Arama Sonuçları - (experiential OR experimental) learning.

Experiential learning : experience as the source of learning and development / Yazar: Kolb, David A.

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Work-integrated learning in the 21st century : global perspectives on the future /

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Hafıza yanılmalarının doğuşu ve ‘iki ayrı hafıza kodu’ teorisi/ Yazar: Özakpınar, Yılmaz

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Dewey and education in the 21st century : fighting back /

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Innovation and entrepreneurship in education /

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Experimental organic chemistry : a miniscale and microscale approach / Yazar: Gilbert, John C.

Advances in Cross-Cultural Decision Making Proceedings of the AHFE 2016 International Conference on Cross-Cultural Decision Making (CCDM), July 27-31,2016, Walt Disney World®, Flor...

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Experimental Vibration Analysis for Civil Structures Testing, Sensing, Monitoring, and Control /

İçindekiler: “…Experimental evaluation of the effect of geometric nonlinearities on structural resonances -- Vortex-induced vibration of stay cables, verification on the footbridge -- The selection of a dynamic model of a RC chimney based on in situ research -- A new approach to damage detection in bridges using machine learning -- Vibration based damage identification method for cantilever beam using artificial neural network -- Vertical vibration mitigation of a bridge cable using a non smooth absorber under gravity -- Advanced statistical techniques applied to raw data for structural damage detection -- A new system identification method operated in the pole domain -- Identification of extremely close modes with an improved stochastic subspace algorithm.…”
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The future of learning and teaching in next generation learning spaces

İçindekiler: “…Crisp -- Spaces for engaging, experiential, collaborative learning in higher education / Roger Hadgraft, Jo Dane -- What does it take to learn in next generation learning spaces? …”
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Machine Learning Paradigms Artificial Immune Systems and their Applications in Software Personalization / Yazar: Sotiropoulos, Dionisios N., Tsihrintzis, George A.

İçindekiler: “…Introduction -- Machine Learning -- The Class Imbalance Problem -- Addressing the Class Imbalance Problem -- Machine Learning Paradigms -- Immune System Fundamentals -- Artificial Immune Systems -- Experimental Evaluation of Artificial Immune System-based Learning Algorithms -- Conclusions and Future Work.…”
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Evidence-based practices

Konular: “…Education Special Education Learning Disabilities. bisacsh…”
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Machine Learning for Evolution Strategies Yazar: Kramer, Oliver

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Deep Learning-Based Face Analytics. Yazar: Ratha, Nalini K.

İçindekiler: “…7.7.2 IJB-A -- 7.7.3 IJB-B -- 7.7.4 IJB-C -- 7.8 Open Issues -- 7.9 Conclusion -- References -- 8 Evolution of Newborn Face Recognition -- 8.1 Introduction -- 8.1.1 Biometric Modalities for Newborns -- 8.1.2 Characteristics and Challenges of Newborn Face Recognition -- 8.2 Datasets for Newborn Face Recognition -- 8.2.1 Newborns Face Database -- 8.2.2 Newborns, Infants, and Toddler Longitudinal Face Database -- 8.2.3 Children Multimodal Biometric Database (CMDB) -- 8.3 Existing Techniques for Newborn Face Recognition -- 8.3.1 Handcrafted Feature Extraction Methods -- 8.3.2 Autoencoder Learning-Based Method -- 8.3.3 Class-Based Penalty in CNN Filter Learning -- 8.3.4 Learning Structure and Strength of CNN Filters -- 8.4 Results and Analysis of Existing Newborn Face Recognition Techniques -- 8.5 Conclusion -- References -- 9 Deep Feature Fusion for Face Analytics -- 9.1 Introduction -- 9.2 Feature Aggregation for Face Recognition -- 9.2.1 Metadata-Based Feature Aggregator Network (M-FAN) -- 9.2.2 Architecture -- 9.2.3 Gradient Backpropagation -- 9.2.4 Batch Training -- 9.2.5 Experiment Setup -- 9.2.6 Results on IJB-A -- 9.2.7 Results on Janus CS4 -- 9.3 Feature Enhancement for Facial Action Unit Recognition -- 9.3.1 Multi-modal Conditional Feature Enhancement (MCFE) -- 9.3.2 Feature Extraction -- 9.3.3 Deep Feature Enhancement -- 9.3.4 Training MCFE for AU Recognition -- 9.3.5 Datasets for Experimental Analysis -- 9.3.6 Experiment Settings -- 9.3.7 Results -- 9.4 Conclusion -- References -- 10 Deep Learning for Video Face Recognition -- 10.1 Introduction -- 10.2 Traditional Methods -- 10.3 Existing Deep Learning-based Approaches -- 10.3.1 Pairwise Distance-Based Methods -- 10.3.2 Pooling-Based Methods -- 10.4 Neural Aggregation Network -- 10.4.1 Feature Embedding Module -- 10.4.2 Aggregation Module -- 10.4.3 Network Training -- 10.5 Experiments.…”
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Theoretical models of learning and literacy development

İçindekiler: “…Attraction theory / Evan Ortlieb -- Spacing theory / Evan Ortlieb -- Backwards sequencing theory / Evan Ortlieb -- Read fast, read slow theory / Evan Ortlieb -- Experiential learning theory / Evan Ortlieb -- Extending theory / Evan Ortlieb -- Language creation / Evan Ortlieb -- Capital investment theory / Evan Ortlieb -- Learn over theory / Evan Ortlieb -- E-reading theory / Evan Ortlieb.…”
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Active learning strategies in higher education /

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Skin Biophysics From Experimental Characterisation to Advanced Modelling /

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Machine Learning Techniques for Gait Biometric Recognition Using the Ground Reaction Force / Yazar: Mason, James Eric, Traoré, Issa, Woungang, Isaac

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Automatic Tuning of Compilers Using Machine Learning Yazar: Ashouri, Amir H., Palermo, Gianluca, Cavazos, John, Silvano, Cristina

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Machine Learning Control - Taming Nonlinear Dynamics and Turbulence Yazar: Duriez, Thomas, Brunton, Steven L., Noack, Bernd R.

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Increasing student engagement and retention using online learning activities wikis, blogs and webquests /

İçindekiler: “…Watts -- Blogging clinical placement : harnessing technologies to increase off-campus engagement with healthcare learners / Stephanie Mckendry, Vic Boyd -- Using video and wiki technology to increase student engagement with learning in large international cohorts in UK higher education / Elisabeth Dunne, Jenny Wren, Alex Janes -- Using the wiki as an experiential learning tool to engage students in undergraduate and graduate university courses / Michael J.D. …”
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