WorldWideScience

Sample records for hybrid generative-discriminative learning

  1. A hybrid generative-discriminative approach to speaker diarization

    NARCIS (Netherlands)

    Noulas, A.K.; van Kasteren, T.; Kröse, B.J.A.

    2008-01-01

    In this paper we present a sound probabilistic approach to speaker diarization. We use a hybrid framework where a distribution over the number of speakers at each point of a multimodal stream is estimated with a discriminative model. The output of this process is used as input in a generative model

  2. Activity Recognition Using Hybrid Generative/Discriminative Models on Home Environments Using Binary Sensors

    Directory of Open Access Journals (Sweden)

    Araceli Sanchis

    2013-04-01

    Full Text Available Activities of daily living are good indicators of elderly health status, and activity recognition in smart environments is a well-known problem that has been previously addressed by several studies. In this paper, we describe the use of two powerful machine learning schemes, ANN (Artificial Neural Network and SVM (Support Vector Machines, within the framework of HMM (Hidden Markov Model in order to tackle the task of activity recognition in a home setting. The output scores of the discriminative models, after processing, are used as observation probabilities of the hybrid approach. We evaluate our approach by comparing these hybrid models with other classical activity recognition methods using five real datasets. We show how the hybrid models achieve significantly better recognition performance, with significance level p < 0:05, proving that the hybrid approach is better suited for the addressed domain.

  3. 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.

  4. Assessment on Hybrid E-Learning Instrument

    OpenAIRE

    Intan Farahana Kamsin; Rosseni Din

    2015-01-01

    This study aims to improve Hybrid e-Learning 9.3. A total of 233 students of International Islamic University Malaysia, Gombak who have the experience in hybrid teaching and learning were involved as respondents. Rasch Measurement Model was used for this study. Validity analyses conducted were on (i) the compatibility of the items, (ii) mapping of items and respondents, (iii) scaling of instruments, and (iv) unidimentional items. The findings of the study show that (i) the items developed cor...

  5. Hybrid e-learning tool TransLearning

    NARCIS (Netherlands)

    Meij, van der Marjoleine G.; Kupper, Frank; Beers, P.J.; Broerse, Jacqueline E.W.

    2016-01-01

    E-learning and storytelling approaches can support informal vicarious learning within geographically widely distributed multi-stakeholder collaboration networks. This case study evaluates hybrid e-learning and video-storytelling approach ‘TransLearning’ by investigation into how its storytelling

  6. Architecture for Collaborative Learning Activities in Hybrid Learning Environments

    OpenAIRE

    Ibáñez, María Blanca; Maroto, David; García Rueda, José Jesús; Leony, Derick; Delgado Kloos, Carlos

    2012-01-01

    3D virtual worlds are recognized as collaborative learning environments. However, the underlying technology is not sufficiently mature and the virtual worlds look cartoonish, unlinked to reality. Thus, it is important to enrich them with elements from the real world to enhance student engagement in learning activities. Our approach is to build learning environments where participants can either be in the real world or in its mirror world while sharing the same hybrid space in a collaborative ...

  7. A Hybrid Teaching and Learning Model

    Science.gov (United States)

    Juhary, Jowati Binti

    This paper aims at analysing the needs for a specific teaching and learning model for the National Defence University of Malaysia (NDUM). The main argument is that whether there are differences between teaching and learning for academic component versus military component at the university. It is further argued that in order to achieve excellence, there should be one teaching and learning culture. Data were collected through interviews with military cadets. It is found that there are variations of teaching and learning strategies for academic courses, in comparison to a dominant teaching and learning style for military courses. Thus, in the interest of delivering quality education and training for students at the university, the paper argues that possibly a hybrid model for teaching and learning is fundamental in order to generate a one culture of academic and military excellence for the NDUM.

  8. Adventure Learning: Theory and Implementation of Hybrid Learning

    Science.gov (United States)

    Doering, A.

    2008-12-01

    Adventure Learning (AL), a hybrid distance education approach, provides students and teachers with the opportunity to learn about authentic curricular content areas while interacting with adventurers, students, and content experts at various locations throughout the world within an online learning environment (Doering, 2006). An AL curriculum and online environment provides collaborative community spaces where traditional hierarchical classroom roles are blurred and learning is transformed. AL has most recently become popular in K-12 classrooms nationally and internationally with millions of students participating online. However, in the literature, the term "adventure learning" many times gets confused with phrases such as "virtual fieldtrip" and activities where someone "exploring" is posting photos and text. This type of "adventure learning" is not "Adventure Learning" (AL), but merely a slideshow of their activities. The learning environment may not have any curricular and/or social goals, and if it does, the environment design many times does not support these objectives. AL, on the other hand, is designed so that both teachers and students understand that their online and curriculum activities are in synch and supportive of the curricular goals. In AL environments, there are no disparate activities as the design considers the educational, social, and technological affordances (Kirschner, Strijbos, Kreijns, & Beers, 2004); in other words, the artifacts of the learning environment encourage and support the instructional goals, social interactions, collaborative efforts, and ultimately learning. AL is grounded in two major theoretical approaches to learning - experiential and inquiry-based learning. As Kolb (1984) noted, in experiential learning, a learner creates meaning from direct experiences and reflections. Such is the goal of AL within the classroom. Additionally, AL affords learners a real-time authentic online learning experience concurrently as they

  9. Applying a Hybrid Model: Can It Enhance Student Learning Outcomes?

    Science.gov (United States)

    Potter, Jodi

    2015-01-01

    There has been a marked increase in the use of online learning over the past decade. There remains conflict in the current body of research on the efficacy of online versus face to face learning in these environments. One resolution of these issues is the hybrid learning option which is a combination of face-to-face classroom instruction with…

  10. Hybrid Teaching in Extension: Learning at the Crossroads

    Science.gov (United States)

    Hino, Jeff; Kahn, Cub

    2016-01-01

    Extension clients' learning preferences are changing, with many increasingly going online for educational content. In response, Oregon State University Extension pilot tested a training program for Extension educators to explore hybrid teaching--a methodology that could provide more flexible access to a wider audience. Hybrid teaching offers a…

  11. 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....

  12. Evaluation of Hybrid and Distance Education Learning Environments in Spain

    Science.gov (United States)

    Ferrer-Cascales, Rosario; Walker, Scott L.; Reig-Ferrer, Abilio; Fernandez-Pascual, Maria Dolores; Albaladejo-Blazquez, Natalia

    2011-01-01

    This article describes the adaptation and validation of the "Distance Education Learning Environments Survey" (DELES) for use in investigating the qualities found in distance and hybrid education psycho-social learning environments in Spain. As Europe moves toward post-secondary student mobility, equanimity in access to higher education,…

  13. Hybrid E-Textbooks as Comprehensive Interactive Learning Environments

    Science.gov (United States)

    Ghaem Sigarchian, Hajar; Logghe, Sara; Verborgh, Ruben; de Neve, Wesley; Salliau, Frank; Mannens, Erik; Van de Walle, Rik; Schuurman, Dimitri

    2018-01-01

    An e-TextBook can serve as an interactive learning environment (ILE), facilitating more effective teaching and learning processes. In this paper, we propose the novel concept of an EPUB 3-based Hybrid e-TextBook, which allows for interaction between the digital and the physical world. In that regard, we first investigated the gap between the…

  14. Hybrid Model for e-Learning Quality Evaluation

    Directory of Open Access Journals (Sweden)

    Suzana M. Savic

    2012-02-01

    Full Text Available E-learning is becoming increasingly important for the competitive advantage of economic organizations and higher education institutions. Therefore, it is becoming a significant aspect of quality which has to be integrated into the management system of every organization or institution. The paper examines e-learning quality characteristics, standards, criteria and indicators and presents a multi-criteria hybrid model for e-learning quality evaluation based on the method of Analytic Hierarchy Process, trend analysis, and data comparison.

  15. Hybrid E-Learning Tool TransLearning: Video Storytelling to Foster Vicarious Learning within Multi-Stakeholder Collaboration Networks

    Science.gov (United States)

    van der Meij, Marjoleine G.; Kupper, Frank; Beers, Pieter J.; Broerse, Jacqueline E. W.

    2016-01-01

    E-learning and storytelling approaches can support informal vicarious learning within geographically widely distributed multi-stakeholder collaboration networks. This case study evaluates hybrid e-learning and video-storytelling approach "TransLearning" by investigation into how its storytelling e-tool supported informal vicarious…

  16. Evaluation of hybrid and distance education learning environments in Spain

    OpenAIRE

    Ferrer-Cascales, Rosario; Walker, Scott L.; Reig-Ferrer, Abilio; Fernández-Pascual, M. Dolores; Albaladejo-Blázquez, Natalia

    2011-01-01

    This article describes the adaptation and validation of the Distance Education Learning Environments Survey (DELES) for use in investigating the qualities found in distance and hybrid education psycho-social learning environments in Spain. As Europe moves toward post-secondary student mobility, equanimity in access to higher education, and more standardised degree programs across the European Higher Education Area (EHEA) the need for a high quality method for continually assessing the excelle...

  17. Hybrid chickadees are deficient in learning and memory.

    Science.gov (United States)

    McQuillan, Michael A; Roth, Timothy C; Huynh, Alex V; Rice, Amber M

    2018-05-01

    Identifying the phenotypes underlying postzygotic reproductive isolation is crucial for fully understanding the evolution and maintenance of species. One potential postzygotic isolating barrier that has rarely been examined is learning and memory ability in hybrids. Learning and memory are important fitness-related traits, especially in scatter-hoarding species, where accurate retrieval of hoarded food is vital for winter survival. Here, we test the hypothesis that learning and memory ability can act as a postzygotic isolating barrier by comparing these traits among two scatter-hoarding songbird species, black-capped (Poecile atricapillus) and Carolina chickadees (Poecile carolinensis), and their naturally occurring hybrids. In an outdoor aviary setting, we find that hybrid chickadees perform significantly worse on an associative learning spatial task and are worse at solving a novel problem compared to both parental species. Deficiencies in learning and memory abilities could therefore contribute to postzygotic reproductive isolation between chickadee species. Given the importance of learning and memory for fitness, our results suggest that these traits may play an important, but as yet overlooked, role in postzygotic reproductive isolation. © 2018 The Author(s). Evolution © 2018 The Society for the Study of Evolution.

  18. Serious Games: improving the Learning Effect with Hybrid Games

    OpenAIRE

    Barhaug, Martin

    2017-01-01

    Previous work at NTNU has sparked an interest in hybrid board games. These kinds of games combine elements in digital and board games together. This has resulted in a platform called AnyBoard, which is a platform that makes it easier for developers to create and develop hybrid board games. The platform was created at NTNU and has been worked on by students and employees at the IDI institute. This thesis aims to investigate this platform, and look at the potential it has to influence learn...

  19. Does the acceptance of hybrid learning affect learning approaches in France?

    Science.gov (United States)

    Marco, Lionel Di; Venot, Alain; Gillois, Pierre

    2017-01-01

    Acceptance of a learning technology affects students' intention to use that technology, but the influence of the acceptance of a learning technology on learning approaches has not been investigated in the literature. A deep learning approach is important in the field of health, where links must be created between skills, knowledge, and habits. Our hypothesis was that acceptance of a hybrid learning model would affect students' way of learning. We analysed these concepts, and their correlations, in the context of a flipped classroom method using a local learning management system. In a sample of all students within a single year of study in the midwifery program (n= 38), we used 3 validated scales to evaluate these concepts (the Study Process Questionnaire, My Intellectual Work Tools, and the Hybrid E-Learning Acceptance Model: Learner Perceptions). Our sample had a positive acceptance of the learning model, but a neutral intention to use it. Students reported that they were distractible during distance learning. They presented a better mean score for the deep approach than for the superficial approach (Paffected by acceptance of a hybrid learning model, due to the flexibility of the tool. However, we identified problems in the students' time utilization, which explains their neutral intention to use the system.

  20. Hybrid and Blended Learning: Modifying Pedagogy across Path, Pace, Time, and Place

    Science.gov (United States)

    O'Byrne, W. Ian; Pytash, Kristine E.

    2015-01-01

    Hybrid or blended learning is defined as a pedagogical approach that includes a combination of face-to-face instruction with computer-mediated instruction. The terms "blended learning", "hybrid learning", and "mixed-mode learning" are used interchangeably in current research; however, in the United States,…

  1. 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.

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

    Science.gov (United States)

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

    2012-01-01

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

  3. Maze learning by a hybrid brain-computer system.

    Science.gov (United States)

    Wu, Zhaohui; Zheng, Nenggan; Zhang, Shaowu; Zheng, Xiaoxiang; Gao, Liqiang; Su, Lijuan

    2016-09-13

    The combination of biological and artificial intelligence is particularly driven by two major strands of research: one involves the control of mechanical, usually prosthetic, devices by conscious biological subjects, whereas the other involves the control of animal behaviour by stimulating nervous systems electrically or optically. However, to our knowledge, no study has demonstrated that spatial learning in a computer-based system can affect the learning and decision making behaviour of the biological component, namely a rat, when these two types of intelligence are wired together to form a new intelligent entity. Here, we show how rule operations conducted by computing components contribute to a novel hybrid brain-computer system, i.e., ratbots, exhibit superior learning abilities in a maze learning task, even when their vision and whisker sensation were blocked. We anticipate that our study will encourage other researchers to investigate combinations of various rule operations and other artificial intelligence algorithms with the learning and memory processes of organic brains to develop more powerful cyborg intelligence systems. Our results potentially have profound implications for a variety of applications in intelligent systems and neural rehabilitation.

  4. Maze learning by a hybrid brain-computer system

    Science.gov (United States)

    Wu, Zhaohui; Zheng, Nenggan; Zhang, Shaowu; Zheng, Xiaoxiang; Gao, Liqiang; Su, Lijuan

    2016-09-01

    The combination of biological and artificial intelligence is particularly driven by two major strands of research: one involves the control of mechanical, usually prosthetic, devices by conscious biological subjects, whereas the other involves the control of animal behaviour by stimulating nervous systems electrically or optically. However, to our knowledge, no study has demonstrated that spatial learning in a computer-based system can affect the learning and decision making behaviour of the biological component, namely a rat, when these two types of intelligence are wired together to form a new intelligent entity. Here, we show how rule operations conducted by computing components contribute to a novel hybrid brain-computer system, i.e., ratbots, exhibit superior learning abilities in a maze learning task, even when their vision and whisker sensation were blocked. We anticipate that our study will encourage other researchers to investigate combinations of various rule operations and other artificial intelligence algorithms with the learning and memory processes of organic brains to develop more powerful cyborg intelligence systems. Our results potentially have profound implications for a variety of applications in intelligent systems and neural rehabilitation.

  5. Problem and Project Based Learning in Hybrid Spaces

    DEFF Research Database (Denmark)

    Ryberg, Thomas; Davidsen, Jacob; Hodgson, Vivien

    2016-01-01

    There is a need within networked learning to understand and conceptualise the interplay between digital and physical spaces or what we could term hybrid spaces. Therefore, we discuss a recent study of students from two different programmes who are engaged in long-term, group-based problem...... and project based learning. Based on interviews, workshops and observations of students’ actual group practices in open, shared and flexible spaces in Aalborg University (AAU), we identify and discuss how students incorporate networked and digital technologies into their group work and into the study places...... they create for themselves. We describe how in one of the programmes ‘nomadic’ groups of students used different technologies and spaces for ‘placemaking’. We then show how their experience and approach to collaborative work differs to that of the more static or ‘artisan’ groups of students in the other...

  6. Enriching Student Learning of Astronomy in Online Courses via Hybrid Texts

    Science.gov (United States)

    Montgomery, M.

    2016-01-01

    Hybrid texts such as Horizons: Exploring the Universe, Hybrid (with CengageNOW) and Universe, Hybrid (with CengageNOW) are designed for higher education learning of astronomy in undergraduate online courses. In these hybrid texts, quiz and test bank questions have been revised to minimize easy look-up of answers by students via the Internet and discussion threads have been re-designed to allow for student selection of learning and for personalized learning, for example. By establishing connections between the student and the course content, student learning is enriched, students spend more time learning the material, student copying of answers is minimized, and student social engagement on the subject matter is increased. In this presentation, we discuss how Hybrid texts in Astronomy can increase student learning in online courses.

  7. Motivation, students' needs and learning outcomes: a hybrid game-based app for enhanced language learning.

    Science.gov (United States)

    Berns, Anke; Isla-Montes, José-Luis; Palomo-Duarte, Manuel; Dodero, Juan-Manuel

    2016-01-01

    In the context of European Higher Education students face an increasing focus on independent, individual learning-at the expense of face-to-face interaction. Hence learners are, all too often, not provided with enough opportunities to negotiate in the target language. The current case study aims to address this reality by going beyond conventional approaches to provide students with a hybrid game-based app, combining individual and collaborative learning opportunities. The 4-week study was carried out with 104 German language students (A1.2 CEFR) who had previously been enrolled in a first-semester A1.1 level course at a Spanish university. The VocabTrainerA1 app-designed specifically for this study-harnesses the synergy of combining individual learning tasks and a collaborative murder mystery game in a hybrid level-based architecture. By doing so, the app provides learners with opportunities to apply their language skills to real-life-like communication. The purpose of the study was twofold: on one hand we aimed to measure learner motivation, perceived usefulness and added value of hybrid game-based apps; on the other, we sought to determine their impact on language learning. To this end, we conducted focus group interviews and an anonymous Technology Acceptance Model survey (TAM). In addition, students took a pre-test and a post-test. Scores from both tests were compared with the results obtained in first-semester conventional writing tasks, with a view to measure learning outcomes. The study provides qualitative and quantitative data supporting our initial hypotheses. Our findings suggest that hybrid game-based apps like VocabTrainerA1-which seamlessly combine individual and collaborative learning tasks-motivate learners, stimulate perceived usefulness and added value, and better meet the language learning needs of today's digital natives. In terms of acceptance, outcomes and sustainability, the data indicate that hybrid game-based apps significantly improve

  8. Biomimetic Hybrid Feedback Feedforward Neural-Network Learning Control.

    Science.gov (United States)

    Pan, Yongping; Yu, Haoyong

    2017-06-01

    This brief presents a biomimetic hybrid feedback feedforward neural-network learning control (NNLC) strategy inspired by the human motor learning control mechanism for a class of uncertain nonlinear systems. The control structure includes a proportional-derivative controller acting as a feedback servo machine and a radial-basis-function (RBF) NN acting as a feedforward predictive machine. Under the sufficient constraints on control parameters, the closed-loop system achieves semiglobal practical exponential stability, such that an accurate NN approximation is guaranteed in a local region along recurrent reference trajectories. Compared with the existing NNLC methods, the novelties of the proposed method include: 1) the implementation of an adaptive NN control to guarantee plant states being recurrent is not needed, since recurrent reference signals rather than plant states are utilized as NN inputs, which greatly simplifies the analysis and synthesis of the NNLC and 2) the domain of NN approximation can be determined a priori by the given reference signals, which leads to an easy construction of the RBF-NNs. Simulation results have verified the effectiveness of this approach.

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

    Science.gov (United States)

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

    2015-10-01

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

  10. Maladaptive learning and memory in hybrids as a reproductive isolating barrier.

    Science.gov (United States)

    Rice, Amber M; McQuillan, Michael A

    2018-05-30

    Selection against hybrid offspring, or postzygotic reproductive isolation, maintains species boundaries in the face of gene flow from hybridization. In this review, we propose that maladaptive learning and memory in hybrids is an important, but overlooked form of postzygotic reproductive isolation. Although a role for learning in premating isolation has been supported, whether learning deficiencies can contribute to postzygotic isolation has rarely been tested. We argue that the novel genetic combinations created by hybridization have the potential to impact learning and memory abilities through multiple possible mechanisms, and that any displacement from optima in these traits is likely to have fitness consequences. We review evidence supporting the potential for hybridization to affect learning and memory, and evidence of links between learning abilities and fitness. Finally, we suggest several avenues for future research. Given the importance of learning for fitness, especially in novel and unpredictable environments, maladaptive learning and memory in hybrids may be an increasingly important source of postzygotic reproductive isolation. © 2018 The Author(s).

  11. Hybrid High-Impact Pedagogies: Integrating Service-Learning with Three Other High-Impact Pedagogies

    Science.gov (United States)

    Bringle, Robert G.

    2017-01-01

    This article proposes enhancing student learning through civic engagement by considering the advantages of integrating service-learning with study away, research, and internships and pre-professional courses into first-order, second-order, and third-order hybrid high-impact pedagogies. Service-learning contributes numerous attributes to the other…

  12. A Hybrid Approach for Supporting Adaptivity in E-Learning Environments

    Science.gov (United States)

    Al-Omari, Mohammad; Carter, Jenny; Chiclana, Francisco

    2016-01-01

    Purpose: The purpose of this paper is to identify a framework to support adaptivity in e-learning environments. The framework reflects a novel hybrid approach incorporating the concept of the event-condition-action (ECA) model and intelligent agents. Moreover, a system prototype is developed reflecting the hybrid approach to supporting adaptivity…

  13. Duo: A Human/Wearable Hybrid for Learning About Common Manipulate Objects

    National Research Council Canada - National Science Library

    Kemp, Charles C

    2002-01-01

    ... with them. Duo is a human/wearable hybrid that is designed to learn about this important domain of human intelligence by interacting with natural manipulable objects in unconstrained environments...

  14. Specialized hybrid learners resolve Rogers' paradox about the adaptive value of social learning.

    Science.gov (United States)

    Kharratzadeh, Milad; Montrey, Marcel; Metz, Alex; Shultz, Thomas R

    2017-02-07

    Culture is considered an evolutionary adaptation that enhances reproductive fitness. A common explanation is that social learning, the learning mechanism underlying cultural transmission, enhances mean fitness by avoiding the costs of individual learning. This explanation was famously contradicted by Rogers (1988), who used a simple mathematical model to show that cheap social learning can invade a population without raising its mean fitness. He concluded that some crucial factor remained unaccounted for, which would reverse this surprising result. Here we extend this model to include a more complex environment and limited resources, where individuals cannot reliably learn everything about the environment on their own. Under such conditions, cheap social learning evolves and enhances mean fitness, via hybrid learners capable of specializing their individual learning. We then show that while spatial or social constraints hinder the evolution of hybrid learners, a novel social learning strategy, complementary copying, can mitigate these effects. Copyright © 2016 Elsevier Ltd. All rights reserved.

  15. Self-directed learning readiness of Asian students: students perspective on a hybrid problem based learning curriculum.

    Science.gov (United States)

    Leatemia, Lukas D; Susilo, Astrid P; van Berkel, Henk

    2016-12-03

    To identify the student's readiness to perform self-directed learning and the underlying factors influencing it on the hybrid problem based learning curriculum. A combination of quantitative and qualitative studies was conducted in five medical schools in Indonesia. In the quantitative study, the Self Directed Learning Readiness Scale was distributed to all students in all batches, who had experience with the hybrid problem based curriculum. They were categorized into low- and high -level based on the score of the questionnaire. Three focus group discussions (low-, high-, and mixed level) were conducted in the qualitative study with six to twelve students chosen randomly from each group to find the factors influencing their self-directed learning readiness. Two researchers analysed the qualitative data as a measure of triangulation. The quantitative study showed only half of the students had a high-level of self-directed learning readiness, and a similar trend also occurred in each batch. The proportion of students with a high level of self-directed learning readiness was lower in the senior students compared to more junior students. The qualitative study showed that problem based learning processes, assessments, learning environment, students' life styles, students' perceptions of the topics, and mood, were factors influencing their self-directed learning. A hybrid problem based curriculum may not fully affect the students' self-directed learning. The curriculum system, teacher's experiences, student's background and cultural factors might contribute to the difficulties for the student's in conducting self-directed learning.

  16. A novel hybrid ensemble learning paradigm for nuclear energy consumption forecasting

    International Nuclear Information System (INIS)

    Tang, Ling; Yu, Lean; Wang, Shuai; Li, Jianping; Wang, Shouyang

    2012-01-01

    Highlights: ► A hybrid ensemble learning paradigm integrating EEMD and LSSVR is proposed. ► The hybrid ensemble method is useful to predict time series with high volatility. ► The ensemble method can be used for both one-step and multi-step ahead forecasting. - Abstract: In this paper, a novel hybrid ensemble learning paradigm integrating ensemble empirical mode decomposition (EEMD) and least squares support vector regression (LSSVR) is proposed for nuclear energy consumption forecasting, based on the principle of “decomposition and ensemble”. This hybrid ensemble learning paradigm is formulated specifically to address difficulties in modeling nuclear energy consumption, which has inherently high volatility, complexity and irregularity. In the proposed hybrid ensemble learning paradigm, EEMD, as a competitive decomposition method, is first applied to decompose original data of nuclear energy consumption (i.e. a difficult task) into a number of independent intrinsic mode functions (IMFs) of original data (i.e. some relatively easy subtasks). Then LSSVR, as a powerful forecasting tool, is implemented to predict all extracted IMFs independently. Finally, these predicted IMFs are aggregated into an ensemble result as final prediction, using another LSSVR. For illustration and verification purposes, the proposed learning paradigm is used to predict nuclear energy consumption in China. Empirical results demonstrate that the novel hybrid ensemble learning paradigm can outperform some other popular forecasting models in both level prediction and directional forecasting, indicating that it is a promising tool to predict complex time series with high volatility and irregularity.

  17. Diverse Strategies for Diverse Learners: Action Learning in a Hybrid Mode

    Directory of Open Access Journals (Sweden)

    Esmarie Strydom

    2007-08-01

    Full Text Available This paper describes an action research study during which a flexible or hybrid approach to delivering an Information and Communication Technology competency course is implemented in the preparation of student teachers. The course incorporates Web-based course-content delivery, face-to-face classroom meetings to satisfy the need for human interaction, a variety of assessment methods, as well as recognition of prior learning. The objectives are to accommodate learning diversity, make learning focused and achievable for each learner, allow for intervention if the learning outcomes are not met, and focus on and guide the learning process, i.e. teach learners how to learn. This paper reports on the perspectives and experiences of two groups of first year learners, namely student teachers who attended a hybrid ICT course and first year learners who attended an e-learning ICT course. It was found that the success rate of the hybrid mode ICT course was significantly higher than that of the similar e-learning ICT course. The hybrid mode ICT course also enabled the learners to become self-directed to a higher degree.

  18. Self-regulated Learning in a Hybrid Science Course at a Community College

    Science.gov (United States)

    Manuelito, Shannon Joy

    Community college students are attracted to courses with alternative delivery formats such as hybrid courses because the more flexible delivery associated with such courses provides convenience for busy students. In a hybrid course, face-to-face, structured seat time is exchanged for online components. In such courses, students take more responsibility for their learning because they assume additional responsibility for learning more of the course material on their own. Thus, self-regulated learning (SRL) behaviors have the potential to be useful for students to successfully navigate hybrid courses because the online components require exercise of more personal control over the autonomous learning situations inherent in hybrid courses. Self-regulated learning theory includes three components: metacognition, motivation, and behavioral actions. In the current study, this theoretical framework is used to examine how inducing self-regulated learning activities among students taking a hybrid course influence performance in a community college science course. The intervention for this action research study consisted of a suite of activities that engage students in self-regulated learning behaviors to foster student performance. The specific SRL activities included predicting grades, reflections on coursework and study efforts in course preparation logs, explanation of SRL procedures in response to a vignette, photo ethnography work on their personal use of SRL approaches, and a personalized study plan. A mixed method approach was employed to gather evidence for the study. Results indicate that community college students use a variety of self-regulated learning strategies to support their learning of course material. Further, engaging community college students in learning reflection activities appears to afford some students with opportunities to refine their SRL skills and influence their learning. The discussion focuses on integrating the quantitative and qualitative

  19. Visual Hybrid Development Learning System (VHDLS) framework for children with autism.

    Science.gov (United States)

    Banire, Bilikis; Jomhari, Nazean; Ahmad, Rodina

    2015-10-01

    The effect of education on children with autism serves as a relative cure for their deficits. As a result of this, they require special techniques to gain their attention and interest in learning as compared to typical children. Several studies have shown that these children are visual learners. In this study, we proposed a Visual Hybrid Development Learning System (VHDLS) framework that is based on an instructional design model, multimedia cognitive learning theory, and learning style in order to guide software developers in developing learning systems for children with autism. The results from this study showed that the attention of children with autism increased more with the proposed VHDLS framework.

  20. StackInsights: Cognitive Learning for Hybrid Cloud Readiness

    OpenAIRE

    Qiao, Mu; Bathen, Luis; Génot, Simon-Pierre; Lee, Sunhwan; Routray, Ramani

    2017-01-01

    Hybrid cloud is an integrated cloud computing environment utilizing a mix of public cloud, private cloud, and on-premise traditional IT infrastructures. Workload awareness, defined as a detailed full range understanding of each individual workload, is essential in implementing the hybrid cloud. While it is critical to perform an accurate analysis to determine which workloads are appropriate for on-premise deployment versus which workloads can be migrated to a cloud off-premise, the assessment...

  1. Bringing Online Learning to Campus: The Hybridization of Teaching and Learning at Brigham Young University

    Directory of Open Access Journals (Sweden)

    Gregory L. Waddoups

    2002-01-01

    Full Text Available The primary purpose of Brigham Young University (BYU is to provide students with a combination of sacred and secular education often described as the "BYU experience". Achieving this purpose is challenged by the rapid growth in Church membership and an enrollment cap of 30,000 students. To address these challenges, BYU sponsors the use of technology to bridge the gap between the increased Church membership and the number of students allowed under the enrollment caps. This institutional case study shows how these challenges have influenced the hybridization of teaching and learning for on campus (resident and off campus (distance students. It also describes how BYU has brought distance education to campus, and is beginning to bring campus-based educational practices to distance education.

  2. Identification of chaotic systems by neural network with hybrid learning algorithm

    International Nuclear Information System (INIS)

    Pan, S.-T.; Lai, C.-C.

    2008-01-01

    Based on the genetic algorithm (GA) and steepest descent method (SDM), this paper proposes a hybrid algorithm for the learning of neural networks to identify chaotic systems. The systems in question are the logistic map and the Duffing equation. Different identification schemes are used to identify both the logistic map and the Duffing equation, respectively. Simulation results show that our hybrid algorithm is more efficient than that of other methods

  3. Comparing Hybrid Learning with Traditional Approaches on Learning the Microsoft Office Power Point 2003 Program in Tertiary Education

    Science.gov (United States)

    Vernadakis, Nikolaos; Antoniou, Panagiotis; Giannousi, Maria; Zetou, Eleni; Kioumourtzoglou, Efthimis

    2011-01-01

    The purpose of this study was to determine the effectiveness of a hybrid learning approach to deliver a computer science course concerning the Microsoft office PowerPoint 2003 program in comparison to delivering the same course content in the form of traditional lectures. A hundred and seventy-two first year university students were randomly…

  4. Energy Management Strategy for a Hybrid Electric Vehicle Based on Deep Reinforcement Learning

    OpenAIRE

    Yue Hu; Weimin Li; Kun Xu; Taimoor Zahid; Feiyan Qin; Chenming Li

    2018-01-01

    An energy management strategy (EMS) is important for hybrid electric vehicles (HEVs) since it plays a decisive role on the performance of the vehicle. However, the variation of future driving conditions deeply influences the effectiveness of the EMS. Most existing EMS methods simply follow predefined rules that are not adaptive to different driving conditions online. Therefore, it is useful that the EMS can learn from the environment or driving cycle. In this paper, a deep reinforcement learn...

  5. Problem and Project Based Learning in Hybrid Spaces:Nomads and Artisans

    OpenAIRE

    Ryberg, Thomas; Davidsen, Jacob; Hodgson, Vivien

    2016-01-01

    There is a need within networked learning to understand and conceptualise the interplay between digital and physical spaces or what we could term hybrid spaces. Therefore, we discuss a recent study of students from two different programmes who are engaged in long-term, group-based problem and project based learning. Based on interviews, workshops and observations of students’ actual group practices in open, shared and flexible spaces in Aalborg University (AAU), we identify and discuss how st...

  6. Perceived Learning and Timely Graduation for Business Undergraduates Taking an Online or Hybrid Course

    Science.gov (United States)

    Blau, Gary; Drennan, Rob B.; Hochner, Arthur; Kapanjie, Darin

    2016-01-01

    An online survey tested the impact of background, technological, and course-related variables on perceived learning and timely graduation for a complete data sample of 263 business undergraduates taking at least one online or hybrid course in the fall of 2015. Hierarchical regression results showed that course-related variables (instructor…

  7. Communicator Style as a Predictor of Cyberbullying in a Hybrid Learning Environment

    Science.gov (United States)

    Dursun, Ozcan Ozgur; Akbulut, Yavuz

    2012-01-01

    This study aimed to describe the characteristics of undergraduate students in a hybrid learning environment with regard to their communicator styles and cyberbullying behaviors. Moreover, relationships between cyberbullying victimization and learners' perceived communicator styles were investigated. Cyberbullying victimization was measured through…

  8. Extended Immersive Learning Environment: A Hybrid Remote/Virtual Laboratory

    Directory of Open Access Journals (Sweden)

    Lírio Shaeffer

    2010-09-01

    Full Text Available This paper presents a collaborative virtual learning environment, which includes technologies such as 3D virtual representations, learning and content management systems, remote experiments, and collaborative learning spaces, among others. It intends to facilitate the construction, management and sharing of knowledge among teachers and students, in a global perspective. The environment proposes the use of 3D social representations for accessing learning materials in a dynamic and interactive form, which is regarded to be closer to the physical reality experienced by teachers and students in a learning context. A first implementation of the proposed extended immersive learning environment, in the area of solid mechanics, is also described, including the access to theoretical contents and a remote experiment to determine the elastic modulus of a given object.These instructions give you basic guidelines for preparing camera-ready papers for conference proceedings. Use this document as a template if you are using Microsoft Word 6.0 or later. Otherwise, use this document as an instruction set. The electronic file of your paper will be formatted further. Define all symbols used in the abstract. Do not cite references in the abstract.

  9. Hybrid forecasting of chaotic processes: Using machine learning in conjunction with a knowledge-based model

    Science.gov (United States)

    Pathak, Jaideep; Wikner, Alexander; Fussell, Rebeckah; Chandra, Sarthak; Hunt, Brian R.; Girvan, Michelle; Ott, Edward

    2018-04-01

    A model-based approach to forecasting chaotic dynamical systems utilizes knowledge of the mechanistic processes governing the dynamics to build an approximate mathematical model of the system. In contrast, machine learning techniques have demonstrated promising results for forecasting chaotic systems purely from past time series measurements of system state variables (training data), without prior knowledge of the system dynamics. The motivation for this paper is the potential of machine learning for filling in the gaps in our underlying mechanistic knowledge that cause widely-used knowledge-based models to be inaccurate. Thus, we here propose a general method that leverages the advantages of these two approaches by combining a knowledge-based model and a machine learning technique to build a hybrid forecasting scheme. Potential applications for such an approach are numerous (e.g., improving weather forecasting). We demonstrate and test the utility of this approach using a particular illustrative version of a machine learning known as reservoir computing, and we apply the resulting hybrid forecaster to a low-dimensional chaotic system, as well as to a high-dimensional spatiotemporal chaotic system. These tests yield extremely promising results in that our hybrid technique is able to accurately predict for a much longer period of time than either its machine-learning component or its model-based component alone.

  10. Active semi-supervised learning method with hybrid deep belief networks.

    Science.gov (United States)

    Zhou, Shusen; Chen, Qingcai; Wang, Xiaolong

    2014-01-01

    In this paper, we develop a novel semi-supervised learning algorithm called active hybrid deep belief networks (AHD), to address the semi-supervised sentiment classification problem with deep learning. First, we construct the previous several hidden layers using restricted Boltzmann machines (RBM), which can reduce the dimension and abstract the information of the reviews quickly. Second, we construct the following hidden layers using convolutional restricted Boltzmann machines (CRBM), which can abstract the information of reviews effectively. Third, the constructed deep architecture is fine-tuned by gradient-descent based supervised learning with an exponential loss function. Finally, active learning method is combined based on the proposed deep architecture. We did several experiments on five sentiment classification datasets, and show that AHD is competitive with previous semi-supervised learning algorithm. Experiments are also conducted to verify the effectiveness of our proposed method with different number of labeled reviews and unlabeled reviews respectively.

  11. Learning Document Semantic Representation with Hybrid Deep Belief Network

    Directory of Open Access Journals (Sweden)

    Yan Yan

    2015-01-01

    it is also an effective way to remove noise from the different document representation type; the DBN can enhance extract abstract of the document in depth, making the model learn sufficient semantic representation. At the same time, we explore different input strategies for semantic distributed representation. Experimental results show that our model using the word embedding instead of single word has better performance.

  12. A novel hybrid ensemble learning paradigm for tourism forecasting

    Science.gov (United States)

    Shabri, Ani

    2015-02-01

    In this paper, a hybrid forecasting model based on Empirical Mode Decomposition (EMD) and Group Method of Data Handling (GMDH) is proposed to forecast tourism demand. This methodology first decomposes the original visitor arrival series into several Intrinsic Model Function (IMFs) components and one residual component by EMD technique. Then, IMFs components and the residual components is forecasted respectively using GMDH model whose input variables are selected by using Partial Autocorrelation Function (PACF). The final forecasted result for tourism series is produced by aggregating all the forecasted results. For evaluating the performance of the proposed EMD-GMDH methodologies, the monthly data of tourist arrivals from Singapore to Malaysia are used as an illustrative example. Empirical results show that the proposed EMD-GMDH model outperforms the EMD-ARIMA as well as the GMDH and ARIMA (Autoregressive Integrated Moving Average) models without time series decomposition.

  13. The Effect of Haptic Guidance on Learning a Hybrid Rhythmic-Discrete Motor Task.

    Science.gov (United States)

    Marchal-Crespo, Laura; Bannwart, Mathias; Riener, Robert; Vallery, Heike

    2015-01-01

    Bouncing a ball with a racket is a hybrid rhythmic-discrete motor task, combining continuous rhythmic racket movements with discrete impact events. Rhythmicity is exceptionally important in motor learning, because it underlies fundamental movements such as walking. Studies suggested that rhythmic and discrete movements are governed by different control mechanisms at different levels of the Central Nervous System. The aim of this study is to evaluate the effect of fixed/fading haptic guidance on learning to bounce a ball to a desired apex in virtual reality with varying gravity. Changing gravity changes dominance of rhythmic versus discrete control: The higher the value of gravity, the more rhythmic the task; lower values reduce the bouncing frequency and increase dwell times, eventually leading to a repetitive discrete task that requires initiation and termination, resembling target-oriented reaching. Although motor learning in the ball-bouncing task with varying gravity has been studied, the effect of haptic guidance on learning such a hybrid rhythmic-discrete motor task has not been addressed. We performed an experiment with thirty healthy subjects and found that the most effective training condition depended on the degree of rhythmicity: Haptic guidance seems to hamper learning of continuous rhythmic tasks, but it seems to promote learning for repetitive tasks that resemble discrete movements.

  14. Beam-column joint shear prediction using hybridized deep learning neural network with genetic algorithm

    Science.gov (United States)

    Mundher Yaseen, Zaher; Abdulmohsin Afan, Haitham; Tran, Minh-Tung

    2018-04-01

    Scientifically evidenced that beam-column joints are a critical point in the reinforced concrete (RC) structure under the fluctuation loads effects. In this novel hybrid data-intelligence model developed to predict the joint shear behavior of exterior beam-column structure frame. The hybrid data-intelligence model is called genetic algorithm integrated with deep learning neural network model (GA-DLNN). The genetic algorithm is used as prior modelling phase for the input approximation whereas the DLNN predictive model is used for the prediction phase. To demonstrate this structural problem, experimental data is collected from the literature that defined the dimensional and specimens’ properties. The attained findings evidenced the efficitveness of the hybrid GA-DLNN in modelling beam-column joint shear problem. In addition, the accurate prediction achived with less input variables owing to the feasibility of the evolutionary phase.

  15. Hybrid Method for Mobile learning Cooperative: Study of Timor Leste

    Science.gov (United States)

    da Costa Tavares, Ofelia Cizela; Suyoto; Pranowo

    2018-02-01

    In the modern world today the decision support system is very useful to help in solving a problem, so this study discusses the learning process of savings and loan cooperatives in Timor Leste. The purpose of the observation is that the people of Timor Leste are still in the process of learning the use DSS for good saving and loan cooperative process. Based on existing research on the Timor Leste community on credit cooperatives, a mobile application will be built that will help the cooperative learning process in East Timorese society. The methods used for decision making are AHP (Analytical Hierarchy Process) and SAW (simple additive Weighting) method to see the result of each criterion and the weight of the value. The result of this research is mobile leaning cooperative in decision support system by using SAW and AHP method. Originality Value: Changed the two methods of mobile application development using AHP and SAW methods to help the decision support system process of a savings and credit cooperative in Timor Leste.

  16. Hybrid Method for Mobile learning Cooperative: Study of Timor Leste

    Directory of Open Access Journals (Sweden)

    da Costa Tavares Ofelia Cizela

    2018-01-01

    Full Text Available In the modern world today the decision support system is very useful to help in solving a problem, so this study discusses the learning process of savings and loan cooperatives in Timor Leste. The purpose of the observation is that the people of Timor Leste are still in the process of learning the use DSS for good saving and loan cooperative process. Based on existing research on the Timor Leste community on credit cooperatives, a mobile application will be built that will help the cooperative learning process in East Timorese society. The methods used for decision making are AHP (Analytical Hierarchy Process and SAW (simple additive Weighting method to see the result of each criterion and the weight of the value. The result of this research is mobile leaning cooperative in decision support system by using SAW and AHP method. Originality Value: Changed the two methods of mobile application development using AHP and SAW methods to help the decision support system process of a savings and credit cooperative in Timor Leste.

  17. Locomotion training of legged robots using hybrid machine learning techniques

    Science.gov (United States)

    Simon, William E.; Doerschuk, Peggy I.; Zhang, Wen-Ran; Li, Andrew L.

    1995-01-01

    In this study artificial neural networks and fuzzy logic are used to control the jumping behavior of a three-link uniped robot. The biped locomotion control problem is an increment of the uniped locomotion control. Study of legged locomotion dynamics indicates that a hierarchical controller is required to control the behavior of a legged robot. A structured control strategy is suggested which includes navigator, motion planner, biped coordinator and uniped controllers. A three-link uniped robot simulation is developed to be used as the plant. Neurocontrollers were trained both online and offline. In the case of on-line training, a reinforcement learning technique was used to train the neurocontroller to make the robot jump to a specified height. After several hundred iterations of training, the plant output achieved an accuracy of 7.4%. However, when jump distance and body angular momentum were also included in the control objectives, training time became impractically long. In the case of off-line training, a three-layered backpropagation (BP) network was first used with three inputs, three outputs and 15 to 40 hidden nodes. Pre-generated data were presented to the network with a learning rate as low as 0.003 in order to reach convergence. The low learning rate required for convergence resulted in a very slow training process which took weeks to learn 460 examples. After training, performance of the neurocontroller was rather poor. Consequently, the BP network was replaced by a Cerebeller Model Articulation Controller (CMAC) network. Subsequent experiments described in this document show that the CMAC network is more suitable to the solution of uniped locomotion control problems in terms of both learning efficiency and performance. A new approach is introduced in this report, viz., a self-organizing multiagent cerebeller model for fuzzy-neural control of uniped locomotion is suggested to improve training efficiency. This is currently being evaluated for a possible

  18. Students' perception towards the problem based learning tutorial session in a system-based hybrid curriculum.

    Science.gov (United States)

    Al-Drees, Abdulmajeed A; Khalil, Mahmoud S; Irshad, Mohammad; Abdulghani, Hamza M

    2015-03-01

    To evaluate students' perception towards the problem based learning (PBL) session in a system-based hybrid curriculum. We conducted a cross-sectional study in the College of Medicine, King Saud University, Saudi Arabia at the end of the 2012-2013 academic year. The survey questionnaire was self-administered, and examined perceptions of PBL session benefits, appropriate running of sessions, and tutor's roles. Out of 510 students, 275 (53.9%) completed the questionnaire. Most of the students reported that PBL sessions were helpful in understanding basic sciences concepts (p=0.04). In addition, they agreed that PBL sessions increased their knowledge of basic sciences (p=0.01). Most students reported that PBL sessions encouraged self-directed learning, collaborative learning, and improved decision making skills. However, 54.5% of students reported lack of proper training before starting the PBL sessions, and only 25.1% of students agreed that the teaching staff are well prepared to run the sessions. Most students used the internet (93.1%), lecture notes (76.7%), and books (64.4%) as learning resources. Most students reported repetition of topics between PBL sessions and lectures (p=0.07). The study highlighted the significant role of PBL in a system-based hybrid curriculum and helped students improve their knowledge and different learning skills. Students and staff training is required before the utilizing the PBL as an instructional method.

  19. Modeling And Simulation As The Basis For Hybridity In The Graphic Discipline Learning/Teaching Area

    Directory of Open Access Journals (Sweden)

    Jana Žiljak Vujić

    2009-01-01

    Full Text Available Only some fifteen years have passed since the scientific graphics discipline was established. In the transition period from the College of Graphics to «Integrated Graphic Technology Studies» to the contemporary Faculty of Graphics Arts with the University in Zagreb, three main periods of development can be noted: digital printing, computer prepress and automatic procedures in postpress packaging production. Computer technology has enabled a change in the methodology of teaching graphics technology and studying it on the level of secondary and higher education. The task has been set to create tools for simulating printing processes in order to master the program through a hybrid system consisting of methods that are separate in relation to one another: learning with the help of digital models and checking in the actual real system. We are setting a hybrid project for teaching because the overall acquired knowledge is the result of completely different methods. The first method is on the free programs level functioning without consequences. Everything remains as a record in the knowledge database that can be analyzed, statistically processed and repeated with new parameter values of the system being researched. The second method uses the actual real system where the results are in proving the value of new knowledge and this is something that encourages and stimulates new cycles of hybrid behavior in mastering programs. This is the area where individual learning incurs. The hybrid method allows the possibility of studying actual situations on a computer model, proving it on an actual real model and entering the area of learning envisaging future development.

  20. Modeling and Simulation as the Basis for Hybridity in the Graphic Discipline Learning/Teaching Area

    Directory of Open Access Journals (Sweden)

    Vilko Ziljak

    2009-11-01

    Full Text Available Only some fifteen years have passed since the scientific graphics discipline was established. In the transition period from the College of Graphics to «Integrated Graphic Technology Studies» to the contemporary Faculty of Graphics Arts with the University in Zagreb, three main periods of development can be noted: digital printing, computer prepress and automatic procedures in postpress packaging production. Computer technology has enabled a change in the methodology of teaching graphics technology and studying it on the level of secondary and higher education. The task has been set to create tools for simulating printing processes in order to master the program through a hybrid system consisting of methods that are separate in relation to one another: learning with the help of digital models and checking in the actual real system.  We are setting a hybrid project for teaching because the overall acquired knowledge is the result of completely different methods. The first method is on the free programs level functioning without consequences. Everything remains as a record in the knowledge database that can be analyzed, statistically processed and repeated with new parameter values of the system being researched. The second method uses the actual real system where the results are in proving the value of new knowledge and this is something that encourages and stimulates new cycles of hybrid behavior in mastering programs. This is the area where individual learning incurs. The hybrid method allows the possibility of studying actual situations on a computer model, proving it on an actual real model and entering the area of learning envisaging future development.

  1. The Use of a Hybrid Strategy Combining Problem-based Learning and Magisterial Lectures to Enhance Learning

    Directory of Open Access Journals (Sweden)

    Carlos Alberto Acosta-Nassar

    2014-09-01

    Full Text Available This paper addresses the problem of capturing the attention of intermediate level students in the Thermodynamics 1 course from the Mechanical and Agricultural Engineering Program, with the purpose of helping students improve their learning process. A hybrid teaching strategy was proposed based on Problem-based Learning (PBL principles combined with magisterial lectures. Digital and traditional didactic resources were also used in order to find the best mean to minimize the lack of attention in learners. The strategy was developed by sensitizing students to get involved in their formation process. PowerPoint presentations, video clips, the traditional white board and an ultra slim digital tablet board were used to develop the theoretical issues and present the solutions to the problems chosen for the PBL strategy. Finally, the strategy was evaluated and results were analyzed, indicating that using a hybrid strategy combining PBL and traditional magisterial lectures is an optimal resource to improve the learning process of students taking Thermodynamics 1. In addition, it was also concluded that the ultra slim digital tablet board is the optimal didactic resource.

  2. AN INDUCTIVE, INTERACTIVE AND ADAPTIVE HYBRID PROBLEM-BASED LEARNING METHODOLOGY: APPLICATION TO STATISTICS

    Directory of Open Access Journals (Sweden)

    ADA ZHENG

    2011-10-01

    Full Text Available We have developed an innovative hybrid problem-based learning (PBL methodology. The methodology has the following distinctive features: i Each complex question was decomposed into a set of coherent finer subquestions by following the carefully designed criteria to maintain a delicate balance between guiding the students and inspiring them to think independently. This learning methodology enabled the students to solve the complex questions progressively in an inductive context. ii Facilitated by the utilization of our web-based learning systems, the teacher was able to interact with the students intensively and could allocate more teaching time to provide tailor-made feedback for individual student. The students were actively engaged in the learning activities, stimulated by the intensive interaction. iii The answers submitted by the students could be automatically consolidated in the report of the Moodle system in real-time. The teacher could adjust the teaching schedule and focus of the class to adapt to the learning progress of the students by analysing the automatically generated report and log files of the web-based learning system. As a result, the attendance rate of the students increased from about 50% to more than 90%, and the students’ learning motivation have been significantly enhanced.

  3. Learning Design Patterns for Hybrid Synchronous Video-Mediated Learning Environments

    DEFF Research Database (Denmark)

    Weitze, Charlotte Lærke

    2016-01-01

    This article describes an innovative learning environment where remote and face-to-face full-time general upper secondary adult students jointly participate in the same live classes at VUC Storstrøm, an adult learning centre in Denmark. The teachers developed new learning designs as a part of the...... activating and equal learning designs for the students. This article is written on the basis of a chapter in the PhD–thesis by the author....

  4. E-Learning Personalization Based on Hybrid Recommendation Strategy and Learning Style Identification

    Science.gov (United States)

    Klasnja-Milicevic, Aleksandra; Vesin, Boban; Ivanovic, Mirjana; Budimac, Zoran

    2011-01-01

    Personalized learning occurs when e-learning systems make deliberate efforts to design educational experiences that fit the needs, goals, talents, and interests of their learners. Researchers had recently begun to investigate various techniques to help teachers improve e-learning systems. In this paper, we describe a recommendation module of a…

  5. DLNE: A hybridization of deep learning and neuroevolution for visual control

    DEFF Research Database (Denmark)

    Poulsen, Andreas Precht; Thorhauge, Mark; Funch, Mikkel Hvilshj

    2017-01-01

    This paper investigates the potential of combining deep learning and neuroevolution to create a bot for a simple first person shooter (FPS) game capable of aiming and shooting based on high-dimensional raw pixel input. The deep learning component is responsible for visual recognition...... on evolution, and (3) how well they allow the deep network and evolved network to interface with each other. Overall, 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...... and translating raw pixels to compact feature representations, while the evolving network takes those features as inputs to infer actions. Two types of feature representations are evaluated in terms of (1) how precise they allow the deep network to recognize the position of the enemy, (2) their effect...

  6. Training versus Education: eLearning, Hybrid, and Face-to-Face Modalities - a Participatory Debate

    Directory of Open Access Journals (Sweden)

    Risa Blair

    2016-10-01

    Full Text Available Is training education or is education training? Universities and organizations treat training and education synonymously, but it is worth exploring the differences. Universities are scrambling to standardize a preferred delivery method of education and training. With the blended modalities of eLearning, face-to-face, and hybrid learning, the educational delivery seems to be equalizing. The disruptive shift with technology in education or training is complicated by the expectations of our millennial, Gen Y, and Gen Z students. As an added pressure at the university level, even more importantly, the expectation of the administration and the accrediting bodies keep changing the 'play book' on requirements. Given the ever changing complexities of today's paradigm-shift in education and learning, we explored the complexities of navigating the delivery methods to achieve educational goals in higher education or training goals in corporate America.

  7. Assessing the Effectiveness of a Hybrid-Flipped Model of Learning on Fluid Mechanics Instruction: Overall Course Performance, Homework, and Far- and Near-Transfer of Learning

    Science.gov (United States)

    Harrison, David J.; Saito, Laurel; Markee, Nancy; Herzog, Serge

    2017-01-01

    To examine the impact of a hybrid-flipped model utilising active learning techniques, the researchers inverted one section of an undergraduate fluid mechanics course, reduced seat time, and engaged in active learning sessions in the classroom. We compared this model to the traditional section on four performance measures. We employed a propensity…

  8. Identifying reports of randomized controlled trials (RCTs) via a hybrid machine learning and crowdsourcing approach.

    Science.gov (United States)

    Wallace, Byron C; Noel-Storr, Anna; Marshall, Iain J; Cohen, Aaron M; Smalheiser, Neil R; Thomas, James

    2017-11-01

    Identifying all published reports of randomized controlled trials (RCTs) is an important aim, but it requires extensive manual effort to separate RCTs from non-RCTs, even using current machine learning (ML) approaches. We aimed to make this process more efficient via a hybrid approach using both crowdsourcing and ML. We trained a classifier to discriminate between citations that describe RCTs and those that do not. We then adopted a simple strategy of automatically excluding citations deemed very unlikely to be RCTs by the classifier and deferring to crowdworkers otherwise. Combining ML and crowdsourcing provides a highly sensitive RCT identification strategy (our estimates suggest 95%-99% recall) with substantially less effort (we observed a reduction of around 60%-80%) than relying on manual screening alone. Hybrid crowd-ML strategies warrant further exploration for biomedical curation/annotation tasks. © The Author 2017. Published by Oxford University Press on behalf of the American Medical Informatics Association.

  9. Engineering Hybrid Learning Communities: The Case of a Regional Parent Community

    Directory of Open Access Journals (Sweden)

    Sven Strickroth

    2014-09-01

    Full Text Available We present an approach (and a corresponding system design for supporting regionally bound hybrid learning communities (i.e., communities which combine traditional face-to-face elements with web based media such as online community platforms, e-mail and SMS newsletters. The goal of the example community used to illustrate the approach was to support and motivate (especially hard-to-reach underprivileged parents in the education of their young children. The article describes the design process used and the challenges faced during the socio-technical system design. An analysis of the community over more than one year indicates that the hybrid approach works better than the two separated “traditional” approaches separately. Synergy effects like advertising effects from the offline trainings for the online platform and vice versa occurred and regular newsletters turned out to have a noticeable effect on the community.

  10. 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.

  11. 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.

  12. The Effect of Think-Pair-Share-Write Based on Hybrid Learning on Metakognitive Skills, Creative Thinking and Cognitive Learning at SMA Negeri 3 Malang

    Directory of Open Access Journals (Sweden)

    Ika Yulianti Siregar

    2017-07-01

    Full Text Available The results of biology learning observation show that there are many constraints during the learning process in the class and consultation meeting between teacher and students. The think-pair-share-write based on hybrid learning was conducted to analyze the effect on metacognitive skills, creative thinking and learning outcomes. The research design was quasi experiment with pretest-posttest non-equivalent control group design. The independent variable is think-pair-share-write based on Hybrid learning model, while the dependent variables are metacognitive skills, creative thinking, and cognitive learning outcomes. Metacognitive skills are measured by using metacognitive rubrics. Creative thinking skills and cognitive learning outcomes are measured by using a description test. The data were taken by conducting pretest and posttest. The hypothesis test used was anakova with level of significance 0,05 (P <0,05, as the test result was significant then the test was continued to LSD. Before the anakova test, normality and homogeneity test were performed. The results showed that think-pair-share-write based on Hybrid Learning significantly affecting: 1 the metacognitive skills with F arithmetic of 183,472 and Sig. 0,000; 2 the creative thinking skill with F value of 325,111 and Sig. 0,000; 3 the cognitive learning outcomes with F arithmetic of 175.068 and Sig. 0,000.

  13. Energy Management Strategy for a Hybrid Electric Vehicle Based on Deep Reinforcement Learning

    Directory of Open Access Journals (Sweden)

    Yue Hu

    2018-01-01

    Full Text Available An energy management strategy (EMS is important for hybrid electric vehicles (HEVs since it plays a decisive role on the performance of the vehicle. However, the variation of future driving conditions deeply influences the effectiveness of the EMS. Most existing EMS methods simply follow predefined rules that are not adaptive to different driving conditions online. Therefore, it is useful that the EMS can learn from the environment or driving cycle. In this paper, a deep reinforcement learning (DRL-based EMS is designed such that it can learn to select actions directly from the states without any prediction or predefined rules. Furthermore, a DRL-based online learning architecture is presented. It is significant for applying the DRL algorithm in HEV energy management under different driving conditions. Simulation experiments have been conducted using MATLAB and Advanced Vehicle Simulator (ADVISOR co-simulation. Experimental results validate the effectiveness of the DRL-based EMS compared with the rule-based EMS in terms of fuel economy. The online learning architecture is also proved to be effective. The proposed method ensures the optimality, as well as real-time applicability, in HEVs.

  14. Assessing the effectiveness of a hybrid-flipped model of learning on fluid mechanics instruction: overall course performance, homework, and far- and near-transfer of learning

    Science.gov (United States)

    Harrison, David J.; Saito, Laurel; Markee, Nancy; Herzog, Serge

    2017-11-01

    To examine the impact of a hybrid-flipped model utilising active learning techniques, the researchers inverted one section of an undergraduate fluid mechanics course, reduced seat time, and engaged in active learning sessions in the classroom. We compared this model to the traditional section on four performance measures. We employed a propensity score method entailing a two-stage regression analysis that considered eight covariates to address the potential bias of treatment selection. First, we estimated the probability score based on the eight covariates, and second, we used the inverse of the probability score as a regression weight on the performance of learners who did not select into the hybrid course. Results suggest that enrolment in the hybrid-flipped section had a marginally significant negative impact on the total course score and a significant negative impact on homework performance, possibly because of poor video usage by the hybrid-flipped learners. Suggested considerations are also discussed.

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

    Science.gov (United States)

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

    2016-01-01

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

  16. Hybrid Learning in Higher Education: The Potential of Teaching and Learning with Robot-Mediated Communication

    Science.gov (United States)

    Gleason, Benjamin; Greenhow, Christine

    2017-01-01

    Blended learning, which combines online and face-to-face pedagogy, is a fast-growing mode of instruction as universities strive for equitable and alternative pathways to course enrollment, retention, and educational attainment. However, challenges to successfully implementing blended instruction are that "social presence," or students'…

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

    Science.gov (United States)

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

    2016-01-01

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

  18. Wind Power Ramp Events Prediction with Hybrid Machine Learning Regression Techniques and Reanalysis Data

    Directory of Open Access Journals (Sweden)

    Laura Cornejo-Bueno

    2017-11-01

    Full Text Available Wind Power Ramp Events (WPREs are large fluctuations of wind power in a short time interval, which lead to strong, undesirable variations in the electric power produced by a wind farm. Its accurate prediction is important in the effort of efficiently integrating wind energy in the electric system, without affecting considerably its stability, robustness and resilience. In this paper, we tackle the problem of predicting WPREs by applying Machine Learning (ML regression techniques. Our approach consists of using variables from atmospheric reanalysis data as predictive inputs for the learning machine, which opens the possibility of hybridizing numerical-physical weather models with ML techniques for WPREs prediction in real systems. Specifically, we have explored the feasibility of a number of state-of-the-art ML regression techniques, such as support vector regression, artificial neural networks (multi-layer perceptrons and extreme learning machines and Gaussian processes to solve the problem. Furthermore, the ERA-Interim reanalysis from the European Center for Medium-Range Weather Forecasts is the one used in this paper because of its accuracy and high resolution (in both spatial and temporal domains. Aiming at validating the feasibility of our predicting approach, we have carried out an extensive experimental work using real data from three wind farms in Spain, discussing the performance of the different ML regression tested in this wind power ramp event prediction problem.

  19. A hybrid fuzzy logic and extreme learning machine for improving efficiency of circulating water systems in power generation plant

    Science.gov (United States)

    Aziz, Nur Liyana Afiqah Abdul; Siah Yap, Keem; Afif Bunyamin, Muhammad

    2013-06-01

    This paper presents a new approach of the fault detection for improving efficiency of circulating water system (CWS) in a power generation plant using a hybrid Fuzzy Logic System (FLS) and Extreme Learning Machine (ELM) neural network. The FLS is a mathematical tool for calculating the uncertainties where precision and significance are applied in the real world. It is based on natural language which has the ability of "computing the word". The ELM is an extremely fast learning algorithm for neural network that can completed the training cycle in a very short time. By combining the FLS and ELM, new hybrid model, i.e., FLS-ELM is developed. The applicability of this proposed hybrid model is validated in fault detection in CWS which may help to improve overall efficiency of power generation plant, hence, consuming less natural recourses and producing less pollutions.

  20. A hybrid fuzzy logic and extreme learning machine for improving efficiency of circulating water systems in power generation plant

    International Nuclear Information System (INIS)

    Aziz, Nur Liyana Afiqah Abdul; Yap, Keem Siah; Bunyamin, Muhammad Afif

    2013-01-01

    This paper presents a new approach of the fault detection for improving efficiency of circulating water system (CWS) in a power generation plant using a hybrid Fuzzy Logic System (FLS) and Extreme Learning Machine (ELM) neural network. The FLS is a mathematical tool for calculating the uncertainties where precision and significance are applied in the real world. It is based on natural language which has the ability of c omputing the word . The ELM is an extremely fast learning algorithm for neural network that can completed the training cycle in a very short time. By combining the FLS and ELM, new hybrid model, i.e., FLS-ELM is developed. The applicability of this proposed hybrid model is validated in fault detection in CWS which may help to improve overall efficiency of power generation plant, hence, consuming less natural recourses and producing less pollutions.

  1. Hybrid Augmented Reality for Participatory Learning: The Hidden Efficacy of Multi-User Game-Based Simulation

    Science.gov (United States)

    Oh, Seungjae; So, Hyo-Jeong; Gaydos, Matthew

    2018-01-01

    The goal for this research is to articulate and test a new hybrid Augmented Reality (AR) environment for conceptual understanding. From the theoretical lens of embodied interaction, we have designed a multi-user participatory simulation called ARfract where visitors in a science museum can learn about complex scientific concepts on the refraction…

  2. Exploring the Use of Interactive Digital Storytelling Video: Promoting Student Engagement and Learning in a University Hybrid Course

    Science.gov (United States)

    Shelton, Catharyn C.; Warren, Annie E.; Archambault, Leanna M.

    2016-01-01

    This study explores interactive digital storytelling in a university hybrid course. Digital stories leverage imagery and narrative-based content to explore concepts, while appealing to millennials. When digital storytelling is used as the main source of course content, tensions arise regarding how to engage and support student learning while…

  3. Teachers and Students' Perceptions of a Hybrid Sport Education and Teaching for Personal and Social Responsibility Learning Unit

    Science.gov (United States)

    Fernandez-Rio, Javier; Menendez-Santurio, Jose Ignacio

    2017-01-01

    Purpose: The purpose of this study was to assess students and teachers' perceptions concerning their participation in an educational kickboxing learning unit based on a hybridization of two pedagogical models: Sport Education and Teaching for Personal and Social Responsibility. Method: Seventy-one students and three physical education teachers…

  4. Developing a Hybrid Model to Predict Student First Year Retention in STEM Disciplines Using Machine Learning Techniques

    Science.gov (United States)

    Alkhasawneh, Ruba; Hargraves, Rosalyn Hobson

    2014-01-01

    The purpose of this research was to develop a hybrid framework to model first year student retention for underrepresented minority (URM) students comprising African Americans, Hispanic Americans, and Native Americans. Identifying inputs that best contribute to student retention provides significant information for institutions to learn about…

  5. Predicting Freeway Work Zone Delays and Costs with a Hybrid Machine-Learning Model

    Directory of Open Access Journals (Sweden)

    Bo Du

    2017-01-01

    Full Text Available A hybrid machine-learning model, integrating an artificial neural network (ANN and a support vector machine (SVM model, is developed to predict spatiotemporal delays, subject to road geometry, number of lane closures, and work zone duration in different periods of a day and in the days of a week. The model is very user friendly, allowing the least inputs from the users. With that the delays caused by a work zone on any location of a New Jersey freeway can be predicted. To this end, tremendous amounts of data from different sources were collected to establish the relationship between the model inputs and outputs. A comparative analysis was conducted, and results indicate that the proposed model outperforms others in terms of the least root mean square error (RMSE. The proposed hybrid model can be used to calculate contractor penalty in terms of cost overruns as well as incentive reward schedule in case of early work competition. Additionally, it can assist work zone planners in determining the best start and end times of a work zone for developing and evaluating traffic mitigation and management plans.

  6. A hybrid bird mating optimizer algorithm with teaching-learning-based optimization for global numerical optimization

    Directory of Open Access Journals (Sweden)

    Qingyang Zhang

    2015-02-01

    Full Text Available Bird Mating Optimizer (BMO is a novel meta-heuristic optimization algorithm inspired by intelligent mating behavior of birds. However, it is still insufficient in convergence of speed and quality of solution. To overcome these drawbacks, this paper proposes a hybrid algorithm (TLBMO, which is established by combining the advantages of Teaching-learning-based optimization (TLBO and Bird Mating Optimizer (BMO. The performance of TLBMO is evaluated on 23 benchmark functions, and compared with seven state-of-the-art approaches, namely BMO, TLBO, Artificial Bee Bolony (ABC, Particle Swarm Optimization (PSO, Fast Evolution Programming (FEP, Differential Evolution (DE, Group Search Optimization (GSO. Experimental results indicate that the proposed method performs better than other existing algorithms for global numerical optimization.

  7. A Prediction Method of Airport Noise Based on Hybrid Ensemble Learning

    Directory of Open Access Journals (Sweden)

    Tao XU

    2014-05-01

    Full Text Available Using monitoring history data to build and to train a prediction model for airport noise is a normal method in recent years. However, the single model built in different ways has various performances in the storage, efficiency and accuracy. In order to predict the noise accurately in some complex environment around airport, this paper presents a prediction method based on hybrid ensemble learning. The proposed method ensembles three algorithms: artificial neural network as an active learner, nearest neighbor as a passive leaner and nonlinear regression as a synthesized learner. The experimental results show that the three learners can meet forecast demands respectively in on- line, near-line and off-line. And the accuracy of prediction is improved by integrating these three learners’ results.

  8. A Hybrid dasymetric and machine learning approach to high-resolution residential electricity consumption modeling

    Energy Technology Data Exchange (ETDEWEB)

    Morton, April M [ORNL; Nagle, Nicholas N [ORNL; Piburn, Jesse O [ORNL; Stewart, Robert N [ORNL; McManamay, Ryan A [ORNL

    2017-01-01

    As urban areas continue to grow and evolve in a world of increasing environmental awareness, the need for detailed information regarding residential energy consumption patterns has become increasingly important. Though current modeling efforts mark significant progress in the effort to better understand the spatial distribution of energy consumption, the majority of techniques are highly dependent on region-specific data sources and often require building- or dwelling-level details that are not publicly available for many regions in the United States. Furthermore, many existing methods do not account for errors in input data sources and may not accurately reflect inherent uncertainties in model outputs. We propose an alternative and more general hybrid approach to high-resolution residential electricity consumption modeling by merging a dasymetric model with a complementary machine learning algorithm. The method s flexible data requirement and statistical framework ensure that the model both is applicable to a wide range of regions and considers errors in input data sources.

  9. Robust total energy demand estimation with a hybrid Variable Neighborhood Search – Extreme Learning Machine algorithm

    International Nuclear Information System (INIS)

    Sánchez-Oro, J.; Duarte, A.; Salcedo-Sanz, S.

    2016-01-01

    Highlights: • The total energy demand in Spain is estimated with a Variable Neighborhood algorithm. • Socio-economic variables are used, and one year ahead prediction horizon is considered. • Improvement of the prediction with an Extreme Learning Machine network is considered. • Experiments are carried out in real data for the case of Spain. - Abstract: Energy demand prediction is an important problem whose solution is evaluated by policy makers in order to take key decisions affecting the economy of a country. A number of previous approaches to improve the quality of this estimation have been proposed in the last decade, the majority of them applying different machine learning techniques. In this paper, the performance of a robust hybrid approach, composed of a Variable Neighborhood Search algorithm and a new class of neural network called Extreme Learning Machine, is discussed. The Variable Neighborhood Search algorithm is focused on obtaining the most relevant features among the set of initial ones, by including an exponential prediction model. While previous approaches consider that the number of macroeconomic variables used for prediction is a parameter of the algorithm (i.e., it is fixed a priori), the proposed Variable Neighborhood Search method optimizes both: the number of variables and the best ones. After this first step of feature selection, an Extreme Learning Machine network is applied to obtain the final energy demand prediction. Experiments in a real case of energy demand estimation in Spain show the excellent performance of the proposed approach. In particular, the whole method obtains an estimation of the energy demand with an error lower than 2%, even when considering the crisis years, which are a real challenge.

  10. Prediction Errors of Molecular Machine Learning Models Lower than Hybrid DFT Error.

    Science.gov (United States)

    Faber, Felix A; Hutchison, Luke; Huang, Bing; Gilmer, Justin; Schoenholz, Samuel S; Dahl, George E; Vinyals, Oriol; Kearnes, Steven; Riley, Patrick F; von Lilienfeld, O Anatole

    2017-11-14

    We investigate the impact of choosing regressors and molecular representations for the construction of fast machine learning (ML) models of 13 electronic ground-state properties of organic molecules. The performance of each regressor/representation/property combination is assessed using learning curves which report out-of-sample errors as a function of training set size with up to ∼118k distinct molecules. Molecular structures and properties at the hybrid density functional theory (DFT) level of theory come from the QM9 database [ Ramakrishnan et al. Sci. Data 2014 , 1 , 140022 ] and include enthalpies and free energies of atomization, HOMO/LUMO energies and gap, dipole moment, polarizability, zero point vibrational energy, heat capacity, and the highest fundamental vibrational frequency. Various molecular representations have been studied (Coulomb matrix, bag of bonds, BAML and ECFP4, molecular graphs (MG)), as well as newly developed distribution based variants including histograms of distances (HD), angles (HDA/MARAD), and dihedrals (HDAD). Regressors include linear models (Bayesian ridge regression (BR) and linear regression with elastic net regularization (EN)), random forest (RF), kernel ridge regression (KRR), and two types of neural networks, graph convolutions (GC) and gated graph networks (GG). Out-of sample errors are strongly dependent on the choice of representation and regressor and molecular property. Electronic properties are typically best accounted for by MG and GC, while energetic properties are better described by HDAD and KRR. The specific combinations with the lowest out-of-sample errors in the ∼118k training set size limit are (free) energies and enthalpies of atomization (HDAD/KRR), HOMO/LUMO eigenvalue and gap (MG/GC), dipole moment (MG/GC), static polarizability (MG/GG), zero point vibrational energy (HDAD/KRR), heat capacity at room temperature (HDAD/KRR), and highest fundamental vibrational frequency (BAML/RF). We present numerical

  11. Scheduled power tracking control of the wind-storage hybrid system based on the reinforcement learning theory

    Science.gov (United States)

    Li, Ze

    2017-09-01

    In allusion to the intermittency and uncertainty of the wind electricity, energy storage and wind generator are combined into a hybrid system to improve the controllability of the output power. A scheduled power tracking control method is proposed based on the reinforcement learning theory and Q-learning algorithm. In this method, the state space of the environment is formed with two key factors, i.e. the state of charge of the energy storage and the difference value between the actual wind power and scheduled power, the feasible action is the output power of the energy storage, and the corresponding immediate rewarding function is designed to reflect the rationality of the control action. By interacting with the environment and learning from the immediate reward, the optimal control strategy is gradually formed. After that, it could be applied to the scheduled power tracking control of the hybrid system. Finally, the rationality and validity of the method are verified through simulation examples.

  12. Inference of time-delayed gene regulatory networks based on dynamic Bayesian network hybrid learning method.

    Science.gov (United States)

    Yu, Bin; Xu, Jia-Meng; Li, Shan; Chen, Cheng; Chen, Rui-Xin; Wang, Lei; Zhang, Yan; Wang, Ming-Hui

    2017-10-06

    Gene regulatory networks (GRNs) research reveals complex life phenomena from the perspective of gene interaction, which is an important research field in systems biology. Traditional Bayesian networks have a high computational complexity, and the network structure scoring model has a single feature. Information-based approaches cannot identify the direction of regulation. In order to make up for the shortcomings of the above methods, this paper presents a novel hybrid learning method (DBNCS) based on dynamic Bayesian network (DBN) to construct the multiple time-delayed GRNs for the first time, combining the comprehensive score (CS) with the DBN model. DBNCS algorithm first uses CMI2NI (conditional mutual inclusive information-based network inference) algorithm for network structure profiles learning, namely the construction of search space. Then the redundant regulations are removed by using the recursive optimization algorithm (RO), thereby reduce the false positive rate. Secondly, the network structure profiles are decomposed into a set of cliques without loss, which can significantly reduce the computational complexity. Finally, DBN model is used to identify the direction of gene regulation within the cliques and search for the optimal network structure. The performance of DBNCS algorithm is evaluated by the benchmark GRN datasets from DREAM challenge as well as the SOS DNA repair network in Escherichia coli , and compared with other state-of-the-art methods. The experimental results show the rationality of the algorithm design and the outstanding performance of the GRNs.

  13. Saliency U-Net: A regional saliency map-driven hybrid deep learning network for anomaly segmentation

    Science.gov (United States)

    Karargyros, Alex; Syeda-Mahmood, Tanveer

    2018-02-01

    Deep learning networks are gaining popularity in many medical image analysis tasks due to their generalized ability to automatically extract relevant features from raw images. However, this can make the learning problem unnecessarily harder requiring network architectures of high complexity. In case of anomaly detection, in particular, there is often sufficient regional difference between the anomaly and the surrounding parenchyma that could be easily highlighted through bottom-up saliency operators. In this paper we propose a new hybrid deep learning network using a combination of raw image and such regional maps to more accurately learn the anomalies using simpler network architectures. Specifically, we modify a deep learning network called U-Net using both the raw and pre-segmented images as input to produce joint encoding (contraction) and expansion paths (decoding) in the U-Net. We present results of successfully delineating subdural and epidural hematomas in brain CT imaging and liver hemangioma in abdominal CT images using such network.

  14. Can Hybrid Educational Activities of Team and Problem Based Learning Program be Effective for Japanese Medical Students?

    Science.gov (United States)

    Iwata, Kentaro; Doi, Asako

    2017-11-10

    The purpose of this study is to investigate the medical students'perceptions of the Hybrid Educational Activities between team based learning (TBL) and problem based learning (PBL) Program (HEATAPP), a novel educational program that combines characteristics of PBL and TBL. A five-day HEATAPP on infectious diseases was provided to 4th year medical students at Kobe University School of Medicine, Kobe, Japan. After the program, a focus group discussion was held among 6 medical students who participated in HEATAPP. We qualitatively analyzed the recorded data to delineate the effectiveness of, and the perceptions on, HEATAPP. Some students considered HEATAPP being effective as an active learning, and in developing questions. However, some students found active learning difficult to execute, since they were so familiar with passive learning such as lectures and examinations. They also found it difficult to identify important points by reading authentic textbooks on given issues, particularly English textbooks. Even though active learning and group discussion are underscored as important in medicine, some Japanese medical students may be reluctant to shift towards these since they are so used to passive learning since childhood. English language is another barrier to active learning. The introduction of active learning in the earlier stages of education might be an effective solution. Teachers at medical schools in Japan should be mindful of the students'potentially negative attitudes towards active learning, which is claimed to be successful in western countries.

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

    KAUST Repository

    Prasetyo Utomo, Chandra

    2011-06-01

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

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

    Science.gov (United States)

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

    2017-01-01

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

  17. Students' satisfaction to hybrid problem-based learning format for basic life support/advanced cardiac life support teaching.

    Science.gov (United States)

    Chilkoti, Geetanjali; Mohta, Medha; Wadhwa, Rachna; Saxena, Ashok Kumar; Sharma, Chhavi Sarabpreet; Shankar, Neelima

    2016-11-01

    Students are exposed to basic life support (BLS) and advanced cardiac life support (ACLS) training in the first semester in some medical colleges. The aim of this study was to compare students' satisfaction between lecture-based traditional method and hybrid problem-based learning (PBL) in BLS/ACLS teaching to undergraduate medical students. We conducted a questionnaire-based, cross-sectional survey among 118 1 st -year medical students from a university medical college in the city of New Delhi, India. We aimed to assess the students' satisfaction between lecture-based and hybrid-PBL method in BLS/ACLS teaching. Likert 5-point scale was used to assess students' satisfaction levels between the two teaching methods. Data were collected and scores regarding the students' satisfaction levels between these two teaching methods were analysed using a two-sided paired t -test. Most students preferred hybrid-PBL format over traditional lecture-based method in the following four aspects; learning and understanding, interest and motivation, training of personal abilities and being confident and satisfied with the teaching method ( P < 0.05). Implementation of hybrid-PBL format along with the lecture-based method in BLS/ACLS teaching provided high satisfaction among undergraduate medical students.

  18. Feedback error learning controller for functional electrical stimulation assistance in a hybrid robotic system for reaching rehabilitation

    Directory of Open Access Journals (Sweden)

    Francisco Resquín

    2016-07-01

    Full Text Available Hybrid robotic systems represent a novel research field, where functional electrical stimulation (FES is combined with a robotic device for rehabilitation of motor impairment. Under this approach, the design of robust FES controllers still remains an open challenge. In this work, we aimed at developing a learning FES controller to assist in the performance of reaching movements in a simple hybrid robotic system setting. We implemented a Feedback Error Learning (FEL control strategy consisting of a feedback PID controller and a feedforward controller based on a neural network. A passive exoskeleton complemented the FES controller by compensating the effects of gravity. We carried out experiments with healthy subjects to validate the performance of the system. Results show that the FEL control strategy is able to adjust the FES intensity to track the desired trajectory accurately without the need of a previous mathematical model.

  19. WWC Review of the Report "Interactive Online Learning on Campus: Testing MOOCs and Other Platforms in Hybrid Formats in the University System of Maryland." What Works Clearinghouse Single Study Review

    Science.gov (United States)

    What Works Clearinghouse, 2015

    2015-01-01

    In the 2014 study, "Interactive Online Learning on Campus: Testing MOOCs and Other Platforms in Hybrid Formats in the University System of Maryland," researchers examined the impact of using hybrid forms of interactive online learning in seven undergraduate courses across seven universities in Maryland. Hybrid forms of interactive online…

  20. Fast and accurate semantic annotation of bioassays exploiting a hybrid of machine learning and user confirmation.

    Science.gov (United States)

    Clark, Alex M; Bunin, Barry A; Litterman, Nadia K; Schürer, Stephan C; Visser, Ubbo

    2014-01-01

    Bioinformatics and computer aided drug design rely on the curation of a large number of protocols for biological assays that measure the ability of potential drugs to achieve a therapeutic effect. These assay protocols are generally published by scientists in the form of plain text, which needs to be more precisely annotated in order to be useful to software methods. We have developed a pragmatic approach to describing assays according to the semantic definitions of the BioAssay Ontology (BAO) project, using a hybrid of machine learning based on natural language processing, and a simplified user interface designed to help scientists curate their data with minimum effort. We have carried out this work based on the premise that pure machine learning is insufficiently accurate, and that expecting scientists to find the time to annotate their protocols manually is unrealistic. By combining these approaches, we have created an effective prototype for which annotation of bioassay text within the domain of the training set can be accomplished very quickly. Well-trained annotations require single-click user approval, while annotations from outside the training set domain can be identified using the search feature of a well-designed user interface, and subsequently used to improve the underlying models. By drastically reducing the time required for scientists to annotate their assays, we can realistically advocate for semantic annotation to become a standard part of the publication process. Once even a small proportion of the public body of bioassay data is marked up, bioinformatics researchers can begin to construct sophisticated and useful searching and analysis algorithms that will provide a diverse and powerful set of tools for drug discovery researchers.

  1. Fast and accurate semantic annotation of bioassays exploiting a hybrid of machine learning and user confirmation

    Directory of Open Access Journals (Sweden)

    Alex M. Clark

    2014-08-01

    Full Text Available Bioinformatics and computer aided drug design rely on the curation of a large number of protocols for biological assays that measure the ability of potential drugs to achieve a therapeutic effect. These assay protocols are generally published by scientists in the form of plain text, which needs to be more precisely annotated in order to be useful to software methods. We have developed a pragmatic approach to describing assays according to the semantic definitions of the BioAssay Ontology (BAO project, using a hybrid of machine learning based on natural language processing, and a simplified user interface designed to help scientists curate their data with minimum effort. We have carried out this work based on the premise that pure machine learning is insufficiently accurate, and that expecting scientists to find the time to annotate their protocols manually is unrealistic. By combining these approaches, we have created an effective prototype for which annotation of bioassay text within the domain of the training set can be accomplished very quickly. Well-trained annotations require single-click user approval, while annotations from outside the training set domain can be identified using the search feature of a well-designed user interface, and subsequently used to improve the underlying models. By drastically reducing the time required for scientists to annotate their assays, we can realistically advocate for semantic annotation to become a standard part of the publication process. Once even a small proportion of the public body of bioassay data is marked up, bioinformatics researchers can begin to construct sophisticated and useful searching and analysis algorithms that will provide a diverse and powerful set of tools for drug discovery researchers.

  2. Communicator Style as a Predictor of Cyberbullying in a Hybrid Learning Environment

    Directory of Open Access Journals (Sweden)

    Özcan Özgür Dursun

    2012-07-01

    Full Text Available This study aimed to describe the characteristics of undergraduate students in a hybrid learning environment with regard to their communicator styles and cyberbullying behaviors. Moreover, relationships between cyberbullying victimization and learners’ perceived communicator styles were investigated. Cyberbullying victimization was measured through a recently developed 28-item scale with a single-factor structure, whereas the communicator styles were measured through Norton’s (1983 scale which was recently validated in Turkey. Participants were a total of 59 undergraduate Turkish students enrolled in an effective communication course in 2010 spring and fall semesters. Face-to-face instruction was supported through web 2.0 tools where learners’ hid their real identities through nicknames. Participants used personal blogs in addition to the official online platform of the course. Their posts on these platforms were used as the source of the qualitative data. Descriptive analyses were followed by the investigation of qualitative and quantitative interrelationships between the cyberbullying variable and the components of the communicator style measure. Correlations among victimization and communicator style variables were not significant. However, qualitative analysis revealed that cyberbullying instances varied with regard to discussion topics, nature of the discussions and communicator styles. Example patterns from the log files were presented accompanied with suggestions for further implementations.

  3. Communicator Style as a Predictor of Cyberbullying in a Hybrid Learning Environment

    Directory of Open Access Journals (Sweden)

    Özcan Özgür Dursun

    2012-03-01

    Full Text Available This study aimed to describe the characteristics of undergraduate students in a hybrid learning environment with regard to their communicator styles and cyberbullying behaviors. Moreover, relationships between cyberbullying victimization and learners’ perceived communicator styles were investigated. Cyberbullying victimization was measured through a recently developed 28-item scale with a single-factor structure, whereas the communicator styles were measured through Norton’s (1983 scale which was recently validated in Turkey. Participants were a total of 59 undergraduate Turkish students enrolled in an effective communication course in 2010 spring and fall semesters. Face-to-face instruction was supported through web 2.0 tools where learners’ hid their real identities through nicknames. Participants used personal blogs in addition to the official online platform of the course. Their posts on these platforms were used as the source of the qualitative data. Descriptive analyses were followed by the investigation of qualitative and quantitative interrelationships between the cyberbullying variable and the components of the communicator style measure. Correlations among victimization and communicator style variables were not significant. However, qualitative analysis revealed that cyberbullying instances varied with regard to discussion topics, nature of the discussions and communicator styles. Example patterns from the log files were presented accompanied with suggestions for further implementations

  4. A DDoS Attack Detection Method Based on Hybrid Heterogeneous Multiclassifier Ensemble Learning

    Directory of Open Access Journals (Sweden)

    Bin Jia

    2017-01-01

    Full Text Available The explosive growth of network traffic and its multitype on Internet have brought new and severe challenges to DDoS attack detection. To get the higher True Negative Rate (TNR, accuracy, and precision and to guarantee the robustness, stability, and universality of detection system, in this paper, we propose a DDoS attack detection method based on hybrid heterogeneous multiclassifier ensemble learning and design a heuristic detection algorithm based on Singular Value Decomposition (SVD to construct our detection system. Experimental results show that our detection method is excellent in TNR, accuracy, and precision. Therefore, our algorithm has good detective performance for DDoS attack. Through the comparisons with Random Forest, k-Nearest Neighbor (k-NN, and Bagging comprising the component classifiers when the three algorithms are used alone by SVD and by un-SVD, it is shown that our model is superior to the state-of-the-art attack detection techniques in system generalization ability, detection stability, and overall detection performance.

  5. Hybrid fitness, adaptation and evolutionary diversification: lessons learned from Louisiana Irises.

    Science.gov (United States)

    Arnold, M L; Ballerini, E S; Brothers, A N

    2012-03-01

    Estimates of hybrid fitness have been used as either a platform for testing the potential role of natural hybridization in the evolution of species and species complexes or, alternatively, as a rationale for dismissing hybridization events as being of any evolutionary significance. From the time of Darwin's publication of The Origin, through the neo-Darwinian synthesis, to the present day, the observation of variability in hybrid fitness has remained a challenge for some models of speciation. Yet, Darwin and others have reported the elevated fitness of hybrid genotypes under certain environmental conditions. In modern scientific terminology, this observation reflects the fact that hybrid genotypes can demonstrate genotype × environment interactions. In the current review, we illustrate the development of one plant species complex, namely the Louisiana Irises, into a 'model system' for investigating hybrid fitness and the role of genetic exchange in adaptive evolution and diversification. In particular, we will argue that a multitude of approaches, involving both experimental and natural environments, and incorporating both manipulative analyses and surveys of natural populations, are necessary to adequately test for the evolutionary significance of introgressive hybridization. An appreciation of the variability of hybrid fitness leads to the conclusion that certain genetic signatures reflect adaptive evolution. Furthermore, tests of the frequency of allopatric versus sympatric/parapatric divergence (that is, divergence with ongoing gene flow) support hybrid genotypes as a mechanism of evolutionary diversification in numerous species complexes.

  6. On the electrification of road transport - Learning rates and price forecasts for hybrid-electric and battery-electric vehicles

    International Nuclear Information System (INIS)

    Weiss, Martin; Patel, Martin K.; Junginger, Martin; Perujo, Adolfo; Bonnel, Pierre; Grootveld, Geert van

    2012-01-01

    Hybrid-electric vehicles (HEVs) and battery-electric vehicles (BEVs) are currently more expensive than conventional passenger cars but may become cheaper due to technological learning. Here, we obtain insight into the prospects of future price decline by establishing ex-post learning rates for HEVs and ex-ante price forecasts for HEVs and BEVs. Since 1997, HEVs have shown a robust decline in their price and price differential at learning rates of 7±2% and 23±5%, respectively. By 2010, HEVs were only 31±22 € 2010 kW −1 more expensive than conventional cars. Mass-produced BEVs are currently introduced into the market at prices of 479±171 € 2010 kW −1 , which is 285±213 € 2010 kW −1 and 316±209 € 2010 kW −1 more expensive than HEVs and conventional cars. Our forecast suggests that price breakeven with these vehicles may only be achieved by 2026 and 2032, when 50 and 80 million BEVs, respectively, would have been produced worldwide. We estimate that BEVs may require until then global learning investments of 100–150 billion € which is less than the global subsidies for fossil fuel consumption paid in 2009. These findings suggest that HEVs, including plug-in HEVs, could become the dominant vehicle technology in the next two decades, while BEVs may require long-term policy support. - Highlights: ► Learning rates for hybrid-electric and battery-electric vehicles. ► Prices and price differentials of hybrid-electric vehicles show a robust decline. ► Battery-electric vehicles may require policy support for decades.

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

    Directory of Open Access Journals (Sweden)

    Miraemiliana Murat

    2017-09-01

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

  8. Looking into the crystal ball: future device learning using hybrid e-beam and optical lithography (Keynote Paper)

    Science.gov (United States)

    Steen, S. E.; McNab, S. J.; Sekaric, L.; Babich, I.; Patel, J.; Bucchignano, J.; Rooks, M.; Fried, D. M.; Topol, A. W.; Brancaccio, J. R.; Yu, R.; Hergenrother, J. M.; Doyle, J. P.; Nunes, R.; Viswanathan, R. G.; Purushothaman, S.; Rothwell, M. B.

    2005-05-01

    Semiconductor process development teams are faced with increasing process and integration complexity while the time between lithographic capability and volume production has remained more or less constant over the last decade. Lithography tools have often gated the volume checkpoint of a new device node on the ITRS roadmap. The processes have to be redeveloped after the tooling capability for the new groundrule is obtained since straight scaling is no longer sufficient. In certain cases the time window that the process development teams have is actually decreasing. In the extreme, some forecasts are showing that by the time the 45nm technology node is scheduled for volume production, the tooling vendors will just begin shipping the tools required for this technology node. To address this time pressure, IBM has implemented a hybrid-lithography strategy that marries the advantages of optical lithography (high throughput) with electron beam direct write lithography (high resolution and alignment capability). This hybrid-lithography scheme allows for the timely development of semiconductor processes for the 32nm node, and beyond. In this paper we will describe how hybrid lithography has enabled early process integration and device learning and how IBM applied e-beam & optical hybrid lithography to create the world's smallest working SRAM cell.

  9. Research and application of a novel hybrid decomposition-ensemble learning paradigm with error correction for daily PM10 forecasting

    Science.gov (United States)

    Luo, Hongyuan; Wang, Deyun; Yue, Chenqiang; Liu, Yanling; Guo, Haixiang

    2018-03-01

    In this paper, a hybrid decomposition-ensemble learning paradigm combining error correction is proposed for improving the forecast accuracy of daily PM10 concentration. The proposed learning paradigm is consisted of the following two sub-models: (1) PM10 concentration forecasting model; (2) error correction model. In the proposed model, fast ensemble empirical mode decomposition (FEEMD) and variational mode decomposition (VMD) are applied to disassemble original PM10 concentration series and error sequence, respectively. The extreme learning machine (ELM) model optimized by cuckoo search (CS) algorithm is utilized to forecast the components generated by FEEMD and VMD. In order to prove the effectiveness and accuracy of the proposed model, two real-world PM10 concentration series respectively collected from Beijing and Harbin located in China are adopted to conduct the empirical study. The results show that the proposed model performs remarkably better than all other considered models without error correction, which indicates the superior performance of the proposed model.

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

    Science.gov (United States)

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

    2018-03-01

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

  11. A Novel Approach for Enhancing Lifelong Learning Systems by Using Hybrid Recommender System

    Science.gov (United States)

    Kardan, Ahmad A.; Speily, Omid R. B.; Modaberi, Somayyeh

    2011-01-01

    The majority of current web-based learning systems are closed learning environments where courses and learning materials are fixed, and the only dynamic aspect is the organization of the material that can be adapted to allow a relatively individualized learning environment. In this paper, we propose an evolving web-based learning system which can…

  12. Strategic and organizational Insights into learning and innovation in hybrids and "new" organizations

    NARCIS (Netherlands)

    Annosi, M.C.; Brunetta, Federica

    2018-01-01

    The aim of this chapter is to introduce the reader to the concepts of hybrid and new organizations. Its intent is also to make clear the type of contribution the book is intended to bring to the literature on hybrid organizations. The structure of the book and how to navigate it, together with a

  13. Pedagogy and Process: A Case Study of Writing in a Hybrid Learning Model

    Science.gov (United States)

    Keiner, Jason F.

    2017-01-01

    This qualitative case study explored the perceived experiences and outcomes of writing in a hybrid model of instruction in a large suburban high school. In particular, the impact of a hybrid model on the writing process and on future writing performance were examined. In addition, teacher expectation and teacher attitude and their impact upon…

  14. Innovation Online Teaching Module Plus Digital Engineering Kit with Proteus Software through Hybrid Learning Method to Improve Student Skills

    Science.gov (United States)

    Kholis, Nur; Syariffuddien Zuhrie, Muhamad; Rahmadian, Reza

    2018-04-01

    Demands the competence (competence) needs of the industry today is a competent workforce to the field of work. However, during this lecture material Digital Engineering (Especially Digital Electronics Basics and Digital Circuit Basics) is limited to the delivery of verbal form of lectures (classical method) is dominated by the Lecturer (Teacher Centered). Though the subject of Digital Engineering requires learning tools and is required understanding of electronic circuits, digital electronics and high logic circuits so that learners can apply in the world of work. One effort to make it happen is by creating an online teaching module and educational aids (Kit) with the help of Proteus software that can improve the skills of learners. This study aims to innovate online teaching modules plus kits in Proteus-assisted digital engineering courses through hybrid learning approaches to improve the skills of learners. The process of innovation is done by considering the skills and mastery of the technology of students (students) Department of Electrical Engineering - Faculty of Engineering – Universitas Negeri Surabaya to produce quality graduates Use of online module plus Proteus software assisted kit through hybrid learning approach. In general, aims to obtain adequate results with affordable cost of investment, user friendly, attractive and interactive (easily adapted to the development of Information and Communication Technology). With the right design, implementation and operation, both in the form of software both in the form of Online Teaching Module, offline teaching module, Kit (Educational Viewer), and e-learning learning content (both online and off line), the use of the three tools of the expenditure will be able to adjust the standard needs of Information and Communication Technology world, both nationally and internationally.

  15. Hybrid attribute-based recommender system for learning material using genetic algorithm and a multidimensional information model

    Directory of Open Access Journals (Sweden)

    Mojtaba Salehi

    2013-03-01

    Full Text Available In recent years, the explosion of learning materials in the web-based educational systems has caused difficulty of locating appropriate learning materials to learners. A personalized recommendation is an enabling mechanism to overcome information overload occurred in the new learning environments and deliver suitable materials to learners. Since users express their opinions based on some specific attributes of items, this paper proposes a hybrid recommender system for learning materials based on their attributes to improve the accuracy and quality of recommendation. The presented system has two main modules: explicit attribute-based recommender and implicit attribute-based recommender. In the first module, weights of implicit or latent attributes of materials for learner are considered as chromosomes in genetic algorithm then this algorithm optimizes the weights according to historical rating. Then, recommendation is generated by Nearest Neighborhood Algorithm (NNA using the optimized weight vectors implicit attributes that represent the opinions of learners. In the second, preference matrix (PM is introduced that can model the interests of learner based on explicit attributes of learning materials in a multidimensional information model. Then, a new similarity measure between PMs is introduced and recommendations are generated by NNA. The experimental results show that our proposed method outperforms current algorithms on accuracy measures and can alleviate some problems such as cold-start and sparsity.

  16. Implementation of real-time energy management strategy based on reinforcement learning for hybrid electric vehicles and simulation validation.

    Directory of Open Access Journals (Sweden)

    Zehui Kong

    Full Text Available To further improve the fuel economy of series hybrid electric tracked vehicles, a reinforcement learning (RL-based real-time energy management strategy is developed in this paper. In order to utilize the statistical characteristics of online driving schedule effectively, a recursive algorithm for the transition probability matrix (TPM of power-request is derived. The reinforcement learning (RL is applied to calculate and update the control policy at regular time, adapting to the varying driving conditions. A facing-forward powertrain model is built in detail, including the engine-generator model, battery model and vehicle dynamical model. The robustness and adaptability of real-time energy management strategy are validated through the comparison with the stationary control strategy based on initial transition probability matrix (TPM generated from a long naturalistic driving cycle in the simulation. Results indicate that proposed method has better fuel economy than stationary one and is more effective in real-time control.

  17. Implementation of real-time energy management strategy based on reinforcement learning for hybrid electric vehicles and simulation validation.

    Science.gov (United States)

    Kong, Zehui; Zou, Yuan; Liu, Teng

    2017-01-01

    To further improve the fuel economy of series hybrid electric tracked vehicles, a reinforcement learning (RL)-based real-time energy management strategy is developed in this paper. In order to utilize the statistical characteristics of online driving schedule effectively, a recursive algorithm for the transition probability matrix (TPM) of power-request is derived. The reinforcement learning (RL) is applied to calculate and update the control policy at regular time, adapting to the varying driving conditions. A facing-forward powertrain model is built in detail, including the engine-generator model, battery model and vehicle dynamical model. The robustness and adaptability of real-time energy management strategy are validated through the comparison with the stationary control strategy based on initial transition probability matrix (TPM) generated from a long naturalistic driving cycle in the simulation. Results indicate that proposed method has better fuel economy than stationary one and is more effective in real-time control.

  18. Simulated human patients and patient-centredness: The uncanny hybridity of nursing education, technology, and learning to care.

    Science.gov (United States)

    Ireland, Aileen V

    2017-01-01

    Positioned within a hybrid of the human and technology, professional nursing practice has always occupied a space that is more than human. In nursing education, technology is central in providing tools with which practice knowledge is mobilized so that students can safely engage with simulated human patients without causing harm to real people. However, while there is an increased emphasis on deploying these simulated humans as emissaries from person-centred care to demonstrate what it is like to care for real humans, the nature of what is really going on in simulation-what is real and what is simulated-is very rarely discussed and poorly understood. This paper explores how elements of postcolonial critical thought can aid in understanding the challenges of educating nurses to provide person-centred care within a healthcare culture that is increasingly reliant on technology. Because nursing education is itself a hybrid of real and simulated practice, it provides an appropriate case study to explore the philosophical question of technology in healthcare discourse, particularly as it relates to the relationship between the human patient and its uncanny simulated double. Drawing on postcolonial elements such as the uncanny, diaspora, hybridity, and créolité, the hybrid conditions of nursing education are examined in order to open up new possibilities of thinking about how learning to care is entangled with this technological space to assist in shaping professional knowledge of person-centred care. Considering these issues through a postcolonial lens opens up questions about the nature of the difficulty in using simulated human technologies in clinical education, particularly with the paradoxical aim of providing person-centred care within a climate that increasingly characterized as posthuman. © 2016 John Wiley & Sons Ltd.

  19. The Hybrid Studio--Introducing Google+ as a Blended Learning Platform for Architectural Design Studio Teaching

    Science.gov (United States)

    Steinø, Nicolai; Khalid, Md. Saufuddin

    2017-01-01

    Much architecture and design teaching is based on the studio format, where the co-presence in time and space of students, instructors and physical learning artefacts form a triangle from which the learning emerges. Yet with the advent of online communication platforms and learning management systems (LMS), there is reason to study how these…

  20. Is K-12 Blended Learning Disruptive? An Introduction to the Theory of Hybrids

    Science.gov (United States)

    Christensen, Clayton M.; Horn, Michael B.; Staker, Heather

    2013-01-01

    The Clayton Christensen Institute for Disruptive Innovation, formerly the Innosight Institute, has published three papers describing the rise of K-12 blended learning--that is, formal education programs that combine online learning and brick-and-mortar schools. This fourth paper is the first to analyze blended learning through the lens of…

  1. Representing Clarity: Using Universal Design Principles to Create Effective Hybrid Course Learning Materials

    Science.gov (United States)

    Spiegel, Cheri Lemieux

    2012-01-01

    This article describes how the author applied principles of universal design to hybrid course materials to increase student understanding and, ultimately, success. Pulling the three principles of universal design--consistency, color, and icon representation--into the author's Blackboard course allowed her to change the types of reading skills…

  2. Language and learning in the international university from English uniformity to diversity and hybridity

    CERN Document Server

    Preisler, Bent; Fabricius, Anne

    2011-01-01

    Based on a series of studies from universities around the world, this book suggests that internationalization does not equate with across-the-board use of English, and instead represents a new cultural and linguistic hybridity with the potential to develop new identities unfettered by traditional 'us-and-them' binary thinking.

  3. Hybrid qualifications. Increasing the value of vocational education and training in the comtext of Lifelong Learning

    DEFF Research Database (Denmark)

    Jørgensen, Christian Helms; Lindvig, Katrine

    The aim of this second report is to present the results of an empirical study of the perceptions and views of the key stakeholders (teachers, learners, employers, policy-makers) in relation to hybrid qualifications (vocational and general qualifications). A special attention is given to the new h...

  4. Hybrid Task Design: Connecting Learning Opportunities Related to Critical Thinking and Statistical Thinking

    Science.gov (United States)

    Kuntze, Sebastian; Aizikovitsh-Udi, Einav; Clarke, David

    2017-01-01

    Stimulating thinking related to mathematical content is the focus of many tasks in the mathematics classroom. Beyond such content-related thinking, promoting forms of higher order thinking is among the goals of mathematics instruction as well. So-called hybrid tasks focus on combining both goals: they aim at fostering mathematical thinking and…

  5. A Meta-Relational Approach for the Definition and Management of Hybrid Learning Objects

    Science.gov (United States)

    Navarro, Antonio; Fernandez-Pampillon, Ana Ma.; Fernandez-Chamizo, Carmen; Fernandez-Valmayor, Alfredo

    2013-01-01

    Electronic learning objects (LOs) are commonly conceived of as digital units of information used for teaching and learning. To facilitate their classification for pedagogical planning and retrieval purposes, LOs are complemented with metadata (e.g., the author). These metadata are usually restricted by a set of predetermined tags to which the…

  6. HyDR-MI : A hybrid algorithm to reduce dimensionality in multiple instance learning

    NARCIS (Netherlands)

    Zafra, A.; Pechenizkiy, M.; Ventura, S.

    2013-01-01

    Feature selection techniques have been successfully applied in many applications for making supervised learning more effective and efficient. These techniques have been widely used and studied in traditional supervised learning settings, where each instance is expected to have a label. In multiple

  7. 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.

  8. Making tangible the intangible: Hybridization of the real and the virtual to enhance learning of abstract phenomena

    Directory of Open Access Journals (Sweden)

    Stephanie FLECK

    2016-12-01

    Full Text Available Interactive systems based on Augmented Reality (AR and Tangible User Interfaces (TUI hold great promise for enhancing the learning and understanding of abstract phenomena. In particular, they enable to take advantage of numerical simulation and pedagogical supports, while keeping the learner involved in true physical experimentations. In this paper, we present three examples based on AR and TUI, where the concepts to be learnt are difficult to perceive. The first one, Helios, targets K-12 learners in the field of astronomy. The second one, Hobit is dedicated to experiments in wave optics. Finally, the third one, Teegi, allows one to get to know more about brain activity. These three hybrid interfaces have emerged from a common basis that jointly combines research and development work in the fields of Instructional Design and Human-Computer Interaction, from theoretical to practical aspects. On the basis of investigations carried out in real context of use and on the grounding works in education and HCI which corroborate the design choices that were made, we formalize how and why the hybridization of the real and the virtual enables to leverage the way learners understand intangible phenomena in Sciences education.

  9. 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

  10. A fast hybrid methodology based on machine learning, quantum methods, and experimental measurements for evaluating material properties

    Science.gov (United States)

    Kong, Chang Sun; Haverty, Michael; Simka, Harsono; Shankar, Sadasivan; Rajan, Krishna

    2017-09-01

    We present a hybrid approach based on both machine learning and targeted ab-initio calculations to determine adhesion energies between dissimilar materials. The goals of this approach are to complement experimental and/or all ab-initio computational efforts, to identify promising materials rapidly and identify in a quantitative manner the relative contributions of the different material attributes affecting adhesion. Applications of the methodology to predict bulk modulus, yield strength, adhesion and wetting properties of copper (Cu) with other materials including metals, nitrides and oxides is discussed in this paper. In the machine learning component of this methodology, the parameters that were chosen can be roughly divided into four types: atomic and crystalline parameters (which are related to specific elements such as electronegativities, electron densities in Wigner-Seitz cells); bulk material properties (e.g. melting point), mechanical properties (e.g. modulus) and those representing atomic characteristics in ab-initio formalisms (e.g. pseudopotentials). The atomic parameters are defined over one dataset to determine property correlation with published experimental data. We then develop a semi-empirical model across multiple datasets to predict adhesion in material interfaces outside the original datasets. Since adhesion is between two materials, we appropriately use parameters which indicate differences between the elements that comprise the materials. These semi-empirical predictions agree reasonably with the trend in chemical work of adhesion predicted using ab-initio techniques and are used for fast materials screening. For the screened candidates, the ab-initio modeling component provides fundamental understanding of the chemical interactions at the interface, and explains the wetting thermodynamics of thin Cu layers on various substrates. Comparison against ultra-high vacuum (UHV) experiments for well-characterized Cu/Ta and Cu/α-Al2O3 interfaces is

  11. A hybrid training approach for leaf area index estimation via Cubist and random forests machine-learning

    KAUST Repository

    McCabe, Matthew

    2017-12-06

    With an increasing volume and dimensionality of Earth observation data, enhanced integration of machine-learning methodologies is needed to effectively analyze and utilize these information rich datasets. In machine-learning, a training dataset is required to establish explicit associations between a suite of explanatory ‘predictor’ variables and the target property. The specifics of this learning process can significantly influence model validity and portability, with a higher generalization level expected with an increasing number of observable conditions being reflected in the training dataset. Here we propose a hybrid training approach for leaf area index (LAI) estimation, which harnesses synergistic attributes of scattered in-situ measurements and systematically distributed physically based model inversion results to enhance the information content and spatial representativeness of the training data. To do this, a complimentary training dataset of independent LAI was derived from a regularized model inversion of RapidEye surface reflectances and subsequently used to guide the development of LAI regression models via Cubist and random forests (RF) decision tree methods. The application of the hybrid training approach to a broad set of Landsat 8 vegetation index (VI) predictor variables resulted in significantly improved LAI prediction accuracies and spatial consistencies, relative to results relying on in-situ measurements alone for model training. In comparing the prediction capacity and portability of the two machine-learning algorithms, a pair of relatively simple multi-variate regression models established by Cubist performed best, with an overall relative mean absolute deviation (rMAD) of ∼11%, determined based on a stringent scene-specific cross-validation approach. In comparison, the portability of RF regression models was less effective (i.e., an overall rMAD of ∼15%), which was attributed partly to model saturation at high LAI in association

  12. A hybrid training approach for leaf area index estimation via Cubist and random forests machine-learning

    KAUST Repository

    McCabe, Matthew; McCabe, Matthew

    2017-01-01

    With an increasing volume and dimensionality of Earth observation data, enhanced integration of machine-learning methodologies is needed to effectively analyze and utilize these information rich datasets. In machine-learning, a training dataset is required to establish explicit associations between a suite of explanatory ‘predictor’ variables and the target property. The specifics of this learning process can significantly influence model validity and portability, with a higher generalization level expected with an increasing number of observable conditions being reflected in the training dataset. Here we propose a hybrid training approach for leaf area index (LAI) estimation, which harnesses synergistic attributes of scattered in-situ measurements and systematically distributed physically based model inversion results to enhance the information content and spatial representativeness of the training data. To do this, a complimentary training dataset of independent LAI was derived from a regularized model inversion of RapidEye surface reflectances and subsequently used to guide the development of LAI regression models via Cubist and random forests (RF) decision tree methods. The application of the hybrid training approach to a broad set of Landsat 8 vegetation index (VI) predictor variables resulted in significantly improved LAI prediction accuracies and spatial consistencies, relative to results relying on in-situ measurements alone for model training. In comparing the prediction capacity and portability of the two machine-learning algorithms, a pair of relatively simple multi-variate regression models established by Cubist performed best, with an overall relative mean absolute deviation (rMAD) of ∼11%, determined based on a stringent scene-specific cross-validation approach. In comparison, the portability of RF regression models was less effective (i.e., an overall rMAD of ∼15%), which was attributed partly to model saturation at high LAI in association

  13. A hybrid training approach for leaf area index estimation via Cubist and random forests machine-learning

    Science.gov (United States)

    Houborg, Rasmus; McCabe, Matthew F.

    2018-01-01

    With an increasing volume and dimensionality of Earth observation data, enhanced integration of machine-learning methodologies is needed to effectively analyze and utilize these information rich datasets. In machine-learning, a training dataset is required to establish explicit associations between a suite of explanatory 'predictor' variables and the target property. The specifics of this learning process can significantly influence model validity and portability, with a higher generalization level expected with an increasing number of observable conditions being reflected in the training dataset. Here we propose a hybrid training approach for leaf area index (LAI) estimation, which harnesses synergistic attributes of scattered in-situ measurements and systematically distributed physically based model inversion results to enhance the information content and spatial representativeness of the training data. To do this, a complimentary training dataset of independent LAI was derived from a regularized model inversion of RapidEye surface reflectances and subsequently used to guide the development of LAI regression models via Cubist and random forests (RF) decision tree methods. The application of the hybrid training approach to a broad set of Landsat 8 vegetation index (VI) predictor variables resulted in significantly improved LAI prediction accuracies and spatial consistencies, relative to results relying on in-situ measurements alone for model training. In comparing the prediction capacity and portability of the two machine-learning algorithms, a pair of relatively simple multi-variate regression models established by Cubist performed best, with an overall relative mean absolute deviation (rMAD) of ∼11%, determined based on a stringent scene-specific cross-validation approach. In comparison, the portability of RF regression models was less effective (i.e., an overall rMAD of ∼15%), which was attributed partly to model saturation at high LAI in association with

  14. A Hybrid Short-Term Traffic Flow Prediction Model Based on Singular Spectrum Analysis and Kernel Extreme Learning Machine.

    Directory of Open Access Journals (Sweden)

    Qiang Shang

    Full Text Available Short-term traffic flow prediction is one of the most important issues in the field of intelligent transport system (ITS. Because of the uncertainty and nonlinearity, short-term traffic flow prediction is a challenging task. In order to improve the accuracy of short-time traffic flow prediction, a hybrid model (SSA-KELM is proposed based on singular spectrum analysis (SSA and kernel extreme learning machine (KELM. SSA is used to filter out the noise of traffic flow time series. Then, the filtered traffic flow data is used to train KELM model, the optimal input form of the proposed model is determined by phase space reconstruction, and parameters of the model are optimized by gravitational search algorithm (GSA. Finally, case validation is carried out using the measured data of an expressway in Xiamen, China. And the SSA-KELM model is compared with several well-known prediction models, including support vector machine, extreme learning machine, and single KLEM model. The experimental results demonstrate that performance of the proposed model is superior to that of the comparison models. Apart from accuracy improvement, the proposed model is more robust.

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

    Directory of Open Access Journals (Sweden)

    Muhammad Sohaib

    2017-12-01

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

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

    Science.gov (United States)

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

    2017-12-11

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

  17. Can Personalized Nudges Improve Learning in Hybrid Classes? Experimental Evidence from an Introductory Undergraduate Course

    Science.gov (United States)

    O'Connell, Stephen D.; Lang, Guido

    2018-01-01

    A field experiment was conducted to investigate whether personalized e-mail reminders can improve study consistency and learning outcomes in an introductory-level undergraduate course. By randomly assigning whether nearly 300 students would receive occasional e-mail messages encouraging out-of-class study, we find that these reminders increased…

  18. Untethering Education: Creating a Pilot Hybrid Class to Enhance Learning in Intercultural Communication

    Science.gov (United States)

    Lawton, Bessie; Foeman, Anita; Thompsen, Philip

    2014-01-01

    Improvements in educational technology in the past couple of decades have led institutions of higher learning to encourage and implement various types of distance education courses. This article reports on the conversion process of a face-to-face Intercultural Communication class at a mid-Atlantic university in the USA. First, the impetus for its…

  19. Visual Hybrid Development Learning System (VHDLS) Framework for Children with Autism

    Science.gov (United States)

    Banire, Bilikis; Jomhari, Nazean; Ahmad, Rodina

    2015-01-01

    The effect of education on children with autism serves as a relative cure for their deficits. As a result of this, they require special techniques to gain their attention and interest in learning as compared to typical children. Several studies have shown that these children are visual learners. In this study, we proposed a Visual Hybrid…

  20. Boundedly rational learning and heterogeneous trading strategies with hybrid neuro-fuzzy models

    NARCIS (Netherlands)

    Bekiros, S.D.

    2009-01-01

    The present study deals with heterogeneous learning rules in speculative markets where heuristic strategies reflect the rules-of-thumb of boundedly rational investors. The major challenge for "chartists" is the development of new models that would enhance forecasting ability particularly for time

  1. "From Bricks to Clicks": Hybrid Commercial Spaces in the Landscape of Early Literacy and Learning

    Science.gov (United States)

    Nixon, Helen

    2011-01-01

    In their quest for resources to support children's early literacy learning and development, parents encounter and traverse different spaces in which discourses and artifacts are produced and circulated. This paper uses conceptual tools from the field of geosemiotics to examine some commercial spaces designed for parents and children that…

  2. Using Multimedia Learning Modules in a Hybrid-Online Course in Electricity and Magnetism

    Science.gov (United States)

    Sadaghiani, Homeyra R.

    2011-01-01

    We have been piloting web-based multimedia learning modules (MLMs), developed by the Physics Education Research Group at the University of Illinois at Urbana Champaign (UIUC), as a "prelecture assignment" in several introductory physics courses at California State Polytechnic University at Pomona. In this study, we report the results…

  3. Self-learning control system for plug-in hybrid vehicles

    Science.gov (United States)

    DeVault, Robert C [Knoxville, TN

    2010-12-14

    A system is provided to instruct a plug-in hybrid electric vehicle how optimally to use electric propulsion from a rechargeable energy storage device to reach an electric recharging station, while maintaining as high a state of charge (SOC) as desired along the route prior to arriving at the recharging station at a minimum SOC. The system can include the step of calculating a straight-line distance and/or actual distance between an orientation point and the determined instant present location to determine when to initiate optimally a charge depleting phase. The system can limit extended driving on a deeply discharged rechargeable energy storage device and reduce the number of deep discharge cycles for the rechargeable energy storage device, thereby improving the effective lifetime of the rechargeable energy storage device. This "Just-in-Time strategy can be initiated automatically without operator input to accommodate the unsophisticated operator and without needing a navigation system/GPS input.

  4. Analysis of Rules for Islamic Inheritance Law in Indonesia Using Hybrid Rule Based Learning

    Science.gov (United States)

    Khosyi'ah, S.; Irfan, M.; Maylawati, D. S.; Mukhlas, O. S.

    2018-01-01

    Along with the development of human civilization in Indonesia, the changes and reform of Islamic inheritance law so as to conform to the conditions and culture cannot be denied. The distribution of inheritance in Indonesia can be done automatically by storing the rule of Islamic inheritance law in the expert system. In this study, we analyze the knowledge of experts in Islamic inheritance in Indonesia and represent it in the form of rules using rule-based Forward Chaining (FC) and Davis-Putman-Logemann-Loveland (DPLL) algorithms. By hybridizing FC and DPLL algorithms, the rules of Islamic inheritance law in Indonesia are clearly defined and measured. The rules were conceptually validated by some experts in Islamic laws and informatics. The results revealed that generally all rules were ready for use in an expert system.

  5. Structural acoustic response of a shape memory alloy hybrid composite panel (lessons learned)

    Science.gov (United States)

    Turner, Travis L.

    2002-07-01

    This study presents results from an effort to fabricate a shape memory alloy hybrid composite (SMAHC) panel specimen and test the structure for dynamic response and noise transmission characteristics under the action of thermal and random acoustic loads. A method for fabricating a SMAHC laminate with bi-directional SMA reinforcement is described. Glass-epoxy unidirectional prepreg tape and Nitinol ribbon comprise the material system. Thermal activation of the Nitinol actuators was achieved through resistive heating. The experimental hardware required for mechanical support of the panel/actuators and for establishing convenient electrical connectivity to the actuators is presented. Other experimental apparatus necessary for controlling the panel temperature and acquiring structural acoustic data are also described. Deficiency in the thermal control system was discovered in the process of performing the elevated temperature tests. Discussion of the experimental results focuses on determining the causes for the deficiency and establishing means for rectifying the problem.

  6. A hybrid machine learning model to estimate nitrate contamination of production zone groundwater in the Central Valley, California

    Science.gov (United States)

    Ransom, K.; Nolan, B. T.; Faunt, C. C.; Bell, A.; Gronberg, J.; Traum, J.; Wheeler, D. C.; Rosecrans, C.; Belitz, K.; Eberts, S.; Harter, T.

    2016-12-01

    A hybrid, non-linear, machine learning statistical model was developed within a statistical learning framework to predict nitrate contamination of groundwater to depths of approximately 500 m below ground surface in the Central Valley, California. A database of 213 predictor variables representing well characteristics, historical and current field and county scale nitrogen mass balance, historical and current landuse, oxidation/reduction conditions, groundwater flow, climate, soil characteristics, depth to groundwater, and groundwater age were assigned to over 6,000 private supply and public supply wells measured previously for nitrate and located throughout the study area. The machine learning method, gradient boosting machine (GBM) was used to screen predictor variables and rank them in order of importance in relation to the groundwater nitrate measurements. The top five most important predictor variables included oxidation/reduction characteristics, historical field scale nitrogen mass balance, climate, and depth to 60 year old water. Twenty-two variables were selected for the final model and final model errors for log-transformed hold-out data were R squared of 0.45 and root mean square error (RMSE) of 1.124. Modeled mean groundwater age was tested separately for error improvement in the model and when included decreased model RMSE by 0.5% compared to the same model without age and by 0.20% compared to the model with all 213 variables. 1D and 2D partial plots were examined to determine how variables behave individually and interact in the model. Some variables behaved as expected: log nitrate decreased with increasing probability of anoxic conditions and depth to 60 year old water, generally decreased with increasing natural landuse surrounding wells and increasing mean groundwater age, generally increased with increased minimum depth to high water table and with increased base flow index value. Other variables exhibited much more erratic or noisy behavior in

  7. LANGUAGE LEARNING UNDER CLASSROOM CONDITIONS DURING THE TRANSITION TO HYBRID INSTRUCTION: A CASE-STUDY OF STUDENT PERFORMANCE DURING THE IMPLEMENTATION OF INSTRUCTIONAL TECHNOLOGY

    OpenAIRE

    Lisbeth O. Swain; Timothy D. Swain

    2017-01-01

    We examined the unmanipulated performance of students under real classroom conditions in order to assess the effect of a technology-enhanced hybrid learning approach to second language, (L2) instruction on beginning and advanced Spanish language learners. This research focused on the transition period of technology implementation when the entire section of Spanish of a modern language department of a liberal arts university transitioned from traditional face-to-face instruction, to a technolo...

  8. Soutenir le cheminement de stage d’apprentis enseignants au secondaire par un environnement d’apprentissage hybride / Supporting the advancement of student-teachers in their practica with the use of a hybrid learning environment

    Directory of Open Access Journals (Sweden)

    Stéphane Allaire

    2009-03-01

    Full Text Available Résumé : Dans un contexte de pratiques éducatives en renouvellement, la recherche participative étudie l’apport d’un environnement d’apprentissage hybride pour l’analyse réflexive de stagiaires en enseignement secondaire. Des analyses qualitatives et quantitatives descriptives illustrent le potentiel des dispositifs mis en place pour soutenir l’intégration à un contexte de stage innovateur, une réflexivité diversifiée et la coélaboration de connaissances. Abstract : In the context of evolving educational practices, participatory research is used to study the contribution of a hybrid learning environment when used by student teachers in secondary teaching for reflective analysis. Both quantitative analysis and qualitative descriptives illustrate the potential of the devices and strategies used to support the student teachers in their integration into an innovative practicum context, a diversified reflective practice and knowledge building.

  9. A Hybrid Computer-aided-diagnosis System for Prediction of Breast Cancer Recurrence (HPBCR Using Optimized Ensemble Learning

    Directory of Open Access Journals (Sweden)

    Mohammad R. Mohebian

    Full Text Available Cancer is a collection of diseases that involves growing abnormal cells with the potential to invade or spread to the body. Breast cancer is the second leading cause of cancer death among women. A method for 5-year breast cancer recurrence prediction is presented in this manuscript. Clinicopathologic characteristics of 579 breast cancer patients (recurrence prevalence of 19.3% were analyzed and discriminative features were selected using statistical feature selection methods. They were further refined by Particle Swarm Optimization (PSO as the inputs of the classification system with ensemble learning (Bagged Decision Tree: BDT. The proper combination of selected categorical features and also the weight (importance of the selected interval-measurement-scale features were identified by the PSO algorithm. The performance of HPBCR (hybrid predictor of breast cancer recurrence was assessed using the holdout and 4-fold cross-validation. Three other classifiers namely as supported vector machines, DT, and multilayer perceptron neural network were used for comparison. The selected features were diagnosis age, tumor size, lymph node involvement ratio, number of involved axillary lymph nodes, progesterone receptor expression, having hormone therapy and type of surgery. The minimum sensitivity, specificity, precision and accuracy of HPBCR were 77%, 93%, 95% and 85%, respectively in the entire cross-validation folds and the hold-out test fold. HPBCR outperformed the other tested classifiers. It showed excellent agreement with the gold standard (i.e. the oncologist opinion after blood tumor marker and imaging tests, and tissue biopsy. This algorithm is thus a promising online tool for the prediction of breast cancer recurrence. Keywords: Breast cancer, Cancer recurrence, Computer-assisted diagnosis, Machine learning, Prognosis

  10. A hybrid machine learning model to predict and visualize nitrate concentration throughout the Central Valley aquifer, California, USA

    Science.gov (United States)

    Ransom, Katherine M.; Nolan, Bernard T.; Traum, Jonathan A.; Faunt, Claudia; Bell, Andrew M.; Gronberg, Jo Ann M.; Wheeler, David C.; Zamora, Celia; Jurgens, Bryant; Schwarz, Gregory E.; Belitz, Kenneth; Eberts, Sandra; Kourakos, George; Harter, Thomas

    2017-01-01

    Intense demand for water in the Central Valley of California and related increases in groundwater nitrate concentration threaten the sustainability of the groundwater resource. To assess contamination risk in the region, we developed a hybrid, non-linear, machine learning model within a statistical learning framework to predict nitrate contamination of groundwater to depths of approximately 500 m below ground surface. A database of 145 predictor variables representing well characteristics, historical and current field and landscape-scale nitrogen mass balances, historical and current land use, oxidation/reduction conditions, groundwater flow, climate, soil characteristics, depth to groundwater, and groundwater age were assigned to over 6000 private supply and public supply wells measured previously for nitrate and located throughout the study area. The boosted regression tree (BRT) method was used to screen and rank variables to predict nitrate concentration at the depths of domestic and public well supplies. The novel approach included as predictor variables outputs from existing physically based models of the Central Valley. The top five most important predictor variables included two oxidation/reduction variables (probability of manganese concentration to exceed 50 ppb and probability of dissolved oxygen concentration to be below 0.5 ppm), field-scale adjusted unsaturated zone nitrogen input for the 1975 time period, average difference between precipitation and evapotranspiration during the years 1971–2000, and 1992 total landscape nitrogen input. Twenty-five variables were selected for the final model for log-transformed nitrate. In general, increasing probability of anoxic conditions and increasing precipitation relative to potential evapotranspiration had a corresponding decrease in nitrate concentration predictions. Conversely, increasing 1975 unsaturated zone nitrogen leaching flux and 1992 total landscape nitrogen input had an increasing relative

  11. A hybrid stock trading framework integrating technical analysis with machine learning techniques

    Directory of Open Access Journals (Sweden)

    Rajashree Dash

    2016-03-01

    Full Text Available In this paper, a novel decision support system using a computational efficient functional link artificial neural network (CEFLANN and a set of rules is proposed to generate the trading decisions more effectively. Here the problem of stock trading decision prediction is articulated as a classification problem with three class values representing the buy, hold and sell signals. The CEFLANN network used in the decision support system produces a set of continuous trading signals within the range 0–1 by analyzing the nonlinear relationship exists between few popular technical indicators. Further the output trading signals are used to track the trend and to produce the trading decision based on that trend using some trading rules. The novelty of the approach is to engender the profitable stock trading decision points through integration of the learning ability of CEFLANN neural network with the technical analysis rules. For assessing the potential use of the proposed method, the model performance is also compared with some other machine learning techniques such as Support Vector Machine (SVM, Naive Bayesian model, K nearest neighbor model (KNN and Decision Tree (DT model.

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

    Science.gov (United States)

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

    2018-02-01

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

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

    Directory of Open Access Journals (Sweden)

    Honghui Yang

    2010-10-01

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

  14. RNA-protein binding motifs mining with a new hybrid deep learning based cross-domain knowledge integration approach.

    Science.gov (United States)

    Pan, Xiaoyong; Shen, Hong-Bin

    2017-02-28

    RNAs play key roles in cells through the interactions with proteins known as the RNA-binding proteins (RBP) and their binding motifs enable crucial understanding of the post-transcriptional regulation of RNAs. How the RBPs correctly recognize the target RNAs and why they bind specific positions is still far from clear. Machine learning-based algorithms are widely acknowledged to be capable of speeding up this process. Although many automatic tools have been developed to predict the RNA-protein binding sites from the rapidly growing multi-resource data, e.g. sequence, structure, their domain specific features and formats have posed significant computational challenges. One of current difficulties is that the cross-source shared common knowledge is at a higher abstraction level beyond the observed data, resulting in a low efficiency of direct integration of observed data across domains. The other difficulty is how to interpret the prediction results. Existing approaches tend to terminate after outputting the potential discrete binding sites on the sequences, but how to assemble them into the meaningful binding motifs is a topic worth of further investigation. In viewing of these challenges, we propose a deep learning-based framework (iDeep) by using a novel hybrid convolutional neural network and deep belief network to predict the RBP interaction sites and motifs on RNAs. This new protocol is featured by transforming the original observed data into a high-level abstraction feature space using multiple layers of learning blocks, where the shared representations across different domains are integrated. To validate our iDeep method, we performed experiments on 31 large-scale CLIP-seq datasets, and our results show that by integrating multiple sources of data, the average AUC can be improved by 8% compared to the best single-source-based predictor; and through cross-domain knowledge integration at an abstraction level, it outperforms the state-of-the-art predictors by 6

  15. Formula hybrid SAE.

    Science.gov (United States)

    2013-09-01

    User-friendly tools are needed for undergraduates to learn about component sizing, powertrain integration, and control : strategies for student competitions involving hybrid vehicles. A TK Solver tool was developed at the University of Idaho for : th...

  16. Hybrid Spintronic-CMOS Spiking Neural Network with On-Chip Learning: Devices, Circuits, and Systems

    Science.gov (United States)

    Sengupta, Abhronil; Banerjee, Aparajita; Roy, Kaushik

    2016-12-01

    Over the past decade, spiking neural networks (SNNs) have emerged as one of the popular architectures to emulate the brain. In SNNs, information is temporally encoded and communication between neurons is accomplished by means of spikes. In such networks, spike-timing-dependent plasticity mechanisms require the online programing of synapses based on the temporal information of spikes transmitted by spiking neurons. In this work, we propose a spintronic synapse with decoupled spike-transmission and programing-current paths. The spintronic synapse consists of a ferromagnet-heavy-metal heterostructure where the programing current through the heavy metal generates spin-orbit torque to modulate the device conductance. Low programing energy and fast programing times demonstrate the efficacy of the proposed device as a nanoelectronic synapse. We perform a simulation study based on an experimentally benchmarked device-simulation framework to demonstrate the interfacing of such spintronic synapses with CMOS neurons and learning circuits operating in the transistor subthreshold region to form a network of spiking neurons that can be utilized for pattern-recognition problems.

  17. A Novel Hybrid Model Based on Extreme Learning Machine, k-Nearest Neighbor Regression and Wavelet Denoising Applied to Short-Term Electric Load Forecasting

    Directory of Open Access Journals (Sweden)

    Weide Li

    2017-05-01

    Full Text Available Electric load forecasting plays an important role in electricity markets and power systems. Because electric load time series are complicated and nonlinear, it is very difficult to achieve a satisfactory forecasting accuracy. In this paper, a hybrid model, Wavelet Denoising-Extreme Learning Machine optimized by k-Nearest Neighbor Regression (EWKM, which combines k-Nearest Neighbor (KNN and Extreme Learning Machine (ELM based on a wavelet denoising technique is proposed for short-term load forecasting. The proposed hybrid model decomposes the time series into a low frequency-associated main signal and some detailed signals associated with high frequencies at first, then uses KNN to determine the independent and dependent variables from the low-frequency signal. Finally, the ELM is used to get the non-linear relationship between these variables to get the final prediction result for the electric load. Compared with three other models, Extreme Learning Machine optimized by k-Nearest Neighbor Regression (EKM, Wavelet Denoising-Extreme Learning Machine (WKM and Wavelet Denoising-Back Propagation Neural Network optimized by k-Nearest Neighbor Regression (WNNM, the model proposed in this paper can improve the accuracy efficiently. New South Wales is the economic powerhouse of Australia, so we use the proposed model to predict electric demand for that region. The accurate prediction has a significant meaning.

  18. A Hybrid Computer-aided-diagnosis System for Prediction of Breast Cancer Recurrence (HPBCR) Using Optimized Ensemble Learning.

    Science.gov (United States)

    Mohebian, Mohammad R; Marateb, Hamid R; Mansourian, Marjan; Mañanas, Miguel Angel; Mokarian, Fariborz

    2017-01-01

    Cancer is a collection of diseases that involves growing abnormal cells with the potential to invade or spread to the body. Breast cancer is the second leading cause of cancer death among women. A method for 5-year breast cancer recurrence prediction is presented in this manuscript. Clinicopathologic characteristics of 579 breast cancer patients (recurrence prevalence of 19.3%) were analyzed and discriminative features were selected using statistical feature selection methods. They were further refined by Particle Swarm Optimization (PSO) as the inputs of the classification system with ensemble learning (Bagged Decision Tree: BDT). The proper combination of selected categorical features and also the weight (importance) of the selected interval-measurement-scale features were identified by the PSO algorithm. The performance of HPBCR (hybrid predictor of breast cancer recurrence) was assessed using the holdout and 4-fold cross-validation. Three other classifiers namely as supported vector machines, DT, and multilayer perceptron neural network were used for comparison. The selected features were diagnosis age, tumor size, lymph node involvement ratio, number of involved axillary lymph nodes, progesterone receptor expression, having hormone therapy and type of surgery. The minimum sensitivity, specificity, precision and accuracy of HPBCR were 77%, 93%, 95% and 85%, respectively in the entire cross-validation folds and the hold-out test fold. HPBCR outperformed the other tested classifiers. It showed excellent agreement with the gold standard (i.e. the oncologist opinion after blood tumor marker and imaging tests, and tissue biopsy). This algorithm is thus a promising online tool for the prediction of breast cancer recurrence.

  19. The Hybrid Advantage: Graduate Student Perspectives of Hybrid Education Courses

    Science.gov (United States)

    Hall, Sarah; Villareal, Donna

    2015-01-01

    Hybrid courses combine online and face-to-face learning environments. To organize and teach hybrid courses, instructors must understand the uses of multiple online learning tools and face-toface classroom activities to promote and monitor the progress of students. The purpose of this phenomenological study was to explore the perspectives of…

  20. A Hybrid Model through the Fusion of Type-2 Fuzzy Logic Systems and Sensitivity-Based Linear Learning Method for Modeling PVT Properties of Crude Oil Systems

    Directory of Open Access Journals (Sweden)

    Ali Selamat

    2012-01-01

    Full Text Available Sensitivity-based linear learning method (SBLLM has recently been used as a predictive tool due to its unique characteristics and performance, particularly its high stability and consistency during predictions. However, the generalisation capability of SBLLM is sometimes limited depending on the nature of the dataset, particularly on whether uncertainty is present in the dataset or not. Since it made use of sensitivity analysis in relation to the data sets used, it is surely very prone to being affected by the nature of the dataset. In order to reduce the effects of uncertainties in SBLLM prediction and improve its generalisation ability, this paper proposes a hybrid system through the unique combination of type-2 fuzzy logic systems (type-2 FLSs and SBLLM; thereafter the hybrid system was used to model PVT properties of crude oil systems. Type-2 FLS has been choosen in order to better handle uncertainties existing in datasets beyond the capability of type-1 fuzzy logic systems. In the proposed hybrid, the type-2 FLS is used to handle uncertainties in reservoir data so that the cleaned data from type-2 FLS is then passed to the SBLLM for training and then final prediction using testing dataset follows. Comparative studies have been carried out to compare the performance of the newly proposed T2-SBLLM hybrid system with each of the constituent type-2 FLS and SBLLM. Empirical results from simulation show that the proposed T2-SBLLM hybrid system has greatly improved upon the performance of SBLLM, while also maintaining a better performance above that of the type-2 FLS.

  1. Designing and Developing a Novel Hybrid Adaptive Learning Path Recommendation System (ALPRS) for Gamification Mathematics Geometry Course

    Science.gov (United States)

    Su, Chung-Ho

    2017-01-01

    Since recommendation systems possess the advantage of adaptive recommendation, they have gradually been applied to e-learning systems to recommend subsequent learning content for learners. However, problems exist in current learning recommender systems available to students in that they are often general learning content and unable to offer…

  2. Analysis and Modeling for China’s Electricity Demand Forecasting Using a Hybrid Method Based on Multiple Regression and Extreme Learning Machine: A View from Carbon Emission

    Directory of Open Access Journals (Sweden)

    Yi Liang

    2016-11-01

    Full Text Available The power industry is the main battlefield of CO2 emission reduction, which plays an important role in the implementation and development of the low carbon economy. The forecasting of electricity demand can provide a scientific basis for the country to formulate a power industry development strategy and further promote the sustained, healthy and rapid development of the national economy. Under the goal of low-carbon economy, medium and long term electricity demand forecasting will have very important practical significance. In this paper, a new hybrid electricity demand model framework is characterized as follows: firstly, integration of grey relation degree (GRD with induced ordered weighted harmonic averaging operator (IOWHA to propose a new weight determination method of hybrid forecasting model on basis of forecasting accuracy as induced variables is presented; secondly, utilization of the proposed weight determination method to construct the optimal hybrid forecasting model based on extreme learning machine (ELM forecasting model and multiple regression (MR model; thirdly, three scenarios in line with the level of realization of various carbon emission targets and dynamic simulation of effect of low-carbon economy on future electricity demand are discussed. The resulting findings show that, the proposed model outperformed and concentrated some monomial forecasting models, especially in boosting the overall instability dramatically. In addition, the development of a low-carbon economy will increase the demand for electricity, and have an impact on the adjustment of the electricity demand structure.

  3. Students’ perceptions and satisfaction level of hybrid problem-based learning for 16 years in Kyungpook National University School of Medicine, Korea

    Directory of Open Access Journals (Sweden)

    Sanghee Yeo

    2016-03-01

    Full Text Available Purpose: Kyungpook National University School of Medicine has been implementing hybrid problem-based learning (PBL since 1999. The aim of this study was to investigate the changes in the students’ perceptions and satisfaction levels of hybrid PBL. Methods: The target period of our study was from 1999 to 2014, and target subjects were second-year medical students in Kyungpook National University School of Medicine. The survey was conducted at the end of semester. We had a focused interview with group leaders and some volunteer students. Results: As for the scores regarding students’ overall satisfaction with PBL, there was significant improvement in 2005 compared to 2002, but the scores decreased and no differences between the survey years noted after 2005. The students’ preference ratio for the once a week PBL sessions, tutor presence, synchronization of contents, and arrangement of PBL sessions and related lectures was 60%–80%, 50%–90%, 52%–96%, and 78%–93%, respectively. Conclusion: In order to increase students’ satisfaction with hybrid PBL and to improve the perception of it, firstly, it is necessary to arrange the date and the time of PBL sessions so that students can concentrate on PBL. Secondly, PBL cases should be selected and arranged to be well synchronized with the ongoing lectures. Finally, it is important to create a safe atmosphere so that students can engage actively in PBL sessions.

  4. Modular Rapid E-Learning Framework (MORELF) in Desktop Virtualization Environment: An Effective Hybrid Implementation in Nurse Education

    Science.gov (United States)

    Parlakkilic, Alattin

    2015-01-01

    Generally it is not easy for an instructor to prepare and deliver electronic courses via e-learning. Therefore it is necessary to work and develop an easy system. In this context module technology was used to for provide modularity in conducting educational development of e-learning course. Then, rapid e-learning was used for more quick and easy…

  5. Hybrid Pareto artificial bee colony algorithm for multi-objective single machine group scheduling problem with sequence-dependent setup times and learning effects.

    Science.gov (United States)

    Yue, Lei; Guan, Zailin; Saif, Ullah; Zhang, Fei; Wang, Hao

    2016-01-01

    Group scheduling is significant for efficient and cost effective production system. However, there exist setup times between the groups, which require to decrease it by sequencing groups in an efficient way. Current research is focused on a sequence dependent group scheduling problem with an aim to minimize the makespan in addition to minimize the total weighted tardiness simultaneously. In most of the production scheduling problems, the processing time of jobs is assumed as fixed. However, the actual processing time of jobs may be reduced due to "learning effect". The integration of sequence dependent group scheduling problem with learning effects has been rarely considered in literature. Therefore, current research considers a single machine group scheduling problem with sequence dependent setup times and learning effects simultaneously. A novel hybrid Pareto artificial bee colony algorithm (HPABC) with some steps of genetic algorithm is proposed for current problem to get Pareto solutions. Furthermore, five different sizes of test problems (small, small medium, medium, large medium, large) are tested using proposed HPABC. Taguchi method is used to tune the effective parameters of the proposed HPABC for each problem category. The performance of HPABC is compared with three famous multi objective optimization algorithms, improved strength Pareto evolutionary algorithm (SPEA2), non-dominated sorting genetic algorithm II (NSGAII) and particle swarm optimization algorithm (PSO). Results indicate that HPABC outperforms SPEA2, NSGAII and PSO and gives better Pareto optimal solutions in terms of diversity and quality for almost all the instances of the different sizes of problems.

  6. The shortcomings of semi-local and hybrid functionals: what we can learn from surface science studies

    International Nuclear Information System (INIS)

    Stroppa, A; Kresse, G

    2008-01-01

    A study of the adsorption of CO on late 4d and 5d transition metal (111) surfaces (Ru, Rh, Pd, Ag, Os, Ir and Pt) considering atop and hollow site adsorption is presented. The applied functionals include the gradient-corrected Perdew-Burke-Ernzerhof (PBE) and Becke-Lee-Yang-Parr (BLYP) functionals, and the corresponding hybrid Hartree-Fock density functionals HSE and B3LYP. We find that PBE-based hybrid functionals (specifically HSE) yield, with the exception of Pt, the correct site order on all considered metals, but they also considerably overestimate the adsorption energies compared to experiment. On the other hand, the semi-local BLYP functional and the corresponding hybrid functional B3LYP yield very satisfactory adsorption energies and the correct adsorption site for all surfaces. We are thus faced with a Procrustean problem: the B3LYP and BLYP functionals seem to be the overall best choice for describing adsorption on metal surfaces, but they simultaneously fail to account well for the properties of the metal, vastly overestimating the equilibrium volume and underestimating the atomization energies. Setting out from these observations, general conclusions are drawn on the relative merits and drawbacks of various semi-local and hybrid functionals. The discussion includes a revised version of the PBE functional specifically optimized for bulk properties and surface energies (PBEsol), a revised version of the PBE functional specifically optimized to predict accurate adsorption energies (rPBE), as well as the aforementioned BLYP functional. We conclude that no semi-local functional is capable of describing all aspects properly, and including non-local exchange also only improves some but worsens other properties

  7. A novel hybrid model for air quality index forecasting based on two-phase decomposition technique and modified extreme learning machine.

    Science.gov (United States)

    Wang, Deyun; Wei, Shuai; Luo, Hongyuan; Yue, Chenqiang; Grunder, Olivier

    2017-02-15

    The randomness, non-stationarity and irregularity of air quality index (AQI) series bring the difficulty of AQI forecasting. To enhance forecast accuracy, a novel hybrid forecasting model combining two-phase decomposition technique and extreme learning machine (ELM) optimized by differential evolution (DE) algorithm is developed for AQI forecasting in this paper. In phase I, the complementary ensemble empirical mode decomposition (CEEMD) is utilized to decompose the AQI series into a set of intrinsic mode functions (IMFs) with different frequencies; in phase II, in order to further handle the high frequency IMFs which will increase the forecast difficulty, variational mode decomposition (VMD) is employed to decompose the high frequency IMFs into a number of variational modes (VMs). Then, the ELM model optimized by DE algorithm is applied to forecast all the IMFs and VMs. Finally, the forecast value of each high frequency IMF is obtained through adding up the forecast results of all corresponding VMs, and the forecast series of AQI is obtained by aggregating the forecast results of all IMFs. To verify and validate the proposed model, two daily AQI series from July 1, 2014 to June 30, 2016 collected from Beijing and Shanghai located in China are taken as the test cases to conduct the empirical study. The experimental results show that the proposed hybrid model based on two-phase decomposition technique is remarkably superior to all other considered models for its higher forecast accuracy. Copyright © 2016 Elsevier B.V. All rights reserved.

  8. Teaching with technology: learning outcomes for a combined dental and dental hygiene online hybrid oral histology course.

    Science.gov (United States)

    Gadbury-Amyot, Cynthia C; Singh, Amul H; Overman, Pamela R

    2013-06-01

    Among the challenges leaders in dental and allied dental education have faced in recent years is a shortage of well-qualified faculty members, especially in some specialty areas of dentistry. One proposed solution has been the use of technology. At the University of Missouri-Kansas City School of Dentistry, the departure of a faculty member who taught the highly specialized content in oral histology and embryology provided the opportunity to implement distance delivery of that course. The course is taught once a year to a combined group of dental and dental hygiene students. Previous to spring semester of 2009, the course was taught using traditional face-to-face, in-class lectures and multiple-choice examinations. During the spring semesters of 2009, 2010, and 2011, the course was taught using synchronous and asynchronous distance delivery technology. Outcomes for these courses (including course grades and performance on the National Board Dental Examination Part I) were compared to those from the 2006, 2007, and 2008 courses. Students participating in the online hybrid course were also given an author-designed survey, and the perceptions of the faculty member who made the transition from teaching the course in a traditional face-to-face format to teaching in an online hybrid format were solicited. Overall, student and faculty perceptions and student outcomes and course reviews have been positive. The results of this study can provide guidance to those seeking to use technology as one method of curricular delivery.

  9. A robust hybrid model integrating enhanced inputs based extreme learning machine with PLSR (PLSR-EIELM) and its application to intelligent measurement.

    Science.gov (United States)

    He, Yan-Lin; Geng, Zhi-Qiang; Xu, Yuan; Zhu, Qun-Xiong

    2015-09-01

    In this paper, a robust hybrid model integrating an enhanced inputs based extreme learning machine with the partial least square regression (PLSR-EIELM) was proposed. The proposed PLSR-EIELM model can overcome two main flaws in the extreme learning machine (ELM), i.e. the intractable problem in determining the optimal number of the hidden layer neurons and the over-fitting phenomenon. First, a traditional extreme learning machine (ELM) is selected. Second, a method of randomly assigning is applied to the weights between the input layer and the hidden layer, and then the nonlinear transformation for independent variables can be obtained from the output of the hidden layer neurons. Especially, the original input variables are regarded as enhanced inputs; then the enhanced inputs and the nonlinear transformed variables are tied together as the whole independent variables. In this way, the PLSR can be carried out to identify the PLS components not only from the nonlinear transformed variables but also from the original input variables, which can remove the correlation among the whole independent variables and the expected outputs. Finally, the optimal relationship model of the whole independent variables with the expected outputs can be achieved by using PLSR. Thus, the PLSR-EIELM model is developed. Then the PLSR-EIELM model served as an intelligent measurement tool for the key variables of the Purified Terephthalic Acid (PTA) process and the High Density Polyethylene (HDPE) process. The experimental results show that the predictive accuracy of PLSR-EIELM is stable, which indicate that PLSR-EIELM has good robust character. Moreover, compared with ELM, PLSR, hierarchical ELM (HELM), and PLSR-ELM, PLSR-EIELM can achieve much smaller predicted relative errors in these two applications. Copyright © 2015 ISA. Published by Elsevier Ltd. All rights reserved.

  10. Learning Concepts, Language, and Literacy in Hybrid Linguistic Codes: The Multilingual Maze of Urban Grade 1 Classrooms in South Africa

    Science.gov (United States)

    Henning, Elizabeth

    2012-01-01

    From the field of developmental psycholinguistics and from conceptual development theory there is evidence that excessive linguistic "code-switching" in early school education may pose some hazards for the learning of young multilingual children. In this article the author addresses the issue, invoking post-Piagetian and neo-Vygotskian…

  11. A Hybrid Approach to Develop an Analytical Model for Enhancing the Service Quality of E-Learning

    Science.gov (United States)

    Wu, Hung-Yi; Lin, Hsin-Yu

    2012-01-01

    The digital content industry is flourishing as a result of the rapid development of technology and the widespread use of computer networks. As has been reported, the market size of the global e-learning (i.e., distance education and telelearning) will reach USD 49.6 billion in 2014. However, to retain and/or increase the market share associated…

  12. Thinking outside the Box Office: Using Movies to Build Shared Experiences and Student Engagement in Online or Hybrid Learning

    Science.gov (United States)

    Kresse, William; Watland, Kathleen Hanold

    2016-01-01

    Movies and films are widely recognized as valuable pedagogical tools. Motion pictures provide concrete and illustrative examples of important concepts and can improve students' understanding of course material as well as increase their satisfaction with courses. Online learning is becoming an increasing dominant facet of higher education. Online…

  13. Didactical suggestion for a Dynamic Hybrid Intelligent e-Learning Environment (DHILE) applying the PENTHA ID Model

    Science.gov (United States)

    dall'Acqua, Luisa

    2011-08-01

    The teleology of our research is to propose a solution to the request of "innovative, creative teaching", proposing a methodology to educate creative Students in a society characterized by multiple reference points and hyper dynamic knowledge, continuously subject to reviews and discussions. We apply a multi-prospective Instructional Design Model (PENTHA ID Model), defined and developed by our research group, which adopts a hybrid pedagogical approach, consisting of elements of didactical connectivism intertwined with aspects of social constructivism and enactivism. The contribution proposes an e-course structure and approach, applying the theoretical design principles of the above mentioned ID Model, describing methods, techniques, technologies and assessment criteria for the definition of lesson modes in an e-course.

  14. TEMPTING system: a hybrid method of rule and machine learning for temporal relation extraction in patient discharge summaries.

    Science.gov (United States)

    Chang, Yung-Chun; Dai, Hong-Jie; Wu, Johnny Chi-Yang; Chen, Jian-Ming; Tsai, Richard Tzong-Han; Hsu, Wen-Lian

    2013-12-01

    Patient discharge summaries provide detailed medical information about individuals who have been hospitalized. To make a precise and legitimate assessment of the abundant data, a proper time layout of the sequence of relevant events should be compiled and used to drive a patient-specific timeline, which could further assist medical personnel in making clinical decisions. The process of identifying the chronological order of entities is called temporal relation extraction. In this paper, we propose a hybrid method to identify appropriate temporal links between a pair of entities. The method combines two approaches: one is rule-based and the other is based on the maximum entropy model. We develop an integration algorithm to fuse the results of the two approaches. All rules and the integration algorithm are formally stated so that one can easily reproduce the system and results. To optimize the system's configuration, we used the 2012 i2b2 challenge TLINK track dataset and applied threefold cross validation to the training set. Then, we evaluated its performance on the training and test datasets. The experiment results show that the proposed TEMPTING (TEMPoral relaTion extractING) system (ranked seventh) achieved an F-score of 0.563, which was at least 30% better than that of the baseline system, which randomly selects TLINK candidates from all pairs and assigns the TLINK types. The TEMPTING system using the hybrid method also outperformed the stage-based TEMPTING system. Its F-scores were 3.51% and 0.97% better than those of the stage-based system on the training set and test set, respectively. Copyright © 2013 Elsevier Inc. All rights reserved.

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

    Science.gov (United States)

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

    2016-06-01

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

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

    Science.gov (United States)

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

    2018-06-01

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

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

    International Nuclear Information System (INIS)

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

    2014-01-01

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

  18. HSTLBO: A hybrid algorithm based on Harmony Search and Teaching-Learning-Based Optimization for complex high-dimensional optimization problems.

    Directory of Open Access Journals (Sweden)

    Shouheng Tuo

    Full Text Available Harmony Search (HS and Teaching-Learning-Based Optimization (TLBO as new swarm intelligent optimization algorithms have received much attention in recent years. Both of them have shown outstanding performance for solving NP-Hard optimization problems. However, they also suffer dramatic performance degradation for some complex high-dimensional optimization problems. Through a lot of experiments, we find that the HS and TLBO have strong complementarity each other. The HS has strong global exploration power but low convergence speed. Reversely, the TLBO has much fast convergence speed but it is easily trapped into local search. In this work, we propose a hybrid search algorithm named HSTLBO that merges the two algorithms together for synergistically solving complex optimization problems using a self-adaptive selection strategy. In the HSTLBO, both HS and TLBO are modified with the aim of balancing the global exploration and exploitation abilities, where the HS aims mainly to explore the unknown regions and the TLBO aims to rapidly exploit high-precision solutions in the known regions. Our experimental results demonstrate better performance and faster speed than five state-of-the-art HS variants and show better exploration power than five good TLBO variants with similar run time, which illustrates that our method is promising in solving complex high-dimensional optimization problems. The experiment on portfolio optimization problems also demonstrate that the HSTLBO is effective in solving complex read-world application.

  19. RNA-protein binding motifs mining with a new hybrid deep learning based cross-domain knowledge integration approach

    DEFF Research Database (Denmark)

    Pan, Xiaoyong; Shen, Hong Bin

    2017-01-01

    , their domain specific features and formats have posed significant computational challenges. One of current difficulties is that the cross-source shared common knowledge is at a higher abstraction level beyond the observed data, resulting in a low efficiency of direct integration of observed data across domains...... space using multiple layers of learning blocks, where the shared representations across different domains are integrated. To validate our iDeep method, we performed experiments on 31 large-scale CLIP-seq datasets, and our results show that by integrating multiple sources of data, the average AUC can...... be improved by 8% compared to the best single-source-based predictor; and through cross-domain knowledge integration at an abstraction level, it outperforms the state-of-the-art predictors by 6%. Besides the overall enhanced prediction performance, the convolutional neural network module embedded in i...

  20. Observation versus classification in supervised category learning.

    Science.gov (United States)

    Levering, Kimery R; Kurtz, Kenneth J

    2015-02-01

    The traditional supervised classification paradigm encourages learners to acquire only the knowledge needed to predict category membership (a discriminative approach). An alternative that aligns with important aspects of real-world concept formation is learning with a broader focus to acquire knowledge of the internal structure of each category (a generative approach). Our work addresses the impact of a particular component of the traditional classification task: the guess-and-correct cycle. We compare classification learning to a supervised observational learning task in which learners are shown labeled examples but make no classification response. The goals of this work sit at two levels: (1) testing for differences in the nature of the category representations that arise from two basic learning modes; and (2) evaluating the generative/discriminative continuum as a theoretical tool for understand learning modes and their outcomes. Specifically, we view the guess-and-correct cycle as consistent with a more discriminative approach and therefore expected it to lead to narrower category knowledge. Across two experiments, the observational mode led to greater sensitivity to distributional properties of features and correlations between features. We conclude that a relatively subtle procedural difference in supervised category learning substantially impacts what learners come to know about the categories. The results demonstrate the value of the generative/discriminative continuum as a tool for advancing the psychology of category learning and also provide a valuable constraint for formal models and associated theories.

  1. 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

  2. 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.

  3. Unifying generative and discriminative learning principles

    Directory of Open Access Journals (Sweden)

    Strickert Marc

    2010-02-01

    Full Text Available Abstract Background The recognition of functional binding sites in genomic DNA remains one of the fundamental challenges of genome research. During the last decades, a plethora of different and well-adapted models has been developed, but only little attention has been payed to the development of different and similarly well-adapted learning principles. Only recently it was noticed that discriminative learning principles can be superior over generative ones in diverse bioinformatics applications, too. Results Here, we propose a generalization of generative and discriminative learning principles containing the maximum likelihood, maximum a posteriori, maximum conditional likelihood, maximum supervised posterior, generative-discriminative trade-off, and penalized generative-discriminative trade-off learning principles as special cases, and we illustrate its efficacy for the recognition of vertebrate transcription factor binding sites. Conclusions We find that the proposed learning principle helps to improve the recognition of transcription factor binding sites, enabling better computational approaches for extracting as much information as possible from valuable wet-lab data. We make all implementations available in the open-source library Jstacs so that this learning principle can be easily applied to other classification problems in the field of genome and epigenome analysis.

  4. Hybrid composites

    CSIR Research Space (South Africa)

    Jacob John, Maya

    2009-04-01

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

  5. Hybrid intermediaries

    OpenAIRE

    Cetorelli, Nicola

    2014-01-01

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

  6. Hybrid stars

    Indian Academy of Sciences (India)

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

  7. Análisis de la interacción en ambientes híbridos de aprendizaje Interaction Analysis in Hybrid Learning Environment

    Directory of Open Access Journals (Sweden)

    Josep María Duart Montoliu

    2011-10-01

    Full Text Available El análisis de la interacción en ambientes virtuales e híbridos es un tema complejo, puesto que es necesario superar la aproximación cuantitativa, número de mensajes, y lograr información sobre las dinámicas de interacción, en el marco de las actividades educativas. En este trabajo se presenta un conjunto de estrategias para el análisis de la interacción, las cuales se diseñaron durante el desarrollo de una tesis doctoral, como respuesta a dos retos que fueron identificados: ¿cómo observar la interacción?, ¿cómo relacionar la interacción con el rendimiento académico? Las estrategias diseñadas ofrecen elementos para el análisis de las actividades educativas, análisis de las discusiones virtuales asincrónicas, representación de las interacciones y la relación entre la interacción y el rendimiento académico. El conjunto de estrategias permitió reconocer el fenómeno de la interacción en el marco de actividades educativas, así como el proceso o dinámica en la interacción grupal, que muestra la evolución del grupo hacia la construcción de conocimiento. Por otro lado, también permitió analizar los procesos virtuales de interacción y establecer comparaciones entre las dinámicas de los grupos y la relación entre éstas y los resultados de rendimiento académico. Si bien el grupo de estrategias surgen en un estudio específico, ofrecen herramientas que pueden utilizarse en otros contextos. La manera de utilizar las estrategias se ilustra en este artículo con un ejemplo.Interaction analysis in virtual and hybrid learning environments is a complex issue, since it is necessary to go beyond a quantitative approach (number of messages and obtain information about interaction dynamics in the context of educational activities. This article presents a set of interaction analysis strategies, which were designed during the development of a doctoral thesis in response to the two challenges identified: First, how can

  8. Learning

    Directory of Open Access Journals (Sweden)

    Mohsen Laabidi

    2014-01-01

    Full Text Available Nowadays learning technologies transformed educational systems with impressive progress of Information and Communication Technologies (ICT. Furthermore, when these technologies are available, affordable and accessible, they represent more than a transformation for people with disabilities. They represent real opportunities with access to an inclusive education and help to overcome the obstacles they met in classical educational systems. In this paper, we will cover basic concepts of e-accessibility, universal design and assistive technologies, with a special focus on accessible e-learning systems. Then, we will present recent research works conducted in our research Laboratory LaTICE toward the development of an accessible online learning environment for persons with disabilities from the design and specification step to the implementation. We will present, in particular, the accessible version “MoodleAcc+” of the well known e-learning platform Moodle as well as new elaborated generic models and a range of tools for authoring and evaluating accessible educational content.

  9. Quelles aides les formations hybrides en langues proposent-elles à l'apprenant pour favoriser son autonomie ? What kind of assistance do blended language learning courses provide to learners in order to foster their autonomy?

    Directory of Open Access Journals (Sweden)

    Elke Nissen

    2007-11-01

    Full Text Available L'apprenant qui suit une formation hybride en langues travaille partiellement à distance, ce qui lui demande une certaine autonomie. La question alors est de savoir si ces formations soutiennent l'apprenant dans le développement de son autonomie et si oui, comment. Les réponses des concepteurs de huit formations hybrides à un questionnaire auto-administré montrent que les nécessaires développement et soutien de l'autonomie sont toujours respectés ; ainsi, ces huit formations proposent des aides pour favoriser l'autonomie dans les domaines technique, méthodologique, social et, bien sûr, langagier. Développer ces autonomies semble donc être devenu un standard dans le cadre des formations observées. En revanche, les autonomies de type psycho-affectif, informationnel, cognitif et métacognitif ne sont pas prises en considération dans toutes les formations.When taking a blended learning course, a learner works partially at a distance, which requires some autonomy. The aim of this study is to find out whether blended learning courses sustain the development of learner autonomy and if they do so, how they do it. The statements that 8 course designers made in a questionnaire show that their courses always help the learners to become or to be autonomous. All 8 courses provide assistance (advice, information and activities in order to foster technical, methodological, social and, of course, language autonomy. Consequently, sustaining these four types of autonomy seems to have become a standard in blended learning courses. But, on the contrary, assistance for other types of autonomy is not systematically provided: only several of these courses help the learners to develop psycho affective, informational, cognitive and metacognive autonomy.

  10. An Exploratory Study of the Drivers of Student Satisfaction and Learning Experience in Hybrid-Online and Purely Online Marketing Courses

    Science.gov (United States)

    Estelami, Hooman

    2012-01-01

    Much of the existing research in distance education has focused on contrasting the outcomes between traditional face-to-face teaching and purely online courses, in which the entire course content is delivered online. However, research has not examined the effectiveness of hybrid-online courses, in which a combination of online delivery and…

  11. Two months make a difference in spatial orientation learning in very old hybrid Fischer 344 X Brown Norway (FBNF1) rats

    NARCIS (Netherlands)

    Staay, van der F.J.

    2006-01-01

    Age-related changes in cognitive performance may be more pronounced in the period near or exceeding the median life span. Therefore, we compared the acquisition of a Morris water escape task by two groups of very old Fischer344 × Brown Norway hybrid rats. The mean age difference between the two

  12. Formations hybrides et interactions en ligne du point de vue de l'enseignant : pratiques, représentations, évolutions Blended learning and online interaction from the teacher's perspective: practice, representation and evolution

    Directory of Open Access Journals (Sweden)

    Christian Degache

    2008-10-01

    Full Text Available Les formations hybrides sont de plus en plus nombreuses dans le domaine des langues mais ne sont, une fois créées, pas toujours stables dans le temps. Devant ce constat, nous avons fait l'hypothèse, qui est au fondement du présent article, que ces évolutions sont liées au déroulement des interactions qui ont effectivement eu lieu dans le cadre de ces formations. Pour vérifier notre hypothèse, nous avons mené des entretiens, basés sur des questionnaires hétéro-administrés, avec 15 concepteurs de formations en langues pour spécialistes d'autres disciplines (Lansad conçues dans le cadre du projet Flodi. L'analyse des données ainsi obtenues a permis d'identifier les pratiques d'interaction, les représentations des concepteurs et les évolutions de formations hybrides. Elle montre que l'interaction effective est bien un facteur déterminant pour leur évolution. Par ailleurs, l'observation des évolutions passées, présentes ou futures nous a permis de distinguer quatre tendances des formations hybrides en langues : introductive (des Tice, optimisatrice, réorganisatrice et collaborative.Language training increasingly uses blended learning systems. One can state that the latter, once they are set up, often continue to be modified. We argue that these modifications are due to the interaction during the related training sessions. To verify our hypothesis we interviewed 15 designers of blended learning systems in the field of languages for specialists of other disciplines which are part of the Flodi-project, filling out questionnaires while interviewing them. An analysis of the data reveals interactional habits, course designers' representations, as well as past and foreseen modifications of the blended learning systems. The results show that interactions during training sessions did influence the evolution of the system. Moreover, we were able to distinguish between four tendencies of past, present and future modification of the

  13. Analysis and Modeling for Short- to Medium-Term Load Forecasting Using a Hybrid Manifold Learning Principal Component Model and Comparison with Classical Statistical Models (SARIMAX, Exponential Smoothing and Artificial Intelligence Models (ANN, SVM: The Case of Greek Electricity Market

    Directory of Open Access Journals (Sweden)

    George P. Papaioannou

    2016-08-01

    Full Text Available In this work we propose a new hybrid model, a combination of the manifold learning Principal Components (PC technique and the traditional multiple regression (PC-regression, for short and medium-term forecasting of daily, aggregated, day-ahead, electricity system-wide load in the Greek Electricity Market for the period 2004–2014. PC-regression is shown to effectively capture the intraday, intraweek and annual patterns of load. We compare our model with a number of classical statistical approaches (Holt-Winters exponential smoothing of its generalizations Error-Trend-Seasonal, ETS models, the Seasonal Autoregressive Moving Average with exogenous variables, Seasonal Autoregressive Integrated Moving Average with eXogenous (SARIMAX model as well as with the more sophisticated artificial intelligence models, Artificial Neural Networks (ANN and Support Vector Machines (SVM. Using a number of criteria for measuring the quality of the generated in-and out-of-sample forecasts, we have concluded that the forecasts of our hybrid model outperforms the ones generated by the other model, with the SARMAX model being the next best performing approach, giving comparable results. Our approach contributes to studies aimed at providing more accurate and reliable load forecasting, prerequisites for an efficient management of modern power systems.

  14. Learning Ionic

    CERN Document Server

    Ravulavaru, Arvind

    2015-01-01

    This book is intended for those who want to learn how to build hybrid mobile applications using Ionic. It is also ideal for people who want to explore theming for Ionic apps. Prior knowledge of AngularJS is essential to complete this book successfully.

  15. Hybrid Qualifications

    DEFF Research Database (Denmark)

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

  16. Hybrid Gear

    Science.gov (United States)

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

    2016-01-01

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

  17. Cloud E-Learning Service Strategies for Improving E-Learning Innovation Performance in a Fuzzy Environment by Using a New Hybrid Fuzzy Multiple Attribute Decision-Making Model

    Science.gov (United States)

    Su, Chiu Hung; Tzeng, Gwo-Hshiung; Hu, Shu-Kung

    2016-01-01

    The purpose of this study was to address this problem by applying a new hybrid fuzzy multiple criteria decision-making model including (a) using the fuzzy decision-making trial and evaluation laboratory (DEMATEL) technique to construct the fuzzy scope influential network relationship map (FSINRM) and determine the fuzzy influential weights of the…

  18. Towards a Pattern Language for Hybrid Education

    DEFF Research Database (Denmark)

    Köppe, Christian; Nørgård, Rikke Toft; Pedersen, Alex Young

    2017-01-01

    -digital, academic-nonacademic, online-offline, formal-informal, learning-teaching and individual-collective. In doing so, hybrid education invites uncertainty, open-endedness, risk-taking, experimentation, critical creativity, disruption, dialogue and democracy (back) into the heart of education. Accordingly, we......In this paper we offer an initial framework for a pattern language of hybrid education. With the term hybrid education, we imply the use of educational design patterns that actively strive to cut across, circumventing or upheave traditional dichotomies within education such as physical...... see, within hybrid education, the promise to push against and circumvent current trends of marketization, managerialism and standardization in higher education today. Here, a pattern language for hybrid education presents an alternative way of designing for future higher education in ways...

  19. Towards a Pattern Language for Hybrid Education

    DEFF Research Database (Denmark)

    Köppe, Christian; Nørgård, Rikke Toft; Pedersen, Alex Young

    2018-01-01

    In this paper we offer an initial framework for a pattern language of hybrid education. With the term hybrid education, we imply the use of educa- tional design patterns that actively strive to cut across, circumventing or upheave traditional dichotomies within education such as physical-digital......, academic-nonacademic, online-offline, formal-informal, learning-teaching and individual-collective. In doing so, hybrid education invites uncertainty, open-endedness, risk-taking, experimentation, critical creativity, disruption, dialogue and democracy (back) into the heart of education. Accordingly we see...... on teaching to the test, playing it safe, rankings or gaming the system approaches. Rather, hybrid education focuses on open-endedness, risk-taking, relational entanglements, experimentation, exploration and empathy. In this way, designing for hybrid education is in this paper achieved, partly by taking...

  20. 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....

  1. Hybridized Tetraquarks

    CERN Document Server

    Esposito, A.; Polosa, A.D.

    2016-01-01

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

  2. Continuity controlled Hybrid Automata

    NARCIS (Netherlands)

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

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

  3. Continuity Controlled Hybrid Automata

    NARCIS (Netherlands)

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

    2004-01-01

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

  4. Continuity controlled hybrid automata

    NARCIS (Netherlands)

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

    2004-01-01

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

  5. Continuity controlled hybrid automata

    NARCIS (Netherlands)

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

    2006-01-01

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

  6. Corporate Hybrid Bonds

    OpenAIRE

    Ahlberg, Johan; Jansson, Anton

    2016-01-01

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

  7. Hybridization and molecular geometry: A number game | Ojha ...

    African Journals Online (AJOL)

    Present article emphasize the new pedagogy to learn the hybridization and molecular geometry. It is always a challenge for the students to remember the hybridization and geometry of the molecule correctly. This topic has several importance in subjective and objective type questions and answers since in most of the ...

  8. A Hybrid Course Design: The Best of Both Educational Worlds

    Science.gov (United States)

    Poirier, Sandra

    2010-01-01

    Career and technical educators are constantly being challenged to have their courses meet the changing needs of their students in this fast-paced world people live in. As the name implies, the hybrid online course is a melding of traditional and online learning. In this article, the author describes her experience designing hybrid courses that…

  9. Hybrid XRF

    International Nuclear Information System (INIS)

    Heckel, J.

    2002-01-01

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

  10. 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

  11. La evaluación alternativa y autentica en los ambientes de aprendizaje híbridos y a distancia / The alternative and authentique evaluation in the hybrid and distance learning environments

    Directory of Open Access Journals (Sweden)

    Alejandra Fernández

    2017-12-01

    Full Text Available La evaluación del rendimiento es uno de los procesos críticos en la educación, que amerita profundizar la investigación y práctica, para hacer su aplicación más pedagógica y menos hacia el uso de tareas irrelevantes y a la medición, cuya aplicación al rendimiento de los alumnos persiste tanto en la educación presencial, como en los ambientes educativos híbridos y a distancia. Varios factores inciden en esta problemática como son: el aprecio institucional por la evaluación tradicional, la dificultad de evaluar en situaciones de aprendizaje con narrativas hibridas, el énfasis en la aplicación de pruebas finales y el uso de herramientas tecnológicas para evaluar. En este artículo se aborda el análisis didáctico, desde el diagnostico, de las aplicaciones tecnológicas de uso en la evaluación de la educación hibrida y a distancia , así como los aspectos críticos de la evaluación tradicional, con su énfasis objetivista, el uso de pruebas, la valoración de productos finales y la evaluación supeditada al control administrativo. Del diagnóstico y análisis didáctico, se genera una propuesta de cambios a partir de los supuestos de la evaluación alternativa y autentica, de ejecución y por competencias. Estas metodologías son claves para los cambios en la evaluación del rendimiento, al tomar en cuenta el real desempeño del estudiante para que responda a la realidad de su contexto, de manera relevante, más allá de la evaluación puramente académica. The evaluation of performance is one of the critical processes in education, which merits deepening research and practice, to make its application more pedagogical and less to the use of irrelevant tasks and measurement, whose application to student performance persists both in face-to-face education, as in hybrid and distance learning environments. Several factors affect this problem, such as: institutional appreciation for traditional assessment, difficulty in evaluating

  12. Designframework for an Adaptive, Hybrid MOOC

    DEFF Research Database (Denmark)

    Gynther, Karsten

    2015-01-01

    The research project has developed a design framework for an adaptive hybrid MOOC that complements the MOOC format with blended learning. The design framework consists of a design model and a series of pedagogical design principles that can be used to design courses for teacher professional...

  13. Hybrid Management in Hospitals

    DEFF Research Database (Denmark)

    Byrkjeflot, Haldor; Jespersen, Peter Kragh

    2010-01-01

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

  14. Hydraulic Hybrid Vehicles

    Science.gov (United States)

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

  15. Mesoscale hybrid calibration artifact

    Science.gov (United States)

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

    2010-09-07

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

  16. 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.

  17. 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.

  18. 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

  19. 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

  20. Henkin and Hybrid Logic

    DEFF Research Database (Denmark)

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

    2014-01-01

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

  1. Hybrid Action Systems

    DEFF Research Database (Denmark)

    Ronkko, Mauno; Ravn, Anders P.

    1997-01-01

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

  2. Nanoscale Organic Hybrid Electrolytes

    KAUST Repository

    Nugent, Jennifer L.

    2010-08-20

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

  3. Nanoscale Organic Hybrid Electrolytes

    KAUST Repository

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

    2010-01-01

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

  4. HYBRID VEHICLE CONTROL SYSTEM

    Directory of Open Access Journals (Sweden)

    V. Dvadnenko

    2016-06-01

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

  5. Hybrid radiator cooling system

    Science.gov (United States)

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

    2016-03-15

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

  6. Toronto hybrid taxi pilot

    Energy Technology Data Exchange (ETDEWEB)

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

    2009-10-15

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

  7. Managing hybrid marketing systems.

    Science.gov (United States)

    Moriarty, R T; Moran, U

    1990-01-01

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

  8. Toronto hybrid taxi pilot

    International Nuclear Information System (INIS)

    Stevens, M.; Marans, B.

    2009-10-01

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

  9. Hybrid FOSS Project

    Data.gov (United States)

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

  10. From hybrid swarms to swarms of hybrids

    Science.gov (United States)

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

    2014-01-01

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

  11. 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.

  12. Hybridization in geese

    NARCIS (Netherlands)

    Ottenburghs, Jente; Hooft, van Pim; Wieren, van Sipke E.; Ydenberg, Ronald C.; Prins, Herbert H.T.

    2016-01-01

    The high incidence of hybridization in waterfowl (ducks, geese and swans) makes this bird group an excellent study system to answer questions related to the evolution and maintenance of species boundaries. However, knowledge on waterfowl hybridization is biased towards ducks, with a large

  13. Mirror hybrid reactor studies

    International Nuclear Information System (INIS)

    Bender, D.J.

    1978-01-01

    The hybrid reactor studies are reviewed. The optimization of the point design and work on a reference design are described. The status of the nuclear analysis of fast spectrum blankets, systems studies for fissile fuel producing hybrid reactor, and the mechanical design of the machine are reviewed

  14. Hybrid Universities in Malaysia

    Science.gov (United States)

    Lee, Molly; Wan, Chang Da; Sirat, Morshidi

    2017-01-01

    Are Asian universities different from those in Western countries? Premised on the hypothesis that Asian universities are different because of hybridization between Western academic models and local traditional cultures, this paper investigates the hybrid characteristics in Malaysian universities resulting from interaction between contemporary…

  15. Cardiac hybrid imaging

    Energy Technology Data Exchange (ETDEWEB)

    Gaemperli, Oliver [University Hospital Zurich, Cardiac Imaging, Zurich (Switzerland); University Hospital Zurich, Nuclear Cardiology, Cardiovascular Center, Zurich (Switzerland); Kaufmann, Philipp A. [University Hospital Zurich, Cardiac Imaging, Zurich (Switzerland); Alkadhi, Hatem [University Hospital Zurich, Institute of Diagnostic and Interventional Radiology, Zurich (Switzerland)

    2014-05-15

    Hybrid cardiac single photon emission computed tomography (SPECT)/CT imaging allows combined assessment of anatomical and functional aspects of cardiac disease. In coronary artery disease (CAD), hybrid SPECT/CT imaging allows detection of coronary artery stenosis and myocardial perfusion abnormalities. The clinical value of hybrid imaging has been documented in several subsets of patients. In selected groups of patients, hybrid imaging improves the diagnostic accuracy to detect CAD compared to the single imaging techniques. Additionally, this approach facilitates functional interrogation of coronary stenoses and guidance with regard to revascularization procedures. Moreover, the anatomical information obtained from CT coronary angiography or coronary artery calcium scores (CACS) adds prognostic information over perfusion data from SPECT. The use of cardiac hybrid imaging has been favoured by the dissemination of dedicated hybrid systems and the release of dedicated image fusion software, which allow simple patient throughput for hybrid SPECT/CT studies. Further technological improvements such as more efficient detector technology to allow for low-radiation protocols, ultra-fast image acquisition and improved low-noise image reconstruction algorithms will be instrumental to further promote hybrid SPECT/CT in research and clinical practice. (orig.)

  16. Hybrid job shop scheduling

    NARCIS (Netherlands)

    Schutten, Johannes M.J.

    1995-01-01

    We consider the problem of scheduling jobs in a hybrid job shop. We use the term 'hybrid' to indicate that we consider a lot of extensions of the classic job shop, such as transportation times, multiple resources, and setup times. The Shifting Bottleneck procedure can be generalized to deal with

  17. Hybrid Shipboard Microgrids

    DEFF Research Database (Denmark)

    Othman @ Marzuki, Muzaidi Bin; Anvari-Moghaddam, Amjad; Guerrero, Josep M.

    2017-01-01

    Strict regulation on emissions of air pollutants imposed by the maritime authorities has led to the introduction of hybrid microgrids to the shipboard power systems (SPSs) which acts toward energy efficient ships with less pollution. A hybrid energy system can include different means of generation...

  18. Hybrid intelligent engineering systems

    CERN Document Server

    Jain, L C; Adelaide, Australia University of

    1997-01-01

    This book on hybrid intelligent engineering systems is unique, in the sense that it presents the integration of expert systems, neural networks, fuzzy systems, genetic algorithms, and chaos engineering. It shows that these new techniques enhance the capabilities of one another. A number of hybrid systems for solving engineering problems are presented.

  19. Editorial: Hybrid Systems

    DEFF Research Database (Denmark)

    Olderog, Ernst-Rüdiger; Ravn, Anders Peter

    2007-01-01

    An introduction to three papers in a special issue on Hybrid Systems. These paper were first presented at an IFIP WG 2.2 meeting in Skagen 2005.......An introduction to three papers in a special issue on Hybrid Systems. These paper were first presented at an IFIP WG 2.2 meeting in Skagen 2005....

  20. Course on hybrid calculation

    International Nuclear Information System (INIS)

    Weill, J.; Tellier; Bonnemay; Craigne; Chareton; Di Falco

    1969-02-01

    After a definition of hybrid calculation (combination of analogue and digital calculation) with a distinction between series and parallel hybrid computing, and a description of a hybrid computer structure and of task sharing between computers, this course proposes a description of hybrid hardware used in Saclay and Cadarache computing centres, and of operations performed by these systems. The next part addresses issues related to programming languages and software. The fourth part describes how a problem is organised for its processing on these computers. Methods of hybrid analysis are then addressed: resolution of optimisation problems, of partial differential equations, and of integral equations by means of different methods (gradient, maximum principle, characteristics, functional approximation, time slicing, Monte Carlo, Neumann iteration, Fischer iteration)

  1. Hybrid functional pseudopotentials

    Science.gov (United States)

    Yang, Jing; Tan, Liang Z.; Rappe, Andrew M.

    2018-02-01

    The consistency between the exchange-correlation functional used in pseudopotential construction and in the actual density functional theory calculation is essential for the accurate prediction of fundamental properties of materials. However, routine hybrid density functional calculations at present still rely on generalized gradient approximation pseudopotentials due to the lack of hybrid functional pseudopotentials. Here, we present a scheme for generating hybrid functional pseudopotentials, and we analyze the importance of pseudopotential density functional consistency for hybrid functionals. For the PBE0 hybrid functional, we benchmark our pseudopotentials for structural parameters and fundamental electronic gaps of the Gaussian-2 (G2) molecular dataset and some simple solids. Our results show that using our PBE0 pseudopotentials in PBE0 calculations improves agreement with respect to all-electron calculations.

  2. Faculty Perceptions of Pedagogical Considerations in the Design of Hybrid Courses

    Science.gov (United States)

    Jeghalef, Salma

    2016-01-01

    Changes in student demographics and in technology are driving American higher education to embrace innovative instruction. The hybrid mode of instruction is providing a learning modality that offers the flexibility and convenience of online learning without losing the benefits of a face-to-face learning environment. This mode of instruction is…

  3. NASA Workshop on Hybrid (Mixed-Actuator) Spacecraft Attitude Control

    Science.gov (United States)

    Dennehy, Cornelius J.; Kunz, Nans

    2014-01-01

    At the request of the Science Mission Directorate Chief Engineer, the NASA Technical Fellow for Guidance, Navigation & Control assembled and facilitated a workshop on Spacecraft Hybrid Attitude Control. This multi-Center, academic, and industry workshop, sponsored by the NASA Engineering and Safety Center (NESC), was held in April 2013 to unite nationwide experts to present and discuss the various innovative solutions, techniques, and lessons learned regarding the development and implementation of the various hybrid attitude control system solutions investigated or implemented. This report attempts to document these key lessons learned with the 16 findings and 9 NESC recommendations.

  4. Hybrid electric vehicles TOPTEC

    Energy Technology Data Exchange (ETDEWEB)

    NONE

    1994-06-21

    This one-day TOPTEC session began with an overview of hybrid electric vehicle technology. Updates were given on alternative types of energy storage, APU control for low emissions, simulation programs, and industry and government activities. The keynote speech was about battery technology, a key element to the success of hybrids. The TOPEC concluded with a panel discussion on the mission of hybrid electric vehicles, with a perspective from industry and government experts from United States and Canada on their view of the role of this technology.

  5. Hybrid systems with constraints

    CERN Document Server

    Daafouz, Jamal; Sigalotti, Mario

    2013-01-01

    Control theory is the main subject of this title, in particular analysis and control design for hybrid dynamic systems.The notion of hybrid systems offers a strong theoretical and unified framework to cope with the modeling, analysis and control design of systems where both continuous and discrete dynamics interact. The theory of hybrid systems has been the subject of intensive research over the last decade and a large number of diverse and challenging problems have been investigated. Nevertheless, many important mathematical problems remain open.This book is dedicated mainly to

  6. Towers of hybrid mesons

    International Nuclear Information System (INIS)

    Semay, Claude; Buisseret, Fabien; Silvestre-Brac, Bernard

    2009-01-01

    A hybrid meson is a quark-antiquark pair in which, contrary to ordinary mesons, the gluon field is in an excited state. In the framework of constituent models, the interaction potential is assumed to be the energy of an excited string. An approximate, but accurate, analytical solution of the Schroedinger equation with such a potential is presented. When applied to hybrid charmonia and bottomonia, towers of states are predicted in which the masses are a linear function of a harmonic oscillator band number for the quark-antiquark pair. Such a formula could be a reliable guide for the experimental detection of heavy hybrid mesons.

  7. Hybrid Bloch brane

    Energy Technology Data Exchange (ETDEWEB)

    Bazeia, D.; Lima, Elisama E.M.; Losano, L. [Universidade Federal da Paraiba, Departamento de Fisica, Joao Pessoa, PB (Brazil)

    2017-02-15

    This work reports on models described by two real scalar fields coupled with gravity in the five-dimensional spacetime, with a warped geometry involving one infinite extra dimension. Through a mechanism that smoothly changes a thick brane into a hybrid brane, one investigates the appearance of hybrid branes hosting internal structure, characterized by the splitting on the energy density and the volcano potential, induced by the parameter which controls interactions between the two scalar fields. In particular, we investigate distinct symmetric and asymmetric hybrid brane scenarios. (orig.)

  8. 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

  9. Developing a Blended Type Course of Introduction to Hybrid Vehicles

    Directory of Open Access Journals (Sweden)

    Na Zhu

    2016-02-01

    Full Text Available An innovative course of introduction to hybrid vehicles is developed for both associate and bachelor degree programs for engineering technology with automotive/mechanical concentration. The hybrid vehicle course content includes several topics, such as the rational of pure electric vehicle and hybrid vehicle, hybrid vehicle propulsion systems, fundamentals of motor/generator systems, fundamentals of battery and energy management system, and introduction to various configurations of hybrid vehicle systems available in market and under development. Hybrid vehicle technology is a new area and developed rapidly in the field of automotive and mechanical engineering. Students need not only the fundamentals and concepts from college, but also the ability to keep up with the latest technology after their graduation. Therefore, a blended course type is employed to help students have a better understanding of the fundamentals of hybrid vehicle and developing their self-studying ability. Topics in the course have three steps of learning. Firstly, on-ground lecture is given in class, where the instructor explains basic knowledge, such as principles, equations, and design rules.  In this way, the students will have enough background knowledge and be able to conduct further self-reading and research work. Secondly, students are required to go to university’s desire to learn (D2L online system and finish the online part of the topic. In the D2L system, students will find a quiz and its supporting materials. Thirdly, students come back to the on-ground lecture and discuss the quiz in groups with instructor. After the discussion, the instructor gives students a conclusion of the topic and moves forward to the next topic. A computer simulation class is also given to help student better understand the operation strategies of the hybrid vehicle systems and have a trial of design of hybrid vehicle.

  10. Hybrid adsorptive membrane reactor

    Science.gov (United States)

    Tsotsis, Theodore T [Huntington Beach, CA; Sahimi, Muhammad [Altadena, CA; Fayyaz-Najafi, Babak [Richmond, CA; Harale, Aadesh [Los Angeles, CA; Park, Byoung-Gi [Yeosu, KR; Liu, Paul K. T. [Lafayette Hill, PA

    2011-03-01

    A hybrid adsorbent-membrane reactor in which the chemical reaction, membrane separation, and product adsorption are coupled. Also disclosed are a dual-reactor apparatus and a process using the reactor or the apparatus.

  11. Hybrid plasmachemical reactor

    Energy Technology Data Exchange (ETDEWEB)

    Lelevkin, V. M., E-mail: lelevkin44@mail.ru; Smirnova, Yu. G.; Tokarev, A. V. [Kyrgyz-Russian Slavic University (Kyrgyzstan)

    2015-04-15

    A hybrid plasmachemical reactor on the basis of a dielectric barrier discharge in a transformer is developed. The characteristics of the reactor as functions of the dielectric barrier discharge parameters are determined.

  12. Marine Fish Hybridization

    KAUST Repository

    He, Song

    2017-01-01

    for each hybrid offspring in each case, haploweb analysis on diagnostic markers (nuclear and/or mitochondrial) and the DAPC/PCA analysis on microsatellite data were used. By combining the genetic evidences, morphological traits, and ecological observations

  13. Hybrid vertical cavity laser

    DEFF Research Database (Denmark)

    Chung, Il-Sug; Mørk, Jesper

    2010-01-01

    A new hybrid vertical cavity laser structure for silicon photonics is suggested and numerically investigated. It incorporates a silicon subwavelength grating as a mirror and a lateral output coupler to a silicon ridge waveguide.......A new hybrid vertical cavity laser structure for silicon photonics is suggested and numerically investigated. It incorporates a silicon subwavelength grating as a mirror and a lateral output coupler to a silicon ridge waveguide....

  14. Blended/Hybrid Courses: A Review of the Literature and Recommendations for Instructional Designers and Educators

    Science.gov (United States)

    Helms, Samuel A.

    2014-01-01

    This article explores some of the literature on blended/hybrid learning and identifies recommendations for instructional designers and faculty. Terminology and definitions are discussed first including the debate between the words "blended" and "hybrid." A working definition for the article is discussed but the article does not…

  15. Assessing Student Performance in Hybrid versus Web-Facilitated Personal Health Courses

    Science.gov (United States)

    Cathorall, Michelle L.; Xin, Huaibo; Blankson, Faustina; Kempland, Monica; Schaefer, Courtney

    2018-01-01

    This study aims to examine the effectiveness of web-facilitated and hybrid course delivery formats on student learning outcomes for four sections of an undergraduate Personal Health course at a public institution. This is a quasi-experimental study. Two sections were taught as hybrid classes and two sections were taught as webfacilitated classes.…

  16. Testing the Efficacy of MyPsychlab to Replace Traditional Instruction in a Hybrid Course

    Science.gov (United States)

    Powers, Kasey L.; Brooks, Patricia J.; Galazyn, Magdalena; Donnelly, Seamus

    2016-01-01

    Online course-packs are marketed as improving grades in introductory-level coursework, yet it is unknown whether these course-packs can effectively replace, as opposed to supplement, in-class instruction. This study compared learning outcomes for Introductory Psychology students in hybrid and traditional sections, with hybrid sections replacing…

  17. Effectiveness of a Hybrid Classroom in the Delivery of Medical Terminology Course Content

    Science.gov (United States)

    Martin, Jeffrey S.; Kreiger, Joan E.; Apicerno, Amy L

    2015-01-01

    Hybrid courses are emerging as a viable option for content delivery across college campuses. In an attempt to maximize learning outcomes while leveraging resources, one institution used several sections of a Medical Terminology course as a pilot. Traditional and hybrid course delivery were compared utilizing a quantitative research method to…

  18. Human hybrid hybridoma

    Energy Technology Data Exchange (ETDEWEB)

    Tiebout, R.F.; van Boxtel-Oosterhof, F.; Stricker, E.A.M.; Zeijlemaker, W.P.

    1987-11-15

    Hybrid hybridomas are obtained by fusion of two cells, each producing its own antibody. Several authors have reported the construction of murine hybrid hybridomas with the aim to obtain bispecific monoclonal antibodies. The authors have investigated, in a model system, the feasibility of constructing a human hybrid hybridoma. They fused two monoclonal cell lines: an ouabain-sensitive and azaserine/hypoxanthine-resistant Epstein-Barr virus-transformed human cell line that produces an IgG1kappa antibody directed against tetanus toxiod and an azaserine/hypoxanthine-sensitive and ouabain-resistant human-mouse xenohybrid cell line that produces a human IgG1lambda antibody directed against hepatitis-B surface antigen. Hybrid hybridoma cells were selected in culture medium containing azaserine/hypoxanthine and ouabain. The hybrid nature of the secreted antibodies was analyzed by means of two antigen-specific immunoassay. The results show that it is possible, with the combined use of transformation and xenohybridization techniques, to construct human hybrid hybridomas that produce bispecific antibodies. Bispecific antibodies activity was measured by means of two radioimmunoassays.

  19. Systems for hybrid cars

    Science.gov (United States)

    Bitsche, Otmar; Gutmann, Guenter

    Not only sharp competition but also legislation are pushing development of hybrid drive trains. Based on conventional internal combustion engine (ICE) vehicles, these drive trains offer a wide range of benefits from reduced fuel consumption and emission to multifaceted performance improvements. Hybrid electric drive trains may also facilitate the introduction of fuel cells (FC). The battery is the key component for all hybrid drive trains, as it dominates cost and performance issues. The selection of the right battery technology for the specific automotive application is an important task with an impact on costs of development and use. Safety, power, and high cycle life are a must for all hybrid applications. The greatest pressure to reduce cost is in soft hybrids, where lead-acid embedded in a considerate management presents the cheapest solution, with a considerable improvement in performance needed. From mild to full hybridization, an improvement in specific power makes higher costs more acceptable, provided that the battery's service life is equivalent to the vehicle's lifetime. Today, this is proven for the nickel-metal hydride system. Lithium ion batteries, which make use of a multiple safety concept, and with some development anticipated, provide even better prospects in terms of performance and costs. Also, their scalability permits their application in battery electric vehicles—the basis for better performance and enhanced user acceptance. Development targets for the batteries are discussed with a focus on system aspects such as electrical and thermal management and safety.

  20. Building Integrated PV and PV/Hybrid Products - The PV:BONUS Experience: Preprint

    Energy Technology Data Exchange (ETDEWEB)

    Thomas, H.; Pierce, L. K.

    2001-10-01

    Presented at the 2001 NCPV Program Review Meeting: Successes and lessons learned from PV:BONUS (Building Opportunities in the United States in PV). This program has funded the development of PV or PV/hybrid products for building applications.

  1. Hybrid-augmented intelligence:collaboration and cognition

    Institute of Scientific and Technical Information of China (English)

    Nan-ning ZHENG; Zi-yi LIU; Peng-ju REN; Yong-qiang MA; Shi-tao CHEN; Si-yu YU; Jian-ru XUE

    2017-01-01

    The long-term goal of artificial intelligence (AI) is to make machines learn and think like human beings. Due to the high levels of uncertainty and vulnerability in human life and the open-ended nature of problems that humans are facing, no matter how intelligent machines are, they are unable to completely replace humans. Therefore, it is necessary to introduce human cognitive capabilities or human-like cognitive models into AI systems to develop a new form of AI, that is, hybrid-augmented intelligence. This form of AI or machine intelligence is a feasible and important developing model. Hybrid-augmented intelligence can be divided into two basic models:one is human-in-the-loop augmented intelligence with human-computer collaboration, and the other is cognitive computing based augmented intelligence, in which a cognitive model is embedded in the machine learning system. This survey describes a basic framework for human-computer collaborative hybrid-augmented intelligence, and the basic elements of hybrid-augmented intelligence based on cognitive computing. These elements include intuitive reasoning, causal models, evolution of memory and knowledge, especially the role and basic principles of intuitive reasoning for complex problem solving, and the cognitive learning framework for visual scene understanding based on memory and reasoning. Several typical applications of hybrid-augmented intelligence in related fields are given.

  2. Hybrid Neuro-Fuzzy Classifier Based On Nefclass Model

    Directory of Open Access Journals (Sweden)

    Bogdan Gliwa

    2011-01-01

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

  3. Students' Perceptions of Learning Mode in Mathematics

    Science.gov (United States)

    Krishnan, Saras

    2016-01-01

    Blended courses or hybrid courses have gained popularity over the years because of their flexibility and convenience. Technology use in the online component of the blended/hybrid courses is another influence particularly to the younger generation of learners who enjoy learning interactively in a virtual environment. However, depending on the…

  4. 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.

  5. Using Technology to Support Experiential Learning in Extension Nutrition and Health Programs

    Science.gov (United States)

    Schuster, Ellen

    2013-01-01

    Much has been written about hybrid or blended learning in K-12 and higher education. In hybrid, or blended learning, face-to-face and online delivery of content are provided. The challenge is how best to use each delivery mode to optimize learning. For example, students may view videos or other multimedia content outside of class, with class time…

  6. Fusion-fission hybrid reactors

    International Nuclear Information System (INIS)

    Greenspan, E.

    1984-01-01

    This chapter discusses the range of characteristics attainable from hybrid reactor blankets; blanket design considerations; hybrid reactor designs; alternative fuel hybrid reactors; multi-purpose hybrid reactors; and hybrid reactors and the energy economy. Hybrid reactors are driven by a fusion neutron source and include fertile and/or fissile material. The fusion component provides a copious source of fusion neutrons which interact with a subcritical fission component located adjacent to the plasma or pellet chamber. Fissile fuel and/or energy are the main products of hybrid reactors. Topics include high F/M blankets, the fissile (and tritium) breeding ratio, effects of composition on blanket properties, geometrical considerations, power density and first wall loading, variations of blanket properties with irradiation, thermal-hydraulic and mechanical design considerations, safety considerations, tokamak hybrid reactors, tandem-mirror hybrid reactors, inertial confinement hybrid reactors, fusion neutron sources, fissile-fuel and energy production ability, simultaneous production of combustible and fissile fuels, fusion reactors for waste transmutation and fissile breeding, nuclear pumped laser hybrid reactors, Hybrid Fuel Factories (HFFs), and scenarios for hybrid contribution. The appendix offers hybrid reactor fundamentals. Numerous references are provided

  7. Development of Web-Based Learning Application for Generation Z

    Science.gov (United States)

    Hariadi, Bambang; Dewiyani Sunarto, M. J.; Sudarmaningtyas, Pantjawati

    2016-01-01

    This study aimed to develop a web-based learning application as a form of learning revolution. The form of learning revolution includes the provision of unlimited teaching materials, real time class organization, and is not limited by time or place. The implementation of this application is in the form of hybrid learning by using Google Apps for…

  8. Novel hybrid adaptive controller for manipulation in complex perturbation environments.

    Directory of Open Access Journals (Sweden)

    Alex M C Smith

    Full Text Available In this paper we present a hybrid control scheme, combining the advantages of task-space and joint-space control. The controller is based on a human-like adaptive design, which minimises both control effort and tracking error. Our novel hybrid adaptive controller has been tested in extensive simulations, in a scenario where a Baxter robot manipulator is affected by external disturbances in the form of interaction with the environment and tool-like end-effector perturbations. The results demonstrated improved performance in the hybrid controller over both of its component parts. In addition, we introduce a novel method for online adaptation of learning parameters, using the fuzzy control formalism to utilise expert knowledge from the experimenter. This mechanism of meta-learning induces further improvement in performance and avoids the need for tuning through trial testing.

  9. La régulation par des tâches médiatisées et scénarisées dans un dispositif hybride utilisant le TBI Regulation through mediated and didactised tasks in a blended learning course in which an interactive whiteboard is used

    Directory of Open Access Journals (Sweden)

    Sandrine Aguerre

    2011-12-01

    Full Text Available L'auteure présente un dispositif hybride de "formation à distance enrichie par le présentiel" dans lequel le temps en présentiel a pour fonction spécifique la régulation. Cette régulation concerne aussi bien le versant apprentissage que le versant enseignement de la situation. Elle s'attache notamment à situer les tâches et les sous-tâches par rapport à la réalisation d'une tâche globale et par rapport à l'apprentissage, notamment par un travail de décontextualisation et recontextualisation de ces tâches. L'utilisation du TBI lors du temps en présentiel a un effet non seulement sur la médiatisation pendant cette séance, mais aussi sur la scénarisation et la médiatisation (tant dans son aspect humain que technologique des tâches réalisées à distance, en permettant à l'apprenant de prendre part à la scénarisation et à la médiation.The author presents a blended-learning environment in which most learning activities are e-learning activities, and face to face situation is dedicated to regulation. Regulation is a mean to adapt learning as well as teaching; it aims particularly at considering tasks and sub-tasks in relation to a global task, and to learning. This control allows decontextualization and re-contextualization of the tasks. The use of the interactive whiteboard during face to face situation has an effect on task setting and task mediation (technological as well as human, making possible for the learner to take part in these.

  10. Hybrid discrete choice models: Gained insights versus increasing effort

    International Nuclear Information System (INIS)

    Mariel, Petr; Meyerhoff, Jürgen

    2016-01-01

    Hybrid choice models expand the standard models in discrete choice modelling by incorporating psychological factors as latent variables. They could therefore provide further insights into choice processes and underlying taste heterogeneity but the costs of estimating these models often significantly increase. This paper aims at comparing the results from a hybrid choice model and a classical random parameter logit. Point of departure for this analysis is whether researchers and practitioners should add hybrid choice models to their suite of models routinely estimated. Our comparison reveals, in line with the few prior studies, that hybrid models gain in efficiency by the inclusion of additional information. The use of one of the two proposed approaches, however, depends on the objective of the analysis. If disentangling preference heterogeneity is most important, hybrid model seems to be preferable. If the focus is on predictive power, a standard random parameter logit model might be the better choice. Finally, we give recommendations for an adequate use of hybrid choice models based on known principles of elementary scientific inference. - Highlights: • The paper compares performance of a Hybrid Choice Model (HCM) and a classical Random Parameter Logit (RPL) model. • The HCM indeed provides insights regarding preference heterogeneity not gained from the RPL. • The RPL has similar predictive power as the HCM in our data. • The costs of estimating HCM seem to be justified when learning more on taste heterogeneity is a major study objective.

  11. Hybrid discrete choice models: Gained insights versus increasing effort

    Energy Technology Data Exchange (ETDEWEB)

    Mariel, Petr, E-mail: petr.mariel@ehu.es [UPV/EHU, Economía Aplicada III, Avda. Lehendakari Aguire, 83, 48015 Bilbao (Spain); Meyerhoff, Jürgen [Institute for Landscape Architecture and Environmental Planning, Technical University of Berlin, D-10623 Berlin, Germany and The Kiel Institute for the World Economy, Duesternbrooker Weg 120, 24105 Kiel (Germany)

    2016-10-15

    Hybrid choice models expand the standard models in discrete choice modelling by incorporating psychological factors as latent variables. They could therefore provide further insights into choice processes and underlying taste heterogeneity but the costs of estimating these models often significantly increase. This paper aims at comparing the results from a hybrid choice model and a classical random parameter logit. Point of departure for this analysis is whether researchers and practitioners should add hybrid choice models to their suite of models routinely estimated. Our comparison reveals, in line with the few prior studies, that hybrid models gain in efficiency by the inclusion of additional information. The use of one of the two proposed approaches, however, depends on the objective of the analysis. If disentangling preference heterogeneity is most important, hybrid model seems to be preferable. If the focus is on predictive power, a standard random parameter logit model might be the better choice. Finally, we give recommendations for an adequate use of hybrid choice models based on known principles of elementary scientific inference. - Highlights: • The paper compares performance of a Hybrid Choice Model (HCM) and a classical Random Parameter Logit (RPL) model. • The HCM indeed provides insights regarding preference heterogeneity not gained from the RPL. • The RPL has similar predictive power as the HCM in our data. • The costs of estimating HCM seem to be justified when learning more on taste heterogeneity is a major study objective.

  12. Students' Positive and Negative Experiences in Hybrid and Online Classes

    Science.gov (United States)

    El Mansour, Bassou; Mupinga, Davison M.

    2007-01-01

    As higher education institutions struggle to meet the growing demand for education from non-traditional students, many are turning to hybrid and online courses. These courses, free up classroom space, allow faculty to reach a wider audience using technology; and are therefore cost effective. But, what learning experiences do these courses provide…

  13. Using a Hybrid Approach for a Leadership Cohort Program

    Science.gov (United States)

    Norman, Maxine A.

    2013-01-01

    Because information technology continues to change rapidly, Extension is challenged with learning and using technology appropriately. We assert Extension cannot shy away from the challenges but must embrace technology because audiences and external forces demand it. A hybrid, or blended, format of a leadership cohort program was offered to public…

  14. Research on Hybrid Vehicle Drivetrain

    Science.gov (United States)

    Xie, Zhongzhi

    Hybrid cars as a solution to energy saving, emission reduction measures, have received widespread attention. Motor drive system as an important part of the hybrid vehicles as an important object of study. Based on the hybrid electric vehicle powertrain control system for permanent magnet synchronous motor as the object of study. Can be applied to hybrid car compares the characteristics of traction motors, chose permanent magnet synchronous Motors as drive motors for hybrid vehicles. Building applications in hybrid cars in MATLAB/Simulink simulation model of permanent-magnet synchronous motor speed control system and analysis of simulation results.

  15. New hybrid systems

    International Nuclear Information System (INIS)

    Bernardin, B.

    2001-01-01

    New hybrid systems are made up of a subcritical core, a spallation target and a proton accelerator. The neutrons that are produced in the target by the flux of protons are necessary to maintain the chain reaction of fission. Some parameters that are important for a classical nuclear reactor like doppler coefficient or delayed neutron fraction do not matter in a hybrid system. In a PWR-type reactor or in a fast reactor the concentration of actinides has a bad impact on these 2 parameters, so it is justified to study hybrid systems as actinide transmuters. The hybrid system, because of its external source of neutrons can put aside an important reactivity margin. This reactivity margin can be used to design safer nuclear reactors (particularly in some situations of reactivity accidents) or to irradiate fuel elements containing high concentrations of minor actinides that could not be allowed in a classical reactor. This article reviews various ways of integrating hybrid systems in a population of already existing nuclear reactors in order to manage quantities of plutonium, of minor actinides or of long-life fission products. (A.C.)

  16. The Hybrid Museum: Hybrid Economies of Meaning

    DEFF Research Database (Denmark)

    Vestergaard, Vitus

    2013-01-01

    Social media has created new ways of communicating and has brought about a new distinctive ethos. New literacies are not simply about new technology but also about this new ethos. Many museums are embracing this ethos by what is often called participatory practices. From a sociocultural perspective...... this article shows that there are two different museum mindsets where the second mindset leans towards participatory practices. It is shown how a museum can support a hybrid economy of meaning that builds on both a user generated economy of meaning and an institutional economy of meaning and adds value to both...

  17. Hybrid system concepts

    International Nuclear Information System (INIS)

    Landeyro, P.A.

    1995-01-01

    Hybrid systems studied for fissile material production, were reconsidered for minor actinide and long-lived fission product destruction as alternative to the traditional final disposal of nuclear waste. Now there are attempts to extend the use of the concepts developed for minor actinide incineration to plutonium burning. The most promising hybrid system concept considers fuel and target both as liquids. From the results obtained, the possibility to adopt composite targets seems the most promising solution, but still there remains the problem of Pu production, not acceptable in a burning system. This kind of targets can be mainly used for fissile material production, while for accelerator driven burners it is most convenient to use a liquid lead target. The most suitable solvent is heavy water for minor actinide annihilation in the blanket of a hybrid system. Due to the criticality conditions and the necessity of electric energy production, the blanket using plutonium dissolved in molten salts is the most convenient one. (author)

  18. Hybrid strategies in nanolithography

    Energy Technology Data Exchange (ETDEWEB)

    Saavedra, Hector M; Mullen, Thomas J; Zhang Pengpeng; Dewey, Daniel C; Claridge, Shelley A; Weiss, Paul S [Department of Chemistry, The Pennsylvania State University, University Park, PA 16802 (United States)], E-mail: psw@cnsi.ucla.edu

    2010-03-15

    Hybrid nanoscale patterning strategies combine the registration and addressability of conventional lithographic techniques with the chemical and physical functionality enabled by intermolecular, electrostatic and/or biological interactions. This review aims to highlight and to provide a comprehensive description of recent developments in hybrid nanoscale patterning strategies that enhance existing lithographic techniques or can be used to fabricate functional chemical patterns that interact with their environment. These functional structures create new capabilities, such as the fabrication of physicochemical surfaces that can recognize and capture analytes from complex liquid or gaseous mixtures. The nanolithographic techniques we describe can be classified into three general areas: traditional lithography, soft lithography and scanning-probe lithography. The strengths and limitations of each hybrid patterning technique will be discussed, along with the current and potential applications of the resulting patterned, functional surfaces.

  19. Hybrid Taxis Give Fuel Economy a Lift, Clean Cities, Fleet Experiences, April 2009 (Fact Sheet)

    Energy Technology Data Exchange (ETDEWEB)

    2009-04-01

    Clean Cities helped Boston, San Antonio, and Cambridge create hybrid taxi programs. The hybrid taxis are able to achieve about twice the gas mileage of a conventional taxi while helping cut gasoline use and fuel costs. Tax credits and other incentives are helping both company owners and drivers make the switch to hybrids. Program leaders have learned some important lessons other cities can benefit from including learning a city's taxi structure, relaying benefits to drivers, and understanding the needs of owners.

  20. The tokamak hybrid reactor

    International Nuclear Information System (INIS)

    Kelly, J.L.; Rose, R.P.

    1981-01-01

    At a time when the potential benefits of various energy options are being seriously evaluated in many countries through-out the world, it is both timely and important to evaluate the practical application of fusion reactors for their economical production of nuclear fissile fuels from fertile fuels. The fusion hybrid reactor represents a concept that could assure the availability of adequate fuel supplies for a proven nuclear technology and have the potential of being an electrical energy source as opposed to an energy consumer as are the present fuel enrichment processes. Westinghouse Fusion Power Systems Department, under Contract No. EG-77-C-02-4544 with the Department of Energy, Office of Fusion Energy, has developed a preliminary conceptual design for an early twenty-first century fusion hybrid reactor called the commercial Tokamak Hybrid Reactor (CTHR). This design was developed as a first generation commercial plant producing fissile fuel to support a significant number of client Light Water Reactor (LWR) Plants. To the depth this study has been performed, no insurmountable technical problems have been identified. The study has provided a basis for reasonable cost estimates of the hybrid plants as well as the hybrid/LWR system busbar electricity costs. This energy system can be optimized to have a net cost of busbar electricity that is equivalent to the conventional LWR plant, yet is not dependent on uranium ore prices or standard enrichment costs, since the fusion hybrid can be fueled by numerous fertile fuel resources. A nearer-term concept is also defined using a beam driven fusion driver in lieu of the longer term ignited operating mode. (orig.)

  1. 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 ...

  2. Hydraulic Hybrid Vehicle Publications | Transportation Research | NREL

    Science.gov (United States)

    Hydraulic Hybrid Vehicle Publications Hydraulic Hybrid Vehicle Publications The following technical papers and fact sheets provide information about NREL's hydraulic hybrid fleet vehicle evaluations . Refuse Trucks Project Startup: Evaluating the Performance of Hydraulic Hybrid Refuse Vehicles. Bob

  3. Doubts about hybrids

    International Nuclear Information System (INIS)

    Anon.

    1982-01-01

    The natural draught wet cooling tower with a height of 160 m is considerably taller than the 80 m high hybrid cooling tower, but the latter has a considerably larger diameter. Spray losses for both types are about 4.5 kg/sec for a thermal output of 2500 MW. Apart from the pump load, the natural cooling tower requires no power. Apart from higher pump loads, the hybrid cooling tower requires power for the fans. The energy demand for this purpose is 1.5 to 3% of the nett powerstation output. For the Isar 2 nuclear powerstation this would mean a reduction in puput of about 35 MW. (orig.) [de

  4. Analog and hybrid computing

    CERN Document Server

    Hyndman, D E

    2013-01-01

    Analog and Hybrid Computing focuses on the operations of analog and hybrid computers. The book first outlines the history of computing devices that influenced the creation of analog and digital computers. The types of problems to be solved on computers, computing systems, and digital computers are discussed. The text looks at the theory and operation of electronic analog computers, including linear and non-linear computing units and use of analog computers as operational amplifiers. The monograph examines the preparation of problems to be deciphered on computers. Flow diagrams, methods of ampl

  5. Toyota hybrid synergy drive

    Energy Technology Data Exchange (ETDEWEB)

    Gautschi, H.

    2008-07-01

    This presentation made at the Swiss 2008 research conference on traffic by Hannes Gautschi, director of service and training at the Toyota company in Switzerland, takes a look at Toyota's hybrid drive vehicles. The construction of the vehicles and their combined combustion engines and electric generators and drives is presented and the combined operation of these components is described. Braking and energy recovery are discussed. Figures on the performance, fuel consumption and CO{sub 2} output of the hybrid vehicles are compared with those of conventional vehicles.

  6. Mirror fusion--fission hybrids

    International Nuclear Information System (INIS)

    Lee, J.D.

    1978-01-01

    The fusion-fission concept and the mirror fusion-fission hybrid program are outlined. Magnetic mirror fusion drivers and blankets for hybrid reactors are discussed. Results of system analyses are presented and a reference design is described

  7. Economics of hybrid photovoltaic power plants

    Energy Technology Data Exchange (ETDEWEB)

    Breyer, Christian

    2012-08-16

    The global power supply stability is faced to several severe and fundamental threats, in particular steadily increasing power demand, diminishing and degrading fossil and nuclear energy resources, very harmful greenhouse gas emissions, significant energy injustice and a structurally misbalanced ecological footprint. Photovoltaic (PV) power systems are analysed in various aspects focusing on economic and technical considerations of supplemental and substitutional power supply to the constraint conventional power system. To infer the most relevant system approach for PV power plants several solar resources available for PV systems are compared. By combining the different solar resources and respective economics, two major PV systems are identified to be very competitive in almost all regions in the world. The experience curve concept is used as a key technique for the development of scenario assumptions on economic projections for the decade of the 2010s. Main drivers for cost reductions in PV systems are learning and production growth rate, thus several relevant aspects are discussed such as research and development investments, technical PV market potential, different PV technologies and the energetic sustainability of PV. Three major market segments for PV systems are identified: off-grid PV solutions, decentralised small scale on-grid PV systems (several kWp) and large scale PV power plants (tens of MWp). Mainly by application of 'grid-parity' and 'fuel-parity' concepts per country, local market and conventional power plant basis, the global economic market potential for all major PV system segments is derived. PV power plant hybridization potential of all relevant power technologies and the global power plant structure are analyzed regarding technical, economical and geographical feasibility. Key success criteria for hybrid PV power plants are discussed and comprehensively analysed for all adequate power plant technologies, i.e. oil, gas and coal fired power

  8. Economics of hybrid photovoltaic power plants

    Energy Technology Data Exchange (ETDEWEB)

    Breyer, Christian

    2012-08-16

    The global power supply stability is faced to several severe and fundamental threats, in particular steadily increasing power demand, diminishing and degrading fossil and nuclear energy resources, very harmful greenhouse gas emissions, significant energy injustice and a structurally misbalanced ecological footprint. Photovoltaic (PV) power systems are analysed in various aspects focusing on economic and technical considerations of supplemental and substitutional power supply to the constraint conventional power system. To infer the most relevant system approach for PV power plants several solar resources available for PV systems are compared. By combining the different solar resources and respective economics, two major PV systems are identified to be very competitive in almost all regions in the world. The experience curve concept is used as a key technique for the development of scenario assumptions on economic projections for the decade of the 2010s. Main drivers for cost reductions in PV systems are learning and production growth rate, thus several relevant aspects are discussed such as research and development investments, technical PV market potential, different PV technologies and the energetic sustainability of PV. Three major market segments for PV systems are identified: off-grid PV solutions, decentralised small scale on-grid PV systems (several kWp) and large scale PV power plants (tens of MWp). Mainly by application of 'grid-parity' and 'fuel-parity' concepts per country, local market and conventional power plant basis, the global economic market potential for all major PV system segments is derived. PV power plant hybridization potential of all relevant power technologies and the global power plant structure are analyzed regarding technical, economical and geographical feasibility. Key success criteria for hybrid PV power plants are discussed and comprehensively analysed for all adequate power plant technologies, i.e. oil, gas and

  9. Security in hybrid cloud computing

    OpenAIRE

    Koudelka, Ondřej

    2016-01-01

    This bachelor thesis deals with the area of hybrid cloud computing, specifically with its security. The major aim of the thesis is to analyze and compare the chosen hybrid cloud providers. For the minor aim this thesis compares the security challenges of hybrid cloud as opponent to other deployment models. In order to accomplish said aims, this thesis defines the terms cloud computing and hybrid cloud computing in its theoretical part. Furthermore the security challenges for cloud computing a...

  10. 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.

  11. Hybrid Ventilation Air Flow Process

    DEFF Research Database (Denmark)

    Heiselberg, Per Kvols

    The scope of this annex is therefore to obtain better knowledge of the use of hybrid ventilation technologies. The annex focus on development of control strategies for hybrid ventilation, on development of methods to predict hybrid ventilation performance in office buildings and on implementation...

  12. USING THE US EXPERIENCE OF ONLINE AND HYBRID EDUCATION IN UKRAINIAN UNIVERSITIES

    Directory of Open Access Journals (Sweden)

    Ірина Задорожна

    2015-12-01

    Full Text Available The article investigates the best practices of the US universities on providing hybrid and online education that can be implemented at Ukrainian universities which experience lack of finances and a decrease in student enrollment. Basic factors of online and hybrid courses popularity are analysed (flexibility; accessibility, especially for students with special needs; saving time; convenience; motivation as students often feel less stressed in a virtual classroom than in a face-to-face environment. The main challenges of online and hybrid learning (faculty training and professional development for online education (in terms of pedagogy, communication and technology, supporting student learning in the online environment, and creating an efficient and interactive online learning community are defined in the article. Hybrid courses are regarded as such that promote some equivalence between digital and live communication.

  13. Teelt van hybride wintertarwerassen

    NARCIS (Netherlands)

    Timmer, R.D.; Paauw, J.G.M.

    2003-01-01

    Om de mogelijkheden van de teelt van hybride wintertarwerassen onder Nederlandse omstandigheden in beeld te brengen zijn er van 2000-2002 proeven uitgevoerd op het PPO-proefbedrijf te Lelystad. In deze proeven zijn een 4-tal hybriderassen (Hybnos, Hyno-braba, Hyno-esta, Mercury) vergeleken met een

  14. Hybrid FSAE Vehicle Realization

    Science.gov (United States)

    2010-12-01

    The goal of this multi-year project is to create a fully functional University of Idaho entry in the hybrid FSAE competition. Vehicle integration is underway as part of a variety of 2010-11 senior design projects. This leverages a variety of analytic...

  15. Electric and hybrid vehicles

    Science.gov (United States)

    1979-01-01

    Report characterizes state-of-the-art electric and hybrid (combined electric and heat engine) vehicles. Performance data for representative number of these vehicles were obtained from track and dynamometer tests. User experience information was obtained from fleet operators and individual owners of electric vehicles. Data on performance and physical characteristics of large number of vehicles were obtained from manufacturers and available literature.

  16. Nuclear hybrid energy infrastructure

    Energy Technology Data Exchange (ETDEWEB)

    Agarwal, Vivek; Tawfik, Magdy S.

    2015-02-01

    The nuclear hybrid energy concept is becoming a reality for the US energy infrastructure where combinations of the various potential energy sources (nuclear, wind, solar, biomass, and so on) are integrated in a hybrid energy system. This paper focuses on challenges facing a hybrid system with a Small Modular Reactor at its core. The core of the paper will discuss efforts required to develop supervisory control center that collects data, supports decision-making, and serves as an information hub for supervisory control center. Such a center will also be a model for integrating future technologies and controls. In addition, advanced operations research, thermal cycle analysis, energy conversion analysis, control engineering, and human factors engineering will be part of the supervisory control center. Nuclear hybrid energy infrastructure would allow operators to optimize the cost of energy production by providing appropriate means of integrating different energy sources. The data needs to be stored, processed, analyzed, trended, and projected at right time to right operator to integrate different energy sources.

  17. Hybridization of biomedical circuitry

    Science.gov (United States)

    Rinard, G. A.

    1978-01-01

    The design and fabrication of low power hybrid circuits to perform vital signs monitoring are reported. The circuits consist of: (1) clock; (2) ECG amplifier and cardiotachometer signal conditioner; (3) impedance pneumobraph and respiration rate processor; (4) hear/breath rate processor; (5) temperature monitor; and (6) LCD display.

  18. Glueballs, Hybrids and Exotics

    Science.gov (United States)

    Reyes, M. A.; Moreno, G.

    2006-09-01

    We comment on the physics analysis carried out by the Experimental High Energy Physics (EHEP) group of the Instituto de Fisica of the University of Guanajuato (IFUG), Mexico. In particular, this group has been involved in analysis carried out to search for glueball, hybrid and exotic candidates.

  19. Hybrid wars’ information component

    Directory of Open Access Journals (Sweden)

    T. A. Nevskaya

    2015-01-01

    Full Text Available The war of the new generation - hybrid war, the information component which is directed not so much on the direct destruction of the enemy, how to achieve the goals without warfare. Fighting in the information field is no less important than immediate military action.

  20. Glueballs, Hybrids and Exotics

    International Nuclear Information System (INIS)

    Reyes, M. A.; Moreno, G.

    2006-01-01

    We comment on the physics analysis carried out by the Experimental High Energy Physics (EHEP) group of the Instituto de Fisica of the University of Guanajuato (IFUG), Mexico. In particular, this group has been involved in analysis carried out to search for glueball, hybrid and exotic candidates

  1. Hybrid quantum computation

    International Nuclear Information System (INIS)

    Sehrawat, Arun; Englert, Berthold-Georg; Zemann, Daniel

    2011-01-01

    We present a hybrid model of the unitary-evolution-based quantum computation model and the measurement-based quantum computation model. In the hybrid model, part of a quantum circuit is simulated by unitary evolution and the rest by measurements on star graph states, thereby combining the advantages of the two standard quantum computation models. In the hybrid model, a complicated unitary gate under simulation is decomposed in terms of a sequence of single-qubit operations, the controlled-z gates, and multiqubit rotations around the z axis. Every single-qubit and the controlled-z gate are realized by a respective unitary evolution, and every multiqubit rotation is executed by a single measurement on a required star graph state. The classical information processing in our model requires only an information flow vector and propagation matrices. We provide the implementation of multicontrol gates in the hybrid model. They are very useful for implementing Grover's search algorithm, which is studied as an illustrative example.

  2. Hybrid keyword search auctions

    KAUST Repository

    Goel, Ashish; Munagala, Kamesh

    2009-01-01

    Search auctions have become a dominant source of revenue generation on the Internet. Such auctions have typically used per-click bidding and pricing. We propose the use of hybrid auctions where an advertiser can make a per-impression as well as a per-click bid, and the auctioneer then chooses one of the two as the pricing mechanism. We assume that the advertiser and the auctioneer both have separate beliefs (called priors) on the click-probability of an advertisement. We first prove that the hybrid auction is truthful, assuming that the advertisers are risk-neutral. We then show that this auction is superior to the existing per-click auction in multiple ways: 1. We show that risk-seeking advertisers will choose only a per-impression bid whereas risk-averse advertisers will choose only a per-click bid, and argue that both kind of advertisers arise naturally. Hence, the ability to bid in a hybrid fashion is important to account for the risk characteristics of the advertisers. 2. For obscure keywords, the auctioneer is unlikely to have a very sharp prior on the click-probabilities. In such situations, we show that having the extra information from the advertisers in the form of a per-impression bid can result in significantly higher revenue. 3. An advertiser who believes that its click-probability is much higher than the auctioneer's estimate can use per-impression bids to correct the auctioneer's prior without incurring any extra cost. 4. The hybrid auction can allow the advertiser and auctioneer to implement complex dynamic programming strategies to deal with the uncertainty in the click-probability using the same basic auction. The per-click and per-impression bidding schemes can only be used to implement two extreme cases of these strategies. As Internet commerce matures, we need more sophisticated pricing models to exploit all the information held by each of the participants. We believe that hybrid auctions could be an important step in this direction. The hybrid

  3. Hybrid keyword search auctions

    KAUST Repository

    Goel, Ashish

    2009-01-01

    Search auctions have become a dominant source of revenue generation on the Internet. Such auctions have typically used per-click bidding and pricing. We propose the use of hybrid auctions where an advertiser can make a per-impression as well as a per-click bid, and the auctioneer then chooses one of the two as the pricing mechanism. We assume that the advertiser and the auctioneer both have separate beliefs (called priors) on the click-probability of an advertisement. We first prove that the hybrid auction is truthful, assuming that the advertisers are risk-neutral. We then show that this auction is superior to the existing per-click auction in multiple ways: 1. We show that risk-seeking advertisers will choose only a per-impression bid whereas risk-averse advertisers will choose only a per-click bid, and argue that both kind of advertisers arise naturally. Hence, the ability to bid in a hybrid fashion is important to account for the risk characteristics of the advertisers. 2. For obscure keywords, the auctioneer is unlikely to have a very sharp prior on the click-probabilities. In such situations, we show that having the extra information from the advertisers in the form of a per-impression bid can result in significantly higher revenue. 3. An advertiser who believes that its click-probability is much higher than the auctioneer\\'s estimate can use per-impression bids to correct the auctioneer\\'s prior without incurring any extra cost. 4. The hybrid auction can allow the advertiser and auctioneer to implement complex dynamic programming strategies to deal with the uncertainty in the click-probability using the same basic auction. The per-click and per-impression bidding schemes can only be used to implement two extreme cases of these strategies. As Internet commerce matures, we need more sophisticated pricing models to exploit all the information held by each of the participants. We believe that hybrid auctions could be an important step in this direction. The

  4. Direct electrical arc ignition of hybrid rocket motors

    Science.gov (United States)

    Judson, Michael I., Jr.

    Hybrid rockets motors provide distinct safety advantages when compared to traditional liquid or solid propellant systems, due to the inherent stability and relative inertness of the propellants prior to established combustion. As a result of this inherent propellant stability, hybrid motors have historically proven difficult to ignite. State of the art hybrid igniter designs continue to require solid or liquid reactants distinct from the main propellants. These ignition methods however, reintroduce to the hybrid propulsion system the safety and complexity disadvantages associated with traditional liquid or solid propellants. The results of this study demonstrate the feasibility of a novel direct electrostatic arc ignition method for hybrid motors. A series of small prototype stand-alone thrusters demonstrating this technology were successfully designed and tested using Acrylonitrile Butadiene Styrene (ABS) plastic and Gaseous Oxygen (GOX) as propellants. Measurements of input voltage and current demonstrated that arc-ignition will occur using as little as 10 watts peak power and less than 5 joules total energy. The motor developed for the stand-alone small thruster was adapted as a gas generator to ignite a medium-scale hybrid rocket motor using nitrous oxide /and HTPB as propellants. Multiple consecutive ignitions were performed. A large data set as well as a collection of development `lessons learned' were compiled to guide future development and research. Since the completion of this original groundwork research, the concept has been developed into a reliable, operational igniter system for a 75mm hybrid motor using both gaseous oxygen and liquid nitrous oxide as oxidizers. A development map of the direct spark ignition concept is presented showing the flow of key lessons learned between this original work and later follow on development.

  5. Epitaxial growth of hybrid nanostructures

    Science.gov (United States)

    Tan, Chaoliang; Chen, Junze; Wu, Xue-Jun; Zhang, Hua

    2018-02-01

    Hybrid nanostructures are a class of materials that are typically composed of two or more different components, in which each component has at least one dimension on the nanoscale. The rational design and controlled synthesis of hybrid nanostructures are of great importance in enabling the fine tuning of their properties and functions. Epitaxial growth is a promising approach to the controlled synthesis of hybrid nanostructures with desired structures, crystal phases, exposed facets and/or interfaces. This Review provides a critical summary of the state of the art in the field of epitaxial growth of hybrid nanostructures. We discuss the historical development, architectures and compositions, epitaxy methods, characterization techniques and advantages of epitaxial hybrid nanostructures. Finally, we provide insight into future research directions in this area, which include the epitaxial growth of hybrid nanostructures from a wider range of materials, the study of the underlying mechanism and determining the role of epitaxial growth in influencing the properties and application performance of hybrid nanostructures.

  6. Mirror hybrid reactor optimization studies

    International Nuclear Information System (INIS)

    Bender, D.J.

    1976-01-01

    A system model of the mirror hybrid reactor has been developed. The major components of the model include (1) the reactor description, (2) a capital cost analysis, (3) various fuel management schemes, and (4) an economic analysis that includes the hybrid plus its associated fission burner reactors. The results presented describe the optimization of the mirror hybrid reactor, the objective being to minimize the cost of electricity from the hybrid fission-burner reactor complex. We have examined hybrid reactors with two types of blankets, one containing natural uranium, the other thorium. The major difference between the two optimized reactors is that the uranium hybrid is a significant net electrical power producer, whereas the thorium hybrid just about breaks even on electrical power. Our projected costs for fissile fuel production are approximately 50 $/g for 239 Pu and approximately 125 $/g for 233 U

  7. 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

  8. Learning How to Learn

    DEFF Research Database (Denmark)

    Lauridsen, Karen M.; Lauridsen, Ole

    Ole Lauridsen, Aarhus School of Business and Social Sciences, Aarhus University, Denmark Karen M. Lauridsen, Aarhus School of Business and Social Sciences, Aarhus University, Denmark Learning Styles in Higher Education – Learning How to Learn Applying learning styles (LS) in higher education...... by Constructivist learning theory and current basic knowledge of how the brain learns. The LS concept will thus be placed in a broader learning theoretical context as a strong learning and teaching tool. Participants will be offered the opportunity to have their own LS preferences established before...... teaching leads to positive results and enhanced student learning. However, learning styles should not only be considered a didactic matter for the teacher, but also a tool for the individual students to improve their learning capabilities – not least in contexts where information is not necessarily...

  9. Sneutrino Hybrid Inflation

    International Nuclear Information System (INIS)

    Antusch, Stefan

    2006-01-01

    We review the scenario of sneutrino hybrid inflation, where one of the singlet sneutrinos, the superpartners of the right-handed neutrinos, plays the role of the inflaton. In a minimal model of sneutrino hybrid inflation, the spectral index is given by ns ≅ 1 + 2γ. With γ = 0.025 ± 0.01 constrained by WMAP, a running spectral index vertical bar dns/dlnk vertical bar << vertical barγvertical bar and a tensor-to-scalar ratio r << γ2 are predicted. Small neutrino masses arise from the seesaw mechanism, with heavy masses for the singlet (s)neutrinos generated by the vacuum expectation value of the waterfall field after inflation. The baryon asymmetry of the universe can be explained by non-thermal leptogenesis via sneutrino inflaton decay, with low reheat temperature TRH ≅ 106 GeV

  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. Hybrid superconducting magnetic suspensions

    International Nuclear Information System (INIS)

    Tixador, P.; Hiebel, P.; Brunet, Y.; Chaud, X.; Gautier-Picard, P.

    1996-01-01

    Superconductors, especially high T c ones, are the most attractive materials to design stable and fully passive magnetic suspensions which have to control five degrees of freedom. The hybrid superconducting magnetic suspensions present high performances and a simple cooling mode. They consist of a permanent magnet bearing, stabilized by a suitable magnet-superconductor structure. Several designs are given and compared in terms of forces and stiffnesses. The design of the magnet bearing plays an important part. The superconducting magnetic bearing participates less in levitation but must provide a high stabilizing stiffness. This is achieved by the magnet configuration, a good material in term of critical current density and field cooling. A hybrid superconducting suspension for a flywheel is presented. This system consists of a magnet thrust bearing stabilized by superconductors interacting with an alternating polarity magnet structure. First tests and results are reported. Superconducting materials are magnetically melt-textured YBaCuO

  12. The Power of Hybridization

    CERN Multimedia

    CERN. Geneva

    2011-01-01

    Programming languages always seem to do some things well but not others: Python punts when it comes to user interfaces, Java’s artificial complexity prevents rapid development and produces tangles, and it will be awhile before we see benefits from C++ concurrency work. The cognitive load of languages and their blind spots increases the cost of experimentation, impeding your ability to fail fast and iterate. If you use a single language to solve your problem, you are binding yourself to the worldview limitations and the mistakes made by the creator of that language. Consider increasing your wiggle room by crossing language boundaries, complementing a language that is powerful in one area with a different language powerful in another. Language hybridization can speed development to quickly discover your real problems, giving you more time to fix them. After making a case for hybridizing your thinking in general, I will present a number of simple examples; first showing the benefits of using other languages...

  13. Tokamak hybrid study

    International Nuclear Information System (INIS)

    Tenney, F.H.

    1976-09-01

    A report on one year of study of a tokamak hybrid reactor is presented. The plasma is maintained by both D and T beams. To obtain long burn times a poloidal field divertor is required. Both the single null and the double null style of divertor are considered. The blanket consists of a neutron multiplier region containing natural uranium followed by burner regions of molten salt (flibe) loaded with PuF 3 to enhance the energy multiplication. Economic analysis has been applied only recently to a variety of reactor sizes and plasma conditions. Early indications suggest that the most attractive hybrids will have large plasmas of major radius in excess of 8 meters

  14. Tokamak hybrid study

    International Nuclear Information System (INIS)

    Tenney, F.H.

    1976-01-01

    A report on one year of study of a tokamak hybrid reactor is given. The plasma is maintained by both D and T beams. To obtain long burn times a poloidal field divertor is required. Both the single null and the double null style of divertor are considered. The blanket consists of a neutron multiplier region containing natural uranium followed by burner regions of molten salt (flibe) loaded with PuF 3 to enhance the energy multiplication. Economic analysis has been applied only recently to a variety of reactor sizes and plasma conditions. Early indications suggest that the most attractive hybrids will have large plasmas of major radius in excess of 8 meters

  15. 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.

  16. Hybrid electroluminescent devices

    Science.gov (United States)

    Shiang, Joseph John; Duggal, Anil Raj; Michael, Joseph Darryl

    2010-08-03

    A hybrid electroluminescent (EL) device comprises at least one inorganic diode element and at least one organic EL element that are electrically connected in series. The absolute value of the breakdown voltage of the inorganic diode element is greater than the absolute value of the maximum reverse bias voltage across the series. The inorganic diode element can be a power diode, a Schottky barrier diode, or a light-emitting diode.

  17. 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

  18. The challenge of hybridization

    CERN Document Server

    Caccia, Massimo

    2000-01-01

    Hybridization of pixel detector systems has to satisfy tight requirements: high yield, long term reliability, mechanical stability, thermal compliance and robustness have to go together with low passive mass added to the system, radiation hardness, flexibility in the technology end eventually low cost. The current technologies for the interconnection of the front-end chips and the sensor are reviewed and compared, together with the solutions for the interface to the far-end electronics.

  19. Asymmetric Hybrid Nanoparticles

    Energy Technology Data Exchange (ETDEWEB)

    Chumanov, George [Clemson Univ., SC (United States)

    2015-11-05

    Hybrid Nanoparticles (AHNs) are rationally-designed multifunctional nanostructures and novel building blocks for the next generation of advanced materials and devices. Nanoscale materials attract considerable interest because of their unusual properties and potential for practical applications. Most of the activity in this field is focused on the synthesis of homogeneous nanoparticles from metals, metal oxides, semiconductors, and polymers. It is well recognized that properties of nanoparticles can be further enhanced if they are made as hybrid structures. This program is concerned with the synthesis, characterization, and application of such hybrid structures termed AHNs. AHNs are composed of a homogeneous core and several caps of different materials deposited on its surface (Fig. 1). Combined properties of the core and the caps as well as new properties that arise from core-cap and cap-cap interactions render AHNs multifunctional. In addition, specific chemical reactivity of the caps enables directional self-assembly of AHNs into complex architectures that are not possible with only spherical nanoparticles.

  20. 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.

  1. A Hybrid Prognostic Approach for Remaining Useful Life Prediction of Lithium-Ion Batteries

    Directory of Open Access Journals (Sweden)

    Wen-An Yang

    2016-01-01

    Full Text Available Lithium-ion battery is a core component of many systems such as satellite, spacecraft, and electric vehicles and its failure can lead to reduced capability, downtime, and even catastrophic breakdowns. Remaining useful life (RUL prediction of lithium-ion batteries before the future failure event is extremely crucial for proactive maintenance/safety actions. This study proposes a hybrid prognostic approach that can predict the RUL of degraded lithium-ion batteries using physical laws and data-driven modeling simultaneously. In this hybrid prognostic approach, the relevant vectors obtained with the selective kernel ensemble-based relevance vector machine (RVM learning algorithm are fitted to the physical degradation model, which is then extrapolated to failure threshold for estimating the RUL of the lithium-ion battery of interest. The experimental results indicated that the proposed hybrid prognostic approach can accurately predict the RUL of degraded lithium-ion batteries. Empirical comparisons show that the proposed hybrid prognostic approach using the selective kernel ensemble-based RVM learning algorithm performs better than the hybrid prognostic approaches using the popular learning algorithms of feedforward artificial neural networks (ANNs like the conventional backpropagation (BP algorithm and support vector machines (SVMs. In addition, an investigation is also conducted to identify the effects of RVM learning algorithm on the proposed hybrid prognostic approach.

  2. Learning to Learn.

    Science.gov (United States)

    Weiss, Helen; Weiss, Martin

    1988-01-01

    The article reviews theories of learning (e.g., stimulus-response, trial and error, operant conditioning, cognitive), considers the role of motivation, and summarizes nine research-supported rules of effective learning. Suggestions are applied to teaching learning strategies to learning-disabled students. (DB)

  3. The Hybrid Studio

    DEFF Research Database (Denmark)

    Steinø, Nicolai; Khalid, Md. Saifuddin

    2017-01-01

    in progress. It also worked as a one-on-one supervision platform for whenever students were in need of supervision and advice outside class hours.Methodologically, a phenomenographic approach was adopted in a single-case study in the form of a student workshop using an adapted problem-tree analysis method...... as a participatory learning and action method, in order to understand the students’ experiences andevaluation of blended learning systems and contexts.The paper gives an introduction to the traditional architecture and design studio teaching format, to blended learning, as well as to the preparation and setup...

  4. First-Order Hybrid Logic

    DEFF Research Database (Denmark)

    Braüner, Torben

    2011-01-01

    Hybrid logic is an extension of modal logic which allows us to refer explicitly to points of the model in the syntax of formulas. It is easy to justify interest in hybrid logic on applied grounds, with the usefulness of the additional expressive power. For example, when reasoning about time one...... often wants to build up a series of assertions about what happens at a particular instant, and standard modal formalisms do not allow this. What is less obvious is that the route hybrid logic takes to overcome this problem often actually improves the behaviour of the underlying modal formalism....... For example, it becomes far simpler to formulate proof-systems for hybrid logic, and completeness results can be proved of a generality that is simply not available in modal logic. That is, hybridization is a systematic way of remedying a number of known deficiencies of modal logic. First-order hybrid logic...

  5. An Exploration of Blended Learning in Fifth Grade Literacy Classrooms

    Science.gov (United States)

    Ramadan, Kimberly Heintschel

    2017-01-01

    The development of the Internet allows for hybrid models of instruction that marry face-to-face and online learning (Osguthorpe & Graham, 2003). The purpose of this study was to explore blended learning and traditional instruction in three fifth grade literacy classrooms, examining the teaching and learning students engaged in during the…

  6. Learning Styles of Medical Students Change in Relation to Time

    Science.gov (United States)

    Gurpinar, Erol; Bati, Hilal; Tetik, Cihat

    2011-01-01

    The aim of the present study was to investigate if any changes exist in the learning styles of medical students over time and in relation to different curriculum models with these learning styles. This prospective cohort study was conducted in three different medical faculties, which implement problem-based learning (PBL), hybrid, and integrated…

  7. Student Perceptions of Facebook as a Learning Aid

    Science.gov (United States)

    Daniel, Michael Aubrey

    2018-01-01

    Hybrid learning has been shown to enhance students' experiences in the classroom and can promote deeper learning when the tools used meet the students' particular learning needs. Many digital natives are familiar with Facebook and are able to navigate it with little difficulty. When used in an education setting in the place of traditional…

  8. Teacher and learner: Supervised and unsupervised learning in communities.

    Science.gov (United States)

    Shafto, Michael G; Seifert, Colleen M

    2015-01-01

    How far can teaching methods go to enhance learning? Optimal methods of teaching have been considered in research on supervised and unsupervised learning. Locally optimal methods are usually hybrids of teaching and self-directed approaches. The costs and benefits of specific methods have been shown to depend on the structure of the learning task, the learners, the teachers, and the environment.

  9. Hybrid solar lighting distribution systems and components

    Science.gov (United States)

    Muhs, Jeffrey D [Lenoir City, TN; Earl, Dennis D [Knoxville, TN; Beshears, David L [Knoxville, TN; Maxey, Lonnie C [Powell, TN; Jordan, John K [Oak Ridge, TN; Lind, Randall F [Lenoir City, TN

    2011-07-05

    A hybrid solar lighting distribution system and components having at least one hybrid solar concentrator, at least one fiber receiver, at least one hybrid luminaire, and a light distribution system operably connected to each hybrid solar concentrator and each hybrid luminaire. A controller operates all components.

  10. Completeness in Hybrid Type Theory

    DEFF Research Database (Denmark)

    Areces, Carlos; Blackburn, Patrick Rowan; Huertas, Antonia

    2014-01-01

    We show that basic hybridization (adding nominals and @ operators) makes it possible to give straightforward Henkin-style completeness proofs even when the modal logic being hybridized is higher-order. The key ideas are to add nominals as expressions of type t, and to extend to arbitrary types th......-style intensional models; we build, as simply as we can, hybrid logicover Henkin’s logic...

  11. Glueballs, hybrids, multiquarks

    Energy Technology Data Exchange (ETDEWEB)

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

    2007-12-15

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

  12. Hybrid spectral CT reconstruction.

    Directory of Open Access Journals (Sweden)

    Darin P Clark

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

  13. Hybrid spectral CT reconstruction

    Science.gov (United States)

    Clark, Darin P.

    2017-01-01

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

  14. Hybrid Maritime Warfare

    DEFF Research Database (Denmark)

    Schaub Jr, Gary John; Murphy, Martin; Hoffman, Frank

    2017-01-01

    Russia’s use of hybrid warfare techniques has raised concerns about the security of the Baltic States. Gary Schaub, Jr, Martin Murphy and Frank G Hoffman recommend a series of measures to augment NATO’s Readiness Action Plan in the Baltic region, including increasing the breadth and depth of naval...... exercises, and improving maritime domain awareness through cooperative programmes. They also suggest unilateral and cooperative measures to develop a sound strategic communications strategy to counter Moscow’s information operations, reduce dependence on Russian energy supplies and build the resilience...

  15. Indexical Hybrid Tense Logic

    DEFF Research Database (Denmark)

    Blackburn, Patrick Rowan; Jørgensen, Klaus Frovin

    2012-01-01

    In this paper we explore the logic of now, yesterday, today and tomorrow by combining the semantic approach to indexicality pioneered by Hans Kamp [9] and refined by David Kaplan [10] with hybrid tense logic. We first introduce a special now nominal (our @now corresponds to Kamp’s original now...... operator N) and prove completeness results for both logical and contextual validity. We then add propositional constants to handle yesterday, today and tomorrow; our system correctly treats sentences like “Niels will die yesterday” as contextually unsatisfiable. Building on our completeness results for now......, we prove completeness for the richer language, again for both logical and contextual validity....

  16. Hybrid Dark Matter

    OpenAIRE

    Chao, Wei

    2018-01-01

    Dark matter can be produced in the early universe via the freeze-in or freeze-out mechanisms. Both scenarios were investigated in references, but the production of dark matters via the combination of these two mechanisms are not addressed. In this paper we propose a hybrid dark matter model where dark matters have two components with one component produced thermally and the other one produced non-thermally. We present for the first time the analytical calculation for the relic abundance of th...

  17. Reflections on Intellectual Hybridity

    Directory of Open Access Journals (Sweden)

    Kimala Price

    2012-05-01

    Full Text Available Drawing from the growing literature on interdisciplinarity and my own experiences as an intellectual hybrid, I discuss the personal and institutional challenges inherent in crossing disciplinary boundaries in the academy. I argue that boundary crossing is a natural occurrence and that the issue of (interdisciplinarity is a matter of degree and of determining who gets to define the boundaries. Defining boundaries is not merely an intellectual enterprise, but also a political act that delineates what is, or is not, legitimate scholarship. This issue is especially salient to women's and gender studies during times of economic distress and educational budget cuts.

  18. Hybrid vehicle potential assessment. Volume 7: Hybrid vehicle review

    Science.gov (United States)

    Leschly, K. O.

    1979-01-01

    Review of hybrid vehicles built during the past ten years or planned to be built in the near future is presented. An attempt is made to classify and analyze these vehicles to get an overall picture of their key characteristics. The review includes onroad hybrid passenger cars, trucks, vans, and buses.

  19. PV-HYBRID and MINI-GRID. Proceedings

    Energy Technology Data Exchange (ETDEWEB)

    NONE

    2006-07-01

    design and validation of PV-hybrid sysem technology for rural electrification programmes in remote areas of Europe (Xavier Valive); (17) Analysis of inverter-controlled Island grids - transient simulations with ATP-EMTP and PowerFactory (Martin Braun); (18) Design of a PV-diesel hybrid energy system (William Lawrance); (19) Hybrid storage systems in PV stand alone applications impact on sizing and performance (Julien Labbe); (20) Sizing and analysis of a small hydro PV hybrid system for the rural electrification in developing countries (Joseph Kenfack); (21) Identification of dynamic equivalents for microgrids with high penetration of solar energy using ANNs (F.O. Resende); (22) Constructing village PV hybrid power systems on a wide-scale in Western China: Experience gained (Henrik Bindner); (23) Experiences with large-scale construction of PH hybrid village power systems in Western China (Winfried Klinghammer); (24) A detailed data based analysis of the behaviour of a 10+5+20 KW wind-PV-diesel hybrid sysem (Luis M. Arribas); (25) PV hybrid village electrification in French Guyana (Christian Dumbs); (26) Energy consumption patterns in village PV-diesel-hybrid systems (Javier Munoz); (27) From Subag to Ponelo hybrid photovoltaic-diesel system in Indonesia, lessons learned (Adjat Sudradjat); (28) PV diesel hybrid system in rural Africa - an inter-disciplinary approach (Markus Landau); (29) Making PV-diesel hybrids and PV or wind mini-grids sustainable in remote developing country sites: the Nabouwalu case (Philippe Veyan); (30) Mini-grid for an isolated island sandwip in Bangladesh (B.K. Bala).

  20. Hybrid ellipsoidal fuzzy systems in forecasting regional electricity loads

    Energy Technology Data Exchange (ETDEWEB)

    Pai, Ping-Feng [Department of Information Management, National Chi Nan University, 1 University Road, Puli, Nantou 545, Taiwan (China)

    2006-09-15

    Because of the privatization of electricity in many countries, load forecasting has become one of the most crucial issues in the planning and operations of electric utilities. In addition, accurate regional load forecasting can provide the transmission and distribution operators with more information. The hybrid ellipsoidal fuzzy system was originally designed to solve control and pattern recognition problems. The main objective of this investigation is to develop a hybrid ellipsoidal fuzzy system for time series forecasting (HEFST) and apply the proposed model to forecast regional electricity loads in Taiwan. Additionally, a scaled conjugate gradient learning method is employed in the supervised learning phase of the HEFST model. Subsequently, numerical data taken from the existing literature is used to demonstrate the forecasting performance of the HEFST model. Simulation results reveal that the proposed model has better forecasting performance than the artificial neural network model and the regression model. Thus, the HEFST model is a valid and promising alternative for forecasting regional electricity loads. (author)

  1. 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.

  2. Learning Styles.

    Science.gov (United States)

    Missouri Univ., Columbia. Coll. of Education.

    Information is provided regarding major learning styles and other factors important to student learning. Several typically asked questions are presented regarding different learning styles (visual, auditory, tactile and kinesthetic, and multisensory learning), associated considerations, determining individuals' learning styles, and appropriate…

  3. Hybrid Disease Diagnosis Using Multiobjective Optimization with Evolutionary Parameter Optimization

    Directory of Open Access Journals (Sweden)

    MadhuSudana Rao Nalluri

    2017-01-01

    Full Text Available With the widespread adoption of e-Healthcare and telemedicine applications, accurate, intelligent disease diagnosis systems have been profoundly coveted. In recent years, numerous individual machine learning-based classifiers have been proposed and tested, and the fact that a single classifier cannot effectively classify and diagnose all diseases has been almost accorded with. This has seen a number of recent research attempts to arrive at a consensus using ensemble classification techniques. In this paper, a hybrid system is proposed to diagnose ailments using optimizing individual classifier parameters for two classifier techniques, namely, support vector machine (SVM and multilayer perceptron (MLP technique. We employ three recent evolutionary algorithms to optimize the parameters of the classifiers above, leading to six alternative hybrid disease diagnosis systems, also referred to as hybrid intelligent systems (HISs. Multiple objectives, namely, prediction accuracy, sensitivity, and specificity, have been considered to assess the efficacy of the proposed hybrid systems with existing ones. The proposed model is evaluated on 11 benchmark datasets, and the obtained results demonstrate that our proposed hybrid diagnosis systems perform better in terms of disease prediction accuracy, sensitivity, and specificity. Pertinent statistical tests were carried out to substantiate the efficacy of the obtained results.

  4. Hybrid Multi-objective Forecasting of Solar Photovoltaic Output Using Kalman Filter based Interval Type-2 Fuzzy Logic System

    DEFF Research Database (Denmark)

    Hassan, Saima; Ahmadieh Khanesar, Mojtaba; Hajizadeh, Amin

    2017-01-01

    Learning of fuzzy parameters for system modeling using evolutionary algorithms is an interesting topic. In this paper, two optimal design and tuning of Interval type-2 fuzzy logic system are proposed using hybrid learning algorithms. The consequent parameters of the interval type-2 fuzzy logic...... system in both the hybrid algorithms are tuned using Kalman filter. Whereas the antecedent parameters of the system in the first hybrid algorithm is optimized using the multi-objective particle swarm optimization (MOPSO) and using the multi-objective evolutionary algorithm Based on Decomposition (MOEA...

  5. Interactive Digital Storytelling: Towards a Hybrid Conceptual Approach

    OpenAIRE

    Spierling, Ulrike

    2005-01-01

    1 Introduction In this contribution, Interactive Digital Storytelling is viewed as a hybrid form of game design and cinematic storytelling for the understanding and making of future learning and entertainment applications. The paper shall present formal design models that provide a conceptual bridge between both traditional linear narrative techniques as well as agent-based emergent conversations with virtual characters. In summary, a theoretical classification of thinking models for authors ...

  6. Nonminimally coupled hybrid inflation

    International Nuclear Information System (INIS)

    Koh, Seoktae; Minamitsuji, Masato

    2011-01-01

    We discuss the hybrid inflation model where the inflaton field is nonminimally coupled to gravity. In the Jordan frame, the potential contains φ 4 term as well as terms in the original hybrid inflation model. In our model, inflation can be classified into the type (I) and the type (II). In the type (I), inflation is terminated by the tachyonic instability of the waterfall field, while in the type (II) by the violation of slow-roll conditions. In our model, the reheating takes place only at the true minimum and even in the case (II) finally the tachyonic instability occurs after the termination of inflation. For a negative nonminimal coupling, inflation takes place in the vacuum-dominated region, in the large field region, or near the local minimum/maximum. Inflation in the vacuum-dominated region becomes either the type (I) or (II), resulting in a blue or red spectrum of the curvature perturbations, respectively. Inflation around the local maximum can be either the type (I) or the type (II), which results in the red spectrum of the curvature perturbations, while around the local minimum it must be the type (I), which results in the blue spectrum. In the large field region, to terminate inflation, potential in the Einstein frame must be positively tilted, always resulting in the red spectrum. We then numerically solve the equations of motion to investigate the whole dynamics of inflaton and confirm that the spectrum of curvature perturbations changes from red to blue ones as scales become smaller.

  7. Hybrid Turbine Electric Vehicle

    Science.gov (United States)

    Viterna, Larry A.

    1997-01-01

    Hybrid electric power trains may revolutionize today's ground passenger vehicles by significantly improving fuel economy and decreasing emissions. The NASA Lewis Research Center is working with industry, universities, and Government to develop and demonstrate a hybrid electric vehicle. Our partners include Bowling Green State University, the Cleveland Regional Transit Authority, Lincoln Electric Motor Division, the State of Ohio's Department of Development, and Teledyne Ryan Aeronautical. The vehicle will be a heavy class urban transit bus offering double the fuel economy of today's buses and emissions that are reduced to 1/10th of the Environmental Protection Agency's standards. At the heart of the vehicle's drive train is a natural-gas-fueled engine. Initially, a small automotive engine will be tested as a baseline. This will be followed by the introduction of an advanced gas turbine developed from an aircraft jet engine. The engine turns a high-speed generator, producing electricity. Power from both the generator and an onboard energy storage system is then provided to a variable-speed electric motor attached to the rear drive axle. An intelligent power-control system determines the most efficient operation of the engine and energy storage system.

  8. Hybrid spread spectrum radio system

    Science.gov (United States)

    Smith, Stephen F [London, TN; Dress, William B [Camas, WA

    2010-02-09

    Systems and methods are described for hybrid spread spectrum radio systems. A method, includes receiving a hybrid spread spectrum signal including: fast frequency hopping demodulating and direct sequence demodulating a direct sequence spread spectrum signal, wherein multiple frequency hops occur within a single data-bit time and each bit is represented by chip transmissions at multiple frequencies.

  9. The governance of hybrid organisations

    DEFF Research Database (Denmark)

    Spear, Roger; Cornforth, Chris

    2010-01-01

    The focus of this chapter is on the governance of third sector organizations (TSOs) and the challenges that are raised by hybridity. In particular it will focus on the question how does hybridity affect governance structures and processes and the challenges that governing bodies face?...

  10. Electric/Hybrid Vehicle Simulation

    Science.gov (United States)

    Slusser, R. A.; Chapman, C. P.; Brennand, J. P.

    1985-01-01

    ELVEC computer program provides vehicle designer with simulation tool for detailed studies of electric and hybrid vehicle performance and cost. ELVEC simulates performance of user-specified electric or hybrid vehicle under user specified driving schedule profile or operating schedule. ELVEC performs vehicle design and life cycle cost analysis.

  11. Electric-hybrid-vehicle simulation

    Science.gov (United States)

    Pasma, D. C.

    The simulation of electric hybrid vehicles is to be performed using experimental data to model propulsion system components. The performance of an existing ac propulsion system will be used as the baseline for comparative purposes. Hybrid components to be evaluated include electrically and mechanically driven flywheels, and an elastomeric regenerative braking system.

  12. 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....

  13. Conceptual innovations in hybrid reactors

    International Nuclear Information System (INIS)

    Greenspan, E.; Miley, G.H.

    1980-01-01

    A number of innovations in the conception of fusion-fission hybrid reactors, including the blanket, the fusion driver, the coupling of the fusion and the fission components as well as the application of hybrid reactors are described, and their feasibility assessed

  14. Toward a Freedom to Learn in Continuing Professional Education.

    Science.gov (United States)

    Boyer, Cheryl

    1986-01-01

    A hybrid of professional continuing education and Carl Rogers's humanistic philosophy supporting freedom in learning is proposed, and the five principles of the philosophy are examined for their potential for transfer to professional education. (MSE)

  15. Learning Networks, Networked Learning

    NARCIS (Netherlands)

    Sloep, Peter; Berlanga, Adriana

    2010-01-01

    Sloep, P. B., & Berlanga, A. J. (2011). Learning Networks, Networked Learning [Redes de Aprendizaje, Aprendizaje en Red]. Comunicar, XIX(37), 55-63. Retrieved from http://dx.doi.org/10.3916/C37-2011-02-05

  16. On-line identification of hybrid systems using an adaptive growing and pruning RBF neural network

    DEFF Research Database (Denmark)

    Alizadeh, Tohid

    2008-01-01

    This paper introduces an adaptive growing and pruning radial basis function (GAP-RBF) neural network for on-line identification of hybrid systems. The main idea is to identify a global nonlinear model that can predict the continuous outputs of hybrid systems. In the proposed approach, GAP......-RBF neural network uses a modified unscented kalman filter (UKF) with forgetting factor scheme as the required on-line learning algorithm. The effectiveness of the resulting identification approach is tested and evaluated on a simulated benchmark hybrid system....

  17. Hybrid laser-arc welding

    DEFF Research Database (Denmark)

    Hybrid laser-arc welding (HLAW) is a combination of laser welding with arc welding that overcomes many of the shortfalls of both processes. This important book gives a comprehensive account of hybrid laser-arc welding technology and applications. The first part of the book reviews...... the characteristics of the process, including the properties of joints produced by hybrid laser-arc welding and ways of assessing weld quality. Part II discusses applications of the process to such metals as magnesium alloys, aluminium and steel as well as the use of hybrid laser-arc welding in such sectors as ship...... building and the automotive industry. With its distinguished editor and international team of contributors, Hybrid laser-arc welding, will be a valuable source of reference for all those using this important welding technology. Professor Flemming Ove Olsen works in the Department of Manufacturing...

  18. Laser driven fusion fission hybrids

    International Nuclear Information System (INIS)

    Hansen, L.F.; Maniscalco, J.A.

    1977-11-01

    The role of the fusion-fission hybrid reactor (FFHR) as a fissile fuel and/or power producer is discussed. As long range options to supply the world energy needs, hybrid-fueled thermal-burner reactors are compared to liquid metal fast breeder reactors (LMFBR). A discussion of different fuel cycles (thorium, depleted uranium, and spent fuel) is presented in order to compare the energy multiplication, the production of fissile fuel, the laser efficiency and pellet gain requirements of the hybrid reactor. Lawrence Livermore Laboratory (LLL) has collaborated with Bechtel Corporation and with Westinghouse in two engineering design studies of laser fusion driven hybrid power plants. The hybrid designs which have resulted from these two studies are briefly described and analyzed by considering operational parameters, such as energy multiplication, power density, burn-up and plutonium production as a function time

  19. Promoting Student Autonomy and Competence Using a Hybrid Model for Teaching Physical Activity

    Directory of Open Access Journals (Sweden)

    Christine Bachman

    2015-01-01

    Full Text Available For approximately twenty-years, Web-enhanced learning environments have been popular in higher education. Much research has examined how best practices can integrate technology, pedagogical theories, and resources to enhance learning. Numerous studies of hybrid teaching have revealed mostly positive effects. Yet, very little research has examined how to teach a successful physical activity course using a hybrid format. Review of the literature: We reviewed the research regarding the design and implementation of a Web-enhanced physical activity course in a college population using pedagogical principles of learning and the10 self-determination theory. Method: Data were collected from students at the beginning and end of the course. The hybrid course consisted of completing weekly online activities, and selecting and participating in a face-to-face physical activity based on student’s choice. Conclusion: The authors propose this template as a model to assist faculty in designing and implementing a blended physical activity course.

  20. Hybrid Cemetery Culture

    DEFF Research Database (Denmark)

    Sabra, Jakob Borrits; Andersen, Hans Jørgen; Rodil, Kasper

    2016-01-01

    , using a contemporary Danish urban cemetery as case. It discusses a number of emerging digital platforms for mourning, heritage and online remembrance that influence the use of the urban cemetery today, and show the potentials of learning and experience from tethering burial sites with augmented mobile...

  1. Hybrid Optical Inference Machines

    Science.gov (United States)

    1991-09-27

    with labels. Now, events. a set of facts cal be generated in the dyadic form "u, R 1,2" Eichmann and Caulfield (19] consider the same type of and can...these enceding-schemes. These architectures are-based pri- 19. G. Eichmann and H. J. Caulfield, "Optical Learning (Inference)marily on optical inner

  2. Hybrid Natural Inflation

    Science.gov (United States)

    Ross, Graham G.; Germán, Gabriel; Vázquez, J. Alberto

    2016-05-01

    We construct two simple effective field theory versions of Hybrid Natural Inflation (HNI) that illustrate the range of its phenomenological implications. The resulting inflationary sector potential, V = Δ4(1 + acos( ϕ/f)), arises naturally, with the inflaton field a pseudo-Nambu-Goldstone boson. The end of inflation is triggered by a waterfall field and the conditions for this to happen are determined. Also of interest is the fact that the slow-roll parameter ɛ (and hence the tensor r) is a non-monotonic function of the field with a maximum where observables take universal values that determines the maximum possible tensor to scalar ratio r. In one of the models the inflationary scale can be as low as the electroweak scale. We explore in detail the associated HNI phenomenology, taking account of the constraints from Black Hole production, and perform a detailed fit to the Planck 2015 temperature and polarisation data.

  3. Hybrid Natural Inflation

    International Nuclear Information System (INIS)

    Ross, Graham G.; Germán, Gabriel; Vázquez, J. Alberto

    2016-01-01

    We construct two simple effective field theory versions of Hybrid Natural Inflation (HNI) that illustrate the range of its phenomenological implications. The resulting inflationary sector potential, V=Δ"4(1+acos (ϕ/f)), arises naturally, with the inflaton field a pseudo-Nambu-Goldstone boson. The end of inflation is triggered by a waterfall field and the conditions for this to happen are determined. Also of interest is the fact that the slow-roll parameter ϵ (and hence the tensor r) is a non-monotonic function of the field with a maximum where observables take universal values that determines the maximum possible tensor to scalar ratio r. In one of the models the inflationary scale can be as low as the electroweak scale. We explore in detail the associated HNI phenomenology, taking account of the constraints from Black Hole production, and perform a detailed fit to the Planck 2015 temperature and polarisation data.

  4. Hybrid powertrain system

    Science.gov (United States)

    Grillo, Ricardo C.; O'Neil, Walter K.; Preston, David M.

    2005-09-20

    A hybrid powertrain system is provided that includes a first prime mover having a rotational output, a second prime mover having a rotational output, and a transmission having a main shaft supporting at least two main shaft gears thereon. The transmission includes a first independent countershaft drivingly connected to the first prime mover and including at least one ratio gear supported thereon that meshes with a respective main shaft gear. A second independent countershaft is drivingly connected to the second prime mover and includes at least one ratio gear supported thereon that meshes with a respective main shaft gear. The ratio gears on the first and second countershafts cooperate with the main shaft gears to provide at least one gear ratio between the first and second countershafts and the main shaft. A shift control mechanism selectively engages and disengages the first and second countershafts for rotation with the main shaft.

  5. Hybrid vehicle control

    Science.gov (United States)

    Shallvari, Iva; Velnati, Sashidhar; DeGroot, Kenneth P.

    2015-07-28

    A method and apparatus for heating a catalytic converter's catalyst to an efficient operating temperature in a hybrid electric vehicle when the vehicle is in a charge limited mode such as e.g., the charge depleting mode or when the vehicle's high voltage battery is otherwise charge limited. The method and apparatus determine whether a high voltage battery of the vehicle is incapable of accepting a first amount of charge associated with a first procedure to warm-up the catalyst. If it is determined that the high voltage battery is incapable of accepting the first amount of charge, a second procedure with an acceptable amount of charge is performed to warm-up the catalyst.

  6. Hyper- and hybrid nonlocality

    Science.gov (United States)

    Li, Yanna; Gessner, Manuel; Li, Weidong; Smerzi, Augusto

    2018-02-01

    The controlled generation and identification of quantum correlations, usually encoded in either qubits or continuous degrees of freedom, builds the foundation of quantum information science. Recently, more sophisticated approaches, involving a combination of two distinct degrees of freedom, have been proposed to improve on the traditional strategies. Hyperentanglement describes simultaneous entanglement in more than one distinct degree of freedom, whereas hybrid entanglement refers to entanglement shared between a discrete and a continuous degree of freedom. In this work we propose a scheme that allows us to combine the two approaches, and to extend them to the strongest form of quantum correlations. Specifically, we show how two identical, initially separated particles can be manipulated to produce Bell nonlocality among their spins, among their momenta, as well as across their spins and momenta. We discuss possible experimental realizations with atomic and photonic systems.

  7. Hybrid Electric Transit Bus

    Science.gov (United States)

    Viterna, Larry A.

    1997-01-01

    A government, industry, and university cooperative is developing an advanced hybrid electric city transit bus. Goals of this effort include doubling the fuel economy compared to current buses and reducing emissions to one-tenth of current EPA standards. Unique aspects of the vehicle's power system include the use of ultra-capacitors as an energy storage system, and a planned natural gas fueled turbogenerator developed from a small jet engine. Power from both the generator and energy storage system is provided to a variable speed electric motor attached to the rear axle. At over 15000 kg gross weight, this is the largest vehicle of its kind ever built using ultra-capacitor energy storage. This paper describes the overall power system architecture, the evolution of the control strategy, and its performance over industry standard drive cycles.

  8. Hybrid Magnetic Shielding

    Science.gov (United States)

    Royal, Kevin; Crawford, Christopher; Mullins, Andrew; Porter, Greg; Blanton, Hunter; Johnstone, Connor; Kistler, Ben; Olivera, Daniela

    2017-09-01

    The search for the electric dipole moment of the neutron requires the ambient magnetic field to be on the pT scale which is accomplished with large magnetic shielding rooms. These rooms are fitted with large mu-metal sheets to allow for passive cancellation of background magnetic fields. Active shielding technology cannot uniformly cancel background magnetic fields. These issues can be remedied by combining the methods into a hybrid system. The design used is composed of panels that have an active layer of cancellation between two sheets of mu-metal. The panels form a cube and draw in magnetic fields perpendicular to the surface which can then be reduced using active shielding. This work is supported by the Department of Energy under Contract DE-SC0008107.

  9. A Hybrid Imagination

    DEFF Research Database (Denmark)

    Jamison, Andrew; Christensen, Steen Hyldgaard; Botin, Lars

    “hubris” that is so much taken for granted in contemporary science and engineering discourses and practices with a sense of cooperation and social responsibility. The book portrays the history of science and technology as an underlying tension between hubris – literally the ambition to “play god...... an alternative approach, devoting special attention to the role played by social and cultural movements in the making of science and technology. They show how social and cultural movements, from the Renaissance of the late 15th century to the environmental and global justice movements of our time, have provided......” on the part of many a scientist and engineer and neglect the consequences - and a hybrid imagination, connecting scientific “facts” and technological “artifacts” with cultural understanding. The book concludes with chapters on the recent transformations in the modes of scientific and technological production...

  10. Hybrid Action Systems

    DEFF Research Database (Denmark)

    Rönnkö, M.; Ravn, Anders Peter; Sere, K.

    2003-01-01

    In this paper we investigate the use of action systems with differential actions in the specifcation of hybrid systems. As the main contribution we generalize the definition of a differential action, allowing the use of arbitrary relations over model variables and their time......-derivatives in modelling continuous-time dynamics. The generalized differential action has an intuitively appealing predicate transformer semantics, which we show to be both conjunctive and monotonic. In addition, we show that differential actions blend smoothly with conventional actions in action systems, even under...... parallel composition. Moreover, as the strength of the action system formalism is the support for stepwise development by refinement, we investigate refinement involving a differential action. We show that, due to the predicate transformer semantics, standard action refinement techniques apply also...

  11. Nanoporous hybrid electrolytes

    KAUST Repository

    Schaefer, Jennifer L.

    2011-01-01

    Oligomer-suspended SiO2-polyethylene glycol nanoparticles are studied as porous media electrolytes. At SiO2 volume fractions, , bracketing a critical value y ≈ 0.29, the suspensions jam and their mechanical modulus increase by more than seven orders. For >y, the mean pore diameter is close to the anion size, yet the ionic conductivity remains surprisingly high and can be understood, at all , using a simple effective medium model proposed by Maxwell. SiO 2-polyethylene glycol hybrid electrolytes are also reported to manifest attractive electrochemical stability windows (0.3-6.3 V) and to reach a steady-state interfacial impedance when in contact with metallic lithium. © 2010 The Royal Society of Chemistry.

  12. Hybrid Filter Membrane

    Science.gov (United States)

    Laicer, Castro; Rasimick, Brian; Green, Zachary

    2012-01-01

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

  13. Spacecraft Hybrid (Mixed-Actuator) Attitude Control Experiences on NASA Science Missions

    Science.gov (United States)

    Dennehy, Cornelius J.

    2014-01-01

    There is a heightened interest within NASA for the design, development, and flight implementation of mixed-actuator hybrid attitude control systems for science spacecraft that have less than three functional reaction wheel actuators. This interest is driven by a number of recent reaction wheel failures on aging, but what could be still scientifically productive, NASA spacecraft if a successful hybrid attitude control mode can be implemented. Over the years, hybrid (mixed-actuator) control has been employed for contingency attitude control purposes on several NASA science mission spacecraft. This paper provides a historical perspective of NASA's previous engineering work on spacecraft mixed-actuator hybrid control approaches. An update of the current situation will also be provided emphasizing why NASA is now so interested in hybrid control. The results of the NASA Spacecraft Hybrid Attitude Control Workshop, held in April of 2013, will be highlighted. In particular, the lessons learned captured from that workshop will be shared in this paper. An update on the most recent experiences with hybrid control on the Kepler spacecraft will also be provided. This paper will close with some future considerations for hybrid spacecraft control.

  14. Hybrid Simulation in Teaching Clinical Breast Examination to Medical Students.

    Science.gov (United States)

    Nassif, Joseph; Sleiman, Abdul-Karim; Nassar, Anwar H; Naamani, Sima; Sharara-Chami, Rana

    2017-10-10

    Clinical breast examination (CBE) is traditionally taught to third-year medical students using a lecture and a tabletop breast model. The opportunity to clinically practice CBE depends on patient availability and willingness to be examined by students, especially in culturally sensitive environments. We propose the use of a hybrid simulation model consisting of a standardized patient (SP) wearing a silicone breast simulator jacket and hypothesize that this, compared to traditional teaching methods, would result in improved learning. Consenting third-year medical students (N = 82) at a university-affiliated tertiary care center were cluster-randomized into two groups: hybrid simulation (breast jacket + SP) and control (tabletop breast model). Students received the standard lecture by instructors blinded to the randomization, followed by randomization group-based learning and practice sessions. Two weeks later, participants were assessed in an Objective Structured Clinical Examination (OSCE), which included three stations with SPs blinded to the intervention. The SPs graded the students on CBE completeness, and students completed a self-assessment of their performance and confidence during the examination. CBE completeness scores did not differ between the two groups (p = 0.889). Hybrid simulation improved lesion identification grades (p simulation relieved the fear of missing a lesion on CBE (p = 0.043) and increased satisfaction with the teaching method among students (p = 0.002). As a novel educational tool, hybrid simulation improves the sensitivity of CBE performed by medical students without affecting its specificity. Hybrid simulation may play a role in increasing the confidence of medical students during CBE.

  15. Hybrid computing - Generalities and bibliography

    International Nuclear Information System (INIS)

    Neel, Daniele

    1970-01-01

    This note presents the content of a research thesis. It describes the evolution of hybrid computing systems, discusses the benefits and shortcomings of analogue or hybrid systems, discusses the building up of an hybrid system (requires properties), comments different possible uses, addresses the issues of language and programming, discusses analysis methods and scopes of application. An appendix proposes a bibliography on these issues and notably the different scopes of application (simulation, fluid dynamics, biology, chemistry, electronics, energy, errors, space, programming languages, hardware, mechanics, and optimisation of equations or processes, physics) [fr

  16. Research of a hybrid undulator

    International Nuclear Information System (INIS)

    Ma Youwu; Wu Bing; Liu Bo

    1995-12-01

    A 1.5 m tapered hybrid undulator has been designed and built for mid-infrared free electron laser experiments at CIAE. The undulator utilizes the REC-steel hybrid configuration. The magnetic gap and magnetic field taper can be continuously adjusted. The rms error of the peak field is less than 0.53%. The electron trajectory deviation is around 0.03 mm. The design of undulator, sorting of magnets in hybrid undulator using simulated annealing technique, the motion of electron beam in the ideal and measured magnetic field, magnetic field measurement technique and magnetic field adjustment are described. (6 refs., 10 figs., 1 tab)

  17. Interspecific Hybridization within Ornamental Plants

    DEFF Research Database (Denmark)

    Kuligowska, Katarzyna

    commercially important genera of ornamental plants: Kalanchoë and Hibiscus. The nature of hybridization barriers hampering hybrid production was investigated during pre- and post-fertilization stages. For each genus the interspecific crosses of Kalanchoë species and Hibiscus species, abnormal germination...... and growth of pollen tubes, as well as lower frequencies of pollen tubes were observed in specific cross-combinations. Post-fertilization barriers related to endosperm development and hybrid incompatibility were also observed in Kalanchoë and Hibiscus genus, respectively. Qualitative and quantitative...

  18. Triplex in-situ hybridization

    Science.gov (United States)

    Fresco, Jacques R.; Johnson, Marion D.

    2002-01-01

    Disclosed are methods for detecting in situ the presence of a target sequence in a substantially double-stranded nucleic acid segment, which comprises: a) contacting in situ under conditions suitable for hybridization a substantially double-stranded nucleic acid segment with a detectable third strand, said third strand being capable of hybridizing to at least a portion of the target sequence to form a triple-stranded structure, if said target sequence is present; and b) detecting whether hybridization between the third strand and the target sequence has occured.

  19. Evolution of hybrid defect networks

    International Nuclear Information System (INIS)

    Martins, C. J. A. P.

    2009-01-01

    We apply a recently developed analytic model for the evolution of monopole networks to the case of monopoles attached to one string, usually known as hybrid networks. We discuss scaling solutions for both local and global hybrid networks, and also find an interesting application for the case of vortons. Our quantitative results agree with previous estimates in indicating that the hybrid networks will usually annihilate soon after the string-forming phase transition. However, we also show that in some specific circumstances these networks can survive considerably more than a Hubble time.

  20. Program Hybrid/GDH. Revision

    International Nuclear Information System (INIS)

    Blann, M.; Bisplinghoff, J.

    1975-10-01

    This code is the most recent in a series of codes for doing a-priori pre-equilibrium decay calculations. It has been written to permit the user to exercise many options at time of execution. It will, for example, permit calculation with either Hybrid model or the geometry dependent Hybrid model (GDH). Intranuclear transition rates can be calculated using either a nucleon-nucleon scattering approach (improved over earlier results) or based on the imaginary optical potential. Transition rates based on exciton lifetimes can be selected (as suggested in the Hybrid model formulation) or an average lifetime for each n-exciton configuration may be selected

  1. Compositional Modelling of Stochastic Hybrid Systems

    NARCIS (Netherlands)

    Strubbe, S.N.

    2005-01-01

    In this thesis we present a modelling framework for compositional modelling of stochastic hybrid systems. Hybrid systems consist of a combination of continuous and discrete dynamics. The state space of a hybrid system is hybrid in the sense that it consists of a continuous component and a discrete

  2. Alternative Fuels Data Center: Hybrid Electric Vehicles

    Science.gov (United States)

    . A wide variety of hybrid electric vehicle models is currently available. Although HEVs are often -go traffic), further improving fuel economy. Mild hybrid systems cannot power the vehicle using Hybrid Electric Vehicles to someone by E-mail Share Alternative Fuels Data Center: Hybrid Electric

  3. Hybrid Electric Vehicle Testing | Transportation Research | NREL

    Science.gov (United States)

    Hybrid Electric Vehicle Evaluations Hybrid Electric Vehicle Evaluations How Hybrid Electric Vehicles Work Hybrid electric vehicles combine a primary power source, an energy storage system, and an is used to propel the vehicle during normal drive cycles. The batteries supply additional power for

  4. Hybrid Electric Vehicle Publications | Transportation Research | NREL

    Science.gov (United States)

    Hybrid Electric Vehicle Publications Hybrid Electric Vehicle Publications The following technical papers, conference papers, and fact sheets provide information about NREL's hybrid electric fleet vehicle Class 8 Hybrid Electric Delivery Trucks. Mike Lammert. (2011) FedEx Delivery Trucks In-Use and Vehicle

  5. Hybridization and management of oak populations

    Science.gov (United States)

    Oliver Gailing

    2017-01-01

    Hybridization can result in the transfer of adaptations among species and may contribute to speciation processes. On the other hand, hybridization can also result in a loss of species diversity due to asymmetric gene flow between species (genetic swamping) and in low hybrid fitness. An understanding of the outcomes of interspecific hybridization is crucial for the...

  6. Retrieval practice with short-answer, multiple-choice, and hybrid tests.

    Science.gov (United States)

    Smith, Megan A; Karpicke, Jeffrey D

    2014-01-01

    Retrieval practice improves meaningful learning, and the most frequent way of implementing retrieval practice in classrooms is to have students answer questions. In four experiments (N=372) we investigated the effects of different question formats on learning. Students read educational texts and practised retrieval by answering short-answer, multiple-choice, or hybrid questions. In hybrid conditions students first attempted to recall answers in short-answer format, then identified answers in multiple-choice format. We measured learning 1 week later using a final assessment with two types of questions: those that could be answered by recalling information verbatim from the texts and those that required inferences. Practising retrieval in all format conditions enhanced retention, relative to a study-only control condition, on both verbatim and inference questions. However, there were little or no advantages of answering short-answer or hybrid format questions over multiple-choice questions in three experiments. In Experiment 4, when retrieval success was improved under initial short-answer conditions, there was an advantage of answering short-answer or hybrid questions over multiple-choice questions. The results challenge the simple conclusion that short-answer questions always produce the best learning, due to increased retrieval effort or difficulty, and demonstrate the importance of retrieval success for retrieval-based learning activities.

  7. Learning Problems

    Science.gov (United States)

    ... Staying Safe Videos for Educators Search English Español Learning Problems KidsHealth / For Kids / Learning Problems What's in ... for how to make it better. What Are Learning Disabilities? Learning disabilities aren't contagious, but they ...

  8. HYBRIDIZATION AND CHAMELEONIC JOURNALISM

    Directory of Open Access Journals (Sweden)

    Adriana Schryver Kurtz

    2016-12-01

    Full Text Available O texto aborda a crescente hibridização entre o Jornalismo e demais formatos midiáticos como resultado natural de um processo que já está na própria raiz da comunicação enquanto atividade histórica. A lógica interna e as potencialidades estéticas e discursivas do fenômeno são analisadas a partir das convergências entre jornalismo e cinema. Para tanto, utiliza o falso documentário Zelig (1983, texto fílmico de Woody Allen, híbrido por natureza, postulado como um microcosmo rico em pistas e sugestões para refletir sobre a fusão entre conteúdos informativos e não informativos.   PALAVRAS-CHAVE: Hibridização; Jornalismo; Cinema; Zelig.       ABSTRACT The text discusses the growing hybridization between journalism and other media formats as a natural result of a process that is already in the very root of communication while historical activity. The internal logic and the aesthetic and discursive potential of the phenomenon are analyzed through the convergences between journalism and cinema. Therefore, uses the mockumentary Zelig (1983, filmic text of Woody Allen, hybrid by nature, postulated as a microcosm rich in clues and suggestions to reflect about the merger between informative and uninformative content.      KEYWORDS: Hybridization; Journalism; Cinema; Zelig.     RESUMEN El texto aborda la creciente hibridación entre el periodismo y otros formatos de medios como um resultado natural de un proceso que ya está en la raíz misma de la comunicación mientras actividad histórica. Se analizan la lógica interna y el potencial estético y discursivo del fenómeno a través de las convergencias entre el periodismo y el cine. Para ello, utiliza el falso documental Zelig (1983, texto fílmico de Woody Allen, híbrido en su naturaleza, postulado como un microcosmos rico en pistas y sugerencias para reflexionar sobre la fusión entre contenidos informativos y no informativos.      PALABRAS CLAVE: Hibridaci

  9. Hybrid Experiential-Heuristic Cognitive Radio Engine Architecture and Implementation

    Directory of Open Access Journals (Sweden)

    Ashwin Amanna

    2012-01-01

    Full Text Available The concept of cognitive radio (CR focuses on devices that can sense their environment, adapt configuration parameters, and learn from past behaviors. Architectures tend towards simplified decision-making algorithms inspired by human cognition. Initial works defined cognitive engines (CEs founded on heuristics, such as genetic algorithms (GAs, and case-based reasoning (CBR experiential learning algorithms. This hybrid architecture enables both long-term learning, faster decisions based on past experience, and capability to still adapt to new environments. This paper details an autonomous implementation of a hybrid CBR-GA CE architecture on a universal serial radio peripheral (USRP software-defined radio focused on link adaptation. Details include overall process flow, case base structure/retrieval method, estimation approach within the GA, and hardware-software lessons learned. Unique solutions to realizing the concept include mechanisms for combining vector distance and past fitness into an aggregate quantification of similarity. Over-the-air performance under several interference conditions is measured using signal-to-noise ratio, packet error rate, spectral efficiency, and throughput as observable metrics. Results indicate that the CE is successfully able to autonomously change transmit power, modulation/coding, and packet size to maintain the link while a non-cognitive approach loses connectivity. Solutions to existing shortcomings are proposed for improving case-base searching and performance estimation methods.

  10. Optical Properties of Hybrid Nanomaterials

    Indian Academy of Sciences (India)

    owner

    K. George Thomas. Photosciences & Photonics Group. National Institute for Interdisciplinary. Science and Technology (NIIST), CSIR,. Trivandrum- 695 019, INDIA. (kgt@vsnl.com). Optical Properties of Hybrid. Nanomaterials ...

  11. Hybrid-Vehicle Transmission System

    Science.gov (United States)

    Lupo, G.; Dotti, G.

    1985-01-01

    Continuously-variable transmission system for hybrid vehicles couples internal-combustion engine and electric motor section, either individually or in parallel, to power vehicle wheels during steering and braking.

  12. MTU hybrid powerpack for railcars

    Energy Technology Data Exchange (ETDEWEB)

    Lehmann, Ingo; Schmalzing, Claus-Oliver [MTU Friedrichshafen GmbH (Germany); Werner, Claus [DB RegioNetz Verkehrs GmbH (Germany); Bold, Uwe [DB Systemtechnik Engineering Kassel (Germany)

    2011-11-15

    Up to 25 percent lower fuel consumption and emission-free train movements in station areas are possible with the MTU hybrid drive system. First field tests on tracks of the Deutsche Bahn started in autumn 2011. (orig.)

  13. 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....

  14. Epigenomics: dissecting hybridization and polyploidization.

    Science.gov (United States)

    Jackson, Scott A

    2017-06-19

    Epigenetic profiling in diploid, allopolyploid, and domesticated cotton shows that despite most DNA methylation being conserved and stably inherited, alterations likely due to hybridization and domestication affect gene expression.

  15. Real and Hybrid Atomic Orbitals.

    Science.gov (United States)

    Cook, D. B.; Fowler, P. W.

    1981-01-01

    Demonstrates that the Schrodinger equation for the hydrogenlike atom separates in both spheroconal and prolate spheroidal coordinates and that these separations provide a sound theoretical basis for the real and hybrid atomic orbitals. (Author/SK)

  16. 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.

  17. Hybrid mask for deep etching

    KAUST Repository

    Ghoneim, Mohamed T.

    2017-01-01

    Deep reactive ion etching is essential for creating high aspect ratio micro-structures for microelectromechanical systems, sensors and actuators, and emerging flexible electronics. A novel hybrid dual soft/hard mask bilayer may be deposited during

  18. Hybrid Fuel Cell Technology Overview

    Energy Technology Data Exchange (ETDEWEB)

    None available

    2001-05-31

    For the purpose of this STI product and unless otherwise stated, hybrid fuel cell systems are power generation systems in which a high temperature fuel cell is combined with another power generating technology. The resulting system exhibits a synergism in which the combination performs with an efficiency far greater than can be provided by either system alone. Hybrid fuel cell designs under development include fuel cell with gas turbine, fuel cell with reciprocating (piston) engine, and designs that combine different fuel cell technologies. Hybrid systems have been extensively analyzed and studied over the past five years by the Department of Energy (DOE), industry, and others. These efforts have revealed that this combination is capable of providing remarkably high efficiencies. This attribute, combined with an inherent low level of pollutant emission, suggests that hybrid systems are likely to serve as the next generation of advanced power generation systems.

  19. Nitrous Paraffin Hybrid, Phase I

    Data.gov (United States)

    National Aeronautics and Space Administration — The Nitrous Oxide Paraffin Hybrid engine (N2OP) is a proposed technology designed to provide small launch vehicles with high specific impulse, indefinitely storable...

  20. Hybrid Materials for Molecular Sieves

    NARCIS (Netherlands)

    ten Elshof, Johan E.; Klein, Lisa; Aparicio, Mario; Jitianu, Andrei

    2016-01-01

    Hybrid microporous organosilica membranes for molecular separations made by acid-catalyzed solgel synthesis from bridged silsesquioxane precursors have demonstrated good performance in terms of flux and selectivity and remarkable hydrothermal stability in various pervaporation and gas separation

  1. Hybrid quantum-classical master equations

    International Nuclear Information System (INIS)

    Diósi, Lajos

    2014-01-01

    We discuss hybrid master equations of composite systems, which are hybrids of classical and quantum subsystems. A fairly general form of hybrid master equations is suggested. Its consistency is derived from the consistency of Lindblad quantum master equations. We emphasize that quantum measurement is a natural example of exact hybrid systems. We derive a heuristic hybrid master equation of time-continuous position measurement (monitoring). (paper)

  2. Hybrid particles and associated methods

    Science.gov (United States)

    Fox, Robert V; Rodriguez, Rene; Pak, Joshua J; Sun, Chivin

    2015-02-10

    Hybrid particles that comprise a coating surrounding a chalcopyrite material, the coating comprising a metal, a semiconductive material, or a polymer; a core comprising a chalcopyrite material and a shell comprising a functionalized chalcopyrite material, the shell enveloping the core; or a reaction product of a chalcopyrite material and at least one of a reagent, heat, and radiation. Methods of forming the hybrid particles are also disclosed.

  3. Hybrid spacecraft attitude control system

    OpenAIRE

    Renuganth Varatharajoo; Ramly Ajir; Tamizi Ahmad

    2016-01-01

    The hybrid subsystem design could be an attractive approach for futurespacecraft to cope with their demands. The idea of combining theconventional Attitude Control System and the Electrical Power System ispresented in this article. The Combined Energy and Attitude ControlSystem (CEACS) consisting of a double counter rotating flywheel assemblyis investigated for small satellites in this article. Another hybrid systemincorporating the conventional Attitude Control System into the ThermalControl...

  4. 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...

  5. 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...

  6. Hybrid spacecraft attitude control system

    Directory of Open Access Journals (Sweden)

    Renuganth Varatharajoo

    2016-02-01

    Full Text Available The hybrid subsystem design could be an attractive approach for futurespacecraft to cope with their demands. The idea of combining theconventional Attitude Control System and the Electrical Power System ispresented in this article. The Combined Energy and Attitude ControlSystem (CEACS consisting of a double counter rotating flywheel assemblyis investigated for small satellites in this article. Another hybrid systemincorporating the conventional Attitude Control System into the ThermalControl System forming the Combined Attitude and Thermal ControlSystem (CATCS consisting of a "fluid wheel" and permanent magnets isalso investigated for small satellites herein. The governing equationsdescribing both these novel hybrid subsystems are presented and theironboard architectures are numerically tested. Both the investigated novelhybrid spacecraft subsystems comply with the reference missionrequirements.The hybrid subsystem design could be an attractive approach for futurespacecraft to cope with their demands. The idea of combining theconventional Attitude Control System and the Electrical Power System ispresented in this article. The Combined Energy and Attitude ControlSystem (CEACS consisting of a double counter rotating flywheel assemblyis investigated for small satellites in this article. Another hybrid systemincorporating the conventional Attitude Control System into the ThermalControl System forming the Combined Attitude and Thermal ControlSystem (CATCS consisting of a "fluid wheel" and permanent magnets isalso investigated for small satellites herein. The governing equationsdescribing both these novel hybrid subsystems are presented and theironboard architectures are numerically tested. Both the investigated novelhybrid spacecraft subsystems comply with the reference missionrequirements.

  7. Optimal control of hybrid vehicles

    CERN Document Server

    Jager, Bram; Kessels, John

    2013-01-01

    Optimal Control of Hybrid Vehicles provides a description of power train control for hybrid vehicles. The background, environmental motivation and control challenges associated with hybrid vehicles are introduced. The text includes mathematical models for all relevant components in the hybrid power train. The power split problem in hybrid power trains is formally described and several numerical solutions detailed, including dynamic programming and a novel solution for state-constrained optimal control problems based on Pontryagin’s maximum principle.   Real-time-implementable strategies that can approximate the optimal solution closely are dealt with in depth. Several approaches are discussed and compared, including a state-of-the-art strategy which is adaptive for vehicle conditions like velocity and mass. Two case studies are included in the book: ·        a control strategy for a micro-hybrid power train; and ·        experimental results obtained with a real-time strategy implemented in...

  8. Linkages between motivation, self-efficacy, self-regulated learning and preferences for traditional learning environments or those with an online component

    Directory of Open Access Journals (Sweden)

    Daniel Auld

    2010-10-01

    Full Text Available This study assessed 96 law school students’ preferences for online, hybrid, or traditional learning environments, and their reasons for these preferences, learning strategies, and motivational orientations. A discriminant analysis revealed that non-traditional learning environment familiarity, self-efficacy, and employment status were the strongest predictors of preferences for non-traditional learning environments. Preferences for traditional environments were attributed to students’ familiarity and ability to engage in and foster personal interaction. Preferences for hybrid and online environments were attributed to opportunities for enhanced learning given the convenience and flexible manner in which students with time and familial constraints could access these environments.

  9. Hybrid power source

    Science.gov (United States)

    Singh, Harmohan N.

    2012-06-05

    A hybrid power system is comprised of a high energy density element such as a fuel-cell and high power density elements such as a supercapacitor banks. A DC/DC converter electrically connected to the fuel cell and converting the energy level of the energy supplied by the fuel cell. A first switch is electrically connected to the DC/DC converter. First and second supercapacitors are electrically connected to the first switch and a second switch. A controller is connected to the first switch and the second switch, monitoring charge levels of the supercapacitors and controls the switching in response to the charge levels. A load is electrically connected to the second switch. The first switch connects the DC/DC converter to the first supercapacitor when the second switch connects the second supercapacitor to the load. The first switch connects the DC/DC converter to the second supercapacitor when the second switch connects the first supercapacitor to the load.

  10. Protaper--hybrid technique.

    Science.gov (United States)

    Simon, Stephane; Lumley, Philip; Tomson, Phillip; Pertot, Wilhelm-Joseph; Machtou, Pierre

    2008-03-01

    Crown down preparation is the most known and described technique since the introduction of Nickel Titanium (NiTi) rotary instruments in endodontics. This technique gives good results but has limitations, such as not addressing the initial anatomy of oval or dumb-bell shaped canals. The specific design of the Protaper instruments allows use of them with a different technique and, specifically, with a brushing motion in the body of the canal. The recent introduction of hand Protaper files has expanded the range of application of this system, especially in curved canals. The 'hybrid technique', using rotary and hand files, and the advantages of the combination of both instruments, are clearly described in this article. Used with this technique, the Protaper is a very safe system to use, and more controllable, for both inexperienced and experienced practitioners alike, than other systems. To understand the precautions needed with rotary files, and how to use them to preserve the anatomy of the canal and get a tapered shaping, even in severely curved canals.

  11. Comparative genomic hybridization.

    Science.gov (United States)

    Pinkel, Daniel; Albertson, Donna G

    2005-01-01

    Altering DNA copy number is one of the many ways that gene expression and function may be modified. Some variations are found among normal individuals ( 14, 35, 103 ), others occur in the course of normal processes in some species ( 33 ), and still others participate in causing various disease states. For example, many defects in human development are due to gains and losses of chromosomes and chromosomal segments that occur prior to or shortly after fertilization, whereas DNA dosage alterations that occur in somatic cells are frequent contributors to cancer. Detecting these aberrations, and interpreting them within the context of broader knowledge, facilitates identification of critical genes and pathways involved in biological processes and diseases, and provides clinically relevant information. Over the past several years array comparative genomic hybridization (array CGH) has demonstrated its value for analyzing DNA copy number variations. In this review we discuss the state of the art of array CGH and its applications in medical genetics and cancer, emphasizing general concepts rather than specific results.

  12. Hybrid vehicle assessment. Phase I. Petroleum savings analysis

    Energy Technology Data Exchange (ETDEWEB)

    Levin, R.; Liddle, S.; Deshpande, G.; Trummel, M.; Vivian, H.

    1984-03-01

    This report presents the results of a comprehensive analysis of near-term electric-hybrid vehicles. Its purpose was to estimate their potential to save significant amounts of petroleum on a national scale in the 1990s. Performance requirements and expected annual usage patterns of these vehicles were first modeled. The projected US fleet composition was estimated, and conceptual hybrid vehicle designs were conceived and analyzed for petroleum use when driven in the expected annual patterns. These petroleum consumption estimates were then compared to similar estimates for projected 1990 conventional vehicles having the same performance and driven in the same patterns. Results are presented in the form of three utility functions and comparisons of several conceptual designs are made. The Hybrid Vehicle (HV) design and assessment techniques are discussed and a general method is explained for selecting the optimum energy management strategy for any vehicle-mission-battery combination. A discussion of lessons learned during the construction and test of the General Electric Hybrid Test Vehicle is also presented. Conclusions and recommendations are presented, and development recommendations are identified.

  13. Hybrid simulation using mixed reality for interventional ultrasound imaging training.

    Science.gov (United States)

    Freschi, C; Parrini, S; Dinelli, N; Ferrari, M; Ferrari, V

    2015-07-01

    Ultrasound (US) imaging offers advantages over other imaging modalities and has become the most widespread modality for many diagnostic and interventional procedures. However, traditional 2D US requires a long training period, especially to learn how to manipulate the probe. A hybrid interactive system based on mixed reality was designed, implemented and tested for hand-eye coordination training in diagnostic and interventional US. A hybrid simulator was developed integrating a physical US phantom and a software application with a 3D virtual scene. In this scene, a 3D model of the probe with its relative scan plane is coherently displayed with a 3D representation of the phantom internal structures. An evaluation study of the diagnostic module was performed by recruiting thirty-six novices and four experts. The performances of the hybrid (HG) versus physical (PG) simulator were compared. After the training session, each novice was required to visualize a particular target structure. The four experts completed a 5-point Likert scale questionnaire. Seventy-eight percentage of the HG novices successfully visualized the target structure, whereas only 45% of the PG reached this goal. The mean scores from the questionnaires were 5.00 for usefulness, 4.25 for ease of use, 4.75 for 3D perception, and 3.25 for phantom realism. The hybrid US training simulator provides ease of use and is effective as a hand-eye coordination teaching tool. Mixed reality can improve US probe manipulation training.

  14. 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.

  15. Learning about Learning

    Science.gov (United States)

    Siegler, Robert S.

    2004-01-01

    The field of children's learning was thriving when the Merrill-Palmer Quarterly was launched; the field later went into eclipse and now is in the midst of a resurgence. This commentary examines reasons for these trends, and describes the emerging field of children's learning. In particular, the new field is seen as differing from the old in its…

  16. Learning to Learn Differently

    Science.gov (United States)

    Olsen, Trude Høgvold; Glad, Tone; Filstad, Cathrine

    2018-01-01

    Purpose: This paper aims to investigate whether the formal and informal learning patterns of community health-care nurses changed in the wake of a reform that altered their work by introducing new patient groups, and to explore whether conditions in the new workplaces facilitated or impeded shifts in learning patterns. Design/methodology/approach:…

  17. Hybrid Arrays for Chemical Sensing

    Science.gov (United States)

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

    In recent years, multisensory approaches to environment monitoring for chemical detection as well as other forms of situational awareness have become increasingly popular. A hybrid sensor is a multimodal system that incorporates several sensing elements and thus produces data that are multivariate in nature and may be significantly increased in complexity compared to data provided by single-sensor systems. Though a hybrid sensor is itself an array, hybrid sensors are often organized into more complex sensing systems through an assortment of network topologies. Part of the reason for the shift to hybrid sensors is due to advancements in sensor technology and computational power available for processing larger amounts of data. There is also ample evidence to support the claim that a multivariate analytical approach is generally superior to univariate measurements because it provides additional redundant and complementary information (Hall, D. L.; Linas, J., Eds., Handbook of Multisensor Data Fusion, CRC, Boca Raton, FL, 2001). However, the benefits of a multisensory approach are not automatically achieved. Interpretation of data from hybrid arrays of sensors requires the analyst to develop an application-specific methodology to optimally fuse the disparate sources of data generated by the hybrid array into useful information characterizing the sample or environment being observed. Consequently, multivariate data analysis techniques such as those employed in the field of chemometrics have become more important in analyzing sensor array data. Depending on the nature of the acquired data, a number of chemometric algorithms may prove useful in the analysis and interpretation of data from hybrid sensor arrays. It is important to note, however, that the challenges posed by the analysis of hybrid sensor array data are not unique to the field of chemical sensing. Applications in electrical and process engineering, remote sensing, medicine, and of course, artificial

  18. Hybrid platform. Economical hybrid drive for commercial vehicles; Hybrid Plattform. Wirtschaftlicher Hybridantrieb fuer Nutzfahrzeuge

    Energy Technology Data Exchange (ETDEWEB)

    Wallner, S.; Lamke, M.; Mohr, M.; Sedlacek, M.; Speck, F.D. [ZF Friedrichshafen AG, Friedrichshafen (Germany)

    2011-07-01

    Up to now, hybrid systems have been adapted to their specific requirements in the various applications for trucks, buses as well as mobile and building machines. From a technical point of view, this does indeed result in optimized hybrid drives for each single vehicle application, but due to small volumes, such single developments are critical from a business point of view. ZF Friedrichshafen AG is providing a solution to the technical and economical requirements of the cost-sensitive CV segment in the form of a modular CV parallel hybrid platform composed of a hybrid module system, an inverter, a battery system, and a hybrid software integrated into the overall vehicle. Thanks to the intelligent combination of assemblies and the use of as many identical parts as possible, platforms are realized which cover power ranges between 60 and 120 kW, voltage ranges between 350 and 650 V, and battery capacities between 2 and 4 kWh. The dimensions of the platform elements are such that integration into the diverse commercial vehicle applications is made easy. The hybrid software required for the vehicle-specific functions is also configurable for the mentioned CV applications. (orig.)

  19. A Blended Learning Approach to Teaching Project Management: A Model for Active Participation and Involvement--Insights from Norway

    Science.gov (United States)

    Hussein, Bassam A.

    2015-01-01

    The paper demonstrates and evaluates the effectiveness of a blended learning approach to create a meaningful learning environment. We use the term blended learning approach in this paper to refer to the use of multiple or hybrid instructional methods that emphasize the role of learners as contributors to the learning process rather than recipients…

  20. Reconfiguration of photovoltaic panels for reducing the hydrogen consumption in fuel cells of hybrid systems

    Directory of Open Access Journals (Sweden)

    Daniel González-Montoya

    2017-05-01

    Full Text Available Hybrid generation combines advantages from fuel cell systems with non-predictable generation approaches, such as photovoltaic and wind generators. In such hybrid systems, it is desirable to minimize as much as possible the fuel consumption, for the sake of reducing costs and increasing the system autonomy. This paper proposes an optimization algorithm, referred to as population-based incremental learning, in order to maximize the produced power of a photovoltaic generator. This maximization reduces the fuel consumption in the hybrid aggregation. Moreover, the algorithm's speed enables the real-time computation of the best configuration for the photovoltaic system, which also optimizes the fuel consumption in the complementary fuel cell system. Finally, a system experimental validation is presented considering 6 photovoltaic modules and a NEXA 1.2KW fuel cell. Such a validation demonstrates the effectiveness of the proposed algorithm to reduce the hydrogen consumption in these hybrid systems.

  1. Probabilistic Wind Power Forecasting with Hybrid Artificial Neural Networks

    DEFF Research Database (Denmark)

    Wan, Can; Song, Yonghua; Xu, Zhao

    2016-01-01

    probabilities of prediction errors provide an alternative yet effective solution. This article proposes a hybrid artificial neural network approach to generate prediction intervals of wind power. An extreme learning machine is applied to conduct point prediction of wind power and estimate model uncertainties...... via a bootstrap technique. Subsequently, the maximum likelihood estimation method is employed to construct a distinct neural network to estimate the noise variance of forecasting results. The proposed approach has been tested on multi-step forecasting of high-resolution (10-min) wind power using...... actual wind power data from Denmark. The numerical results demonstrate that the proposed hybrid artificial neural network approach is effective and efficient for probabilistic forecasting of wind power and has high potential in practical applications....

  2. Learning Mixtures of Polynomials of Conditional Densities from Data

    DEFF Research Database (Denmark)

    L. López-Cruz, Pedro; Nielsen, Thomas Dyhre; Bielza, Concha

    2013-01-01

    Mixtures of polynomials (MoPs) are a non-parametric density estimation technique for hybrid Bayesian networks with continuous and discrete variables. We propose two methods for learning MoP ap- proximations of conditional densities from data. Both approaches are based on learning MoP approximatio...

  3. The Integration of Psychomotor Skills in a Hybrid-PBL Dental Curriculum: The Clinical Clerkships.

    Science.gov (United States)

    Walton, Joanne N.; MacNeil, M. A. J.; Harrison, Rosamund L.; Clark, D. Christopher

    1998-01-01

    Describes the restructuring of clinical clerkships at the University of British Columbia (Canada) dental school as part of a new, hybrid, problem-based learning (PBL) curriculum, focusing on strategies for integrating development of psychomotor skills. Methods of achieving both horizontal and vertical integration of competencies through grouping…

  4. Understanding New Hybrid Professions: Bourdieu, "Illusio" and the Case of Public Service Interpreters

    Science.gov (United States)

    Colley, Helen; Guéry, Frédérique

    2015-01-01

    Public spending reductions across the advanced capitalist world are creating new professions that have a "hybrid" status and/or role. However, research on professional learning has paid little attention to them. This qualitative study of one such profession, public service interpreting (PSI), addresses that lacuna. The paper focuses on…

  5. Mechanical and thermal design of hybrid blankets

    International Nuclear Information System (INIS)

    Schultz, K.R.

    1978-01-01

    The thermal and mechanical aspects of hybrid reactor blanket design considerations are discussed. This paper is intended as a companion to that of J. D. Lee of Lawrence Livermore Laboratory on the nuclear aspects of hybrid reactor blanket design. The major design characteristics of hybrid reactor blankets are discussed with emphasis on the areas of difference between hybrid reactors and standard fusion or fission reactors. Specific examples are used to illustrate the design tradeoffs and choices that must be made in hybrid reactor design. These examples are drawn from the work on the Mirror Hybrid Reactor

  6. Hybrid pine for tough sites

    International Nuclear Information System (INIS)

    Davidson, W.H.

    1994-01-01

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

  7. Case for the fusion hybrid

    International Nuclear Information System (INIS)

    Rose, R.P.

    1981-01-01

    The use of nuclear fusion to produce fuel for nuclear fission power stations is discussed in the context of a crucial need for future energy options. The fusion hybrid is first considered as an element in the future of nuclear fission power to provide long term assurance of adequate fuel supplies for both breeder and convertor reactors. Generic differences in neutronic characteristics lead to a fuel production potential of fusion-fission hybrid systems which is significantly greater than that obtainable with fission systems alone. Furthermore, cost benefit studies show a variety of scenarios in which the hybrid offers sufficient potential to justify development costs ranging in the tens of billions of dollars. The hybrid is then considered as an element in the ultimate development of fusion electric power. The hybrid offers a near term application of fusion where experience with the requisite technologies can be derived as a vital step in mapping a credible route to eventual commercial feasibility of pure fusion systems. Finally, the criteria for assessment of future energy options are discussed with prime emphasis on the need for rational comparision of alternatives

  8. Hybridity and complexity

    DEFF Research Database (Denmark)

    Lønsmann, Dorte; Haberland, Hartmut

    2013-01-01

    -speaking but multilingual in practice. The book assesses the factors common to successful bilingual learners, and provides university administrators, policy makers and teachers around the world with a much-needed commentary on the challenges they face in increasingly multilingual surroundings characterized......Reflecting the increased use of English as lingua franca in today’s university education, this volume maps the interplay and competition between English and other tongues in a learning community that in practice is not only bilingual but multilingual. The volume includes case studies from Japan......, Australia, South Africa, Germany, Catalonia, China, Denmark and Sweden, analysing a range of issues such as the conflict between the students’ native languages and English, the reality of parallel teaching in English as well as in the local language, and classrooms that are nominally English...

  9. Machine learning for evolution strategies

    CERN Document Server

    Kramer, Oliver

    2016-01-01

    This book introduces numerous algorithmic hybridizations between both worlds that show how machine learning can improve and support evolution strategies. The set of methods comprises covariance matrix estimation, meta-modeling of fitness and constraint functions, dimensionality reduction for search and visualization of high-dimensional optimization processes, and clustering-based niching. After giving an introduction to evolution strategies and machine learning, the book builds the bridge between both worlds with an algorithmic and experimental perspective. Experiments mostly employ a (1+1)-ES and are implemented in Python using the machine learning library scikit-learn. The examples are conducted on typical benchmark problems illustrating algorithmic concepts and their experimental behavior. The book closes with a discussion of related lines of research.

  10. Genetic Learning Particle Swarm Optimization.

    Science.gov (United States)

    Gong, Yue-Jiao; Li, Jing-Jing; Zhou, Yicong; Li, Yun; Chung, Henry Shu-Hung; Shi, Yu-Hui; Zhang, Jun

    2016-10-01

    Social learning in particle swarm optimization (PSO) helps collective efficiency, whereas individual reproduction in genetic algorithm (GA) facilitates global effectiveness. This observation recently leads to hybridizing PSO with GA for performance enhancement. However, existing work uses a mechanistic parallel superposition and research has shown that construction of superior exemplars in PSO is more effective. Hence, this paper first develops a new framework so as to organically hybridize PSO with another optimization technique for "learning." This leads to a generalized "learning PSO" paradigm, the *L-PSO. The paradigm is composed of two cascading layers, the first for exemplar generation and the second for particle updates as per a normal PSO algorithm. Using genetic evolution to breed promising exemplars for PSO, a specific novel *L-PSO algorithm is proposed in the paper, termed genetic learning PSO (GL-PSO). In particular, genetic operators are used to generate exemplars from which particles learn and, in turn, historical search information of particles provides guidance to the evolution of the exemplars. By performing crossover, mutation, and selection on the historical information of particles, the constructed exemplars are not only well diversified, but also high qualified. Under such guidance, the global search ability and search efficiency of PSO are both enhanced. The proposed GL-PSO is tested on 42 benchmark functions widely adopted in the literature. Experimental results verify the effectiveness, efficiency, robustness, and scalability of the GL-PSO.

  11. Collaborative distance learning: Developing an online learning community

    Science.gov (United States)

    Stoytcheva, Maria

    2017-12-01

    The method of collaborative distance learning has been applied for years in a number of distance learning courses, but they are relatively few in foreign language learning. The context of this research is a hybrid distance learning of French for specific purposes, delivered through the platform UNIV-RcT (Strasbourg University), which combines collaborative activities for the realization of a common problem-solving task online. The study focuses on a couple of aspects: on-line interactions carried out in small, tutored groups and the process of community building online. By analyzing the learner's perceptions of community and collaborative learning, we have tried to understand the process of building and maintenance of online learning community and to see to what extent the collaborative distance learning contribute to the development of the competence expectations at the end of the course. The analysis of the results allows us to distinguish the advantages and limitations of this type of e-learning and thus evaluate their pertinence.

  12. Beyond the Didactic Classroom: Educational Models to Encourage Active Student Involvement in Learning

    OpenAIRE

    Shreeve, Michael W.

    2008-01-01

    In a chiropractic college that utilizes a hybrid curriculum model composed of adult-based learning strategies along with traditional lecture-based course delivery, a literature search for educational delivery methods that would integrate the affective domain and the cognitive domain of learning provided some insights into the use of problem-based learning (PBL), experiential learning theory (ELT), and the emerging use of appreciative inquiry (AI) to enhance the learning experience. The purpos...

  13. Experimental study of hybrid-knife endoscopic submucosal dissection (ESD) versus standard ESD in a Western country.

    Science.gov (United States)

    De-la-Peña, Joaquín; Calderón, Ángel; Esteban, José Miguel; López-Rosés, Leopoldo; Martínez-Ares, David; Nogales, Óscar; Orive-Calzada, Aitor; Rodríguez, Sarbelio; Sánchez-Hernández, Eloy; Vila, Juan; Fernández-Esparrach, Gloria

    2014-02-01

    Endoscopic submucosal dissection (ESD) is an effective but time-consuming treatment for early neoplasia that requires a high level of expertise. The objective of this study was to assess the efficacy and learning curve of gastric ESD with a hybrid knife with high pressure water jet and to compare with standard ESD. We performed a prospective non survival animal study comparing hybrid-knife and standard gastric ESD. Variables recorded were: Number of en-bloc ESD, number of ESD with all marks included (R0), size of specimens, time and speed of dissection and adverse events. Ten endoscopists performed a total of 50 gastric ESD (30 hybrid-knife and 20 standard). Forty-six (92 %) ESD were en-bloc and 25 (50 %) R0 (hybrid-knife: n = 13, 44 %; standard: n = 16, 80 %; p = 0.04). Hybrid-knife ESD was faster than standard (time: 44.6 +/- 21.4 minutes vs. 68.7 +/- 33.5 minutes; p = 0.009 and velocity: 20.8 +/- 9.2 mm(2)/min vs. 14.3 +/- 9.3 mm(2)/min (p = 0.079). Adverse events were not different. There was no change in speed with any of two techniques (hybrid-knife: From 20.33 +/- 15.68 to 28.18 +/- 20.07 mm(2)/min; p = 0.615 and standard: From 6.4 +/- 0.3 to 19.48 +/- 19.21 mm(2)/min; p = 0.607). The learning curve showed a significant improvement in R0 rate in the hybrid-knife group (from 30 % to 100 %). despite the initial performance of hybrid-knife ESD is worse than standard ESD, the learning curve with hybrid knife ESD is short and is associated with a rapid improvement. The introduction of new tools to facilitate ESD should be implemented with caution in order to avoid a negative impact on the results.

  14. 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

  15. Hybrid magnets at Tohoku University

    International Nuclear Information System (INIS)

    Muto, Yoshio; Nakagawa, Yasuaki; Noto, Koshichi; Hoshi, Akira; Miura, Shigeto; Watanabe, Kazuo; Kido, Giyuu

    1984-01-01

    The High Field Laboratory for Superconducting Materials was established in April 1981 at Tohoku University in order to provide research facilities for the development of superconducting materials suitable for superconducting magnets for the plasma confinement in fusion reactors. Main facilities of this laboratory are three hybrid magnets up to 30 Tesla dc magnetic fields with inner bores from 32 to 52mm in diameter. The magnets consist of superconducting outer solenoids and water-cooled inner ones with a maximum steady power dissipation of 8 MW. The design and construction of these three hybrid magnets have finished in last three years, and two of them (HM-3;20T, 32 mm bore and HM-2; 23T, 52 mm bore) have already opened to scientists and engineers in the superconductivity and other fields. The rated field of the third hybrid magnet (HM-1) is 31 (or 29) Tesla in a bore of 32 (or 52) mm in diameter. By this hybrid system we have succeeded to produce 29.3 Tesla on April 21, 1984. Detailed descriptions are presented on the superconducting magnets, power supplies and cooling systems for them, water-cooled magnets, dc-high power source and water-cooled system for them, the monitoring and control system for the hybrid magnets including a super-minicomputer system, a hard-wired interlock system for the safety of human beings and machines, and so on. The fourth hybrid magnet system which aims at 35 Tesla as the next phase is also discussed. (author)

  16. 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

  17. 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....

  18. Reverse hybrid total hip arthroplasty

    DEFF Research Database (Denmark)

    Wangen, Helge; Havelin, Leif I.; Fenstad, Anne M

    2017-01-01

    Background and purpose - The use of a cemented cup together with an uncemented stem in total hip arthroplasty (THA) has become popular in Norway and Sweden during the last decade. The results of this prosthetic concept, reverse hybrid THA, have been sparsely described. The Nordic Arthroplasty....... Patients and methods - From the NARA, we extracted data on reverse hybrid THAs from January 1, 2000 until December 31, 2013. 38,415 such hips were studied and compared with cemented THAs. The Kaplan-Meier method and Cox regression analyses were used to estimate the prosthesis survival and the relative risk...

  19. Hard electroproduction of hybrid mesons

    International Nuclear Information System (INIS)

    Anikin, I.V.; LPT Universite Paris-Sud, Orsay; Szymanowski, L.; Teryaev, O.V.; ); Wallon, S.

    2005-01-01

    We estimate the sizeable cross section for deep exclusive electroproduction of an exotic J PC = 1 -+ hybrid meson in the Bjorken regime. The production amplitude scales like the one for usual meson electroproduction, i.e. as 1/Q 2 . This is due to the non-vanishing leading twist distribution amplitude for the hybrid meson, which may be normalized thanks to its relation to the energy momentum tensor and to the QCD sum rules technique. The hard amplitude is considered up to next-to-leading order in as and we explore the consequences of fixing the renormalization scale ambiguity through the BLM procedure. (author)

  20. Inference in hybrid Bayesian networks

    International Nuclear Information System (INIS)

    Langseth, Helge; Nielsen, Thomas D.; Rumi, Rafael; Salmeron, Antonio

    2009-01-01

    Since the 1980s, Bayesian networks (BNs) have become increasingly popular for building statistical models of complex systems. This is particularly true for boolean systems, where BNs often prove to be a more efficient modelling framework than traditional reliability techniques (like fault trees and reliability block diagrams). However, limitations in the BNs' calculation engine have prevented BNs from becoming equally popular for domains containing mixtures of both discrete and continuous variables (the so-called hybrid domains). In this paper we focus on these difficulties, and summarize some of the last decade's research on inference in hybrid Bayesian networks. The discussions are linked to an example model for estimating human reliability.

  1. Hybrid Magnetics and Power Applications

    DEFF Research Database (Denmark)

    Mo, Wai Keung; Paasch, Kasper

    2017-01-01

    A hybrid magnetic approach, merging two different magnetic core properites such as ferrite and iron powder cores, is an effective solution for power converter applications. It can offer similar magnetic properties to that of magnetic powder cores but showing less copper loss than powder cores....... In order to prevent ferrite core saturation, placing an effective air gap within the ferrite core is a key method to obtain optimum hybrid magnetic performance. Furthermore, a relatively large inductance at low loading current is an excellent way to minimze power loss in order to achieve high efficiency...

  2. Essentialism, hybridism and cultural critique

    DEFF Research Database (Denmark)

    Frello, Birgitta

    2007-01-01

    to social and cultural critique. Through a critical discussion of the concept of hybridity, I argue that rather than expecting to find definite emancipating or suppressing capacities connected to constructions of the ‘hybrid' and the ‘pure', we should focus on how these two poles are invested with meaning...... and related to power. Hence, while insisting on Cultural Studies' commitment to social and cultural critique, I argue that this critique would benefit from an analytical sensitivity towards the uses and abuses of the discursive power to designate meaningful and legitimate subject positions, rather than...

  3. Hybrid Simulation of Composite Structures

    DEFF Research Database (Denmark)

    Høgh, Jacob Herold

    experiment. The technique has primarily been used within earthquake engineering but many other fields of engineering have utilized the method with benefit. However, these previous efforts have focused on structures with a simple boundary between the numerical and physical substructure i.e. few degrees...... the transfer system and the control and monitoring techniques in the shared boundary is therefore a key issue in this type of hybrid simulation. During the research, hybrid simulation platforms have been programmed capable of running on different time scales with advanced control and monitoring techniques...

  4. Rocket to Creativity: A Field Experience in Problem-Based and Project-Based Learning

    Science.gov (United States)

    Dole, Sharon F.; Bloom, Lisa A.; Doss, Kristy Kowalske

    2016-01-01

    This article reports the impact of a field experience in problem-based (PBL) and project-based learning (PjBL) on in-service teachers' conceptions of experiential learning. Participants had been enrolled in a hybrid class that included an online component in which they learned about PBL and PjBL, and an experiential component in which they…

  5. Can Learning Style Predict Student Satisfaction with Different Instruction Methods and Academic Achievement in Medical Education?

    Science.gov (United States)

    Gurpinar, Erol; Alimoglu, Mustafa Kemal; Mamakli, Sumer; Aktekin, Mehmet

    2010-01-01

    The curriculum of our medical school has a hybrid structure including both traditional training (lectures) and problem-based learning (PBL) applications. The purpose of this study was to determine the learning styles of our medical students and investigate the relation of learning styles with each of satisfaction with different instruction methods…

  6. From hybrid-media system to hybrid-media politicians

    DEFF Research Database (Denmark)

    Blach-Ørsten, Mark; Eberholst, Mads Kæmsgaard; Burkal, Rasmus

    2017-01-01

    ’ media use is changing rapidly; 15%–16% of Danish candidates used Twitter in 2011 but 68% in 2015. In this large-sample content analysis, party leaders have high traditional-news-media and low Twitter presence, and younger candidates visa-versa, but some politicians have high presence in both. Hybrid...

  7. Field errors in hybrid insertion devices

    International Nuclear Information System (INIS)

    Schlueter, R.D.

    1995-02-01

    Hybrid magnet theory as applied to the error analyses used in the design of Advanced Light Source (ALS) insertion devices is reviewed. Sources of field errors in hybrid insertion devices are discussed

  8. Field errors in hybrid insertion devices

    Energy Technology Data Exchange (ETDEWEB)

    Schlueter, R.D. [Lawrence Berkeley Lab., CA (United States)

    1995-02-01

    Hybrid magnet theory as applied to the error analyses used in the design of Advanced Light Source (ALS) insertion devices is reviewed. Sources of field errors in hybrid insertion devices are discussed.

  9. Distance Learning

    National Research Council Canada - National Science Library

    Braddock, Joseph

    1997-01-01

    A study reviewing the existing Army Distance Learning Plan (ADLP) and current Distance Learning practices, with a focus on the Army's training and educational challenges and the benefits of applying Distance Learning techniques...

  10. Microlearning mApp raises health competence: hybrid service design.

    Science.gov (United States)

    Simons, Luuk P A; Foerster, Florian; Bruck, Peter A; Motiwalla, Luvai; Jonker, Catholijn M

    Work place health support interventions can help support our aging work force, with mApps offering cost-effectiveness opportunities. Previous research shows that health support apps should offer users enough newness and relevance each time they are used. Otherwise the 'eHealth law of attrition' applies: 90 % of users are lost prematurely. Our research study builds on this prior research with further investigation on whether a mobile health quiz provides added value for users within a hybrid service mix and whether it promotes long term health? We developed a hybrid health support intervention solution that uses a mix of electronic and physical support services for improving health behaviours, including a mobile micro-learning health quiz. This solution was evaluated in a multiple-case study at three work sites with 86 users. We find that both our mobile health quiz and the overall hybrid solution contributed to improvements in health readiness, -behaviour and -competence. Users indicated that the micro-learning health quiz courses provided new and relevant information. Relatively high utilization rates of the health quiz were observed. Participants indicated that health insights were given that directly influenced every day health perceptions, -choices, coping and goal achievement strategies, plus motivation and self-norms. This points to increased user health self-management competence. Moreover, even after 10 months they indicated to still have improved health awareness, -motivation and -behaviours (food, physical activity, mental recuperation). A design analysis was conducted regarding service mix efficacy; the mobile micro-learning health quiz helped fulfil a set of key requirements that exist for designing ICT-enabled lifestyle interventions, largely in the way it was anticipated.

  11. ADVANCED HYBRID PARTICULATE COLLECTOR

    Energy Technology Data Exchange (ETDEWEB)

    Ye Zhuang; Stanley J. Miller; Michelle R. Olderbak; Rich Gebert

    2001-12-01

    A new concept in particulate control, called an advanced hybrid particulate collector (AHPC), is being developed under funding from the U.S. Department of Energy. The AHPC combines the best features of electrostatic precipitators (ESPs) and baghouses in an entirely novel manner. The AHPC concept combines fabric filtration and electrostatic precipitation in the same housing, providing major synergism between the two methods, both in the particulate collection step and in transfer of dust to the hopper. The AHPC provides ultrahigh collection efficiency, overcoming the problem of excessive fine-particle emissions with conventional ESPs, and solves the problem of reentrainment and re-collection of dust in conventional baghouses. Phase I of the development effort consisted of design, construction, and testing of a 5.7-m{sup 3}/min (200-acfm) working AHPC model. Results from both 8-hr parametric tests and 100-hr proof-of-concept tests with two different coals demonstrated excellent operability and greater than 99.99% fine-particle collection efficiency. Since all of the developmental goals of Phase I were met, the approach was scaled up in Phase II to a size of 255 m{sup 3}/min (9000 acfm) (equivalent in size to 2.5 MW) and was installed on a slipstream at the Big Stone Power Plant. For Phase II, the AHPC at Big Stone Power Plant was operated continuously from late July 1999 until mid-December 1999. The Phase II results were highly successful in that ultrahigh particle collection efficiency was achieved, pressure drop was well controlled, and system operability was excellent. For Phase III, the AHPC was modified into a more compact configuration, and components were installed that were closer to what would be used in a full-scale commercial design. The modified AHPC was operated from April to July 2000. While operational results were acceptable during this time, inspection of bags in the summer of 2000 revealed some membrane damage to the fabric that appeared to be

  12. Constructing decidable hybrid systems with velocity bounds

    NARCIS (Netherlands)

    Belta, C.; Habets, L.C.G.J.M.

    2004-01-01

    In this paper, the question of bi-similarity between hybrid systems and their discrete quotients is studied from a new point of view. We consider two classes of hybrid systems: piecewise affine hybrid systems on simplices and piecewise multi-affine systems on multi-dimensional rectangles. Given a

  13. Deriving simulators for hybrid Chi models

    NARCIS (Netherlands)

    Beek, van D.A.; Man, K.L.; Reniers, M.A.; Rooda, J.E.; Schiffelers, R.R.H.

    2006-01-01

    The hybrid Chi language is formalism for modeling, simulation and verification of hybrid systems. The formal semantics of hybrid Chi allows the definition of provably correct implementations for simulation, verification and realtime control. This paper discusses the principles of deriving an

  14. Hybrid Doctoral Program: Innovative Practices and Partnerships

    Science.gov (United States)

    Alvich, Dori; Manning, JoAnn; McCormick, Kathy; Campbell, Robert

    2012-01-01

    This paper reflects on how one mid-Atlantic University innovatively incorporated technology into the development of a hybrid doctoral program in educational leadership. The paper describes a hybrid doctoral degree program using a rigorous design; challenges of reworking a traditional syllabus of record to a hybrid doctoral program; the perceptions…

  15. Internal combustion engines in hybrid vehicles

    NARCIS (Netherlands)

    Mourad, S.; Weijer, C.J.T. van de; Beckman, D.E.

    1998-01-01

    In this paper the use of internal combustion engines in hybrid powertrains is investigated. The substantial difference between the use of internal combustion engines in conventional and in hybrid vehicles mean that engines for hybrid vehicles should be designed specifically for the purpose. At the

  16. 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...

  17. 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…

  18. Hybrid synchronization of hyperchaotic Lu system

    Indian Academy of Sciences (India)

    In this paper, we study the hybrid synchronization between two identical hyperchaotic Lu systems. Hybrid synchronization of hyperchaotic Lu system is achieved through synchronization of two pairs of states and anti-synchronization of the other two pairs of states. Active controls are designed to achieve hybrid ...

  19. Detecting Urban Transport Modes Using a Hybrid Knowledge Driven Framework from GPS Trajectory

    Directory of Open Access Journals (Sweden)

    Rahul Deb Das

    2016-11-01

    Full Text Available Transport mode information is essential for understanding people’s movement behavior and travel demand estimation. Current approaches extract travel information once the travel is complete. Such approaches are limited in terms of generating just-in-time information for a number of mobility based applications, e.g., real time mode specific patronage estimation. In order to detect the transport modalities from GPS trajectories, various machine learning approaches have already been explored. However, the majority of them produce only a single conclusion from a given set of evidences, ignoring the uncertainty of any mode classification. Also, the existing machine learning approaches fall short in explaining their reasoning scheme. In contrast, a fuzzy expert system can explain its reasoning scheme in a human readable format along with a provision of inferring different outcome possibilities, but lacks the adaptivity and learning ability of machine learning. In this paper, a novel hybrid knowledge driven framework is developed by integrating a fuzzy logic and a neural network to complement each other’s limitations. Thus the aim of this paper is to automate the tuning process in order to generate an intelligent hybrid model that can perform effectively in near-real time mode detection using GPS trajectory. Tests demonstrate that a hybrid knowledge driven model works better than a purely knowledge driven model and at per the machine learning models in the context of transport mode detection.

  20. Sharing e-Learning Experiences: A Personalised Approach

    Science.gov (United States)

    Clematis, Andrea; Forcheri, Paola; Ierardi, Maria Grazia; Quarati, Alfonso

    A two-tier architecture is presented, based on hybrid peer-to-peer technology, aimed at providing personalized access to heterogeneous learning sources. The architecture deploys a conceptual model that is superimposed over logically and physically separated repositories. The model is based on the interactions between users and learning resources, described by means of coments. To support users to find out material satisfying their needs, mechanisms for ranking resources and for extracting personalized views of the learning space are provided.

  1. Formal Description of Hybrid Systems

    DEFF Research Database (Denmark)

    Zhou, Chaochen; Ji, Wang; Ravn, Anders P.

    1996-01-01

    A language to describe hybrid systems, i.e. networks of communicating discrete and continuous processes, is proposed. A semantics of the language is given in Extended Duration Calculus, a real-time interval logic with a proof system that allows reasoning in mathematical analysis about continuous ...

  2. Hybrid mesons with auxiliary fields

    International Nuclear Information System (INIS)

    Buisseret, F.; Mathieu, V.

    2006-01-01

    Hybrid mesons are exotic mesons in which the color field is not in the ground state. Their understanding deserves interest from a theoretical point of view, because it is intimately related to nonperturbative aspects of QCD. Moreover, it seems that some recently detected particles, such as the π 1 (1600) and the Y(4260), are serious hybrid candidates. In this work, we investigate the description of such exotic hadrons by applying the auxiliary fields technique (also known as the einbein field method) to the widely used spinless Salpeter Hamiltonian with appropriate linear confinement. Instead of the usual numerical resolution, this technique allows to find simplified analytical mass spectra and wave functions of the Hamiltonian, which still lead to reliable qualitative predictions. We analyse and compare two different descriptions of hybrid mesons, namely a two-body q system with an excited flux tube, or a three-body qg system. We also compute the masses of the 1 -+ hybrids. Our results are shown to be in satisfactory agreement with lattice QCD and other effective models. (orig.)

  3. The threat of hybrid Phytophthoras

    Science.gov (United States)

    The majority of invasive plant pathogens have resulted from the introduction of exotic organisms. However, another mechanism for invasiveness results from hybridization between species. This phenomenon has been documented in plants and animals, but its role in plant pathology has only recently been ...

  4. 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

  5. Inference in hybrid Bayesian networks

    DEFF Research Database (Denmark)

    Lanseth, Helge; Nielsen, Thomas Dyhre; Rumí, Rafael

    2009-01-01

    Since the 1980s, Bayesian Networks (BNs) have become increasingly popular for building statistical models of complex systems. This is particularly true for boolean systems, where BNs often prove to be a more efficient modelling framework than traditional reliability-techniques (like fault trees...... decade's research on inference in hybrid Bayesian networks. The discussions are linked to an example model for estimating human reliability....

  6. Towards Modelling of Hybrid Systems

    DEFF Research Database (Denmark)

    Wisniewski, Rafal

    2006-01-01

    system consists of a number of dynamical systems that are glued together according to information encoded in the discrete part of the system. We develop a definition of a hybrid system as a functor from the category generated by a transition system to the category of directed topological spaces. Its...

  7. Transgressive Hybrids as Hopeful Monsters.

    Science.gov (United States)

    Dittrich-Reed, Dylan R; Fitzpatrick, Benjamin M

    2013-06-01

    The origin of novelty is a critical subject for evolutionary biologists. Early geneticists speculated about the sudden appearance of new species via special macromutations, epitomized by Goldschmidt's infamous "hopeful monster". Although these ideas were easily dismissed by the insights of the Modern Synthesis, a lingering fascination with the possibility of sudden, dramatic change has persisted. Recent work on hybridization and gene exchange suggests an underappreciated mechanism for the sudden appearance of evolutionary novelty that is entirely consistent with the principles of modern population genetics. Genetic recombination in hybrids can produce transgressive phenotypes, "monstrous" phenotypes beyond the range of parental populations. Transgressive phenotypes can be products of epistatic interactions or additive effects of multiple recombined loci. We compare several epistatic and additive models of transgressive segregation in hybrids and find that they are special cases of a general, classic quantitative genetic model. The Dobzhansky-Muller model predicts "hopeless" monsters, sterile and inviable transgressive phenotypes. The Bateson model predicts "hopeful" monsters with fitness greater than either parental population. The complementation model predicts both. Transgressive segregation after hybridization can rapidly produce novel phenotypes by recombining multiple loci simultaneously. Admixed populations will also produce many similar recombinant phenotypes at the same time, increasing the probability that recombinant "hopeful monsters" will establish true-breeding evolutionary lineages. Recombination is not the only (or even most common) process generating evolutionary novelty, but might be the most credible mechanism for sudden appearance of new forms.

  8. Hybrid winding concept for toroids

    DEFF Research Database (Denmark)

    Schneider, Henrik; Andersen, Thomas; Knott, Arnold

    2013-01-01

    and placement machinery. This opens up the possibility for both an automated manufacturing process and an automated production process of toroidal magnetics such as power inductors, filtering inductors, air core inductors, transformers etc. Both the proposed hybrid and the common wire wound winding...

  9. 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.)

  10. Sugar pine and its hybrids

    Science.gov (United States)

    W. B. Critchfield; B. B. Kinloch

    1986-01-01

    Unlike most white pines, sugar pine (Pinus lambertiana) is severely restricted in its ability to hybridize with other species. It has not been successfully crossed with any other North American white pine, nor with those Eurasian white pines it most closely resembles. Crosses with the dissimilar P. koraiensis and P....

  11. Organic and hybrid solar cells

    CERN Document Server

    Huang, Hui

    2014-01-01

    This book delivers a comprehensive evaluation of organic and hybrid solar cells and identifies their fundamental principles and numerous applications. Great attention is given to the charge transport mechanism, donor and acceptor materials, interfacial materials, alternative electrodes, device engineering and physics, and device stability. The authors provide an industrial perspective on the future of photovoltaic technologies.

  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. Information transmission on hybrid networks

    Science.gov (United States)

    Chen, Rongbin; Cui, Wei; Pu, Cunlai; Li, Jie; Ji, Bo; Gakis, Konstantinos; Pardalos, Panos M.

    2018-01-01

    Many real-world communication networks often have hybrid nature with both fixed nodes and moving modes, such as the mobile phone networks mainly composed of fixed base stations and mobile phones. In this paper, we discuss the information transmission process on the hybrid networks with both fixed and mobile nodes. The fixed nodes (base stations) are connected as a spatial lattice on the plane forming the information-carrying backbone, while the mobile nodes (users), which are the sources and destinations of information packets, connect to their current nearest fixed nodes respectively to deliver and receive information packets. We observe the phase transition of traffic load in the hybrid network when the packet generation rate goes from below and then above a critical value, which measures the network capacity of packets delivery. We obtain the optimal speed of moving nodes leading to the maximum network capacity. We further improve the network capacity by rewiring the fixed nodes and by considering the current load of fixed nodes during packets transmission. Our purpose is to optimize the network capacity of hybrid networks from the perspective of network science, and provide some insights for the construction of future communication infrastructures.

  14. SYSTEM APPROACH TO THE BLENDED LEARNING

    Directory of Open Access Journals (Sweden)

    Vladimir Kukharenko

    2015-10-01

    Full Text Available Currently, much attention is paid to the development of learning sour cream – a combination of traditional and distance (30-70% of training. Such training is sometimes called hybrid and referred to disruptive technologies. Purpose – to show that the use of systemic campaign in blended learning provides a high quality of education, and the technology can be devastating. The subject of the study – blended learning, object of study – Mixed learning process. The analysis results show that the combined training increases the motivation of students, qualification of teachers, personalized learning process. At the same time there are no reliable methods of assessing the quality of education and training standards. It is important that blended learning strategy to support the institutional goals and had an effective organizational model for support.

  15. Designing Learning for Co-Creation

    DEFF Research Database (Denmark)

    Gnaur, Dorina; Larsen-Nielsen, Marie

    2017-01-01

    Designing learning for co-creation - conceptual and practical considerations, Dorina Gnaur and Inger Marie Larsen-Nielsen explore the practical educational point of view. The question they are posing themselves is: how can higher and further education (HE) educate for co-creation, that is, provide...... educational frameworks that respond to the societal demand for co-creation, particularly within the public welfare sector? First, they focus on which organisational and individual requirements an HE learning design should take into account in order to support the diffusion of co-creation competences....... Then they argue for the need to integrate these considerations in the learning design and demonstrate a practical application in the form of a didactical design. They call this a hybrid learning design, in that it takes advantage of technological developments to mediate co-creative learning in multiple learning...

  16. Blended learning

    DEFF Research Database (Denmark)

    Dau, Susanne

    2016-01-01

    Blended Learning has been implemented, evaluated and researched for the last decades within different educational areas and levels. Blended learning has been coupled with different epistemological understandings and learning theories, but the fundamental character and dimensions of learning...... in blended learning are still insufficient. Moreover, blended learning is a misleading concept described as learning, despite the fact that it fundamentally is an instructional and didactic approach (Oliver & Trigwell, 2005) addressing the learning environment (Inglis, Palipoana, Trenhom & Ward, 2011......) instead of the learning processes behind. Much of the existing research within the field seems to miss this perspective. The consequence is a lack of acknowledgement of the driven forces behind the context and the instructional design limiting the knowledge foundation of learning in blended learning. Thus...

  17. Shape Memory Composite Hybrid Hinge

    Science.gov (United States)

    Fang, Houfei; Im, Eastwood; Lin, John; Scarborough, Stephen

    2012-01-01

    There are two conventional types of hinges for in-space deployment applications. The first type is mechanically deploying hinges. A typical mechanically deploying hinge is usually composed of several tens of components. It is complicated, heavy, and bulky. More components imply higher deployment failure probability. Due to the existence of relatively moving components among a mechanically deploying hinge, it unavoidably has microdynamic problems. The second type of conventional hinge relies on strain energy for deployment. A tape-spring hinge is a typical strain energy hinge. A fundamental problem of a strain energy hinge is that its deployment dynamic is uncontrollable. Usually, its deployment is associated with a large impact, which is unacceptable for many space applications. Some damping technologies have been experimented with to reduce the impact, but they increased the risks of an unsuccessful deployment. Coalescing strain energy components with shape memory composite (SMC) components to form a hybrid hinge is the solution. SMCs are well suited for deployable structures. A SMC is created from a high-performance fiber and a shape memory polymer resin. When the resin is heated to above its glass transition temperature, the composite becomes flexible and can be folded or packed. Once cooled to below the glass transition temperature, the composite remains in the packed state. When the structure is ready to be deployed, the SMC component is reheated to above the glass transition temperature, and it returns to its as-fabricated shape. A hybrid hinge is composed of two strain energy flanges (also called tape-springs) and one SMC tube. Two folding lines are placed on the SMC tube to avoid excessive strain on the SMC during folding. Two adapters are used to connect the hybrid hinge to its adjacent structural components. While the SMC tube is heated to above its glass transition temperature, a hybrid hinge can be folded and stays at folded status after the temperature

  18. HybridPLAY: A New Technology to Foster Outdoors Physical Activity, Verbal Communication and Teamwork.

    Science.gov (United States)

    Díaz, Diego José; Boj, Clara; Portalés, Cristina

    2016-04-23

    This paper presents HybridPLAY, a novel technology composed of a sensor and mobile-based video games that transforms urban playgrounds into game scenarios. With this technology we aim to stimulate physical activity and playful learning by creating an entertaining environment in which users can actively participate and collaborate. HybridPLAY is different from other existing technologies that enhance playgrounds, as it is not integrated in them but can be attached to the different elements of the playgrounds, making its use more ubiquitous (i.e., not restricted to the playgrounds). HybridPLAY was born in 2007 as an artistic concept, and evolved after different phases of research and testing by almost 2000 users around the world (in workshops, artistic events, conferences, etc.). Here, we present the temporal evolution of HybridPLAY with the different versions of the sensors and the video games, and a detailed technical description of the sensors and the way interactions are produced. We also present the outcomes after the evaluation by users at different events and workshops. We believe that HybridPLAY has great potential to contribute to increased physical activity in kids, and also to improve the learning process and monitoring at school centres by letting users create the content of the apps, leading to new narratives and fostering creativity.

  19. HybridPLAY: A New Technology to Foster Outdoors Physical Activity, Verbal Communication and Teamwork

    Directory of Open Access Journals (Sweden)

    Diego José Díaz

    2016-04-01

    Full Text Available This paper presents HybridPLAY, a novel technology composed of a sensor and mobile-based video games that transforms urban playgrounds into game scenarios. With this technology we aim to stimulate physical activity and playful learning by creating an entertaining environment in which users can actively participate and collaborate. HybridPLAY is different from other existing technologies that enhance playgrounds, as it is not integrated in them but can be attached to the different elements of the playgrounds, making its use more ubiquitous (i.e., not restricted to the playgrounds. HybridPLAY was born in 2007 as an artistic concept, and evolved after different phases of research and testing by almost 2000 users around the world (in workshops, artistic events, conferences, etc.. Here, we present the temporal evolution of HybridPLAY with the different versions of the sensors and the video games, and a detailed technical description of the sensors and the way interactions are produced. We also present the outcomes after the evaluation by users at different events and workshops. We believe that HybridPLAY has great potential to contribute to increased physical activity in kids, and also to improve the learning process and monitoring at school centres by letting users create the content of the apps, leading to new narratives and fostering creativity.

  20. HybridPLAY: A New Technology to Foster Outdoors Physical Activity, Verbal Communication and Teamwork

    Science.gov (United States)

    Díaz, Diego José; Boj, Clara; Portalés, Cristina

    2016-01-01

    This paper presents HybridPLAY, a novel technology composed of a sensor and mobile-based video games that transforms urban playgrounds into game scenarios. With this technology we aim to stimulate physical activity and playful learning by creating an entertaining environment in which users can actively participate and collaborate. HybridPLAY is different from other existing technologies that enhance playgrounds, as it is not integrated in them but can be attached to the different elements of the playgrounds, making its use more ubiquitous (i.e., not restricted to the playgrounds). HybridPLAY was born in 2007 as an artistic concept, and evolved after different phases of research and testing by almost 2000 users around the world (in workshops, artistic events, conferences, etc.). Here, we present the temporal evolution of HybridPLAY with the different versions of the sensors and the video games, and a detailed technical description of the sensors and the way interactions are produced. We also present the outcomes after the evaluation by users at different events and workshops. We believe that HybridPLAY has great potential to contribute to increased physical activity in kids, and also to improve the learning process and monitoring at school centres by letting users create the content of the apps, leading to new narratives and fostering creativity. PMID:27120601

  1. A hybrid air conditioner driven by a hybrid solar collector

    Science.gov (United States)

    Al-Alili, Ali

    The objective of this thesis is to search for an efficient way of utilizing solar energy in air conditioning applications. The current solar Air Conditioners (A/C)s suffer from low Coefficient of Performance (COP) and performance degradation in hot and humid climates. By investigating the possible ways of utilizing solar energy in air conditioning applications, the bottlenecks in these approaches were identified. That resulted in proposing a novel system whose subsystem synergy led to a COP higher than unity. The proposed system was found to maintain indoor comfort at a higher COP compared to the most common solar A/Cs, especially under very hot and humid climate conditions. The novelty of the proposed A/C is to use a concentrating photovoltaic/thermal collector, which outputs thermal and electrical energy simultaneously, to drive a hybrid A/C. The performance of the hybrid A/C, which consists of a desiccant wheel, an enthalpy wheel, and a vapor compression cycle (VCC), was investigated experimentally. This work also explored the use of a new type of desiccant material, which can be regenerated with a low temperature heat source. The experimental results showed that the hybrid A/C is more effective than the standalone VCC in maintaining the indoor conditions within the comfort zone. Using the experimental data, the COP of the hybrid A/C driven by a hybrid solar collector was found to be at least double that of the current solar A/Cs. The innovative integration of its subsystems allows each subsystem to do what it can do best. That leads to lower energy consumption which helps reduce the peak electrical loads on electric utilities and reduces the consumer operating cost since less energy is purchased during the on peak periods and less solar collector area is needed. In order for the proposed A/C to become a real alternative to conventional systems, its performance and total cost were optimized using the experimentally validated model. The results showed that for an

  2. Overview of hybrid electric vehicle trend

    Science.gov (United States)

    Wang, Haomiao; Yang, Weidong; Chen, Yingshu; Wang, Yun

    2018-04-01

    With the increase of per capita energy consumption, environmental pollution is worsening. Using new alternative sources of energy, reducing the use of conventional fuel-powered engines is imperative. Due to the short period, pure electric vehicles cannot be mass-produced and there are many problems such as imperfect charging facilities. Therefore, the development of hybrid electric vehicles is particularly important in a certain period. In this paper, the classification of hybrid vehicle, research status of hybrid vehicle and future development trends of hybrid vehicles is introduced. It is conducive to the public understanding of hybrid electric vehicles, which has a certain theoretical significance.

  3. Analyse de l'efficacité des stratégies de travail d'étudiants Lansad à distance dans un dispositif hybride – Étape d'une recherche-action Action research to evaluate ESP students' off site working strategies in a blended learning environment – interim report

    Directory of Open Access Journals (Sweden)

    Cédric Brudermann

    2010-05-01

    Full Text Available Cet article se propose de revenir sur la conception et l'utilisation d'un centre de ressources en ligne visant à mettre en œuvre des expériences d'apprentissage (Bange, 1992 potentiellement favorables à l'acquisition de l'anglais langue étrangère, dans un dispositif hybride d'enseignement / apprentissage des langues pour spécialistes d'autres disciplines (désormais Lansad. Une recherche expérimentale menée à l'institut universitaire de formation des maîtres (désormais IUFM de Perpignan auprès d'un public de professeurs des écoles de niveau B1 / B2 au cours de l'année universitaire 2007-2008 a permis de recueillir des données plus précises quant aux besoins des apprenants au cours de la réalisation de tâches écrites et orales à distance. Leur traitement a montré que la plupart des obstacles provenaient d'aspects de la langue anglaise de niveau A2 / B1 qui avaient déjà été travaillés par les apprenants lors de leurs études dans le secondaire. Pour les aider, un "centre de ressources en ligne" fonctionnant d'après leurs besoins en L2 a été conçu (Brudermann, 2008, de façon à leur laisser toute latitude pour se prendre en charge dans un climat sécurisé lors de la réalisation de ces travaux et les conduire à réinvestir leurs acquis dans l'élaboration de tâches ultérieures (Van Harmelen, 2006.This article deals with the implementation of an online database of pedagogical resources in a blended learning device, in order to lead ESP students to a potential improvement of their English as a foreign language knowledge. Action research was carried out in 2007-2008 in a French University (Perpignan amongst B1/B2 teachers-to-be ESP students. The data collected showed that most linguistic obstacles derived from A2/B1 elements they had already been taught during their secondary education. A database of pedagogical resources was set up online to provide students with relevant items and links when needed, whilst

  4. Hybrid LSA-ANN Based Home Energy Management Scheduling Controller for Residential Demand Response Strategy

    Directory of Open Access Journals (Sweden)

    Maytham S. Ahmed

    2016-09-01

    Full Text Available Demand response (DR program can shift peak time load to off-peak time, thereby reducing greenhouse gas emissions and allowing energy conservation. In this study, the home energy management scheduling controller of the residential DR strategy is proposed using the hybrid lightning search algorithm (LSA-based artificial neural network (ANN to predict the optimal ON/OFF status for home appliances. Consequently, the scheduled operation of several appliances is improved in terms of cost savings. In the proposed approach, a set of the most common residential appliances are modeled, and their activation is controlled by the hybrid LSA-ANN based home energy management scheduling controller. Four appliances, namely, air conditioner, water heater, refrigerator, and washing machine (WM, are developed by Matlab/Simulink according to customer preferences and priority of appliances. The ANN controller has to be tuned properly using suitable learning rate value and number of nodes in the hidden layers to schedule the appliances optimally. Given that finding proper ANN tuning parameters is difficult, the LSA optimization is hybridized with ANN to improve the ANN performances by selecting the optimum values of neurons in each hidden layer and learning rate. Therefore, the ON/OFF estimation accuracy by ANN can be improved. Results of the hybrid LSA-ANN are compared with those of hybrid particle swarm optimization (PSO based ANN to validate the developed algorithm. Results show that the hybrid LSA-ANN outperforms the hybrid PSO based ANN. The proposed scheduling algorithm can significantly reduce the peak-hour energy consumption during the DR event by up to 9.7138% considering four appliances per 7-h period.

  5. Generation to generation: discrimination and harassment experiences of physician mothers and their physician daughters.

    Science.gov (United States)

    Shrier, Diane K; Zucker, Alyssa N; Mercurio, Andrea E; Landry, Laura J; Rich, Michael; Shrier, Lydia A

    2007-01-01

    To examine bias and sexual harassment experiences of physician mothers and their physician daughters; correlations of these experiences with career satisfaction, stress at work, stress at home, and percentage of women in specialty; and influences of the mother on her daughter's experiences. A convenience sample of 214 families with mother and daughter physicians was sent a 56-item survey that included questions on bias and sexual harassment experiences. Statistical comparisons were made within 136 dyads where both mother and daughter returned the questionnaire. Eighty-four percent of mothers and 87% of daughters responded. Mothers and daughters reported similarly high rates and severity of sexual harassment before medical school, while in residency/fellowship, while in practice/work setting, and by teachers and supervisors. Daughters reported higher rates of harassment during medical school and by patients, mothers by colleagues. Gender and racial/ethnic discrimination was lower for daughters compared with their mothers, but gender discrimination was still substantial. Compared with other daughters, daughters who experienced discrimination or sexual harassment reported lower career satisfaction and more stress at work and at home and worked in specialties with fewer women. Gender discrimination and sexual harassment remain entrenched in medical education and professional workplaces. Maternal role models and mentors were not as protective as anticipated. Leadership of medical institutions and professional associations must deal more effectively with persistent discrimination and harassment or risk the loss of future leaders.

  6. Revisiting Organisational Learning in Integrated Care.

    Science.gov (United States)

    Nuño-Solinís, Roberto

    2017-08-11

    Progress in health care integration is largely linked to changes in processes and ways of doing. These changes have knowledge management and learning implications. For this reason, the use of the concept of organisational learning is explored in the field of integrated care. There are very limited contributions that have connected the fields of organisational learning and care integration in a systematic way, both at the theoretical and empirical level. For this reason, hybridization of both perspectives still provides opportunities for understanding care integration initiatives from a research perspective as well as potential applications in health care management and planning.

  7. Learning Algorithms for Audio and Video Processing: Independent Component Analysis and Support Vector Machine Based Approaches

    National Research Council Canada - National Science Library

    Qi, Yuan

    2000-01-01

    In this thesis, we propose two new machine learning schemes, a subband-based Independent Component Analysis scheme and a hybrid Independent Component Analysis/Support Vector Machine scheme, and apply...

  8. Neural-network hybrid control for antilock braking systems.

    Science.gov (United States)

    Lin, Chih-Min; Hsu, C F

    2003-01-01

    The antilock braking systems are designed to maximize wheel traction by preventing the wheels from locking during braking, while also maintaining adequate vehicle steerability; however, the performance is often degraded under harsh road conditions. In this paper, a hybrid control system with a recurrent neural network (RNN) observer is developed for antilock braking systems. This hybrid control system is comprised of an ideal controller and a compensation controller. The ideal controller, containing an RNN uncertainty observer, is the principal controller; and the compensation controller is a compensator for the difference between the system uncertainty and the estimated uncertainty. Since for dynamic response the RNN has capabilities superior to the feedforward NN, it is utilized for the uncertainty observer. The Taylor linearization technique is employed to increase the learning ability of the RNN. In addition, the on-line parameter adaptation laws are derived based on a Lyapunov function, so the stability of the system can be guaranteed. Simulations are performed to demonstrate the effectiveness of the proposed NN hybrid control system for antilock braking control under various road conditions.

  9. Surface hardness of hybrid ionomer cement after immersion in antiseptic solution

    Directory of Open Access Journals (Sweden)

    Anita Yuliati

    2006-06-01

    Full Text Available Hybrid ionomer cement or resin modified glass ionomer cement is a developed form of conventional glass ionomer cement. This hybrid ionomer cement can be eroded if in direct contact with acid solution which will affect surface hardness. The aim of this study is to learn surface hardness of hybrid ionomer cement after immersion in methyl salicylate 0.06% (pH 3.6 and povidon iodine 1% (pH 2.9 solution. Sample of hybrid ionomer cement with 5 mm diameter and 3 mm thickness was immersed in sterile aquadest solution (control, methyl salicylate pH 3.6, povidon iodine pH 2.9 for 1 minute, 7 and 14 minutes. Surface hardness was measured with Micro Vickers Hardness Tester. The obtained data was analyzed statistically with ANOVA followed by LSD test. The result of hybrid ionomer cement after immersion in sterile aquadest, methyl salicylate 0.06% pH 3.6 and povidon iodine 1% pH 2.9 for one minute, showed no significant difference; while immersion for 7 and 14 minutes showed a significant difference. The conclusion states that hybrid ionomer cement after 14 minutes immersion in povidon iodine 1% pH 2.9 has the lowest surface hardness.

  10. Gasoline hybrid pneumatic engine for efficient vehicle powertrain hybridization

    OpenAIRE

    Dimitrova, Zlatina; Maréchal, François

    2015-01-01

    The largest applied convertors in passenger cars are the internal combustion engines – gasoline, diesel, adapted also for operating on alternative fuels and hybrid modes. The number of components that are necessary to realize modern future propulsion system is inexorably increasing. The need for efficiency improvement of the vehicle energy system induces the search for an innovative methodology during the design process. In this article the compressed air is investigated as an innovative solu...

  11. A Hybrid Analysis Approach to Improve Financial Distress Forecasting: Empirical Evidence from Iran

    Directory of Open Access Journals (Sweden)

    Shakiba Khademolqorani

    2015-01-01

    Full Text Available Bankruptcy prediction is an important problem facing financial decision support for stakeholders of firms, including auditors, managers, shareholders, debt-holders, and potential investors, as well as academic researchers. Popular discourse on financial distress forecasting focuses on developing the discrete models to improve the prediction. The aim of this paper is to develop a novel hybrid financial distress model based on combining various statistical and machine learning methods. Then multiple attribute decision making method is exploited to choose the optimized model from the implemented ones. Proposed approaches have also been applied in Iranian companies that performed previous models and it can be consolidated with the help of the hybrid approach.

  12. Hybrid of Genetic Programming with PBIL

    International Nuclear Information System (INIS)

    Caldas, Gustavo Henrique Flores; Schirru, Roberto

    2005-01-01

    Genetic programming and PBIL (Population-Based Incremental Learning) are evolutionary algorithms that have found applications in several fields of application. The Genetic Programming searches a solution allowing that the individuals of a population modify, mainly, its structures. The PBIL, on the other hand, works with individuals of fixed structure and is particularly successful in finding numerical solutions. There are problems where the simultaneous adjustment of the structure and numerical constants in a solution is essential. The Symbolic Regression is an example where both the form and the constants of a mathematical expression must be found. Although the traditional Genetic Programming is capable to solve this problem by itself, it is interesting to explore a cooperation with the PBIL, allowing each algorithm to do only that they do best: the Genetic Programming tries to find a structure while the PBIL adjust the constants that will be enclosed in the structure. In this work, the benchmark 'the sextic polynomial regression problem' is used to compare some traditional techniques of Genetic Programming with the proposed Hybrid of Genetic Programming with PBIL. The results are presented and discussed. (author)

  13. Learning to Mow Grass: IDF Adaptations to Hybrid Threats

    Science.gov (United States)

    2017-05-25

    April 2006. The language of SOD, however, was a mixed bag from “post-modern French philosophy, literary theory, architecture and psychology.”44 It...ground forces OCL soon proved this assessment. Near the end of 2008, Hamas had broken the Egyptian -brokered truce between it and Israel. Having...turned to southern Gaza to destroy more of Hamas tunnel network near the Egyptian border.176

  14. Evaluating Machine Learning Classifiers for Hybrid Network Intrusion Detection Systems

    Science.gov (United States)

    2015-03-26

    and the value-focused method. Comparing results from the two evaluation methods, fallacies are revealed with 2 of the 5 notional weighting schemes...for them, because of their relentless support, love , and encouragement. I give a sincere thank you to my research advisor, Dr. Robert Mills, for his...though Ad- aBoost.BayesNet dominated the traditional PR space using a single curve approach. This evaluation fallacy has not been demonstrated prior to

  15. A new hybrid teaching–learning particle swarm optimization ...

    Indian Academy of Sciences (India)

    Ramanpreet Singh

    2017-11-07

    Nov 7, 2017 ... factor and social parameters, whereas DE needs crossover constant and scaling ... networks to obtain superior results in comparison with GA. [24]. ...... effective algorithm for solving a wide range of problems. The results of ...

  16. Genetic basis to hybrid inviability is more complex than hybrid male sterility in Caenorhabditis nematodes.

    Science.gov (United States)

    Bundus, Joanna D; Wang, Donglin; Cutter, Asher D

    2018-04-07

    Hybrid male sterility often evolves before female sterility or inviability of hybrids, implying that the accumulation of divergence between separated lineages should lead hybrid male sterility to have a more polygenic basis. However, experimental evidence is mixed. Here, we use the nematodes Caenorhabditis remanei and C. latens to characterize the underlying genetic basis of asymmetric hybrid male sterility and hybrid inviability. We demonstrate that hybrid male sterility is consistent with a simple genetic basis, involving a single X-autosome incompatibility. We also show that hybrid inviability involves more genomic compartments, involving diverse nuclear-nuclear incompatibilities, a mito-nuclear incompatibility, and maternal effects. These findings demonstrate that male sensitivity to genetic perturbation may be genetically simple compared to hybrid inviability in Caenorhabditis and motivates tests of generality for the genetic architecture of hybrid incompatibility across the breadth of phylogeny.

  17. Associative learning and animal cognition.

    Science.gov (United States)

    Dickinson, Anthony

    2012-10-05

    Associative learning plays a variety of roles in the study of animal cognition from a core theoretical component to a null hypothesis against which the contribution of cognitive processes is assessed. Two developments in contemporary associative learning have enhanced its relevance to animal cognition. The first concerns the role of associatively activated representations, whereas the second is the development of hybrid theories in which learning is determined by prediction errors, both directly and indirectly through associability processes. However, it remains unclear whether these developments allow associative theory to capture the psychological rationality of cognition. I argue that embodying associative processes within specific processing architectures provides mechanisms that can mediate psychological rationality and illustrate such embodiment by discussing the relationship between practical reasoning and the associative-cybernetic model of goal-directed action.

  18. Stochastic effects in hybrid inflation

    Science.gov (United States)

    Martin, Jérôme; Vennin, Vincent

    2012-02-01

    Hybrid inflation is a two-field model where inflation ends due to an instability. In the neighborhood of the instability point, the potential is very flat and the quantum fluctuations dominate over the classical motion of the inflaton and waterfall fields. In this article, we study this regime in the framework of stochastic inflation. We numerically solve the two coupled Langevin equations controlling the evolution of the fields and compute the probability distributions of the total number of e-folds and of the inflation exit point. Then, we discuss the physical consequences of our results, in particular, the question of how the quantum diffusion can affect the observable predictions of hybrid inflation.

  19. 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...

  20. Adaptive hybrid control of manipulators

    Science.gov (United States)

    Seraji, H.

    1987-01-01

    Simple methods for the design of adaptive force and position controllers for robot manipulators within the hybrid control architecuture is presented. The force controller is composed of an adaptive PID feedback controller, an auxiliary signal and a force feedforward term, and it achieves tracking of desired force setpoints in the constraint directions. The position controller consists of adaptive feedback and feedforward controllers and an auxiliary signal, and it accomplishes tracking of desired position trajectories in the free directions. The controllers are capable of compensating for dynamic cross-couplings that exist between the position and force control loops in the hybrid control architecture. The adaptive controllers do not require knowledge of the complex dynamic model or parameter values of the manipulator or the environment. The proposed control schemes are computationally fast and suitable for implementation in on-line control with high sampling rates.