteria are investigated and a hybrid feature generation and selection algorithm using grammatical evolution is proposed. The book contains graphical illustrations to explain the feature generation process. The proposed approaches are demonstrated by predicting the closing price of major stock market indices, peak electricity load and net hourly foreign exchange client trade volume. The proposed method ...

  3. Simulating movement of tRNA through the ribosome during hybrid-state formation.

    Science.gov (United States)

    Whitford, Paul C; Sanbonmatsu, Karissa Y

    2013-09-28

    Biomolecular simulations provide a means for exploring the relationship between flexibility, energetics, structure, and function. With the availability of atomic models from X-ray crystallography and cryoelectron microscopy (cryo-EM), and rapid increases in computing capacity, it is now possible to apply molecular dynamics (MD) simulations to large biomolecular machines, and systematically partition the factors that contribute to function. A large biomolecular complex for which atomic models are available is the ribosome. In the cell, the ribosome reads messenger RNA (mRNA) in order to synthesize proteins. During this essential process, the ribosome undergoes a wide range of conformational rearrangements. One of the most poorly understood transitions is translocation: the process by which transfer RNA (tRNA) molecules move between binding sites inside of the ribosome. The first step of translocation is the adoption of a "hybrid" configuration by the tRNAs, which is accompanied by large-scale rotations in the ribosomal subunits. To illuminate the relationship between these rearrangements, we apply MD simulations using a multi-basin structure-based (SMOG) model, together with targeted molecular dynamics protocols. From 120 simulated transitions, we demonstrate the viability of a particular route during P/E hybrid-state formation, where there is asynchronous movement along rotation and tRNA coordinates. These simulations not only suggest an ordering of events, but they highlight atomic interactions that may influence the kinetics of hybrid-state formation. From these simulations, we also identify steric features (H74 and surrounding residues) encountered during the hybrid transition, and observe that flexibility of the single-stranded 3'-CCA tail is essential for it to reach the endpoint. Together, these simulations provide a set of structural and energetic signatures that suggest strategies for modulating the physical-chemical properties of protein synthesis by the

  4. Near-term hybrid vehicle program, phase 1

    Science.gov (United States)

    1979-01-01

    The preliminary design of a hybrid vehicle which fully meets or exceeds the requirements set forth in the Near Term Hybrid Vehicle Program is documented. Topics addressed include the general layout and styling, the power train specifications with discussion of each major component, vehicle weight and weight breakdown, vehicle performance, measures of energy consumption, and initial cost and ownership cost. Alternative design options considered and their relationship to the design adopted, computer simulation used, and maintenance and reliability considerations are also discussed.

  5. A study on feature analysis for musical instrument classification.

    Science.gov (United States)

    Deng, Jeremiah D; Simmermacher, Christian; Cranefield, Stephen

    2008-04-01

    In tackling data mining and pattern recognition tasks, finding a compact but effective set of features has often been found to be a crucial step in the overall problem-solving process. In this paper, we present an empirical study on feature analysis for recognition of classical instrument, using machine learning techniques to select and evaluate features extracted from a number of different feature schemes. It is revealed that there is significant redundancy between and within feature schemes commonly used in practice. Our results suggest that further feature analysis research is necessary in order to optimize feature selection and achieve better results for the instrument recognition problem.

  6. Iris recognition based on key image feature extraction.

    Science.gov (United States)

    Ren, X; Tian, Q; Zhang, J; Wu, S; Zeng, Y

    2008-01-01

    In iris recognition, feature extraction can be influenced by factors such as illumination and contrast, and thus the features extracted may be unreliable, which can cause a high rate of false results in iris pattern recognition. In order to obtain stable features, an algorithm was proposed in this paper to extract key features of a pattern from multiple images. The proposed algorithm built an iris feature template by extracting key features and performed iris identity enrolment. Simulation results showed that the selected key features have high recognition accuracy on the CASIA Iris Set, where both contrast and illumination variance exist.

  7. Probability Aggregates in Probability Answer Set Programming

    OpenAIRE

    Saad, Emad

    2013-01-01

    Probability answer set programming is a declarative programming that has been shown effective for representing and reasoning about a variety of probability reasoning tasks. However, the lack of probability aggregates, e.g. {\\em expected values}, in the language of disjunctive hybrid probability logic programs (DHPP) disallows the natural and concise representation of many interesting problems. In this paper, we extend DHPP to allow arbitrary probability aggregates. We introduce two types of p...

  8. Research on Hybrid Vehicle Drivetrain

    Science.gov (United States)

    Xie, Zhongzhi

    Hybrid cars as a solution to energy saving, emission reduction measures, have received widespread attention. Motor drive system as an important part of the hybrid vehicles as an important object of study. Based on the hybrid electric vehicle powertrain control system for permanent magnet synchronous motor as the object of study. Can be applied to hybrid car compares the characteristics of traction motors, chose permanent magnet synchronous Motors as drive motors for hybrid vehicles. Building applications in hybrid cars in MATLAB/Simulink simulation model of permanent-magnet synchronous motor speed control system and analysis of simulation results.

  9. New hybrid systems

    International Nuclear Information System (INIS)

    Bernardin, B.

    2001-01-01

    New hybrid systems are made up of a subcritical core, a spallation target and a proton accelerator. The neutrons that are produced in the target by the flux of protons are necessary to maintain the chain reaction of fission. Some parameters that are important for a classical nuclear reactor like doppler coefficient or delayed neutron fraction do not matter in a hybrid system. In a PWR-type reactor or in a fast reactor the concentration of actinides has a bad impact on these 2 parameters, so it is justified to study hybrid systems as actinide transmuters. The hybrid system, because of its external source of neutrons can put aside an important reactivity margin. This reactivity margin can be used to design safer nuclear reactors (particularly in some situations of reactivity accidents) or to irradiate fuel elements containing high concentrations of minor actinides that could not be allowed in a classical reactor. This article reviews various ways of integrating hybrid systems in a population of already existing nuclear reactors in order to manage quantities of plutonium, of minor actinides or of long-life fission products. (A.C.)

  10. Creating fair lineups for suspects with distinctive features.

    Science.gov (United States)

    Zarkadi, Theodora; Wade, Kimberley A; Stewart, Neil

    2009-12-01

    In their descriptions, eyewitnesses often refer to a culprit's distinctive facial features. However, in a police lineup, selecting the only member with the described distinctive feature is unfair to the suspect and provides the police with little further information. For fair and informative lineups, the distinctive feature should be either replicated across foils or concealed on the target. In the present experiments, replication produced more correct identifications in target-present lineups--without increasing the incorrect identification of foils in target-absent lineups--than did concealment. This pattern, and only this pattern, is predicted by the hybrid-similarity model of recognition.

  11. Abdominal cocoon: sonographic features.

    Science.gov (United States)

    Vijayaraghavan, S Boopathy; Palanivelu, Chinnusamy; Sendhilkumar, Karuppusamy; Parthasarathi, Ramakrishnan

    2003-07-01

    An abdominal cocoon is a rare condition in which the small bowel is encased in a membrane. The diagnosis is usually established at surgery. Here we describe the sonographic features of this condition.

  12. Mesoblastic nephroma: Pathological features

    African Journals Online (AJOL)

    N.M. El-Badawy

    determined mainly by its histologic type, we found it worthwhile to elaborate more on the gross and microscopic features of ... behavior of mesoblastic nephroma is determined mainly by its his- .... However, it exhibits a nodular growth pattern at.

  13. A hybrid approach to automatic de-identification of psychiatric notes.

    Science.gov (United States)

    Lee, Hee-Jin; Wu, Yonghui; Zhang, Yaoyun; Xu, Jun; Xu, Hua; Roberts, Kirk

    2017-11-01

    De-identification, or identifying and removing protected health information (PHI) from clinical data, is a critical step in making clinical data available for clinical applications and research. This paper presents a natural language processing system for automatic de-identification of psychiatric notes, which was designed to participate in the 2016 CEGS N-GRID shared task Track 1. The system has a hybrid structure that combines machine leaning techniques and rule-based approaches. The rule-based components exploit the structure of the psychiatric notes as well as characteristic surface patterns of PHI mentions. The machine learning components utilize supervised learning with rich features. In addition, the system performance was boosted with integration of additional data to the training set through domain adaptation. The hybrid system showed overall micro-averaged F-score 90.74 on the test set, second-best among all the participants of the CEGS N-GRID task. Copyright © 2017. Published by Elsevier Inc.

  14. Patient set-up verification by infrared optical localization and body surface sensing in breast radiation therapy

    International Nuclear Information System (INIS)

    Spadea, Maria Francesca; Baroni, Guido; Riboldi, Marco; Orecchia, Roberto; Pedotti, Antonio; Tagaste, Barbara; Garibaldi, Cristina

    2006-01-01

    Background and purpose: The aim of the study was to investigate the clinical application of a technique for patient set-up verification in breast cancer radiotherapy, based on the 3D localization of a hybrid configuration of surface control points. Materials and methods: An infrared optical tracker provided the 3D position of two passive markers and 10 laser spots placed around and within the irradiation field on nine patients. A fast iterative constrained minimization procedure was applied to detect and compensate patient set-up errors, through the control points registration with reference data coming from treatment plan (markers reference position, CT-based surface model). Results: The application of the corrective spatial transformation estimated by the registration procedure led to significant improvement of patient set-up. Median value of 3D errors affecting three additional verification markers within the irradiation field decreased from 5.7 to 3.5 mm. Errors variability (25-75%) decreased from 3.2 to 2.1 mm. Laser spots registration on the reference surface model was documented to contribute substantially to set-up errors compensation. Conclusions: Patient set-up verification through a hybrid set of control points and constrained surface minimization algorithm was confirmed to be feasible in clinical practice and to provide valuable information for the improvement of the quality of patient set-up, with minimal requirement of operator-dependant procedures. The technique combines conveniently the advantages of passive markers based methods and surface registration techniques, by featuring immediate and robust estimation of the set-up accuracy from a redundant dataset

  15. UpSet: Visualization of Intersecting Sets

    Science.gov (United States)

    Lex, Alexander; Gehlenborg, Nils; Strobelt, Hendrik; Vuillemot, Romain; Pfister, Hanspeter

    2016-01-01

    Understanding relationships between sets is an important analysis task that has received widespread attention in the visualization community. The major challenge in this context is the combinatorial explosion of the number of set intersections if the number of sets exceeds a trivial threshold. In this paper we introduce UpSet, a novel visualization technique for the quantitative analysis of sets, their intersections, and aggregates of intersections. UpSet is focused on creating task-driven aggregates, communicating the size and properties of aggregates and intersections, and a duality between the visualization of the elements in a dataset and their set membership. UpSet visualizes set intersections in a matrix layout and introduces aggregates based on groupings and queries. The matrix layout enables the effective representation of associated data, such as the number of elements in the aggregates and intersections, as well as additional summary statistics derived from subset or element attributes. Sorting according to various measures enables a task-driven analysis of relevant intersections and aggregates. The elements represented in the sets and their associated attributes are visualized in a separate view. Queries based on containment in specific intersections, aggregates or driven by attribute filters are propagated between both views. We also introduce several advanced visual encodings and interaction methods to overcome the problems of varying scales and to address scalability. UpSet is web-based and open source. We demonstrate its general utility in multiple use cases from various domains. PMID:26356912

  16. Hybrid stochastic simplifications for multiscale gene networks

    Directory of Open Access Journals (Sweden)

    Debussche Arnaud

    2009-09-01

    Full Text Available Abstract Background Stochastic simulation of gene networks by Markov processes has important applications in molecular biology. The complexity of exact simulation algorithms scales with the number of discrete jumps to be performed. Approximate schemes reduce the computational time by reducing the number of simulated discrete events. Also, answering important questions about the relation between network topology and intrinsic noise generation and propagation should be based on general mathematical results. These general results are difficult to obtain for exact models. Results We propose a unified framework for hybrid simplifications of Markov models of multiscale stochastic gene networks dynamics. We discuss several possible hybrid simplifications, and provide algorithms to obtain them from pure jump processes. In hybrid simplifications, some components are discrete and evolve by jumps, while other components are continuous. Hybrid simplifications are obtained by partial Kramers-Moyal expansion 123 which is equivalent to the application of the central limit theorem to a sub-model. By averaging and variable aggregation we drastically reduce simulation time and eliminate non-critical reactions. Hybrid and averaged simplifications can be used for more effective simulation algorithms and for obtaining general design principles relating noise to topology and time scales. The simplified models reproduce with good accuracy the stochastic properties of the gene networks, including waiting times in intermittence phenomena, fluctuation amplitudes and stationary distributions. The methods are illustrated on several gene network examples. Conclusion Hybrid simplifications can be used for onion-like (multi-layered approaches to multi-scale biochemical systems, in which various descriptions are used at various scales. Sets of discrete and continuous variables are treated with different methods and are coupled together in a physically justified approach.

  17. Modular supervisory controller for hybrid power systems

    Energy Technology Data Exchange (ETDEWEB)

    Lemos Pereira, A. de

    2000-06-01

    The power supply of remote places has been commonly provided by thermal power plants, usually diesel generators. Although hybrid power systems may constitute the most economical solution in many applications their widespread application to the electrification schemes of remote areas still depends on improvements in the issues of design and operation control. The main limitations of the present hybrid power systems technology, which are identified in this work, are related to the control and supervision of the power system. Therefore this thesis focuses on the modularity of supervisory controllers in order to design cost-competitive and reliable hybrid power systems. The modular supervisory controller created in this project is considered an important part of a system design approach that aims to overcome the technical difficulties of the current engineering practice and contribute to open the market of hybrid power systems. The term modular refers to a set of design characteristics that allows the use of basically the same supervisory controller in different projects. The modularization and standardisation of the controller include several issues such as interfacing components, communication protocols, modelling, programming and control strategies. The modularity can reduce the highly specialised system engineering related to the integration of components, operation and control. It can also avoid the high costs for installation, service and maintenance. A modular algorithm for supervisory controllers has been developed (a Matlab program called SuperCon) using an object-oriented design and it has been tested through several simulations using different hybrid system configurations and different control strategies. This thesis presents a complete control system design process which can be used as the basis for the development and implementation of intelligent and autonomous supervisory controllers for hybrid power systems with modular characteristics. (au)

  18. Enhanced performance hybrid-arq

    KAUST Repository

    Fareed, Muhammad Mehboob

    2016-06-16

    Apparatuses, computer readable media, and methods are provided for enhancing hybrid automatic repeat request (ARQ) performance. In an example method, a communication device transmits a first element of a vector, where the vector is selected using the information bits to be transmitted as an index in a code book. In some embodiments, this code book is constructed using Linear Constellation Precoding (LCP). If a NACK is received, the communication device transmits a second element of the vector. The process of transmitting elements of the vector continues until an ACK is received or the maximum number of transmission attempts is reached. If an ACK is received, the communication device transmits a first element of another vector of the code book that encodes a second set of information bits. This procedure may continue until all information bits have been transmitted successfully.

  19. Enhanced performance hybrid-arq

    KAUST Repository

    Fareed, Muhammad Mehboob; Yang, Hong-Chuan; Alouini, Mohamed-Slim

    2016-01-01

    Apparatuses, computer readable media, and methods are provided for enhancing hybrid automatic repeat request (ARQ) performance. In an example method, a communication device transmits a first element of a vector, where the vector is selected using the information bits to be transmitted as an index in a code book. In some embodiments, this code book is constructed using Linear Constellation Precoding (LCP). If a NACK is received, the communication device transmits a second element of the vector. The process of transmitting elements of the vector continues until an ACK is received or the maximum number of transmission attempts is reached. If an ACK is received, the communication device transmits a first element of another vector of the code book that encodes a second set of information bits. This procedure may continue until all information bits have been transmitted successfully.

  20. Feature Binding in Zebrafish

    Directory of Open Access Journals (Sweden)

    P Neri

    2012-07-01

    Full Text Available Binding operations are primarily ascribed to cortex or similarly complex avian structures. My experiments show that the zebrafish, a lower vertebrate lacking cortex, supports visual feature binding of form and motion for the purpose of social behavior. These results challenge the notion that feature binding may require highly evolved neural structures and demonstrate that the nervous system of lower vertebrates can afford unexpectedly complex computations.

  1. Hybrid Computational Model for High-Altitude Aeroassist Vehicles, Phase I

    Data.gov (United States)

    National Aeronautics and Space Administration — A hybrid continuum/noncontinuum computational model will be developed for analyzing the aerodynamics and heating on aeroassist vehicles. Unique features of this...

  2. Continuation of Sets of Constrained Orbit Segments

    DEFF Research Database (Denmark)

    Schilder, Frank; Brøns, Morten; Chamoun, George Chaouki

    Sets of constrained orbit segments of time continuous flows are collections of trajectories that represent a whole or parts of an invariant set. A non-trivial but simple example is a homoclinic orbit. A typical representation of this set consists of an equilibrium point of the flow and a trajectory...... that starts close and returns close to this fixed point within finite time. More complicated examples are hybrid periodic orbits of piecewise smooth systems or quasi-periodic invariant tori. Even though it is possible to define generalised two-point boundary value problems for computing sets of constrained...... orbit segments, this is very disadvantageous in practice. In this talk we will present an algorithm that allows the efficient continuation of sets of constrained orbit segments together with the solution of the full variational problem....

  3. Comparative gene expression profiles between heterotic and non-heterotic hybrids of tetraploid Medicago sativa

    Directory of Open Access Journals (Sweden)

    Nettleton Dan

    2009-08-01

    Full Text Available Abstract Background Heterosis, the superior performance of hybrids relative to parents, has clear agricultural value, but its genetic control is unknown. Our objective was to test the hypotheses that hybrids expressing heterosis for biomass yield would show more gene expression levels that were different from midparental values and outside the range of parental values than hybrids that do not exhibit heterosis. Results We tested these hypotheses in three Medicago sativa (alfalfa genotypes and their three hybrids, two of which expressed heterosis for biomass yield and a third that did not, using Affymetrix M. truncatula GeneChip arrays. Alfalfa hybridized to approximately 47% of the M. truncatula probe sets. Probe set signal intensities were analyzed using MicroArray Suite v.5.0 (MAS and robust multi-array average (RMA algorithms. Based on MAS analysis, the two heterotic hybrids performed similarly, with about 27% of genes showing differential expression among the parents and their hybrid compared to 12.5% for the non-heterotic hybrid. At a false discovery rate of 0.15, 4.7% of differentially expressed genes in hybrids (~300 genes showed nonadditive expression compared to only 0.5% (16 genes in the non-heterotic hybrid. Of the nonadditively expressed genes, approximately 50% showed expression levels that fell outside the parental range in heterotic hybrids, but only one of 16 showed a similar profile in the non-heterotic hybrid. Genes whose expression differed in the parents were three times more likely to show nonadditive expression than genes whose parental transcript levels were equal. Conclusion The higher proportions of probe sets with expression level that differed from the parental midparent value and that were more extreme than either parental value in the heterotic hybrids compared to a non-heterotic hybrid were also found using RMA. We conclude that nonadditive expression of transcript levels may contribute to heterosis for biomass

  4. The Hybrid Museum: Hybrid Economies of Meaning

    DEFF Research Database (Denmark)

    Vestergaard, Vitus

    2013-01-01

    Social media has created new ways of communicating and has brought about a new distinctive ethos. New literacies are not simply about new technology but also about this new ethos. Many museums are embracing this ethos by what is often called participatory practices. From a sociocultural perspective...... this article shows that there are two different museum mindsets where the second mindset leans towards participatory practices. It is shown how a museum can support a hybrid economy of meaning that builds on both a user generated economy of meaning and an institutional economy of meaning and adds value to both...

  5. Origin of African Physacanthus (Acanthaceae via wide hybridization.

    Directory of Open Access Journals (Sweden)

    Erin A Tripp

    Full Text Available Gene flow between closely related species is a frequent phenomenon that is known to play important roles in organismal evolution. Less clear, however, is the importance of hybridization between distant relatives. We present molecular and morphological evidence that support origin of the plant genus Physacanthus via "wide hybridization" between members of two distantly related lineages in the large family Acanthaceae. These two lineages are well characterized by very different morphologies yet, remarkably, Physacanthus shares features of both. Chloroplast sequences from six loci indicate that all three species of Physacanthus contain haplotypes from both lineages, suggesting that heteroplasmy likely predated speciation in the genus. Although heteroplasmy is thought to be unstable and thus transient, multiple haplotypes have been maintained through time in Physacanthus. The most likely scenario to explain these data is that Physacanthus originated via an ancient hybridization event that involved phylogenetically distant parents. This wide hybridization has resulted in the establishment of an independently evolving clade of flowering plants.

  6. Long-range hybrid ridge and trench plasmonic waveguides

    Energy Technology Data Exchange (ETDEWEB)

    Bian, Yusheng [State Key Laboratory for Mesoscopic Physics, Department of Physics, Peking University, Beijing 100871 (China); Gong, Qihuang, E-mail: qhgong@pku.edu.cn [State Key Laboratory for Mesoscopic Physics, Department of Physics, Peking University, Beijing 100871 (China); Collaborative Innovation Center of Quantum Matter, Beijing 100871 (China)

    2014-06-23

    We report a class of long-range hybrid plasmon polariton waveguides capable of simultaneously achieving low propagation loss and tight field localization at telecommunication wavelength. The symmetric (quasi-symmetric) hybrid configurations featuring high-refractive-index-contrast near the non-uniform metallic nanostructures enable significantly improved optical performance over conventional hybrid waveguides, exhibiting considerably longer propagation distances and dramatically enhanced figure of merits for similar degrees of confinement. Compared to their traditional long-range plasmonic counterparts, the proposed hybrid waveguides put much less stringent requirements on index-matching conditions, demonstrating nice performance under a wide range of physical dimensions and robust characteristics against certain fabrication imperfections. Studies concerning crosstalk between adjacent identical waveguides further reveal their potential for photonic integrations. In addition, alternative configurations with comparable guiding properties to the structures in our case studies are also proposed, which can potentially serve as attractive prototypes for numerous high-performance nanophotonic components.

  7. Hybrid classifiers methods of data, knowledge, and classifier combination

    CERN Document Server

    Wozniak, Michal

    2014-01-01

    This book delivers a definite and compact knowledge on how hybridization can help improving the quality of computer classification systems. In order to make readers clearly realize the knowledge of hybridization, this book primarily focuses on introducing the different levels of hybridization and illuminating what problems we will face with as dealing with such projects. In the first instance the data and knowledge incorporated in hybridization were the action points, and then a still growing up area of classifier systems known as combined classifiers was considered. This book comprises the aforementioned state-of-the-art topics and the latest research results of the author and his team from Department of Systems and Computer Networks, Wroclaw University of Technology, including as classifier based on feature space splitting, one-class classification, imbalance data, and data stream classification.

  8. Hybrid system concepts

    International Nuclear Information System (INIS)

    Landeyro, P.A.

    1995-01-01

    Hybrid systems studied for fissile material production, were reconsidered for minor actinide and long-lived fission product destruction as alternative to the traditional final disposal of nuclear waste. Now there are attempts to extend the use of the concepts developed for minor actinide incineration to plutonium burning. The most promising hybrid system concept considers fuel and target both as liquids. From the results obtained, the possibility to adopt composite targets seems the most promising solution, but still there remains the problem of Pu production, not acceptable in a burning system. This kind of targets can be mainly used for fissile material production, while for accelerator driven burners it is most convenient to use a liquid lead target. The most suitable solvent is heavy water for minor actinide annihilation in the blanket of a hybrid system. Due to the criticality conditions and the necessity of electric energy production, the blanket using plutonium dissolved in molten salts is the most convenient one. (author)

  9. Hybrid strategies in nanolithography

    Energy Technology Data Exchange (ETDEWEB)

    Saavedra, Hector M; Mullen, Thomas J; Zhang Pengpeng; Dewey, Daniel C; Claridge, Shelley A; Weiss, Paul S [Department of Chemistry, The Pennsylvania State University, University Park, PA 16802 (United States)], E-mail: psw@cnsi.ucla.edu

    2010-03-15

    Hybrid nanoscale patterning strategies combine the registration and addressability of conventional lithographic techniques with the chemical and physical functionality enabled by intermolecular, electrostatic and/or biological interactions. This review aims to highlight and to provide a comprehensive description of recent developments in hybrid nanoscale patterning strategies that enhance existing lithographic techniques or can be used to fabricate functional chemical patterns that interact with their environment. These functional structures create new capabilities, such as the fabrication of physicochemical surfaces that can recognize and capture analytes from complex liquid or gaseous mixtures. The nanolithographic techniques we describe can be classified into three general areas: traditional lithography, soft lithography and scanning-probe lithography. The strengths and limitations of each hybrid patterning technique will be discussed, along with the current and potential applications of the resulting patterned, functional surfaces.

  10. Molas Baju Wara: Hybridity in Manggarai Rap Music

    Directory of Open Access Journals (Sweden)

    Ans. Prawati Yuliantari

    2017-06-01

    Full Text Available Rap music which has been popular since 2007 in Manggarai region, East Nusa Tenggara, Indonesia, gave rise to rap hybrid phenomenon. The mixture between American rap music formats and local elements of Manggarai attracted the attention of young people in the region. One of the local songs that feature hybridity in rap Manggarai is "Molas Baju Wara" created by Lipooz, one of the pioneers of rap in Ruteng, the capital city of Manggarai district. To discuss this phenomenon, the concept of hybridity in cultural territory proposed by James Lull is adopted. This concept is used particularly to analyze the forms of hybridity reflected in " Molas Baju Wara" and the ways they are used in showing the social and cultural conditions of Manggarai. "Molas Baju Wara" was selected as the object of study because the song is clearly showing the characteristics of hybridity in music. The study shows that hybridity could be perceived in Manggarai rap music specifically in the use of local musical instruments like drums, cajon, and tambourine as a substitute for percussive sounds of drums, boombox, or turn-table which are commonly used by rap musicians in their home country, the U.S.A. In addition, there are elements of local sound such as the sound of rain that represents Ruteng as the rain city. Hybridity characteristics can also be found in the use of Manggarai vernacular in the whole lyrics as well as the narration of local themes and certain sites that represent Ruteng.

  11. Classification Using Markov Blanket for Feature Selection

    DEFF Research Database (Denmark)

    Zeng, Yifeng; Luo, Jian

    2009-01-01

    Selecting relevant features is in demand when a large data set is of interest in a classification task. It produces a tractable number of features that are sufficient and possibly improve the classification performance. This paper studies a statistical method of Markov blanket induction algorithm...... for filtering features and then applies a classifier using the Markov blanket predictors. The Markov blanket contains a minimal subset of relevant features that yields optimal classification performance. We experimentally demonstrate the improved performance of several classifiers using a Markov blanket...... induction as a feature selection method. In addition, we point out an important assumption behind the Markov blanket induction algorithm and show its effect on the classification performance....

  12. Effective traffic features selection algorithm for cyber-attacks samples

    Science.gov (United States)

    Li, Yihong; Liu, Fangzheng; Du, Zhenyu

    2018-05-01

    By studying the defense scheme of Network attacks, this paper propose an effective traffic features selection algorithm based on k-means++ clustering to deal with the problem of high dimensionality of traffic features which extracted from cyber-attacks samples. Firstly, this algorithm divide the original feature set into attack traffic feature set and background traffic feature set by the clustering. Then, we calculates the variation of clustering performance after removing a certain feature. Finally, evaluating the degree of distinctiveness of the feature vector according to the result. Among them, the effective feature vector is whose degree of distinctiveness exceeds the set threshold. The purpose of this paper is to select out the effective features from the extracted original feature set. In this way, it can reduce the dimensionality of the features so as to reduce the space-time overhead of subsequent detection. The experimental results show that the proposed algorithm is feasible and it has some advantages over other selection algorithms.

  13. The tokamak hybrid reactor

    International Nuclear Information System (INIS)

    Kelly, J.L.; Rose, R.P.

    1981-01-01

    At a time when the potential benefits of various energy options are being seriously evaluated in many countries through-out the world, it is both timely and important to evaluate the practical application of fusion reactors for their economical production of nuclear fissile fuels from fertile fuels. The fusion hybrid reactor represents a concept that could assure the availability of adequate fuel supplies for a proven nuclear technology and have the potential of being an electrical energy source as opposed to an energy consumer as are the present fuel enrichment processes. Westinghouse Fusion Power Systems Department, under Contract No. EG-77-C-02-4544 with the Department of Energy, Office of Fusion Energy, has developed a preliminary conceptual design for an early twenty-first century fusion hybrid reactor called the commercial Tokamak Hybrid Reactor (CTHR). This design was developed as a first generation commercial plant producing fissile fuel to support a significant number of client Light Water Reactor (LWR) Plants. To the depth this study has been performed, no insurmountable technical problems have been identified. The study has provided a basis for reasonable cost estimates of the hybrid plants as well as the hybrid/LWR system busbar electricity costs. This energy system can be optimized to have a net cost of busbar electricity that is equivalent to the conventional LWR plant, yet is not dependent on uranium ore prices or standard enrichment costs, since the fusion hybrid can be fueled by numerous fertile fuel resources. A nearer-term concept is also defined using a beam driven fusion driver in lieu of the longer term ignited operating mode. (orig.)

  14. Dissipative dynamics of superconducting hybrid qubit systems

    International Nuclear Information System (INIS)

    Montes, Enrique; Calero, Jesus M; Reina, John H

    2009-01-01

    We perform a theoretical study of composed superconducting qubit systems for the case of a coupled qubit configuration based on a hybrid qubit circuit made of both charge and phase qubits, which are coupled via a σ x x σ z interaction. We compute the system's eigen-energies in terms of the qubit transition frequencies and the strength of the inter-qubit coupling, and describe the sensitivity of the energy crossing/anti-crossing features to such coupling. We compute the hybrid system's dissipative dynamics for the cases of i) collective and ii) independent decoherence, whereby the system interacts with one common and two different baths of harmonic oscillators, respectively. The calculations have been performed within the Bloch-Redfield formalism and we report the solutions for the populations and the coherences of the system's reduced density matrix. The dephasing and relaxation rates are explicitly calculated as a function of the heat bath temperature.

  15. Multiuser hybrid switched-selection diversity systems

    KAUST Repository

    Shaqfeh, Mohammad

    2011-09-01

    A new multiuser scheduling scheme is proposed and analyzed in this paper. The proposed system combines features of conventional full-feedback selection-based diversity systems and reduced-feedback switch-based diversity systems. The new hybrid system provides flexibility in trading-off the channel information feedback overhead with the prospected multiuser diversity gains. The users are clustered into groups, and the users\\' groups are ordered into a sequence. Per-group feedback thresholds are used and optimized to maximize the system overall achievable rate. The proposed hybrid system applies switched diversity criterion to choose one of the groups, and a selection criterion to decide the user to be scheduled from the chosen group. Numerical results demonstrate that the system capacity increases as the number of users per group increases, but at the cost of more required feedback messages. © 2011 IEEE.

  16. Non-adaptive and adaptive hybrid approaches for enhancing water quality management

    Science.gov (United States)

    Kalwij, Ineke M.; Peralta, Richard C.

    2008-09-01

    SummaryUsing optimization to help solve groundwater management problems cost-effectively is becoming increasingly important. Hybrid optimization approaches, that combine two or more optimization algorithms, will become valuable and common tools for addressing complex nonlinear hydrologic problems. Hybrid heuristic optimizers have capabilities far beyond those of a simple genetic algorithm (SGA), and are continuously improving. SGAs having only parent selection, crossover, and mutation are inefficient and rarely used for optimizing contaminant transport management. Even an advanced genetic algorithm (AGA) that includes elitism (to emphasize using the best strategies as parents) and healing (to help assure optimal strategy feasibility) is undesirably inefficient. Much more efficient than an AGA is the presented hybrid (AGCT), which adds comprehensive tabu search (TS) features to an AGA. TS mechanisms (TS probability, tabu list size, search coarseness and solution space size, and a TS threshold value) force the optimizer to search portions of the solution space that yield superior pumping strategies, and to avoid reproducing similar or inferior strategies. An AGCT characteristic is that TS control parameters are unchanging during optimization. However, TS parameter values that are ideal for optimization commencement can be undesirable when nearing assumed global optimality. The second presented hybrid, termed global converger (GC), is significantly better than the AGCT. GC includes AGCT plus feedback-driven auto-adaptive control that dynamically changes TS parameters during run-time. Before comparing AGCT and GC, we empirically derived scaled dimensionless TS control parameter guidelines by evaluating 50 sets of parameter values for a hypothetical optimization problem. For the hypothetical area, AGCT optimized both well locations and pumping rates. The parameters are useful starting values because using trial-and-error to identify an ideal combination of control

  17. Hydraulic Hybrid Vehicle Publications | Transportation Research | NREL

    Science.gov (United States)

    Hydraulic Hybrid Vehicle Publications Hydraulic Hybrid Vehicle Publications The following technical papers and fact sheets provide information about NREL's hydraulic hybrid fleet vehicle evaluations . Refuse Trucks Project Startup: Evaluating the Performance of Hydraulic Hybrid Refuse Vehicles. Bob

  18. Doubts about hybrids

    International Nuclear Information System (INIS)

    Anon.

    1982-01-01

    The natural draught wet cooling tower with a height of 160 m is considerably taller than the 80 m high hybrid cooling tower, but the latter has a considerably larger diameter. Spray losses for both types are about 4.5 kg/sec for a thermal output of 2500 MW. Apart from the pump load, the natural cooling tower requires no power. Apart from higher pump loads, the hybrid cooling tower requires power for the fans. The energy demand for this purpose is 1.5 to 3% of the nett powerstation output. For the Isar 2 nuclear powerstation this would mean a reduction in puput of about 35 MW. (orig.) [de

  19. Analog and hybrid computing

    CERN Document Server

    Hyndman, D E

    2013-01-01

    Analog and Hybrid Computing focuses on the operations of analog and hybrid computers. The book first outlines the history of computing devices that influenced the creation of analog and digital computers. The types of problems to be solved on computers, computing systems, and digital computers are discussed. The text looks at the theory and operation of electronic analog computers, including linear and non-linear computing units and use of analog computers as operational amplifiers. The monograph examines the preparation of problems to be deciphered on computers. Flow diagrams, methods of ampl

  20. Toyota hybrid synergy drive

    Energy Technology Data Exchange (ETDEWEB)

    Gautschi, H.

    2008-07-01

    This presentation made at the Swiss 2008 research conference on traffic by Hannes Gautschi, director of service and training at the Toyota company in Switzerland, takes a look at Toyota's hybrid drive vehicles. The construction of the vehicles and their combined combustion engines and electric generators and drives is presented and the combined operation of these components is described. Braking and energy recovery are discussed. Figures on the performance, fuel consumption and CO{sub 2} output of the hybrid vehicles are compared with those of conventional vehicles.

  1. Particularidades de la medición de presión sonora y vibraciones en grupos electrógenos MAN 18 V48/60 B // Distinctive features for sound pressure level and vibration measurements over engine generator sets type MAN 18 v48/60 b

    Directory of Open Access Journals (Sweden)

    Yanexi Cepero‐Aguilera

    2011-01-01

    Full Text Available Como parte de las líneas de investigación del Centro de Estudios en Ingeniería de Mantenimiento, sedesarrolla un proyecto de investigación encaminado a establecer las pautas para la evaluación de lacondición de grupos electrógenos. El presente artículo muestra las particularidades de la mediciónde sonido y vibraciones sobre un Grupo Electrógeno MAN 18 V48/60 B. Se analiza lo indicado en elestándar ISO 3744 concluyéndose con la imposibilidad práctica de su aplicación en el entornoindustrial y para grandes máquinas como lo es el caso de los grupos electrógenos MAN 18 V48/60 B.El interés de esta investigación se enfoca al generador del grupo electrógeno y por ello no obstante,se efectuaron mediciones de presión sonora orientando el micrófono hacia los cojinetes de este,sobre los cuales también se registraron sus vibraciones siguiendo lo indicado en el estándar ISO8528-9. El análisis comparativo de los registros espectrales de presión sonora y de vibracionesobligó a convertir los espectros FFT en espectros de ancho de banda proporcional constante. Comoresultado fundamental se obtiene la no correlación de las frecuencias espectrales de presión sonoracon las de vibraciones y una evaluación preliminar del generador exhibiendo una condición normal.Palabras claves: nivel de presión sonora, medición de vibraciones, ancho de banda proporcionalconstante, grupos electrógenos._________________________________________________________________AbstractA research project for condition monitoring of engine generator sets is developed as part of mainresearches at Maintenance Engineering Research Center. Sound pressure level and vibrationmeasurements over an engine generator set MAN 18 V48/60 B are made with the goal of identifythose frequencies present in both, sound pressure level and vibration spectra which could give thepossibility to use sound pressure level as a symptom parameter because of the continuous feature ofthis kind of

  2. Hybrid Vehicle Technologies and their potential for reducing oil use

    Science.gov (United States)

    German, John

    2006-04-01

    Vehicles with hybrid gasoline-electric powertrains are starting to gain market share. Current hybrid vehicles add an electric motor, battery pack, and power electronics to the conventional powertrain. A variety of engine/motor configurations are possible, each with advantages and disadvantages. In general, efficiency is improved due to engine shut-off at idle, capture of energy during deceleration that is normally lost as heat in the brakes, downsizing of the conventional engine, and, in some cases, propulsion on the electric motor alone. Ongoing increases in hybrid market share are dependent on cost reduction, especially the battery pack, efficiency synergies with other vehicle technologies, use of the high electric power to provide features desired by customers, and future fuel price and availability. Potential barriers include historically low fuel prices, high discounting of the fuel savings by new vehicle purchasers, competing technologies, and tradeoffs with other factors desired by customers, such as performance, utility, safety, and luxury features.

  3. Metastrategies in large-scale bargaining settings

    NARCIS (Netherlands)

    Hennes, D.; Jong, S. de; Tuyls, K.; Gal, Y.

    2015-01-01

    This article presents novel methods for representing and analyzing a special class of multiagent bargaining settings that feature multiple players, large action spaces, and a relationship among players' goals, tasks, and resources. We show how to reduce these interactions to a set of bilateral

  4. Mirror fusion--fission hybrids

    International Nuclear Information System (INIS)

    Lee, J.D.

    1978-01-01

    The fusion-fission concept and the mirror fusion-fission hybrid program are outlined. Magnetic mirror fusion drivers and blankets for hybrid reactors are discussed. Results of system analyses are presented and a reference design is described

  5. Hybrid fixed point in CAT(0 spaces

    Directory of Open Access Journals (Sweden)

    Hemant Kumar Pathak

    2018-02-01

    Full Text Available In this paper, we introduce an ultrapower approach to prove fixed point theorems for $H^{+}$-nonexpansive multi-valued mappings in the setting of CAT(0 spaces and prove several hybrid fixed point results in CAT(0 spaces for families of single-valued nonexpansive or quasinonexpansive mappings and multi-valued upper semicontinuous, almost lower semicontinuous or $H^{+}$-nonexpansive mappings which are weakly commuting. We also establish a result about structure of the set of fixed points of $H^{+}$-quasinonexpansive mapping on a CAT(0 space.

  6. Fuzzy sets, rough sets, multisets and clustering

    CERN Document Server

    Dahlbom, Anders; Narukawa, Yasuo

    2017-01-01

    This book is dedicated to Prof. Sadaaki Miyamoto and presents cutting-edge papers in some of the areas in which he contributed. Bringing together contributions by leading researchers in the field, it concretely addresses clustering, multisets, rough sets and fuzzy sets, as well as their applications in areas such as decision-making. The book is divided in four parts, the first of which focuses on clustering and classification. The second part puts the spotlight on multisets, bags, fuzzy bags and other fuzzy extensions, while the third deals with rough sets. Rounding out the coverage, the last part explores fuzzy sets and decision-making.

  7. Relative biocompatibility of micro-hybrid and nano-hybrid light-activated composite resins.

    Science.gov (United States)

    Olabisi Arigbede, Abiodun; Folasade Adeyemi, Bukola; Femi-Akinlosotu, Omowumi

    2017-01-01

    Background. In vitro studies have revealed a direct association between resin content and cytotoxicity of composite resins; however, implantation studies in this regard are sparse. This study investigates the relationship between filler content of composite resins and biocompatibility. Methods. This research employed twelve 180‒200-gr male Wistar rats, 1 nano-hybrid (Prime-Dent Inc.) and 1 micro-hybrid (Medental Inc.) composite resins containing 74% and 80‒90% filler content, respectively. The samples were assessed on the 2nd, 14th and 90th day of implantation. Four rats were allocated to each day in this experimental study. A section of 1.5mm long cured nano-hybrid and micro-hybrid materials were implanted into the right and left upper and lower limbs of the rats, respectively. Eight samples were generated on each day of observation. Inflammation was graded according to the criteria suggested by Orstavik and Major. Pearson's chi-squared test was employed to determine the relationship between the tissue responses of the two materials. Statistical significance was set at P resin had a score of 3.0 for cellular inflammation. On the 14th day, the micro-hybrid resin also exhibited a lower average grade for cellular inflammation. On the 90th day, the micro-hybrid resin had a higher grade of inflammation (0.9) compared to 0.3 recorded for nano-hybrid. The composite resins with higher filler content elicited a significantly lower grade of inflammation irrespective of the duration (χ=20.000, df=8, P=0.010) while the composite resins with lower filler content elicited a significantly lower inflammatory response on the 90th day (χ=4.000, df=1, P=0.046). Conclusion. The composite resins with higher filler content generally elicited significantly lower grades of inflammation, and the composite resins with lower filler content exhibited significantly lower inflammatory response on the 90th day of implantation.

  8. Assessment of RISAT-1 and Radarsat-2 for Sea Ice Observations from a Hybrid-Polarity Perspective

    Directory of Open Access Journals (Sweden)

    Martine M. Espeseth

    2017-10-01

    Full Text Available Utilizing several Synthetic Aperture Radar (SAR missions will provide a data set with higher temporal resolution. It is of great importance to understand the difference between various available sensors and polarization modes and to consider how to homogenize the data sets for a following combined analysis. In this study, a uniform and consistent analysis across different SAR missions is carried out. Three pairs of overlapping hybrid- and full-polarimetric C-band SAR scenes from the Radar Imaging Satellite-1 (RISAT-1 and Radarsat-2 satellites are used. The overlapping Radarsat-2 and RISAT-1 scenes are taken close in time, with a relatively similar incidence angle covering sea ice in the Fram Strait and Northeast Greenland in September 2015. The main objective of this study is to identify the similarities and dissimilarities between a simulated and a real hybrid-polarity (HP SAR system. The similarities and dissimilarities between the two sensors are evaluated using 13 HP features. The results indicate a similar separability between the sea ice types identified within the real HP system in RISAT-1 and the simulated HP system from Radarsat-2. The HP features that are sensitive to surface scattering and depolarization due to volume scattering showed great potential for separating various sea ice types. A subset of features (the second parameter in the Stokes vector, the ratio between the HP intensity coefficients, and the α s angle were affected by the non-circularity property of the transmitted wave in the simulated HP system across all the scene pairs. Overall, the best features, showing high separability between various sea ice types and which are invariant to the non-circularity property of the transmitted wave, are the intensity coefficients from the right-hand circular transmit and the linear horizontal receive channel and the right-hand circular on both the transmit and the receive channel, and the first parameter in the Stokes vector.

  9. Green Settings for Children in Preschools

    DEFF Research Database (Denmark)

    Lerstrup, Inger Elisabeth

    settings for preschools. The intent is to facilitate transfer of knowledge from preschools to planners and managers of green settings such as woodland, parks, green lots and playgrounds. The central concept applied is that of affordances, here defined as the meaningful action possibilities......This Danish study investigates the relationship between children in preschool (age range 3-6.5 years) and the outdoor environments they use. The main aim is to describe and analyse the outdoor features of significance for children’s activities and of importance for design and management of green...... between forest features and manufactured features, a detailed account of the affordances of ditches, and a description of the forest sites used by a Danish forest preschool. Children were attracted to features with changing and not fully explored action possibilities; forest features added variation...

  10. Hybrid incompatibilities are affected by dominance and dosage in the haplodiploid wasp Nasonia

    Science.gov (United States)

    Beukeboom, Leo W.; Koevoets, Tosca; Morales, Hernán E.; Ferber, Steven; van de Zande, Louis

    2015-01-01

    Study of genome incompatibilities in species hybrids is important for understanding the genetic basis of reproductive isolation and speciation. According to Haldane's rule hybridization affects the heterogametic sex more than the homogametic sex. Several theories have been proposed that attribute asymmetry in hybridization effects to either phenotype (sex) or genotype (heterogamety). Here we investigate the genetic basis of hybrid genome incompatibility in the haplodiploid wasp Nasonia using the powerful features of haploid males and sex reversal. We separately investigate the effects of heterozygosity (ploidy level) and sex by generating sex reversed diploid hybrid males and comparing them to genotypically similar haploid hybrid males and diploid hybrid females. Hybrid effects of sterility were more pronounced than of inviability, and were particularly strong in haploid males, but weak to absent in diploid males and females, indicating a strong ploidy level but no sex specific effect. Molecular markers identified a number of genomic regions associated with hybrid inviability in haploid males that disappeared under diploidy in both hybrid males and females. Hybrid inviability was rescued by dominance effects at some genomic regions, but aggravated or alleviated by dosage effects at other regions, consistent with cytonuclear incompatibilities. Dosage effects underlying Bateson–Dobzhansky–Muller (BDM) incompatibilities need more consideration in explaining Haldane's rule in diploid systems. PMID:25926847

  11. Security in hybrid cloud computing

    OpenAIRE

    Koudelka, Ondřej

    2016-01-01

    This bachelor thesis deals with the area of hybrid cloud computing, specifically with its security. The major aim of the thesis is to analyze and compare the chosen hybrid cloud providers. For the minor aim this thesis compares the security challenges of hybrid cloud as opponent to other deployment models. In order to accomplish said aims, this thesis defines the terms cloud computing and hybrid cloud computing in its theoretical part. Furthermore the security challenges for cloud computing a...

  12. Supernumerary ring chromosome 20 characterized by fluorescence in situ hybridization

    NARCIS (Netherlands)

    Van Langen, Irene M.; Otter, Mariëlle A.; Aronson, Daniël C.; Overweg-Plandsoen, W.C.G.; Hennekam, Raoul C.M.; Leschot, Nico J.; Hoovers, Jan M.N.

    1996-01-01

    We report on a boy with mild dysmorphic features and developmental delay, in whom karyotyping showed an additional minute ring chromosome in 60% of metaphases. Fluorescence in situ hybridization (FISH) with a centromere specific probe demonstrated that the ring chromosome contained the centromeric

  13. Calculation of Cogging Torque in Hybrid Stepping Motors | Agber ...

    African Journals Online (AJOL)

    When the windings of a hybrid stepping motor are unexcited the permanent magnet's flux produces cogging torque. This torque has both desirable and undesirable features depending on the application that the motor is put into. This paper formulates an analytical method for predicting cogging torque using measured ...

  14. Joint Optimal Design and Operation of Hybrid Energy Storage Systems

    NARCIS (Netherlands)

    Y. Ghiassi-Farrokhfal (Yashar); C. Rosenberg; S. Keshav (Srinivasam); M.-B. Adjaho (Marie-Benedicte)

    2016-01-01

    markdownabstractThe wide range of performance characteristics of storage technologies motivates the use of a hybrid energy storage systems (HESS) that combines the best features of multiple technologies. However, HESS design is complex, in that it involves the choice of storage technologies, the

  15. Prominent feature extraction for review analysis: an empirical study

    Science.gov (United States)

    Agarwal, Basant; Mittal, Namita

    2016-05-01

    Sentiment analysis (SA) research has increased tremendously in recent times. SA aims to determine the sentiment orientation of a given text into positive or negative polarity. Motivation for SA research is the need for the industry to know the opinion of the users about their product from online portals, blogs, discussion boards and reviews and so on. Efficient features need to be extracted for machine-learning algorithm for better sentiment classification. In this paper, initially various features are extracted such as unigrams, bi-grams and dependency features from the text. In addition, new bi-tagged features are also extracted that conform to predefined part-of-speech patterns. Furthermore, various composite features are created using these features. Information gain (IG) and minimum redundancy maximum relevancy (mRMR) feature selection methods are used to eliminate the noisy and irrelevant features from the feature vector. Finally, machine-learning algorithms are used for classifying the review document into positive or negative class. Effects of different categories of features are investigated on four standard data-sets, namely, movie review and product (book, DVD and electronics) review data-sets. Experimental results show that composite features created from prominent features of unigram and bi-tagged features perform better than other features for sentiment classification. mRMR is a better feature selection method as compared with IG for sentiment classification. Boolean Multinomial Naïve Bayes) algorithm performs better than support vector machine classifier for SA in terms of accuracy and execution time.

  16. Formation of diploid and triploid hybrid groupers (hybridization of Epinephelus coioides ♀ × Epinephelus lanceolatus ♂) and their 5S gene analysis.

    Science.gov (United States)

    Huang, Wen; Qin, Qinbo; Yang, Huirong; Li, Shuisheng; Hu, Chaoqun; Wang, Yude; Zhang, Yong; Liu, Shaojun; Lin, Haoran

    2016-10-07

    Interspecies hybridization is widely used to achieve heterosis or hybrid vigor, which has been observed and harnessed by breeders for centuries. Natural allopolyploid hybrids generally exhibit more superior heterosis than both the diploid progenies and their parental species. However, polyploid formation processes have been long ignored, the genetic basis of heterosis in polyploids remains elusive. In the present study, triploid hybrids had been demonstrated to contain two sets of chromosomes from mother species and one set from father species. Cellular polyploidization process in the embryos had been traced. The triploid hybrids might be formed by failure formation of the second polarized genome during the second meiosis stage. Four spindle centers were observed in anaphase stage of the first cell division. Three spindle centers were observed in side of cell plate after the first cell division. The 5S rDNA genes of four types of groupers were cloned and analyzed. The diploid and triploid hybrids had been proved to contain the tandem chimera structures which were recombined by maternal and paternal monomer units. The results indicated that genome re-fusion had occurred in the hybrid progenies. To further elucidate the genetic patterns of diploid and triploid hybrids, fluorescence chromosome location had been carried out, maternal 5S gene (M-386) were used as the probe. The triploid hybrids contained fewer fluorescence loci numbers than the maternal species. The results indicated that participation of paternal 5S gene in the triploid hybrid genome had degraded the match rates of M-386 probe. Our study is the first to investigate the cellular formation processes of natural allopolyploids in hybrid fish, the cellular polyploidization process may be caused by failure formation of the second polarized genome during the meiosis, and our results will provide the molecular basis of hybrid vigor in interspecies hybridization.

  17. Personality Features of Motorists

    Directory of Open Access Journals (Sweden)

    Andrej Justinek

    1997-12-01

    Full Text Available Justinek tries to answer the question whether or not motorists have specific personality features which predispose them for safe and well-mannered driving. A good driver should have sensory abilities which enable psycho-motor coordiation of a vehicle, intellectual and cognitive features that are important for solving problems in new, unknown situations, and emotional and motivational trails defining a driver's maturity. Justmek advocates the belief that in training future drivers greater attention should be paid to developing these features which are vital for safe driving and appropriate behaviour of drivers in traffic. He also suggests certain learning methods leading to development of the above­ mentioned personality traits. Justinek introduces the notion of the 'philosophy of driving' as an essential educational category in training future drivers.

  18. Hybrid Ventilation Air Flow Process

    DEFF Research Database (Denmark)

    Heiselberg, Per Kvols

    The scope of this annex is therefore to obtain better knowledge of the use of hybrid ventilation technologies. The annex focus on development of control strategies for hybrid ventilation, on development of methods to predict hybrid ventilation performance in office buildings and on implementation...

  19. Structure of herbivore communities in two oak (Quercus spp.) hybrid zones.

    Science.gov (United States)

    Boecklen, William J; Spellenberg, Richard

    1990-11-01

    We examined patterns of density and species diversity for leaf-mining Lepidopterans and gall-forming Hymenopterans in two oak (Quercus spp.) hybrid zones: Quercus depressipes x Q. rugosa and Q. emoryi x Q. coccolobifolia. In both species complexes, hybrid hosts typically supported significantly lower densities and species diversity of parasites than did parental types. This contradicts the findings of Whitham (1989) that suggested that hybrid hosts may act as parasite sinks both in ecological and evolutionary time. We discuss features of hybrid zones that are likely to influence patterns of herbivory.

  20. Teelt van hybride wintertarwerassen

    NARCIS (Netherlands)

    Timmer, R.D.; Paauw, J.G.M.

    2003-01-01

    Om de mogelijkheden van de teelt van hybride wintertarwerassen onder Nederlandse omstandigheden in beeld te brengen zijn er van 2000-2002 proeven uitgevoerd op het PPO-proefbedrijf te Lelystad. In deze proeven zijn een 4-tal hybriderassen (Hybnos, Hyno-braba, Hyno-esta, Mercury) vergeleken met een