327 research outputs found

    Effect of Projet-Based Learning on the Creative Personality, Teamwork Competence and Self-Regulated Efficacy of Undergraduate Nursing Students

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    This paper deals with learner-centered teaching methods according to the demand for improvement in university education. Project-based learning methods improve students’ self- learning and creative problem-solving ability. In clinical practice, creative problem-solving ability and teamwork competence are important among nurses’ competencies. This purpose of study was to apply a project-based learning method to curriculum to see changes in creative personality, teamwork competence, and self-regulated efficacy. This study conducted from September to December 2019 with 34 participants. To achieve this purpose, 34 students taking a health program development and evaluation course were tested for their creative personality, teamwork competence, and self-regulation efficacy. The analysis results showed that it is effective in creative personality, teamwork competency, and self-regulation efficacy (p<.001). It was found that teamwork competence and self-regulation efficacy had a positive correlation (p=.002). Therefore, the effect of project-based learning method used in nursing students was verified and indicates significance in increasing competency of undergraduate nursing students

    “Whose Utopia?” Kimsooja & Bottari Utopia

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    This thesis will explore the progressive evolution of utopia and utopianism in order to answer the question: “Whose utopia? in the context of the COVID-19 pandemic and its disproportionate impact on people who were already marginalized, disadvantaged, and discriminated against. I will first review the writings of Sir Thomas More, Ernst Bloch, Michel Foucault, Edward Said, Owkui Enwezor, and Jose Estaban Muñoz tracing the progressive evolution of utopian ideals. I will then introduce and survey the artist, Kimsooja’s oeuvre in relation to salient features from my review of utopia\u27s progression, and gradually revealing her aesthetics of making as revealing utopian hope and creating what I have named “Bottari utopia” based on the metaphoric extension of her artistic vocabulary. As chronicled in her numerous performances and videos, her concern is for persons not included, outcast, enduring violence... Bottari utopia bundles all: persons, places, things and time, in time, and is particularly inspiring, uplifting, and instructional today, as we (the world) find ourselves navigating isolation, and displacement, and face the fragility of life and uncertain future caused by the COVID-19 pandemic. I will then turn my attention to artist-activists and their import in transforming society for a better future, whether digital, virtual, or real

    Example-based learning for single-image super-resolution and JPEG artifact removal

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    This paper proposes a framework for single-image super-resolution and JPEG artifact removal. The underlying idea is to learn a map from input low-quality images (suitably preprocessed low-resolution or JPEG encoded images) to target high-quality images based on example pairs of input and output images. To retain the complexity of the resulting learning problem at a moderate level, a patch-based approach is taken such that kernel ridge regression (KRR) scans the input image with a small window (patch) and produces a patchvalued output for each output pixel location. These constitute a set of candidate images each of which reflects different local information. An image output is then obtained as a convex combination of candidates for each pixel based on estimated confidences of candidates. To reduce the time complexity of training and testing for KRR, a sparse solution is found by combining the ideas of kernel matching pursuit and gradient descent. As a regularized solution, KRR leads to a better generalization than simply storing the examples as it has been done in existing example-based super-resolution algorithms and results in much less noisy images. However, this may introduce blurring and ringing artifacts around major edges as sharp changes are penalized severely. A prior model of a generic image class which takes into account the discontinuity property of images is adopted to resolve this problem. Comparison with existing super-resolution and JPEG artifact removal methods shows the effectiveness of the proposed method. Furthermore, the proposed method is generic in that it has the potential to be applied to many other image enhancement applications

    Adjoint centroid-moment tensor inversions

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    We determine centroid-moment tensor (CMT) solutions by minimizing waveform differences between observed and simulated seismograms based on an adjoint method. Synthetic seismograms and FrĂ©chet derivatives are calculated based on a spectral-element method. The non-linear adjoint CMT inversion algorithm requires three simulations for each iteration: one ‘forward’ simulation to obtain synthetics for the current source parameters, one ‘adjoint’ simulation which involves injecting time-reversed differences between observed and simulated seismograms as simultaneous virtual sources at each of the receivers, and an extra forward simulation to compute the step length in the conjugate-gradient direction. Whereas the vertical component of the adjoint wavefield reflects the radiation pattern near the centroid location, the components of the adjoint strain tensor capture the elements of the moment tensor. We use the method to determine adjoint CMT solutions for two representative southern California earthquakes using recent 3-D crustal model CVM-6.2. The adjoint CMT solutions are in good agreement with classical Hessian-based CMT solutions involving 3-D Green's functions. In general, adjoint CMT inversions require fewer numerical simulations than traditional Hessian-based inversions. This faster convergence holds promise for multiple moment-tensor and kinematic rupture inversions in 3-D earth models

    Evidence of a collision between the YucatĂĄn Block and Mexico in the Miocene

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    We present the evidence for an anomalous southwest-dipping slab in southern Mexico. The main evidence comes from a clear receiver function image along a seismic line across the Isthmus of Tehuantepec and is also supported by a previous global tomographic model. The slab dips at 35°, is approximately 250 km in length and appears to truncate the Cocos slab at about 120 km depth. We hypothesize that the slab was created by subduction of oceanic lithosphere prior to the collision of the Yucatån Block with Mexico at approximately 12 Ma. This scenario would explain the Chiapas Fold and Thrust Belt as the product of this collision, and its age constrains the date of the event to be in the Miocene
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