WorldWideScience

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. 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/.

  5. 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)

  6. 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

  7. 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.

  8. 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.

  9. 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)

  10. 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.

  11. 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.

  12. 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

  13. 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.

  14. 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...

  15. 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.

  16. 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 ...

  17. 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.

  18. 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.

  19. 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

  20. 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.

  1. 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.

  2. 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.

  3. 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

  4. 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...

  5. 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.

  6. 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.

  7. 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.

  8. 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.

  9. 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).

  10. 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.

  11. 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.

  12. 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...

  13. 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.

  14. 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.

  15. 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.

  16. 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 ...

  17. 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.

  18. 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...

  19. 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.

  20. 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.

  1. 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.

  2. 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 ...

  3. 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.

  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. 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.

  6. 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.

  7. 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.

  8. 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....

  9. 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

  10. 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

  11. 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

  12. 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.

  13. 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 ...

  14. 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.

  15. 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.

  16. 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.

  17. 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.)

  18. 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.

  19. 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.

  20. 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.

  1. 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.

  2. 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.

  3. 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

  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. 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

  7. 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.

  8. 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.

  9. 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.

  10. 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.

  11. 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

  12. 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…

  13. 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.

  14. 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.

  15. 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.

  16. 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.

  17. 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.

  18. 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.

  19. 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

  20. 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

  1. 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

  2. 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.

  3. 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.)

  4. 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

  5. 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...

  6. 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

  7. 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

  8. 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

  9. 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.

  10. 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.

  11. 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.)

  12. 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.)

  13. 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.

  14. 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

  15. 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.

  16. 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)

  17. 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.

  18. 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

  19. 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).

  20. 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

  1. 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

  2. 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.

  3. 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...

  4. 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.

  5. 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.

  6. 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.

  7. 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.

  8. 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...

  9. 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.

  10. 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.

  11. 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.

  12. 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

  13. 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.

  14. 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.

  15. 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.

  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. 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.

  18. 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...

  19. 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.

  20. 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.

  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. 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

  3. 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.

  4. 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

  5. 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

  6. 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.

  7. 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.

  8. 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).

  9. 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.

  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. 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....

  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. 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…

  14. 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.

  15. 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.

  16. 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....

  17. 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

  18. 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

  19. 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.

  20. 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

  1. 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

  2. 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...

  3. 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...

  4. 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.

  5. 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.

  6. 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.

  7. 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.

  8. 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.

  9. 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....

  10. 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

  11. 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.

  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. 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.

  14. 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.

  15. 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

  16. 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.

  17. 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.

  18. 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.

  19. 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.

  20. 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...

  1. 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.

  2. 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.

  3. 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.

  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. 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…

  6. 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.

  7. 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.

  8. 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...

  9. 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)

  10. 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…

  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. 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.

  13. 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.

  14. 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

  15. 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.

  16. Hybridizing Differential Evolution with a Genetic Algorithm for Color Image Segmentation

    Directory of Open Access Journals (Sweden)

    R. V. V. Krishna

    2016-10-01

    Full Text Available This paper proposes a hybrid of differential evolution and genetic algorithms to solve the color image segmentation problem. Clustering based color image segmentation algorithms segment an image by clustering the features of color and texture, thereby obtaining accurate prototype cluster centers. In the proposed algorithm, the color features are obtained using the homogeneity model. A new texture feature named Power Law Descriptor (PLD which is a modification of Weber Local Descriptor (WLD is proposed and further used as a texture feature for clustering. Genetic algorithms are competent in handling binary variables, while differential evolution on the other hand is more efficient in handling real parameters. The obtained texture feature is binary in nature and the color feature is a real value, which suits very well the hybrid cluster center optimization problem in image segmentation. Thus in the proposed algorithm, the optimum texture feature centers are evolved using genetic algorithms, whereas the optimum color feature centers are evolved using differential evolution.

  17. 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...

  18. 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.

  19. Procedure for the Design of a Hybrid-Series Vehicle and the Hybridization Degree Choice

    Directory of Open Access Journals (Sweden)

    Antonino Coccia

    2010-03-01

    Full Text Available For years, the interest of the UDR1 research group has focused on the development of a Hybrid Series (HS vehicle, different from the standard one thanks to the use of a Gas Turbine set (GT as a thermal engine. The reason for this choice resides in the opportunity to reduce weight and dimensions, in comparison to a traditional Internal Combustion Engine (ICE. It is not possible to use the GT engine set directly for the vehicle traction, therefore the UDR1 HS configuration shows the GT set connected with the electric generator only. The result is that the traction is purely electric. The resulting engine configuration is a commonly defined Hybrid Series. Many efforts are spent in the definition of a generic scientific method to define the correct ratio (Degree of Hybridization between the installed power of the battery pack and that of the GT electric generator, which simultaneously guarantees the life of the battery pack and the capacity of the vehicle to complete a common mission without lack of energy or stopping. This article reports a method to define the power ratio between battery pack and GT generator, applied to a recent commission for the development of a mini city bus.

  20. 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

  1. 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

  2. Ensemble of hybrid genetic algorithm for two-dimensional phase unwrapping

    Science.gov (United States)

    Balakrishnan, D.; Quan, C.; Tay, C. J.

    2013-06-01

    The phase unwrapping is the final and trickiest step in any phase retrieval technique. Phase unwrapping by artificial intelligence methods (optimization algorithms) such as hybrid genetic algorithm, reverse simulated annealing, particle swarm optimization, minimum cost matching showed better results than conventional phase unwrapping methods. In this paper, Ensemble of hybrid genetic algorithm with parallel populations is proposed to solve the branch-cut phase unwrapping problem. In a single populated hybrid genetic algorithm, the selection, cross-over and mutation operators are applied to obtain new population in every generation. The parameters and choice of operators will affect the performance of the hybrid genetic algorithm. The ensemble of hybrid genetic algorithm will facilitate to have different parameters set and different choice of operators simultaneously. Each population will use different set of parameters and the offspring of each population will compete against the offspring of all other populations, which use different set of parameters. The effectiveness of proposed algorithm is demonstrated by phase unwrapping examples and advantages of the proposed method are discussed.

  3. 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.

  4. 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).

  5. 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

  6. 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.

  7. 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

  8. 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

  9. 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

  10. 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

  11. Battery control system for hybrid vehicle and method for controlling a hybrid vehicle battery

    Science.gov (United States)

    Bockelmann, Thomas R [Battle Creek, MI; Beaty, Kevin D [Kalamazoo, MI; Zou, Zhanijang [Battle Creek, MI; Kang, Xiaosong [Battle Creek, MI

    2009-07-21

    A battery control system for controlling a state of charge of a hybrid vehicle battery includes a detecting arrangement for determining a vehicle operating state or an intended vehicle operating state and a controller for setting a target state of charge level of the battery based on the vehicle operating state or the intended vehicle operating state. The controller is operable to set a target state of charge level at a first level during a mobile vehicle operating state and at a second level during a stationary vehicle operating state or in anticipation of the vehicle operating in the stationary vehicle operating state. The invention further includes a method for controlling a state of charge of a hybrid vehicle battery.

  12. 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.

  13. 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.

  14. 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

  15. 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....

  16. 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.

  17. 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.

  18. 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.

  19. Axelrod Model of Social Influence with Cultural Hybridization

    Science.gov (United States)

    Radillo-Díaz, Alejandro; Pérez, Luis A.; Del Castillo-Mussot, Marcelo

    2012-10-01

    Since cultural interactions between a pair of social agents involve changes in both individuals, we present simulations of a new model based on Axelrod's homogenization mechanism that includes hybridization or mixture of the agents' features. In this new hybridization model, once a cultural feature of a pair of agents has been chosen for the interaction, the average of the values for this feature is reassigned as the new value for both agents after interaction. Moreover, a parameter representing social tolerance is implemented in order to quantify whether agents are similar enough to engage in interaction, as well as to determine whether they belong to the same cluster of similar agents after the system has reached the frozen state. The transitions from a homogeneous state to a fragmented one decrease in abruptness as tolerance is increased. Additionally, the entropy associated to the system presents a maximum within the transition, the width of which increases as tolerance does. Moreover, a plateau was found inside the transition for a low-tolerance system of agents with only two cultural features.

  20. 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.

  1. 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.

  2. 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.

  3. 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...

  4. 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...

  5. Effect of dominant features on neural network performance in the classification of mammographic lesions

    International Nuclear Information System (INIS)

    Zhimin Huo; Giger, M.L.; Metz, C.E.

    1999-01-01

    Two different classifiers, an artificial neural network (Ann) and a hybrid system (one step rule-based method followed by an artificial neural network) have been investigated to merge computer-extracted features in the task of differentiating between malignant and benign masses. A database consisting of 65 cases (38 malignant and 26 benign) was used in the study. A total of four computer-extracted features - spiculation, margin sharpness and two density-related measures - was used to characterize these masses. Results from our previous study showed that the hybrid system performed better than the ANN classifier. In our current study, to understand the difference between the two classifiers, we investigated their learning and decision-making processes by studying the relationships between the input features and the outputs. A correlation study showed that the outputs from the ANN-alone method correlated strongly with one of the input features (spiculation), yielding a correlation coefficient of 0.91, whereas the correlation coefficients (absolute value) for the other features ranged from 0.19 to 0.40. This strong correlation between the ANN output and spiculation measure indicates that the learning and decision-making processes of the ANN-alone method were dominated by the spiculation measure. Three-dimensional plots of the computer output as functions of the input features demonstrate that the ANN-alone method did not learn as effectively as the hybrid system in differentiating non-spiculated malignant masses from benign masses, thus resulting in an inferior performance at the high sensitivity levels. We found that with a limited database it is detrimental for an ANN to learn the significance of other features in the presence of a dominant feature. The hybrid system, which initially applied a rule concerning the value of the spiculation measure prior to employing an ANN, prevents over-learning from the dominant feature and performed better than the ANN-alone method

  6. A reconfigurable hybrid supervisory system for process control

    International Nuclear Information System (INIS)

    Garcia, H.E.; Ray, A.; Edwards, R.M.

    1994-01-01

    This paper presents a reconfigurable approach to decision and control systems for complex dynamic processes. The proposed supervisory control system is a reconfigurable hybrid architecture structured into three functional levels of hierarchy, namely, execution, supervision, and coordination. While the bottom execution level is constituted by either reconfigurable continuously varying or discrete event systems, the top two levels are necessarily governed by reconfigurable sets of discrete event decision and control systems. Based on the process status, the set of active control and supervisory algorithm is chosen. The reconfigurable hybrid system is briefly described along with a discussion on its implementation at the Experimental Breeder Reactor II of Argonne National Laboratory. A process control application of this hybrid system is presented and evaluated in an in-plant experiment

  7. A reconfigurable hybrid supervisory system for process control

    International Nuclear Information System (INIS)

    Garcia, H.E.; Ray, A.; Edwards, R.M.

    1994-01-01

    This paper presents a reconfigurable approach to decision and control systems for complex dynamic processes. The proposed supervisory control system is a reconfigurable hybrid architecture structured into three functional levels of hierarchy, namely, execution, supervision, and coordination. While, the bottom execution level is constituted by either reconfigurable continuously varying or discrete event systems, the top two levels are necessarily governed by reconfigurable sets of discrete event decision and control systems. Based on the process status, the set of active control and supervisory algorithm is chosen. The reconfigurable hybrid system is briefly described along with a discussion on its implementation at the Experimental Breeder Reactor 2 of Argonne National Laboratory. A process control application of this hybrid system is presented and evaluated in an in-plant experiment

  8. 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.

  9. Multi-dimensional conversion to the ion-hybrid mode

    International Nuclear Information System (INIS)

    Tracy, E.R.; Kaufman, A.N.; Brizard, A.J.; Morehead, J.J.

    1996-01-01

    We first demonstrate that the dispersion matrix for linear conversion of a magnetosonic wave to an ion-hybrid wave (as in a D-T plasma) can be congruently transformed to Friedland's normal form. As a result, this conversion can be represented as a two-step process of successive linear conversions in phase space. We then proceed to study the multi-dimensional case of tokamak geometry. After fourier transforming the toroidal dependence, we deal with the two-dimensional poloidal xy-plane and the two-dimensional k x k y -plane, forming a four-dimensional phase space. The dispersion manifolds for the magnetosonic wave [D M (x, k) = 0] and the ion-hybrid wave [D H (x, k) = 0] are each three-dimensional. (Their intersection, on which mode conversion occurs, is two-dimensional.) The incident magnetosonic wave (radiated by an antenna) is a two-dimensional set of rays (a lagrangian manifold): k(x) = ∇θ(x), with θ(x) the phase of the magnetosonic wave. When these rays pierce the ion-hybrid dispersion manifold, they convert to a set of ion-hybrid rays. Then, when those rays intersect the magnetosonic dispersion manifold, they convert to a set of open-quotes reflectedclose quotes magnetosonic rays. This set of rays is distinct from the set of incident rays that have been reflected by the inner surface of the tokamak plasma. As a result, the total destructive interference that can occur in the one-dimensional case may become only partial. We explore the implications of this startling phenomenon both analytically and geometrically

  10. Application of Hybrid Optimization Algorithm in the Synthesis of Linear Antenna Array

    Directory of Open Access Journals (Sweden)

    Ezgi Deniz Ülker

    2014-01-01

    Full Text Available The use of hybrid algorithms for solving real-world optimization problems has become popular since their solution quality can be made better than the algorithms that form them by combining their desirable features. The newly proposed hybrid method which is called Hybrid Differential, Particle, and Harmony (HDPH algorithm is different from the other hybrid forms since it uses all features of merged algorithms in order to perform efficiently for a wide variety of problems. In the proposed algorithm the control parameters are randomized which makes its implementation easy and provides a fast response. This paper describes the application of HDPH algorithm to linear antenna array synthesis. The results obtained with the HDPH algorithm are compared with three merged optimization techniques that are used in HDPH. The comparison shows that the performance of the proposed algorithm is comparatively better in both solution quality and robustness. The proposed hybrid algorithm HDPH can be an efficient candidate for real-time optimization problems since it yields reliable performance at all times when it gets executed.

  11. 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.

  12. Searching while loaded: Visual working memory does not interfere with hybrid search efficiency but hybrid search uses working memory capacity.

    Science.gov (United States)

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

    2016-02-01

    In "hybrid search" tasks, such as finding items on a grocery list, one must search the scene for targets while also searching the list in memory. How is the representation of a visual item compared with the representations of items in the memory set? Predominant theories would propose a role for visual working memory (VWM) either as the site of the comparison or as a conduit between visual and memory systems. In seven experiments, we loaded VWM in different ways and found little or no effect on hybrid search performance. However, the presence of a hybrid search task did reduce the measured capacity of VWM by a constant amount regardless of the size of the memory or visual sets. These data are broadly consistent with an account in which VWM must dedicate a fixed amount of its capacity to passing visual representations to long-term memory for comparison to the items in the memory set. The data cast doubt on models in which the search template resides in VWM or where memory set item representations are moved from LTM through VWM to earlier areas for comparison to visual items.

  13. Reproductive biology and natural hybridization between two endemic species of Pitcairnia (Bromeliaceae).

    Science.gov (United States)

    Wendt, T; Canela, M B; Gelli de Faria, A P; Rios, R I

    2001-10-01

    We investigated pollination biology and breeding systems in hybridizing populations of Pitcairnia albiflos and P. staminea; both species are endemic to rocky outcrops at Rio de Janeiro, Brazil. These species are morphologically distinct and easily recognized by floral color: white in P. albiflos and red in P. staminea. Putative hybrids show a large range of intermediate pink floral colors. The showy hermaphroditic flowers offer pollen and nectar that attract many visitors including bees, butterflies, hawk moths, and bats. Although the flowers of both parental species and hybrids open at night, only P. albiflos had other adaptations for nocturnal pollination. Flowering times overlapped during three consecutive years of observation. Bees visited both species and putative hybrids. Cross-pollinations were performed within and among parental species and hybrids in a greenhouse using plants transplanted from the field. Pitcairnia staminea and hybrids are self-compatible and could be spontaneously self-pollinated, whereas P. albiflos, though self-compatible, needs pollinators' services for self-pollination. Facultative agamospermy was found in the parental species. Prezygotic and postzygotic reproductive barriers between these taxa were weak. Reciprocal hand-pollinations between parental species and with hybrids yielded high fruit sets with viable seeds. Evaluations of fruit set, seed set, seed germination, and pollen viability were undertaken to compare the fitness of the hybrids relative to their parents. The hybrids showed equivalent fitness, except for lower pollen viability. Some conservation implications are noted.

  14. 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.

  15. 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.

  16. 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.

  17. A Review of Hybrid Brain-Computer Interface Systems

    Directory of Open Access Journals (Sweden)

    Setare Amiri

    2013-01-01

    Full Text Available Increasing number of research activities and different types of studies in brain-computer interface (BCI systems show potential in this young research area. Research teams have studied features of different data acquisition techniques, brain activity patterns, feature extraction techniques, methods of classifications, and many other aspects of a BCI system. However, conventional BCIs have not become totally applicable, due to the lack of high accuracy, reliability, low information transfer rate, and user acceptability. A new approach to create a more reliable BCI that takes advantage of each system is to combine two or more BCI systems with different brain activity patterns or different input signal sources. This type of BCI, called hybrid BCI, may reduce disadvantages of each conventional BCI system. In addition, hybrid BCIs may create more applications and possibly increase the accuracy and the information transfer rate. However, the type of BCIs and their combinations should be considered carefully. In this paper, after introducing several types of BCIs and their combinations, we review and discuss hybrid BCIs, different possibilities to combine them, and their advantages and disadvantages.

  18. 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.

  19. 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...

  20. 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.

  1. 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...

  2. A hybrid measure-correlate-predict method for long-term wind condition assessment

    International Nuclear Information System (INIS)

    Zhang, Jie; Chowdhury, Souma; Messac, Achille; Hodge, Bri-Mathias

    2014-01-01

    Highlights: • A hybrid measure-correlate-predict (MCP) methodology with greater accuracy is developed. • Three sets of performance metrics are proposed to evaluate the hybrid MCP method. • Both wind speed and direction are considered in the hybrid MCP method. • The best combination of MCP algorithms is determined. • The developed hybrid MCP method is uniquely helpful for long-term wind resource assessment. - Abstract: This paper develops a hybrid measure-correlate-predict (MCP) strategy to assess long-term wind resource variations at a farm site. The hybrid MCP method uses recorded data from multiple reference stations to estimate long-term wind conditions at a target wind plant site with greater accuracy than is possible with data from a single reference station. The weight of each reference station in the hybrid strategy is determined by the (i) distance and (ii) elevation differences between the target farm site and each reference station. In this case, the wind data is divided into sectors according to the wind direction, and the MCP strategy is implemented for each wind direction sector separately. The applicability of the proposed hybrid strategy is investigated using five MCP methods: (i) the linear regression; (ii) the variance ratio; (iii) the Weibull scale; (iv) the artificial neural networks; and (v) the support vector regression. To implement the hybrid MCP methodology, we use hourly averaged wind data recorded at five stations in the state of Minnesota between 07-01-1996 and 06-30-2004. Three sets of performance metrics are used to evaluate the hybrid MCP method. The first set of metrics analyze the statistical performance, including the mean wind speed, wind speed variance, root mean square error, and mean absolute error. The second set of metrics evaluate the distribution of long-term wind speed; to this end, the Weibull distribution and the Multivariate and Multimodal Wind Distribution models are adopted. The third set of metrics analyze

  3. Micro-Doppler Feature Extraction and Recognition Based on Netted Radar for Ballistic Targets

    Directory of Open Access Journals (Sweden)

    Feng Cun-qian

    2015-12-01

    Full Text Available This study examines the complexities of using netted radar to recognize and resolve ballistic midcourse targets. The application of micro-motion feature extraction to ballistic mid-course targets is analyzed, and the current status of application and research on micro-motion feature recognition is concluded for singlefunction radar networks such as low- and high-resolution imaging radar networks. Advantages and disadvantages of these networks are discussed with respect to target recognition. Hybrid-mode radar networks combine low- and high-resolution imaging radar and provide a specific reference frequency that is the basis for ballistic target recognition. Main research trends are discussed for hybrid-mode networks that apply micromotion feature extraction to ballistic mid-course targets.

  4. Components and systems for hybrid- and electromobiles; Komponenten und Systeme fuer Hybrid- und Elektrofahrzeuge

    Energy Technology Data Exchange (ETDEWEB)

    Immle, Michael; Burgmayr, Thomas [Panasonic Electric Works Europe AG, Holzkirchen (Germany)

    2010-07-01

    On the Hybrid and Electric Vehicle sector Panasonic Electric Works is working among others on electro-mechanical products, such as contactors for battery disconnection or battery charging, on semi-conductor relays for battery monitoring and on complex systems as battery disconnect units. This paper will show experience on the hybrid vehicle sector. Further on different switching components and their usage will be introduced. As a main topic battery disconnected units will be discussed. Based on an actual example basic development items and system features will be touched and important development stages will be shown. As a general topic a future view on vehicles and batteries, as well as on charging systems and infrastructural necessities will be introduced. (orig.)

  5. 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.

  6. Features Selection for Skin Micro-Image Symptomatic Recognition

    Institute of Scientific and Technical Information of China (English)

    HUYue-li; CAOJia-lin; ZHAOQian; FENGXu

    2004-01-01

    Automatic recognition of skin micro-image symptom is important in skin diagnosis and treatment. Feature selection is to improve the classification performance of skin micro-image symptom.This paper proposes a hybrid approach based on the support vector machine (SVM) technique and genetic algorithm (GA) to select an optimum feature subset from the feature group extracted from the skin micro-images. An adaptive GA is introduced for maintaining the convergence rate. With the proposed method, the average cross validation accuracy is increased from 88.25% using all features to 96.92% using only selected features provided by a classifier for classification of 5 classes of skin symptoms. The experimental results are satisfactory.

  7. Features Selection for Skin Micro-Image Symptomatic Recognition

    Institute of Scientific and Technical Information of China (English)

    HU Yue-li; CAO Jia-lin; ZHAO Qian; FENG Xu

    2004-01-01

    Automatic recognition of skin micro-image symptom is important in skin diagnosis and treatment. Feature selection is to improve the classification performance of skin micro-image symptom.This paper proposes a hybrid approach based on the support vector machine (SVM) technique and genetic algorithm (GA) to select an optimum feature subset from the feature group extracted from the skin micro-images. An adaptive GA is introduced for maintaining the convergence rate. With the proposed method, the average cross validation accuracy is increased from 88.25% using all features to 96.92 % using only selected features provided by a classifier for classification of 5 classes of skin symptoms. The experimental results are satisfactory.

  8. 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.

  9. Hydrogen atom as a quantum-classical hybrid system

    International Nuclear Information System (INIS)

    Zhan, Fei; Wu, Biao

    2013-01-01

    Hydrogen atom is studied as a quantum-classical hybrid system, where the proton is treated as a classical object while the electron is regarded as a quantum object. We use a well known mean-field approach to describe this hybrid hydrogen atom; the resulting dynamics for the electron and the proton is compared to their full quantum dynamics. The electron dynamics in the hybrid description is found to be only marginally different from its full quantum counterpart. The situation is very different for the proton: in the hybrid description, the proton behaves like a free particle; in the fully quantum description, the wave packet center of the proton orbits around the center of mass. Furthermore, we find that the failure to describe the proton dynamics properly can be regarded as a manifestation of the fact that there is no conservation of momentum in the mean-field hybrid approach. We expect that such a failure is a common feature for all existing approaches for quantum-classical hybrid systems of Born-Oppenheimer type.

  10. 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...

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

    Science.gov (United States)

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

    2014-12-01

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

  12. 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.

  13. 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.

  14. 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.

  15. 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.

  16. 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.

  17. 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.

  18. 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...

  19. 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

  20. 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...

  1. 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...

  2. 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

  3. Do Hybrid Trees Inherit Invasive Characteristics? Fruits of Corymbia torelliana X C. citriodora Hybrids and Potential for Seed Dispersal by Bees.

    Science.gov (United States)

    Wallace, Helen Margaret; Leonhardt, Sara Diana

    2015-01-01

    Tree invasions have substantial impacts on biodiversity and ecosystem functioning, and trees that are dispersed by animals are more likely to become invasive. In addition, hybridisation between plants is well documented as a source of new weeds, as hybrids gain new characteristics that allow them to become invasive. Corymbia torelliana is an invasive tree with an unusual animal dispersal mechanism: seed dispersal by stingless bees, that hybridizes readily with other species. We examined hybrids between C. torelliana and C. citriodora subsp. citriodora to determine whether hybrids have inherited the seed dispersal characteristics of C. torelliana that allow bee dispersal. Some hybrid fruits displayed the characteristic hollowness, resin production and resin chemistry associated with seed dispersal by bees. However, we did not observe bees foraging on any hybrid fruits until they had been damaged. We conclude that C. torelliana and C. citriodora subsp. citriodora hybrids can inherit some fruit characters that are associated with dispersal by bees, but we did not find a hybrid with the complete set of characters that would enable bee dispersal. However, around 20,000 hybrids have been planted in Australia, and ongoing monitoring is necessary to identify any hybrids that may become invasive.

  4. 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.

  5. 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.

  6. 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.

  7. 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.

  8. 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.

  9. 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.

  10. 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

  11. 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

  12. 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.

  13. 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.

  14. 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.

  15. 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.

  16. The Ion Cyclotron, Lower Hybrid, and Alfven Wave Heating Methods

    International Nuclear Information System (INIS)

    Koch, R.

    2004-01-01

    This lecture covers the practical features and experimental results of the three heating methods. The emphasis is on ion cyclotron heating. First, we briefly come back to the main non-collisional heating mechanisms and to the particular features of the quasilinear coefficient in the ion cyclotron range of frequencies (ICRF). The specific case of the ion-ion hybrid resonance is treated, as well as the polarisation issue and minority heating scheme. The various ICRF scenarios are reviewed. The experimental applications of ion cyclotron resonance heating (ICRH) systems are outlined. Then, the lower hybrid and Alfven wave heating and current drive experimental results are covered more briefly. Where applicable, the prospects for ITER are commented

  17. 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.)

  18. 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.

  19. 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

  20. 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....

  1. 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.

  2. 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...

  3. 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.

  4. In Silico Genomic Fingerprints of the Bacillus anthracis Group Obtained by Virtual Hybridization

    Directory of Open Access Journals (Sweden)

    Hueman Jaimes-Díaz

    2015-02-01

    Full Text Available In this study we evaluate the capacity of Virtual Hybridization to identify between highly related bacterial strains. Eight genomic fingerprints were obtained by virtual hybridization for the Bacillus anthracis genome set, and a set of 15,264 13-nucleotide short probes designed to produce genomic fingerprints unique for each organism. The data obtained from each genomic fingerprint were used to obtain hybridization patterns simulating a DNA microarray. Two virtual hybridization methods were used: the Direct and the Extended method to identify the number of potential hybridization sites and thus determine the minimum sensitivity value to discriminate between genomes with 99.9% similarity. Genomic fingerprints were compared using both methods and phylogenomic trees were constructed to verify that the minimum detection value is 0.000017. Results obtained from the genomic fingerprints suggest that the distribution in the trees is correct, as compared to other taxonomic methods. Specific virtual hybridization sites for each of the genomes studied were also identified.

  5. 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.

  6. A Hybrid Neuro-Fuzzy Model For Integrating Large Earth-Science Datasets

    Science.gov (United States)

    Porwal, A.; Carranza, J.; Hale, M.

    2004-12-01

    A GIS-based hybrid neuro-fuzzy approach to integration of large earth-science datasets for mineral prospectivity mapping is described. It implements a Takagi-Sugeno type fuzzy inference system in the framework of a four-layered feed-forward adaptive neural network. Each unique combination of the datasets is considered a feature vector whose components are derived by knowledge-based ordinal encoding of the constituent datasets. A subset of feature vectors with a known output target vector (i.e., unique conditions known to be associated with either a mineralized or a barren location) is used for the training of an adaptive neuro-fuzzy inference system. Training involves iterative adjustment of parameters of the adaptive neuro-fuzzy inference system using a hybrid learning procedure for mapping each training vector to its output target vector with minimum sum of squared error. The trained adaptive neuro-fuzzy inference system is used to process all feature vectors. The output for each feature vector is a value that indicates the extent to which a feature vector belongs to the mineralized class or the barren class. These values are used to generate a prospectivity map. The procedure is demonstrated by an application to regional-scale base metal prospectivity mapping in a study area located in the Aravalli metallogenic province (western India). A comparison of the hybrid neuro-fuzzy approach with pure knowledge-driven fuzzy and pure data-driven neural network approaches indicates that the former offers a superior method for integrating large earth-science datasets for predictive spatial mathematical modelling.

  7. 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...

  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. CSP-based chemical kinetics mechanisms simplification strategy for non-premixed combustion: An application to hybrid rocket propulsion

    KAUST Repository

    Ciottoli, Pietro P.

    2017-08-14

    A set of simplified chemical kinetics mechanisms for hybrid rocket applications using gaseous oxygen (GOX) and hydroxyl-terminated polybutadiene (HTPB) is proposed. The starting point is a 561-species, 2538-reactions, detailed chemical kinetics mechanism for hydrocarbon combustion. This mechanism is used for predictions of the oxidation of butadiene, the primary HTPB pyrolysis product. A Computational Singular Perturbation (CSP) based simplification strategy for non-premixed combustion is proposed. The simplification algorithm is fed with the steady-solutions of classical flamelet equations, these being representative of the non-premixed nature of the combustion processes characterizing a hybrid rocket combustion chamber. The adopted flamelet steady-state solutions are obtained employing pure butadiene and gaseous oxygen as fuel and oxidizer boundary conditions, respectively, for a range of imposed values of strain rate and background pressure. Three simplified chemical mechanisms, each comprising less than 20 species, are obtained for three different pressure values, 3, 17, and 36 bar, selected in accordance with an experimental test campaign of lab-scale hybrid rocket static firings. Finally, a comprehensive strategy is shown to provide simplified mechanisms capable of reproducing the main flame features in the whole pressure range considered.

  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. 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....

  12. A Hybrid Soft Computing Approach for Subset Problems

    Directory of Open Access Journals (Sweden)

    Broderick Crawford

    2013-01-01

    Full Text Available Subset problems (set partitioning, packing, and covering are formal models for many practical optimization problems. A set partitioning problem determines how the items in one set (S can be partitioned into smaller subsets. All items in S must be contained in one and only one partition. Related problems are set packing (all items must be contained in zero or one partitions and set covering (all items must be contained in at least one partition. Here, we present a hybrid solver based on ant colony optimization (ACO combined with arc consistency for solving this kind of problems. ACO is a swarm intelligence metaheuristic inspired on ants behavior when they search for food. It allows to solve complex combinatorial problems for which traditional mathematical techniques may fail. By other side, in constraint programming, the solving process of Constraint Satisfaction Problems can dramatically reduce the search space by means of arc consistency enforcing constraint consistencies either prior to or during search. Our hybrid approach was tested with set covering and set partitioning dataset benchmarks. It was observed that the performance of ACO had been improved embedding this filtering technique in its constructive phase.

  13. 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

  14. 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.

  15. Performance Evaluation of the Concept of Hybrid Heat Pipe as Passive In-core Cooling Systems for Advanced Nuclear Power Plant

    International Nuclear Information System (INIS)

    Jeong, Yeong Shin; Kim, Kyung Mo; Kim, In Guk; Bang, In Cheol

    2015-01-01

    As an arising issue for inherent safety of nuclear power plant, the concept of hybrid heat pipe as passive in-core cooling systems was introduced. Hybrid heat pipe has unique features that it is inserted in core directly to remove decay heat from nuclear fuel without any changes of structures of existing facilities of nuclear power plant, substituting conventional control rod. Hybrid heat pipe consists of metal cladding, working fluid, wick structure, and neutron absorber. Same with working principle of the heat pipe, heat is transported by phase change of working fluid inside metal cask. Figure 1 shows the systematic design of the hybrid heat pipe cooling system. In this study, the concept of a hybrid heat pipe was introduced as a Passive IN-core Cooling Systems (PINCs) and demonstrated for internal design features of heat pipe containing neutron absorber. Using a commercial CFD code, single hybrid heat pipe model was analyzed to evaluate thermal performance in designated operating condition. Also, 1-dimensional reactor transient analysis was done by calculating temperature change of the coolant inside reactor pressure vessel using MATLAB. As a passive decay heat removal device, hybrid heat pipe was suggested with a concept of combination of heat pipe and control rod. Hybrid heat pipe has distinct feature that it can be a unique solution to cool the reactor when depressurization process is impossible so that refueling water cannot be injected into RPV by conventional ECCS. It contains neutron absorber material inside heat pipe, so it can stop the reactor and at the same time, remove decay heat in core. For evaluating the concept of hybrid heat pipe, its thermal performance was analyzed using CFD and one-dimensional transient analysis. From single hybrid heat pipe simulation, the hybrid heat pipe can transport heat from the core inside to outside about 18.20 kW, and total thermal resistance of hybrid heat pipe is 0.015 .deg. C/W. Due to unique features of long heat

  16. 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.

  17. 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.

  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. Development of the Multiple Use Plug Hybrid for Nanosats (MUPHyN) miniature thruster

    Science.gov (United States)

    Eilers, Shannon

    The Multiple Use Plug Hybrid for Nanosats (MUPHyN) prototype thruster incorporates solutions to several major challenges that have traditionally limited the deployment of chemical propulsion systems on small spacecraft. The MUPHyN thruster offers several features that are uniquely suited for small satellite applications. These features include 1) a non-explosive ignition system, 2) non-mechanical thrust vectoring using secondary fluid injection on an aerospike nozzle cooled with the oxidizer flow, 3) a non-toxic, chemically-stable combination of liquid and inert solid propellants, 4) a compact form factor enabled by the direct digital manufacture of the inert solid fuel grain. Hybrid rocket motors provide significant safety and reliability advantages over both solid composite and liquid propulsion systems; however, hybrid motors have found only limited use on operational vehicles due to 1) difficulty in modeling the fuel flow rate 2) poor volumetric efficiency and/or form factor 3) significantly lower fuel flow rates than solid rocket motors 4) difficulty in obtaining high combustion efficiencies. The features of the MUPHyN thruster are designed to offset and/or overcome these shortcomings. The MUPHyN motor design represents a convergence of technologies, including hybrid rocket regression rate modeling, aerospike secondary injection thrust vectoring, multiphase injector modeling, non-pyrotechnic ignition, and nitrous oxide regenerative cooling that address the traditional challenges that limit the use of hybrid rocket motors and aerospike nozzles. This synthesis of technologies is unique to the MUPHyN thruster design and no comparable work has been published in the open literature.

  20. 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 ...

  1. HyDe: a Python Package for Genome-Scale Hybridization Detection.

    Science.gov (United States)

    Blischak, Paul D; Chifman, Julia; Wolfe, Andrea D; Kubatko, Laura S

    2018-03-19

    The analysis of hybridization and gene flow among closely related taxa is a common goal for researchers studying speciation and phylogeography. Many methods for hybridization detection use simple site pattern frequencies from observed genomic data and compare them to null models that predict an absence of gene flow. The theory underlying the detection of hybridization using these site pattern probabilities exploits the relationship between the coalescent process for gene trees within population trees and the process of mutation along the branches of the gene trees. For certain models, site patterns are predicted to occur in equal frequency (i.e., their difference is 0), producing a set of functions called phylogenetic invariants. In this paper we introduce HyDe, a software package for detecting hybridization using phylogenetic invariants arising under the coalescent model with hybridization. HyDe is written in Python, and can be used interactively or through the command line using pre-packaged scripts. We demonstrate the use of HyDe on simulated data, as well as on two empirical data sets from the literature. We focus in particular on identifying individual hybrids within population samples and on distinguishing between hybrid speciation and gene flow. HyDe is freely available as an open source Python package under the GNU GPL v3 on both GitHub (https://github.com/pblischak/HyDe) and the Python Package Index (PyPI: https://pypi.python.org/pypi/phyde).

  2. 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.

  3. 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.

  4. 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.

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

    Science.gov (United States)

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

    2015-01-01

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

  6. Organization and variation analysis of 5S rDNA in different ploidy-level hybrids of red crucian carp × topmouth culter.

    Science.gov (United States)

    He, Weiguo; Qin, Qinbo; Liu, Shaojun; Li, Tangluo; Wang, Jing; Xiao, Jun; Xie, Lihua; Zhang, Chun; Liu, Yun

    2012-01-01

    Through distant crossing, diploid, triploid and tetraploid hybrids of red crucian carp (Carassius auratus red var., RCC♀, Cyprininae, 2n = 100) × topmouth culter (Erythroculter ilishaeformis Bleeker, TC♂, Cultrinae, 2n = 48) were successfully produced. Diploid hybrids possessed 74 chromosomes with one set from RCC and one set from TC; triploid hybrids harbored 124 chromosomes with two sets from RCC and one set from TC; tetraploid hybrids had 148 chromosomes with two sets from RCC and two sets from TC. The 5S rDNA of the three different ploidy-level hybrids and their parents were sequenced and analyzed. There were three monomeric 5S rDNA classes (designated class I: 203 bp; class II: 340 bp; and class III: 477 bp) in RCC and two monomeric 5S rDNA classes (designated class IV: 188 bp, and class V: 286 bp) in TC. In the hybrid offspring, diploid hybrids inherited three 5S rDNA classes from their female parent (RCC) and only class IV from their male parent (TC). Triploid hybrids inherited class II and class III from their female parent (RCC) and class IV from their male parent (TC). Tetraploid hybrids gained class II and class III from their female parent (RCC), and generated a new 5S rDNA sequence (designated class I-N). The specific paternal 5S rDNA sequence of class V was not found in the hybrid offspring. Sequence analysis of 5S rDNA revealed the influence of hybridization and polyploidization on the organization and variation of 5S rDNA in fish. This is the first report on the coexistence in vertebrates of viable diploid, triploid and tetraploid hybrids produced by crossing parents with different chromosome numbers, and these new hybrids are novel specimens for studying the genomic variation in the first generation of interspecific hybrids, which has significance for evolution and fish genetics.

  7. 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/.

  8. 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...

  9. 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

  10. 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.

  11. A direct hybrid SN method for slab-geometry lattice calculations

    International Nuclear Information System (INIS)

    Silva, Davi J.M.; Barros, Ricardo C.; Zani, Jose H.

    2011-01-01

    In this work we describe a hybrid direct method for calculating the thermal disadvantage factor and the neutron flux distribution in fuel-moderator lattices. For the mathematical model, we use the one-speed slab-geometry discrete ordinates (S N ) transport equation with linearly anisotropic scattering. The basic idea is to use higher order angular quadrature set in the highly absorbing fuel region (S NF ) and lower order angular quadrature set in the diffusive moderator region (S NM ) , i.e., N F > N M . We apply special continuity conditions based on the equivalence of the S N and P N-1 equations, which characterize the hybrid model. Numerical results to a typical model problem are given to illustrate the accuracy and the efficiency of the offered hybrid method. (author)

  12. CSP: A Multifaceted Hybrid Architecture for Space Computing

    Science.gov (United States)

    Rudolph, Dylan; Wilson, Christopher; Stewart, Jacob; Gauvin, Patrick; George, Alan; Lam, Herman; Crum, Gary Alex; Wirthlin, Mike; Wilson, Alex; Stoddard, Aaron

    2014-01-01

    Research on the CHREC Space Processor (CSP) takes a multifaceted hybrid approach to embedded space computing. Working closely with the NASA Goddard SpaceCube team, researchers at the National Science Foundation (NSF) Center for High-Performance Reconfigurable Computing (CHREC) at the University of Florida and Brigham Young University are developing hybrid space computers that feature an innovative combination of three technologies: commercial-off-the-shelf (COTS) devices, radiation-hardened (RadHard) devices, and fault-tolerant computing. Modern COTS processors provide the utmost in performance and energy-efficiency but are susceptible to ionizing radiation in space, whereas RadHard processors are virtually immune to this radiation but are more expensive, larger, less energy-efficient, and generations behind in speed and functionality. By featuring COTS devices to perform the critical data processing, supported by simpler RadHard devices that monitor and manage the COTS devices, and augmented with novel uses of fault-tolerant hardware, software, information, and networking within and between COTS devices, the resulting system can maximize performance and reliability while minimizing energy consumption and cost. NASA Goddard has adopted the CSP concept and technology with plans underway to feature flight-ready CSP boards on two upcoming space missions.

  13. 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.

  14. 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.

  15. Hybrid modelling of soil-structure interaction for embedded structures

    International Nuclear Information System (INIS)

    Gupta, S.; Penzien, J.

    1981-01-01

    The basic methods currently being used for the analysis of soil-structure interaction fail to properly model three-dimensional embedded structures with flexible foundations. A hybrid model for the analysis of soil-structure interaction is developed in this investigation which takes advantage of the desirable features of both the finite element and substructure methods and which minimizes their undesirable features. The hybrid model is obtained by partitioning the total soil-structure system into a nearfield and a far-field with a smooth hemispherical interface. The near-field consists of the structure and a finite region of soil immediately surrounding its base. The entire near-field may be modelled in three-dimensional form using the finite element method; thus, taking advantage of its ability to model irregular geometries, and the non-linear soil behavior in the immediate vicinity of the structure. (orig./WL)

  16. Transition Features from Simplicity-Universality to Complexity-Diversification Under UHNTF

    International Nuclear Information System (INIS)

    Fang Jinqing; Li Yong

    2010-01-01

    A large unified hybrid network model with a variable speed growth (LUHNM-VSG) is proposed as third model of the unified hybrid network theoretical framework (UHNTF). A hybrid growth ratio vg of deterministic linking number to random linking number and variable speed growth index α are introduced in it. The main effects of vg and α on topological transition features of the LUHNM-VSG are revealed. For comparison with the other models, we construct a type of the network complexity pyramid with seven levels, in which from the bottom level-1 to the top level-7 of the pyramid simplicity-universality is increasing but complexity-diversity is decreasing. The transition relations between them depend on matching of four hybrid ratios (dr, fd, gr, vg). Thus the most of network models can be investigated in the unification way via four hybrid ratios (dr, fd, gr, vg). The LUHNM-VSG as the level-1 of the pyramid is much better and closer to description of real-world networks as well as has potential application. (interdisciplinary physics and related areas of science and technology)

  17. 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.

  18. 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

  19. 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

  20. An insight into the biological activities of heterocyclic-fatty acid hybrid molecules.

    Science.gov (United States)

    Venepally, Vijayendar; Reddy Jala, Ram Chandra

    2017-12-01

    Heterocyclic compounds are the interesting core structures for the development of new bioactive compounds. Fatty acids are derived from renewable raw materials and exhibit various biological activities. Several researchers are amalgamating these two bioactive components to yield bioactive hybrid molecules with some desirable features. Heterocyclic-fatty acid hybrid derivatives are a new class of heterocyclic compounds with a broad range of biological activities and significance in the field of medicinal chemistry. Over the last few years, many research articles emphasized the significance of heterocyclic-fatty acid hybrid derivatives. The present review article focuses the developments in designing and biological evaluation of heterocyclic-fatty acid hybrid molecules. Copyright © 2017. Published by Elsevier Masson SAS.

  1. 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.

  2. 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.

  3. The role of object categories in hybrid visual and memory search

    Science.gov (United States)

    Cunningham, Corbin A.; Wolfe, Jeremy M.

    2014-01-01

    In hybrid search, observers (Os) search for any of several possible targets in a visual display containing distracting items and, perhaps, a target. Wolfe (2012) found that responses times (RT) in such tasks increased linearly with increases in the number of items in the display. However, RT increased linearly with the log of the number of items in the memory set. In earlier work, all items in the memory set were unique instances (e.g. this apple in this pose). Typical real world tasks involve more broadly defined sets of stimuli (e.g. any “apple” or, perhaps, “fruit”). The present experiments show how sets or categories of targets are handled in joint visual and memory search. In Experiment 1, searching for a digit among letters was not like searching for targets from a 10-item memory set, though searching for targets from an N-item memory set of arbitrary alphanumeric characters was like searching for targets from an N-item memory set of arbitrary objects. In Experiment 2, Os searched for any instance of N sets or categories held in memory. This hybrid search was harder than search for specific objects. However, memory search remained logarithmic. Experiment 3 illustrates the interaction of visual guidance and memory search when a subset of visual stimuli are drawn from a target category. Furthermore, we outline a conceptual model, supported by our results, defining the core components that would be necessary to support such categorical hybrid searches. PMID:24661054

  4. Performance Analysis of a Hybrid Power Cutting System for Roadheader

    Directory of Open Access Journals (Sweden)

    Yang Yang

    2017-01-01

    Full Text Available An electrohydraulic hybrid power cutting transmission system for roadheader under specific working condition was proposed in this paper. The overall model for the new system composed of an electric motor model, a hydraulic pump-motor model, a torsional planetary set model, and a hybrid power train model was established. The working mode characteristics were simulated under the conditions of taking the effect of cutting picks into account. The advantages of new hybrid power cutting system about the dynamic response under shock load were investigated compared with the traditional cutting system. The results illustrated that the hybrid power system had an obvious cushioning in terms of the dynamic load of cutting electric motor and planetary gear set. Besides, the hydraulic motor could provide an auxiliary power to improve the performance of the electric motor. With further analysis, a dynamic load was found to have a high relation to the stiffness and damping of coupling in the transmission train. The results could be a useful guide for the design of cutting transmission of roadheader.

  5. 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.

  6. 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.

  7. Test Beam Results of Geometry Optimized Hybrid Pixel Detectors

    CERN Document Server

    Becks, K H; Grah, C; Mättig, P; Rohe, T

    2006-01-01

    The Multi-Chip-Module-Deposited (MCM-D) technique has been used to build hybrid pixel detector assemblies. This paper summarises the results of an analysis of data obtained in a test beam campaign at CERN. Here, single chip hybrids made of ATLAS pixel prototype read-out electronics and special sensor tiles were used. They were prepared by the Fraunhofer Institut fuer Zuverlaessigkeit und Mikrointegration, IZM, Berlin, Germany. The sensors feature an optimized sensor geometry called equal sized bricked. This design enhances the spatial resolution for double hits in the long direction of the sensor cells.

  8. A quadratic kernel for computing the hybridization number of multiple trees

    NARCIS (Netherlands)

    L.J.J. van Iersel (Leo); S. Linz

    2012-01-01

    htmlabstractIt has recently been shown that the NP-hard problem of calculating the minimum number of hybridization events that is needed to explain a set of rooted binary phylogenetic trees by means of a hybridization network is fixed-parameter tractable if an instance of the problem consists of

  9. 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.

  10. 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.)

  11. 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

  12. 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

  13. Detection of DNA hybridizations using solid-state nanopores

    International Nuclear Information System (INIS)

    Balagurusamy, Venkat S K; Weinger, Paul; Sean Ling, Xinsheng

    2010-01-01

    We report an experimental study of using DNA translocation through solid-state nanopores to detect the sequential arrangement of two double-stranded 12-mer hybridization segments on a single-stranded DNA molecule. The sample DNA is a trimer molecule formed by hybridizing three single-stranded oligonucleotides. A polystyrene bead is attached to the end of the trimer DNA, providing a mechanism in slowing down the translocation and suppressing the thermal diffusion, thereby allowing the detection of short features of DNA by standard patch-clamp electronics. The electrical signature of the translocation of a trimer molecule through a nanopore has been identified successfully in the temporal traces of ionic current. The results reported here represent the first successful attempt in using a solid-state nanopore as an ionic scanning device in resolving individual hybridization segments (or 'probes') on a DNA molecule.

  14. Detection of DNA hybridizations using solid-state nanopores

    Energy Technology Data Exchange (ETDEWEB)

    Balagurusamy, Venkat S K; Weinger, Paul; Sean Ling, Xinsheng, E-mail: Xinsheng_Ling@brown.edu [Department of Physics, Brown University, Providence, RI 02912 (United States)

    2010-08-20

    We report an experimental study of using DNA translocation through solid-state nanopores to detect the sequential arrangement of two double-stranded 12-mer hybridization segments on a single-stranded DNA molecule. The sample DNA is a trimer molecule formed by hybridizing three single-stranded oligonucleotides. A polystyrene bead is attached to the end of the trimer DNA, providing a mechanism in slowing down the translocation and suppressing the thermal diffusion, thereby allowing the detection of short features of DNA by standard patch-clamp electronics. The electrical signature of the translocation of a trimer molecule through a nanopore has been identified successfully in the temporal traces of ionic current. The results reported here represent the first successful attempt in using a solid-state nanopore as an ionic scanning device in resolving individual hybridization segments (or 'probes') on a DNA molecule.

  15. Comprehensive exergetic and economic comparison of PWR and hybrid fossil fuel-PWR power plants

    International Nuclear Information System (INIS)

    Sayyaadi, Hoseyn; Sabzaligol, Tooraj

    2010-01-01

    A typical 1000 MW Pressurized Water Reactor (PWR) nuclear power plant and two similar hybrid 1000 MW PWR plants operate with natural gas and coal fired fossil fuel superheater-economizers (Hybrid PWR-Fossil fuel plants) are compared exergetically and economically. Comparison is performed based on energetic and economic features of three systems. In order to compare system at their optimum operating point, three workable base case systems including the conventional PWR, and gas and coal fired hybrid PWR-Fossil fuel power plants considered and optimized in exergetic and exergoeconomic optimization scenarios, separately. The thermodynamic modeling of three systems is performed based on energy and exergy analyses, while an economic model is developed according to the exergoeconomic analysis and Total Revenue Requirement (TRR) method. The objective functions based on exergetic and exergoeconomic analyses are developed. The exergetic and exergoeconomic optimizations are performed using the Genetic Algorithm (GA). Energetic and economic features of exergetic and exergoeconomic optimized conventional PWR and gas and coal fired Hybrid PWR-Fossil fuel power plants are compared and discussed comprehensively.

  16. Hybrid structure in civil engineering construction.; Doboku bun`ya ni okeru fukugo kozo.

    Energy Technology Data Exchange (ETDEWEB)

    Ikeda, S. [Yokohama National Univ. (Japan). Faculty of Engineering

    1995-03-30

    The structure of steel-concrete hybrid structure which is recently attracting attention is outlined quoting some examples. The effects of steel-concrete hybrid structure are classified according to the characteristics. The Normandie Bridge completed in January this year near the mouth of the Seine River in France is a cable stayed bridge with the world largest span, and it has a hybrid structure of ingeniously combined steel and concrete. The Dole Bridge in France is a hybrid bridge with 7 continuous spans having steel corrugated sheets in the web. Hybrid structure has come to be applied to many structures other than the superstructure works of bridges. The substructures of bridges are applied to immersed tunnels, and the usefulness has come to be recognized widely. The features of hybrid structure can contribute well to the reinforcement of existing structures. In addition, adoption of hybrid structure has been studied as the best method for repairing and reinforcing structures damaged by earthquakes. 8 refs., 6 figs., 1 tab.

  17. Two-field axion-monodromy hybrid inflation model: Dante's Waterfall

    Science.gov (United States)

    Carone, Christopher D.; Erlich, Joshua; Sensharma, Anuraag; Wang, Zhen

    2015-02-01

    We describe a hybrid axion-monodromy inflation model motivated by the Dante's Inferno scenario. In Dante's Inferno, a two-field potential features a stable trench along which a linear combination of the two fields slowly rolls, rendering the dynamics essentially identical to that of single-field chaotic inflation. A shift symmetry allows for the Lyth bound to be effectively evaded as in other axion-monodromy models. In our proposal, the potential is concave downward near the origin and the inflaton trajectory is a gradual downward spiral, ending at a point where the trench becomes unstable. There, the fields begin falling rapidly towards the minimum of the potential and inflation terminates as in a hybrid model. We find parameter choices that reproduce observed features of the cosmic microwave background, and discuss our model in light of recent results from the BICEP2 and Planck experiments.

  18. Hybridization of mouse lemurs: different patterns under different ecological conditions

    Directory of Open Access Journals (Sweden)

    Rosenkranz David

    2011-10-01

    Full Text Available Abstract Background Several mechanistic models aim to explain the diversification of the multitude of endemic species on Madagascar. The island's biogeographic history probably offered numerous opportunities for secondary contact and subsequent hybridization. Existing diversification models do not consider a possible role of these processes. One key question for a better understanding of their potential importance is how they are influenced by different environmental settings. Here, we characterized a contact zone between two species of mouse lemurs, Microcebus griseorufus and M. murinus, in dry spiny bush and mesic gallery forest that border each other sharply without intermediate habitats between them. We performed population genetic analyses based on mtDNA sequences and nine nuclear microsatellites and compared the results to a known hybrid zone of the same species in a nearby wide gradient from dry spiny bush over transitional forest to humid littoral forest. Results In the spiny-gallery system, Microcebus griseorufus is restricted to the spiny bush; Microcebus murinus occurs in gallery forest and locally invades the dryer habitat of its congener. We found evidence for bidirectional introgressive hybridization, which is closely linked to increased spatial overlap within the spiny bush. Within 159 individuals, we observed 18 hybrids with mitochondrial haplotypes of both species. Analyses of simulated microsatellite data indicate that we identified hybrids with great accuracy and that we probably underestimated their true number. We discuss short-term climatic fluctuations as potential trigger for the dynamic of invasion and subsequent hybridization. In the gradient hybrid zone in turn, long-term aridification could have favored unidirectional nuclear introgression from Microcebus griseorufus into M. murinus in transitional forest. Conclusions Madagascar's southeastern transitional zone harbors two very different hybrid zones of mouse lemurs

  19. The new era of cardiac surgery: hybrid therapy for cardiovascular disease.

    Science.gov (United States)

    Solenkova, Natalia V; Umakanthan, Ramanan; Leacche, Marzia; Zhao, David X; Byrne, John G

    2010-11-01

    Surgical therapy for cardiovascular disease carries excellent long-term outcomes but it is relatively invasive. With the development of new devices and techniques, modern cardiovascular surgery is trending toward less invasive approaches, especially for patients at high risk for traditional open heart surgery. A hybrid strategy combines traditional surgical treatments performed in the operating room with treatments traditionally available only in the catheterization laboratory with the goal of offering patients the best available therapy for any set of cardiovascular diseases. Examples of hybrid procedures include hybrid coronary artery bypass grafting, hybrid valve surgery and percutaneous coronary intervention, hybrid endocardial and epicardial atrial fibrillation procedures, and hybrid coronary artery bypass grafting/carotid artery stenting. This multidisciplinary approach requires strong collaboration between cardiac surgeons, vascular surgeons, and interventional cardiologists to obtain optimal patient outcomes.

  20. Hybrid Psychology: The marriage of discourse analysis with neuroscience

    Directory of Open Access Journals (Sweden)

    Rom Harré

    2010-07-01

    Full Text Available As the 21st Century opened the controversial and unstable discipline of `academic psychology’ seemed to separating into two radically distinct and perhaps irreconcilable domains. Discursive psychology focused on the management of meaning in a world of norms while Neuropsychology focused on the investigation of brain and cognitive processes. These two domains can be reconciled in a hybrid science that brings them together into a synthesis more powerful than anything psychologists have achieved before. In this paper means Hybrid psychology depends on the intuition that while brains can be assimilated into the world of persons, people cannot be assimilated into the world of cell structures and molecular processes. The project of setting up a hybrid science, in which the symbol using capacities of human beings are brought into a unified scheme with the organic aspects of members of the species homo sapiens, demands the dissolution of the mind-body problem, somehow setting it aside as an illusion, based on a mistaken presupposition.

  1. 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

  2. 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.

  3. New MPPT algorithm for PV applications based on hybrid dynamical approach

    KAUST Repository

    Elmetennani, Shahrazed

    2016-10-24

    This paper proposes a new Maximum Power Point Tracking (MPPT) algorithm for photovoltaic applications using the multicellular converter as a stage of power adaptation. The proposed MPPT technique has been designed using a hybrid dynamical approach to model the photovoltaic generator. The hybrid dynamical theory has been applied taking advantage of the particular topology of the multicellular converter. Then, a hybrid automata has been established to optimize the power production. The maximization of the produced solar energy is achieved by switching between the different operative modes of the hybrid automata, which is conditioned by some invariance and transition conditions. These conditions have been validated by simulation tests under different conditions of temperature and irradiance. Moreover, the performance of the proposed algorithm has been then evaluated by comparison with standard MPPT techniques numerically and by experimental tests under varying external working conditions. The results have shown the interesting features that the hybrid MPPT technique presents in terms of performance and simplicity for real time implementation.

  4. New MPPT algorithm for PV applications based on hybrid dynamical approach

    KAUST Repository

    Elmetennani, Shahrazed; Laleg-Kirati, Taous-Meriem; Djemai, M.; Tadjine, M.

    2016-01-01

    This paper proposes a new Maximum Power Point Tracking (MPPT) algorithm for photovoltaic applications using the multicellular converter as a stage of power adaptation. The proposed MPPT technique has been designed using a hybrid dynamical approach to model the photovoltaic generator. The hybrid dynamical theory has been applied taking advantage of the particular topology of the multicellular converter. Then, a hybrid automata has been established to optimize the power production. The maximization of the produced solar energy is achieved by switching between the different operative modes of the hybrid automata, which is conditioned by some invariance and transition conditions. These conditions have been validated by simulation tests under different conditions of temperature and irradiance. Moreover, the performance of the proposed algorithm has been then evaluated by comparison with standard MPPT techniques numerically and by experimental tests under varying external working conditions. The results have shown the interesting features that the hybrid MPPT technique presents in terms of performance and simplicity for real time implementation.

  5. 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.

  6. 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

  7. 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.

  8. The role of object categories in hybrid visual and memory search.

    Science.gov (United States)

    Cunningham, Corbin A; Wolfe, Jeremy M

    2014-08-01

    In hybrid search, observers search for any of several possible targets in a visual display containing distracting items and, perhaps, a target. Wolfe (2012) found that response times (RTs) in such tasks increased linearly with increases in the number of items in the display. However, RT increased linearly with the log of the number of items in the memory set. In earlier work, all items in the memory set were unique instances (e.g., this apple in this pose). Typical real-world tasks involve more broadly defined sets of stimuli (e.g., any "apple" or, perhaps, "fruit"). The present experiments show how sets or categories of targets are handled in joint visual and memory search. In Experiment 1, searching for a digit among letters was not like searching for targets from a 10-item memory set, though searching for targets from an N-item memory set of arbitrary alphanumeric characters was like searching for targets from an N-item memory set of arbitrary objects. In Experiment 2, observers searched for any instance of N sets or categories held in memory. This hybrid search was harder than search for specific objects. However, memory search remained logarithmic. Experiment 3 illustrates the interaction of visual guidance and memory search when a subset of visual stimuli are drawn from a target category. Furthermore, we outline a conceptual model, supported by our results, defining the core components that would be necessary to support such categorical hybrid searches. PsycINFO Database Record (c) 2014 APA, all rights reserved.

  9. Analysis on a hybrid desiccant air-conditioning system

    International Nuclear Information System (INIS)

    Jia, C.X.; Dai, Y.J.; Wu, J.Y.; Wang, R.Z.

    2006-01-01

    Hybrid desiccant-assisted preconditioner and split cooling coil system, which combines the merits of moisture removal by desiccant and cooling coil for sensible heat removal, is a potential alternative to conventional vapor compression cooling systems. In this paper, experiments on a hybrid desiccant air-conditioning system, which is actually an integration of a rotary solid desiccant dehumidification and a vapor compression air-conditioning unit, had been carried out. It is found that, compared with the conventional VC (vapor compression) system, the hybrid desiccant cooling system economizes 37.5% electricity powers when the process air temperature and relative humidity are maintained at 30 o C, and 55% respectively. The reason why the hybrid desiccant cooling system features better performance relative to the VC system lies in the improvement brought about in the performance of the evaporator in VC unit due to desiccant dehumidification. A thermodynamic model of the hybrid desiccant system with R-22 as the refrigerant has been developed and the impact of operating parameters on the sensible heat ratio of the evaporator and the electric power saving rate has been analyzed. It is found that a majority of evaporators can operate in the dry condition even if the regeneration temperature is lower (i.e. 80 o C)

  10. Optimal Control of Hybrid Systems in Air Traffic Applications

    Science.gov (United States)

    Kamgarpour, Maryam

    Growing concerns over the scalability of air traffic operations, air transportation fuel emissions and prices, as well as the advent of communication and sensing technologies motivate improvements to the air traffic management system. To address such improvements, in this thesis a hybrid dynamical model as an abstraction of the air traffic system is considered. Wind and hazardous weather impacts are included using a stochastic model. This thesis focuses on the design of algorithms for verification and control of hybrid and stochastic dynamical systems and the application of these algorithms to air traffic management problems. In the deterministic setting, a numerically efficient algorithm for optimal control of hybrid systems is proposed based on extensions of classical optimal control techniques. This algorithm is applied to optimize the trajectory of an Airbus 320 aircraft in the presence of wind and storms. In the stochastic setting, the verification problem of reaching a target set while avoiding obstacles (reach-avoid) is formulated as a two-player game to account for external agents' influence on system dynamics. The solution approach is applied to air traffic conflict prediction in the presence of stochastic wind. Due to the uncertainty in forecasts of the hazardous weather, and hence the unsafe regions of airspace for aircraft flight, the reach-avoid framework is extended to account for stochastic target and safe sets. This methodology is used to maximize the probability of the safety of aircraft paths through hazardous weather. Finally, the problem of modeling and optimization of arrival air traffic and runway configuration in dense airspace subject to stochastic weather data is addressed. This problem is formulated as a hybrid optimal control problem and is solved with a hierarchical approach that decouples safety and performance. As illustrated with this problem, the large scale of air traffic operations motivates future work on the efficient

  11. Affordable and accurate large-scale hybrid-functional calculations on GPU-accelerated supercomputers

    Science.gov (United States)

    Ratcliff, Laura E.; Degomme, A.; Flores-Livas, José A.; Goedecker, Stefan; Genovese, Luigi

    2018-03-01

    Performing high accuracy hybrid functional calculations for condensed matter systems containing a large number of atoms is at present computationally very demanding or even out of reach if high quality basis sets are used. We present a highly optimized multiple graphics processing unit implementation of the exact exchange operator which allows one to perform fast hybrid functional density-functional theory (DFT) calculations with systematic basis sets without additional approximations for up to a thousand atoms. With this method hybrid DFT calculations of high quality become accessible on state-of-the-art supercomputers within a time-to-solution that is of the same order of magnitude as traditional semilocal-GGA functionals. The method is implemented in a portable open-source library.

  12. 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

  13. 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

  14. 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.

  15. 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.

  16. 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.

  17. Absorption properties of metal-semiconductor hybrid nanoparticles.

    Science.gov (United States)

    Shaviv, Ehud; Schubert, Olaf; Alves-Santos, Marcelo; Goldoni, Guido; Di Felice, Rosa; Vallée, Fabrice; Del Fatti, Natalia; Banin, Uri; Sönnichsen, Carsten

    2011-06-28

    The optical response of hybrid metal-semiconductor nanoparticles exhibits different behaviors due to the proximity between the disparate materials. For some hybrid systems, such as CdS-Au matchstick-shaped hybrids, the particles essentially retain the optical properties of their original components, with minor changes. Other systems, such as CdSe-Au dumbbell-shaped nanoparticles, exhibit significant change in the optical properties due to strong coupling between the two materials. Here, we study the absorption of these hybrids by comparing experimental results with simulations using the discrete dipole approximation method (DDA) employing dielectric functions of the bare components as inputs. For CdS-Au nanoparticles, the DDA simulation provides insights on the gold tip shape and its interface with the semiconductor, information that is difficult to acquire by experimental means alone. Furthermore, the qualitative agreement between DDA simulations and experimental data for CdS-Au implies that most effects influencing the absorption of this hybrid system are well described by local dielectric functions obtained separately for bare gold and CdS nanoparticles. For dumbbell shaped CdSe-Au, we find a shortcoming of the electrodynamic model, as it does not predict the "washing out" of the optical features of the semiconductor and the metal observed experimentally. The difference between experiment and theory is ascribed to strong interaction of the metal and semiconductor excitations, which spectrally overlap in the CdSe case. The present study exemplifies the employment of theoretical approaches used to describe the optical properties of semiconductors and metal nanoparticles, to achieve better understanding of the behavior of metal-semiconductor hybrid nanoparticles.

  18. 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.

  19. MetaFIND: A feature analysis tool for metabolomics data

    Directory of Open Access Journals (Sweden)

    Cunningham Pádraig

    2008-11-01

    Full Text Available Abstract Background Metabolomics, or metabonomics, refers to the quantitative analysis of all metabolites present within a biological sample and is generally carried out using NMR spectroscopy or Mass Spectrometry. Such analysis produces a set of peaks, or features, indicative of the metabolic composition of the sample and may be used as a basis for sample classification. Feature selection may be employed to improve classification accuracy or aid model explanation by establishing a subset of class discriminating features. Factors such as experimental noise, choice of technique and threshold selection may adversely affect the set of selected features retrieved. Furthermore, the high dimensionality and multi-collinearity inherent within metabolomics data may exacerbate discrepancies between the set of features retrieved and those required to provide a complete explanation of metabolite signatures. Given these issues, the latter in particular, we present the MetaFIND application for 'post-feature selection' correlation analysis of metabolomics data. Results In our evaluation we show how MetaFIND may be used to elucidate metabolite signatures from the set of features selected by diverse techniques over two metabolomics datasets. Importantly, we also show how MetaFIND may augment standard feature selection and aid the discovery of additional significant features, including those which represent novel class discriminating metabolites. MetaFIND also supports the discovery of higher level metabolite correlations. Conclusion Standard feature selection techniques may fail to capture the full set of relevant features in the case of high dimensional, multi-collinear metabolomics data. We show that the MetaFIND 'post-feature selection' analysis tool may aid metabolite signature elucidation, feature discovery and inference of metabolic correlations.

  20. 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.

  1. General motors front wheel drive 2-mode hybrid transmission

    Energy Technology Data Exchange (ETDEWEB)

    Hendrickson, James [General Motors Corp., Pontiac, MI (United States). New Transmission Products Group.; Holmes, Alan G. [General Motors Corp., Pontiac, MI (United States). Powertrain Hybrid Architecture

    2009-07-01

    General Motors now expands the application of two-mode hybrid technology to front wheel drive vehicles with the development of a hybrid electric transmission packaged into essentially the same space as a conventional automatic transmission for front wheel drive. This was accomplished using a space-efficient arrangement based on two planetary gear sets and electric motor-generators with large internal diameters. A combination of damper and hydraulically-controlled clutch allow comfortable shutdown and restarting of large-displacement engines in front wheel drive vehicles. The hybrid system delivers electric low-speed urban driving, two continuously variable ranges of transmission speed ratios, four fixed transmission speed ratios, electric acceleration boosting, and regenerative braking. In the first vehicle application, the two-mode hybrid helps to reduce vehicle fuel consumption by approximately one-third. (orig.)

  2. 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...

  3. 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

  4. Hybrid viscous damper with filtered integral force feedback control

    DEFF Research Database (Denmark)

    Høgsberg, Jan; Brodersen, Mark L.

    2016-01-01

    In hybrid damper systems active control devices are usually introduced to enhance the performance of otherwise passive dampers. In the present paper a hybrid damper concept is comprised of a passive viscous damper placed in series with an active actuator and a force sensor. The actuator motion...... is controlled by a filtered integral force feedback strategy, where the main feature is the filter, which is designed to render a damper force that in a phase-plane representation operates in front of the corresponding damper velocity. It is demonstrated that in the specific parameter regime where the damper...

  5. 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.

  6. Energy metrics analysis of hybrid - photovoltaic (PV) modules

    Energy Technology Data Exchange (ETDEWEB)

    Tiwari, Arvind [Department of Electronics and Communication, Krishna Institute of Engineering and Technology, 13 k.m. stone, Ghaziabad - Meerut Road, Ghaziabad 201 206, UP (India); Barnwal, P.; Sandhu, G.S.; Sodha, M.S. [Centre for Energy Studies, Indian Institute of Technology Delhi, Hauz Khas, New Delhi 110 016 (India)

    2009-12-15

    In this paper, energy metrics (energy pay back time, electricity production factor and life cycle conversion efficiency) of hybrid photovoltaic (PV) modules have been analyzed and presented for the composite climate of New Delhi, India. For this purpose, it is necessary to calculate (1) the energy consumption in making different components of the PV modules and (2) the annual energy (electrical and thermal) available from the hybrid-PV modules. A set of mathematical relations have been reformulated for computation of the energy metrics. The manufacturing energy, material production energy, energy use and distribution energy of the system have been taken into account, to determine the embodied energy for the hybrid-PV modules. The embodied energy and annual energy outputs have been used for evaluation of the energy metrics. For hybrid PV module, it has been observed that the EPBT gets significantly reduced by taking into account the increase in annual energy availability of the thermal energy in addition to the electrical energy. The values of EPF and LCCE of hybrid PV module become higher as expected. (author)

  7. ASDC Advances in the Utilization of Microservices and Hybrid Cloud Environments

    Science.gov (United States)

    Baskin, W. E.; Herbert, A.; Mazaika, A.; Walter, J.

    2017-12-01

    The Atmospheric Science Data Center (ASDC) is transitioning many of its software tools and applications to standalone microservices deployable in a hybrid cloud, offering benefits such as scalability and efficient environment management. This presentation features several projects the ASDC staff have implemented leveraging the OpenShift Container Application Platform and OpenStack Hybrid Cloud Environment focusing on key tools and techniques applied to: Earth Science data processing Spatial-Temporal metadata generation, validation, repair, and curation Archived Data discovery, visualization, and access

  8. 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...

  9. 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

  10. 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

  11. Denoising GPS-Based Structure Monitoring Data Using Hybrid EMD and Wavelet Packet

    Directory of Open Access Journals (Sweden)

    Lu Ke

    2017-01-01

    Full Text Available High-frequency components are often discarded for data denoising when applying pure wavelet multiscale or empirical mode decomposition (EMD based approaches. Instead, they may raise the problem of energy leakage in vibration signals. Hybrid EMD and wavelet packet (EMD-WP is proposed to denoise Global Positioning System- (GPS- based structure monitoring data. First, field observables are decomposed into a collection of intrinsic mode functions (IMFs with different characteristics. Second, high-frequency IMFs are denoised using the wavelet packet; then the monitoring data are reconstructed using the denoised IMFs together with the remaining low-frequency IMFs. Our algorithm is demonstrated on a synthetic displacement response of a 3-story frame excited by El Centro earthquake along with a set of Gaussian random white noises on different levels added. We find that the hybrid method can effectively weaken the multipath effect with low frequency and can potentially extract vibration feature. However, false modals may still exist by the rest of the noise contained in the high-frequency IMFs and when the frequency of the noise is located in the same band as that of effective vibration. Finally, real GPS observables are implemented to evaluate the efficiency of EMD-WP method in mitigating low-frequency multipath.

  12. 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

  13. 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

  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. Prostate cancer multi-feature analysis using trans-rectal ultrasound images

    International Nuclear Information System (INIS)

    Mohamed, S S; Salama, M M A; Kamel, M; El-Saadany, E F; Rizkalla, K; Chin, J

    2005-01-01

    This note focuses on extracting and analysing prostate texture features from trans-rectal ultrasound (TRUS) images for tissue characterization. One of the principal contributions of this investigation is the use of the information of the images' frequency domain features and spatial domain features to attain a more accurate diagnosis. Each image is divided into regions of interest (ROIs) by the Gabor multi-resolution analysis, a crucial stage, in which segmentation is achieved according to the frequency response of the image pixels. The pixels with a similar response to the same filter are grouped to form one ROI. Next, from each ROI two different statistical feature sets are constructed; the first set includes four grey level dependence matrix (GLDM) features and the second set consists of five grey level difference vector (GLDV) features. These constructed feature sets are then ranked by the mutual information feature selection (MIFS) algorithm. Here, the features that provide the maximum mutual information of each feature and class (cancerous and non-cancerous) and the minimum mutual information of the selected features are chosen, yeilding a reduced feature subset. The two constructed feature sets, GLDM and GLDV, as well as the reduced feature subset, are examined in terms of three different classifiers: the condensed k-nearest neighbour (CNN), the decision tree (DT) and the support vector machine (SVM). The accuracy classification results range from 87.5% to 93.75%, where the performance of the SVM and that of the DT are significantly better than the performance of the CNN. (note)

  16. How to simultaneously achieve low emissions and high efficiency in a hybrid powertrain

    NARCIS (Netherlands)

    Mourad, S.; Eijnden, E. van den; Foster, D.L.; Helden, M. van; Rondel, M.; Schmal, P.

    2001-01-01

    In order to investigate the possibilities of hybrid driveline architecture and to provide a platform for further technical developments, TNO has designed and prototyped a test platform for a series hybrid powertrain, including a compact, highly advanced generator set. This powertrain is subjected to

  17. 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 ...

  18. Hybrid system by Mercedes-Benz for the M-class; Hybridsystem fuer die M-Klasse von Mercedes-Benz

    Energy Technology Data Exchange (ETDEWEB)

    Weiss, Michael; Ruhl, Thomas [Daimler AG, Sindelfingen (Germany). M-Klasse Hybrid; Armstrong, Neil; Nietfeld, Franz [Daimler AG, Troy, MI (United States); Schenk, Juergen [Daimler AG, Sindelfingen (Germany). Elektrofahrzeuge; Lueckert, Peter [Daimler AG, Stuttgart (Germany). Ottomotoren; Goedecke, Tobias [Daimler AG, Stuttgart (Germany). Abt. Transmission Development AHS

    2009-09-15

    The ML 450 Hybrid is the first Mercedes-Benz full hybrid vehicle, promising significant fuel consumption and emission reductions while retaining superb driving characteristics. The main feature of the 'AHS-C two-mode hybrid system', used here for the first time, is its great efficiency both in inner city 'stop and go- traffic and on fast long-distance journeys at increasing engine loads and higher speed ranges. The ML 450 Hybrid is, therefore, a central element of the Mercedes-Benz strategy for achieving sustainable mobility. (orig.)

  19. A direct hybrid S{sub N} method for slab-geometry lattice calculations

    Energy Technology Data Exchange (ETDEWEB)

    Silva, Davi J.M.; Barros, Ricardo C., E-mail: rcbarros@pq.cnpq.b [Universidade do Estado do Rio de Janeiro (IPRJ/UERJ), Nova Friburgo, RJ (Brazil). Programa de Pos-graduacao em Modelagem Computacional; Zani, Jose H. [Fundacao Educacional Serra dos Orgaos, Teresopolis, RJ (Brazil). Ciencia da Computacao

    2011-07-01

    In this work we describe a hybrid direct method for calculating the thermal disadvantage factor and the neutron flux distribution in fuel-moderator lattices. For the mathematical model, we use the one-speed slab-geometry discrete ordinates (S{sub N}) transport equation with linearly anisotropic scattering. The basic idea is to use higher order angular quadrature set in the highly absorbing fuel region (S{sub NF}) and lower order angular quadrature set in the diffusive moderator region (S{sub NM}) , i.e., N{sub F} > N{sub M}. We apply special continuity conditions based on the equivalence of the S{sub N} and P{sub N-1} equations, which characterize the hybrid model. Numerical results to a typical model problem are given to illustrate the accuracy and the efficiency of the offered hybrid method. (author)

  20. Nano-Structured Bio-Inorganic Hybrid Material for High Performing Oxygen Reduction Catalyst.

    Science.gov (United States)

    Jiang, Rongzhong; Tran, Dat T; McClure, Joshua P; Chu, Deryn

    2015-08-26

    In this study, we demonstrate a non-Pt nanostructured bioinorganic hybrid (BIH) catalyst for catalytic oxygen reduction in alkaline media. This catalyst was synthesized through biomaterial hemin, nanostructured Ag-Co alloy, and graphene nano platelets (GNP) by heat-treatment and ultrasonically processing. This hybrid catalyst has the advantages of the combined features of these bio and inorganic materials. A 10-fold improvement in catalytic activity (at 0.8 V vs RHE) is achieved in comparison of pure Ag nanoparticles (20-40 nm). The hybrid catalyst reaches 80% activity (at 0.8 V vs RHE) of the state-of-the-art catalyst (containing 40% Pt and 60% active carbon). Comparable catalytic stability for the hybrid catalyst with the Pt catalyst is observed by chronoamperometric experiment. The hybrid catalyst catalyzes 4-electron oxygen reduction to produce water with fast kinetic rate. The rate constant obtained from the hybrid catalyst (at 0.6 V vs RHE) is 4 times higher than that of pure Ag/GNP catalyst. A catalytic model is proposed to explain the oxygen reduction reaction at the BIH catalyst.

  1. Hybrid photovoltaic–thermal solar collectors dynamic modeling

    International Nuclear Information System (INIS)

    Amrizal, N.; Chemisana, D.; Rosell, J.I.

    2013-01-01

    Highlights: ► A hybrid photovoltaic/thermal dynamic model is presented. ► The model, once calibrated, can predict the power output for any set of climate data. ► The physical electrical model includes explicitly thermal and irradiance dependences. ► The results agree with those obtained through steady-state characterization. ► The model approaches the junction cell temperature through the system energy balance. -- Abstract: A hybrid photovoltaic/thermal transient model has been developed and validated experimentally. The methodology extends the quasi-dynamic thermal model stated in the EN 12975 in order to involve the electrical performance and consider the dynamic behavior minimizing constraints when characterizing the collector. A backward moving average filtering procedure has been applied to improve the model response for variable working conditions. Concerning the electrical part, the model includes the thermal and radiation dependences in its variables. The results revealed that the characteristic parameters included in the model agree reasonably well with the experimental values obtained from the standard steady-state and IV characteristic curve measurements. After a calibration process, the model is a suitable tool to predict the thermal and electrical performance of a hybrid solar collector, for a specific weather data set.

  2. 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.

  3. 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.

  4. Feature Selection Methods for Zero-Shot Learning of Neural Activity

    Directory of Open Access Journals (Sweden)

    Carlos A. Caceres

    2017-06-01

    Full Text Available Dimensionality poses a serious challenge when making predictions from human neuroimaging data. Across imaging modalities, large pools of potential neural features (e.g., responses from particular voxels, electrodes, and temporal windows have to be related to typically limited sets of stimuli and samples. In recent years, zero-shot prediction models have been introduced for mapping between neural signals and semantic attributes, which allows for classification of stimulus classes not explicitly included in the training set. While choices about feature selection can have a substantial impact when closed-set accuracy, open-set robustness, and runtime are competing design objectives, no systematic study of feature selection for these models has been reported. Instead, a relatively straightforward feature stability approach has been adopted and successfully applied across models and imaging modalities. To characterize the tradeoffs in feature selection for zero-shot learning, we compared correlation-based stability to several other feature selection techniques on comparable data sets from two distinct imaging modalities: functional Magnetic Resonance Imaging and Electrocorticography. While most of the feature selection methods resulted in similar zero-shot prediction accuracies and spatial/spectral patterns of selected features, there was one exception; A novel feature/attribute correlation approach was able to achieve those accuracies with far fewer features, suggesting the potential for simpler prediction models that yield high zero-shot classification accuracy.

  5. Hybrid real-code ant colony optimisation for constrained mechanical design

    Science.gov (United States)

    Pholdee, Nantiwat; Bureerat, Sujin

    2016-01-01

    This paper proposes a hybrid meta-heuristic based on integrating a local search simplex downhill (SDH) method into the search procedure of real-code ant colony optimisation (ACOR). This hybridisation leads to five hybrid algorithms where a Monte Carlo technique, a Latin hypercube sampling technique (LHS) and a translational propagation Latin hypercube design (TPLHD) algorithm are used to generate an initial population. Also, two numerical schemes for selecting an initial simplex are investigated. The original ACOR and its hybrid versions along with a variety of established meta-heuristics are implemented to solve 17 constrained test problems where a fuzzy set theory penalty function technique is used to handle design constraints. The comparative results show that the hybrid algorithms are the top performers. Using the TPLHD technique gives better results than the other sampling techniques. The hybrid optimisers are a powerful design tool for constrained mechanical design problems.

  6. Model Predictive Control for Connected Hybrid Electric Vehicles

    Directory of Open Access Journals (Sweden)

    Kaijiang Yu

    2015-01-01

    Full Text Available This paper presents a new model predictive control system for connected hybrid electric vehicles to improve fuel economy. The new features of this study are as follows. First, the battery charge and discharge profile and the driving velocity profile are simultaneously optimized. One is energy management for HEV for Pbatt; the other is for the energy consumption minimizing problem of acc control of two vehicles. Second, a system for connected hybrid electric vehicles has been developed considering varying drag coefficients and the road gradients. Third, the fuel model of a typical hybrid electric vehicle is developed using the maps of the engine efficiency characteristics. Fourth, simulations and analysis (under different parameters, i.e., road conditions, vehicle state of charge, etc. are conducted to verify the effectiveness of the method to achieve higher fuel efficiency. The model predictive control problem is solved using numerical computation method: continuation and generalized minimum residual method. Computer simulation results reveal improvements in fuel economy using the proposed control method.

  7. 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)...

  8. PV-Diesel Hybrid SCADA Experiment Network Design

    Science.gov (United States)

    Kalu, Alex; Durand, S.; Emrich, Carol; Ventre, G.; Wilson, W.; Acosta, R.

    1999-01-01

    The essential features of an experimental network for renewable power system satellite based supervisory, control and data acquisition (SCADA) are communication links, controllers, diagnostic equipment and a hybrid power system. Required components for implementing the network consist of two satellite ground stations, to satellite modems, two 486 PCs, two telephone receivers, two telephone modems, two analog telephone lines, one digital telephone line, a hybrid-power system equipped with controller and a satellite spacecraft. In the technology verification experiment (TVE) conducted by Savannah State University and Florida Solar Energy Center, the renewable energy hybrid system is the Apex-1000 Mini-Hybrid which is equipped with NGC3188 for user interface and remote control and the NGC2010 for monitoring and basic control tasks. This power system is connected to a satellite modem via a smart interface, RS232. Commands are sent to the power system control unit through a control PC designed as PC1. PC1 is thus connected to a satellite model through RS232. A second PC, designated PC2, the diagnostic PC is connected to both satellite modems via separate analog telephone lines for checking modems'health. PC2 is also connected to PC1 via a telephone line. Due to the unavailability of a second ground station for the ACTS, one ground station is used to serve both the sending and receiving functions in this experiment. Signal is sent from the control PC to the Hybrid system at a frequency f(sub 1), different from f(sub 2), the signal from the hybrid system to the control PC. f(sub l) and f(sub 2) are sufficiently separated to avoid interference.

  9. 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.

  10. 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.

  11. 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

  12. Outage Performance of Hybrid FSO/RF System with Low-Complexity Power Adaptation

    KAUST Repository

    Rakia, Tamer

    2016-02-26

    Hybrid free-space optical (FSO) / radio-frequency (RF) systems have emerged as a promising solution for high data- rate wireless communication systems. We consider truncated channel inversion based power adaptation strategy for coherent and non- coherent hybrid FSO/RF systems, employing an adaptive combining scheme. Specifically, we activate the RF link along with the FSO link when FSO link quality is unacceptable, and adaptively set RF transmission power to ensure constant combined signal-to-noise ratio at receiver terminal. Analytical expressions for the outage probability of the hybrid system with and without power adaptation are derived. Numerical examples show that, the hybrid FSO/RF systems with power adaptation achieve considerable outage performance improvement over conventional hybrid FSO/RF systems without power adaptation. © 2015 IEEE.

  13. Demand response impacts on off-grid hybrid photovoltaic-diesel generator microgrids

    Directory of Open Access Journals (Sweden)

    Aaron St. Leger

    2015-08-01

    Full Text Available Hybrid microgrids consisting of diesel generator set(s and converter based power sources, such as solar photovoltaic or wind sources, offer an alternative to generator based off-grid power systems. The hybrid approach has been shown to be economical in many off-grid applications and can result in reduced generator operation, fuel requirements, and maintenance. However, the intermittent nature of demand and renewable energy sources typically require energy storage, such as batteries, to properly operate the hybrid microgrid. These batteries increase the system cost, require proper operation and maintenance, and have been shown to be unreliable in case studies on hybrid microgrids. This work examines the impacts of leveraging demand response in a hybrid microgrid in lieu of energy storage. The study is performed by simulating two different hybrid diesel generator—PV microgrid topologies, one with a single diesel generator and one with multiple paralleled diesel generators, for a small residential neighborhood with varying levels of demand response. Various system designs are considered and the optimal design, based on cost of energy, is presented for each level of demand response. The solar resources, performance of solar PV source, performance of diesel generators, costs of system components, maintenance, and operation are modeled and simulated at a time interval of ten minutes over a twenty-five year period for both microgrid topologies. Results are quantified through cost of energy, diesel fuel requirements, and utilization of the energy sources under varying levels of demand response. The results indicate that a moderate level of demand response can have significant positive impacts to the operation of hybrid microgrids through reduced energy cost, fuel consumption, and increased utilization of PV sources.

  14. 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

  15. Flavorful hybrid anomaly-gravity mediation

    International Nuclear Information System (INIS)

    Gross, Christian; Hiller, Gudrun

    2011-01-01

    We consider supersymmetric models where anomaly and gravity mediation give comparable contributions to the soft terms and discuss how this can be realized in a five-dimensional brane world. The gaugino mass pattern of anomaly mediation is preserved in such a hybrid setup. The flavorful gravity-mediated contribution cures the tachyonic slepton problem of anomaly mediation. The supersymmetric flavor puzzle is solved by alignment. We explicitly show how a working flavor-tachyon link can be realized with Abelian flavor symmetries and give the characteristic signatures of the framework, including O(1) slepton mass splittings between different generations and between doublets and singlets. This provides opportunities for same flavor dilepton edge measurements with missing energy at the Large Hadron Collider (LHC). Rare lepton decay rates could be close to their current experimental limit. Compared to pure gravity mediation, the hybrid model is advantageous because it features a heavy gravitino which can avoid the cosmological gravitino problem of gravity-mediated models combined with leptogenesis.

  16. Hybrid mesons (Q anti Qg) in N anti N annihilation

    International Nuclear Information System (INIS)

    Dover, C.B.; Gutsche, T.; Faessler, A.

    1993-09-01

    N anti N annihilation reactions provide exciting possibilities to study mesonic resonances beyond the usual Q anti Q spectrum. Particularly the search for Q anti Qg mesons containing an explicit dynamical excitation of the gluon field is not promising, since hybrids are predicted to display unique features: exotic quantum numbers (J πC ) and dynamical selection rules for their decay modes. The authors have investigated the possibility of producing hybrids from p anti p atomic states in reactions of the type N anti N(L= 0,1) → π + Q anti Qg. Production rates for hybrid mesons are found to display a strong dependence on the quantum numbers and kinematical factors associated with the transition. The dependence on the orbital angular momentum L of the p anti p atomic state, accessible in p anti p annihilation at rest, would provide a striking signature for the production of hybrids. In estimating branching ratios for the formation of Q anti Qg hybrid mesons in N anti N annihilation reactions at rest, the authors have employed a microscopic model with constituent quarks and gluons in analogy to the annihilation model for the production of Q anti Q mesons

  17. Proteomic Analysis of Pachytene Spermatocytes of Sterile Hybrid Male Mice.

    Science.gov (United States)

    Wang, Lu; Guo, Yueshuai; Liu, Wenjing; Zhao, Weidong; Song, Gendi; Zhou, Tao; Huang, Hefeng; Guo, Xuejiang; Sun, Fei

    2016-09-01

    Incompatibilities in interspecific hybrids, such as reduced hybrid fertility and lethality, are common features resulting from reproductive isolation that lead to speciation. Subspecies crosses of house mice produce offspring in which one sex is infertile or absent, yet the molecular mechanisms of hybrid sterility are poorly understood. In this study, we observed extensive asynapsis of chromosomes and disturbance of the sex body in pachytene spermatocytes of sterile F1 males (PWK/Ph female × C57BL/6J male). We report the high-confidence identification of 4005 proteins in the pachytene spermatocytes of fertile F1 males (PWK/Ph male × C57BL/6J female) and sterile F1 males (PWK/Ph female × C57BL/6J male), of which 215 were upregulated and 381 were downregulated. Bioinformatics analysis of the proteome led to the identification of 43 and 59 proteins known to be essential for male meiosis and spermatogenesis in mice, respectively. Characterization of the proteome of pachytene spermatocytes associated with hybrid male sterility provides an inventory of proteins that is useful for understanding meiosis and the mechanisms of hybrid male infertility. © 2016 by the Society for the Study of Reproduction, Inc.

  18. Feature Scaling via Second-Order Cone Programming

    Directory of Open Access Journals (Sweden)

    Zhizheng Liang

    2016-01-01

    Full Text Available Feature scaling has attracted considerable attention during the past several decades because of its important role in feature selection. In this paper, a novel algorithm for learning scaling factors of features is proposed. It first assigns a nonnegative scaling factor to each feature of data and then adopts a generalized performance measure to learn the optimal scaling factors. It is of interest to note that the proposed model can be transformed into a convex optimization problem: second-order cone programming (SOCP. Thus the scaling factors of features in our method are globally optimal in some sense. Several experiments on simulated data, UCI data sets, and the gene data set are conducted to demonstrate that the proposed method is more effective than previous methods.

  19. Intragenus (Campylomormyrus) and intergenus hybrids in mormyrid fish: Physiological and histological investigations of the electric organ ontogeny.

    Science.gov (United States)

    Kirschbaum, Frank; Nguyen, Linh; Baumgartner, Stephanie; Chi, Hiu Wan Linda; Wolfart, Rene; Elarbani, Khouloud; Eppenstein, Hari; Korniienko, Yevheniia; Guido-Böhm, Lilian; Mamonekene, Victor; Vater, Marianne; Tiedemann, Ralph

    2016-10-01

    African weakly electric mormyrid fish show a high diversity of their electric organ discharge (EOD) both across and within genera. Thanks to a recently developed technique of artificial reproduction in mormyrid fish, we were able to perform hybridizations between different genera and within one genus (Campylomormyrus). The hybrids of intergenus hybridizations exhibited different degrees of reduced survival related to the phylogenetic distance of the parent species: hybrids of the crosses between C. rhynchophorus and its sister genus Gnathonemus survived and developed normally. Hybrids between C. rhynchophorus and a Mormyrus species (a more basal clade compared to Campylomormyrus s) survived up to 42days and developed many malformations, e.g., at the level of the unpaired fins. Hybrids between C. numenius and Hippopotamyrus pictus (a derived clade, only distantly related to Campylomormyrus) only survived for two days during embryological development. Eight different hybrid combinations among five Campylomormyrus species (C. tamandua, C. compressirostris, C. tshokwe, C. rhynchophorus, C. numenius) were performed. The aim of the hybridizations was to combine species with (1) either caudal or rostral position of the main stalk innervating the electrocytes in the electric organ and (2) short, median or long duration of their EOD. The hybrids, though they are still juveniles, show very interesting features concerning electrocyte geometry as well as EOD form and duration: the caudal position of the stalk is prevailing over the rostral position, and the penetration of the stalk is dominant over the non-penetrating feature (in the Campylomormyrus hybrids); in the hybrid between C. rhynchophorus and Gnathonemus petersii it is the opposite. When crossing species with long and short EODs, it is always the long duration EOD that is expressed in the hybrids. The F1-Hybrids of the cross C. tamandua×C. compressirostris are fertile: viable F2-fish could be obtained with artificial

  20. Physicochemical properties and biocompatibility of chitosan oligosaccharide/gelatin/calcium phosphate hybrid cements

    Energy Technology Data Exchange (ETDEWEB)

    Chiang, Ting-Yi [Department of Dental Laboratory Technology, Central Taiwan University of Science and Technology, Taichung 406, Taiwan (China); Ho, Chia-Che [Institute of Oral Biology and Biomaterials Science, Chung-Shan Medical University, Taichung 402, Taiwan (China); Chen, David Chan-Hen [Institute of Veterinary Microbiology, National Chung-Hsing University, Taichung 402, Taiwan (China); Lai, Meng-Heng [Institute of Oral Biology and Biomaterials Science, Chung-Shan Medical University, Taichung 402, Taiwan (China); Ding, Shinn-Jyh, E-mail: sjding@csmu.edu.tw [Institute of Oral Biology and Biomaterials Science, Chung-Shan Medical University, Taichung 402, Taiwan (China); Department of Dentistry, Chung-Shan Medical University Hospital, Taichung 402, Taiwan (China)

    2010-04-15

    A bone substitute material was developed consisting of a chitosan oligosaccharide (COS) solution in a liquid phase and gelatin (GLT) containing calcium phosphate powder in a solid phase. The physicochemical and biocompatible properties of the hybrid cements were evaluated. The addition of COS to cement did not affect the setting time or diametral tensile strength of the hybrid cements, whereas GLT significantly prolonged the setting time and decreased the strength slightly. The setting reaction was inhibited by the addition of GLT to the initial mixture, but not by COS. However, the presence of GLT appreciably improved the anti-washout properties of the hybrid cement compared with COS. COS may promote the cement's biocompatibility as an approximate twofold increase in cell proliferation for 10% COS-containing cements was observed on day 3 as compared with the controls. The combination of GLT and COS was chosen due to the benefits achieved from several synergistic effects and for their clinical applications. Cement with 5% GLT and 10% COS may be a better choice among cements in terms of anti-washout properties and biological activity.

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

    Science.gov (United States)

    Jiang, Zhenhua

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

  2. TNB Experience in Developing Solar Hybrid Station at RPS Kemar, Gerik, Perak Darul Ridzuan

    International Nuclear Information System (INIS)

    Aziz, K A; Shamsudin, K N

    2013-01-01

    This paper will discuss on TNB experience in developing Solar Hybrid Station at RPS Kemar, Gerik, Perak. TNB has been approached by KKLW to submit proposal to provide electricity in the rural area namely RPS Kemar. Looking at area and source available, Solar Hybrid System was the best method in order to provide electricity at this area. This area is far from national grid sources. Solar Hybrid System is the best method to produce electrical power using the renewable energy from Solar PV, Battery and Diesel Generator Set. Nowadays, price of petroleum is slightly high due to higher demand from industry. Solar energy is good alternative in this country to practice in order to reduce cost for produce of electrical energy. Generally, Solar will produce energy during daytime and when become cloudy and dark, automatically battery and diesel generator set will recover the system through the hybrid controller system.

  3. Feature selection gait-based gender classification under different circumstances

    Science.gov (United States)

    Sabir, Azhin; Al-Jawad, Naseer; Jassim, Sabah

    2014-05-01

    This paper proposes a gender classification based on human gait features and investigates the problem of two variations: clothing (wearing coats) and carrying bag condition as addition to the normal gait sequence. The feature vectors in the proposed system are constructed after applying wavelet transform. Three different sets of feature are proposed in this method. First, Spatio-temporal distance that is dealing with the distance of different parts of the human body (like feet, knees, hand, Human Height and shoulder) during one gait cycle. The second and third feature sets are constructed from approximation and non-approximation coefficient of human body respectively. To extract these two sets of feature we divided the human body into two parts, upper and lower body part, based on the golden ratio proportion. In this paper, we have adopted a statistical method for constructing the feature vector from the above sets. The dimension of the constructed feature vector is reduced based on the Fisher score as a feature selection method to optimize their discriminating significance. Finally k-Nearest Neighbor is applied as a classification method. Experimental results demonstrate that our approach is providing more realistic scenario and relatively better performance compared with the existing approaches.

  4. Design of a real-time hybrid controller

    NARCIS (Netherlands)

    Lim, K.W.; Preisig, H.A.; Rauch, H.E.

    1998-01-01

    This paper describes the framework of an automated supervisory control system realisation. It is developed to support rapid prototyping of real time hybrid con trol systems, described using a simple and flexible set of text descriptors. The design is versatile in allow ing the user to define

  5. Packed-fluidized-bed blanket concept for a thorium-fueled commercial tokamak hybrid reactor

    International Nuclear Information System (INIS)

    Chi, J.W.H.; Miller, J.W.; Karbowski, J.S.; Chapin, D.L.; Kelly, J.L.

    1980-09-01

    A preliminary design of a thorium blanket was carried out as a part of the Commercial Tokamak Hybrid Reactor (CTHR) study. A fixed fuel blanket concept was developed as the reference CTHR blanket with uranium carbide fuel and helium coolant. A fixed fuel blanket was initially evaluated for the thorium blanket study. Subsequently, a new type of hybrid blanket, a packed-fluidized bed (PFB), was conceived. The PFB blanket concept has a number of unique features that may solve some of the problems encountered in the design of tokamak hybrid reactor blankets. This report documents the thorium blanket study and describes the feasibility assessment of the PFB blanket concept

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

    DEFF Research Database (Denmark)

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

    2013-01-01

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

  7. Organosilica hybrid nanomaterials with a high organic content: syntheses and applications of silsesquioxanes

    KAUST Repository

    Croissant, Jonas G.

    2016-11-07

    Organic-inorganic hybrid materials garner properties from their organic and inorganic matrices as well as synergistic features, and therefore have recently attracted much attention at the nanoscale. Non-porous organosilica hybrid nanomaterials with a high organic content such as silsesquioxanes (R-SiO, with R organic groups) and bridged silsesquioxanes (OSi-R-SiO) are especially attractive hybrids since they provide 20 to 80 weight percent of organic functional groups in addition to the known chemistry and stability of silica. In the organosilica family, silsesquioxanes (R-SiO) stand between silicas (SiO) and silicones (RSiO), and are variously called organosilicas, ormosil (organically-modified silica), polysilsesquioxanes and silica hybrids. Herein, we comprehensively review non-porous silsesquioxane and bridged silsesquioxane nanomaterials and their applications in nanomedicine, electro-optics, and catalysis.

  8. Detection of fraudulent emails by employing advanced feature abundance

    Directory of Open Access Journals (Sweden)

    Sarwat Nizamani

    2014-11-01

    Full Text Available In this paper, we present a fraudulent email detection model using advanced feature choice. We extracted various kinds of features and compared the performance of each category of features with the others in terms of the fraudulent email detection rate. The different types of features are incorporated step by step. The detection of fraudulent email has been considered as a classification problem and it is evaluated using various state-of-the art algorithms and on CCM (Nizamani et al., 2011 [1] which is authors’ previous cluster based classification model. The experiments have been performed on diverse feature sets and the different classification methods. The comparison of the results is also presented and the evaluation show that for the fraudulent email detection tasks, the feature set is more important regardless of classification method. The results of the study suggest that the task of fraudulent emails detection requires the better choice of feature set; while the choice of classification method is of less importance.

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

    International Nuclear Information System (INIS)

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

    1998-01-01

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

  10. The formation of diploid and triploid hybrids of female grass carp × male blunt snout bream and their 5S rDNA analysis.

    Science.gov (United States)

    He, Weiguo; Xie, Lihua; Li, Tangluo; Liu, Shaojun; Xiao, Jun; Hu, Jie; Wang, Jing; Qin, Qinbo; Liu, Yun

    2013-11-23

    Hybridization is a useful strategy to alter the genotypes and phenotypes of the offspring. It could transfer the genome of one species to another through combing the different genome of parents in the hybrid offspring. And the offspring may exhibit advantages in growth rate, disease resistance, survival rate and appearance, which resulting from the combination of the beneficial traits from both parents. Diploid and triploid hybrids of female grass carp (Ctenopharyngodon idellus, GC, Cyprininae, 2n = 48) × male blunt snout bream (Megalobrama amblycephala, BSB, Cultrinae, 2n = 48) were successfully obtained by distant hybridization. Diploid hybrids had 48 chromosomes, with one set from GC and one set from BSB. Triploid hybrids possessed 72 chromosomes, with two sets from GC and one set from BSB.The morphological traits, growth rates, and feeding ecology of the parents and hybrid offspring were compared and analyzed. The two kinds of hybrid offspring exhibited significantly phenotypic divergence from GC and BSB. 2nGB hybrids showed similar growth rate compared to that of GC, and 3nGB hybrids significantly higher results. Furthermore, the feeding ecology of hybrid progeny was omnivorous.The 5S rDNA of GC, BSB and their hybrid offspring were also cloned and sequenced. There was only one type of 5S rDNA (designated type I: 180 bp) in GC and one type of 5S rDNA (designated type II: 188 bp) in BSB. However, in the hybrid progeny, diploid and triploid hybrids both inherited type I and type II from their parents, respectively. In addition, a chimera of type I and type II was observed in the genome of diploid and triploid hybrids, excepting a 10 bp of polyA insertion in type II sequence of the chimera of the diploid hybrids. This is the first report of diploid and triploid hybrids being produced by crossing GC and BSB, which have the same chromosome number. The obtainment of two new hybrid offspring has significance in fish genetic breeding. The results illustrate the effect

  11. Effect of radiation on fruit pollen germination and distant hybridization compatibility

    International Nuclear Information System (INIS)

    Li Jing; Shang Xiaoli

    2006-01-01

    Pollens of Zhouxingshantao peach trees, apricot cultivar Katy and plum cultivar Friar were irradiated by different doses of 60 Co γ-rays and ultraviolet to study the radiation effect on the pollen germination and distant hybridization settings. The germination percentages of the pollen irradiated by 60 Co γ-rays and ultraviolet were lower than those of the controls. The pollens of the tested fruits have different sensitivities of 60 Co γ-rays and ultraviolet: the Friar pollen was the most sensitive to the radiation, and the Katy was the least. With the germinate percentages of the irradiated pollen dropping, the distant hybridization fruit setting percentage also lowered. (authors)

  12. Genetic characterization of hybridization between native and invasive bittersweet vines (Celastrus spp.)

    Science.gov (United States)

    Zaya, David N.; Leicht-Young, Stacey A.; Pavlovic, Noel B.; Feldheim, Kevin A.; Ashley, Mary V.

    2015-01-01

    Hybridization associated with species introductions can accelerate the decline of native species. The main objective of this study was to determine if the decline of a North American liana (American bittersweet, Celastrus scandens) in the eastern portion of its range is related to hybridization with an introduced congener (oriental bittersweet, C. orbiculatus). We used newly characterized microsatellite loci, a maternally-inherited chloroplast DNA marker, and field observation to survey individuals across the USA to determine the prevalence of hybrids, their importance in the invasion of C. orbiculatus, and the predominant direction of hybridization. We found that only 8.4 % of non-native genotypes were hybrids (20 of 239), and these hybrids were geographically widespread. Hybrids showed reduced seed set (decline of >98 %) and small, likely inviable pollen. Genetic analysis of a maternally inherited chloroplast marker showed that all 20 identified hybrids came from C. scandens seed parents. The strong asymmetry in pollen flow that favors fecundity in introduced males has the potential to greatly accelerate the decline of native species by wasting limited female reproductive effort.

  13. 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

  14. The feature-weighted receptive field: an interpretable encoding model for complex feature spaces.

    Science.gov (United States)

    St-Yves, Ghislain; Naselaris, Thomas

    2017-06-20

    We introduce the feature-weighted receptive field (fwRF), an encoding model designed to balance expressiveness, interpretability and scalability. The fwRF is organized around the notion of a feature map-a transformation of visual stimuli into visual features that preserves the topology of visual space (but not necessarily the native resolution of the stimulus). The key assumption of the fwRF model is that activity in each voxel encodes variation in a spatially localized region across multiple feature maps. This region is fixed for all feature maps; however, the contribution of each feature map to voxel activity is weighted. Thus, the model has two separable sets of parameters: "where" parameters that characterize the location and extent of pooling over visual features, and "what" parameters that characterize tuning to visual features. The "where" parameters are analogous to classical receptive fields, while "what" parameters are analogous to classical tuning functions. By treating these as separable parameters, the fwRF model complexity is independent of the resolution of the underlying feature maps. This makes it possible to estimate models with thousands of high-resolution feature maps from relatively small amounts of data. Once a fwRF model has been estimated from data, spatial pooling and feature tuning can be read-off directly with no (or very little) additional post-processing or in-silico experimentation. We describe an optimization algorithm for estimating fwRF models from data acquired during standard visual neuroimaging experiments. We then demonstrate the model's application to two distinct sets of features: Gabor wavelets and features supplied by a deep convolutional neural network. We show that when Gabor feature maps are used, the fwRF model recovers receptive fields and spatial frequency tuning functions consistent with known organizational principles of the visual cortex. We also show that a fwRF model can be used to regress entire deep

  15. Characterization of hybrid integrated all-optical flip-flop

    NARCIS (Netherlands)

    Liu, Y.; McDougall, R.; Seoane, J.; Kehayas, E.; Hill, M.T.; Maxwell, G.D.; Zhang, S.; Harmon, R.; Huijskens, Frans; Rivers, L.; Van Holm-Nielsen, P.; Martinez, J.M.; Herrera Llorente, J.; Ramos, F.; Marti, J.; Avramopoulos, H.; Jeppesen, P.; Koonen, A.M.J.; Poustie, A.; Dorren, H.J.S.

    2006-01-01

    We present a fully-packaged, hybrid-integrated all-optical flip-flop with separate optical set and reset operation. The flip-flop can control a wavelength converter to route 40 Gb/s data packets all-optically. The experimental results are given

  16. Characterisation of hybrid integrated all-optical flip-flop

    DEFF Research Database (Denmark)

    Liu, Y.; McDougall, R.; Seoane, Jorge

    2006-01-01

    We present a fully-packaged, hybrid-integrated all-optical flip-flop with separate optical set and reset operation. The flip-flop can control a wavelength converter to route 40 Gb/s data packets all-optically. The experimental results are given....

  17. Conceptual Design and Optimal Power Control Strategy for AN Eco-Friendly Hybrid Vehicle

    Science.gov (United States)

    Nasiri, N. Mir; Chieng, Frederick T. A.

    2011-06-01

    This paper presents a new concept for a hybrid vehicle using a torque and speed splitting technique. It is implemented by the newly developed controller in combination with a two degree of freedom epicyclic gear transmission. This approach enables optimization of the power split between the less powerful electrical motor and more powerful engine while driving a car load. The power split is fundamentally a dual-energy integration mechanism as it is implemented by using the epicyclic gear transmission that has two inputs and one output for a proper power distribution. The developed power split control system manages the operation of both the inputs to have a known output with the condition of maintaining optimum operating efficiency of the internal combustion engine and electrical motor. This system has a huge potential as it is possible to integrate all the features of hybrid vehicle known to-date such as the regenerative braking system, series hybrid, parallel hybrid, series/parallel hybrid, and even complex hybrid (bidirectional). By using the new power split system it is possible to further reduce fuel consumption and increase overall efficiency.

  18. 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.

  19. 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

  20. A putative hybrid swarm within Oonopsis foliosa (Asteraceae: Astereae)

    Science.gov (United States)

    Hughes, J.F.; Brown, G.K.

    2004-01-01

    Oo??nopsis foliosa var. foliosa and var. monocephala are endemic to short-grass steppe of southeastern Colorado and until recently were considered geographically disjunct. The only known qualitative feature separating these 2 varieties is floral head type; var. foliosa has radiate heads, whereas var. monocephala heads are discoid. Sympatry between these varieties is restricted to a small area in which a range of parental types and intermediate head morphologies is observed. We used distribution mapping, morphometric analyses, chromosome cytology, and pollen stainability to characterize the sympatric zone. Morphometrics confirms that the only discrete difference between var. foliosa and var. monocephala is radiate versus discoid heads, respectively. The outer florets of putative hybrid individuals ranged from conspicuously elongated yet radially symmetric disc-floret corollas, to elongated radially asymmetric bilabiate- or deeply cleft corollas, to stunted ray florets with appendages remnant of corolla lobes. Chromosome cytology of pollen mother cells from both putative parental varieties and a series of intermediate morphological types collected at the sympatric zone reveal evidence of translocation heterozygosity. Pollen stainability shows no significant differences in viability between the parental varieties and putative hybrids. The restricted distribution of putative hybrids to a narrow zone of sympatry between the parental types and the presence of meiotic chromosome-pairing anomalies in these intermediate plants are consistent with a hybrid origin. The high stainability of putative-hybrid pollen adds to a growing body of evidence that hybrids are not universally unfit.

  1. Working memory for visual features and conjunctions in schizophrenia.

    Science.gov (United States)

    Gold, James M; Wilk, Christopher M; McMahon, Robert P; Buchanan, Robert W; Luck, Steven J

    2003-02-01

    The visual working memory (WM) storage capacity of patients with schizophrenia was investigated using a change detection paradigm. Participants were presented with 2, 3, 4, or 6 colored bars with testing of both single feature (color, orientation) and feature conjunction conditions. Patients performed significantly worse than controls at all set sizes but demonstrated normal feature binding. Unlike controls, patient WM capacity declined at set size 6 relative to set size 4. Impairments with subcapacity arrays suggest a deficit in task set maintenance: Greater impairment for supercapacity set sizes suggests a deficit in the ability to selectively encode information for WM storage. Thus, the WM impairment in schizophrenia appears to be a consequence of attentional deficits rather than a reduction in storage capacity.

  2. A keyword spotting model using perceptually significant energy features

    Science.gov (United States)

    Umakanthan, Padmalochini

    The task of a keyword recognition system is to detect the presence of certain words in a conversation based on the linguistic information present in human speech. Such keyword spotting systems have applications in homeland security, telephone surveillance and human-computer interfacing. General procedure of a keyword spotting system involves feature generation and matching. In this work, new set of features that are based on the psycho-acoustic masking nature of human speech are proposed. After developing these features a time aligned pattern matching process was implemented to locate the words in a set of unknown words. A word boundary detection technique based on frame classification using the nonlinear characteristics of speech is also addressed in this work. Validation of this keyword spotting model was done using widely acclaimed Cepstral features. The experimental results indicate the viability of using these perceptually significant features as an augmented feature set in keyword spotting.

  3. 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...

  4. Increased mannoprotein content in wines produced by Saccharomyces kudriavzevii×Saccharomyces cerevisiae hybrids.

    Science.gov (United States)

    Pérez-Través, Laura; Querol, Amparo; Pérez-Torrado, Roberto

    2016-11-21

    Several wine quality aspects are influenced by yeast mannoproteins on account of aroma compounds retention, lactic-acid bacterial growth stimulation, protection against protein haze and astringency reduction. Thus selecting a yeast strain that produces high levels of mannoproteins is important for the winemaking industry. In this work, we observed increased levels of mannoproteins in S. cerevisiae×S. kudriavzevii hybrids, compared to the S. cerevisiae strain, in wine fermentations. Furthermore, the expression of a key gene related to mannoproteins biosynthesis, PMT1, increased in the S. cerevisiae×S. kudriavzevii hybrid. We showed that artificially constructed S. cerevisiae×S. kudriavzevii hybrids also increased the levels of mannoproteins. This work demonstrates that either natural or artificial S. cerevisiae×S. kudriavzevii hybrids present mannoprotein overproducing capacity under winemaking conditions, a desirable physiological feature for this industry. These results suggest that genome interaction in hybrids generates a physiological environment that enhances the release of mannoproteins. Copyright © 2016 Elsevier B.V. All rights reserved.

  5. Buffer Management and Hybrid Probability Choice Routing for Packet Delivery in Opportunistic Networks

    Directory of Open Access Journals (Sweden)

    Daru Pan

    2012-01-01

    Full Text Available Due to the features of long connection delays, frequent network partitions, and topology unsteadiness, the design of opportunistic networks faces the challenge of how to effectively deliver data based only on occasional encountering of nodes, where the conventional routing schemes do not work properly. This paper proposes a hybrid probability choice routing protocol with buffer management for opportunistic networks. A delivery probability function is set up based on continuous encounter duration time, which is used for selecting a better node to relay packets. By combining the buffer management utility and the delivery probability, a total utility is used to decide whether the packet should be kept in the buffer or be directly transmitted to the encountering node. Simulation results show that the proposed routing outperforms the existing one in terms of the delivery rate and the average delay.

  6. Oscillation of an anuran hybrid zone: morphological evidence spanning 50 years.

    Directory of Open Access Journals (Sweden)

    Jean-Sébastien Roy

    Full Text Available The hybrid zone between the primarily forest-dwelling American toad, Anaxyrus americanus, and the prairie-adapted Canadian toad, A. hemiophrys, in southeastern Manitoba is known to have shifted its position during the past 50 years. Hybrid zones are areas of interbreeding between species and their movement across a landscape should reflect their underlying dynamics and environmental change. However, empirical demonstrations of hybrid zone movements over long periods of time are rare. This hybrid zone is dominated by individuals of intermediate morphology and genetic composition. We sought to determine if it had continued to move and if that movement was associated with shifts in habitat, as predicted.We used variation in the toads' most diagnostic morphological feature, the separation between their interorbital cranial crests, to determine the geographic position of the hybrid zone center at four times between 1960 and 2009 using maximum likelihood methods. The hybrid zone center moved west by 38 km over 19 years and then east again by 10 km over the succeeding 29 years. The position of the hybrid zone did not track either the direction or the magnitude of movement of the forest-prairie habitat transition over the same time period.This is the first reported evidence of oscillation in the position of a hybrid zone. The back and forth movement indicates that neither species maintains a selective advantage over the other in the long term. However, the movement of the hybrid zone was not bounded by the breadth of the habitat transition. Its oscillation suggests that the hybrid zone is better described as being elastically tethered to the habitat transition.

  7. Artificial Neural Network and Genetic Algorithm Hybrid Intelligence for Predicting Thai Stock Price Index Trend

    Directory of Open Access Journals (Sweden)

    Montri Inthachot

    2016-01-01

    Full Text Available 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.

  8. 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...

  9. 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...

  10. Direct deposition of inorganic–organic hybrid semiconductors and their template-assisted microstructures

    International Nuclear Information System (INIS)

    Dwivedi, V.K.; Baumberg, J.J.; Prakash, G. Vijaya

    2013-01-01

    A straight-forward method is developed to deposit a new class of self-organized inorganic–organic (IO) hybrid, (C 12 H 25 NH 3 ) 2 PbI 4 . These IO hybrid structures are stacked-up as natural multiple quantum well structures and exhibit strong room-temperature exciton emission and other multifunctional features. Here it is successfully demonstrated that these materials can be directly carved into 2D photonic structures from the inexpensive template-assisted electrochemical deposition followed by solution processing. The applicability of this method for many such varieties of IO-hybrids is also explored. By appropriately controlling the deposition conditions and the self-assembly templates, target structures are developed for new-generation low-cost photonic devices. -- Highlights: ► New fabrication methodology for self-organized inorganic–organic hybrids. ► Strongly confined exciton emission and photoconductive properties. ► Simple bottom-up fabrication for device applications.

  11. Features of the repetition frequency of edge localized modes in EAST

    DEFF Research Database (Denmark)

    Jiang, M.; Xiao, C.; Xu, G.S.

    2012-01-01

    This paper presents the features of the edge localized modes (ELMs) observed in the 2010 experimental campaign on the Experimental Advanced Superconducting Tokamak (EAST). The first high-confinement mode (H-mode) at an H-factor of HIPB98(y, 2)~1 has been obtained with about 1 MW lower hybrid wave...

  12. Personal Rotorcraft Design and Performance with Electric Hybridization

    Science.gov (United States)

    Snyder, Christopher A.

    2017-01-01

    Recent and projected improvements for more or all-electric aviation propulsion systems can enable greater personal mobility, while also reducing environmental impact (noise and emissions). However, all-electric energy storage capability is significantly less than present, hydrocarbon-fueled systems. A system study was performed exploring design and performance assuming hybrid propulsion ranging from traditional hydrocarbon-fueled cycles (gasoline Otto and diesel) to all-electric systems using electric motors generators, with batteries for energy storage and load leveling. Study vehicles were a conventional, single-main rotor (SMR) helicopter and an advanced vertical takeoff and landing (VTOL) aircraft. Vehicle capability was limited to two or three people (including pilot or crew); the design range for the VTOL aircraft was set to 150 miles (about one hour total flight). Search and rescue (SAR), loiter, and cruise-dominated missions were chosen to illustrate each vehicle and degree of hybrid propulsion strengths and weaknesses. The traditional, SMR helicopter is a hover-optimized design; electric hybridization was performed assuming a parallel hybrid approach by varying degree of hybridization. Many of the helicopter hybrid propulsion combinations have some mission capabilities that might be effective for short range or on-demand mobility missions. However, even for 30 year technology electrical components, all hybrid propulsion systems studied result in less available fuel, lower maximum range, and reduced hover and loiter duration than the baseline vehicle. Results for the VTOL aircraft were more encouraging. Series hybrid combinations reflective of near-term systems could improve range and loiter duration by 30. Advanced, higher performing series hybrid combinations could double or almost triple the VTOL aircrafts range and loiter duration. Additional details on the study assumptions and work performed are given, as well as suggestions for future study effort.

  13. Integrated energy and advanced thermal management system for hybrid electric vehicles

    NARCIS (Netherlands)

    Wei, C.

    2017-01-01

    Hybrid electric vehicles (HEVs) featuring a fuel source engine and an energy storage source battery play an important role in improving fuel efficiency compared with its conventional counterparts. In view of the drawbacks of the existing research neglecting the thermal aspects when it comes to

  14. Comparative genomic hybridization detects novel amplifications in fibroadenomas of the breast

    DEFF Research Database (Denmark)

    Ojopi, E P; Rogatto, S R; Caldeira, J R

    2001-01-01

    Comparative genomic hybridization analysis was performed for identification of chromosomal imbalances in 23 samples of fibroadenomas of the breast. Chromosomal gains rather than losses were a feature of these lesions. Only two cases with a familial and/or previous history of breast lesions had gain...

  15. Action recognition using mined hierarchical compound features.

    Science.gov (United States)

    Gilbert, Andrew; Illingworth, John; Bowden, Richard

    2011-05-01

    The field of Action Recognition has seen a large increase in activity in recent years. Much of the progress has been through incorporating ideas from single-frame object recognition and adapting them for temporal-based action recognition. Inspired by the success of interest points in the 2D spatial domain, their 3D (space-time) counterparts typically form the basic components used to describe actions, and in action recognition the features used are often engineered to fire sparsely. This is to ensure that the problem is tractable; however, this can sacrifice recognition accuracy as it cannot be assumed that the optimum features in terms of class discrimination are obtained from this approach. In contrast, we propose to initially use an overcomplete set of simple 2D corners in both space and time. These are grouped spatially and temporally using a hierarchical process, with an increasing search area. At each stage of the hierarchy, the most distinctive and descriptive features are learned efficiently through data mining. This allows large amounts of data to be searched for frequently reoccurring patterns of features. At each level of the hierarchy, the mined compound features become more complex, discriminative, and sparse. This results in fast, accurate recognition with real-time performance on high-resolution video. As the compound features are constructed and selected based upon their ability to discriminate, their speed and accuracy increase at each level of the hierarchy. The approach is tested on four state-of-the-art data sets, the popular KTH data set to provide a comparison with other state-of-the-art approaches, the Multi-KTH data set to illustrate performance at simultaneous multiaction classification, despite no explicit localization information provided during training. Finally, the recent Hollywood and Hollywood2 data sets provide challenging complex actions taken from commercial movie sequences. For all four data sets, the proposed hierarchical

  16. Targeted 2D/3D registration using ray normalization and a hybrid optimizer

    International Nuclear Information System (INIS)

    Dey, Joyoni; Napel, Sandy

    2006-01-01

    X-ray images are often used to guide minimally invasive procedures in interventional radiology. The use of a preoperatively obtained 3D volume can enhance the visualization needed for guiding catheters and other surgical devices. However, for intraoperative usefulness, the 3D dataset needs to be registered to the 2D x-ray images of the patient. We investigated the effect of targeting subvolumes of interest in the 3D datasets and registering the projections with C-arm x-ray images. We developed an intensity-based 2D/3D rigid-body registration using a Monte Carlo-based hybrid algorithm as the optimizer, using a single view for registration. Pattern intensity (PI) and mutual information (MI) were two metrics tested. We used normalization of the rays to address the problems due to truncation in 3D necessary for targeting. We tested the algorithm on a C-arm x-ray image of a pig's head and a 3D dataset reconstructed from multiple views of the C-arm. PI and MI were comparable in performance. For two subvolumes starting with a set of initial poses from +/-15 mm in x, from +/-3 mm (random), in y and z and +/-4 deg in the three angles, the robustness was 94% for PI and 91% for MI, with accuracy of 2.4 mm (PI) and 2.6 mm (MI), using the hybrid algorithm. The hybrid optimizer, when compared with a standard Powell's direction set method, increased the robustness from 59% (Powell) to 94% (hybrid). Another set of 50 random initial conditions from [+/-20] mm in x,y,z and [+/-10] deg in the three angles, yielded robustness of 84% (hybrid) versus 38% (Powell) using PI as metric, with accuracies 2.1 mm (hybrid) versus 2.0 mm (Powell)

  17. Restraining approach for the spurious kinematic modes in hybrid equilibrium element

    Science.gov (United States)

    Parrinello, F.

    2013-10-01

    The present paper proposes a rigorous approach for the elimination of spurious kinematic modes in hybrid equilibrium elements, for three well known mesh patches. The approach is based on the identification of the dependent equations in the set of inter-element and boundary equilibrium equations of the sides involved in the spurious kinematic mode. Then the kinematic variables related to the dependent equations are reciprocally constrained and, by application of master slave elimination method, the set of inter-element equilibrium equations is reduced to full rank. The elastic solutions produced by means of the proposed approach verify the homogeneous, the inter-element and the boundary equilibrium equations. Hybrid stress formulation is developed in a rigorous mathematical setting. The results of linear elastic analysis obtained by the proposed approach and by classical displacement based method are compared for some structural examples.

  18. A Feature Subset Selection Method Based On High-Dimensional Mutual Information

    Directory of Open Access Journals (Sweden)

    Chee Keong Kwoh

    2011-04-01

    Full Text Available Feature selection is an important step in building accurate classifiers and provides better understanding of the data sets. In this paper, we propose a feature subset selection method based on high-dimensional mutual information. We also propose to use the entropy of the class attribute as a criterion to determine the appropriate subset of features when building classifiers. We prove that if the mutual information between a feature set X and the class attribute Y equals to the entropy of Y , then X is a Markov Blanket of Y . We show that in some cases, it is infeasible to approximate the high-dimensional mutual information with algebraic combinations of pairwise mutual information in any forms. In addition, the exhaustive searches of all combinations of features are prerequisite for finding the optimal feature subsets for classifying these kinds of data sets. We show that our approach outperforms existing filter feature subset selection methods for most of the 24 selected benchmark data sets.

  19. Reconstruction of the evolutionary history of Saccharomyces cerevisiae x S. kudriavzevii hybrids based on multilocus sequence analysis.

    Directory of Open Access Journals (Sweden)

    David Peris

    Full Text Available In recent years, interspecific hybridization and introgression are increasingly recognized as significant events in the evolution of Saccharomyces yeasts. These mechanisms have probably been involved in the origin of novel yeast genotypes and phenotypes, which in due course were to colonize and predominate in the new fermentative environments created by human manipulation. The particular conditions in which hybrids arose are still unknown, as well as the number of possible hybridization events that generated the whole set of natural hybrids described in the literature during recent years. In this study, we could infer at least six different hybridization events that originated a set of 26 S. cerevisiae x S. kudriavzevii hybrids isolated from both fermentative and non-fermentative environments. Different wine S. cerevisiae strains and European S. kudriavzevii strains were probably involved in the hybridization events according to gene sequence information, as well as from previous data on their genome composition and ploidy. Finally, we postulate that these hybrids may have originated after the introduction of vine growing and winemaking practices by the Romans to the present Northern vine-growing limits and spread during the expansion of improved viticulture and enology practices that occurred during the Late Middle Ages.

  20. Reconstruction of the Evolutionary History of Saccharomyces cerevisiae x S. kudriavzevii Hybrids Based on Multilocus Sequence Analysis

    Science.gov (United States)

    Peris, David; Lopes, Christian A.; Arias, Armando; Barrio, Eladio

    2012-01-01

    In recent years, interspecific hybridization and introgression are increasingly recognized as significant events in the evolution of Saccharomyces yeasts. These mechanisms have probably been involved in the origin of novel yeast genotypes and phenotypes, which in due course were to colonize and predominate in the new fermentative environments created by human manipulation. The particular conditions in which hybrids arose are still unknown, as well as the number of possible hybridization events that generated the whole set of natural hybrids described in the literature during recent years. In this study, we could infer at least six different hybridization events that originated a set of 26 S. cerevisiae x S. kudriavzevii hybrids isolated from both fermentative and non-fermentative environments. Different wine S. cerevisiae strains and European S. kudriavzevii strains were probably involved in the hybridization events according to gene sequence information, as well as from previous data on their genome composition and ploidy. Finally, we postulate that these hybrids may have originated after the introduction of vine growing and winemaking practices by the Romans to the present Northern vine-growing limits and spread during the expansion of improved viticulture and enology practices that occurred during the Late Middle Ages. PMID:23049811

  1. Epigenetic patterns newly established after interspecific hybridization in natural populations of Solanum

    Science.gov (United States)

    Cara, Nicolás; Marfil, Carlos F; Masuelli, Ricardo W

    2013-01-01

    Interspecific hybridization is known for triggering genetic and epigenetic changes, such as modifications on DNA methylation patterns and impact on phenotypic plasticity and ecological adaptation. Wild potatoes (Solanum, section Petota) are adapted to multiple habitats along the Andes, and natural hybridizations have proven to be a common feature among species of this group. Solanum × rechei, a recently formed hybrid that grows sympatrically with the parental species S. kurtzianum and S. microdontum, represents an ideal model for studying the ecologically and evolutionary importance of hybridization in generating of epigenetic variability. Genetic and epigenetic variability and their correlation with morphological variation were investigated in wild and ex situ conserved populations of these three wild potato species using amplified fragment length polymorphism (AFLP) and methylation-sensitive amplified polymorphism (MSAP) techniques. We observed that novel methylation patterns doubled the number of novel genetic patterns in the hybrid and that the morphological variability measured on 30 characters had a higher correlation with the epigenetic than with the genetic variability. Statistical comparison of methylation levels suggested that the interspecific hybridization induces genome demethylation in the hybrids. A Bayesian analysis of the genetic data reveled the hybrid nature of S. × rechei, with genotypes displaying high levels of admixture with the parental species, while the epigenetic information assigned S. × rechei to its own cluster with low admixture. These findings suggested that after the hybridization event, a novel epigenetic pattern was rapidly established, which might influence the phenotypic plasticity and adaptation of the hybrid to new environments. PMID:24198938

  2. Bibliography: Sandia Laboratories hybrid microcircuits and related thin film technology (revised)

    International Nuclear Information System (INIS)

    Oswalt, J.A.

    1975-12-01

    Hybrid circuit applications for nuclear weapons have been considered at Sandia since the mid-60's. However a major commitment was made in 1970 to develop a limited but well understood set of technologies for weapon applications. Development of these technologies and related studies have been documented in a number of publications. This bibliography lists the publications from 1968 to mid-1977 for reference by hybrid designers, users, or technologists

  3. 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....

  4. Obtaining of interspecific hybrids for pea introgressive breeding

    Directory of Open Access Journals (Sweden)

    Sergey Vasilevich Bobkov

    2015-09-01

    Full Text Available Background. Overcoming of reproductive isolation, identification and transfer of agronomic value genes from wild relatives into cultivated pea genomes is an important task for pea introgressive breeding. Materials and methods. Reciprocal hybridization of cultivated pea with wide set of P. fulvum accessions was conducted. Identification of hybrids was carried out with use of biochemical and morphological markers. Identification of unique protein was conducted with use of electrophoretic spectra of mature seeds. Results. Pea interspecific hybrids were obtained in two reciprocal directions of crosses. Cross efficiency in Р. sativum × P. fulvum and P. fulvum × Р. sativum combinations was 36 % and 7 %, respectively. All tested seeds in crosses Р. sativum × P. fulvum were hybrids. Crosses in direction P. fulvum × Р. sativum led to formation of puny seeds restricted in embryo growth. Protein markers of one seed derived in cross P. fulvum × Р. sativum proved its hybrid nature. Morphological markers demonstrated that plant derived from another cross was also a hybrid. Culture of immature embryos was developed for recovering plants in interspecific crosses. Morphogenic calli and regenerated plants were obtained in culture of immature embryos P. fulvum (И592589 × Р. sativum (Aest. Identification of unique protein 7 of P. fulvum was conducted. Inheritance of that protein was proved as monogenic dominant. Conclusion. Efficiency of hybridization in combination P. fulvum × Р. sativum was significantly less in compare to reciprocal one. All products of that cross combination were tested as hybrids. Unique protein 7 of P. fulvum was revealed as a result of mature seed electrophoretic spectra analysis. Inheritance of that protein was determined as monogenic dominant.

  5. Novel gene sets improve set-level classification of prokaryotic gene expression data.

    Science.gov (United States)

    Holec, Matěj; Kuželka, Ondřej; Železný, Filip

    2015-10-28

    Set-level classification of gene expression data has received significant attention recently. In this setting, high-dimensional vectors of features corresponding to genes are converted into lower-dimensional vectors of features corresponding to biologically interpretable gene sets. The dimensionality reduction brings the promise of a decreased risk of overfitting, potentially resulting in improved accuracy of the learned classifiers. However, recent empirical research has not confirmed this expectation. Here we hypothesize that the reported unfavorable classification results in the set-level framework were due to the adoption of unsuitable gene sets defined typically on the basis of the Gene ontology and the KEGG database of metabolic networks. We explore an alternative approach to defining gene sets, based on regulatory interactions, which we expect to collect genes with more correlated expression. We hypothesize that such more correlated gene sets will enable to learn more accurate classifiers. We define two families of gene sets using information on regulatory interactions, and evaluate them on phenotype-classification tasks using public prokaryotic gene expression data sets. From each of the two gene-set families, we first select the best-performing subtype. The two selected subtypes are then evaluated on independent (testing) data sets against state-of-the-art gene sets and against the conventional gene-level approach. The novel gene sets are indeed more correlated than the conventional ones, and lead to significantly more accurate classifiers. The novel gene sets are indeed more correlated than the conventional ones, and lead to significantly more accurate classifiers. Novel gene sets defined on the basis of regulatory interactions improve set-level classification of gene expression data. The experimental scripts and other material needed to reproduce the experiments are available at http://ida.felk.cvut.cz/novelgenesets.tar.gz.

  6. 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.

  7. Design of 240,000 orthogonal 25mer DNA barcode probes.

    Science.gov (United States)

    Xu, Qikai; Schlabach, Michael R; Hannon, Gregory J; Elledge, Stephen J

    2009-02-17

    DNA barcodes linked to genetic features greatly facilitate screening these features in pooled formats using microarray hybridization, and new tools are needed to design large sets of barcodes to allow construction of large barcoded mammalian libraries such as shRNA libraries. Here we report a framework for designing large sets of orthogonal barcode probes. We demonstrate the utility of this framework by designing 240,000 barcode probes and testing their performance by hybridization. From the test hybridizations, we also discovered new probe design rules that significantly reduce cross-hybridization after their introduction into the framework of the algorithm. These rules should improve the performance of DNA microarray probe designs for many applications.

  8. Hybrid Gear Preliminary Results-Application of Composites to Dynamic Mechanical Components

    Science.gov (United States)

    Handschuh, Robert F.; Roberts Gary D.; Sinnamon, R.; Stringer, David B.; Dykas, Brian D.; Kohlman, Lee W.

    2012-01-01

    Composite spur gears were fabricated and then tested at NASA Glenn Research Center. The composite material served as the web of the gear between the gear teeth and a metallic hub for mounting to the torque-applying shaft. The composite web was bonded only to the inner and outer hexagonal features that were machined from an initially all-metallic aerospace quality spur gear. The Hybrid Gear was tested against an all-steel gear and against a mating Hybrid Gear. As a result of the composite to metal fabrication process used, the concentricity of the gears were reduced from their initial high-precision value. Regardless of the concentricity error, the hybrid gears operated successfully for over 300 million cycles at 10000 rpm and 490 in.*lbs torque. Although the design was not optimized for weight, the composite gears were found to be 20% lighter than the all-steel gears. Free vibration modes and vibration/noise tests were also conduct to compare the vibration and damping characteristic of the Hybrid Gear to all-steel gears. The initial results indicate that this type of hybrid design may have a dramatic effect on drive system weight without sacrificing strength.

  9. 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.

  10. Hybrid Tooling: A Review of Process Chains for Tooling Microfabrication within 4M

    DEFF Research Database (Denmark)

    Azcarate, Sabino; Uriarte, Luis; Bigot, Samuel

    2006-01-01

    is introduced. Several examples of ‘hybrid tooling’ within 4M partners are presented. Considered materials are nickel for electroforming, stainless steel for ECF, and tool steel for the other processes. The paper results provide a global comparison between the previously mentioned processes, the current...... limitations of these technologies concerning feature sizes, surface finish, aspect ratios, etc. have been identified. The main conclusion drawn is the imperative requirement to combine individual processes (‘hybrid tooling’) to produce mould inserts required outside research laboratories....

  11. Analysis and control of a hybrid vehicle powered by free-piston energy converter

    OpenAIRE

    Hansson, Jörgen

    2006-01-01

    The introduction of hybrid powertrains has made it possible to utilise unconventional engines as primary power units in vehicles. The free-piston energy converter (FPEC) is such an engine. It is a combination of a free-piston combustion engine and a linear electrical machine. The main features of this configuration are high efficiency and a rapid transient response. In this thesis the free-piston energy converter as part of a hybrid powertrain is studied. One issue of the FPEC is the generati...

  12. 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.

  13. 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

  14. Hybrid generative-discriminative approach to age-invariant face recognition

    Science.gov (United States)

    Sajid, Muhammad; Shafique, Tamoor

    2018-03-01

    Age-invariant face recognition is still a challenging research problem due to the complex aging process involving types of facial tissues, skin, fat, muscles, and bones. Most of the related studies that have addressed the aging problem are focused on generative representation (aging simulation) or discriminative representation (feature-based approaches). Designing an appropriate hybrid approach taking into account both the generative and discriminative representations for age-invariant face recognition remains an open problem. We perform a hybrid matching to achieve robustness to aging variations. This approach automatically segments the eyes, nose-bridge, and mouth regions, which are relatively less sensitive to aging variations compared with the rest of the facial regions that are age-sensitive. The aging variations of age-sensitive facial parts are compensated using a demographic-aware generative model based on a bridged denoising autoencoder. The age-insensitive facial parts are represented by pixel average vector-based local binary patterns. Deep convolutional neural networks are used to extract relative features of age-sensitive and age-insensitive facial parts. Finally, the feature vectors of age-sensitive and age-insensitive facial parts are fused to achieve the recognition results. Extensive experimental results on morphological face database II (MORPH II), face and gesture recognition network (FG-NET), and Verification Subset of cross-age celebrity dataset (CACD-VS) demonstrate the effectiveness of the proposed method for age-invariant face recognition well.

  15. Performance assessment of a multi-fuel hybrid engine for future aircraft

    NARCIS (Netherlands)

    Yin, F.; Gangoli Rao, A.; Bhat, Abhishek; Chen, Min

    2018-01-01

    This paper presents the performance assessment of a novel turbofan engine using two energy sources: Liquid Natural Gas (LNG) and kerosene, called Multi-Fuel Hybrid Engine (MFHE). The MFHE is a new engine concept consisting of several novel features, such as a contra-rotating fan to sustain

  16. Poly(3-hexylthiophene)/ZnO hybrid pn junctions for microelectronics applications

    DEFF Research Database (Denmark)

    Katsia, E.; Huby, N.; Tallarida, G.

    2009-01-01

    Hybrid poly(3-hexylthiophene)/ZnO devices are investigated as rectifying heterojunctions for microelectronics applications. A low-temperature atomic layer deposition of ZnO on top of poly(3-hexylthiophene) allows the fabrication of diodes featuring a rectification ratio of nearly 105 at ±4 V...

  17. 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.

  18. From Elephant God to Man Dog: Hybridity, Mimicry, and the Homo Sacer in Salman Rushdie’s MIDNIGHT’S CHILDREN

    Directory of Open Access Journals (Sweden)

    Peter Arnds

    2017-12-01

    Full Text Available Rushdie’s Midnight’s Children is a work of pastiche. As such it is typically postmodern, literature patched together from other literary texts. Using Grass’s Tin Drum and the German postwar cultural-political situation as a model, Rushdie copies Grass in re-enchanting a secularized country grappling with the memory of genocide through a set of mythological paradigms. By drawing on postcolonial theory and the biopolitical concept of the homo sacer this essay analyses Rushdie’s particular brand of what I have termed as mythical realism in view of its close amalgamation of hybridity with mimicry, subversive mockery, and liminality between the human and the animal, typical features of the postmodern novel trying to come to terms with war and genocide. It is the aim of this study to examine the functions of these key features for Rushdie’s Midnight’s Children for lifting the corks of forgetting and disclosing the concealment of India’s past.

  19. Bioinspired Smart Actuator Based on Graphene Oxide-Polymer Hybrid Hydrogels.

    Science.gov (United States)

    Wang, Tao; Huang, Jiahe; Yang, Yiqing; Zhang, Enzhong; Sun, Weixiang; Tong, Zhen

    2015-10-28

    Rapid response and strong mechanical properties are desired for smart materials used in soft actuators. A bioinspired hybrid hydrogel actuator was designed and prepared by series combination of three trunks of tough polymer-clay hydrogels to accomplish the comprehensive actuation of "extension-grasp-retraction" like a fishing rod. The hydrogels with thermo-creep and thermo-shrinking features were successively irradiated by near-infrared (NIR) to execute extension and retraction, respectively. The GO in the hydrogels absorbed the NIR energy and transformed it into thermo-energy rapidly and effectively. The hydrogel with adhesion or magnetic force was adopted as the "hook" of the hybrid hydrogel actuator for grasping object. The hook of the hybrid hydrogel actuator was replaceable according to applications, even with functional materials other than hydrogels. This study provides an innovative concept to explore new soft actuators through combining response hydrogels and programming the same stimulus.

  20. Using the hybrid fuzzy goal programming model and hybrid genetic algorithm to solve a multi-objective location routing problem for infectious waste disposaL

    Energy Technology Data Exchange (ETDEWEB)

    Wichapa, Narong; Khokhajaikiat, Porntep

    2017-07-01

    Disposal of infectious waste remains one of the most serious problems in the social and environmental domains of almost every nation. Selection of new suitable locations and finding the optimal set of transport routes to transport infectious waste, namely location routing problem for infectious waste disposal, is one of the major problems in hazardous waste management. Design/methodology/approach: Due to the complexity of this problem, location routing problem for a case study, forty hospitals and three candidate municipalities in sub-Northeastern Thailand, was divided into two phases. The first phase is to choose suitable municipalities using hybrid fuzzy goal programming model which hybridizes the fuzzy analytic hierarchy process and fuzzy goal programming. The second phase is to find the optimal routes for each selected municipality using hybrid genetic algorithm which hybridizes the genetic algorithm and local searches including 2-Opt-move, Insertion-move and ?-interchange-move. Findings: The results indicate that the hybrid fuzzy goal programming model can guide the selection of new suitable municipalities, and the hybrid genetic algorithm can provide the optimal routes for a fleet of vehicles effectively. Originality/value: The novelty of the proposed methodologies, hybrid fuzzy goal programming model, is the simultaneous combination of both intangible and tangible factors in order to choose new suitable locations, and the hybrid genetic algorithm can be used to determine the optimal routes which provide a minimum number of vehicles and minimum transportation cost under the actual situation, efficiently.

  1. Using the hybrid fuzzy goal programming model and hybrid genetic algorithm to solve a multi-objective location routing problem for infectious waste disposaL

    International Nuclear Information System (INIS)

    Wichapa, Narong; Khokhajaikiat, Porntep

    2017-01-01

    Disposal of infectious waste remains one of the most serious problems in the social and environmental domains of almost every nation. Selection of new suitable locations and finding the optimal set of transport routes to transport infectious waste, namely location routing problem for infectious waste disposal, is one of the major problems in hazardous waste management. Design/methodology/approach: Due to the complexity of this problem, location routing problem for a case study, forty hospitals and three candidate municipalities in sub-Northeastern Thailand, was divided into two phases. The first phase is to choose suitable municipalities using hybrid fuzzy goal programming model which hybridizes the fuzzy analytic hierarchy process and fuzzy goal programming. The second phase is to find the optimal routes for each selected municipality using hybrid genetic algorithm which hybridizes the genetic algorithm and local searches including 2-Opt-move, Insertion-move and ?-interchange-move. Findings: The results indicate that the hybrid fuzzy goal programming model can guide the selection of new suitable municipalities, and the hybrid genetic algorithm can provide the optimal routes for a fleet of vehicles effectively. Originality/value: The novelty of the proposed methodologies, hybrid fuzzy goal programming model, is the simultaneous combination of both intangible and tangible factors in order to choose new suitable locations, and the hybrid genetic algorithm can be used to determine the optimal routes which provide a minimum number of vehicles and minimum transportation cost under the actual situation, efficiently.

  2. Feature Selection for Audio Surveillance in Urban Environment

    Directory of Open Access Journals (Sweden)

    KIKTOVA Eva

    2014-05-01

    Full Text Available This paper presents the work leading to the acoustic event detection system, which is designed to recognize two types of acoustic events (shot and breaking glass in urban environment. For this purpose, a huge front-end processing was performed for the effective parametric representation of an input sound. MFCC features and features computed during their extraction (MELSPEC and FBANK, then MPEG-7 audio descriptors and other temporal and spectral characteristics were extracted. High dimensional feature sets were created and in the next phase reduced by the mutual information based selection algorithms. Hidden Markov Model based classifier was applied and evaluated by the Viterbi decoding algorithm. Thus very effective feature sets were identified and also the less important features were found.

  3. 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.

  4. Accurate Identification of Cancerlectins through Hybrid Machine Learning Technology.

    Science.gov (United States)

    Zhang, Jieru; Ju, Ying; Lu, Huijuan; Xuan, Ping; Zou, Quan

    2016-01-01

    Cancerlectins are cancer-related proteins that function as lectins. They have been identified through computational identification techniques, but these techniques have sometimes failed to identify proteins because of sequence diversity among the cancerlectins. Advanced machine learning identification methods, such as support vector machine and basic sequence features (n-gram), have also been used to identify cancerlectins. In this study, various protein fingerprint features and advanced classifiers, including ensemble learning techniques, were utilized to identify this group of proteins. We improved the prediction accuracy of the original feature extraction methods and classification algorithms by more than 10% on average. Our work provides a basis for the computational identification of cancerlectins and reveals the power of hybrid machine learning techniques in computational proteomics.

  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. Efficient light emission from inorganic and organic semiconductor hybrid structures by energy-level tuning.

    Science.gov (United States)

    Schlesinger, R; Bianchi, F; Blumstengel, S; Christodoulou, C; Ovsyannikov, R; Kobin, B; Moudgil, K; Barlow, S; Hecht, S; Marder, S R; Henneberger, F; Koch, N

    2015-04-15

    The fundamental limits of inorganic semiconductors for light emitting applications, such as holographic displays, biomedical imaging and ultrafast data processing and communication, might be overcome by hybridization with their organic counterparts, which feature enhanced frequency response and colour range. Innovative hybrid inorganic/organic structures exploit efficient electrical injection and high excitation density of inorganic semiconductors and subsequent energy transfer to the organic semiconductor, provided that the radiative emission yield is high. An inherent obstacle to that end is the unfavourable energy level offset at hybrid inorganic/organic structures, which rather facilitates charge transfer that quenches light emission. Here, we introduce a technologically relevant method to optimize the hybrid structure's energy levels, here comprising ZnO and a tailored ladder-type oligophenylene. The ZnO work function is substantially lowered with an organometallic donor monolayer, aligning the frontier levels of the inorganic and organic semiconductors. This increases the hybrid structure's radiative emission yield sevenfold, validating the relevance of our approach.

  7. Efficient light emission from inorganic and organic semiconductor hybrid structures by energy-level tuning

    Science.gov (United States)

    Schlesinger, R.; Bianchi, F.; Blumstengel, S.; Christodoulou, C.; Ovsyannikov, R.; Kobin, B.; Moudgil, K.; Barlow, S.; Hecht, S.; Marder, S.R.; Henneberger, F.; Koch, N.

    2015-01-01

    The fundamental limits of inorganic semiconductors for light emitting applications, such as holographic displays, biomedical imaging and ultrafast data processing and communication, might be overcome by hybridization with their organic counterparts, which feature enhanced frequency response and colour range. Innovative hybrid inorganic/organic structures exploit efficient electrical injection and high excitation density of inorganic semiconductors and subsequent energy transfer to the organic semiconductor, provided that the radiative emission yield is high. An inherent obstacle to that end is the unfavourable energy level offset at hybrid inorganic/organic structures, which rather facilitates charge transfer that quenches light emission. Here, we introduce a technologically relevant method to optimize the hybrid structure's energy levels, here comprising ZnO and a tailored ladder-type oligophenylene. The ZnO work function is substantially lowered with an organometallic donor monolayer, aligning the frontier levels of the inorganic and organic semiconductors. This increases the hybrid structure's radiative emission yield sevenfold, validating the relevance of our approach. PMID:25872919

  8. Development of DEMO-FNS tokamak for fusion and hybrid technologies

    Science.gov (United States)

    Kuteev, B. V.; Azizov, E. A.; Alexeev, P. N.; Ignatiev, V. V.; Subbotin, S. A.; Tsibulskiy, V. F.

    2015-07-01

    The history of fusion-fission hybrid systems based on a tokamak device as an extremely efficient DT-fusion neutron source has passed through several periods of ample research activity in the world since the very beginning of fusion research in the 1950s. Recently, a new roadmap of the hybrid program has been proposed with the goal to build a pilot hybrid plant (PHP) in Russia by 2030. Development of the DEMO-FNS tokamak for fusion and hybrid technologies, which is planned to be built by 2023, is the key milestone on the path to the PHP. This facility is in the phase of conceptual design aimed at providing feasibility studies for a full set of steady state tokamak technologies at a fusion energy gain factor Q ˜ 1, fusion power of ˜40 MW and opportunities for testing a wide range of hybrid technologies with the emphasis on continuous nuclide processing in molten salts. This paper describes the project motivations, its current status and the key issues of the design.

  9. 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....

  10. 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...

  11. All Set! Evidence of Simultaneous Attentional Control Settings for Multiple Target Colors

    Science.gov (United States)

    Irons, Jessica L.; Folk, Charles L.; Remington, Roger W.

    2012-01-01

    Although models of visual search have often assumed that attention can only be set for a single feature or property at a time, recent studies have suggested that it may be possible to maintain more than one attentional control setting. The aim of the present study was to investigate whether spatial attention could be guided by multiple attentional…

  12. Hybrid rendering of the chest and virtual bronchoscopy [corrected].

    Science.gov (United States)

    Seemann, M D; Seemann, O; Luboldt, W; Gebicke, K; Prime, G; Claussen, C D

    2000-10-30

    Thin-section spiral computed tomography was used to acquire the volume data sets of the thorax. The tracheobronchial system and pathological changes of the chest were visualized using a color-coded surface rendering method. The structures of interest were then superimposed on a volume rendering of the other thoracic structures, thus producing a hybrid rendering. The hybrid rendering technique exploit the advantages of both rendering methods and enable virtual bronchoscopic examinations using different representation models. Virtual bronchoscopic examinations with a transparent color-coded shaded-surface model enables the simultaneous visualization of both the airways and the adjacent structures behind of the tracheobronchial wall and therefore, offers a practical alternative to fiberoptic bronchoscopy. Hybrid rendering and virtual endoscopy obviate the need for time consuming detailed analysis and presentation of axial source images.

  13. 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.

  14. Genome-Wide Prediction of the Performance of Three-Way Hybrids in Barley

    Directory of Open Access Journals (Sweden)

    Zuo Li

    2017-03-01

    Full Text Available Predicting the grain yield performance of three-way hybrids is challenging. Three-way crosses are relevant for hybrid breeding in barley ( L. and maize ( L. adapted to East Africa. The main goal of our study was to implement and evaluate genome-wide prediction approaches of the performance of three-way hybrids using data of single-cross hybrids for a scenario in which parental lines of the three-way hybrids originate from three genetically distinct subpopulations. We extended the ridge regression best linear unbiased prediction (RRBLUP and devised a genomic selection model allowing for subpopulation-specific marker effects (GSA-RRBLUP: general and subpopulation-specific additive RRBLUP. Using an empirical barley data set, we showed that applying GSA-RRBLUP tripled the prediction ability of three-way hybrids from 0.095 to 0.308 compared with RRBLUP, modeling one additive effect for all three subpopulations. The experimental findings were further substantiated with computer simulations. Our results emphasize the potential of GSA-RRBLUP to improve genome-wide hybrid prediction of three-way hybrids for scenarios of genetically diverse parental populations. Because of the advantages of the GSA-RRBLUP model in dealing with hybrids from different parental populations, it may also be a promising approach to boost the prediction ability for hybrid breeding programs based on genetically diverse heterotic groups.

  15. 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.

  16. Hybrid plasmonic bullseye antennas for efficient photon collection

    DEFF Research Database (Denmark)

    Andersen, Sebastian Kim Hjælm; Bozhevolnyi, Sergey I.; Shalaev, Vladimir M.

    2018-01-01

    We propose highly efficient hybrid plasmonic bullseye antennas for collecting photon emission from nm sized quantum emitters. In our approach, the emitter radiation is coupled to surface plasmon polaritons that are consequently converted into highly directional out-of-plane emission. The proposed...... configuration consists of a high-index titania bullseye grating separated from a planar silver film by a thin low-index silica spacer layer. Such hybrid systems are theoretically capable of directing 85% of the dipole emission into a 0.9 NA objective, while featuring a spectrally narrow-band tunable decay rate...... stable operation. For experimental characterization of the antenna properties, a fluorescent nanodiamond containing multiple nitrogen vacancy centers (NV-center) was deterministically placed in the bullseye center, using an atomic force microscope. Probing the NV-center fluorescence we demonstrate...

  17. COED Transactions, Vol. X, No. 9, September 1978. Use of the Analog/Hybrid Computer in Boundary Layer and Convection Studies.

    Science.gov (United States)

    Mitchell, Eugene E., Ed.

    In certain boundary layer or natural convection work, where a similarity transformation is valid, the equations can be reduced to a set of nonlinear ordinary differential equations. They are therefore well-suited to a fast solution on an analog/hybrid computer. This paper illustrates such usage of the analog/hybrid computer by a set of…

  18. Keyhole behavior and liquid flow in molten pool during laser-arc hybrid welding

    Science.gov (United States)

    Naito, Yasuaki; Katayama, Seiji; Matsunawa, Akira

    2003-03-01

    Hybrid welding was carried out on Type 304 stainless steel plate under various conditions using YAG laser combined with TIG arc. During arc and laser-arc hybrid welding, arc voltage variation was measured, and arc plasma, laser-induced plume and evaporation spots as well as keyhole behavior and liquid flow in the molten pool were observed through CCD camera and X-ray real-time transmission apparatus. It was consequently found that hybrid welding possessed many features in comparison with YAG laser welding. The deepest weld bead could be produced when the YAG laser beam of high power density was shot on the molten pool made beforehand stably with TIG arc. A keyhole was long and narrow, and its behavior was rather stable inside the molten pool. It was also confirmed that porosity was reduced by the suppression of bubble formation in hybrid welding utilizing a laser of a moderate power density.

  19. 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....

  20. Experimental evaluation of hybrid propulsion rocket engine operating with paraffin fuel grain and gaseous oxygen

    OpenAIRE

    Genivaldo Pimenta dos Santos

    2014-01-01

    In the last decade the hybrid propulsion has been considering as a viable alternative of chemical energy conversion stored in propellants into kinetic energy. This energy is applied in propulsive systems of manned platforms, maneuvering procedures and even in the repositioning process of micro satellites. It presents attractive features and good balance between performance and environmental impact. Paraffin based grains are the hybrid solid fuels appointed as polymeric fuel substitute. The li...

  1. What goes through the gate? Exploring interference with visual feature binding.

    Science.gov (United States)

    Ueno, Taiji; Mate, Judit; Allen, Richard J; Hitch, Graham J; Baddeley, Alan D

    2011-05-01

    A series of experiments explored the mechanisms determining the encoding and storage of features and objects in visual working memory. We contrasted the effects of three types of visual suffix on cued recall of a display of colored shapes. The suffix was presented after the display and before the recall cue. The latter was either the color or shape of one of the objects and signaled recall of the object's other feature. In Experiments 1 and 2, we found a larger effect of 'plausible' suffixes comprising features (color and shape) drawn from the experimental set, relative to the effect of 'implausible' suffixes comprising features outside the experimental set. Experiment 3 extended this pattern by showing that 'semi-plausible' suffixes containing only one feature (either color or shape) from the experimental set had an equivalent effect to those with both features from the set. Reduction in accuracy was mainly due to an increase in recall of suffix features, rather than within-display confusions. The findings suggest a feature-based filtering process in visual working memory, with any stimuli that pass through this filter serving to directly overwrite existing object representations. Copyright © 2011 Elsevier Ltd. All rights reserved.

  2. 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

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

    Science.gov (United States)

    Zha, Xuan Fang; Sriram, Ram D.

    2004-11-01

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

  4. Transient behaviour and coupling aspects of a hybrid MSF-RO nuclear desalination plant

    International Nuclear Information System (INIS)

    Tewari, P.K.; Misra, B.M.

    1998-01-01

    BARC is setting up a 6300 M 3 /day (1.4 MGD) hybrid MSF-RO nuclear desalination plant for sea water desalination at Madras Atomic Power Station (MAPS) coupled to a 170 MWe Pressurised Heavy Water Reactor (PHWR). The transient behaviour and coupling aspects of this dual purpose plant has been discussed. A hybrid desalination plant appears to offer high availability factor. (author)

  5. The design of the Jet lower hybrid launcher

    International Nuclear Information System (INIS)

    Kaye, A.S.; Brinkschulte, H.; Evans, G.; Gormezano, C.; Jacquinot, J.; Knowlton, S.; Pain, M.; Plancoulaine, J.; Walker, C.; Wilson, G.; Litaudon, X.; Moreau, D.

    1989-01-01

    A large lower hybrid current drive launcher has been designed for coupling 12 MW of 3.7 GHz power to the JET plasma for 20 second pulses. The launcher utilises the multijunction technique to achieve 384 waveguides at the grill mouth in a single JET port. The design features of this launcher are described with details of the principal components and the results of high power RF tests of these components

  6. A general model of distant hybridization reveals the conditions for extinction in Atlantic salmon and brown trout.

    Science.gov (United States)

    Quilodrán, Claudio S; Currat, Mathias; Montoya-Burgos, Juan I

    2014-01-01

    Interspecific hybridization is common in nature but can be increased in frequency or even originated by human actions, such as species introduction or habitat modification, which may threaten species persistence. When hybridization occurs between distantly related species, referred to as "distant hybridization," the resulting hybrids are generally infertile or fertile but do not undergo chromosomal recombination during gametogenesis. Here, we present a model describing this frequent but poorly studied interspecific hybridization to assess its consequences on parental species and to anticipate the conditions under which they can reach extinction. Our general model fully incorporates three important processes: density-dependent competition, dominance/recessivity inheritance of traits and assortative mating. We demonstrate its use and flexibility by assessing population extinction risk between Atlantic salmon and brown trout in Norway, whose interbreeding has recently increased due to farmed fish releases into the wild. We identified the set of conditions under which hybridization may threaten salmonid species. Thanks to the flexibility of our model, we evaluated the effect of an additional risk factor, a parasitic disease, and showed that the cumulative effects dramatically increase the extinction risk. The consequences of distant hybridization are not genetically, but demographically mediated. Our general model is useful to better comprehend the evolution of such hybrid systems and we demonstrated its importance in the field of conservation biology to set up management recommendations when this increasingly frequent type of hybridization is in action.

  7. A General Model of Distant Hybridization Reveals the Conditions for Extinction in Atlantic Salmon and Brown Trout

    Science.gov (United States)

    Quilodrán, Claudio S.; Currat, Mathias; Montoya-Burgos, Juan I.

    2014-01-01

    Interspecific hybridization is common in nature but can be increased in frequency or even originated by human actions, such as species introduction or habitat modification, which may threaten species persistence. When hybridization occurs between distantly related species, referred to as “distant hybridization,” the resulting hybrids are generally infertile or fertile but do not undergo chromosomal recombination during gametogenesis. Here, we present a model describing this frequent but poorly studied interspecific hybridization to assess its consequences on parental species and to anticipate the conditions under which they can reach extinction. Our general model fully incorporates three important processes: density-dependent competition, dominance/recessivity inheritance of traits and assortative mating. We demonstrate its use and flexibility by assessing population extinction risk between Atlantic salmon and brown trout in Norway, whose interbreeding has recently increased due to farmed fish releases into the wild. We identified the set of conditions under which hybridization may threaten salmonid species. Thanks to the flexibility of our model, we evaluated the effect of an additional risk factor, a parasitic disease, and showed that the cumulative effects dramatically increase the extinction risk. The consequences of distant hybridization are not genetically, but demographically mediated. Our general model is useful to better comprehend the evolution of such hybrid systems and we demonstrated its importance in the field of conservation biology to set up management recommendations when this increasingly frequent type of hybridization is in action. PMID:25003336

  8. A general model of distant hybridization reveals the conditions for extinction in Atlantic salmon and brown trout.

    Directory of Open Access Journals (Sweden)

    Claudio S Quilodrán

    Full Text Available Interspecific hybridization is common in nature but can be increased in frequency or even originated by human actions, such as species introduction or habitat modification, which may threaten species persistence. When hybridization occurs between distantly related species, referred to as "distant hybridization," the resulting hybrids are generally infertile or fertile but do not undergo chromosomal recombination during gametogenesis. Here, we present a model describing this frequent but poorly studied interspecific hybridization to assess its consequences on parental species and to anticipate the conditions under which they can reach extinction. Our general model fully incorporates three important processes: density-dependent competition, dominance/recessivity inheritance of traits and assortative mating. We demonstrate its use and flexibility by assessing population extinction risk between Atlantic salmon and brown trout in Norway, whose interbreeding has recently increased due to farmed fish releases into the wild. We identified the set of conditions under which hybridization may threaten salmonid species. Thanks to the flexibility of our model, we evaluated the effect of an additional risk factor, a parasitic disease, and showed that the cumulative effects dramatically increase the extinction risk. The consequences of distant hybridization are not genetically, but demographically mediated. Our general model is useful to better comprehend the evolution of such hybrid systems and we demonstrated its importance in the field of conservation biology to set up management recommendations when this increasingly frequent type of hybridization is in action.

  9. Task representation in individual and joint settings

    Directory of Open Access Journals (Sweden)

    Wolfgang ePrinz

    2015-05-01

    Full Text Available This paper outlines a framework for task representation and discusses applications to interference tasks in individual and joint settings. The framework is derived from the Theory of Event Coding. This theory regards task sets as transient assemblies of event codes in which stimulus and response codes interact and shape each other in particular ways. On the one hand, stimulus and response codes compete with each other within their respective subsets (horizontal interactions. On the other hand, stimulus and response code cooperate with each other (vertical interactions. Code interactions instantiating competition and cooperation apply to two time scales: on-line performance (i.e., doing the task and off-line implementation (i.e., setting the task. Interference arises when stimulus and response codes overlap in features that are irrelevant for stimulus identification, but relevant for response selection. To resolve this dilemma, the feature profiles of event codes may become restructured in various ways. The framework is applied to three kinds of interference paradigms. Special emphasis is given to joint settings where tasks are shared between two participants. Major conclusions derived from these applications include: (1 Response competition is the chief driver of interference. Likewise, different modes of response competition give rise to different patterns of interference. (2 The type of features in which stimulus and response codes overlap is also a crucial factor. Different types of such features give likewise rise to different patterns of interference. (3 Task sets for joint settings conflate intraindividual conflicts between responses (what, with interindividual conflicts between responding agents (whom. Features of response codes may, therefore, not only address responses, but also responding agents (both physically and socially.

  10. Task representation in individual and joint settings

    Science.gov (United States)

    Prinz, Wolfgang

    2015-01-01

    This paper outlines a framework for task representation and discusses applications to interference tasks in individual and joint settings. The framework is derived from the Theory of Event Coding (TEC). This theory regards task sets as transient assemblies of event codes in which stimulus and response codes interact and shape each other in particular ways. On the one hand, stimulus and response codes compete with each other within their respective subsets (horizontal interactions). On the other hand, stimulus and response code cooperate with each other (vertical interactions). Code interactions instantiating competition and cooperation apply to two time scales: on-line performance (i.e., doing the task) and off-line implementation (i.e., setting the task). Interference arises when stimulus and response codes overlap in features that are irrelevant for stimulus identification, but relevant for response selection. To resolve this dilemma, the feature profiles of event codes may become restructured in various ways. The framework is applied to three kinds of interference paradigms. Special emphasis is given to joint settings where tasks are shared between two participants. Major conclusions derived from these applications include: (1) Response competition is the chief driver of interference. Likewise, different modes of response competition give rise to different patterns of interference; (2) The type of features in which stimulus and response codes overlap is also a crucial factor. Different types of such features give likewise rise to different patterns of interference; and (3) Task sets for joint settings conflate intraindividual conflicts between responses (what), with interindividual conflicts between responding agents (whom). Features of response codes may, therefore, not only address responses, but also responding agents (both physically and socially). PMID:26029085

  11. 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.

  12. Energy savings potential of a hybrid desiccant dehumidification air conditioning system in Beirut

    International Nuclear Information System (INIS)

    Ghali, Kamel

    2008-01-01

    In this work, the transient performance of a hybrid desiccant vapor compression air conditioning system is numerically simulated for the ambient conditions of Beirut. The main feature of this hybrid system is that the regenerative heat needed by the desiccant wheel is partly supplied by the condenser dissipated heat while the rest is supplied by an auxiliary gas heater. The hybrid air conditioning system of the present study replaces a 23 kW vapor compression unit for a typical office in Beirut characterized by a high latent load. The vapor compression subsystem size in the hybrid air conditioning system is reduced to 15 kW at the peak load when the regeneration temperature was fixed at 75 deg. C. Also the sensible heat ratio of the combined hybrid system increased from 0.47 to 0.73. Based on hour by hour simulation studies for a wide range of recorded ambient conditions of Beirut city, this paper predicts the annual energy consumption of the hybrid system in comparison with the conventional vapor compression system for the entire cooling season. The annual running costs savings for the hybrid system is 418.39 USD for a gas cost price of 0.141 USD/kg. The pay back period of the hybrid system is less than five years when the initial cost of the hybrid air conditioning system priced an additional 1712.00 USD. Hence, for a 20-year life cycle, the life cycle savings of the hybrid air conditioning system are 4295.19 USD

  13. Quality control considerations for the development of the front end hybrid circuits for the CMS Outer Tracker upgrade

    CERN Document Server

    Gadek, Tomasz; Bonnaud, Julien Yves Robert; De Clercq, Jarne Theo; Honma, Alan; Koliatos, Alexandros; Kovacs, Mark Istvan; Luetic, Jelena

    2017-01-01

    The upgrade of the CMS Outer Tracker for the HL-LHC requires the design of new double-sensor modules. They contain two high-density front end hybrid circuits, equipped with flip-chip ASICs, passives and mechanical structures. First prototype hybrids in a close-to-final form have been ordered from three manufacturers. To qualify these hybrids a test setup was built, which emulates future tracker temperature and humidity conditions, provides temporary interconnection, and implements testing features. The system was automated to minimize the testing time in view of the production phase. Failure modes, deliberately implemented in the produced hybrids, provided feedback on the system’s effectiveness.

  14. 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.

  15. 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.

  16. data sets Simulations in articulating light-weight PRS

    NARCIS (Netherlands)

    Van den Berg, Bert

    2008-01-01

    The data sets are output of 3 different steps in the development a simulations of a PRS as described in chapter 3.3: Simulations in articulating light-weight PRS A case for Pedagogy-oriented and Rating-based Hybrid Recommendation Strategies Rob Nadolski, Bert van den Berg, Adriana Berlanga, Hans

  17. Approximation of a Common Element of the Fixed Point Sets of Multivalued Strictly Pseudocontractive-Type Mappings and the Set of Solutions of an Equilibrium Problem in Hilbert Spaces

    Directory of Open Access Journals (Sweden)

    F. O. Isiogugu

    2016-01-01

    Full Text Available The strong convergence of a hybrid algorithm to a common element of the fixed point sets of multivalued strictly pseudocontractive-type mappings and the set of solutions of an equilibrium problem in Hilbert spaces is obtained using a strict fixed point set condition. The obtained results improve, complement, and extend the results on multivalued and single-valued mappings in the contemporary literature.

  18. 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.

  19. Super-resolution nanofabrication with metal-ion doped hybrid material through an optical dual-beam approach

    International Nuclear Information System (INIS)

    Cao, Yaoyu; Li, Xiangping; Gu, Min

    2014-01-01

    We apply an optical dual-beam approach to a metal-ion doped hybrid material to achieve nanofeatures beyond the optical diffraction limit. By spatially inhibiting the photoreduction and the photopolymerization, we realize a nano-line, consisting of polymer matrix and in-situ generated gold nanoparticles, with a lateral size of sub 100 nm, corresponding to a factor of 7 improvement compared to the diffraction limit. With the existence of gold nanoparticles, a plasmon enhanced super-resolution fabrication mechanism in the hybrid material is observed, which benefits in a further reduction in size of the fabricated feature. The demonstrated nanofeature in hybrid materials paves the way for realizing functional nanostructures

  20. 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...

  1. Disruption of visual feature binding in working memory.

    Science.gov (United States)

    Ueno, Taiji; Allen, Richard J; Baddeley, Alan D; Hitch, Graham J; Saito, Satoru

    2011-01-01

    In a series of five experiments, we studied the effect of a visual suffix on the retention in short-term visual memory of both individual visual features and objects involving the binding of two features. Experiments 1A, 1B, and 2 involved suffixes consisting of features external to the to-be-remembered set and revealed a modest but equivalent disruption on individual and bound feature conditions. Experiments 3A and 3B involved suffixes comprising features that could potentially have formed part of the to-be-remembered set (but did not on that trial). Both experiments showed greater disruption of retention for objects comprising bound features than for their individual features. The results are interpreted as differentiating two components of suffix interference, one affecting memory for features and bindings equally, the other affecting memory for bindings. The general component is tentatively identified with the attentional cost of operating a filter to prevent the suffix from entering visual working memory, whereas the specific component is attributed to the particular fragility of bound representations when the filter fails.

  2. Operational characteristics of hybrid-type SFCL with closed and open cores

    International Nuclear Information System (INIS)

    Cho, Y.S.; Lee, N.Y.; Choi, H.S.; Chung, D.C.; Lim, S.H.

    2007-01-01

    We investigated the operational characteristics of the hybrid-type superconducting fault current limiter (SFCL) with the closed and the open cores, which induced the variation of the magnetic flux between the primary and the secondary windings. The experimental set-up of the hybrid-type SFCL with the closed and the open cores were prepared and the experimental analyses for the current limiting characteristics were performed. The peak value of the fault current in the hybrid-type SFCL with the open core was higher than that of the closed core at the first cycle after fault occurrence. However, in the case of the hybrid-type SFCL with the open core, the limiting current level after fault occurrence was decreased less than that of the hybrid-type SFCL with the closed core, because the magnetic leakage reluctance of the open core was higher than that of the closed core. The quench time (T q ) and the arrival time (T a ) for the peak voltage (V SC ) in the hybrid-type SFCL with the closed core were faster than that of the hybrid-type SFCL with the open core due to the increase of the mutual flux. We verified that the consumption power in the hybrid-type SFCL with the open core was larger owing to the increase of leakage flux by the reduction of mutual inductance between primary and secondary windings

  3. 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.

  4. Energy-Saving Traffic Scheduling in Hybrid Software Defined Wireless Rechargeable Sensor Networks.

    Science.gov (United States)

    Wei, Yunkai; Ma, Xiaohui; Yang, Ning; Chen, Yijin

    2017-09-15

    Software Defined Wireless Rechargeable Sensor Networks (SDWRSNs) are an inexorable trend for Wireless Sensor Networks (WSNs), including Wireless Rechargeable Sensor Network (WRSNs). However, the traditional network devices cannot be completely substituted in the short term. Hybrid SDWRSNs, where software defined devices and traditional devices coexist, will last for a long time. Hybrid SDWRSNs bring new challenges as well as opportunities for energy saving issues, which is still a key problem considering that the wireless chargers are also exhaustible, especially in some rigid environment out of the main supply. Numerous energy saving schemes for WSNs, or even some works for WRSNs, are no longer suitable for the new features of hybrid SDWRSNs. To solve this problem, this paper puts forward an Energy-saving Traffic Scheduling (ETS) algorithm. The ETS algorithm adequately considers the new characters in hybrid SDWRSNs, and takes advantage of the Software Defined Networking (SDN) controller's direct control ability on SDN nodes and indirect control ability on normal nodes. The simulation results show that, comparing with traditional Minimum Transmission Energy (MTE) protocol, ETS can substantially improve the energy efficiency in hybrid SDWRSNs for up to 20-40% while ensuring feasible data delay.

  5. Energy-Saving Traffic Scheduling in Hybrid Software Defined Wireless Rechargeable Sensor Networks

    Directory of Open Access Journals (Sweden)

    Yunkai Wei

    2017-09-01

    Full Text Available Software Defined Wireless Rechargeable Sensor Networks (SDWRSNs are an inexorable trend for Wireless Sensor Networks (WSNs, including Wireless Rechargeable Sensor Network (WRSNs. However, the traditional network devices cannot be completely substituted in the short term. Hybrid SDWRSNs, where software defined devices and traditional devices coexist, will last for a long time. Hybrid SDWRSNs bring new challenges as well as opportunities for energy saving issues, which is still a key problem considering that the wireless chargers are also exhaustible, especially in some rigid environment out of the main supply. Numerous energy saving schemes for WSNs, or even some works for WRSNs, are no longer suitable for the new features of hybrid SDWRSNs. To solve this problem, this paper puts forward an Energy-saving Traffic Scheduling (ETS algorithm. The ETS algorithm adequately considers the new characters in hybrid SDWRSNs, and takes advantage of the Software Defined Networking (SDN controller’s direct control ability on SDN nodes and indirect control ability on normal nodes. The simulation results show that, comparing with traditional Minimum Transmission Energy (MTE protocol, ETS can substantially improve the energy efficiency in hybrid SDWRSNs for up to 20–40% while ensuring feasible data delay.

  6. Short-Term Planning of Hybrid Power System

    Science.gov (United States)

    Knežević, Goran; Baus, Zoran; Nikolovski, Srete

    2016-07-01

    In this paper short-term planning algorithm for hybrid power system consist of different types of cascade hydropower plants (run-of-the river, pumped storage, conventional), thermal power plants (coal-fired power plants, combined cycle gas-fired power plants) and wind farms is presented. The optimization process provides a joint bid of the hybrid system, and thus making the operation schedule of hydro and thermal power plants, the operation condition of pumped-storage hydropower plants with the aim of maximizing profits on day ahead market, according to expected hourly electricity prices, the expected local water inflow in certain hydropower plants, and the expected production of electrical energy from the wind farm, taking into account previously contracted bilateral agreement for electricity generation. Optimization process is formulated as hourly-discretized mixed integer linear optimization problem. Optimization model is applied on the case study in order to show general features of the developed model.

  7. A Survey on Evolutionary Algorithm Based Hybrid Intelligence in Bioinformatics

    Directory of Open Access Journals (Sweden)

    Shan Li

    2014-01-01

    Full Text Available With the rapid advance in genomics, proteomics, metabolomics, and other types of omics technologies during the past decades, a tremendous amount of data related to molecular biology has been produced. It is becoming a big challenge for the bioinformatists to analyze and interpret these data with conventional intelligent techniques, for example, support vector machines. Recently, the hybrid intelligent methods, which integrate several standard intelligent approaches, are becoming more and more popular due to their robustness and efficiency. Specifically, the hybrid intelligent approaches based on evolutionary algorithms (EAs are widely used in various fields due to the efficiency and robustness of EAs. In this review, we give an introduction about the applications of hybrid intelligent methods, in particular those based on evolutionary algorithm, in bioinformatics. In particular, we focus on their applications to three common problems that arise in bioinformatics, that is, feature selection, parameter estimation, and reconstruction of biological networks.

  8. Are Haar-like Rectangular Features for Biometric Recognition Reducible?

    DEFF Research Database (Denmark)

    Nasrollahi, Kamal; Moeslund, Thomas B.

    2013-01-01

    Biometric recognition is still a very difficult task in real-world scenarios wherein unforeseen changes in degradations factors like noise, occlusion, blurriness and illumination can drastically affect the extracted features from the biometric signals. Very recently Haar-like rectangular features...... which have usually been used for object detection were introduced for biometric recognition resulting in systems that are robust against most of the mentioned degradations [9]. The problem with these features is that one can define many different such features for a given biometric signal...... and it is not clear whether all of these features are required for the actual recognition or not. This is exactly what we are dealing with in this paper: How can an initial set of Haar-like rectangular features, that have been used for biometric recognition, be reduced to a set of most influential features...

  9. Automatic feature design for optical character recognition using an evolutionary search procedure.

    Science.gov (United States)

    Stentiford, F W

    1985-03-01

    An automatic evolutionary search is applied to the problem of feature extraction in an OCR application. A performance measure based on feature independence is used to generate features which do not appear to suffer from peaking effects [17]. Features are extracted from a training set of 30 600 machine printed 34 class alphanumeric characters derived from British mail. Classification results on the training set and a test set of 10 200 characters are reported for an increasing number of features. A 1.01 percent forced decision error rate is obtained on the test data using 316 features. The hardware implementation should be cheap and fast to operate. The performance compares favorably with current low cost OCR page readers.

  10. Hybrid Ground-Source Heat Pump Installations: Experiences, Improvements, and Tools

    Energy Technology Data Exchange (ETDEWEB)

    Scott Hackel; Amanda Pertzborn

    2011-06-30

    One innovation to ground-source heat pump (GSHP, or GHP) systems is the hybrid GSHP (HyGSHP) system, which can dramatically decrease the first cost of GSHP systems by using conventional technology (such as a cooling tower or a boiler) to meet a portion of the peak heating or cooling load. This work uses three case studies (two cooling-dominated, one heating-dominated) to demonstrate the performance of the hybrid approach. Three buildings were studied for a year; the measured data was used to validate models of each system. The models were used to analyze further improvements to the hybrid approach, and establish that this approach has positive impacts, both economically and environmentally. Lessons learned by those who design and operate the systems are also documented, including discussions of equipment sizing, pump operation, and cooling tower control. Finally, the measured data sets and models that were created during this work are described; these materials have been made freely available for further study of hybrid systems.

  11. Structural Interplay - Tuning Mechanics in Peptide-Polyurea Hybrids

    Science.gov (United States)

    Korley, Lashanda

    hydrogen bonding and morphology. These structural features correlated well with systematic changes in modulus, extensibility, and hysteresis. Complementary to this effort is the design of PEG-based peptide-polyurea hybrids with tunable and responsive as structural and injectable hydrogels. The authors acknowledge funding support from the National Science Foundation (CAREER DMR-0953236).

  12. Mechanical properties and production quality of hand-layup and vacuum infusion processed hybrid composite materials for GFRP marine structures

    Science.gov (United States)

    Kim, Sang-Young; Shim, Chun Sik; Sturtevant, Caleb; Kim, Dave (Dae-Wook); Song, Ha Cheol

    2014-09-01

    Glass Fiber Reinforced Plastic (GFRP) structures are primarily manufactured using hand lay-up or vacuum infusion techniques, which are cost-effective for the construction of marine vessels. This paper aims to investigate the mechanical properties and failure mechanisms of the hybrid GFRP composites, formed by applying the hand lay-up processed exterior and the vacuum infusion processed interior layups, providing benefits for structural performance and ease of manufacturing. The hybrid GFRP composites contain one, two, and three vacuum infusion processed layer sets with consistent sets of hand lay-up processed layers. Mechanical properties assessed in this study include tensile, compressive and in-plane shear properties. Hybrid composites with three sets of vacuum infusion layers showed the highest tensile mechanical properties while those with two sets had the highest mechanical properties in compression. The batch homogeneity, for the GFRP fabrication processes, is evaluated using the experimentally obtained mechanical properties

  13. Mechanical properties and production quality of hand-layup and vacuum infusion processed hybrid composite materials for GFRP marine structures

    Directory of Open Access Journals (Sweden)

    Kim Sang-Young

    2014-09-01

    Full Text Available Glass Fiber Reinforced Plastic (GFRP structures are primarily manufactured using hand lay-up or vacuum infusion techniques, which are cost-effective for the construction of marine vessels. This paper aims to investigate the mechanical properties and failure mechanisms of the hybrid GFRP composites, formed by applying the hand lay-up processed exterior and the vacuum infusion processed interior layups, providing benefits for structural performance and ease of manufacturing. The hybrid GFRP composites contain one, two, and three vacuum infusion processed layer sets with consistent sets of hand lay-up processed layers. Mechanical properties assessed in this study include tensile, compressive and in-plane shear properties. Hybrid composites with three sets of vacuum infusion layers showed the highest tensile mechanical properties while those with two sets had the highest mechanical properties in compression. The batch homogeneity, for the GFRP fabrication processes, is evaluated using the experimentally obtained mechanical properties

  14. Mechanical properties and production quality of hand-layup and vacuum infusion processed hybrid composite materials for GFRP marine structures

    Directory of Open Access Journals (Sweden)

    Sang-Young Kim

    2014-09-01

    Full Text Available Glass Fiber Reinforced Plastic (GFRP structures are primarily manufactured using hand lay-up or vacuum infusion techniques, which are cost-effective for the construction of marine vessels. This paper aims to investigate the mechanical properties and failure mechanisms of the hybrid GFRP composites, formed by applying the hand lay-up processed exterior and the vacuum infusion processed interior layups, providing benefits for structural performance and ease of manufacturing. The hybrid GFRP composites contain one, two, and three vacuum infusion processed layer sets with consistent sets of hand lay-up processed layers. Mechanical properties assessed in this study include tensile, compressive and in-plane shear properties. Hybrid composites with three sets of vacuum infusion layers showed the highest tensile mechanical properties while those with two sets had the highest mechanical properties in compression. The batch homogeneity, for the GFRP fabrication processes, is evaluated using the experimentally obtained mechanical properties.

  15. Optimal Energy Control Strategy Design for a Hybrid Electric Vehicle

    Directory of Open Access Journals (Sweden)

    Yuan Zou

    2013-01-01

    Full Text Available A heavy-duty parallel hybrid electric truck is modeled, and its optimal energy control is studied in this paper. The fundamental architecture of the parallel hybrid electric truck is modeled feed-forwardly, together with necessary dynamic features of subsystem or components. Dynamic programming (DP technique is adopted to find the optimal control strategy including the gear-shifting sequence and the power split between the engine and the motor subject to a battery SOC-sustaining constraint. Improved control rules are extracted from the DP-based control solution, forming near-optimal control strategies. Simulation results demonstrate that a significant improvement on the fuel economy can be achieved in the heavy-duty vehicle cycle from the natural driving statistics.

  16. The „Pussy riot“ case and the post-secular hybrids

    Directory of Open Access Journals (Sweden)

    Uzlaner Dmitrij

    2013-01-01

    Full Text Available The article is devoted to the analysis of the “Pussy riot” case and the peculiarities of Russian postsecularism. Special emphasis is placed on the phenomenon of post-secular hybrids, i.e. the overcoming of the situation of social differentiation between religion and other social subsystems (one of the main distinctive features of secularization. It is claimed that the materials of the trial against “Pussy riot” make evident the appearance in Russia of at least three post-secular hybrids: 1 the blending of religion and politics; 2 installation of religious norms into the public order of the secular state; 3 significance of confessional legal experts as part of the new “ideological state apparatus”.

  17. High-level intuitive features (HLIFs) for intuitive skin lesion description.

    Science.gov (United States)

    Amelard, Robert; Glaister, Jeffrey; Wong, Alexander; Clausi, David A

    2015-03-01

    A set of high-level intuitive features (HLIFs) is proposed to quantitatively describe melanoma in standard camera images. Melanoma is the deadliest form of skin cancer. With rising incidence rates and subjectivity in current clinical detection methods, there is a need for melanoma decision support systems. Feature extraction is a critical step in melanoma decision support systems. Existing feature sets for analyzing standard camera images are comprised of low-level features, which exist in high-dimensional feature spaces and limit the system's ability to convey intuitive diagnostic rationale. The proposed HLIFs were designed to model the ABCD criteria commonly used by dermatologists such that each HLIF represents a human-observable characteristic. As such, intuitive diagnostic rationale can be conveyed to the user. Experimental results show that concatenating the proposed HLIFs with a full low-level feature set increased classification accuracy, and that HLIFs were able to separate the data better than low-level features with statistical significance. An example of a graphical interface for providing intuitive rationale is given.

  18. 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.

  19. Genomic Prediction of Sunflower Hybrids Oil Content

    Directory of Open Access Journals (Sweden)

    Brigitte Mangin

    2017-09-01

    Full Text Available Prediction of hybrid performance using incomplete factorial mating designs is widely used in breeding programs including different heterotic groups. Based on the general combining ability (GCA of the parents, predictions are accurate only if the genetic variance resulting from the specific combining ability is small and both parents have phenotyped descendants. Genomic selection (GS can predict performance using a model trained on both phenotyped and genotyped hybrids that do not necessarily include all hybrid parents. Therefore, GS could overcome the issue of unknown parent GCA. Here, we compared the accuracy of classical GCA-based and genomic predictions for oil content of sunflower seeds using several GS models. Our study involved 452 sunflower hybrids from an incomplete factorial design of 36 female and 36 male lines. Re-sequencing of parental lines allowed to identify 468,194 non-redundant SNPs and to infer the hybrid genotypes. Oil content was observed in a multi-environment trial (MET over 3 years, leading to nine different environments. We compared GCA-based model to different GS models including female and male genomic kinships with the addition of the female-by-male interaction genomic kinship, the use of functional knowledge as SNPs in genes of oil metabolic pathways, and with epistasis modeling. When both parents have descendants in the training set, the predictive ability was high even for GCA-based prediction, with an average MET value of 0.782. GS performed slightly better (+0.2%. Neither the inclusion of the female-by-male interaction, nor functional knowledge of oil metabolism, nor epistasis modeling improved the GS accuracy. GS greatly improved predictive ability when one or both parents were untested in the training set, increasing GCA-based predictive ability by 10.4% from 0.575 to 0.635 in the MET. In this scenario, performing GS only considering SNPs in oil metabolic pathways did not improve whole genome GS prediction but

  20. Mathematical Modeling of Hybrid Electrical Engineering Systems

    Directory of Open Access Journals (Sweden)

    A. A. Lobaty

    2016-01-01

    Full Text Available A large class of systems that have found application in various industries and households, electrified transportation facilities and energy sector has been classified as electrical engineering systems. Their characteristic feature is a combination of continuous and discontinuous modes of operation, which is reflected in the appearance of a relatively new term “hybrid systems”. A wide class of hybrid systems is pulsed DC converters operating in a pulse width modulation, which are non-linear systems with variable structure. Using various methods for linearization it is possible to obtain linear mathematical models that rather accurately simulate behavior of such systems. However, the presence in the mathematical models of exponential nonlinearities creates considerable difficulties in the implementation of digital hardware. The solution can be found while using an approximation of exponential functions by polynomials of the first order, that, however, violates the rigor accordance of the analytical model with characteristics of a real object. There are two practical approaches to synthesize algorithms for control of hybrid systems. The first approach is based on the representation of the whole system by a discrete model which is described by difference equations that makes it possible to synthesize discrete algorithms. The second approach is based on description of the system by differential equations. The equations describe synthesis of continuous algorithms and their further implementation in a digital computer included in the control loop system. The paper considers modeling of a hybrid electrical engineering system using differential equations. Neglecting the pulse duration, it has been proposed to describe behavior of vector components in phase coordinates of the hybrid system by stochastic differential equations containing generally non-linear differentiable random functions. A stochastic vector-matrix equation describing dynamics of the