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Sample records for hybrid generative-discriminative learning

  1. Hybrid Generative/Discriminative Learning for Automatic Image Annotation

    CERN Document Server

    Yang, Shuang Hong; Zha, Hongyuan

    2012-01-01

    Automatic image annotation (AIA) raises tremendous challenges to machine learning as it requires modeling of data that are both ambiguous in input and output, e.g., images containing multiple objects and labeled with multiple semantic tags. Even more challenging is that the number of candidate tags is usually huge (as large as the vocabulary size) yet each image is only related to a few of them. This paper presents a hybrid generative-discriminative classifier to simultaneously address the extreme data-ambiguity and overfitting-vulnerability issues in tasks such as AIA. Particularly: (1) an Exponential-Multinomial Mixture (EMM) model is established to capture both the input and output ambiguity and in the meanwhile to encourage prediction sparsity; and (2) the prediction ability of the EMM model is explicitly maximized through discriminative learning that integrates variational inference of graphical models and the pairwise formulation of ordinal regression. Experiments show that our approach achieves both su...

  2. Semisupervised learning for a hybrid generative/discriminative classifier based on the maximum entropy principle.

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    Fujino, Akinori; Ueda, Naonori; Saito, Kazumi

    2008-03-01

    This paper presents a method for designing semi-supervised classifiers trained on labeled and unlabeled samples. We focus on probabilistic semi-supervised classifier design for multi-class and single-labeled classification problems, and propose a hybrid approach that takes advantage of generative and discriminative approaches. In our approach, we first consider a generative model trained by using labeled samples and introduce a bias correction model, where these models belong to the same model family, but have different parameters. Then, we construct a hybrid classifier by combining these models based on the maximum entropy principle. To enable us to apply our hybrid approach to text classification problems, we employed naive Bayes models as the generative and bias correction models. Our experimental results for four text data sets confirmed that the generalization ability of our hybrid classifier was much improved by using a large number of unlabeled samples for training when there were too few labeled samples to obtain good performance. We also confirmed that our hybrid approach significantly outperformed generative and discriminative approaches when the performance of the generative and discriminative approaches was comparable. Moreover, we examined the performance of our hybrid classifier when the labeled and unlabeled data distributions were different.

  3. 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

  4. Activity recognition using hybrid generative/discriminative models on home environments using binary sensors.

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    Ordóñez, Fco Javier; de Toledo, Paula; Sanchis, Araceli

    2013-04-24

    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.

  5. 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.

  6. A Hybrid Generative/Discriminative Classifier Design for Semi-supervised Learing

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    Fujino, Akinori; Ueda, Naonori; Saito, Kazumi

    Semi-supervised classifier design that simultaneously utilizes both a small number of labeled samples and a large number of unlabeled samples is a major research issue in machine learning. Existing semi-supervised learning methods for probabilistic classifiers belong to either generative or discriminative approaches. This paper focuses on a semi-supervised probabilistic classifier design for multiclass and single-labeled classification problems and first presents a hybrid approach to take advantage of the generative and discriminative approaches. Our formulation considers a generative model trained on labeled samples and a newly introduced bias correction model, whose belongs to the same model family as the generative model, but whose parameters are different from the generative model. A hybrid classifier is constructed by combining both the generative and bias correction models based on the maximum entropy principle, where the combination weights of these models are determined so that the class labels of labeled samples are as correctly predicted as possible. We apply the hybrid approach to text classification problems by employing naive Bayes as the generative and bias correction models. In our experimental results on three English and one Japanese text data sets, we confirmed that the hybrid classifier significantly outperformed conventional probabilistic generative and discriminative classifiers when the classification performance of the generative classifier was comparable to the discriminative classifier.

  7. Fundamentals of Hybrid Teaching and Learning

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    Linder, Kathryn E.

    2017-01-01

    This chapter provides definitions and distinguishing characteristics of the various terms used in the context of hybrid education. The author also offers an overview of the recent literature on hybrid teaching and learning.

  8. Hybrid Learning at the Community College

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    Snart, Jason

    2017-01-01

    This chapter discusses how the community college represents a potentially ideal educational setting for hybrid learning to thrive. The multimodal nature of hybrids, combining both online and face-to-face learning, affords the opportunity to engage students in a variety of ways. Further, many community college students can benefit from the…

  9. Self-Directed Lifelong Learning in Hybrid Learning Configurations

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    Cremers, Petra H. M.; Wals, Arjen E. J.; Wesselink, Renate; Nieveen, Nienke; Mulder, Martin

    2014-01-01

    Present-day students are expected to be lifelong learners throughout their working life. Higher education must therefore prepare students to self-direct their learning beyond formal education, in real-life working settings. This can be achieved in so-called hybrid learning configurations in which working and learning are integrated. In such a…

  10. Self-directed lifelong learning in hybrid learning configurations

    NARCIS (Netherlands)

    Cremers, P.H.M.; Wals, A.E.J.; Wesselink, R.; Nieveen, N.; Mulder, M.

    2014-01-01

    Present-day students are expected to be lifelong learners throughout their working life. Higher education must therefore prepare students to self-direct their learning beyond formal education, in real-life working settings. This can be achieved in so-called hybrid learning configurations in which

  11. A Hybrid Teaching and Learning Model

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    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.

  12. Hybrid Learning in Enhancing Communicative Skill in English

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    Singaravelu, G.

    2010-01-01

    The present study highlights the effectiveness of Hybrid-Learning in enhancing communicative skill in English among the Trainees of Bachelor of education of School of Distance Education, Bharathiar University,Coimbatore. Hybrid learning refers to mixing of different learning methods or mixing two more methods for teaching learning process. It…

  13. Hybrid discourse practice and science learning

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    Kamberelis, George; Wehunt, Mary D.

    2012-09-01

    In this article, we report on a study of how creative linguistic practices (which we call hybrid discourse practices) were enacted by students in a fifth-grade science unit on barn owls and how these practices helped to produce a synergistic micro-community of scientific practice in the classroom that constituted a fertile space for students (and the teacher) to construct emergent but increasingly legitimate and dynamic disciplinary knowledges and identities. Our findings are important for the ways in which they demonstrate (a) how students use hybrid discourse practices to self-scaffold their work within complex curricular tasks and when they are not completely sure about how to enact these tasks (b) how hybrid discourse practices can promote inquiry orientations to science, (c) how hybrid discourse practices index new and powerful forms of science pedagogy, and (d) how hybrid discourse practices are relevant to more global issues such as the crucial roles of language fluency and creativity, which are known prerequisites for advanced science learning and which aid students in developing skills that are necessary for entry into science and technology careers.

  14. Designing e-learning cognitively: TSOI Hybrid Learning Model

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    Mun Fie Tsoi

    2008-08-01

    Full Text Available Research on learning has proposed various models for learning. However, generally, there has been an inadequate research of the application of these models for learning for example the Kolb’s experiential learning cycle or the Jarvis’s model of reflection and learning to the development of e-learning materials. This is more so especially due to lack of effective yet practical design model for designing interactive e-learning materials. Having this in mind, the TSOI Hybrid Learning Model can be used as a pedagogic model for the cognitive design of e-learning. This Model represents learning as a cyclical cognitive process. A major feature is to promote active cognitive processing in the learner for meaningful learning proceeding from inductive to deductive. Design specificity in science and chemistry education is illustrated in terms of instructional storyboarding and the research-based e-learning product developed. Learners’ cognitive abilities will be addressed as part of the research data collected.

  15. Learning Style, Sense of Community and Learning Effectiveness in Hybrid Learning Environment

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    Chen, Bryan H.; Chiou, Hua-Huei

    2014-01-01

    The purpose of this study is to investigate how hybrid learning instruction affects undergraduate students' learning outcome, satisfaction and sense of community. The other aim of the present study is to examine the relationship between students' learning style and learning conditions in mixed online and face-to-face courses. A quasi-experimental…

  16. Learning Style, Sense of Community and Learning Effectiveness in Hybrid Learning Environment

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    Chen, Bryan H.; Chiou, Hua-Huei

    2014-01-01

    The purpose of this study is to investigate how hybrid learning instruction affects undergraduate students' learning outcome, satisfaction and sense of community. The other aim of the present study is to examine the relationship between students' learning style and learning conditions in mixed online and face-to-face courses. A quasi-experimental…

  17. Adventure Learning: Theory and Implementation of Hybrid Learning

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    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

  18. Hybrid Multiagent System for Automatic Object Learning Classification

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    Gil, Ana; de La Prieta, Fernando; López, Vivian F.

    The rapid evolution within the context of e-learning is closely linked to international efforts on the standardization of learning object metadata, which provides learners in a web-based educational system with ubiquitous access to multiple distributed repositories. This article presents a hybrid agent-based architecture that enables the recovery of learning objects tagged in Learning Object Metadata (LOM) and provides individualized help with selecting learning materials to make the most suitable choice among many alternatives.

  19. Investigations on Hybrid Learning in ANFIS

    Directory of Open Access Journals (Sweden)

    C.Loganathan

    2014-10-01

    Full Text Available Neural networks have attractiveness to several researchers due to their great closeness to the structure of the brain, their characteristics not shared by many traditional systems. An Artificial Neural Network (ANN is a network of interconnected artificial processing elements (called neurons that co-operate with one another in order to solve specific issues. ANNs are inspired by the structure and functional aspects of biological nervous systems. Neural networks, which recognize patterns and adopt themselves to cope with changing environments. Fuzzy inference system incorporates human knowledge and performs inferencing and decision making. The integration of these two complementary approaches together with certain derivative free optimization techniques, results in a novel discipline called Neuro Fuzzy. In Neuro fuzzy development a specific approach is called Adaptive Neuro Fuzzy Inference System (ANFIS, which has shown significant results in modeling nonlinear functions. The basic idea behind the paper is to design a system that uses a fuzzy system to represent knowledge in an interpretable manner and have the learning ability derived from a Runge-Kutta learning method (RKLM to adjust its membership functions and parameters in order to enhance the system performance. The problem of finding appropriate membership functions and fuzzy rules is often a tiring process of trial and error. It requires users to understand the data before training, which is usually difficult to achieve when the database is relatively large. To overcome these problems, a hybrid of Back Propagation Neural network (BPN and RKLM can combine the advantages of two systems and avoid their disadvantages.

  20. A hybrid random field model for scalable statistical learning.

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    Freno, A; Trentin, E; Gori, M

    2009-01-01

    This paper introduces hybrid random fields, which are a class of probabilistic graphical models aimed at allowing for efficient structure learning in high-dimensional domains. Hybrid random fields, along with the learning algorithm we develop for them, are especially useful as a pseudo-likelihood estimation technique (rather than a technique for estimating strict joint probability distributions). In order to assess the generality of the proposed model, we prove that the class of pseudo-likelihood distributions representable by hybrid random fields strictly includes the class of joint probability distributions representable by Bayesian networks. Once we establish this result, we develop a scalable algorithm for learning the structure of hybrid random fields, which we call 'Markov Blanket Merging'. On the one hand, we characterize some complexity properties of Markov Blanket Merging both from a theoretical and from the experimental point of view, using a series of synthetic benchmarks. On the other hand, we evaluate the accuracy of hybrid random fields (as learned via Markov Blanket Merging) by comparing them to various alternative statistical models in a number of pattern classification and link-prediction applications. As the results show, learning hybrid random fields by the Markov Blanket Merging algorithm not only reduces significantly the computational cost of structure learning with respect to several considered alternatives, but it also leads to models that are highly accurate as compared to the alternative ones.

  1. A mixed generative-discriminative framework for pedestrian classification

    NARCIS (Netherlands)

    Enzweiler, M.; Gavrila, D.M.

    2008-01-01

    This paper presents a novel approach to pedestrian classification which involves utilizing the synthesized virtual samples of a learned generative model to enhance the classification performance of a discriminative model. Our generative model captures prior knowledge about the pedestrian class in te

  2. Applying TSOI Hybrid Learning Model to Enhance Blended Learning Experience in Science Education

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    Tsoi, Mun Fie

    2009-01-01

    Purpose: Research on the nature of blended learning and its features has led to a variety of approaches to the practice of blended learning. The purpose of this paper is to provide an alternative practice model, the TSOI hybrid learning model (HLM) to enhance the blended learning experiences in science education. Design/methodology/approach: The…

  3. Hybrid Neural Network Architecture for On-Line Learning

    CERN Document Server

    Chen, Yuhua; Wang, Lei

    2008-01-01

    Approaches to machine intelligence based on brain models have stressed the use of neural networks for generalization. Here we propose the use of a hybrid neural network architecture that uses two kind of neural networks simultaneously: (i) a surface learning agent that quickly adapt to new modes of operation; and, (ii) a deep learning agent that is very accurate within a specific regime of operation. The two networks of the hybrid architecture perform complementary functions that improve the overall performance. The performance of the hybrid architecture has been compared with that of back-propagation perceptrons and the CC and FC networks for chaotic time-series prediction, the CATS benchmark test, and smooth function approximation. It has been shown that the hybrid architecture provides a superior performance based on the RMS error criterion.

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

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    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…

  5. Study on Applying Hybrid Machine Learning into Family Apparel Expenditure

    Institute of Scientific and Technical Information of China (English)

    SHEN Lei

    2008-01-01

    Hybrid Machine Learning (HMD is a kind of advanced algorithm in the field of intelligent information process.It combines the induced learning based-on decision-making tree with the blocking neural network.And it provides a useful intelligent knowledge-based data mining technique.Its core algorithm is ID3 and Field Theory based ART (FTART).The paper introduces the principals of hybrid machine learning firstly, and then applies it into analyzing family apparel expenditures and their influencing factors systematically.Finally, compared with those from the traditional statistic methods, the results from HML is more friendly and easily to be understood.Besides, the forecasting by HML is more correct than by the traditional ways.

  6. Hybrid Genetic Relational Search for Inductive Learning

    NARCIS (Netherlands)

    Divina, F.

    2004-01-01

    An important characteristic of all natural systems is the ability to acquire knowledge through experience and to adapt to new situations. Learning is the single unifying theme of all natural systems. One of the basic ways of gaining knowledge is through examples of some concepts.For instance, we ma

  7. Hybrid Genetic Relational Search for Inductive Learning

    NARCIS (Netherlands)

    Divina, F.

    2004-01-01

    An important characteristic of all natural systems is the ability to acquire knowledge through experience and to adapt to new situations. Learning is the single unifying theme of all natural systems. One of the basic ways of gaining knowledge is through examples of some concepts.For instance, we

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

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    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,…

  9. Accurate Identification of Cancerlectins through Hybrid Machine Learning Technology

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    Jieru Zhang

    2016-01-01

    Full Text Available 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.

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

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    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

  11. Strengthening ecological mindfulness through hybrid learning in vital coalitions

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    Sol, Jifke; Wals, Arjen E. J.

    2015-03-01

    In this contribution a key policy `tool' used in the Dutch Environmental Education and Learning for Sustainability Policy framework is introduced as a means to develop a sense of place and associated ecological mindfulness. The key elements of this tool, called the vital coalition, are described while an example of its use in practice, is analysed using a form of reflexive monitoring and evaluation. The example focuses on a multi-stakeholder learning process around the transformation of a somewhat sterile pre-school playground into an intergenerational green place suitable for play, discovery and engagement. Our analysis of the policy-framework and the case leads us to pointing out the importance of critical interventions at so-called tipping points within the transformation process and a discussion of the potential of hybrid learning in vital coalitions in strengthening ecological mindfulness. This paper does not focus on establishing an evidence base for the causality between this type of learning and a change in behavior or mindfulness among participants as a result contributing to a vital coalition but rather focusses on the conditions, processes and interventions that allow for such learning to take place in the first place.

  12. Maze learning by a hybrid brain-computer system

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    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.

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

    DEFF Research Database (Denmark)

    Weitze, Charlotte Lærke

    2016-01-01

    of their daily practices and also participated in a design-based research project exploring new learning designs for this environment (Weitze, 2015). The teachers’ traditional learning designs were challenged, and this led to altered pedagogical approaches with less group-work and an extensive use of monologue......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......-based teaching. The findings were, however, that the teachers, through pedagogically innovative strategies, developed knowledge about how their pedagogical patterns in this hybrid synchronous learning situation could be supported by an array of additional educational technologies and strategies to create...

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

    DEFF Research Database (Denmark)

    Weitze, Charlotte Lærke

    2016-01-01

    -based teaching. The findings were, however, that the teachers, through pedagogically innovative strategies, developed knowledge about how their pedagogical patterns in this hybrid synchronous learning situation could be supported by an array of additional educational technologies and strategies to create......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 their daily practices and also participated in a design-based research project exploring new learning designs for this environment (Weitze, 2015). The teachers’ traditional learning designs were challenged, and this led to altered pedagogical approaches with less group-work and an extensive use of monologue...

  15. A Hybrid Ensemble Learning Approach to Star-Galaxy Classification

    CERN Document Server

    Kim, Edward J; Kind, Matias Carrasco

    2015-01-01

    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, we consider different scenarios: when a high-quality training set is available with spectroscopic labels from DEEP2, SDSS, VIPERS, and VVDS, 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, s...

  16. Electrical test prediction using hybrid metrology and machine learning

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    Breton, Mary; Chao, Robin; Muthinti, Gangadhara Raja; de la Peña, Abraham A.; Simon, Jacques; Cepler, Aron J.; Sendelbach, Matthew; Gaudiello, John; Emans, Susan; Shifrin, Michael; Etzioni, Yoav; Urenski, Ronen; Lee, Wei Ti

    2017-03-01

    Electrical test measurement in the back-end of line (BEOL) is crucial for wafer and die sorting as well as comparing intended process splits. Any in-line, nondestructive technique in the process flow to accurately predict these measurements can significantly improve mean-time-to-detect (MTTD) of defects and improve cycle times for yield and process learning. Measuring after BEOL metallization is commonly done for process control and learning, particularly with scatterometry (also called OCD (Optical Critical Dimension)), which can solve for multiple profile parameters such as metal line height or sidewall angle and does so within patterned regions. This gives scatterometry an advantage over inline microscopy-based techniques, which provide top-down information, since such techniques can be insensitive to sidewall variations hidden under the metal fill of the trench. But when faced with correlation to electrical test measurements that are specific to the BEOL processing, both techniques face the additional challenge of sampling. Microscopy-based techniques are sampling-limited by their small probe size, while scatterometry is traditionally limited (for microprocessors) to scribe targets that mimic device ground rules but are not necessarily designed to be electrically testable. A solution to this sampling challenge lies in a fast reference-based machine learning capability that allows for OCD measurement directly of the electrically-testable structures, even when they are not OCD-compatible. By incorporating such direct OCD measurements, correlation to, and therefore prediction of, resistance of BEOL electrical test structures is significantly improved. Improvements in prediction capability for multiple types of in-die electrically-testable device structures is demonstrated. To further improve the quality of the prediction of the electrical resistance measurements, hybrid metrology using the OCD measurements as well as X-ray metrology (XRF) is used. Hybrid metrology

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

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    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.

  18. Factors Related to Students' Performance of Hybrid Learning in an English Language Course

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    Wichadee, Saovapa

    2014-01-01

    Redesigning a course along the lines of a hybrid format that blends face-to-face and online learning brings about changes in instructional practice. This paper introduces hybrid teaching that uses multiple web-based tools to supplement the students' face-to-face learning environment in a difficult situation in Thailand. In order to examine factors…

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

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    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

  20. 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.

  1. 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.

  2. 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.

  3. Mechanisms underlying REBT in mood disordered patients: predicting depression from the hybrid model of learning.

    Science.gov (United States)

    Jackson, Chris J; Izadikah, Zahra; Oei, Tian P S

    2012-06-01

    Jackson's (2005, 2008a) hybrid model of learning identifies a number of learning mechanisms that lead to the emergence and maintenance of the balance between rationality and irrationality. We test a general hypothesis that Jackson's model will predict depressive symptoms, such that poor learning is related to depression. We draw comparisons between Jackson's model and Ellis' (2004) Rational Emotive Behavior Therapy and Theory (REBT) and thereby provide a set of testable learning mechanisms potentially underlying REBT. Results from 80 patients diagnosed with depression completed the learning styles profiler (LSP; Jackson, 2005) and two measures of depression. Results provide support for the proposed model of learning and further evidence that low rationality is a key predictor of depression. We conclude that the hybrid model of learning has the potential to explain some of the learning and cognitive processes related to the development and maintenance of irrational beliefs and depression. Copyright © 2011. Published by Elsevier B.V.

  4. 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.

  5. Predicting Grade Point Average from the Hybrid Model of Learning in Personality: Consistent Findings from Ugandan and Australian Students

    Science.gov (United States)

    Jackson, Chris; Baguma, Peter; Furnham, Adrian

    2009-01-01

    Jackson developed a hybrid model of learning in personality, known as the Learning Styles Profiler (LSP), which seeks to explain personality in terms of biological, socio-cognitive and experiential processes. The hybrid model argues that functional learning outcomes can be understood in terms of how cognitions and experiences re-express sensation…

  6. 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.

  7. 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.

  8. 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

  9. Statistical learning makes the hybridization of particle swarm and differential evolution more efficient-A novel hybrid optimizer

    Institute of Scientific and Technical Information of China (English)

    CHEN Jie; XIN Bin; PENG ZhiHong; PAN Feng

    2009-01-01

    This brief paper reports a hybrid algorithm we developed recently to solve the global optimization problems of multimodal functions, by combining the advantages of two powerful population-based metaheuristics-differential evolution (DE) and particle swarm optimization (PSO). In the hybrid denoted by DEPSO, each individual in one generation chooses its evolution method, DE or PSO, in a statistical learning way. The choice depends on the relative success ratio of the two methods in a previous learning period. The proposed DEPSO is compared with its PSO and DE parents, two advanced DE variants one of which is suggested by the originators of DE, two advanced PSO variants one of which is acknowledged as a recent standard by PSO community, and also a previous DEPSO. Benchmark tests demonstrate that the DEPSO is more competent for the global optimization of multimodal functions due to its high optimization quality.

  10. Using a Hybrid Approach to Facilitate Learning Introductory Programming

    Science.gov (United States)

    Cakiroglu, Unal

    2013-01-01

    In order to facilitate students' understanding in introductory programming courses, different types of teaching approaches were conducted. In this study, a hybrid approach including comment first coding (CFC), analogy and template approaches were used. The goal was to investigate the effect of such a hybrid approach on students' understanding in…

  11. 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.

  12. 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…

  13. Researching Hybrid Learning Communities in the Digital Age through Educational Ethnography

    Science.gov (United States)

    James, Nalita; Busher, Hugh

    2013-01-01

    This paper discusses the complexities of investigating the experiences of participants in hybrid (online/offline) learning communities through educational ethnography. In these communities, people construct small cultures in the liminal spaces or "border crossings" between the virtually real and "actually" real, using computer-mediated and…

  14. Hybrid professional learning networks for knowledge workers: educational theory inspiring new practices

    NARCIS (Netherlands)

    Bitter-Rijpkema, Marlies; Verjans, Steven

    2010-01-01

    Bitter-Rijpkema, M., & Verjans, S. (2010). Hybrid professional learning networks for knowledge workers: educational theory inspiring new practices. In L. Creanor, D. Hawkridge, K. Ng, & F. Rennie (Eds.), ALT-C 2010 - Conference Proceedings: "Into something rich and strange" - making sense of the

  15. Optimization of Evolutionary Neural Networks Using Hybrid Learning Algorithms

    OpenAIRE

    Abraham, Ajith

    2004-01-01

    Evolutionary artificial neural networks (EANNs) refer to a special class of artificial neural networks (ANNs) in which evolution is another fundamental form of adaptation in addition to learning. Evolutionary algorithms are used to adapt the connection weights, network architecture and learning algorithms according to the problem environment. Even though evolutionary algorithms are well known as efficient global search algorithms, very often they miss the best local solutions in the complex s...

  16. 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.

  17. Networked Environments that Create Hybrid Spaces for Learning Science

    Science.gov (United States)

    Otrel-Cass, Kathrin; Khoo, Elaine; Cowie, Bronwen

    2014-01-01

    Networked learning environments that embed the essence of the Community of Inquiry (CoI) framework utilise pedagogies that encourage dialogic practices. This can be of significance for classroom teaching across all curriculum areas. In science education, networked environments are thought to support student investigations of scientific problems,…

  18. Strengthening ecological mindfulness through hybrid learning in vital coalitions

    NARCIS (Netherlands)

    Sol, A.J.; Wals, A.E.J.

    2015-01-01

    In this contribution a key policy ‘tool’ used in the Dutch Environmental Education and Learning for Sustainability Policy framework is introduced as a means to develop a sense of place and associated ecological mindfulness. The key elements of this tool, called the vital coalition, are described whi

  19. What drives students' self-directed learning in a hybrid PBL curriculum.

    Science.gov (United States)

    Lee, Young-Mee; Mann, Karen V; Frank, Blye W

    2010-08-01

    Evidence supporting Problem-based learning (PBL) fostering students' self-directed learning (SDL) in hybrid PBL curricula is inconsistent. To explore the influence of PBL in a hybrid curriculum on students' SDL, the authors investigated the following: (1) students' self-assessed SDL ability, (2) students' perceptions of the influence of curricular components on SDL, and (3) the relationships between curricular elements and SDL. The research questions were explored both quantitatively and qualitatively. All year 1 (n = 93) and year 2 (n = 93) students in 2004 were invited to participate. Participants completed a 53-item questionnaire addressing (a) self-assessment of their SDL ability, and (b) perceived influence of individual curriculum elements on individual study and SDL. Student and faculty focus group interviews (FGIs) were conducted. Students rated their SDL skills highly, particularly identifying knowledge deficits, learning skills and strategies, and managing study time. Students thought lectures helped in selecting study topics and learning for the tutorial case. Other components including tutors, unit/case objectives, tests, and tutorial discussions, were seen as influencing what to study and the learning process. No significant difference was observed in the responses between year 1 and 2 students. Among the six curriculum components, tutorial discussion and objectives were weakly correlated with with SDL ability. Findings from students and faculty focus group supported the perceived positive influence of the curriculum on SDL. This study found that students' perceived SDL ability was positively influenced by several components of the hybrid PBL curriculum. However, further investigations are needed for a clearer understanding of the specific effects of the hybrid PBL curriculum on students' SDL.

  20. Accelerating a hybrid continuum-atomistic fluidic model with on-the-fly machine learning

    CERN Document Server

    Stephenson, David; Lockerby, Duncan A

    2016-01-01

    We present a hybrid continuum-atomistic scheme which combines molecular dynamics (MD) simulations with on-the-fly machine learning techniques for the accurate and efficient prediction of multiscale fluidic systems. By using a Gaussian process as a surrogate model for the computationally expensive MD simulations, we use Bayesian inference to predict the system behaviour at the atomistic scale, purely by consideration of the macroscopic inputs and outputs. Whenever the uncertainty of this prediction is greater than a predetermined acceptable threshold, a new MD simulation is performed to continually augment the database, which is never required to be complete. This provides a substantial enhancement to the current generation of hybrid methods, which often require many similar atomistic simulations to be performed, discarding information after it is used once. We apply our hybrid scheme to nano-confined unsteady flow through a high-aspect-ratio converging-diverging channel, and make comparisons between the new s...

  1. 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

  2. Learning and Adaptive Hybrid Systems for Nonlinear Control

    Science.gov (United States)

    1991-05-01

    6 2.1.1 Single Layer Networks 8 Perceptrons 8 Samuel’s Checker Player 10 ADALINE and MADALINE 12 2.1.2 Multilayer Networks 13 Hebbian Learning 13...was Widrow’s ADALINE and MADALINE [Wid89]. He developed a type of adaptive filter which is still in widespread use today in such items as high speed...time step, and used it for pattern recognition. This "Adaptive Linear Neuron" ( ADALINE ) [Wid89] was then built in actual hardware, where weights were

  3. Developing a Collaborative and Autonomous Training and Learning Environment for Hybrid Wireless Networks

    CERN Document Server

    Lobo, Jose Eduardo M; Brust, Matthias R; Rothkugel, Steffen; Adriano, Christian M

    2007-01-01

    With larger memory capacities and the ability to link into wireless networks, more and more students uses palmtop and handheld computers for learning activities. However, existing software for Web-based learning is not well-suited for such mobile devices, both due to constrained user interfaces as well as communication effort required. A new generation of applications for the learning domain that is explicitly designed to work on these kinds of small mobile devices has to be developed. For this purpose, we introduce CARLA, a cooperative learning system that is designed to act in hybrid wireless networks. As a cooperative environment, CARLA aims at disseminating teaching material, notes, and even components of itself through both fixed and mobile networks to interested nodes. Due to the mobility of nodes, CARLA deals with upcoming problems such as network partitions and synchronization of teaching material, resource dependencies, and time constraints.

  4. Hybrid Topological Lie-Hamiltonian Learning in Evolving Energy Landscapes

    Science.gov (United States)

    Ivancevic, Vladimir G.; Reid, Darryn J.

    2015-11-01

    In this Chapter, a novel bidirectional algorithm for hybrid (discrete + continuous-time) Lie-Hamiltonian evolution in adaptive energy landscape-manifold is designed and its topological representation is proposed. The algorithm is developed within a geometrically and topologically extended framework of Hopfield's neural nets and Haken's synergetics (it is currently designed in Mathematica, although with small changes it could be implemented in Symbolic C++ or any other computer algebra system). The adaptive energy manifold is determined by the Hamiltonian multivariate cost function H, based on the user-defined vehicle-fleet configuration matrix W, which represents the pseudo-Riemannian metric tensor of the energy manifold. Search for the global minimum of H is performed using random signal differential Hebbian adaptation. This stochastic gradient evolution is driven (or, pulled-down) by `gravitational forces' defined by the 2nd Lie derivatives of H. Topological changes of the fleet matrix W are observed during the evolution and its topological invariant is established. The evolution stops when the W-topology breaks down into several connectivity-components, followed by topology-breaking instability sequence (i.e., a series of phase transitions).

  5. Visual tracker using sequential bayesian learning: discriminative, generative, and hybrid.

    Science.gov (United States)

    Lei, Yun; Ding, Xiaoqing; Wang, Shengjin

    2008-12-01

    This paper presents a novel solution to track a visual object under changes in illumination, viewpoint, pose, scale, and occlusion. Under the framework of sequential Bayesian learning, we first develop a discriminative model-based tracker with a fast relevance vector machine algorithm, and then, a generative model-based tracker with a novel sequential Gaussian mixture model algorithm. Finally, we present a three-level hierarchy to investigate different schemes to combine the discriminative and generative models for tracking. The presented hierarchical model combination contains the learner combination (at level one), classifier combination (at level two), and decision combination (at level three). The experimental results with quantitative comparisons performed on many realistic video sequences show that the proposed adaptive combination of discriminative and generative models achieves the best overall performance. Qualitative comparison with some state-of-the-art methods demonstrates the effectiveness and efficiency of our method in handling various challenges during tracking.

  6. 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.

  7. 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.

  8. 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.

  9. 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.

  10. Learning strategies used by undergraduate and postgraduate students in hybrid courses in the area of health.

    Science.gov (United States)

    Peixoto, Henry Maia; Peixoto, Mariana Maia; Alves, Elioenai Dornelles

    2012-01-01

    This study aimed to investigate the learning habits and strategies of undergraduate and post-graduate students matriculated in hybrid courses in the area of healthcare at a Brazilian university. 220 graduate students were invited to participate in the research, of whom 67.27% accepted. An exploratory methodology was utilized, which analyzed quantitative data collected by a structured instrument. A similarity may be observed between undergraduate and postgraduate students concerning the majority of education habits and learning strategies, such as the large proportion of those who read more than half of the course content and of those who preferred to study alone, as well as in the high use of the majority of strategies evaluated. It is concluded that both the groups present appropriate study habits and satisfactorily used the learning strategies investigated.

  11. 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.

  12. 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.

  13. 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.

  14. Learning effectiveness and satisfaction of international medical students: Introducing a Hybrid-PBL curriculum in biochemistry.

    Science.gov (United States)

    Yan, Qiu; Ma, Li; Zhu, Lina; Zhang, Wenli

    2017-07-08

    A biochemistry course is a fundamental but important subject in medical education in China. In recent years, the number of international medical students has increased. Curriculum reform in biochemistry teaching is needed because of the knowledge limitations of students, a close linkage of biochemical content with clinics, the shortcomings of lecture-centered teaching, and the requirements for early clinical practice training and competence. In this study, we analyzed a novel curriculum reform, "Hybrid-PBL," which combined problem-based learning (PBL) with biochemistry lectures and was implemented for biochemical teaching at Dalian Medical University (DMU) in China. The change in curriculum affected 189 international medical students. This study selected two PBL cases concerning the basic biochemical issues of carbohydrate metabolism and liver biochemistry for the analysis, and ten examples of learning issues for each case were reported by the international students. A questionnaire was utilized to evaluate students' perceptions of the Hybrid-PBL, and examination scores were analyzed to assess the curriculum reform in biochemistry teaching. A statistical analysis revealed that the Hybrid-PBL curriculum was well accepted by the international students as an effective supplement to lecture-centered teaching programs. The students obtained more abilities, higher examination scores, and an improved understanding of biomedical information from the Hybrid-PBL program than from conventional teaching methods. Our study was an innovative trial that applied a PBL curriculum to the specific discipline of biochemistry and may provide a potential and promising new teaching method that can be widely utilized. © 2017 by The International Union of Biochemistry and Molecular Biology, 45(4):336-342, 2017. © 2017 The International Union of Biochemistry and Molecular Biology.

  15. Hierarchical Wireless Multimedia Sensor Networks for Collaborative Hybrid Semi-Supervised Classifier Learning

    Directory of Open Access Journals (Sweden)

    Liang Ding

    2007-11-01

    Full Text Available Wireless multimedia sensor networks (WMSN have recently emerged as one ofthe most important technologies, driven by the powerful multimedia signal acquisition andprocessing abilities. Target classification is an important research issue addressed in WMSN,which has strict requirement in robustness, quickness and accuracy. This paper proposes acollaborative semi-supervised classifier learning algorithm to achieve durative onlinelearning for support vector machine (SVM based robust target classification. The proposedalgorithm incrementally carries out the semi-supervised classifier learning process inhierarchical WMSN, with the collaboration of multiple sensor nodes in a hybrid computingparadigm. For decreasing the energy consumption and improving the performance, somemetrics are introduced to evaluate the effectiveness of the samples in specific sensor nodes,and a sensor node selection strategy is also proposed to reduce the impact of inevitablemissing detection and false detection. With the ant optimization routing, the learningprocess is implemented with the selected sensor nodes, which can decrease the energyconsumption. Experimental results demonstrate that the collaborative hybrid semi-supervised classifier learning algorithm can effectively implement target classification inhierarchical WMSN. It has outstanding performance in terms of energy efficiency and timecost, which verifies the effectiveness of the sensor nodes selection and ant optimizationrouting.

  16. Semantic Searching and Ranking of Documents using Hybrid Learning System and WordNet

    Directory of Open Access Journals (Sweden)

    Pooja Arora

    2012-06-01

    Full Text Available Semantic searching seeks to improve search accuracy of the search engine by understanding searcher’s intent and the contextual meaning of the terms present in the query to retrieve more relevant results. To find out the semantic similarity between the query terms, WordNet is used as the underlying reference database. Various approaches of Learning to Rank are compared. A new hybrid learning system is introduced which combines learning using Neural Network and Support Vector Machine. As the size of the training set highly affects the performance of the Neural Network, we have used Support Vector Machine to reduce the size of the data set by extracting support vectors that are critical for the learning. The data set containing support vectors is then used for learning a ranking function using Neural Network. The proposed system is compared with RankNet. The experimental results demonstrated very promising performance improvements. For experiments, we have used English-Hindi parallel corpus, Gyannidhi from CDAC. F-measure and Average Interpolated Precision are used for evaluation.

  17. Using multimedia learning modules in a hybrid-online course in electricity and magnetism

    Science.gov (United States)

    Sadaghiani, Homeyra R.

    2011-06-01

    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 from a controlled study utilizing modules on electricity and magnetism as a part of a blended hybrid-online course. We asked students in the experimental section to view the MLMs prior to attending the face-to-face class, and to make sure this would not result in additional instructional time, we reduced the weekly class time by one-third. We found that despite reduced class time, student-learning outcomes were not hindered; in fact, the implementation of the UIUC MLMs resulted in a positive effect on student performance on conceptual tests and classroom discussion questions.

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

    DEFF Research Database (Denmark)

    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...

  19. Using multimedia learning modules in a hybrid-online course in electricity and magnetism

    Directory of Open Access Journals (Sweden)

    Homeyra R. Sadaghiani

    2011-03-01

    Full Text Available 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 from a controlled study utilizing modules on electricity and magnetism as a part of a blended hybrid-online course. We asked students in the experimental section to view the MLMs prior to attending the face-to-face class, and to make sure this would not result in additional instructional time, we reduced the weekly class time by one-third. We found that despite reduced class time, student-learning outcomes were not hindered; in fact, the implementation of the UIUC MLMs resulted in a positive effect on student performance on conceptual tests and classroom discussion questions.

  20. A hybrid manifold learning algorithm for the diagnosis and prognostication of Alzheimer's disease.

    Science.gov (United States)

    Dai, Peng; Gwadry-Sridhar, Femida; Bauer, Michael; Borrie, Michael

    The diagnosis of Alzheimer's disease (AD) requires a variety of medical tests, which leads to huge amounts of multivariate heterogeneous data. Such data are difficult to compare, visualize, and analyze due to the heterogeneous nature of medical tests. We present a hybrid manifold learning framework, which embeds the feature vectors in a subspace preserving the underlying pairwise similarity structure, i.e. similar/dissimilar pairs. Evaluation tests are carried out using the neuroimaging and biological data from the Alzheimer's Disease Neuroimaging Initiative (ADNI) in a three-class (normal, mild cognitive impairment, and AD) classification task using support vector machine (SVM). Furthermore, we make extensive comparison with standard manifold learning algorithms, such as Principal Component Analysis (PCA), Principal Component Analysis (PCA), Multidimensional Scaling (MDS), and isometric feature mapping (Isomap). Experimental results show that our proposed algorithm yields an overall accuracy of 85.33% in the three-class task.

  1. Pattern Recognition in Collective Cognitive Systems: Hybrid Human-Machine Learning (HHML) By Heterogeneous Ensembles

    CERN Document Server

    Dashti, Hesam T; Siahpirani, Alireza F; Tonejc, Jernej; Uilecan, Ioan V; Simas, Tiago; Miranda, Bruno; Ribeiro, Rita; Wang, Liya; Assadi, Amir H

    2010-01-01

    The ubiquitous role of the cyber-infrastructures, such as the WWW, provides myriad opportunities for machine learning and its broad spectrum of application domains taking advantage of digital communication. Pattern classification and feature extraction are among the first applications of machine learning that have received extensive attention. The most remarkable achievements have addressed data sets of moderate-to-large size. The 'data deluge' in the last decade or two has posed new challenges for AI researchers to design new, effective and accurate algorithms for similar tasks using ultra-massive data sets and complex (natural or synthetic) dynamical systems. We propose a novel principled approach to feature extraction in hybrid architectures comprised of humans and machines in networked communication, who collaborate to solve a pre-assigned pattern recognition (feature extraction) task. There are two practical considerations addressed below: (1) Human experts, such as plant biologists or astronomers, often...

  2. Daily reservoir inflow forecasting using multiscale deep feature learning with hybrid models

    Science.gov (United States)

    Bai, Yun; Chen, Zhiqiang; Xie, Jingjing; Li, Chuan

    2016-01-01

    Inflow forecasting applies data supports for the operations and managements of reservoirs. A multiscale deep feature learning (MDFL) method with hybrid models is proposed in this paper to deal with the daily reservoir inflow forecasting. Ensemble empirical mode decomposition and Fourier spectrum are first employed to extract multiscale (trend, period and random) features, which are then represented by three deep belief networks (DBNs), respectively. The weights of each DBN are subsequently applied to initialize a neural network (D-NN). The outputs of the three-scale D-NNs are finally reconstructed using a sum-up strategy toward the forecasting results. A historical daily inflow series (from 1/1/2000 to 31/12/2012) of the Three Gorges reservoir, China, is investigated by the proposed MDFL with hybrid models. For comparison, four peer models are adopted for the same task. The results show that, the present model overwhelms all the peer models in terms of mean absolute percentage error (MAPE = 11.2896%), normalized root-mean-square error (NRMSE = 0.2292), determination coefficient criteria (R2 = 0.8905), and peak percent threshold statistics (PPTS(5) = 10.0229%). The addressed method integrates the deep framework with multiscale and hybrid observations, and therefore being good at exploring sophisticated natures in the reservoir inflow forecasting.

  3. Heart Disease Diagnosis Utilizing Hybrid Fuzzy Wavelet Neural Network and Teaching Learning Based Optimization Algorithm

    Directory of Open Access Journals (Sweden)

    Jamal Salahaldeen Majeed Alneamy

    2014-01-01

    Full Text Available Among the various diseases that threaten human life is heart disease. This disease is considered to be one of the leading causes of death in the world. Actually, the medical diagnosis of heart disease is a complex task and must be made in an accurate manner. Therefore, a software has been developed based on advanced computer technologies to assist doctors in the diagnostic process. This paper intends to use the hybrid teaching learning based optimization (TLBO algorithm and fuzzy wavelet neural network (FWNN for heart disease diagnosis. The TLBO algorithm is applied to enhance performance of the FWNN. The hybrid TLBO algorithm with FWNN is used to classify the Cleveland heart disease dataset obtained from the University of California at Irvine (UCI machine learning repository. The performance of the proposed method (TLBO_FWNN is estimated using K-fold cross validation based on mean square error (MSE, classification accuracy, and the execution time. The experimental results show that TLBO_FWNN has an effective performance for diagnosing heart disease with 90.29% accuracy and superior performance compared to other methods in the literature.

  4. A Hybrid Constructive Algorithm for Single-Layer Feedforward Networks Learning.

    Science.gov (United States)

    Wu, Xing; Rózycki, Paweł; Wilamowski, Bogdan M

    2015-08-01

    Single-layer feedforward networks (SLFNs) have been proven to be a universal approximator when all the parameters are allowed to be adjustable. It is widely used in classification and regression problems. The SLFN learning involves two tasks: determining network size and training the parameters. Most current algorithms could not be satisfactory to both sides. Some algorithms focused on construction and only tuned part of the parameters, which may not be able to achieve a compact network. Other gradient-based optimization algorithms focused on parameters tuning while the network size has to be preset by the user. Therefore, trial-and-error approach has to be used to search the optimal network size. Because results of each trial cannot be reused in another trial, it costs much computation. In this paper, a hybrid constructive (HC)algorithm is proposed for SLFN learning, which can train all the parameters and determine the network size simultaneously. At first, by combining Levenberg-Marquardt algorithm and least-square method, a hybrid algorithm is presented for training SLFN with fixed network size. Then,with the hybrid algorithm, an incremental constructive scheme is proposed. A new randomly initialized neuron is added each time when the training entrapped into local minima. Because the training continued on previous results after adding new neurons, the proposed HC algorithm works efficiently. Several practical problems were given for comparison with other popular algorithms. The experimental results demonstrated that the HC algorithm worked more efficiently than those optimization methods with trial and error, and could achieve much more compact SLFN than those construction algorithms.

  5. In ductive transfer learning for unlabeled target-domainvia hybrid regularization

    Institute of Scientific and Technical Information of China (English)

    ZHUANG FuZhen; LUO Ping; HE Qing; SHI ZhongZhi

    2009-01-01

    Recent years have witnessed an increasing interest in transfer learning. This paper deals with the classification problem that the target-domain with a different distribution from the source-domain is totally unlabeled, and aims to build an inductive model for unseen data. Firstly, we analyze the problem of class ratio drift in the previous work of transductive transfer learning, and propose to use a normalization method to move towards the desired class ratio. Furthermore, we develop a hybrid regularization framework for inductive transfer learning. It considers three factors, including the distribution geometry of the target-domain by manifold regularization, the entropy value of prediction probability by entropy regularization, and the class prior by expectation regularization. This framework is used to adapt the inductive model learnt from the source-domain to the target-domain. Finally, the experiments on the real-world text data show the effectiveness of our inductive method of transfer learning. Meanwhile, it can handle unseen test points.

  6. 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…

  7. 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…

  8. Hybrid independent component analysis and twin support vector machine learning scheme for subtle gesture recognition.

    Science.gov (United States)

    Naik, Ganesh R; Kumar, Dinesh K; Jayadeva

    2010-10-01

    Myoelectric signal classification is one of the most difficult pattern recognition problems because large variations in surface electromyogram features usually exist. In the literature, attempts have been made to apply various pattern recognition methods to classify surface electromyography into components corresponding to the activities of different muscles, but this has not been very successful, as some muscles are bigger and more active than others. This results in dataset discrepancy during classification. Multicategory classification problems are usually solved by solving many, one-versus-rest binary classification tasks. These subtasks unsurprisingly involve unbalanced datasets. Consequently, we need a learning methodology that can take into account unbalanced datasets in addition to large variations in the distributions of patterns corresponding to different classes. Here, we attempt to address the above issues using hybrid features extracted from independent component analysis and twin support vector machine techniques.

  9. Hybridization of Evolutionary Mechanisms for Feature Subset Selection in Unsupervised Learning

    Science.gov (United States)

    Torres, Dolores; Ponce-de-León, Eunice; Torres, Aurora; Ochoa, Alberto; Díaz, Elva

    Feature subset selection for unsupervised learning, is a very important topic in artificial intelligence because it is the base for saving computational resources. In this implementation we use a typical testor’s methodology in order to incorporate an importance index for each variable. This paper presents the general framework and the way two hybridized meta-heuristics work in this NP-complete problem. The evolutionary mechanisms are based on the Univariate Marginal Distribution Algorithm (UMDA) and the Genetic Algorithm (GA). GA and UMDA - Estimation of Distribution Algorithm (EDA) use a very useful rapid operator implemented for finding typical testors on a very large dataset and also, both algorithms, have a local search mechanism for improving time and fitness. Experiments show that EDA is faster than GA because it has a better exploitation performance; nevertheless, GA’ solutions are more consistent.

  10. 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.

  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. SAGA: a hybrid search algorithm for Bayesian Network structure learning of transcriptional regulatory networks.

    Science.gov (United States)

    Adabor, Emmanuel S; Acquaah-Mensah, George K; Oduro, Francis T

    2015-02-01

    Bayesian Networks have been used for the inference of transcriptional regulatory relationships among genes, and are valuable for obtaining biological insights. However, finding optimal Bayesian Network (BN) is NP-hard. Thus, heuristic approaches have sought to effectively solve this problem. In this work, we develop a hybrid search method combining Simulated Annealing with a Greedy Algorithm (SAGA). SAGA explores most of the search space by undergoing a two-phase search: first with a Simulated Annealing search and then with a Greedy search. Three sets of background-corrected and normalized microarray datasets were used to test the algorithm. BN structure learning was also conducted using the datasets, and other established search methods as implemented in BANJO (Bayesian Network Inference with Java Objects). The Bayesian Dirichlet Equivalence (BDe) metric was used to score the networks produced with SAGA. SAGA predicted transcriptional regulatory relationships among genes in networks that evaluated to higher BDe scores with high sensitivities and specificities. Thus, the proposed method competes well with existing search algorithms for Bayesian Network structure learning of transcriptional regulatory networks.

  13. A Hybrid 3D Learning-and-Interaction-based Segmentation Approach Applied on CT Liver Volumes

    Directory of Open Access Journals (Sweden)

    M. Danciu

    2013-04-01

    Full Text Available Medical volume segmentation in various imaging modalities using real 3D approaches (in contrast to slice-by-slice segmentation represents an actual trend. The increase in the acquisition resolution leads to large amount of data, requiring solutions to reduce the dimensionality of the segmentation problem. In this context, the real-time interaction with the large medical data volume represents another milestone. This paper addresses the twofold problem of the 3D segmentation applied to large data sets and also describes an intuitive neuro-fuzzy trained interaction method. We present a new hybrid semi-supervised 3D segmentation, for liver volumes obtained from computer tomography scans. This is a challenging medical volume segmentation task, due to the acquisition and inter-patient variability of the liver parenchyma. The proposed solution combines a learning-based segmentation stage (employing 3D discrete cosine transform and a probabilistic support vector machine classifier with a post-processing stage (automatic and manual segmentation refinement. Optionally, an optimization of the segmentation can be achieved by level sets, using as initialization the segmentation provided by the learning-based solution. The supervised segmentation is applied on elementary cubes in which the CT volume is decomposed by tilling, thus ensuring a significant reduction of the data to be classified by the support vector machine into liver/not liver. On real volumes, the proposed approach provides good segmentation accuracy, with a significant reduction in the computational complexity.

  14. 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.

  15. 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

  16. Conditional Random Field (CRF-Boosting: Constructing a Robust Online Hybrid Boosting Multiple Object Tracker Facilitated by CRF Learning

    Directory of Open Access Journals (Sweden)

    Ehwa Yang

    2017-03-01

    Full Text Available Due to the reasonably acceptable performance of state-of-the-art object detectors, tracking-by-detection is a standard strategy for visual multi-object tracking (MOT. In particular, online MOT is more demanding due to its diverse applications in time-critical situations. A main issue of realizing online MOT is how to associate noisy object detection results on a new frame with previously being tracked objects. In this work, we propose a multi-object tracker method called CRF-boosting which utilizes a hybrid data association method based on online hybrid boosting facilitated by a conditional random field (CRF for establishing online MOT. For data association, learned CRF is used to generate reliable low-level tracklets and then these are used as the input of the hybrid boosting. To do so, while existing data association methods based on boosting algorithms have the necessity of training data having ground truth information to improve robustness, CRF-boosting ensures sufficient robustness without such information due to the synergetic cascaded learning procedure. Further, a hierarchical feature association framework is adopted to further improve MOT accuracy. From experimental results on public datasets, we could conclude that the benefit of proposed hybrid approach compared to the other competitive MOT systems is noticeable.

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

    Directory of Open Access Journals (Sweden)

    Geetanjali Chilkoti

    2016-01-01

    Full Text Available Background and Aims: 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. Methods: 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. Results: 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. Conclusion: Implementation of hybrid-PBL format along with the lecture-based method in BLS/ACLS teaching provided high satisfaction among undergraduate medical students.

  18. 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…

  19. 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.

  20. 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.

  1. Back Analysis of Geomechanical Parameters Using Hybrid Algorithm Based on Difference Evolution and Extreme Learning Machine

    Directory of Open Access Journals (Sweden)

    Zhan-ping Song

    2015-01-01

    Full Text Available Since the geological bodies where tunnels are located have uncertain and complex characteristics, the inverse problem plays an important role in geotechnical engineering. In order to improve the accuracy and speed of surrounding rock identification, the back analysis objective function with usage of the displacement and stress monitoring data has been constructed, with a hybrid algorithm proposed. An extreme learning machine (ELM is employed with optimal architecture trained by the difference evolution (DE arithmetic. First, the three-dimensional numerical simulation is used in the creation of training and testing samples for ELM model construction. Second, the nonlinear relationship between rock parameters and displacement is constructed by numerical simulation. Finally, the geophysics parameters are obtained by DE optimization arithmetic taking into consideration the monitoring data including both displacement and pressure. This method had been applied in the Fusong highway tunnel in Fusong City of China’s Jilin Province, with a good effect obtained. It takes full advantage of DE and ELM and has both calculation speed and precision in the back analysis.

  2. 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.

  3. Application of basic science to clinical problems: traditional vs. hybrid problem-based learning.

    Science.gov (United States)

    Callis, Amber N; McCann, Ann L; Schneiderman, Emet D; Babler, William J; Lacy, Ernestine S; Hale, David Sidney

    2010-10-01

    It is widely acknowledged that clinical problem-solving is a key skill for dental practitioners. The aim of this study was to determine if students in a hybrid problem-based learning curriculum (h-PBL) were better at integrating basic science knowledge with clinical cases than students in a traditional, lecture-based curriculum (TC). The performance of TC students (n=40) was compared to that of h-PBL students (n=31). Participants read two clinical scenarios and answered a series of questions regarding each. To control for differences in ability, Dental Admission Test (DAT) Academic Average scores and predental grade point averages (GPAs) were compared, and an ANCOVA was used to adjust for the significant differences in DAT (t-test, p=0.002). Results showed that h-PBL students were better at applying basic science knowledge to a clinical case (ANCOVA, p=0.022) based on overall scores on one case. TC students' overall scores were better than h-PBL students on a separate case; however, it was not statistically significant (p=0.107). The h-PBL students also demonstrated greater skills in the areas of hypothesis generation (Mann-Whitney U, p=0.016) and communication (p=0.006). Basic science comprehension (p=0.01) and neurology (p<0.001) were two areas in which the TC students did score significantly higher than h-PBL students.

  4. Online Model Learning of Buildings Using Stochastic Hybrid Systems Based on Gaussian Processes

    Directory of Open Access Journals (Sweden)

    Hamzah Abdel-Aziz

    2017-01-01

    Full Text Available Dynamical models are essential for model-based control methodologies which allow smart buildings to operate autonomously in an energy and cost efficient manner. However, buildings have complex thermal dynamics which are affected externally by the environment and internally by thermal loads such as equipment and occupancy. Moreover, the physical parameters of buildings may change over time as the buildings age or due to changes in the buildings’ configuration or structure. In this paper, we introduce an online model learning methodology to identify a nonparametric dynamical model for buildings when the thermal load is latent (i.e., the thermal load cannot be measured. The proposed model is based on stochastic hybrid systems, where the discrete state describes the level of the thermal load and the continuous dynamics represented by Gaussian processes describe the thermal dynamics of the air temperature. We demonstrate the evaluation of the proposed model using two-zone and five-zone buildings. The data for both experiments are generated using the EnergyPlus software. Experimental results show that the proposed model estimates the thermal load level correctly and predicts the thermal behavior with good performance.

  5. Hybrid Metaheuristics

    CERN Document Server

    2013-01-01

    The main goal of this book is to provide a state of the art of hybrid metaheuristics. The book provides a complete background that enables readers to design and implement hybrid metaheuristics to solve complex optimization problems (continuous/discrete, mono-objective/multi-objective, optimization under uncertainty) in a diverse range of application domains. Readers learn to solve large scale problems quickly and efficiently combining metaheuristics with complementary metaheuristics, mathematical programming, constraint programming and machine learning. Numerous real-world examples of problems and solutions demonstrate how hybrid metaheuristics are applied in such fields as networks, logistics and transportation, bio-medical, engineering design, scheduling.

  6. 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.

  7. A Distributed Cooperative Dynamic Task Planning Algorithm for Multiple Satellites Based on Multi-agent Hybrid Learning

    Institute of Scientific and Technical Information of China (English)

    WANG Chong; LI Jun; JING Ning; WANG Jun; CHEN Hao

    2011-01-01

    Traditionally,heuristic re-planning algorithms are used to tackle the problem of dynamic task planning for multiple satellites.However,the traditional heuristic strategies depend on the concrete tasks,which often affect the result's optimality.Noticing that the historical information of cooperative task planning will impact the latter planning results,we propose a hybrid learning algorithrn for dynamic multi-satellite task planning,which is based on the multi-agent reinforcement learning of policy iteration and the transfer learning.The reinforcement learning strategy of each satellite is described with neural networks.The policy neural network individuals with the best topological structure and weights are found by applying co-evolutionary search iteratively.To avoid the failure of the historical learning caused by the randomly occurring observation requests,a novel approach is proposed to balance the quality and efficiency of the task planning,which converts the historical leaming strategy to the current initial learning strategy by applying the transfer learning algorithm.The simulations and analysis show the feasibility and adaptability of the proposed approach especially for the situation with randomly occurring observation requests.

  8. Integrating Internet Video Conferencing Techniques and Online Delivery Systems with Hybrid Classes to Enhance Student Interaction and Learning in Accelerated Programs

    Science.gov (United States)

    Beckwith, E. George; Cunniff, Daniel T.

    2009-01-01

    Online course enrollment has increased dramatically over the past few years. The authors cite the reasons for this rapid growth and the opportunities open for enhancing teaching/learning techniques such as video conferencing and hybrid class combinations. The authors outlined an example of an accelerated learning, eight-class session course…

  9. Preparing Students for Success in Hybrid Learning Environments with Academic Resource Centers

    Science.gov (United States)

    Newman, Daniel; Dickinson, Michael

    2017-01-01

    This chapter describes institutional and andragogical best practices for preparing students to succeed in hybrid courses through the programming of academic resource centers, offers information on how to create peer support systems for students, and outlines some of the common pitfalls for students encountering a hybrid course for the first time.

  10. TAKTAG Two-phase learning method for hybrid statistical/rule-based part-of-speech disambiguation

    CERN Document Server

    Lee, G; Shin, S; Lee, Geunbae; Lee, Jong-Hyeok; Shin, Sanghyun

    1995-01-01

    Both statistical and rule-based approaches to part-of-speech (POS) disambiguation have their own advantages and limitations. Especially for Korean, the narrow windows provided by hidden markov model (HMM) cannot cover the necessary lexical and long-distance dependencies for POS disambiguation. On the other hand, the rule-based approaches are not accurate and flexible to new tag-sets and languages. In this regard, the statistical/rule-based hybrid method that can take advantages of both approaches is called for the robust and flexible POS disambiguation. We present one of such method, that is, a two-phase learning architecture for the hybrid statistical/rule-based POS disambiguation, especially for Korean. In this method, the statistical learning of morphological tagging is error-corrected by the rule-based learning of Brill [1992] style tagger. We also design the hierarchical and flexible Korean tag-set to cope with the multiple tagging applications, each of which requires different tag-set. Our experiments s...

  11. Repetitive Learning Control for Time-varying Robotic Systems: A Hybrid Learning Scheme%时变机器人系统的重复学习控制:一种混合学习方案

    Institute of Scientific and Technical Information of China (English)

    孙明轩; 何熊熊; 陈冰玉

    2007-01-01

    Repetitive learning control is presented for finitetime-trajectory tracking of uncertain time-varying robotic systems. A hybrid learning scheme is given to cope with the constant and time-varying unknowns in system dynamics, where the time functions are learned in an iterative learning way, without the aid of Taylor expression, while the conventional differential learning method is suggested for estimating the constant ones.It is distinct that the presented repetitive learning control avoids the requirement for initial repositioning at the beginning of each cycle, and the time-varying unknowns are not necessary to be periodic. It is shown that with the adoption of hybrid learning,the boundedness of state variables of the closed-loop system is guaranteed and the tracking error is ensured to converge to zero as iteration increases. The effectiveness of the proposed scheme is demonstrated through numerical simulation.

  12. FORECASTING CHINA'S FOREIGN TRADE VOLUME WITH A KERNEL-BASED HYBRID EC-ONOMETRIC-AI ENSEMBLE LEARNING APPROACH

    Institute of Scientific and Technical Information of China (English)

    Lean YU; Shouyang WANG; Kin Keung LAI

    2008-01-01

    Due to the complexity of economic system and the interactive effects between all kinds of economic variables and foreign trade, it is not easy to predict foreign trade volume. However, the difficulty in predicting foreign trade volume is usually attributed to the limitation of many conventional forecasting models. To improve the prediction performance, the study proposes a novel kernel-based ensemble learning approach hybridizing econometric models and artificial intelligence (AI) models to predict China's foreign trade volume. In the proposed approach, an important econometric model, the co-integration-based error correction vector auto-regression (EC-VAR) model is first used to capture the impacts of all kinds of economic variables on Chinese foreign trade from a multivariate linear anal-ysis perspective. Then an artificial neural network (ANN) based EC-VAR model is used to capture the nonlinear effects of economic variables on foreign trade from the nonlinear viewpoint. Subsequently, for incorporating the effects of irregular events on foreign trade, the text mining and expert's judgmental adjustments are also integrated into the nonlinear ANN-based EC-VAR model. Finally, all kinds of economic variables, the outputs of linear and nonlinear EC-VAR models and judgmental adjustment model are used as input variables of a typical kernel-based support vector regression (SVR) for en-semble prediction purpose. For illustration, the proposed kernel-based ensemble learning methodology hybridizing econometric techniques and AI methods is applied to China's foreign trade volume predic-tion problem. Experimental results reveal that the hybrid econometric-AI ensemble learning approach can significantly improve the prediction performance over other linear and nonlinear models listed in this study.

  13. 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.

  14. 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.

  15. An Examination of Collaborative Learning Assessment through Dialogue (CLAD) in Traditional and Hybrid Human Development Courses

    Science.gov (United States)

    McCarthy, Wanda C.; Green, Peter J.; Fitch, Trey

    2010-01-01

    This investigation assessed the effectiveness of using Collaborative Learning Assessment through Dialogue (CLAD) (Fitch & Hulgin, 2007) with students in undergraduate human development courses. The key parts of CLAD are student collaboration, active learning, and altering the role of the instructor to a guide who enhances learning opportunities.…

  16. 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…

  17. 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.

  18. 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...

  19. Hybrid Courses and Online Policy Dialogues: A Transborder Distance Learning Collaboration

    Science.gov (United States)

    Pollock, Katina E.; Winton, Sue M.

    2011-01-01

    This essay describes a blended (hybrid) course collaboration used to facilitate policy dialogues between graduate students at two institutions (one in Canada and the other in the US) as a way to teach about policy. The course content and design is informed by three trends in research and practice: increased policy borrowing across boundaries and…

  20. 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…

  1. The TREEhouse: A Hybrid Model for Experiential Learning in Environmental Education

    Science.gov (United States)

    Corscadden, Kenneth W.; Kevany, Kathleen

    2017-01-01

    This article addresses the need to integrate experiential learning into environmental and sustainability curriculum and considers the challenges faced by academic institutions in providing relevant experiential learning opportunities at an appropriate scale. Through an experiential case study, this article illustrates how adopting a "hybrid…

  2. Hybrid Learning: A Study of Training Environment and Training Transfer in Ecuador

    Science.gov (United States)

    Diaz, Karla

    2013-01-01

    Training transfer can be analyzed in the workplace by studying the results of a validated instrument like the Learning Transfer System Inventory (LTSI) developed by Holton and Bates (2011). This correlational study used the Spearman rho correlation coefficient to examine the relationship between transfer design and opportunity to use learning as…

  3. Simulating light-weight Personalised Recommender Systems in Learning Networks: A case for Pedagogy-Oriented and Rating-based Hybrid Recommendation Strategies

    NARCIS (Netherlands)

    Nadolski, Rob; Van den Berg, Bert; Berlanga, Adriana; Drachsler, Hendrik; Hummel, Hans; Koper, Rob; Sloep, Peter

    2008-01-01

    Nadolski, R. J., Van den Berg, B., Berlanga, A. J., Drachsler, H., Hummel, H. G. K., Koper, R., & Sloep, P. B. (2009). Simulating Light-Weight Personalised Recommender Systems in Learning Networks: A Case for Pedagogy-Oriented and Rating-Based Hybrid Recommendation Strategies. Journal of Artificial

  4. PREDICTION OF TOOL CONDITION DURING TURNING OF ALUMINIUM/ALUMINA/GRAPHITE HYBRID METAL MATRIX COMPOSITES USING MACHINE LEARNING APPROACH

    Directory of Open Access Journals (Sweden)

    N. RADHIKA

    2015-10-01

    Full Text Available Aluminium/alumina/graphite hybrid metal matrix composites manufactured using stir casting technique was subjected to machining studies to predict tool condition during machining. Fresh tool as well as tools with specific amount of wear deliberately created prior to machining experiments was used. Vibration signals were acquired using an accelerometer for each tool condition. These signals were then processed to extract statistical and histogram features to predict the tool condition during machining. Two classifiers namely, Random Forest and Classification and Regression Tree (CART were used to classify the tool condition. Results showed that histogram features with Random Forest classifier yielded maximum efficiency in predicting the tool condition. This machine learning approach enables the prediction of tool failure in advance, thereby minimizing the unexpected breakdown of tool and machine.

  5. Hybrid Short Term Wind Speed Forecasting Using Variational Mode Decomposition and a Weighted Regularized Extreme Learning Machine

    Directory of Open Access Journals (Sweden)

    Nantian Huang

    2016-11-01

    Full Text Available Accurate wind speed forecasting is a fundamental element of wind power prediction. Thus, a new hybrid wind speed forecasting model, using variational mode decomposition (VMD, the partial autocorrelation function (PACF, and weighted regularized extreme learning machine (WRELM, is proposed to improve the accuracy of wind speed forecasting. First, the historic wind speed time series is decomposed into several intrinsic mode functions (IMFs. Second, the partial correlation of each IMF sequence is analyzed using PACF to select the optimal subfeature set for particular predictors of each IMF. Then, the predictors of each IMF are constructed in order to enhance its strength using WRELM. Finally, wind speed is obtained by adding up all the predictors. The experiment, using real wind speed data, verified the effectiveness and advancement of the new approach.

  6. 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.

  7. Estimation of algal colonization growth on mortar surface using a hybridization of machine learning and metaheuristic optimization

    Indian Academy of Sciences (India)

    THU-HIEN TRAN; NHAT-DUC HOANG

    2017-06-01

    Estimation of the algal colonization growth on fac¸ade structure can provide useful information for the task of building maintenance. This research proposes a machine learning method based on the least squares support vector regression (LS-SVR) for modelling the growth time of the green alga Klebsormidium flaccidum on mortar surfaces. Furthermore, to identify an appropriate set of the LS-SVR hyper-parameters, the flower pollination algorithm (FPA) is employed as an optimization technique. The characteristics of the mortar samples, including surface roughness, porosity, surface pH, carbonated condition and type of cement, are employed as input factors for the analysing process. This study relies on a dataset that records 539 laboratory experiments to establish a hybrid model of the LS-SVR and the FPA. The cross-validation process reveals that the proposed method can successfully capture the functional relationship between the algal colonization growth and its influencing factors with a satisfactory outcome (the coefficient of determination R 2 = 0.94 and the root meansquare error RMSE = 4.55). These facts demonstrate that the hybrid model is a promising tool for assisting the decision-making process in building maintenance planning

  8. 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

  9. Exploring learning content and knowledge transfer in baccalaureate nursing students using a hybrid mental health practice experience.

    Science.gov (United States)

    Booth, Richard G; Scerbo, Christina Ko; Sinclair, Barbara; Hancock, Michele; Reid, David; Denomy, Eileen

    2017-04-01

    Little research has been completed exploring knowledge development and transfer from and between simulated and clinical practice settings in nurse education. This study sought to explore the content learned, and the knowledge transferred, in a hybrid mental health clinical course consisting of simulated and clinical setting experiences. A qualitative, interpretive descriptive study design. Clinical practice consisted of six 10-hour shifts in a clinical setting combined with six two-hour simulations. 12 baccalaureate nursing students enrolled in a compressed time frame program at a large, urban, Canadian university participated. Document analysis and a focus group were used to draw thematic representations of content and knowledge transfer between clinical environments (i.e., simulated and clinical settings) using the constant comparative data analysis technique. Four major themes arose: (a) professional nursing behaviors; (b) understanding of the mental health nursing role; (c) confidence gained in interview skills; and, (d) unexpected learning. Nurse educators should further explore the intermingling of simulation and clinical practice in terms of knowledge development and transfer with the goal of preparing students to function within the mental health nursing specialty. Copyright © 2017 Elsevier Ltd. All rights reserved.

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

    Science.gov (United States)

    Shang, Qiang; Lin, Ciyun; Yang, Zhaosheng; Bing, Qichun; Zhou, Xiyang

    2016-01-01

    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.

  11. Evaluation of the Plug-in Hybrid Electric Vehicle Considering Learning Curve on Battery and Power Generation Best Mix

    Science.gov (United States)

    Shinoda, Yukio; Tanaka, Hideo; Akisawa, Atsushi; Kashiwagi, Takao

    Plug-in Hybrid Electric Vehicle (PHEV) is one of the technologies to reduce amount of CO2 emissions in transport section. This paper presents one of the scenarios that shows how widely used the PHEVs will be in the future. And this paper also presents how amount of CO2 will be reduced by the introduction of PHEVs, and whether there are any serious effects on power supply system in those scenarios. PHEV can run with both gasoline and electricity. Therefore we evaluate CO2 emissions not only from gasoline consumption but also from electricity consumption. To consider a distribution of daily-trip-distance is important for evaluating the economical merit and CO2 emissions by introducing of PHEV. Also, the battery cost in the future is very important for making a PHEV's growth scenario. The growth of the number of PHEV makes battery cost lower. Then, we formulate the total model that combines passenger car sector and power supply sector with considering a distribution of daily-trip-distance and Learning Curve on battery costs. We use the iteration method to consider a Learning Curve that is non- linear. Therefore we set battery cost only in the first year of the simulation. Battery costs in the later year are calculated in the model. We focus on the 25-year time frame from 2010 in Japan, with divided in 5 terms (1st∼5th). And that model selects the most economical composition of car type and power sources.

  12. 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…

  13. 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…

  14. 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…

  15. 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

  16. Structuring a Clinical Learning Environment for a Hybrid-PBL Dental Curriculum.

    Science.gov (United States)

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

    1998-01-01

    Describes the evolution and implementation of a joint medical-dental problem-based learning (PBL) curriculum at the University of British Columbia's medical and dental schools, featuring development of an integrated care clinic. Issues in structuring the new curriculum are discussed, including management of the clinic's group practices, affective…

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

    NARCIS (Netherlands)

    S.D. Bekiros

    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 se

  18. 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…

  19. "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…

  20. 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 from a…

  1. 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.

  2. Structural Acoustic Response of a Shape Memory Alloy Hybrid Composite Panel (Lessons Learned)

    Science.gov (United States)

    Turner, Travis L.

    2002-01-01

    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.

  3. Two kinds of attention in Pavlovian conditioning: evidence for a hybrid model of learning.

    Science.gov (United States)

    Haselgrove, Mark; Esber, Guillem R; Pearce, John M; Jones, Peter M

    2010-10-01

    Four appetitive Pavlovian conditioning experiments with rats examined the rate at which the discrimination between compounds AY and AX was solved relative to the discrimination between compounds AY and BY. In Experiments 1 and 2, these discriminations were preceded by training in which A and B were continuously reinforced and X and Y were partially reinforced. Consistent with the Pearce and Hall (1980) model, the results showed that the AY/AX discrimination was solved more readily than the AY/BY discrimination. In Experiments 3 and 4, the discriminations were preceded by feature-positive training in which trials with AX and BY signaled food but trials with X and Y did not. Consistent with the Mackintosh (1975) model, the results showed that the AY/BY discrimination was solved more readily than the AY/AX discrimination. These results are discussed with respect to a hybrid model of conditioning and attention.

  4. Teachers Learning to Research Climate: Development of hybrid teacher professional development to support climate inquiry and research in the classroom

    Science.gov (United States)

    Odell, M. R.; Charlevoix, D. J.; Kennedy, T.

    2011-12-01

    The GLOBE Program is an international science and education focused on connecting scientists, teachers and students around relevant, local environmental issues. GLOBE's focus during the next two years in on climate, global change and understanding climate from a scientific perspective. The GLOBE Student Climate Research Campaign (SCRFC) will engage youth from around the world in understanding and researching climate through investigations of local climate challenges. GLOBE teachers are trained in implementation of inquiry in the classroom and the use of scientific data collection protocols to develop inquiry and research projects of the Earth System. In preparation for the SCRC, GLOBE teachers will need additional training in climate science, global change and communicating climate science in the classroom. GLOBE's reach to 111 countries around the world requires development of scalable models for training teachers. In June GLOBE held the first teacher professional development workshop (Learning to Research Summer Institute) in a hybrid format with two-thirds of the teachers participating face-to-face and the remaining teachers participating virtually using Adobe Connect. The week long workshop prepared teachers to integrate climate science inquiry and research projects in the classrooms in the 2011-12 academic year. GLOBE scientists and other climate science experts will work with teachers and their students throughout the year in designing and executing a climate science research project. Final projects and research results will be presented in May 2012 through a virtual conference. This presentation will provide the framework for hybrid teacher professional development in climate science research and inquiry projects as well as summarize the findings from this inaugural session. The GLOBE Program office, headquartered in Boulder, is funded through cooperative agreements with NASA and NOAA with additional support from NSF and the U.S. Department of State. GLOBE

  5. Hybrid Machine Learning Technique for Forecasting Dhaka Stock Market Timing Decisions

    OpenAIRE

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

    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 unsigh...

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

    CERN Document Server

    Preisler, Bent; Fabricius, Anne H

    2011-01-01

    This book views the international university as a microcosm of a world where internationalization does not equate with across-the-board use of English, but rather with the practice of linguistic and cultural diversity, even in the face of Anglophone dominance. The globalization-localization continuum manifests itself in every university trying to adopt internationalization strategies. The many cases of language and learning issues presented in this book, from universities representing different parts of the world, are all manifestations of a multidimensional space encompassing local vs. global

  8. A hybrid feature selection algorithm integrating an extreme learning machine for landslide susceptibility modeling of Mt. Woomyeon, South Korea

    Science.gov (United States)

    Vasu, Nikhil N.; Lee, Seung-Rae

    2016-06-01

    An ever-increasing trend of extreme rainfall events in South Korea owing to climate change is causing shallow landslides and debris flows in mountains that cover 70% of the total land area of the nation. These catastrophic, gravity-driven processes cost the government several billion KRW (South Korean Won) in losses in addition to fatalities every year. The most common type of landslide observed is the shallow landslide, which occurs at 1-3 m depth, and may mobilize into more catastrophic flow-type landslides. Hence, to predict potential landslide areas, susceptibility maps are developed in a geographical information system (GIS) environment utilizing available morphological, hydrological, geotechnical, and geological data. Landslide susceptibility models were developed using 163 landslide points and an equal number of nonlandslide points in Mt. Woomyeon, Seoul, and 23 landslide conditioning factors. However, because not all of the factors contribute to the determination of the spatial probability for landslide initiation, and a simple filter or wrapper-based approach is not efficient in identifying all of the relevant features, a feedback-loop-based hybrid algorithm was implemented in conjunction with a learning scheme called an extreme learning machine, which is based on a single-layer, feed-forward network. Validation of the constructed susceptibility model was conducted using a testing set of landslide inventory data through a prediction rate curve. The model selected 13 relevant conditioning factors out of the initial 23; and the resulting susceptibility map shows a success rate of 85% and a prediction rate of 89.45%, indicating a good performance, in contrast to the low success and prediction rate of 69.19% and 56.19%, respectively, as obtained using a wrapper technique.

  9. 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; 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

  10. 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.

  11. 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.

  12. 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

  13. 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.

  14. 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…

  15. 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…

  16. Expanding Discourse Repertoires with Hybridity

    Science.gov (United States)

    Kelly, Gregory J.

    2012-01-01

    In "Hybrid discourse practice and science learning" Kamberelis and Wehunt present a theoretically rich argument about the potential of hybrid discourses for science learning. These discourses draw from different forms of "talk, social practice, and material practices" to create interactions that are "intertextually complex" and "interactionally…

  17. Hybrid learning machines

    OpenAIRE

    Abraham, Ajith; Corchado Rodríguez, Emilio Santiago; Corchado Rodríguez, Juan Manuel

    2010-01-01

    [ES] El concepto de máquina inteligente (MI ) es compleja , y por lo tanto muchas teorías y definiciones han surgido en las últimas décadas. Últimamente se ha puesto especial atención en las maquinas inteligentes , los aspectos teóricos y la metodología de diseño de algoritmos recogidos de la naturaleza y la biología. Ejemplos de ello son las redes neuronales artificiales inspiradas en los sistemas neuronales de mamífero, la computación evolutiva en araña por la selección natural en la biol...

  18. 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…

  19. 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.

  20. Hybrid Platforms, Tools, and Resources

    Science.gov (United States)

    Linder, Kathryn E.; Bruenjes, Linda S.; Smith, Sarah A.

    2017-01-01

    This chapter discusses common tools and resources for building a hybrid course in a higher education setting and provides recommendations for best practices in Learning Management Systems and Open Educational Resources.

  1. Hybrid Baryons

    CERN Document Server

    Page, P R

    2003-01-01

    We review the status of hybrid baryons. The only known way to study hybrids rigorously is via excited adiabatic potentials. Hybrids can be modelled by both the bag and flux-tube models. The low-lying hybrid baryon is N 1/2^+ with a mass of 1.5-1.8 GeV. Hybrid baryons can be produced in the glue-rich processes of diffractive gamma N and pi N production, Psi decays and p pbar annihilation.

  2. 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.

  3. 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.

  4. 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…

  5. 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…

  6. 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…

  7. 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.

  8. Active learning in forensic science using Brownfield Action in a traditional or hybrid course in earth, environmental, or engineering sciences

    Science.gov (United States)

    Bower, P.; Liddicoat (2), J.

    2009-04-01

    Brownfield Action (BA - http://www.brownfieldaction.org) is a web-based, interactive, three-dimensional digital space and learning simulation in which students form geotechnical consulting companies and work collaboratively to explore and solve problems in environmental forensics. BA is being used in the United States at 10 colleges and universities in earth, environmental, or engineering sciences undergraduate and graduate courses. As a semester-long activity or done in modular form for specific topics, BA encourages active learning that requires attention to detail, intuition, and positive interaction between peers that results in Phase 1 and Phase 2 Environmental Site Assessments. Besides use in higher education courses, BA also can be adapted for instruction to local, state, and federal governmental employees, and employees in industry where brownfields need to be investigated or require remediation.

  9. An improved hybrid intelligent extreme learning machine%一种新的混合智能极限学习机

    Institute of Scientific and Technical Information of China (English)

    林梅金; 罗飞; 苏彩红; 许玉格

    2015-01-01

    An improved hybrid intelligent algorithm based on differential evolution(DE) and particle swarm optimization (PSO) is proposed. The performance of DEPSO algorithm is verified by simulations on 10 benchmark functions. Then, an improved learning algorithm named DEPSO extreme learning machine(DEPSO-ELM) algorithm for single hidden layer feedforward networks(SLFNs) is proposed. In DEPSO-ELM, DEPSO is used to optimize the network hidden node parameters, and ELM is used to analytically determine the output weights. Simulation results of 6 real world datasets regression problems show that the DEPSO-ELM algorithm performs better than DE-ELM and SaE-ELM. Finally, the effectiveness of the DEPSO-ELM algorithm is verified in the prediction of NC machine tool thermal errors.%提出一种基于差分进化(DE)和粒子群优化(PSO)的混合智能方法—–DEPSO算法,并通过对10个典型函数进行测试,表明DEPSO算法具有良好的寻优性能。针对单隐层前向神经网络(SLFNs)提出一种改进的学习算法—–DEPSO-ELM算法,即应用DEPSO算法优化SLFNs的隐层节点参数,采用极限学习算法(ELM)求取SLFNs的输出权值。将DEPSO-ELM算法应用于6个典型真实数据集的回归计算,并与DE-ELM、SaE-ELM算法相比,获得了更精确的计算结果。最后,将DEPSO-ELM算法应用于数控机床热误差的建模预测,获得了良好的预测效果。

  10. Hybrid vehicles

    Energy Technology Data Exchange (ETDEWEB)

    West, J.G.W. [Electrical Machines (United Kingdom)

    1997-07-01

    The reasons for adopting hybrid vehicles result mainly from the lack of adequate range from electric vehicles at an acceptable cost. Hybrids can offer significant improvements in emissions and fuel economy. Series and parallel hybrids are compared. A combination of series and parallel operation would be the ideal. This can be obtained using a planetary gearbox as a power split device allowing a small generator to transfer power to the propulsion motor giving the effect of a CVT. It allows the engine to run at semi-constant speed giving better fuel economy and reduced emissions. Hybrid car developments are described that show the wide range of possible hybrid systems. (author)

  11. 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.

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

    Science.gov (United States)

    Tuo, Shouheng; Yong, Longquan; Deng, Fang’an; Li, Yanhai; Lin, Yong; Lu, Qiuju

    2017-01-01

    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. PMID:28403224

  13. Estimation of in-situ bioremediation system cost using a hybrid Extreme Learning Machine (ELM)-particle swarm optimization approach

    Science.gov (United States)

    Yadav, Basant; Ch, Sudheer; Mathur, Shashi; Adamowski, Jan

    2016-12-01

    In-situ bioremediation is the most common groundwater remediation procedure used for treating organically contaminated sites. A simulation-optimization approach, which incorporates a simulation model for groundwaterflow and transport processes within an optimization program, could help engineers in designing a remediation system that best satisfies management objectives as well as regulatory constraints. In-situ bioremediation is a highly complex, non-linear process and the modelling of such a complex system requires significant computational exertion. Soft computing techniques have a flexible mathematical structure which can generalize complex nonlinear processes. In in-situ bioremediation management, a physically-based model is used for the simulation and the simulated data is utilized by the optimization model to optimize the remediation cost. The recalling of simulator to satisfy the constraints is an extremely tedious and time consuming process and thus there is need for a simulator which can reduce the computational burden. This study presents a simulation-optimization approach to achieve an accurate and cost effective in-situ bioremediation system design for groundwater contaminated with BTEX (Benzene, Toluene, Ethylbenzene, and Xylenes) compounds. In this study, the Extreme Learning Machine (ELM) is used as a proxy simulator to replace BIOPLUME III for the simulation. The selection of ELM is done by a comparative analysis with Artificial Neural Network (ANN) and Support Vector Machine (SVM) as they were successfully used in previous studies of in-situ bioremediation system design. Further, a single-objective optimization problem is solved by a coupled Extreme Learning Machine (ELM)-Particle Swarm Optimization (PSO) technique to achieve the minimum cost for the in-situ bioremediation system design. The results indicate that ELM is a faster and more accurate proxy simulator than ANN and SVM. The total cost obtained by the ELM-PSO approach is held to a minimum

  14. 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.

  15. 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...

  16. Hybrid composites

    CSIR Research Space (South Africa)

    Jacob John, Maya

    2009-04-01

    Full Text Available effect was observed for the elongation at break of the hybrid composites. The impact strength of the hybrid composites increased with the addition of glass fibres. The tensile and impact properties of thermoplastic natural rubber reinforced short... panels made from conventional structural materials. Figure 3 illustrates the performance of cellular biocomposite panels against conventional systems used for building and residential construction, namely a pre- cast pre-stressed hollow core concrete...

  17. 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.

  18. 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

  19. 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.

  20. 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…

  1. 4 Keys to a Better Hybrid

    Science.gov (United States)

    Schaffhauser, Dian

    2012-01-01

    Blended learning has become a meme. While mixing online instruction with face-to-face time is not exactly new, momentum for hybrid learning has been building ever since a Department of Education meta-study in 2010 quietly announced that traditional education simply does not stack up. In that study, online education was determined to be more…

  2. 4 Keys to a Better Hybrid

    Science.gov (United States)

    Schaffhauser, Dian

    2012-01-01

    Blended learning has become a meme. While mixing online instruction with face-to-face time is not exactly new, momentum for hybrid learning has been building ever since a Department of Education meta-study in 2010 quietly announced that traditional education simply does not stack up. In that study, online education was determined to be more…

  3. 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

  4. Hybrid manifold embedding.

    Science.gov (United States)

    Liu, Yang; Liu, Yan; Chan, Keith C C; Hua, Kien A

    2014-12-01

    In this brief, we present a novel supervised manifold learning framework dubbed hybrid manifold embedding (HyME). Unlike most of the existing supervised manifold learning algorithms that give linear explicit mapping functions, the HyME aims to provide a more general nonlinear explicit mapping function by performing a two-layer learning procedure. In the first layer, a new clustering strategy called geodesic clustering is proposed to divide the original data set into several subsets with minimum nonlinearity. In the second layer, a supervised dimensionality reduction scheme called locally conjugate discriminant projection is performed on each subset for maximizing the discriminant information and minimizing the dimension redundancy simultaneously in the reduced low-dimensional space. By integrating these two layers in a unified mapping function, a supervised manifold embedding framework is established to describe both global and local manifold structure as well as to preserve the discriminative ability in the learned subspace. Experiments on various data sets validate the effectiveness of the proposed method.

  5. 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.

  6. Optimization of fractional PID controller based on hybrid computation intelligent learning algorithm%基于混合计算智能的分数阶PID控制器参数优化

    Institute of Scientific and Technical Information of China (English)

    毛书军; 盛贤君

    2014-01-01

    In order to solve the challenging problem of optimization of five-dimensional parameters in fractional PID controller, based on the introduction of swarm intelligence algorithm and evolutionary computing, a hybrid computation intelligent learning algorithm was proposed, which combined Glowworm Swarm Optimization ( GSO) with Genetic Algorithm ( GA) . The hybrid algorithm was based on the swarm intelligence and individual evolution of creatures, which can greatly increase the accuracy of optimization and ensure that algorithm evolves to optimum. A series of experiments verify that the proposed hybrid algorithm can shorten the time of computing and increase the accuracy of simulation.%为解决分数阶PID控制器五维参数优化的难题,设计了一种把萤火虫算法和遗传算法相结合的混合计算智能算法,阐述了计算智能中的群智能算法和进化计算的基本原理和数学算法。该方法基于生物的群体智能和个体进化相结合的思想,能够有效地提高寻优精度,并使算法向最优方向不断进化。经过仿真验证,混合算法在分数阶PID参数整定方面具有运算时间短、仿真精度高等优点。

  7. 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.

  8. Hybrid microelectronic technology

    Science.gov (United States)

    Moran, P.

    Various areas of hybrid microelectronic technology are discussed. The topics addressed include: basic thick film processing, thick film pastes and substrates, add-on components and attachment methods, thin film processing, and design of thick film hybrid circuits. Also considered are: packaging hybrid circuits, automating the production of hybrid circuits, application of hybrid techniques, customer's view of hybrid technology, and quality control and assurance in hybrid circuit production.

  9. 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…

  10. Expanding discourse repertoires with hybridity

    Science.gov (United States)

    Kelly, Gregory J.

    2012-09-01

    In "Hybrid discourse practice and science learning" Kamberelis and Wehunt present a theoretically rich argument about the potential of hybrid discourses for science learning. These discourses draw from different forms of "talk, social practice, and material practices" to create interactions that are "intertextually complex" and "interactionally dynamic." The hybrid discourse practices are described as involving the dynamic interplay of at least three key elements: "the lamination of multiple cultural frames, the shifting relations between people and their discourse, and the shifting power relations between and among people." Each of these elements requires a respective unit of analysis and are often mutually reinforcing. The authors present a theoretically cogent argument for the study of hybrid discourse practices and identify the potential such discourses may have for science education. This theoretical development leads to an analysis of spoken and written discourse around a set of educational events concerning the investigation of owl pellets by two fifth grade students, their classmates, and teacher. Two discourse segments are presented and analyzed by the authors in detail. The first is a discourse analysis of the dissection of the owl pellet by two students, Kyle and Max. The second analysis examines the science report of these same two students. In this article, I pose a number of questions about the study with the hope that by doing so I expand the conversation around the insightful analysis presented.

  11. 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.

  12. Hybrid Qualifications

    DEFF Research Database (Denmark)

    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...... masters», i.e. by producing skills for the labour market and enabling individuals to progress more or less directly to higher education. The specific focus of this book is placed on conditions, structures and processes which help to combine VET with qualifications leading into higher education...

  13. The Effectiveness of Hybrid Solutions in Higher Education: A Call for Hybrid-Teaching Instructional Design

    Science.gov (United States)

    Trentin, Guglielmo; Bocconi, Stefania

    2014-01-01

    In order to design learning solutions that effectively embed face-to-face and online dimensions, it is crucial to identify the key components underpinning hybrid solutions. Furthermore, once these components have been identified, there is the need to clarify how to recombine them to meet a specific learning objective. This article aims to…

  14. 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....

  15. Continuity Controlled Hybrid Automata

    OpenAIRE

    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 hybrid automata as timed transition systems. We also relate the synchronized product operator on hybrid automata to the parallel composition operator of the process algebra. It turns out that the f...

  16. Student Engagement in a Large Classroom: Using Technology to Generate a Hybridized Problem- Based Learning Experience in a Large First Year Undergraduate Class

    Science.gov (United States)

    Fukuzawa, Sherry; Boyd, Cleo

    2016-01-01

    Large first year undergraduate courses have unique challenges in the promotion of student engagement and self-directed learning due to resource constraints that prohibit small group discussions with instructors. The Monthly Virtual Mystery was developed to increase student engagement in a large (N = 725) first year undergraduate class in…

  17. Learning and Design Processes in a Gamified Learning Design in which Students Create Curriculum-Based Digital Learning Games

    DEFF Research Database (Denmark)

    Weitze, Charlotte Lærke

    2017-01-01

    ’ cognitively complex learning processes, and how four parallel types of processes for designing and learning supported this gamified learning design. The experiment took place in a hybrid synchronous learning environment. The project found that the students experienced deep and motivating learning...

  18. Hybridized tetraquarks

    Directory of Open Access Journals (Sweden)

    A. Esposito

    2016-07-01

    Full Text Available 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 but rather a manifestation of the interplay between the two. While meson molecules need a negative or zero binding energy, its counterpart for h-tetraquarks is required to be positive. 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 Bs0π± 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.

  19. 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.

  20. On-Line Dynamic Index Hybrid Update Scheme Based on Self-Learning of Allocated Space%基于分配空间自学习的在线动态索引混合更新机制

    Institute of Scientific and Technical Information of China (English)

    刘小珠; 彭智勇

    2012-01-01

    To improve time and space efficiencies of index maintenance, an on-line dynamic index hybrid update (ODIHU) technique is proposed based on self-learning of allocated space. Based on Zipf theorem, ODIHU appropriately estimates the number of short and long lists with theoretical analysis, and manages short and long lists with uniform storage model of distinguishing long and short lists based on link. ODIHU manages long list space with history-based adaptive learning allocation (HALA) , and manages short list space with linear allocation (LA), exponential allocation (EA) , and uniform allocation (UA). To decrease index and retrieval cost, ODIHU divides index data set into limited sections and controls index merge with schemes. Then ODIHU merges short lists with immediate merge, and merges long lists with improved Y-limited contiguous multiple merge scheme, which balances the trade-off of the time and space efficiencies effectively. Based on the proposed RABIF, ODIHU not only considers both index level and inverted list level updating, but also effectively improves time and space efficiencies of index updating.%针对索引维护时间和空间效率低的问题,提出了一种基于分配空间自学习的在线动态索引混合更新机制(on-line dynamic index hybrid update,ODIHU).ODIHU根据Zipf分布原理对长短列表数量分布进行估计,并采用基于历史分配空间的自适应学习机制对长短列表空间进行有效管理,然后对短列表采用立即合并更新方式,长列表采用上限Y相邻多路合并的更新方式维护,实现索引更新与查询性能的有效折中.理论分析及实验结果表明,ODIHU能有效地提高索引维护与更新过程中的空间效率、索引合并与查询时间效率.

  1. 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

  2. Continuity controlled Hybrid Automata

    NARCIS (Netherlands)

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

    2008-01-01

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

  3. Improved performance of students instructed in a hybrid PBL format.

    Science.gov (United States)

    Lian, Jiqin; He, Fengtian

    2013-01-01

    As a result of enrollment expansion, increasing numbers of students are entering into medical school in China. This combined with a shortage of teachers, means that the learning environment typically consists of a large classroom setting with traditional lecture-based learning (LBL) as the major mode to teaching and learning. In this article, we investigate the preferences for hybrid problem-based learning (hybrid-PBL) or LBL in a large classroom setting. Two hundred five second-year undergraduate students in Third Military Medical University were randomly divided to two groups. The hybrid-PBL group contained 101 students and was taught by hybrid LBL (60%) and tutor-less PBL(40%) in a large classroom. The LBL group consisted of 104 students and was taught by LBL in a large classroom too. Post-teaching performance was assessed by multiple choice questions, short-essay questions, and case-analysis questions, while the students' teaching preferences and satisfaction were assessed by questionnaires. Analysis of the results of both groups in the examination of biochemistry revealed significantly higher scores on short-essay questions and case-analysis questions in the hybrid-PBL group. Students considered hybrid-PBL to be an effective learning method and favored it over the lecture format. Furthermore, students reported positive effects of hybrid-PBL in terms of additional learning resources, critical thinking, and fun learning experiences. These results suggest that hybrid-PBL is better than the traditional LBL method at improving students' basic knowledge and problem-solving skills. Students preferred hybrid-PBL and were satisfied with it. The tutor-less PBL pattern in a large classroom setting may be feasible in Chinese medical schools. Copyright © 2012 International Union of Biochemistry and Molecular Biology, Inc.

  4. Guiding Professional Life-long Learning Projects: The Case of an Immersive Blended Learning Certificate | Accompagner des projets professionnels en formation continue : le cas d’un certificat de formation hybride et immersive

    Directory of Open Access Journals (Sweden)

    Kalliopi Benetos

    2015-11-01

    Full Text Available This case study presents a blended learning study program offered as a continuing education certificate of advanced studies for post-secondary educators and training professionals in the private, non-governmental, and public sectors. This accredited certificate program is unique in that it allows participants to propose and develop their own practical pedagogical projects. Another distinguishing characteristic is that it is offered in blended learning mode, i.e., alternating face-to-face phases with tutored distance learning phases. The pedagogical team includes one professor and one coordinator who supervise the entire program, as well as external instructors who provide individually tailored consulting on participants’ projects. During their studies, participants experience first-hand, the techno-pedagogical solutions proposed through their implementation within the program.

  5. Design and lmplementation of Ubiquitous Mobile Learning Environment under Hybrid Cloud---Arabic Course Learning Based on Wechat Public Platform%混合云模式下移动学习环境的设计与实现--以微信公共平台下阿拉伯语课程学习为例

    Institute of Scientific and Technical Information of China (English)

    田嵩; 魏启荣

    2014-01-01

    local micro site into Wechat public platform. In Wechat public platform, we can push group messages, reply the private mes-sages and manage users, and also can monitor users and messages status. In local micro site, we can complete the construction of the curriculum system and the learning resource center. Wechat public platform and local micro sites comprise the hybrid cloud model of mobile learning environment, and this model has the advantage of public cloud and private cloud. The URL+Token is used to implement the authentication process between public cloud and private cloud, and the access token is used to complete data communication. In this article, the example we have chosen is the Arabic course with the obvious characteristic of language learn-ing in our school. We know the usage of Wechat application reached one hundred percent according to the question-naire at the beginning of this term. At first, the teacher needs to finish the work is to apply for a subscription number in Wechat official website. And then, the teacher can provide teaching work in mobile learning environment. Wechat public platform is the base of mobile learning environment, and local micro site is the resource center of Arabic course and cultural background. In hybrid cloud model of mobile learning environment, language teaching activities can be easily carried out because Wechat application is very easy to use. The teacher and students can exchange messages, pictures, sound, video, LBS ( Location Based Service) and so on through the Wechat public platform, and also can share curriculum knowledge through circle of friends or Wechat group. In this sense, customizable course content is no longer been restricted by Wechat public platform, at same time local data privacy is well been protected. At the end of this article, the research puts forward an evaluation model for learning effect that considering the particularity of mobile learning environment. The evaluation model is composed of

  6. Student Engagement in a Large Classroom: Using Technology to Generate a Hybridized Problem-based Learning Experience in a Large First Year Undergraduate Class

    Directory of Open Access Journals (Sweden)

    Sherry Fukuzawa

    2016-06-01

    Full Text Available Large first year undergraduate courses have unique challenges in the promotion of student engagement and self-directed learning due to resource constraints that prohibit small group discussions with instructors. The Monthly Virtual Mystery was developed to increase student engagement in a large (N = 725 first year undergraduate class in anthropology at the University of Toronto Mississauga. The teaching challenge was to develop a participation component (worth 6% of the final grade that would increase student engagement without incurring any additional resource costs. The goal of the virtual mystery was to incorporate the principles of problem-based learning to engage students in self-directed learning through an online medium. Groups of approximately 50 students collaborated on a series of “virtual” case studies in a discussion board. Students submitted comments or questions each week to identify the information they needed to solve the mystery. A facilitator oversaw the discussion board to guide students in collaboration and resource acquisition. The final grades of students who participated in the virtual mystery (N=297 were compared to students who participated in a passive online learning exercise that involved watching weekly online videos and answering questions in a course reader (N = 347. Student self-selection determined group participation. Participation completion for both the virtual mystery and the course reader were high (78.8% and 91.6% respectively. There were no significant differences in the distribution of final grades between the participation options. The high completion rate of the virtual mystery demonstrated that an active learning project can be implemented using problem-based learning principles through an online discussion board; however, the large online group collaborations were problematic. Students were frustrated with repetition and inequitable participation in such large groups; however, students evaluated

  7. Cultivating Curiosity: Integrating Hybrid Teaching in Courses in Human Behavior in the Social Environment

    Science.gov (United States)

    Rodriguez-Keyes, Elizabeth; Schneider, Dana A.

    2013-01-01

    This study illustrates an experience of implementing a hybrid model for teaching human behavior in the social environment in an urban university setting. Developing a hybrid model in a BSW program arose out of a desire to reach students in a different way. Designed to promote curiosity and active learning, this particular hybrid model has students…

  8. A Hybrid Approach for Correcting Grammatical Errors

    Science.gov (United States)

    Lee, Kiyoung; Kwon, Oh-Woog; Kim, Young-Kil; Lee, Yunkeun

    2015-01-01

    This paper presents a hybrid approach for correcting grammatical errors in the sentences uttered by Korean learners of English. The error correction system plays an important role in GenieTutor, which is a dialogue-based English learning system designed to teach English to Korean students. During the talk with GenieTutor, grammatical error…

  9. 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...

  10. The learning curve in treating coronary chronic total occlusion early in the experience of an operator at a tertiary medical center: The role of the hybrid approach.

    Science.gov (United States)

    Shammas, Nicolas W; Shammas, Gail A; Robken, Jon; Harris, Thomas; Madison, Ashley; Dinklenburg, Catherine; Shammas, Andrew N; Harb, Christine; Jerin, Michael

    2016-01-01

    Treatment of chronic total occlusion (CTO) is complex and has a low adoption rate by interventional cardiologists. The introduction of the hybrid approach has provided a systematic step-by-step approach to treat complex CTO lesions with a high success rate. We describe the overall experience with the use of the hybrid approach of a non-CTO operator and analyze differences in the procedural and long term outcomes before and after the initial 30 cases performed. A total of 67 unselected, consecutive patients (68 lesions) underwent PCI of a CTO between January 2012 and June 2013 by a non-CTO operator. Patients were followed up for 1year using office and hospital medical records and death certificates. Cases were divided into the first consecutive 30 patients and compared to the subsequent 37 patients. The primary endpoint was acute procedural success defined as residual narrowing of ≤30% with no major adverse events. Secondary endpoints included the independent outcomes of death, major bleeding, perforations with cardiac tamponade, acute stent thrombosis (ST), target lesion revascularization (TLR) and target vessel revascularization (TVR). Descriptive analysis was performed on all variables. Univariate analysis was used to compare both groups. Baseline characteristics were as follows: mean age 63.9±10.6years, males 80.6%, diabetes 41.8%, de novo lesions 100%, ejection fraction 49.9±13.8%, CTO length 76.9±45.7mm, number of drug eluting stents per CTO 2.8±1.6 (median 3), contrast use 397±161.3ml, fluoroscopy time 51±32min and procedure time 134.3±74.7min. Lesions were crossed using an antegrade approach in 70.6% and a combined retrograde/antegrade approach in 29.4%. Crossing was intraluminal in 83.8% and subintimal in 16.2%. Acute procedural success was 95.5%. MAE included pericardial effusion with tamponade in 4.5%. On follow-up, TLR occurred in 6.6% of patients and TVR in 13.1%. There were no definite ST, one (1.6%) probable ST and one (1.6%) possible ST

  11. Research of IDSS Architecture Based on Hybrid Systems

    Institute of Scientific and Technical Information of China (English)

    MA Biao; YANG Bao-an

    2005-01-01

    This paper discusses the necessity of building IDSS on hybrid systems, and adopts XML technology to manage isomeric knowledge in hybrid systems. The paper proposes a new architecture of hybrid systems based IDSS whose core system is isomeric knowledge system. The architecture is composed of knowledge component, problems processing system, data component and intelligent user interface. This new architecture aims to enhance the capability of integrating hybrid systems, to improve the supporting effectiveness of decision-making and the intelligent level of IDSS, and tries a new way to elevate the system's ability of handling and learning knowledge.

  12. La difficile articulation du présentiel et de la distance dans le cadre d'un cours hybride en master Bridging face-to-face and distance communication in a blended learning Master's degree

    Directory of Open Access Journals (Sweden)

    Thierry Soubrié

    2008-03-01

    Full Text Available La mise en place de cours qui alternent le face-à-face et la distance sont loin d'être monnaie courante. Si l'on en croit (Charlier et al., 2004, les premiers dispositifs de ce type seraient apparus en France aux alentours de 1997, alors qu'ils étaient pressentis comme une réponse possible au tout à distance. Les potentialités de ces dispositifs en termes d'innovation pédagogique commencent cependant à être mises en avant, notamment dans un ouvrage récent paru aux Etats-Unis (Graham, 2006. Deux questions se posent alors : quels avantages présente chacune des modalités de formation et comment faire en sorte qu'elles soient complémentaires. C'est à ces questions que j'essaie de répondre dans cet article à partir d'une expérience d'hybridation d'un cours de première année de master de sciences du langage intitulé : "technologies de l'information et de la communication pour l'enseignement / apprentissage du FLE".Classes combining face to face and distance teaching are far from being widespread. According to (Charlier et al., 2004, the first environments of this kind have appeared in France around 1997, as they were perceived as a possible alternative to distance teaching exclusively. In terms of pedagogic innovation however, the potentialities of these environments begin to be emphasised, in particular in a recent book published in the United States (Graham, 2006. Two issues must then be considered: what are the respective advantages of these two training modes and how can we make them complementary. In this article, I will try to answer these questions, through the analysis of an experimental hybrid module being offered on the first year of the Masters: "Information technology and communication for teaching/learning of French as a foreign language".

  13. From hybrid swarms to swarms of hybrids

    Science.gov (United States)

    The introgression of modern humans (Homo sapiens) with Neanderthals 40,000 YBP after a half-million years of separation, may have led to the best example of a hybrid swarm on earth. Modern trade and transportation in support of the human hybrids has continued to introduce additional species, genotyp...

  14. The Hybrid Museum: Hybrid Economies of Meaning

    DEFF Research Database (Denmark)

    Vestergaard, Vitus

    2013-01-01

    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....... Such a museum is referred to as a hybrid museum....

  15. 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.

  16. 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...

  17. Resin Catalyst Hybrids

    Institute of Scientific and Technical Information of China (English)

    S. Asaoka

    2005-01-01

    @@ 1Introduction: What are resin catalyst hybrids? There are typically two types of resin catalyst. One is acidic resin which representative is polystyrene sulfonic acid. The other is basic resin which is availed as metal complex support. The objective items of this study on resin catalyst are consisting of pellet hybrid, equilibrium hybrid and function hybrid of acid and base,as shown in Fig. 1[1-5].

  18. 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.

  19. Realizing the Hybrid Library.

    Science.gov (United States)

    Pinfield, Stephen; Eaton, Jonathan; Edwards, Catherine; Russell, Rosemary; Wissenburg, Astrid; Wynne, Peter

    1998-01-01

    Outlines five projects currently funded by the United Kingdom's Electronic Libraries Program (eLib): HyLiFe (Hybrid Library of the Future), MALIBU (MAnaging the hybrid Library for the Benefit of Users), HeadLine (Hybrid Electronic Access and Delivery in the Library Networked Environment), ATHENS (authentication scheme), and BUILDER (Birmingham…

  20. Homoploid hybrid expectations

    Science.gov (United States)

    Homoploid hybrid speciation occurs when a stable, fertile, and reproductively isolated lineage results from hybridization between two distinct species without a change in ploidy level. Reproductive isolation between a homoploid hybrid species and its parents is generally attained via chromosomal re...

  1. Hybrid armature projectile

    Science.gov (United States)

    Hawke, Ronald S.; Asay, James R.; Hall, Clint A.; Konrad, Carl H.; Sauve, Gerald L.; Shahinpoor, Mohsen; Susoeff, Allan R.

    1993-01-01

    A projectile for a railgun that uses a hybrid armature and provides a seed block around part of the outer surface of the projectile to seed the hybrid plasma brush. In addition, the hybrid armature is continuously vaporized to replenish plasma in a plasma armature to provide a tandem armature and provides a unique ridge and groove to reduce plasama blowby.

  2. Intraply Hybrid Composite Design

    Science.gov (United States)

    Chamis, C. C.; Sinclair, J. H.

    1986-01-01

    Several theoretical approaches combined in program. Intraply hybrid composites investigated theoretically and experimentally at Lewis Research Center. Theories developed during investigations and corroborated by attendant experiments used to develop computer program identified as INHYD (Intraply Hybrid Composite Design). INHYD includes several composites micromechanics theories, intraply hybrid composite theories, and integrated hygrothermomechanical theory. Equations from theories used by program as appropriate for user's specific applications.

  3. 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.

  4. The hydrogen hybrid option

    Energy Technology Data Exchange (ETDEWEB)

    Smith, J.R.

    1993-10-15

    The energy efficiency of various piston engine options for series hybrid automobiles are compared with conventional, battery powered electric, and proton exchange membrane (PEM) fuel cell hybrid automobiles. Gasoline, compressed natural gas (CNG), and hydrogen are considered for these hybrids. The engine and fuel comparisons are done on a basis of equal vehicle weight, drag, and rolling resistance. The relative emissions of these various fueled vehicle options are also presented. It is concluded that a highly optimized, hydrogen fueled, piston engine, series electric hybrid automobile will have efficiency comparable to a similar fuel cell hybrid automobile and will have fewer total emissions than the battery powered vehicle, even without a catalyst.

  5. Hybridization and extinction.

    Science.gov (United States)

    Todesco, Marco; Pascual, Mariana A; Owens, Gregory L; Ostevik, Katherine L; Moyers, Brook T; Hübner, Sariel; Heredia, Sylvia M; Hahn, Min A; Caseys, Celine; Bock, Dan G; Rieseberg, Loren H

    2016-08-01

    Hybridization may drive rare taxa to extinction through genetic swamping, where the rare form is replaced by hybrids, or by demographic swamping, where population growth rates are reduced due to the wasteful production of maladaptive hybrids. Conversely, hybridization may rescue the viability of small, inbred populations. Understanding the factors that contribute to destructive versus constructive outcomes of hybridization is key to managing conservation concerns. Here, we survey the literature for studies of hybridization and extinction to identify the ecological, evolutionary, and genetic factors that critically affect extinction risk through hybridization. We find that while extinction risk is highly situation dependent, genetic swamping is much more frequent than demographic swamping. In addition, human involvement is associated with increased risk and high reproductive isolation with reduced risk. Although climate change is predicted to increase the risk of hybridization-induced extinction, we find little empirical support for this prediction. Similarly, theoretical and experimental studies imply that genetic rescue through hybridization may be equally or more probable than demographic swamping, but our literature survey failed to support this claim. We conclude that halting the introduction of hybridization-prone exotics and restoring mature and diverse habitats that are resistant to hybrid establishment should be management priorities.

  6. Spoof Plasmon Hybridization

    CERN Document Server

    Zhang, Jingjing; Luo, Yu; Shen, Xiaopeng; Maier, Stefan A; Cui, Tie Jun

    2016-01-01

    Plasmon hybridization between closely spaced nanoparticles yields new hybrid modes not found in individual constituents, allowing for the engineering of resonance properties and field enhancement capabilities of metallic nanostructure. Experimental verifications of plasmon hybridization have been thus far mostly limited to optical frequencies, as metals cannot support surface plasmons at longer wavelengths. Here, we introduce the concept of 'spoof plasmon hybridization' in highly conductive metal structures and investigate experimentally the interaction of localized surface plasmon resonances (LSPR) in adjacent metal disks corrugated with subwavelength spiral patterns. We show that the hybridization results in the splitting of spoof plasmon modes into bonding and antibonding resonances analogous to molecular orbital rule and plasmonic hybridization in optical spectrum. These hybrid modes can be manipulated to produce enormous field enhancements (larger than 5000) by tuning the separation between disks or alte...

  7. 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

  8. 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

  9. Partial imputation to improve predictive modelling in insurance risk classification using a hybrid positive selection algorithm and correlation-based feature selection

    CSIR Research Space (South Africa)

    Duma, M

    2013-09-01

    Full Text Available We propose a hybrid missing data imputation technique using positive selection and correlation-based feature selection for insurance data. The hybrid is used to help supervised learning methods improve their classification accuracy and resilience...

  10. 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....

  11. BSA Hybrid Synthesized Polymer

    Institute of Scientific and Technical Information of China (English)

    Zong Bin LIU; Xiao Pei DENG; Chang Sheng ZHAO

    2006-01-01

    Bovine serum albumin (BSA), a naturally occurring biopolymer, was regarded as a polymeric material to graft to an acrylic acid (AA)-N-vinyl pyrrolidone (NVP) copolymer to form a biomacromolecular hybrid polymer. The hybrid polymer can be blended with polyethersulfone (PES) to increase the hydrophilicity of the PES membrane, which suggested that the hybrid polymer might have a wide application in the modification of biomaterials.

  12. 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....

  13. 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.

  14. 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.

  15. 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.

  16. Hybrid Unifying Variable Supernetwork Model

    Institute of Scientific and Technical Information of China (English)

    LIU; Qiang; FANG; Jin-qing; LI; Yong

    2015-01-01

    In order to compare new phenomenon of topology change,evolution,hybrid ratio and network characteristics of unified hybrid network theoretical model with unified hybrid supernetwork model,this paper constructed unified hybrid variable supernetwork model(HUVSM).The first layer introduces a hybrid ratio dr,the

  17. Large Unifying Hybrid Supernetwork Model

    Institute of Scientific and Technical Information of China (English)

    LIU; Qiang; FANG; Jin-qing; LI; Yong

    2015-01-01

    For depicting multi-hybrid process,large unifying hybrid network model(so called LUHNM)has two sub-hybrid ratios except dr.They are deterministic hybrid ratio(so called fd)and random hybrid ratio(so called gr),respectively.

  18. Hybrid Rocket Technology

    National Research Council Canada - National Science Library

    Sankaran Venugopal; K K Rajesh; V Ramanujachari

    2011-01-01

    With their unique operational characteristics, hybrid rockets can potentially provide safer, lower-cost avenues for spacecraft and missiles than the current solid propellant and liquid propellant systems...

  19. 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...

  20. 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

    2015-01-01

    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.

  1. Hybrid Isolation Forest - Application to Intrusion Detection

    OpenAIRE

    Marteau, Pierre-François; Soheily-Khah, Saeid; Béchet, Nicolas

    2017-01-01

    From the identification of a drawback in the Isolation Forest (IF) algorithm that limits its use in the scope of anomaly detection, we propose two extensions that allow to firstly overcome the previously mention limitation and secondly to provide it with some supervised learning capability. The resulting Hybrid Isolation Forest (HIF) that we propose is first evaluated on a synthetic dataset to analyze the effect of the new meta-parameters that are introduced and verify that the addressed limi...

  2. The Promise of Personalized Learning

    Science.gov (United States)

    Headden, Susan

    2013-01-01

    The Alliance Tennenbaum Family Technology High School, a charter school on L.A.'s east side, uses a hybrid model that combines online and traditional instruction and offers students three different ways to learn. In the months since it adopted the rotational model, known as Blended Learning for Alliance School Transformation, or BLAST, Tennenbaum…

  3. Weather forecasting based on hybrid neural model

    Science.gov (United States)

    Saba, Tanzila; Rehman, Amjad; AlGhamdi, Jarallah S.

    2017-02-01

    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.

  4. 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.)

  5. 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.

  6. A Hybrid Imagination

    DEFF Research Database (Denmark)

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

    contexts, or sites, for mixing scientific knowledge and technical skills from different fields and social domains into new combinations, thus fostering what the authors term a “hybrid imagination”. Such a hybrid imagination is especially important today, as a way to counter the competitive and commercial...

  7. Hybrid trajectory spaces

    NARCIS (Netherlands)

    Collins, P.J.

    2005-01-01

    In this paper, we present a general framework for describing and studying hybrid systems. We represent the trajectories of the system as functions on a hybrid time domain, and the system itself by its trajectory space, which is the set of all possible trajectories. The trajectory space is given a na

  8. 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....

  9. Hybrid reactors. [Fuel cycle

    Energy Technology Data Exchange (ETDEWEB)

    Moir, R.W.

    1980-09-09

    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 /sup 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/sup -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.

  10. Hybrid propulsion technology program

    Science.gov (United States)

    1990-01-01

    Technology was identified which will enable application of hybrid propulsion to manned and unmanned space launch vehicles. Two design concepts are proposed. The first is a hybrid propulsion system using the classical method of regression (classical hybrid) resulting from the flow of oxidizer across a fuel grain surface. The second system uses a self-sustaining gas generator (gas generator hybrid) to produce a fuel rich exhaust that was mixed with oxidizer in a separate combustor. Both systems offer cost and reliability improvement over the existing solid rocket booster and proposed liquid boosters. The designs were evaluated using life cycle cost and reliability. The program consisted of: (1) identification and evaluation of candidate oxidizers and fuels; (2) preliminary evaluation of booster design concepts; (3) preparation of a detailed point design including life cycle costs and reliability analyses; (4) identification of those hybrid specific technologies needing improvement; and (5) preperation of a technology acquisition plan and large scale demonstration plan.

  11. 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.

  12. 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.

  13. 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

  14. Hybrid Bloch Brane

    CERN Document Server

    Bazeia, D; Losano, L

    2016-01-01

    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.

  15. 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.)

  16. Hybrid silicon evanescent devices

    Directory of Open Access Journals (Sweden)

    Alexander W. Fang

    2007-07-01

    Full Text Available Si photonics as an integration platform has recently been a focus of optoelectronics research because of the promise of low-cost manufacturing based on the ubiquitous electronics fabrication infrastructure. The key challenge for Si photonic systems is the realization of compact, electrically driven optical gain elements. We review our recent developments in hybrid Si evanescent devices. We have demonstrated electrically pumped lasers, amplifiers, and photodetectors that can provide a low-cost, scalable solution for hybrid integration on a Si platform by using a novel hybrid waveguide architecture, consisting of III-V quantum wells bonded to Si waveguides.

  17. Chaotic mixer improves microarray hybridization.

    Science.gov (United States)

    McQuain, Mark K; Seale, Kevin; Peek, Joel; Fisher, Timothy S; Levy, Shawn; Stremler, Mark A; Haselton, Frederick R

    2004-02-15

    Hybridization is an important aspect of microarray experimental design which influences array signal levels and the repeatability of data within an array and across different arrays. Current methods typically require 24h and use target inefficiently. In these studies, we compare hybridization signals obtained in conventional static hybridization, which depends on diffusional target delivery, with signals obtained in a dynamic hybridization chamber, which employs a fluid mixer based on chaotic advection theory to deliver targets across a conventional glass slide array. Microarrays were printed with a pattern of 102 identical probe spots containing a 65-mer oligonucleotide capture probe. Hybridization of a 725-bp fluorescently labeled target was used to measure average target hybridization levels, local signal-to-noise ratios, and array hybridization uniformity. Dynamic hybridization for 1h with 1 or 10ng of target DNA increased hybridization signal intensities approximately threefold over a 24-h static hybridization. Similarly, a 10- or 60-min dynamic hybridization of 10ng of target DNA increased hybridization signal intensities fourfold over a 24h static hybridization. In time course studies, static hybridization reached a maximum within 8 to 12h using either 1 or 10ng of target. In time course studies using the dynamic hybridization chamber, hybridization using 1ng of target increased to a maximum at 4h and that using 10ng of target did not vary over the time points tested. In comparison to static hybridization, dynamic hybridization reduced the signal-to-noise ratios threefold and reduced spot-to-spot variation twofold. Therefore, we conclude that dynamic hybridization based on a chaotic mixer design improves both the speed of hybridization and the maximum level of hybridization while increasing signal-to-noise ratios and reducing spot-to-spot variation.

  18. 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…

  19. 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.

  20. Seafloor classification using echo- waveforms: A method employing hybrid neural network architecture

    Digital Repository Service at National Institute of Oceanography (India)

    Chakraborty, B.; Mahale, V.; DeSouza, C.; Das, P.

    This letter presents seafloor classification study results of a hybrid artificial neural network architecture known as learning vector quantization. Single beam echo-sounding backscatter waveform data from three different seafloors of the western...

  1. 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…

  2. 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…

  3. Can Hybrid Course Formats Increase Attendance in Undergraduate Environmental Science Courses?

    Science.gov (United States)

    Riffell, Samuel K.; Sibley, Duncan F.

    2004-01-01

    A major problem for large-enrollment, introductory college courses in natural resources and life sciences is poor attendance. To ameliorate this problem, we designed a hybrid course (part online, part face-to-face) to incorporate the advantages of online learning while retaining benefits of face-to-face instruction. We taught a hybrid introductory…

  4. A Best Practice Modular Design of a Hybrid Course Delivery Structure for an Executive Education Program

    Science.gov (United States)

    Klotz, Dorothy E.; Wright, Thomas A.

    2017-01-01

    This article highlights a best practice approach that showcases the highly successful deployment of a hybrid course delivery structure for an Operations core course in an Executive MBA Program. A key design element of the approach was the modular design of both the course itself and the learning materials. While other hybrid deployments may stress…

  5. A Best Practice Modular Design of a Hybrid Course Delivery Structure for an Executive Education Program

    Science.gov (United States)

    Klotz, Dorothy E.; Wright, Thomas A.

    2017-01-01

    This article highlights a best practice approach that showcases the highly successful deployment of a hybrid course delivery structure for an Operations core course in an Executive MBA Program. A key design element of the approach was the modular design of both the course itself and the learning materials. While other hybrid deployments may stress…

  6. 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…

  7. Hybrid polymer microspheres

    Science.gov (United States)

    Rembaum, A.

    1980-01-01

    Techniques have been successfully tested for bonding polymeric spheres, typically 0.1 micron in diameter, to spheres with diameter up to 100 microns. Hybrids are being developed as improved packing material for ion-exchange columns, filters, and separators.

  8. Hybrid adsorptive membrane reactor

    Science.gov (United States)

    Tsotsis, Theodore T. (Inventor); Sahimi, Muhammad (Inventor); Fayyaz-Najafi, Babak (Inventor); Harale, Aadesh (Inventor); Park, Byoung-Gi (Inventor); Liu, Paul K. T. (Inventor)

    2011-01-01

    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.

  9. Hybrid photon detectors

    CERN Document Server

    D'Ambrosio, C

    2003-01-01

    Hybrid photon detectors detect light via vacuum photocathodes and accelerate the emitted photoelectrons by an electric field towards inversely polarized silicon anodes, where they are absorbed, thus producing electron-hole pairs. These, in turn, are collected and generate electronic signals on their ohmic contacts. This review first describes the characteristic properties of the main components of hybrid photon detectors: light entrance windows, photocathodes, and silicon anodes. Then, essential relations describing the trajectories of photoelectrons in electric and magnetic fields and their backscattering from the silicon anodes are derived. Depending on their anode configurations, three families of hybrid photon detectors are presented: hybrid photomultiplier tubes with single anodes for photon counting with high sensitivity and for gamma spectroscopy; multi-anode photon detector tubes with anodes subdivided into square or hexagonal pads for position-sensitive photon detection; imaging silicon pixel array t...

  10. Functional hybrid materials

    National Research Council Canada - National Science Library

    Fahmi, Amir; Pietsch, Torsten; Mendoza, Cesar; Cheval, Nicolas

    2009-01-01

    .... This paper describes our group's achievements towards the development of multifunctional nanostructures via self-assembly of hybrid systems based on the block copolymer PS-b-P4VP and inorganic nanoparticles (NPs...

  11. Hybrid Rocket Technology

    Directory of Open Access Journals (Sweden)

    Sankaran Venugopal

    2011-04-01

    Full Text Available With their unique operational characteristics, hybrid rockets can potentially provide safer, lower-cost avenues for spacecraft and missiles than the current solid propellant and liquid propellant systems. Classical hybrids can be throttled for thrust tailoring, perform in-flight motor shutdown and restart. In classical hybrids, the fuel is stored in the form of a solid grain, requiring only half the feed system hardware of liquid bipropellant engines. The commonly used fuels are benign, nontoxic, and not hazardous to store and transport. Solid fuel grains are not highly susceptible to cracks, imperfections, and environmental temperature and are therefore safer to manufacture, store, transport, and use for launch. The status of development based on the experience of the last few decades indicating the maturity of the hybrid rocket technology is given in brief.Defence Science Journal, 2011, 61(3, pp.193-200, DOI:http://dx.doi.org/10.14429/dsj.61.518

  12. Nitrous Paraffin Hybrid Project

    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...

  13. Hybrid adsorptive membrane reactor

    Science.gov (United States)

    Tsotsis, Theodore T.; Sahimi, Muhammad; Fayyaz-Najafi, Babak; Harale, Aadesh; Park, Byoung-Gi; Liu, Paul K. T.

    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.

  14. Hybridity in Disgrace

    Institute of Scientific and Technical Information of China (English)

    刘建平

    2015-01-01

    John Maxwell Coetzee's masterpiece-Disgrace is the representative work about post colonialism.The novel describes a series of disgraceful events happened between the white and the black in the post apartheid South Africa.The famous literature theory-hybridity of Homi K.Bhabha is the very key theory to analyze the work.In post apartheid South Africa,hybridity is the only way for the white and the black to coexist.

  15. Hybrid Baryon Signatures

    CERN Document Server

    Page, P R

    2000-01-01

    We discuss whether a low-lying hybrid baryon should be defined as a three quark - gluon bound state or as three quarks moving on an excited adiabatic potential. We show that the latter definition becomes exact, not only for very heavy quarks, but also for specific dynamics. We review the literature on the signatures of hybrid baryons, with specific reference to strong hadronic decays, electromagnetic couplings, diffractive production and production in psi decay.

  16. 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....

  17. Requirements for Hybrid Cosimulation

    Science.gov (United States)

    2014-08-16

    hybrid cosimulation version of the Functional Mockup Interface (FMI) standard. A cosimulation standard de nes interfaces that enable diverse simulation...cosimulation standards, and specifically provides guidance for development of a hybrid cosimulation version of the Functional Mockup Interface (FMI) standard...V. Peetz, and S. Wolf. The functional mockup interface for tool independent exchange of simulation models. In Proc. of the 8-th International

  18. Students´ Perspectives on eLearning Activities in Person-Centered, Blended Learning Settings

    Science.gov (United States)

    Haselberger, David; Motsching, Renate

    2016-01-01

    Blended or hybrid learning has become a frequent practice in higher education. In this article our primary research interest was to find out how students perceived eLearning activities in blended learning courses based on the person-centered paradigm. Through analyzing the content of a series of semi-structured interviews we found out that…

  19. 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.

  20. Hybrid ventilation systems and high performance buildings

    Energy Technology Data Exchange (ETDEWEB)

    Utzinger, D.M. [Wisconsin Univ., Milwaukee, WI (United States). School of Architecture and Urban Planning

    2009-07-01

    This paper described hybrid ventilation design strategies and their impact on 3 high performance buildings located in southern Wisconsin. The Hybrid ventilation systems combined occupant controlled natural ventilation with mechanical ventilation systems. Natural ventilation was shown to provide adequate ventilation when appropriately designed. Proper control integration of natural ventilation into hybrid systems was shown to reduce energy consumption in high performance buildings. This paper also described the lessons learned from the 3 buildings. The author served as energy consultant on all three projects and had the responsibility of designing and integrating the natural ventilation systems into the HVAC control strategy. A post occupancy evaluation of building energy performance has provided learning material for architecture students. The 3 buildings included the Schlitz Audubon Nature Center completed in 2003; the Urban Ecology Center completed in 2004; and the Aldo Leopold Legacy Center completed in 2007. This paper included the size, measured energy utilization intensity and percentage of energy supplied by renewable solar power and bio-fuels on site for each building. 6 refs., 2 tabs., 6 figs.

  1. 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.

  2. Novel Hybrid Adaptive Controller for Manipulation in Complex Perturbation Environments

    Science.gov (United States)

    Smith, Alex M. C.; Yang, Chenguang; Ma, Hongbin; Culverhouse, Phil; Cangelosi, Angelo; Burdet, Etienne

    2015-01-01

    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. PMID:26029916

  3. Energy-Efficient Building HVAC Control Using Hybrid System LBMPC

    CERN Document Server

    Aswani, Anil; Taneja, Jay; Krioukov, Andrew; Culler, David; Tomlin, Claire

    2012-01-01

    Improving the energy-efficiency of heating, ventilation, and air-conditioning (HVAC) systems has the potential to realize large economic and societal benefits. This paper concerns the system identification of a hybrid system model of a building-wide HVAC system and its subsequent control using a hybrid system formulation of learning-based model predictive control (LBMPC). Here, the learning refers to model updates to the hybrid system model that incorporate the heating effects due to occupancy, solar effects, outside air temperature (OAT), and equipment, in addition to integrator dynamics inherently present in low-level control. Though we make significant modeling simplifications, our corresponding controller that uses this model is able to experimentally achieve a large reduction in energy usage without any degradations in occupant comfort. It is in this way that we justify the modeling simplifications that we have made. We conclude by presenting results from experiments on our building HVAC testbed, which s...

  4. Collaborations among Diverse Support Areas for Hybrid Success

    Science.gov (United States)

    Haggar, Faye; Kelley, Bruce; Chen, Weichao

    2017-01-01

    Successful implementation of hybrid courses typically demands collaboration among diverse support areas on campus. This article examines these collaborations through the lens of Badrul Khan's theory of managing blended learning support. Also discussed is the central role that faculty developers can play in connecting these support areas to ensure…

  5. 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…

  6. Hybrid Monte Carlo with Chaotic Mixing

    CERN Document Server

    Kadakia, Nirag

    2016-01-01

    We propose a hybrid Monte Carlo (HMC) technique applicable to high-dimensional multivariate normal distributions that effectively samples along chaotic trajectories. The method is predicated on the freedom of choice of the HMC momentum distribution, and due to its mixing properties, exhibits sample-to-sample autocorrelations that decay far faster than those in the traditional hybrid Monte Carlo algorithm. We test the methods on distributions of varying correlation structure, finding that the proposed technique produces superior covariance estimates, is less reliant on step-size tuning, and can even function with sparse or no momentum re-sampling. The method presented here is promising for more general distributions, such as those that arise in Bayesian learning of artificial neural networks and in the state and parameter estimation of dynamical systems.

  7. The Hybrids of Postmodernism

    Directory of Open Access Journals (Sweden)

    Dana BĂDULESCU

    2014-09-01

    Full Text Available Hybridization is a fundamental characteristic of postmodernism, included by Ihab Hassan in his “catena” of features. This paper looks into the hybrids of postmodernism, which are the result of migration, displacement and uprooting, the re-visitation of myths, folklore and legends, or projections of their author’s imagination. The hybrids used as examples here are drawn from several novels written by Salman Rushdie, especially The Satanic Verses, two short stories, one by Márquez and the other by Donald Barthelme, Borges’s Book of Imaginary Beings, Cărtărescu’s Encyclopaedia of Dragons and Michelle Cliff’s No Telephone to Heaven. Diverse as they may be, these hybrids emphasize a defining characteristic of postmodernism, which is its pluralism. I conclude that the hybrids of postmodernism are aesthetically or politically subversive. Besides, what makes them difficult to grasp is their unfixed and protean nature. They ask for high leaps of the imagination, a total suspension of disbelief and a complete surrender to the powerful seduction of imagination on the reader’s part.

  8. Research on Hybrid Vehicle Drivetrain

    Science.gov (United States)

    Xie, Zhongzhi

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

  9. Double Motor Coordinated Control Based on Hybrid Genetic Algorithm and CMAC

    Science.gov (United States)

    Cao, Shaozhong; Tu, Ji

    A novel hybrid cerebellar model articulation controller (CMAC) and online adaptive genetic algorithm (GA) controller is introduced to control two Brushless DC motor (BLDCM) which applied in a biped robot. Genetic Algorithm simulates the random learning among the individuals of a group, and CMAC simulates the self-learning of an individual. To validate the ability and superiority of the novel algorithm, experiments have been done in MATLAB/SIMULINK. Analysis among GA, hybrid GA-CMAC and CMAC feed-forward control is also given. The results prove that the torque ripple of the coordinated control system is eliminated by using the hybrid GA-CMAC algorithm.

  10. for hybrid dynamical systems

    Directory of Open Access Journals (Sweden)

    Wassim M. Haddad

    2001-01-01

    Full Text Available In this paper we develop a unified dynamical systems framework for a general class of systems possessing left-continuous flows; that is, left-continuous dynamical systems. These systems are shown to generalize virtually all existing notions of dynamical systems and include hybrid, impulsive, and switching dynamical systems as special cases. Furthermore, we generalize dissipativity, passivity, and nonexpansivity theory to left-continuous dynamical systems. Specifically, the classical concepts of system storage functions and supply rates are extended to left-continuous dynamical systems providing a generalized hybrid system energy interpretation in terms of stored energy, dissipated energy over the continuous-time dynamics, and dissipated energy over the resetting events. Finally, the generalized dissipativity notions are used to develop general stability criteria for feedback interconnections of left-continuous dynamical systems. These results generalize the positivity and small gain theorems to the case of left-continuous, hybrid, and impulsive dynamical systems.

  11. 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 modell......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...... 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...... to the differential action, thus, allowing stepwise development of hybrid systems Udgivelsesdato: JAN 1...

  12. Conditional Hybrid Nonclassicality

    Science.gov (United States)

    Agudelo, E.; Sperling, J.; Costanzo, L. S.; Bellini, M.; Zavatta, A.; Vogel, W.

    2017-09-01

    We derive and implement a general method to characterize the nonclassicality in compound discrete- and continuous-variable systems. For this purpose, we introduce the operational notion of conditional hybrid nonclassicality which relates to the ability to produce a nonclassical continuous-variable state by projecting onto a general superposition of discrete-variable subsystem. We discuss the importance of this form of quantumness in connection with interfaces for quantum communication. To verify the conditional hybrid nonclassicality, a matrix version of a nonclassicality quasiprobability is derived and its sampling approach is formulated. We experimentally generate an entangled, hybrid Schrödinger cat state, using a coherent photon-addition process acting on two temporal modes, and we directly sample its nonclassicality quasiprobability matrix. The introduced conditional quantum effects are certified with high statistical significance.

  13. Porosity in hybrid materials

    Energy Technology Data Exchange (ETDEWEB)

    Schaefer, D.W.; Beaucage, G.; Loy, D. [Sandia National Labs., Albuquerque, NM (United States)

    1995-12-31

    Multicomponent, or hybrid composites are emerging as precursors to porous materials. Sacrifice of an ephemeral phase can be used to generate porosity, the nature of which depends on precursor structure. Retention of an organic constituent, on the other hand, can add desirable toughness to an otherwise brittle ceramic. We use small-angle x-ray and neutron scattering to examine porosity in both simple and hybrid materials. We find that microphase separation controls porosity in almost all systems studied. Pore distributions are controlled by the detailed bonding within and between phases as well as the flexibility of polymeric constituents. Thus hybridization opens new regions of pore distributions not available in simple systems. We look at several sacrificial concepts and show that it is possible to generate multimodal pore size distributions due to the complicated phase structure in the precursor.

  14. Photoproduction of Hybrid Mesons

    CERN Document Server

    Barnes, T

    1998-01-01

    In this contribution I discuss prospects for photoproducing hybrid mesons at CEBAF, based on recent model results and experimental indications of possible hybrids. One excellent opportunity appears to be a search for the I=1, JPC=2+-, neutral "(b2)o" hybrid in (a2 pi)o through diffractive photoproduction. Other notable possibilities accessible through pi+ or pio exchange photoproduction are I=1, JPC=1-+, charged "pi1+" in f1 pi+, (b1 pi)+ and (rho pi)+; piJ(1770)+ in f2 pi+ and (b1 pi)+; pi(1800)+ in f0 pi+, f2 pi+, omega rho+ and (rho pi)+; a1 in f1 pi+ and f2 pi+; and omega in (rho pi)o, omega eta and (K1 K)o.

  15. Smart hybrid rotary damper

    Science.gov (United States)

    Yang, C. S. Walter; DesRoches, Reginald

    2014-03-01

    This paper develops a smart hybrid rotary damper using a re-centering smart shape memory alloy (SMA) material as well as conventional energy-dissipating metallic plates that are easy to be replaced. The ends of the SMA and steel plates are inserted in the hinge. When the damper rotates, all the plates bend, providing energy dissipating and recentering characteristics. Such smart hybrid rotary dampers can be installed in structures to mitigate structural responses and to re-center automatically. The damaged energy-dissipating plates can be easily replaced promptly after an external excitation, reducing repair time and costs. An OpenSEES model of a smart hybrid rotary was established and calibrated to reproduce the realistic behavior measured from a full-scale experimental test. Furthermore, the seismic performance of a 3-story moment resisting model building with smart hybrid rotary dampers designed for downtown Los Angeles was also evaluated in the OpenSEES structural analysis software. Such a smart moment resisting frame exhibits perfect residual roof displacement, 0.006", extremely smaller than 18.04" for the conventional moment resisting frame subjected to a 2500 year return period ground motion for the downtown LA area (an amplified factor of 1.15 on Kobe earthquake). The smart hybrid rotary dampers are also applied into an eccentric braced steel frame, which combines a moment frame system and a bracing system. The results illustrate that adding smart hybrid rotaries in this braced system not only completely restores the building after an external excitation, but also significantly reduces peak interstory drifts.

  16. 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

  17. Hybrid Weyl semimetal

    Science.gov (United States)

    Li, Fei-Ye; Luo, Xi; Dai, Xi; Yu, Yue; Zhang, Fan; Chen, Gang

    2016-09-01

    We construct a tight-binding model realizing one pair of Weyl nodes and three distinct Weyl semimetals. In the type-I (type-II) Weyl semimetal, both nodes belong to type-I (type-II) Weyl nodes. In addition, there exists a third type, previously undiscovered and dubbed "hybrid Weyl semimetal", in which one Weyl node is of type I while the other is of type II. For the hybrid Weyl semimetal, we further demonstrate the bulk Fermi surfaces and the topologically protected surface states, analyze the unique Landau-level structure and quantum oscillation, and discuss the conditions for possible material realization.

  18. 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.

  19. 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.

  20. THERMALLY CLEAVABLE HYBRID MATERIALS

    Directory of Open Access Journals (Sweden)

    Constantin Gaina

    2011-12-01

    Full Text Available Thermally cleavable hybrid materials were prepared by the Diels-Alder cycloaddition reaction of poly(vinyl furfural to N phenylmaleimido-N’-(triethoxysilylpropylurea followed by the sol-gel condensation reaction of trietoxysilyl groups with water and acetic acid. Thermal and dynamic mechanical analysis, dielectric and FTIR spectroscopy were used to characterize the structure and properties of the composites. The size of the inorganic silica particles in the hybrid material varied dependent on the silica content. The DSC study of the prepared materials revealed that the cleavage process of the formed cycloadducts takes place at temperatures varying between 143-165°C and is an endothermic process.

  1. The hybrid BCI

    Directory of Open Access Journals (Sweden)

    Gert Pfurtscheller

    2010-04-01

    Full Text Available Nowadays, everybody knows what a hybrid car is. A hybrid car normally has 2 engines, its main purpose being to enhance energy efficiency and reduce CO2 output. Similarly, a typical hybrid brain-computer interface (BCI is also composed of 2 BCIs or at least one BCI and another system. Such a hybrid BCI, like any BCI, must fulfil the following four criteria: (i the device must rely on signals recorded directly from the brain; (ii there must be at least one recordable brain signal that the user can intentionally modulate to effect goal-directed behaviour; (iii real time processing; and (iv the user must obtain feedback. This paper introduces some hybrid BCIs which have already been published or are currently in development or validation, and some concepts for future work. The BCIs described classify 2 EEG patterns: One is the event-related (desynchronisation (ERD, ERS of sensorimotor rhythms, and the other is the steady-state visual evoked potential (SSVEP. The hybrid BCI can either have more than one input whereby the inputs are typically processed simultaneously or operate 2 systems sequentially, whereby the first system can act as a “brain switch”. In the case of self-paced operation of a SSVEP-based hand orthosis control with an motor imagery-based switch it was possible to reduce the rate of false positives during resting periods by about 50% compared to the SSVEP BCI alone. It is shown that such a brain switch can also rely on hemodynamic changes measured through near-infrared spectroscopy (NIRS. Another interesting approach is a hybrid BCI with simultaneous operations of ERD- and SSVEP-based BCIs. Here it is important to prove the existing promising offline simulation results with online experiments. Hybrid BCIs can also use one brain signal and another input. Such an additional input can be a physiological signal like the heart rate but also a signal from an external device like, an eye gaze control system.

  2. Hybrid pre training algorithm of Deep Neural Networks

    Directory of Open Access Journals (Sweden)

    Drokin I. S.

    2016-01-01

    Full Text Available This paper proposes a hybrid algorithm of pre training deep networks, using both marked and unmarked data. The algorithm combines and extends the ideas of Self-Taught learning and pre training of neural networks approaches on the one hand, as well as supervised learning and transfer learning on the other. Thus, the algorithm tries to integrate in itself the advantages of each approach. The article gives some examples of applying of the algorithm, as well as its comparison with the classical approach to pre training of neural networks. These examples show the effectiveness of the proposed algorithm.

  3. Hybrid Course Design and Delivery: Faculty Approaches, Essential Components, and the Impact of Professional Development in Community Colleges

    Science.gov (United States)

    Littlefield, Cathy Morgan

    2012-01-01

    Hybrid learning combines the personal contact of the face-to-face learning environment with the convenience of online learning in a way that creates an interactive and engaging environment for students and faculty. This innovative instructional design is capturing the attention of faculty in higher education, but particularly in America's…

  4. Multimodal Task-Driven Dictionary Learning for Image Classification.

    Science.gov (United States)

    Bahrampour, Soheil; Nasrabadi, Nasser M; Ray, Asok; Jenkins, William Kenneth

    2016-01-01

    Dictionary learning algorithms have been successfully used for both reconstructive and discriminative tasks, where an input signal is represented with a sparse linear combination of dictionary atoms. While these methods are mostly developed for single-modality scenarios, recent studies have demonstrated the advantages of feature-level fusion based on the joint sparse representation of the multimodal inputs. In this paper, we propose a multimodal task-driven dictionary learning algorithm under the joint sparsity constraint (prior) to enforce collaborations among multiple homogeneous/heterogeneous sources of information. In this task-driven formulation, the multimodal dictionaries are learned simultaneously with their corresponding classifiers. The resulting multimodal dictionaries can generate discriminative latent features (sparse codes) from the data that are optimized for a given task such as binary or multiclass classification. Moreover, we present an extension of the proposed formulation using a mixed joint and independent sparsity prior, which facilitates more flexible fusion of the modalities at feature level. The efficacy of the proposed algorithms for multimodal classification is illustrated on four different applications--multimodal face recognition, multi-view face recognition, multi-view action recognition, and multimodal biometric recognition. It is also shown that, compared with the counterpart reconstructive-based dictionary learning algorithms, the task-driven formulations are more computationally efficient in the sense that they can be equipped with more compact dictionaries and still achieve superior performance.

  5. A Mathematical Approach to Hybridization

    Science.gov (United States)

    Matthews, P. S. C.; Thompson, J. J.

    1975-01-01

    Presents an approach to hybridization which exploits the similarities between the algebra of wave functions and vectors. This method will account satisfactorily for the number of orbitals formed when applied to hybrids involving the s and p orbitals. (GS)

  6. 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

  7. 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...

  8. (Hybrid) Baryons Symmetries and Masses

    CERN Document Server

    Page, P R

    1999-01-01

    We construct (hybrid) baryons in the flux-tube model of Isgur and Paton. In the limit of adiabatic quark motion, we build proper eigenstates of orbital angular momentum and construct the flavour, spin and J^P of hybrid baryons from the symmetries of the system. The lowest mass hybrid baryon is estimated at approximately 2 GeV.

  9. Towards End-to-End Learning for Dialog State Tracking and Management using Deep Reinforcement Learning

    OpenAIRE

    Zhao, Tiancheng; Eskenazi, Maxine

    2016-01-01

    This paper presents an end-to-end framework for task-oriented dialog systems using a variant of Deep Recurrent Q-Networks (DRQN). The model is able to interface with a relational database and jointly learn policies for both language understanding and dialog strategy. Moreover, we propose a hybrid algorithm that combines the strength of reinforcement learning and supervised learning to achieve faster learning speed. We evaluated the proposed model on a 20 Question Game conversational game simu...

  10. Improved hybrid rocket fuel

    Science.gov (United States)

    Dean, David L.

    1995-01-01

    McDonnell Douglas Aerospace, as part of its Independent R&D, has initiated development of a clean burning, high performance hybrid fuel for consideration as an alternative to the solid rocket thrust augmentation currently utilized by American space launch systems including Atlas, Delta, Pegasus, Space Shuttle, and Titan. It could also be used in single stage to orbit or as the only propulsion system in a new launch vehicle. Compared to solid propellants based on aluminum and ammonium perchlorate, this fuel is more environmentally benign in that it totally eliminates hydrogen chloride and aluminum oxide by products, producing only water, hydrogen, nitrogen, carbon oxides, and trace amounts of nitrogen oxides. Compared to other hybrid fuel formulations under development, this fuel is cheaper, denser, and faster burning. The specific impulse of this fuel is comparable to other hybrid fuels and is between that of solids and liquids. The fuel also requires less oxygen than similar hybrid fuels to produce maximum specific impulse, thus reducing oxygen delivery system requirements.

  11. Workshop on hybrid rice

    Institute of Scientific and Technical Information of China (English)

    TANZhijun

    1994-01-01

    FAO, in collaboration with FEDEARROZ in Colombia and EMBRAPA / CNPAF in Brail, organized a workshop on the Establishment of a Coorperative Research Network on Hybrid Rice in Latin America and the Caribbean held from Mar 16 to 18, 1994 at EMBRAPA/CNPAF in Brazil. Dr MAO Changxiang,

  12. 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 s

  13. Organics go hybrid

    Science.gov (United States)

    Lanzani, Guglielmo; Petrozza, Annamaria; Caironi, Mario

    2017-01-01

    From displays to solar cells, the field of organic optoelectronics has come a long way over the past 50 years, but the realization of an electrically pumped organic laser remains elusive. The answer may lie with hybrid organic-inorganic materials called perovskites.

  14. Hybrid-secure MPC 

    DEFF Research Database (Denmark)

    Lucas, Christoph; Raub, Dominik; Maurer, Ueli

    2010-01-01

    Most protocols for distributed, fault-tolerant computation, or multi-party computation (MPC), provide security guarantees in an all-or-nothing fashion. In contrast, a hybrid-secure protocol provides different security guarantees depending on the set of corrupted parties and the computational powe...

  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...

  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. Hybrid printed electronics

    NARCIS (Netherlands)

    Koetse, M.; Smits, E.; Rubingh, E.; Teunissen, P.; Kusters, R.; Abbel, R.; Brand, J. van den

    2016-01-01

    Although many electronic functionalities can be realized by printed or organic electronics, short-term marketable products often require robust, reproducible, and nondisturbing technologies. In this chapter we show how hybrid electronics, a combination of printed circuitry, thin-film electronics,

  18. Teacher education physical education: In search of a hybrid space

    Directory of Open Access Journals (Sweden)

    Timothy Lynch

    2015-12-01

    Full Text Available It is argued that a learning environment underpinned by a strengths-based collaborative approach between universities and schools offers extended pre-service teacher learning opportunities and subsequently enhanced preparation. The term “hybrid space” describes the ideal environment of shared partnership where knowledge is jointly created, and consequently, as too is collaborative egalitarianism between stakeholders. This study investigates a possible “hybrid space” course within Physical Education Teacher Education (PETE in the UK. While much literature discusses the advantages of the “hybrid space” ideal across education disciplines, high-quality research into PETE hybrid spaces is limited, if not non-existent. Hence, the particular course was chosen for data collection as it advocates intricate connections with schools in the local community. Furthermore, the course was awarded “Outstanding” by the national regulatory authority, England and Wales Office for Standards in Education (Ofsted, one of the major reasons explicitly stated was for its community connections. A qualitative, interpretive study using a case study methodology was adopted to examine the successful primary PETE course. The findings offer insights into the ideal of hybrid spaces in PETE, which appear to benefit various stakeholders within communities. The study is significant as it assists teacher educators from around the world, challenged to rethink their connections between university courses and school field experiences through illustrating a highly successful example.

  19. 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

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

    Science.gov (United States)

    Bachman, Christine; Scherer, Rhonda

    2015-01-01

    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…

  1. Learning How To Learn.

    Science.gov (United States)

    Barnett, Demian

    2000-01-01

    In one California high school, learning to learn is a measurable outcome assessed by all students' participation in graduation by exhibition. Students must meet state requirements and demonstrate learning prowess by publicly exhibiting their skills in math, science, language arts, social science, service learning, and postgraduation planning. (MLH)

  2. Learning How To Learn.

    Science.gov (United States)

    Barnett, Demian

    2000-01-01

    In one California high school, learning to learn is a measurable outcome assessed by all students' participation in graduation by exhibition. Students must meet state requirements and demonstrate learning prowess by publicly exhibiting their skills in math, science, language arts, social science, service learning, and postgraduation planning. (MLH)

  3. 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...... presented in a way that suits their individual LS preferences. In this presentation you will see how we as teachers can assist students in applying LS strategies that cater to their individual learning strengths. This will be based on general recommendations for HE teaching and learning supported...... 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...

  4. Electronic Learning Communities: Issues and Practices.

    Science.gov (United States)

    Reisman, Sorel, Ed.; Flores, John G., Ed.; Edge, Denzil, Ed.

    This book provides information for researchers and practitioners on the current issues and best practices associated with electronic learning communities. Fourteen contributed chapters include: "Interactive Online Educational Experiences: E-volution of Graded Projects" (James Benjamin); "Hybrid Courses as Learning Communities" (Penelope Walters…

  5. Serendipitous offline learning in a neuromorphic robot

    CSIR Research Space (South Africa)

    Stewart, TC

    2016-02-01

    Full Text Available We demonstrate a hybrid neuromorphic learning paradigm that learns complex senso-rimotor mappings based on a small set of hard-coded reflex behaviors. A mobile robot is first controlled by a basic set of reflexive hand-designed behaviors. All sensor...

  6. Distance learning perspectives.

    Science.gov (United States)

    Pandza, Haris; Masic, Izet

    2013-01-01

    The development of modern technology and the Internet has enabled the explosive growth of distance learning. distance learning is a process that is increasingly present in the world. This is the field of education focused on educating students who are not physically present in the traditional classrooms or student's campus. described as a process where the source of information is separated from the students in space and time. If there are situations that require the physical presence of students, such as when a student is required to physically attend the exam, this is called a hybrid form of distance learning. This technology is increasingly used worldwide. The Internet has become the main communication channel for the development of distance learning.

  7. Ants exhibit asymmetric hybridization in a mosaic hybrid zone.

    Science.gov (United States)

    Purcell, Jessica; Zahnd, Sacha; Athanasiades, Anouk; Türler, Rebecca; Chapuisat, Michel; Brelsford, Alan

    2016-10-01

    Research on hybridization between species provides unparalleled insights into the pre- and postzygotic isolating mechanisms that drive speciation. In social organisms, colony-level incompatibilities may provide additional reproductive barriers not present in solitary species, and hybrid zones offer an opportunity to identify these barriers. Here, we use genotyping-by-sequencing to sequence hundreds of markers in a hybrid zone between two socially polymorphic ant species, Formica selysi and Formica cinerea. We characterize the zone, determine the frequency of hybrid workers, infer whether hybrid queens or males are produced and investigate whether hybridization is influenced by colony social organization. We also compare cuticular hydrocarbon profiles and aggression levels between the two species. The hybrid zone exhibits a mosaic structure. The asymmetric distribution of hybrids skewed towards F. cinerea suggests a pattern of unidirectional nuclear gene flow from F. selysi into F. cinerea. The occurrence of backcrossed individuals indicates that hybrid queens and/or males are fertile, and the presence of the F. cinerea mitochondrial haplotype in 97% of hybrids shows that successful F1 hybrids will generally have F. cinerea mothers and F. selysi fathers. We found no evidence that social organization contributes to speciation, because hybrids occur in both single-queen and multiple-queen colonies. Strongly differentiated cuticular hydrocarbon profiles and heightened interspecific aggression further reveal that species recognition cues are both present and perceived. The discovery of fertile hybrids and asymmetrical gene flow is unusual in ants, and this hybrid zone will therefore provide an ideal system with which to investigate speciation in social insects.

  8. Use of Blended Approach in the Learning of Electromagnetic Induction

    CERN Document Server

    Chew, Charles

    2015-01-01

    This paper traces the importance of pedagogical content knowledge in the digital age to prepare today students for the 21st century. It highlights the need for ICT-based pedagogical models that are grounded in both the learning theories of constructivism and connectivism. One such suitable ICT-based pedagogical model is the TSOI Hybrid Learning Model. By means of a physics blended learning exemplar based on the TSOI Hybrid Learning Model, this paper argues for the use of blended learning approach as the way forward for 21st century teaching.

  9. Hybrid k -Nearest Neighbor Classifier.

    Science.gov (United States)

    Yu, Zhiwen; Chen, Hantao; Liuxs, Jiming; You, Jane; Leung, Hareton; Han, Guoqiang

    2016-06-01

    Conventional k -nearest neighbor (KNN) classification approaches have several limitations when dealing with some problems caused by the special datasets, such as the sparse problem, the imbalance problem, and the noise problem. In this paper, we first perform a brief survey on the recent progress of the KNN classification approaches. Then, the hybrid KNN (HBKNN) classification approach, which takes into account the local and global information of the query sample, is designed to address the problems raised from the special datasets. In the following, the random subspace ensemble framework based on HBKNN (RS-HBKNN) classifier is proposed to perform classification on the datasets with noisy attributes in the high-dimensional space. Finally, the nonparametric tests are proposed to be adopted to compare the proposed method with other classification approaches over multiple datasets. The experiments on the real-world datasets from the Knowledge Extraction based on Evolutionary Learning dataset repository demonstrate that RS-HBKNN works well on real datasets, and outperforms most of the state-of-the-art classification approaches.

  10. Marketing image categorization using hybrid human-machine combinations

    Science.gov (United States)

    Gnanasambandam, Nathan; Madhu, Himanshu

    2012-03-01

    Marketing instruments with nested, short-form, symbol loaded content need to be studied differently. Image classification in the Web2.0 world can dynamically use a configurable amount of internal and external data as well as varying levels of crowd-sourcing. Our work is one such examination of how to construct a hybrid technique involving learning and crowd-sourcing. Through a parameter called turkmix and a multitude of crowd-sourcing techniques available we show that we can control the trend of metrics such as precision and recall on the hybrid categorizer.

  11. 基于集合经验模态分解和改进极限学习机的短期风速组合预测研究%A hybrid short-term wind speed forecasting model based on ensemble empirical mode decomposition and improved extreme learning machine

    Institute of Scientific and Technical Information of China (English)

    张翌晖; 王贺; 胡志坚; 王凯; 黄东山; 宁文辉; 张承学

    2014-01-01

    This paper proposes a new short-term combination prediction model of wind speed by means of ensemble empirical mode decomposition (EEMD) and improved extreme learning machine (IELM). Firstly, wind speed series is decomposed into several components with different frequency bands by EEMD to reduce the series non-stationary. Secondly, the phase space of each component is reconstructed in order to solve the randomness and component information lost of input dimensionality selection of extreme learning machine, and then an IELM model of each component is established. Finally, the forecast result of each component is superimposed to get the final result. The simulation result verifies that the hybrid model has higher prediction accuracy of wind speed.%提出一种基于集合经验模态分解(Ensemble empirical mode decomposition)和改进极限学习机(Improved Extreme Learning Machine,IELM)的新型短期风速组合预测模型。采用集合经验模态分解将风速序列分解成不同频段的分量,以降低序列的非平稳性。使用改进极限学习机对各分量分别建模预测,为避免极限学习机输入维数选取的随意性和分量信息丢失等问题,先对各分量重构相空间,最后将各分量预测结果叠加得到最终预测结果。实例研究表明,所提的组合预测模型具有较高的预测精度。

  12. 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 approximations......- ods with the approach for learning mixtures of truncated basis functions from data....

  13. 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

  14. Brain anatomical structure segmentation by hybrid discriminative/generative models.

    Science.gov (United States)

    Tu, Z; Narr, K L; Dollar, P; Dinov, I; Thompson, P M; Toga, A W

    2008-04-01

    In this paper, a hybrid discriminative/generative model for brain anatomical structure segmentation is proposed. The learning aspect of the approach is emphasized. In the discriminative appearance models, various cues such as intensity and curvatures are combined to locally capture the complex appearances of different anatomical structures. A probabilistic boosting tree (PBT) framework is adopted to learn multiclass discriminative models that combine hundreds of features across different scales. On the generative model side, both global and local shape models are used to capture the shape information about each anatomical structure. The parameters to combine the discriminative appearance and generative shape models are also automatically learned. Thus, low-level and high-level information is learned and integrated in a hybrid model. Segmentations are obtained by minimizing an energy function associated with the proposed hybrid model. Finally, a grid-face structure is designed to explicitly represent the 3-D region topology. This representation handles an arbitrary number of regions and facilitates fast surface evolution. Our system was trained and tested on a set of 3-D magnetic resonance imaging (MRI) volumes and the results obtained are encouraging.

  15. Phoxonic Hybrid Superlattice.

    Science.gov (United States)

    Alonso-Redondo, Elena; Huesmann, Hannah; El Boudouti, El-Houssaine; Tremel, Wolfgang; Djafari-Rouhani, Bahram; Butt, Hans-Juergen; Fytas, George

    2015-06-17

    We studied experimentally and theoretically the direction-dependent elastic and electromagnetic wave propagation in a supported film of hybrid PMMA (poly[methyl-methacrylate])-TiO2 superlattice (SL). In the direction normal to the layers, this one-dimensional periodic structure opens propagation band gaps for both hypersonic (GHz) phonons and near-UV photons. The high mismatch of elastic and optical impedance results in a large dual phoxonic band gap. The presence of defects inherent to the spin-coating fabrication technique is sensitively manifested in the band gap region. Utilizing Brillouin light scattering, phonon propagation along the layers was observed to be distinctly different from propagation normal to them and can, under certain conditions (SL thickness and substrate elasticity), reveal the nanomechanical properties of the constituent layers. Besides the first realization of unidirectional phoxonic behavior, hybrid (soft-hard) periodic materials are a promising simple platform for opto-acoustic interactions and applications such as filters and Bragg mirrors.

  16. The Power of Hybridization

    CERN Document Server

    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...

  17. A Pseudoscalar Hybrid Meson?

    CERN Document Server

    Page, P R

    1996-01-01

    New experimental information on the non--exotic J^{PC} = 0^{-+} isovector seen at 1.8 GeV by VES yields convincing evidence of its excited gluonic (hybrid) nature when a critical study of alternative quarkonium assignments is made in the context of ^3 P_0 decay by flux--tube breaking. Production of this gluonic excitation via meson exchange is promising, although its two photon production vanishes.

  18. Military Hybrid Vehicle Survey

    Science.gov (United States)

    2011-08-03

    Furthermore, a standard duty cycle that is accepted for measuring fuel economy does not exist nor does a focus towards a particular technology. This...expanded into mild hybrid with the addition of a clutch connecting the generator to the transmission and additional energy storage [16-17...speed control and one for engine/generator torque [35]. Urban, Highway, Composite 33%, 27.9%, 49% General vehicle simulation [30]. Urban 19.0

  19. Fibonacci-Pell Hybridities

    Science.gov (United States)

    Koshy, Thomas; Gao, Zhenguang

    2012-01-01

    We develop a recurrence satisfied by the Fibonacci and Pell families. We then use it to find explicit formulae and generating functions for the hybrids "F[subscript n]P[subscript n]", "L[subscript n]P[subscript n]", "F[subscript n]Q[subscript n]" and "L[subscript n]Q[subscript n]", where "F[subscript n]", "L[subscript n]", "P[subscript n]" and…

  20. 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.

  1. 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.

  2. 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.

  3. 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.

  4. Hybrid Keyword Search Auctions

    CERN Document Server

    Goel, Ashish

    2008-01-01

    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) It takes into account 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, the hybrid auction can result in significantly higher revenue. 3) An advertiser who believes that its click-probability is much higher than the auctioneer's es...

  5. Printed hybrid systems

    Science.gov (United States)

    Karioja, Pentti; Mäkinen, Jukka-Tapani; Keränen, Kimmo; Aikio, Janne; Alajoki, Teemu; Jaakola, Tuomo; Koponen, Matti; Keränen, Antti; Heikkinen, Mikko; Tuomikoski, Markus; Suhonen, Riikka; Hakalahti, Leena; Kopola, Pälvi; Hast, Jukka; Liedert, Ralf; Hiltunen, Jussi; Masuda, Noriyuki; Kemppainen, Antti; Rönkä, Kari; Korhonen, Raimo

    2012-04-01

    This paper presents research activities carried out at VTT Technical Research Centre of Finland in the field of hybrid integration of optics, electronics and mechanics. Main focus area in our research is the manufacturing of electronic modules and product structures with printed electronics, film-over-molding and polymer sheet lamination technologies and the goal is in the next generation of smart systems utilizing monolithic polymer packages. The combination of manufacturing technologies such as roll-to-roll -printing, injection molding and traditional component assembly is called Printed Hybrid Systems (PHS). Several demonstrator structures have been made, which show the potential of polymer packaging technology. One demonstrator example is a laminated structure with embedded LED chips. Element thickness is only 0.3mm and the flexible stack of foils can be bent in two directions after assembly process and was shaped curved using heat and pressure. The combination of printed flexible circuit boards and injection molding has also been demonstrated with several functional modules. The demonstrators illustrate the potential of origami electronics, which can be cut and folded to 3D shapes. It shows that several manufacturing process steps can be eliminated by Printed Hybrid Systems technology. The main benefits of this combination are small size, ruggedness and conformality. The devices are ideally suited for medical applications as the sensitive electronic components are well protected inside the plastic and the structures can be cleaned easily due to the fact that they have no joints or seams that can accumulate dirt or bacteria.

  6. 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.

  7. Student Variability in Learning Advanced Physics

    CERN Document Server

    Sampson, T

    2013-01-01

    Learning of advanced physics, requires a combination of empirical, conceptual and theoretical understanding. Students use a combination of these approaches to learn new material. Each student has different prior knowledge and will master new material at a different pace. However, conventional classroom teaching usually does not accommodate the different learning paces of students. To both, study and address this issue, we developed an iterative Online Learning Machine (iOLM), which provides new learning content to each student based on their individual learning pace and tracks their progress individually. The iOLM learning module was implemented using server side web software (php) to supplement the undergraduate course in electromagnetic waves for majors in physics in their second year. This approach follows the hybrid online learning model. Students had to complete a section of the course using iOLM, which was only presented online. The data obtained for this class showed a wide spread of learning paces, ra...

  8. Learning Networks, Networked Learning

    NARCIS (Netherlands)

    Sloep, Peter

    2011-01-01

    Sloep, P. B. (2011). Learning Networks, Networked Learning. Presentation at Annual Assembly of the European Society for the Systemic Innovation of Education - ESSIE. May, 27, 2011, Leuven, Belgium: Open University in the Netherlands.

  9. 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

  10. 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

  11. Designing Learning for Co-Creation

    DEFF Research Database (Denmark)

    Gnaur, Dorina; Larsen-Nielsen, Inger Marie

    2017-01-01

    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...

  12. The evolution of learning.

    Science.gov (United States)

    Moore, Bruce R

    2004-05-01

    Most processes or forms of learning have been treated almost as special creations, each as an independent process unrelated to others. This review offers an evolutionary cladogram linking nearly one hundred forms of learning and showing the paths through which they evolved. Many processes have multiple forms. There are at least five imprinting processes, eleven varieties of Pavlovian conditioning, ten of instrumental conditioning, and eight forms of mimicry and imitation. Song learning evolved independently in at least six groups of animals, and movement imitation in three (great apes, cetaceans and psittacine birds). The cladogram also involves at least eight new processes: abstract concept formation, percussive mimicry, cross-modal imitation, apo-conditioning, hybrid conditioning, proto-pantomime, prosodic mimicry, and image-mediated learning. At least eight of the processes evolved from more than one source. Multiple sources are of course consistent with modern evolutionary theory, as seen in some obligate symbionts, and gene-swapping organisms. Song learning is believed to have evolved from two processes: auditory imprinting and skill learning. Many single words evolved from three sources: vocal mimicry, discrimination learning, and abstract concept formation.

  13. 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...

  14. Toward a Student-Centered Measure of Learning Management System Utilization

    Science.gov (United States)

    Malm, Eric; Defranco, Joanna F.

    2012-01-01

    Colleges and universities have spent significant financial and human resources deploying and promoting educational technologies, including Learning Management Systems (LMS). A large body of research now exists on the impact of technology on student learning, including the roles of blended learning, hybrid classes, and distance learning. Yet,…

  15. Hybridization in geese: a review

    OpenAIRE

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

    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 knowledge gap in geese. In this review, we assemble the available information on hybrid geese by focusing on three main themes: (1) incidence and frequency, (2) behavioural mechanisms leading to hybridizatio...

  16. Hybrid solar lighting distribution systems and components

    Science.gov (United States)

    Muhs, Jeffrey D.; Earl, Dennis D.; Beshears, David L.; Maxey, Lonnie C.; Jordan, John K.; Lind, Randall F.

    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.

  17. Hybrid solar lighting systems and components

    Science.gov (United States)

    Muhs, Jeffrey D.; Earl, Dennis D.; Beshears, David L.; Maxey, Lonnie C.; Jordan, John K.; Lind, Randall F.

    2007-06-12

    A hybrid solar lighting 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 each component.

  18. 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?......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?...

  19. 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)

  20. Cryogenic Hybrid Magnetic Bearing

    Science.gov (United States)

    Meeks, Crawford R.; Dirusso, Eliseo; Brown, Gerald V.

    1994-01-01

    Cryogenic hybrid magnetic bearing is example of class of magnetic bearings in which permanent magnets and electromagnets used to suspend shafts. Electromagnets provide active control of position of shaft. Bearing operates at temperatures from -320 degrees F (-196 degrees C) to 650 degrees F (343 degrees C); designed for possible use in rocket-engine turbopumps, where effects of cryogenic environment and fluid severely limit lubrication of conventional ball bearings. This and similar bearings also suitable for terrestrial rotating machinery; for example, gas-turbine engines, high-vacuum pumps, canned pumps, precise gimbals that suspend sensors, and pumps that handle corrosive or gritty fluids.

  1. Hybrid power semiconductor

    Science.gov (United States)

    Chen, D. Y.

    1985-10-01

    The voltage rating of a bipolar transistor may be greatly extended while at the same time reducing its switching time by operating it in conjunction with FETs in a hybrid circuit. One FET is used to drive the bipolar transistor while the other FET is connected in series with the transistor and an inductive load. Both FETs are turned on or off by a single drive signal of load power, the second FET upon ceasing conductions, rendering one power electrode of the bipolar transistor open. Means are provided to dissipate currents which flow after the bipolar transistor is rendered nonconducting.

  2. Hybrid Random Fields

    CERN Document Server

    Freno, Antonino

    2011-01-01

    This book presents an exciting new synthesis of directed and undirected, discrete and continuous graphical models. Combining elements of Bayesian networks and Markov random fields, the newly introduced hybrid random fields are an interesting approach to get the best of both these worlds, with an added promise of modularity and scalability. The authors have written an enjoyable book---rigorous in the treatment of the mathematical background, but also enlivened by interesting and original historical and philosophical perspectives. -- Manfred Jaeger, Aalborg Universitet The book not only marks an

  3. 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.

  4. Hybrid Keyword Search Auctions

    OpenAIRE

    Goel, Ashish; Munagala, Kamesh

    2008-01-01

    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 ...

  5. Hybrid optofluidic biosensors

    Science.gov (United States)

    Parks, Joshua W.

    Optofluidics, born of the desire to create a system containing microfluidic environments with integrated optical elements, has seen dramatic increases in popularity over the last 10 years. In particular, the application of this technology towards chip based molecular sensors has undergone significant development. The most sensitive of these biosensors interface liquid- and solid-core antiresonant reflecting optical waveguides (ARROWs). These sensor chips are created using conventional silicon microfabrication. As such, ARROW technology has previously been unable to utilize state-of-the-art microfluidic developments because the technology used--soft polydimethyl siloxane (PDMS) micromolded chips--is unamenable to the silicon microfabrication workflows implemented in the creation of ARROW detection chips. The original goal of this thesis was to employ hybrid integration, or the connection of independently designed and fabricated optofluidic and microfluidic chips, to create enhanced biosensors with the capability of processing and detecting biological samples on a single hybrid system. After successful demonstration of this paradigm, this work expanded into a new direction--direct integration of sensing and detection technologies on a new platform with dynamic, multi-dimensional photonic re-configurability. This thesis reports a number of firsts, including: • 1,000 fold optical transmission enhancement of ARROW optofluidic detection chips through thermal annealing, • Detection of single nucleic acids on a silicon-based ARROW chip, • Hybrid optofluidic integration of ARROW detection chips and passive PDMS microfluidic chips, • Hybrid optofluidic integration of ARROW detection chips and actively controllable PDMS microfluidic chips with integrated microvalves, • On-chip concentration and detection of clinical Ebola nucleic acids, • Multimode interference (MMI) waveguide based wavelength division multiplexing for detection of single influenza virions,

  6. 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....../D) in the second hybrid algorithm. Root mean square error and maximum absolute error as the two accuracy objective are utilized to find the Pareto-optimal solution with the MOPSO and MOEA/D respectively. The proposed hybrid multi-objective designs of the interval type-2 fuzzy logic system are utilized...

  7. A Novel Hybrid Algorithm for Task Graph Scheduling

    Directory of Open Access Journals (Sweden)

    Vahid Majid Nezhad

    2011-03-01

    Full Text Available One of the important problems in multiprocessor systems is Task Graph Scheduling. Task Graph Scheduling is an NP-Hard problem. Both learning automata and genetic algorithms are search tools which are used for solving many NP-Hard problems. In this paper a new hybrid method based on Genetic Algorithm and Learning Automata is proposed. The proposed algorithm begins with an initial population of randomly generated chromosomes and after some stages, each chromosome maps to an automaton. Experimental results show that superiority of the proposed algorithm over the current approaches.

  8. A Novel Hybrid Algorithm for Task Graph Scheduling

    CERN Document Server

    Nezhad, Vahid Majid; Efimov, Evgueni

    2011-01-01

    One of the important problems in multiprocessor systems is Task Graph Scheduling. Task Graph Scheduling is an NP-Hard problem. Both learning automata and genetic algorithms are search tools which are used for solving many NP-Hard problems. In this paper a new hybrid method based on Genetic Algorithm and Learning Automata is proposed. The proposed algorithm begins with an initial population of randomly generated chromosomes and after some stages, each chromosome maps to an automaton. Experimental results show that superiority of the proposed algorithm over the current approaches.

  9. Using the Two-Hybrid Screen in the Classroom Laboratory

    OpenAIRE

    Odom, Daniel P.; Grossel, Martha J

    2002-01-01

    The National Science Foundation and others have made compelling arguments that research be incorporated into the learning of undergraduates. In response to these arguments, a two-hybrid research project was incorporated into a molecular biology course that contained both a lecture section and a laboratory section. The course was designed around specific goals for educational outcomes, including introducing research to a wide range of students, teaching students experimental design and data an...

  10. Hybrid vehicle potential assessment. Volume 7. Hybrid vehicle review

    Energy Technology Data Exchange (ETDEWEB)

    Leschly, K.O.

    1979-09-30

    Review of hybrid vehicles (HVs) 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 on-road hybrid passenger cars, trucks, vans, and buses.

  11. 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.

  12. 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).

  13. Analysis of hybrid viscous damper by real time hybrid simulations

    DEFF Research Database (Denmark)

    Brodersen, Mark Laier; Ou, Ge; Høgsberg, Jan Becker

    2016-01-01

    Results from real time hybrid simulations are compared to full numerical simulations for a hybrid viscous damper, composed of a viscous dashpot in series with an active actuator and a load cell. By controlling the actuator displacement via filtered integral force feedback the damping performance...... of the hybrid viscous damper is improved, while for pure integral force feedback the damper stroke is instead increased. In the real time hybrid simulations viscous damping is emulated by a bang-bang controlled Magneto-Rheological (MR) damper. The controller activates high-frequency modes and generates drift...... in the actuator displacement, and only a fraction of the measured damper force can therefore be used as input to the investigated integral force feedback in the real time hybrid simulations....

  14. 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.

  15. Arabidopsis hybrid speciation processes.

    Science.gov (United States)

    Schmickl, Roswitha; Koch, Marcus A

    2011-08-23

    The genus Arabidopsis provides a unique opportunity to study fundamental biological questions in plant sciences using the diploid model species Arabidopsis thaliana and Arabidopsis lyrata. However, only a few studies have focused on introgression and hybrid speciation in Arabidopsis, although polyploidy is a common phenomenon within this genus. More recently, there is growing evidence of significant gene flow between the various Arabidopsis species. So far, we know Arabidopsis suecica and Arabidopsis kamchatica as fully stabilized allopolyploid species. Both species evolved during Pleistocene glaciation and deglaciation cycles in Fennoscandinavia and the amphi-Beringian region, respectively. These hybrid studies were conducted either on a phylogeographic scale or reconstructed experimentally in the laboratory. In our study we focus at a regional and population level. Our research area is located in the foothills of the eastern Austrian Alps, where two Arabidopsis species, Arabidopsis arenosa and A. lyrata ssp. petraea, are sympatrically distributed. Our hypothesis of genetic introgression, migration, and adaptation to the changing environment during the Pleistocene has been confirmed: We observed significant, mainly unidirectional gene flow between the two species, which has given rise to the tetraploid A. lyrata. This cytotype was able to escape from the narrow ecological niche occupied by diploid A. lyrata ssp. petraea on limestone outcrops by migrating northward into siliceous areas, leaving behind a trail of genetic differentiation.

  16. Suppression subtractive hybridization.

    Science.gov (United States)

    Ghorbel, Mohamed T; Murphy, David

    2011-01-01

    Comparing two RNA populations that differ from the effects of a single independent variable, such as a drug treatment or a specific genetic defect, can establish differences in the abundance of specific transcripts that vary in a population dependent manner. There are different methods for identifying differentially expressed genes. These methods include microarray, Serial Analysis of Gene Expression (SAGE), and quantitative Reverse-Transcriptase Polymerase Chain Reaction (qRT-PCR). Herein, the protocol describes an easy and cost-effective alternative that does not require prior knowledge of the transcriptomes under examination. It is specifically relevant when low levels of RNA starting material are available. This protocol describes the use of Switching Mechanism At RNA Termini Polymerase Chain Reaction (SMART-PCR) to amplify cDNA from small amounts of RNA. The amplified cDNA populations under comparison are then subjected to Suppression Subtractive Hybridization (SSH-PCR). SSH-PCR is a technique that couples subtractive hybridization with suppression PCR to selectively amplify fragments of differentially expressed genes. The resulting products are cDNA populations enriched for significantly overrepresented transcripts in either of the two input RNAs. These cDNA populations can then be cloned to generate subtracted cDNA library. Microarrays made with clones from the subtracted forward and reverse cDNA libraries are then screened for differentially expressed genes using targets generated from tester and driver total RNAs.

  17. Landmarks in Hybrid Planning

    Directory of Open Access Journals (Sweden)

    Mohamed Elkawkagy

    2013-11-01

    Full Text Available Although planning techniques achieved a significant progress during recent years, solving many planning problem still difficult even for modern planners. In this paper, we will adopt landmark concept to hybrid planning setting - a method that combines reasoning about procedural knowledge and causalities. Land-marks are a well-known concept in the realm of classical planning. Recently, they have been adapted to hierarchical approaches. Such landmarks can be extracted in a pre-processing step from a declarative hierarchical planning domain and problem description. It was shown how this technique allows for a considerable reduction of the search space by eliminating futile plan development options before the actual planning. Therefore, we will present a new approach to in¬tegrate landmark pre-processing technique in the context of hierarchical planning with landmark technique in the classical planning. This integration allows to incorporate the ability of using extracted landmark tasks from hierarchical domain knowledge in the form of HTN and using landmark literals from classical planning. To this end, we will construct a transformation technique to transform the hybrid planning domain into a classical domain model. The method¬ologies in this paper have been implemented successfully, and we will present some experimental results that give evidence for the consid-erable performance increase gained through planning system.

  18. Overview on hybrid propulsion

    Science.gov (United States)

    Calabro, M.

    2011-10-01

    Aside of research works, this historical survey shows propulsion units used by students for small satellites and for gas generation, or those for the Space Ship One, even if LOx/HTPB was studied and tested in large motors for its potential very low cost; however, this combination highlights a series of technical problems without any performance advantage over the existing LOx/Kerosene family and never been operational for ETO applications. The particularity of hybrid propulsion is to use the state-of-the-art of both liquids and solids; the only show stopper is the propellant itself. The past work focused on LOx/HTPB (selected for its low cost) appears to be a dead-end (combustion problems and global low performances resulting from a high level of residuals). The solution that appears through the past experience is the addition of hydrides to a binder (HTPB or other) or to a binder and a homogeneous fuel or a mixture of both, with or without others additives; within these solutions some will not present any manufacturing problem and some may have a low cost. Nevertheless, the studies of the following phases have to demonstrate the compatibility of the potential regression rate range with a high-performance global design of a hybrid Motor and the manufacturing at a reasonable cost of a hydride giving a high level of performances.

  19. 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.

  20. Hybrid internet access

    Science.gov (United States)

    Arora, Vivek; Baras, John S.; Dillon, Douglas; Falk, Aaron; Suphasindhu, Narin

    1995-01-01

    Access to the Internet is either too slow (dial-up SLIP) or too expensive (switched 56 kbps, frame relay) for the home user or small enterprise. The Center for Satellite and Hybrid Communication Networks and Hughes Network Systems have collaborated using systems integration principles to develop a prototype of a low-cost hybrid (dial-up and satellite) newtork terminal which can deliver data from the Internet to the user at rates up to 160 kbps. An asymmetric TCP/IP connection is used breaking the network link into two physical channels: a terrestrial dial-up for carrying data from the terminal into the Internet and a receive-only satellite link carrying IP packets from the Internet to the user. With a goal of supporting bandwidth hungry Internet applications such as Mosaic, Gopher, and FTP, this system has been designed to support any Intel 80386/486 PC, any commercial TCP/IP package, any unmodified host on the Internet, and any of the routers, etc., within the Internet. The design exploits the following three observations: 1) satellites are able to offer high bandwidth connections to a large geographical area, 2) a receive-only VSAT is cheap to manufacture and easier to install than one which can also transmit, and 3) most computer users, especially those in a home environment, will want to consume much more information than they generate. IP encapsulation, or tunneling, issued to manipulate the TCP/IP protocols to route packets asymmetrically.

  1. Unified Hybrid Network Theoretical Model Trilogy

    Institute of Scientific and Technical Information of China (English)

    2011-01-01

    The first of the unified hybrid network theoretical model trilogy (UHNTF) is the harmonious unification hybrid preferential model (HUHPM), seen in the inner loop of Fig. 1, the unified hybrid ratio is defined.

  2. 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.

  3. 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....

  4. Chaotic Dynamics in Hybrid Systems

    NARCIS (Netherlands)

    P.J. Collins (Pieter)

    2008-01-01

    htmlabstractIn this paper we give an overview of some aspects of chaotic dynamics in hybrid systems, which comprise different types of behaviour. Hybrid systems may exhibit discontinuous dependence on initial conditions leading to new dynamical phenomena. We indicate how methods from topological

  5. Chaotic dynamics in hybrid systems

    NARCIS (Netherlands)

    P.J. Collins (Pieter)

    2008-01-01

    htmlabstractIn this paper we give an overview of some aspects of chaotic dynamics in hybrid systems, which comprise different types of behaviour. Hybrid systems may exhibit discontinuous dependence on initial conditions leading to new dynamical phenomena. We indicate how methods from topological

  6. 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?...

  7. 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....

  8. Hybridity in Embedded Computing Systems

    Institute of Scientific and Technical Information of China (English)

    虞慧群; 孙永强

    1996-01-01

    An embedded system is a system that computer is used as a component in a larger device.In this paper,we study hybridity in embedded systems and present an interval based temporal logic to express and reason about hybrid properties of such kind of systems.

  9. 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.

  10. Hybrid Charmonium from Lattice QCD

    CERN Document Server

    Luo, X Q

    2006-01-01

    We review our recent results on the JPC = 0¡¡ exotic hybrid charmonium mass and JPC = 0¡+, 1¡¡ and 1++ nonexotic hybrid charmonium spectrum from anisotropic improved lattice QCD and discuss the relevance to the recent discovery of the Y(4260) state and future experimental search for other states.

  11. 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.

  12. Connectivity of learning in MOOCs: Facilitators’ experiencies in team teaching

    OpenAIRE

    Mercado Varela, Martín A.; Beltran Jesús; Villegas Pérez, Marisol; Rivera Vazquez, Nohemi; Ramírez Montoya, María S.

    2017-01-01

    The role of facilitators in distance learning environments is of substantial importance in supporting the learning process. This article specifically discusses the role of the facilitator in Massive Open Online Courses (MOOC), which are characterized by their stimulation of learning connections. The study analyzes the experiences of 135 facilitators in hybrid courses (cMOOC + xMOOC) where the following are explored: (1) the strategies used by the facilitators to encourage learning connections...

  13. CONNECTIVITY OF LEARNING IN MOOCs: FACILITATORS’ EXPERIENCES IN TEAM TEACHING

    OpenAIRE

    MERCADO-VARELA, Martin Alonso; BELTRAN, Jesus; PEREZ, Marisol Villegas; VAZQUEZ, Nohemi Rivera; RAMIREZ-MONTOYA, Maria-Soledad

    2017-01-01

    The role of facilitators in distance learning environments is of substantial importance in supporting the learning process. This article specifically discusses the role of the facilitator in Massive Open Online Courses (MOOC), which are characterized by their stimulation of learning connections. The study analyzes the experiences of 135 facilitators in hybrid courses (cMOOC + xMOOC) where the following are explored: (1) the strategies used by the facilitators to encourage learning connections...

  14. Learning Problems

    Science.gov (United States)

    ... de los dientes Video: Getting an X-ray Learning Problems KidsHealth > For Kids > Learning Problems Print A ... for how to make it better. What Are Learning Disabilities? Learning disabilities aren't contagious, but they ...

  15. Learning Disabilities

    Science.gov (United States)

    ... Loss Surgery? A Week of Healthy Breakfasts Shyness Learning Disabilities KidsHealth > For Teens > Learning Disabilities Print A ... study engineering as he'd hoped? What Are Learning Disabilities? For someone diagnosed with a learning disability, ...

  16. 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...

  17. Detecting hybridization using ancient DNA.

    Science.gov (United States)

    Schaefer, Nathan K; Shapiro, Beth; Green, Richard E

    2016-06-01

    It is well established that related species hybridize and that this can have varied but significant effects on speciation and environmental adaptation. It should therefore come as no surprise that hybridization is not limited to species that are alive today. In the last several decades, advances in technologies for recovering and sequencing DNA from fossil remains have enabled the assembly of high-coverage genome sequences for a growing diversity of organisms, including many that are extinct. Thanks to the development of new statistical approaches for detecting and quantifying admixture from genomic data, genomes from extinct populations have proven useful both in revealing previously unknown hybridization events and informing the study of hybridization between living organisms. Here, we review some of the key recent statistical innovations for detecting ancient hybridization using genomewide sequence data and discuss how these innovations have revised our understanding of human evolutionary history.

  18. Molecular evidence for hybridization in Colias (Lepidoptera: Pieridae): are Colias hybrids really hybrids?

    Science.gov (United States)

    Dwyer, Heather E; Jasieniuk, Marie; Okada, Miki; Shapiro, Arthur M

    2015-01-01

    Gene flow and hybridization among species dramatically affect our understanding of the species as a biological unit, species relationships, and species adaptations. In North American Colias eurytheme and Colias eriphyle, there has been historical debate over the extent of hybridization occurring and the identity of phenotypically intermediate individuals as genetic hybrids. This study assesses the population structure of these two species to measure the extent of hybridization and the genetic identity of phenotypic intermediates as hybrids. Amplified fragment length polymorphism (AFLP) marker analysis was performed on 378 specimens collected from northern California and Nevada. Population structure was inferred using a Bayesian/Markov chain Monte Carlo method, which probabilistically assigns individuals to genetic clusters. Three genetic clusters provided the best fit for the data. C. eurytheme individuals were primarily assigned to two closely related clusters, and C. eriphyle individuals were mostly assigned to a third, more distantly related cluster. There appeared to be significant hybridization between the two species. Individuals of intermediate phenotype (putative hybrids) were found to be genetically indistinguishable from C. eriphyle, indicating that previous work based on the assumption that these intermediate forms are hybrids may warrant reconsideration. PMID:26306172

  19. HYBRID INTERNET TRAFFIC CLASSIFICATION TECHNIQUE1

    Institute of Scientific and Technical Information of China (English)

    Li Jun; Zhang Shunyi; Lu Yanqing; Yan Junrong

    2009-01-01

    Accurate and real-time classification of network traffic is significant to network operation and management such as QoS differentiation, traffic shaping and security surveillance. However, with many newly emerged P2P applications using dynamic port numbers, masquerading techniques, and payload encryption to avoid detection, traditional classification approaches turn to be ineffective. In this paper, we present a layered hybrid system to classify current Internet traffic, motivated by variety of network activities and their requirements of traffic classification. The proposed method could achieve fast and accurate traffic classification with low overheads and robustness to accommodate both known and unknown/encrypted applications. Furthermore, it is feasible to be used in the context of real-time traffic classification. Our experimental results show the distinct advantages of the proposed classification system, compared with the one-step Machine Learning (ML) approach.

  20. 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.

  1. Auditing Hybrid IT Environments

    Directory of Open Access Journals (Sweden)

    Georgiana Mateescu

    2014-01-01

    Full Text Available This paper presents a personal approach of auditing the hybrid IT environments consisting in both on premise and on demand services and systems. The analysis is performed from both safety and profitability perspectives and it aims to offer to strategy, technical and business teams a representation of the value added by the cloud programme within the company’s portfolio. Starting from the importance of the IT Governance in the actual business environments, we presented in the first section the main principles that drive the technology strategy in order to maximize the value added by IT assets in the business products. Section two summarizes the frameworks leveraged by our approach in order to implement the safety and profitability computation algorithms described in the third section. The paper concludes with benefits of our personal frameworks and presents the future developments.

  2. Hybrid Noncoherent Network Coding

    CERN Document Server

    Skachek, Vitaly; Nedic, Angelia

    2011-01-01

    We describe a novel extension of subspace codes for noncoherent networks, suitable for use when the network is viewed as a communication system that introduces both dimension and symbol errors. We show that when symbol erasures occur in a significantly large number of different basis vectors transmitted through the network and when the min-cut of the networks is much smaller then the length of the transmitted codewords, the new family of codes outperforms their subspace code counterparts. For the proposed coding scheme, termed hybrid network coding, we derive two upper bounds on the size of the codes. These bounds represent a variation of the Singleton and of the sphere-packing bound. We show that a simple concatenated scheme that represents a combination of subspace codes and Reed-Solomon codes is asymptotically optimal with respect to the Singleton bound. Finally, we describe two efficient decoding algorithms for concatenated subspace codes that in certain cases have smaller complexity than subspace decoder...

  3. 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.

  4. Hybrid vehicle control

    Energy Technology Data Exchange (ETDEWEB)

    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.

  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. Hybrid Batch Bayesian Optimization

    CERN Document Server

    Azimi, Javad; Fern, Xiaoli

    2012-01-01

    Bayesian Optimization aims at optimizing an unknown non-convex/concave function that is costly to evaluate. We are interested in application scenarios where concurrent function evaluations are possible. Under such a setting, BO could choose to either sequentially evaluate the function, one input at a time and wait for the output of the function before making the next selection, or evaluate the function at a batch of multiple inputs at once. These two different settings are commonly referred to as the sequential and batch settings of Bayesian Optimization. In general, the sequential setting leads to better optimization performance as each function evaluation is selected with more information, whereas the batch setting has an advantage in terms of the total experimental time (the number of iterations). In this work, our goal is to combine the strength of both settings. Specifically, we systematically analyze Bayesian optimization using Gaussian process as the posterior estimator and provide a hybrid algorithm t...

  7. Photochromic mesoporous hybrid coatings

    Science.gov (United States)

    Raboin, L.; Matheron, M.; Gacoin, T.; Boilot, J.-P.

    2008-09-01

    Spirooxazine (SO) photochromic molecules were trapped in sol-gel matrices. In order to increase the colourability and improve mechanical properties of sol-gel photochromic films, we present an original strategy in which SO photochromic molecules were dispersed in mesoporous organized films using the impregnation technique. Well-ordered organosilicate mesoporous coatings with the 3D-hexagonal symmetry were prepared by the sol-gel technique. These robust mesoporous films, which contain high amounts of hydrophobic methyl groups at the pore surface, offer optimized environments for photochromic dyes dispersed by impregnation technique. After impregnation by a spirooxazine solution, the photochromic response is only slightly slower when compared with mesostructured or soft sol-gel matrices, showing that mesoporous organized hybrid matrix are good host for photochromic dyes. Moreover, the molecular loading in films is easily adjustable in a large range using multi-impregnation procedure and increasing the film thickness leading to coatings for optical switching devices.

  8. Hybrid Heat Exchangers

    Science.gov (United States)

    Tu, Jianping Gene; Shih, Wei

    2010-01-01

    A hybrid light-weight heat exchanger concept has been developed that uses high-conductivity carbon-carbon (C-C) composites as the heat-transfer fins and uses conventional high-temperature metals, such as Inconel, nickel, and titanium as the parting sheets to meet leakage and structural requirements. In order to maximize thermal conductivity, the majority of carbon fiber is aligned in the fin direction resulting in 300 W/m.K or higher conductivity in the fin directions. As a result of this fiber orientation, the coefficient of thermal expansion (CTE) of the C-C composite in both non-fiber directions matches well with the CTE of various high-temperature metal alloys. This allows the joining of fins and parting sheets by using high-temperature braze alloys.

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

    DEFF Research Database (Denmark)

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

    2017-01-01

    An increasingly complex hybrid system of social- and traditional-news media surrounds Nordic election campaigns as politically experienced incumbents favour traditional news media, and younger, lesser-known candidates’ social media. Despite little evidence for hybrid-media politicians, politicians......’ 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...

  10. 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

  11. Wankel engine for hybrid powertrain

    Energy Technology Data Exchange (ETDEWEB)

    Butti, A. [Univ. of Florence (Italy); Site, V.D.

    1995-12-31

    The Wankel engine is suited to be used to drive hybrid propulsion systems. The main disadvantage of hybrid propulsion systems is the complexity that causes a high weight and large dimensions. For these reason hybrid systems are more suitable for large size vehicle (buses, vans) rather than for small passenger cars. A considerable reduction of hybrid systems weight and dimensions can be obtained using a Wankel rotary engine instead of a conventional engine. The Wankel engine is light, compact, simple, and produces low noise and low vibrations. Therefore a Wankel engine powered hybrid system is suited to be used on small cars. In this paper a 1,000 kg parallel hybrid car with continuously variable transmission and a 6,000 kg series hybrid minibus both equipped with Wankel engines are considered. The Wankel engine works at steady state to minimize fuel consumption and exhaust emissions. The simulation of the behavior of these two vehicles during a ECE + EUDC test cycle is presented in order to evaluate the performances of the systems.

  12. Fabrication of Hybrid Petroelectric Vehicle

    Directory of Open Access Journals (Sweden)

    G. Adinarayana

    2014-10-01

    Full Text Available In automobile sector, the need for alternative fuel as a replacement of conventional fossil fuel, due to its depletion and amount of emission has given way for new technologies like Fuel cells vehicles, Electric vehicles. Still a lot of advancement has to take place in these technologies for commercialization. The gap between the current fossil fuel technology and zero emission vehicles can be bridged by hybrid technology. Hybrid vehicles are those which can run on two or more powering sources/fuels. Feasibility of this technology is been proved in four wheelers and automobile giants like Toyota, Honda, and Hyundai have launched successful vehicles like Toyota prius, Honda insight etc. This technology maximizes the advantages of the two fuels and minimizes the disadvantages of the same. The best preferred hybrid pair is electric and fossil fuel. This increases the mileage of the vehicle twice the existing and also reduces the emission to half. At present, we like to explore the hybrid technology in the two wheeler sector and its feasibility on road. This paper deals with an attempt to make a hybrid with electric start and petrol run. Further a design of basic hybrid elements like motor, battery, and engine. As on today, hybrid products are one of the best solutions for all pollution hazards at a fairly nominal price. An investment within the means of a common man that guarantees a better environment to live in.

  13. 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.

  14. 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.

  15. Learning to aid learning.

    Science.gov (United States)

    Richards, Jacqui

    2016-01-01

    The National Health Service (NHS) is one of the largest employers in the world and, with 1.3 million staff, the biggest employer in Europe. With over three hundred different careers on offer (NHS 2015), the acquisition of skills and qualifications, through academic and clinical training, is an integral part of day-to-day life in the health service. As such, mentoring has become a significant feature in the preparation of healthcare professionals, to support students and ensure learning needs and experiences are appropriate to competency. This article examines the mentor's role, in relation to a teaching innovation designed to address students' identified learning needs to meet the requirements of the multi-professional learning and assessment in practice course NM6156. The effectiveness of the aids to learning will be assessed through an online quiz, and its usefulness will be analysed with reference to educational theories of learning and development.

  16. 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.

  17. Hybrid Vehicle Program. Final report

    Energy Technology Data Exchange (ETDEWEB)

    None

    1984-06-01

    This report summarizes the activities on the Hybrid Vehicle Program. The program objectives and the vehicle specifications are reviewed. The Hybrid Vehicle has been designed so that maximum use can be made of existing production components with a minimum compromise to program goals. The program status as of the February 9-10 Hardware Test Review is presented, and discussions of the vehicle subsystem, the hybrid propulsion subsystem, the battery subsystem, and the test mule programs are included. Other program aspects included are quality assurance and support equipment. 16 references, 132 figures, 47 tables.

  18. Pseudovector mesons, hybrids and glueballs

    CERN Document Server

    Burakovsky, L; Burakovsky, Leonid; Page, Philip R.

    2000-01-01

    We consider glueball- (hybrid) meson mixing for the low-lying four pseudovector states. The h_1'(1380) decays dominantly to K*K with some presence in rho pi and omega eta. The newly observed h_1(1600) has a D- to S-wave width ratio to omega eta which does not enable differentiation between a conventional and hybrid meson interpretation. We predict the decay pattern of the isopartner conventional or hybrid meson b_1(1650). A notably narrow s sbar partner h_1'(1810) is predicted.

  19. 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...... the way we interpret @i in propositional and first-order hybrid logic. This means: interpret @iαa , where αa is an expression of any type a , as an expression of type a that rigidly returns the value that αa receives at the i-world. The axiomatization and completeness proofs are generalizations of those...

  20. Hybrid codes: Methods and applications

    Energy Technology Data Exchange (ETDEWEB)

    Winske, D. (Los Alamos National Lab., NM (USA)); Omidi, N. (California Univ., San Diego, La Jolla, CA (USA))

    1991-01-01

    In this chapter we discuss hybrid'' algorithms used in the study of low frequency electromagnetic phenomena, where one or more ion species are treated kinetically via standard PIC methods used in particle codes and the electrons are treated as a single charge neutralizing massless fluid. Other types of hybrid models are possible, as discussed in Winske and Quest, but hybrid codes with particle ions and massless fluid electrons have become the most common for simulating space plasma physics phenomena in the last decade, as we discuss in this paper.

  1. Hybrid laser-arc welding

    DEFF Research Database (Denmark)

    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...

  2. 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…

  3. 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

  4. Advanced Hybrid Computer Systems. Software Technology.

    Science.gov (United States)

    This software technology final report evaluates advances made in Advanced Hybrid Computer System software technology . The report describes what...automatic patching software is available as well as which analog/hybrid programming languages would be most feasible for the Advanced Hybrid Computer...compiler software . The problem of how software would interface with the hybrid system is also presented.

  5. Hybrid Clustering-Classification Neural Network in the Medical Diagnostics of the Reactive Arthritis

    Directory of Open Access Journals (Sweden)

    Yevgeniy Bodyanskiy

    2016-08-01

    Full Text Available In the paper, the hybrid clustering-classification neural network is proposed. This network allows to increase a quality of information processing under the condition of overlapping classes due to the rational choice of learning rate parameter and introducing special procedure of fuzzy reasoning in the clustering-classification process, which occurs both with external learning signal ("supervised", and without one ("unsupervised". As similarity measure neighborhood function or membership one, cosine structures are used, which allow to provide a high flexibility due to self-learning-learning process and to provide some new useful properties. Many realized experiments have confirmed the efficiency of proposed hybrid clustering-classification neural network; also, this network was used for solving diagnostics task of reactive arthritis.

  6. How common is homoploid hybrid speciation?

    Science.gov (United States)

    Schumer, Molly; Rosenthal, Gil G; Andolfatto, Peter

    2014-06-01

    Hybridization has long been considered a process that prevents divergence between species. In contrast to this historical view, an increasing number of empirical studies claim to show evidence for hybrid speciation without a ploidy change. However, the importance of hybridization as a route to speciation is poorly understood, and many claims have been made with insufficient evidence that hybridization played a role in the speciation process. We propose criteria to determine the strength of evidence for homoploid hybrid speciation. Based on an evaluation of the literature using this framework, we conclude that although hybridization appears to be common, evidence for an important role of hybridization in homoploid speciation is more circumscribed.

  7. 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)

  8. 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.

  9. 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.

  10. Hybrid models for complex fluids

    CERN Document Server

    Tronci, Cesare

    2010-01-01

    This paper formulates a new approach to complex fluid dynamics, which accounts for microscopic statistical effects in the micromotion. While the ordinary fluid variables (mass density and momentum) undergo usual dynamics, the order parameter field is replaced by a statistical distribution on the order parameter space. This distribution depends also on the point in physical space and its dynamics retains the usual fluid transport features while containing the statistical information on the order parameter space. This approach is based on a hybrid moment closure for Yang-Mills Vlasov plasmas, which replaces the usual cold-plasma assumption. After presenting the basic properties of the hybrid closure, such as momentum map features, singular solutions and Casimir invariants, the effect of Yang-Mills fields is considered and a direct application to ferromagnetic fluids is presented. Hybrid models are also formulated for complex fluids with symmetry breaking. For the special case of liquid crystals, a hybrid formul...

  11. Annular Hybrid Rocket Motor Project

    Data.gov (United States)

    National Aeronautics and Space Administration — Engineers at SpaceDev have conducted a preliminary design and analysis of a proprietary annular design concept for a hybrid motor. A U.S. Patent application has been...

  12. 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....

  13. Towards Modelling of Hybrid Systems

    DEFF Research Database (Denmark)

    Wisniewski, Rafal

    2006-01-01

    The article is an attempt to use methods of category theory and topology for analysis of hybrid systems. We use the notion of a directed topological space; it is a topological space together with a set of privileged paths. Dynamical systems are examples of directed topological spaces. A hybrid...... 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...... directed homotopy colimit (geometric realization) is a single directed topological space. The behavior of hybrid systems can be then understood in terms of the behavior of dynamical systems through the directed homotopy colimit....

  14. 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.

  15. A hybrid base isolation system

    Energy Technology Data Exchange (ETDEWEB)

    Hart, G.C. [Univ. of California, Los Angeles, CA (United States); Lobo, R.F.; Srinivasan, M. [Hart Consultant Group, Santa Monica, CA (United States); Asher, J.W. [kpff Engineers, Santa Monica, CA (United States)

    1995-12-01

    This paper proposes a new analysis procedure for hybrid base isolation buildings when considering the displacement response of a base isolated building to wind loads. The system is considered hybrid because of the presence of viscous dampers in the building above the isolator level. The proposed analysis approach incorporates a detailed site specific wind study combined with a dynamic nonlinear analysis of the building response.

  16. Ion-atom hybrid systems

    CERN Document Server

    Willitsch, Stefan

    2014-01-01

    The study of interactions between simultaneously trapped cold ions and atoms has emerged as a new research direction in recent years. The development of ion-atom hybrid experiments has paved the way for investigating elastic, inelastic and reactive collisions between these species at very low temperatures, for exploring new cooling mechanisms of ions by atoms and for implementing new hybrid quantum systems. The present lecture reviews experimental methods, recent results and upcoming developments in this emerging field.

  17. Information component of hybrid war

    OpenAIRE

    Bohdanov, Aleksander

    2015-01-01

    A hybrid warfare in the three-dimensional coordinate system «Matter-Information-measure» is considering. In particular, the information component is highlighted and analyzed. The factors of preparation of information operations is defined, which are disclosed as an example of experience of volunteer group information warfare of Institute of special communication and information security of NTUU «KPI».Keywords: coordinate system «Matter-Information-Measure» hybrid warfare, information componen...

  18. 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 ...... processes to be embedded into the logic. The semantics thus provides a secure link to hybrid system models based on a general theory of dynamical systems....

  19. 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.

  20. Hybridity and complexity

    DEFF Research Database (Denmark)

    Lønsmann, Dorte; Haberland, Hartmut

    2013-01-01

    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......-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...

  1. Hybrid cluster identification

    Science.gov (United States)

    Martín-Herrero, J.

    2004-10-01

    I present a hybrid method for the labelling of clusters in two-dimensional lattices, which combines the recursive approach with iterative scanning to reduce the stack size required by the pure recursive technique, while keeping its benefits: single pass and straightforward cluster characterization and percolation detection parallel to the labelling. While the capacity to hold the entire lattice in memory is usually regarded as the major constraint for the applicability of the recursive technique, the required stack size is the real limiting factor. Resorting to recursion only for the transverse direction greatly reduces the recursion depth and therefore the required stack. It also enhances the overall performance of the recursive technique, as is shown by results on a set of uniform random binary lattices and on a set of samples of the Ising model. I also show how this technique may replace the recursive technique in Wolff's cluster algorithm, decreasing the risk of stack overflow and increasing its speed, and the Hoshen-Kopelman algorithm in the Swendsen-Wang cluster algorithm, allowing effortless characterization during generation of the samples and increasing its speed.

  2. ADVANCED HYBRID PARTICULATE COLLECTOR

    Energy Technology Data Exchange (ETDEWEB)

    Stanley J. Miller; Grant L. Schelkoph; Grant E. Dunham

    2000-12-01

    A new concept in particulate control, called an advanced hybrid particulate collector (AHPC), is being developed under funding from the US 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 recollection 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-hour parametric tests and 100-hour proof-of-concept tests with two different coals demonstrated excellent operability and greater than 99.99% fine-particle collection efficiency.

  3. Hybrid superconductor magnet bearings

    Science.gov (United States)

    Chu, Wei-Kan

    1995-01-01

    Hybrid superconductor magnet bearings (HSMB's) utilize high temperature superconductors (HTS's) together with permanent magnets to form a frictionless interface between relatively rotating parts. They are low mass, stable, and do not incur expenditure of energy during normal operation. There is no direct physical contact between rotor and stator, and hence there is no wear and tear. However, just as any other applications of HTS's, it requires a very cold temperature to function. Whereas this might be perceived as a disadvantage on earth, it is of no great concern in space or on the moon. To astronomers, the moon is an excellent site for an observatory, but the cold and dusty vacuum environment on the moon precludes the use of mechanical bearings on the telescope mounts. Furthermore, drive mechanisms with very fine steps, and hence bearings with extremely low friction are needed to track a star from the moon, because the moon rotates very slowly. All aspects considered, the HSMB is about the only candidate that fits in naturally. Here, we present a design for one such bearing, capable of supporting a telescope that weighs about 3 lbs on Earth.

  4. Hybrid Power Management (HPM)

    Science.gov (United States)

    Eichenberg, Dennis J.

    2007-01-01

    The NASA Glenn Research Center s Avionics, Power and Communications Branch of the Engineering and Systems Division initiated the Hybrid Power Management (HPM) Program for the GRC Technology Transfer and Partnership Office. HPM is the innovative integration of diverse, state-of-the-art power devices in an optimal configuration for space and terrestrial applications. The appropriate application and control of the various power devices significantly improves overall system performance and efficiency. The advanced power devices include ultracapacitors and fuel cells. HPM has extremely wide potential. Applications include power generation, transportation systems, biotechnology systems, and space power systems. HPM has the potential to significantly alleviate global energy concerns, improve the environment, and stimulate the economy. One of the unique power devices being utilized by HPM for energy storage is the ultracapacitor. An ultracapacitor is an electrochemical energy storage device, which has extremely high volumetric capacitance energy due to high surface area electrodes, and very small electrode separation. Ultracapacitors are a reliable, long life, maintenance free, energy storage system. This flexible operating system can be applied to all power systems to significantly improve system efficiency, reliability, and performance. There are many existing and conceptual applications of HPM.

  5. 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.

  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. 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.

  9. Perceptions of learning as a function of seminar group factors

    NARCIS (Netherlands)

    Jaarsma, A. Debbie C.; de Grave, Willem S.; Muijtjens, Arno M. M.; Scherpbier, Albert J. J. A.; van Beukelen, Peter

    2008-01-01

    Small-group learning is advocated for enhancing higher-order thinking and the development of skills and attitudes. Teacher performance, group interaction and the quality of assignments have been shown to affect small-group learning in hybrid and problem-based curricula. This study aimed to examine

  10. Spatial Semantic Objects-based Hybrid Learning Method for Automatic Complicated Scene Classification%基于空间语义对象混合学习的复杂图像场景自动分类方法研究

    Institute of Scientific and Technical Information of China (English)

    孙显; 付琨; 王宏琦

    2011-01-01

    Scene image classification refers to the task of grouping different images into semantic categories. A new spatial semantic objects-based hybrid learning method is proposed to overcome the disadvantages existing in most of the relative methods. This method uses generative model to deal with the objects obtained by multi-scale segmentation instead of whole image, and calculates kinds of visual features to mine the category information of every objects. Then, an intermediate vector is generated using spatial-pyramid matching algorithm, to describe both the layer data and semantic information and narrow down the “semantic gap”. The method also combines a discriminative learning procedure to train a more confident classifier. Experimental results demonstrate that the proposed method can achieve high training efficiency and classification accuracy in interpreting manifold and complicated images.%场景分类是将多幅图像标记为不同语义类别的过程.该文针对现有方法对复杂图像场景分类性能欠佳的不足,提出一种新的基于空间语义对象混合学习的复杂图像场景分类方法.该方法以多尺度分割得到的图像对象而非整幅图像为主体进行产生式语义建模,统计各类有效特征挖掘对象的类别分布信息,并通过空间金字塔匹配,构建包含层次数据和语义信息的中间向量,弥补语义鸿沟的缺陷,训练中还结合判别式学习提高分类器的可信性.在实验数据集上的结果表明该方法具备较高的学习性能和分类精度,适用于多种类型和复杂内容图像的解译,具有较强的实用价值.

  11. 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.

  12. The e-Learning Café project of the University of Porto: innovative learning spaces, improving students' engagement in active and collaborative learning

    OpenAIRE

    Pedro Neto; Andrea Vieira; Lígia Ribeiro; Maria Pinto

    2013-01-01

    This paper reports the ongoing research project headed by the University of Porto (U.Porto) and the research group Centre of Spatial Representation and Communication (CCRE), from de R&D Centre of its Faculty of Architecture (FAUP), which aims the design and study of hybrid spatial environments: e-Learning Centres. The state of the art review discusses the significance of informal physical learning spaces for learning activities in academic education. The most important outcomes of research ar...

  13. Hybridization in a warmer world.

    Science.gov (United States)

    Chunco, Amanda J

    2014-05-01

    Climate change is profoundly affecting the evolutionary trajectory of individual species and ecological communities, in part through the creation of novel species assemblages. How climate change will influence competitive interactions has been an active area of research. Far less attention, however, has been given to altered reproductive interactions. Yet, reproductive interactions between formerly isolated species are inevitable as populations shift geographically and temporally as a result of climate change, potentially resulting in introgression, speciation, or even extinction. The susceptibility of hybridization rates to anthropogenic disturbance was first recognized in the 1930s. To date, work on anthropogenically mediated hybridization has focused primarily on either physical habitat disturbance or species invasion. Here, I review recent literature on hybridization to identify how ecological responses to climate change will increase the likelihood of hybridization via the dissolution of species barriers maintained by habitat, time, or behavior. Using this literature, I identify several cases where novel hybrid zones have recently formed, likely as a result of changing climate. Future research should focus on identifying areas and taxonomic groups where reproductive species interactions are most likely to be influenced by climate change. Furthermore, a better understanding of the evolutionary consequences of climate-mediated secondary contact is urgently needed. Paradoxically, hybridization is both a major conservation concern and an important source of novel genetic and phenotypic variation. Hybridization may therefore both contribute to increasing rates of extinction and stimulate the creation of novel phenotypes that will speed adaptation to novel climates. Predicting which result will occur following secondary contact will be an important contribution to conservation for many species.

  14. Modified Immersive Situated Service Learning: A Social Justice Approach to Professional Communication Pedagogy

    Science.gov (United States)

    Jones, Natasha N.

    2017-01-01

    Distinctions between traditional service learning and critical service learning with a social justice focus are important when structuring professional writing courses and defining course outcomes. This article presents a hybrid pedagogical approach for designing a critical service-learning course that integrates a social justice curriculum while…

  15. Designing Disruptions for Productive Hybridity: The Case of Walking Scale Geometry

    Science.gov (United States)

    Ma, Jasmine Y.

    2016-01-01

    This article explores an alternative strategy for designing hybrid instructional environments. Rather than bridging home or community funds of knowledge with school learning, I propose designing disruptions to typical school practices to invite students to recruit out-of-school resources meaningful and sensible to them in order to grapple with…

  16. Evaluating hybrid poplar rooting. I. genotype x environment interactions in three contrasting sites

    Science.gov (United States)

    Ronald S., Jr. Zalesny; Don E. Riemenschneider; Richard B. Hall

    2002-01-01

    We need to learn more about environmental conditions that promote or hinder rooting of unrooted dormant hybrid poplar cuttings. Planting cuttings and recording survival after the growing season is not suitable to keep up with industrial demands for improved stock. This method does not provide information about specific genotype x environment interactions. We know very...

  17. Hybrid Placemaking in the Library: Designing Digital Technology to Enhance Users' On-Site Experience

    Science.gov (United States)

    Bilandzic, Mark; Johnson, Daniel

    2013-01-01

    This paper presents research findings and design strategies that illustrate how digital technology can be applied as a tool for "hybrid" placemaking in ways that would not be possible in purely digital or physical spaces. Digital technology has revolutionised the way people learn and gather new information. This trend has challenged the…

  18. 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…

  19. 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…

  20. 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....

  1. A Dynamic Feature-Based Method for Hybrid Blurred/Multiple Object Detection in Manufacturing Processes

    Directory of Open Access Journals (Sweden)

    Tsun-Kuo Lin

    2016-01-01

    Full Text Available Vision-based inspection has been applied for quality control and product sorting in manufacturing processes. Blurred or multiple objects are common causes of poor performance in conventional vision-based inspection systems. Detecting hybrid blurred/multiple objects has long been a challenge in manufacturing. For example, single-feature-based algorithms might fail to exactly extract features when concurrently detecting hybrid blurred/multiple objects. Therefore, to resolve this problem, this study proposes a novel vision-based inspection algorithm that entails selecting a dynamic feature-based method on the basis of a multiclassifier of support vector machines (SVMs for inspecting hybrid blurred/multiple object images. The proposed algorithm dynamically selects suitable inspection schemes for classifying the hybrid images. The inspection schemes include discrete wavelet transform, spherical wavelet transform, moment invariants, and edge-feature-descriptor-based classification methods. The classification methods for single and multiple objects are adaptive region growing- (ARG- based and local adaptive region growing- (LARG- based learning approaches, respectively. The experimental results demonstrate that the proposed algorithm can dynamically select suitable inspection schemes by applying a selection algorithm, which uses SVMs for classifying hybrid blurred/multiple object samples. Moreover, the method applies suitable feature-based schemes on the basis of the classification results for employing the ARG/LARG-based method to inspect the hybrid objects. The method improves conventional methods for inspecting hybrid blurred/multiple objects and achieves high recognition rates for that in manufacturing processes.

  2. 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...

  3. Blended learning

    DEFF Research Database (Denmark)

    Dau, Susanne

    2016-01-01

    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......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......) 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...

  4. Hybrid multiscale modeling and prediction of cancer cell behavior.

    Science.gov (United States)

    Zangooei, Mohammad Hossein; Habibi, Jafar

    2017-01-01

    Understanding cancer development crossing several spatial-temporal scales is of great practical significance to better understand and treat cancers. It is difficult to tackle this challenge with pure biological means. Moreover, hybrid modeling techniques have been proposed that combine the advantages of the continuum and the discrete methods to model multiscale problems. In light of these problems, we have proposed a new hybrid vascular model to facilitate the multiscale modeling and simulation of cancer development with respect to the agent-based, cellular automata and machine learning methods. The purpose of this simulation is to create a dataset that can be used for prediction of cell phenotypes. By using a proposed Q-learning based on SVR-NSGA-II method, the cells have the capability to predict their phenotypes autonomously that is, to act on its own without external direction in response to situations it encounters. Computational simulations of the model were performed in order to analyze its performance. The most striking feature of our results is that each cell can select its phenotype at each time step according to its condition. We provide evidence that the prediction of cell phenotypes is reliable. Our proposed model, which we term a hybrid multiscale modeling of cancer cell behavior, has the potential to combine the best features of both continuum and discrete models. The in silico results indicate that the 3D model can represent key features of cancer growth, angiogenesis, and its related micro-environment and show that the findings are in good agreement with biological tumor behavior. To the best of our knowledge, this paper is the first hybrid vascular multiscale modeling of cancer cell behavior that has the capability to predict cell phenotypes individually by a self-generated dataset.

  5. Hybrid origins of cultivated potatoes.

    Science.gov (United States)

    Rodríguez, Flor; Ghislain, Marc; Clausen, Andrea M; Jansky, Shelley H; Spooner, David M

    2010-10-01

    Solanum section Petota is taxonomically difficult, partly because of interspecific hybridization at both the diploid and polyploid levels. The taxonomy of cultivated potatoes is particularly controversial. Using DNA sequence data of the waxy gene, we here infer relationships among the four species of cultivated potatoes accepted in the latest taxonomic treatment (S. ajanhuiri, S. curtilobum, S. juzepczukii and S. tuberosum, the latter divided into the Andigenum and Chilotanum Cultivar Groups). The data support prior ideas of hybrid origins of S. ajanhuiri from the S. tuberosum Andigenum Group (2x = S. stenotomum) × S. megistacrolobum; S. juzepczukii from the S. tuberosum Andigenum Group (2x = S. stenotomum) × S. acaule; and S. curtilobum from the S. tuberosum Andigenum Group (4x = S. tuberosum subsp. andigenum) × S. juzepczukii. For the tetraploid cultivar-groups of S. tuberosum, hybrid origins are suggested entirely within much more closely related species, except for two of three examined accessions of the S. tuberosum Chilotanum Group that appear to have hybridized with the wild species S. maglia. Hybrid origins of the crop/weed species S. sucrense are more difficult to support and S. vernei is not supported as a wild species progenitor of the S. tuberosum Andigenum Group.

  6. Somatic hybridization in higher plants.

    Science.gov (United States)

    Constabel, F

    1976-11-01

    Somatic hybridization in higher plants has come into focus since methods have been established for protoplast fusion and uptake of foreign DNA and organelles by protoplasts. Polyethylene glycol (PEG) was an effective agent for inducing fusion. Treatment of protoplasts with PEG resulted in 5 to 30% heterospecific fusion products. Protoplasts of different species, genera and even families were compatible when fused. A number of protoplast combinations (soybean + corn, soybean + pea, soybean + tobacco, carrot + barley, etc.) provided fusion products which underwent cell division and callus formation. Fusion products initially were heterokaryocytes. In dividing heterokaryocytes, random distribution of mitotic nuclei was observed to be accompanied by multiple wall formation and to result in chimeral callus. Juxtaposition of mitotic nuclei suggested nuclear fusion and hybrid formation. Fusion of heterospecific interphase nuclei was demonstrated in soybean + pea and carrot + barley heterokaryons. Provided parental protoplasts carry suitable markers, the fusion products can be recognized. For the isolation and cloning of hybrid cells, fusion experiments must be supplemented with a selective system. Complementation of two non-allelic genes that prevent or inhibit growth under special culture conditions appears as the principle on which to base the selection of somatic hybrids. As protoplasts of some species have been induced to regenerate entire plants, the development of hybrid plants from protoplast fusion products is feasible and has already been demonstrated for tobacco.

  7. Symbolic Algorithmic Analysis of Rectangular Hybrid Systems

    Institute of Scientific and Technical Information of China (English)

    Hai-Bin Zhang; Zhen-Hua Duan

    2009-01-01

    This paper investigates symbolic algorithmic analysis of rectangular hybrid systems. To deal with the symbolic reachability problem, a restricted constraint system called hybrid zone is formalized for the representation and manipulation of rectangular automata state-spaces. Hybrid zones are proved to be closed over symbolic reachability operations of rectangular hybrid systems. They are also applied to model-checking procedures for verifying some important classes of timed computation tree logic formulas. To represent hybrid zones, a data structure called difference constraint matrix is defined.These enable us to deal with the symbolic algorithmic analysis of rectangular hybrid systems in an efficient way.

  8. DNA-based hybrid catalysis.

    Science.gov (United States)

    Rioz-Martínez, Ana; Roelfes, Gerard

    2015-04-01

    In the past decade, DNA-based hybrid catalysis has merged as a promising novel approach to homogeneous (asymmetric) catalysis. A DNA hybrid catalysts comprises a transition metal complex that is covalently or supramolecularly bound to DNA. The chiral microenvironment and the second coordination sphere interactions provided by the DNA are key to achieve high enantioselectivities and, often, additional rate accelerations in catalysis. Nowadays, current efforts are focused on improved designs, understanding the origin of the enantioselectivity and DNA-induced rate accelerations, expanding the catalytic scope of the concept and further increasing the practicality of the method for applications in synthesis. Herein, the recent developments will be reviewed and the perspectives for the emerging field of DNA-based hybrid catalysis will be discussed.

  9. Model Reduction of Hybrid Systems

    DEFF Research Database (Denmark)

    Shaker, Hamid Reza

    systems are derived in this thesis. The results are used for output feedback control of switched nonlinear systems. Model reduction of piecewise affine systems is also studied in this thesis. The proposed method is based on the reduction of linear subsystems inside the polytopes. The methods which......High-Technological solutions of today are characterized by complex dynamical models. A lot of these models have inherent hybrid/switching structure. Hybrid/switched systems are powerful models for distributed embedded systems design where discrete controls are applied to continuous processes...... of hybrid systems, designing controllers and implementations is very high so that the use of these models is limited in applications where the size of the state space is large. To cope with complexity, model reduction is a powerful technique. This thesis presents methods for model reduction and stability...

  10. Additive Manufacturing of Hybrid Circuits

    Science.gov (United States)

    Sarobol, Pylin; Cook, Adam; Clem, Paul G.; Keicher, David; Hirschfeld, Deidre; Hall, Aaron C.; Bell, Nelson S.

    2016-07-01

    There is a rising interest in developing functional electronics using additively manufactured components. Considerations in materials selection and pathways to forming hybrid circuits and devices must demonstrate useful electronic function; must enable integration; and must complement the complex shape, low cost, high volume, and high functionality of structural but generally electronically passive additively manufactured components. This article reviews several emerging technologies being used in industry and research/development to provide integration advantages of fabricating multilayer hybrid circuits or devices. First, we review a maskless, noncontact, direct write (DW) technology that excels in the deposition of metallic colloid inks for electrical interconnects. Second, we review a complementary technology, aerosol deposition (AD), which excels in the deposition of metallic and ceramic powder as consolidated, thick conformal coatings and is additionally patternable through masking. Finally, we show examples of hybrid circuits/devices integrated beyond 2-D planes, using combinations of DW or AD processes and conventional, established processes.

  11. Intercalated hybrid graphite fiber composite

    Science.gov (United States)

    Gaier, James R. (Inventor)

    1993-01-01

    The invention is directed to a highly conductive lightweight hybrid material and methods of producing the same. The hybrid composite is obtained by weaving strands of a high strength carbon or graphite fiber into a fabric-like structure, depositing a layer of carbon onto the structure, heat treating the structure to graphitize the carbon layer, and intercalating the graphitic carbon layer structure. A laminate composite material useful for protection against lightning strikes comprises at least one layer of the hybrid material over at least one layer of high strength carbon or graphite fibers. The composite material of the present invention is compatible with matrix compounds, has a coefficient of thermal expansion which is the same as underlying fiber layers, and is resistant to galvanic corrosion in addition to being highly conductive. These materials are useful in the aerospace industry, in particular as lightning strike protection for airplanes.

  12. Optimizing Hybrid Spreading in Metapopulations

    CERN Document Server

    Zhang, Changwang; 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 \\textit{local spreading}, where infected nodes can only infect a limited set of direct target nodes and \\textit{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. In a metapopulation, made up of many weakly connected subpopulations, we show that one can calculate an optimal tradeoff between local and global spreading which will maximise the extent of the epidemic. As an example we analyse the 2008 outbreak of the Internet worm Conficker, which uses hybrid spreading to propagate through the internet. Our results suggests that the worm would have been eve...

  13. New Supercapacitors of Hybrid Configurations

    Directory of Open Access Journals (Sweden)

    Wako Naoi

    2013-01-01

    Full Text Available In recent years, the improvement of the energydensity of nano-composite battery materials hasbeen object of great study. Hybridizing battery andcapacitor materials overcome the energy densitylimitation of existing generation-I capacitors withoutmuch sacrificing the cycling performances. Normalbattery-capacitor hybrids employ high-energy &sluggish redox electrode and low-energy & fastdouble-layer electrodes, possibly producing a largerworking voltage and higher over-all capacitance. Inorder to smoothly operate such asymmetric systems,however, the rates of the two different electrodes mustbe highly balanced. Especially, the redox rates of thebattery electrodes must be substantially increasedto the levels of double-layer process. In this report,we attempt to identify the essential issues for therealizable hybrids and suggest ways to overcomethe rate enhancement by exemplifying ultrafastperformance of the Li4Ti5O12 nanocrystal preparedvia a unique in-situ material processing technologyunder ultra-centrifuging.

  14. CMS, LMS and LCMS For eLearning

    Directory of Open Access Journals (Sweden)

    Suman Ninoriya

    2011-03-01

    Full Text Available Now a day's most of the educational centre (universities, institutes, colleges and schools are using some eLearning tools as an integral part of their learning systems; to enhance their traditional learning systems or to use an alternative approach for virtual learning environment. These tools may base on content management or learning content management. Recently a composition of Learning Management System (LMS and Content Management System (CMS is used in eLearning. This paper helps you to understand the basic functionality of LMS, CMS and LCMS and how these are helpful in eLearning. In this we have proposed the integration of LMS and CMS. This paper gives the architecture of this hybrid model known as known as LCMS (Learning Content Management system.

  15. The Use of E-Learning in Social Work Education.

    Science.gov (United States)

    Phelan, James E

    2015-07-01

    E-learning is an evolutionary pedagogy in social work. E-learning technologies transform learning so that it can be synchronous or asynchronous. The author provides a systematic discussion of e-learning and its role in social work education. E-learning appears advantageous as a hybrid or blended venue when used in academia and suitable in various formats for continuing education. Theoretical foundations that support positive learning outcomes should guide delivery. Distance delivery, regardless of the media or technology used, is not by itself a contributing variable in students' achievement. The priority of teaching and learning should be on effectiveness of the learning, regardless of the mode of delivery. Current descriptive research on e-learning can be improved by increasing the rigor of methodology and theoretical considerations. This information is necessary as the profession navigates the best ways to meet the changing needs of social work students and social workers in the field.

  16. Cooperative Learning

    Institute of Scientific and Technical Information of China (English)

    桑莹莹

    2015-01-01

    This paper is about the cooperative learning as a teaching method in a second language learning class. It mainly talks about the background, foundation, features, definitions, components, goals, advantages and disadvantages of cooperative learning. And as the encounter of the disadvantages in cooperative learning, this paper also proposes some strategies.

  17. 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

  18. 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

  19. Interspecific Hybridization within Ornamental Plants

    DEFF Research Database (Denmark)

    Kuligowska, Katarzyna

    The economic importance of the ornamental plant industry requires constant development of novel and high quality varieties. Traits attractive for production of new ornamental plants may not be available within the commercial cultivars, but broad genetic variation is present within the plant genera...... 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...

  20. 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...... assuming that certain social forms carry a critical, emancipating or suppressing potential per se....... 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...

  1. Towards an expansive hybrid psychology

    DEFF Research Database (Denmark)

    Brinkmann, Svend

    2011-01-01

    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...... 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...

  2. Hybrid Simulation of Composite Structures

    DEFF Research Database (Denmark)

    Høgh, Jacob Herold

    Hybrid simulation is a substructural method combining a numerical simulation with a physical experiment. A structure is thereby simulated under the assumption that a substructure’s response is well known and easily modelled while a given substructure is studied more accurately in a physical...... of freedom. In this dissertation the main focus is to develop hybrid simulation for composite structures e.g. wind turbine blades where the boundary between the numerical model and the physical experiment is continues i.e. in principal infinite amount of degrees of freedom. This highly complicates...

  3. Charge Qubit-Atom Hybrid

    CERN Document Server

    Yu, Deshui; Hufnagel, C; Kwek, L C; Amico, Luigi; Dumke, R

    2016-01-01

    We investigate a novel hybrid system of a superconducting charge qubit interacting directly with a single neutral atom via electric dipole coupling. Interfacing of the macroscopic superconducting circuit with the microscopic atomic system is accomplished by varying the gate capacitance of the charge qubit. To achieve strong interaction, we employ two Rydberg states with an electric-dipole-allowed transition, which alters the polarizability of the dielectric medium of the gate capacitor. Sweeping the gate voltage with different rates leads to a precise control of hybrid quantum states. Furthermore, we show a possible implementation of a universal two-qubit gate.

  4. Position list word aligned hybrid

    DEFF Research Database (Denmark)

    Deliege, Francois; Pedersen, Torben Bach

    2010-01-01

    Compressed bitmap indexes are increasingly used for efficiently querying very large and complex databases. The Word Aligned Hybrid (WAH) bitmap compression scheme is commonly recognized as the most efficient compression scheme in terms of CPU efficiency. However, WAH compressed bitmaps use a lot...... of storage space. This paper presents the Position List Word Aligned Hybrid (PLWAH) compression scheme that improves significantly over WAH compression by better utilizing the available bits and new CPU instructions. For typical bit distributions, PLWAH compressed bitmaps are often half the size of WAH...

  5. Interspecific Hybridization within Ornamental Plants

    DEFF Research Database (Denmark)

    Kuligowska, Katarzyna

    The economic importance of the ornamental plant industry requires constant development of novel and high quality varieties. Traits attractive for production of new ornamental plants may not be available within the commercial cultivars, but broad genetic variation is present within the plant genera...... 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...

  6. Hybrid winding concept for toroids

    DEFF Research Database (Denmark)

    Schneider, Henrik; Andersen, Thomas; Knott, Arnold;

    2013-01-01

    This paper proposes a hybrid winding concept for toroids using the traces in a printed circuit board to make connection to bended copper foil cutouts. In a final product a number of strips with a certain thickness would be held by a former and the whole assembly could be placed by pick...... 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...

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

    OpenAIRE

    Jia-Shiun Chen

    2015-01-01

    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) ar...

  8. Dance in mental health nursing: a hybrid concept analysis.

    Science.gov (United States)

    Ravelin, Teija; Kylmä, Jari; Korhonen, Teija

    2006-04-01

    The aim of this concept analysis is to describe the defining attributes and consequences of the concept of dance and to define it in a mental health nursing context using hybrid concept analysis. Dance is a human resource learned from culture. Dance implies body movements, steps, expression, and interaction. The outcomes of dance are mostly functional, including a client's physical and emotional health, well-being, ability to cooperate with other people in activities of daily life, and meeting role expectations within family and community. Based on the findings of this concept analysis, dance can be used as a nursing intervention.

  9. 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.

  10. 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

  11. Medical Dataset Classification: A Machine Learning Paradigm Integrating Particle Swarm Optimization with Extreme Learning Machine Classifier

    OpenAIRE

    C. V. Subbulakshmi; Deepa, S. N.

    2015-01-01

    Medical data classification is a prime data mining problem being discussed about for a decade that has attracted several researchers around the world. Most classifiers are designed so as to learn from the data itself using a training process, because complete expert knowledge to determine classifier parameters is impracticable. This paper proposes a hybrid methodology based on machine learning paradigm. This paradigm integrates the successful exploration mechanism called self-regulated learni...

  12. Refining fuzzy logic controllers with machine learning

    Science.gov (United States)

    Berenji, Hamid R.

    1994-01-01

    In this paper, we describe the GARIC (Generalized Approximate Reasoning-Based Intelligent Control) architecture, which learns from its past performance and modifies the labels in the fuzzy rules to improve performance. It uses fuzzy reinforcement learning which is a hybrid method of fuzzy logic and reinforcement learning. This technology can simplify and automate the application of fuzzy logic control to a variety of systems. GARIC has been applied in simulation studies of the Space Shuttle rendezvous and docking experiments. It has the potential of being applied in other aerospace systems as well as in consumer products such as appliances, cameras, and cars.

  13. Learning How to Learn.

    Science.gov (United States)

    Novak, Joseph D.; Gowin, D. Bob

    This eight-chapter book clearly presents a theory of how children learn and, therefore, how teachers and others can help children think about science as well as other topics. Its ideas and techniques may be adopted for preschoolers when objects are conceptually ordered, or for theoretical physicists when findings are conceptually organized. In…

  14. Hybrid Power Management System and Method

    Science.gov (United States)

    Eichenberg, Dennis J. (Inventor)

    2008-01-01

    A system and method for hybrid power management. The system includes photovoltaic cells, ultracapacitors, and pulse generators. In one embodiment, the hybrid power management system is used to provide power for a highway safety flasher.

  15. 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.

  16. How to distinguish Hybrids from Radial Quarkonia

    CERN Document Server

    Close, Francis Edwin; Close, Frank E; Page, Philip R.

    1997-01-01

    We present arguments that reinforce the hybrid interpretation of pi(1800) and we establish that the rho(1450) and the omega(1420) can be interpreted as radial-hybrid mixtures. Some questions for future experiments are raised.

  17. Modeling and analysis using hybrid Petri nets

    CERN Document Server

    Ghomri, Latéfa

    2007-01-01

    This paper is devoted to the use of hybrid Petri nets (PNs) for modeling and control of hybrid dynamic systems (HDS). Modeling, analysis and control of HDS attract ever more of researchers' attention and several works have been devoted to these topics. We consider in this paper the extensions of the PN formalism (initially conceived for modeling and analysis of discrete event systems) in the direction of hybrid modeling. We present, first, the continuous PN models. These models are obtained from discrete PNs by the fluidification of the markings. They constitute the first steps in the extension of PNs toward hybrid modeling. Then, we present two hybrid PN models, which differ in the class of HDS they can deal with. The first one is used for deterministic HDS modeling, whereas the second one can deal with HDS with nondeterministic behavior. Keywords: Hybrid dynamic systems; D-elementary hybrid Petri nets; Hybrid automata; Controller synthesis

  18. Extended Mixture of MLP Experts by Hybrid of Conjugate Gradient Method and Modified Cuckoo Search

    CERN Document Server

    Salimi, Hamid; Soltanshahi, Mohammad Ali; Hatami, Javad

    2012-01-01

    This paper investigates a new method for improving the learning algorithm of Mixture of Experts (ME) model using a hybrid of Modified Cuckoo Search (MCS) and Conjugate Gradient (CG) as a second order optimization technique. The CG technique is combined with Back-Propagation (BP) algorithm to yield a much more efficient learning algorithm for ME structure. In addition, the experts and gating networks in enhanced model are replaced by CG based Multi-Layer Perceptrons (MLPs) to provide faster and more accurate learning. The CG is considerably depends on initial weights of connections of Artificial Neural Network (ANN), so, a metaheuristic algorithm, the so-called Modified Cuckoo Search is applied in order to select the optimal weights. The performance of proposed method is compared with Gradient Decent Based ME (GDME) and Conjugate Gradient Based ME (CGME) in classification and regression problems. The experimental results show that hybrid MSC and CG based ME (MCS-CGME) has faster convergence and better performa...

  19. Distant hybridization leads to different ploidy fishes

    Institute of Scientific and Technical Information of China (English)

    2010-01-01

    Distant hybridization makes it possible to transfer the genome of one species to another, which results in changes in phenotypes and genotypes of the progenies. This study shows that distant hybridization or the combination of this method with gynogenesis or androgenesis lead to different ploidy fishes with genetic variation, including fertile tetraploid hybrids, sterile triploid hybrids, fertile diploid hybrids, fertile diploid gynogenetic fish, and their derived progenies. The formations of the different ploidy fishes depend on the genetic relationship between the parents. In this study, several types of distant hybridization, including red crucian carp (Carassius auratus red var.) (2n=100, abbreviated as RCC) (♀)×common carp (Cyprinus carpio L.) (2n=100, abbreviated as CC) (♂), and RCC (2n=100) (♀)×blunt snout bream (Megalobrama amblycephala) (2n=48, abbreviated as BSB) (♂) are described. In the distant hybridization of RCC (♀)×CC (♂), bisexual fertile F3–F18 allotetraploid hybrids (4n=200, abbreviated as 4nAT) were formed. The diploid hybrid eggs and diploid sperm generated by the females and males of 4nAT developed into diploid gynogenetic hybrids and diploid androgenetic hybrids, respectively, by gynogenesis and androgenesis, without treatment for doubling the chromosome. Improved tetraploid hybrids and improved diploid fishes with genetic variation were derived from the gynogenetic hybrid line. The improved diploid fishes included the high-body RCC and high-body goldfish. The formation of the tetraploid hybrids was related to the occurrence of unreduced gametes generated from the diploid hybrids, which involved in premeiotic endoreduplication, endomitosis, or fusion of germ cells. The sterile triploid hybrids (3n=150) were produced on a large scale by crossing the males of tetraploid hybrids with females of diploid fish (2n=100). In another distant hybridization of RCC (♀)×BSB (♂), different ploidy fishes were obtained, including

  20. Distant hybridization leads to different ploidy fishes.

    Science.gov (United States)

    Liu, ShaoJun

    2010-04-01

    Distant hybridization makes it possible to transfer the genome of one species to another, which results in changes in phenotypes and genotypes of the progenies. This study shows that distant hybridization or the combination of this method with gynogenesis or androgenesis lead to different ploidy fishes with genetic variation, including fertile tetraploid hybrids, sterile triploid hybrids, fertile diploid hybrids, fertile diploid gynogenetic fish, and their derived progenies. The formations of the different ploidy fishes depend on the genetic relationship between the parents. In this study, several types of distant hybridization, including red crucian carp (Carassius auratus red var.) (2n=100, abbreviated as RCC) (female) x common carp (Cyprinus carpio L.) (2n=100, abbreviated as CC) (male), and RCC (2n=100) (female) x blunt snout bream (Megalobrama amblycephala) (2n=48, abbreviated as BSB) (male) are described. In the distant hybridization of RCC (female) x CC (male), bisexual fertile F(3)-F(18) allotetraploid hybrids (4n=200, abbreviated as 4nAT) were formed. The diploid hybrid eggs and diploid sperm generated by the females and males of 4nAT developed into diploid gynogenetic hybrids and diploid androgenetic hybrids, respectively, by gynogenesis and androgenesis, without treatment for doubling the chromosome. Improved tetraploid hybrids and improved diploid fishes with genetic variation were derived from the gynogenetic hybrid line. The improved diploid fishes included the high-body RCC and high-body goldfish. The formation of the tetraploid hybrids was related to the occurrence of unreduced gametes generated from the diploid hybrids, which involved in premeiotic endoreduplication, endomitosis, or fusion of germ cells. The sterile triploid hybrids (3n=150) were produced on a large scale by crossing the males of tetraploid hybrids with females of diploid fish (2n=100). In another distant hybridization of RCC (female) x BSB (male), different ploidy fishes were