Self-Directed Learning in the Workplace: Implications for the Legislation of Trade Union Education in South Korea

The purpose of this study is to theorize self-directed learning (SDL) in the workplace from the perspectives of human resource development (HRD), adult education (AdEd), and lifelong learning in order to suggest the implications for the legislation of trade union education (TUE) in South Korea. Since legislation at the national level can promote workers‘ participation in TUE in the context of SDL for industrial democracy through humanization of education, the South Korean government should provide trade unions with appropriate legislative, financial, and administrative support. Keywords: self-directed learning, trade union education, adult education

Corporate Universities and Adult Education: Implications for Theory and Practice

The purpose of this paper is to explore characteristics of corporate universities (CUs) from the adult education (AdEd) perspective in order to identify implications for AdEd theory and practice. Through an integrative literature review of CUs, the differences among CUs, human resource development centers, and traditional universities are investigated. Considering the AdEd characteristics of CUs, such as individuals’ learning and qualifications/certifications of higher education, the partnership/collaboration model of CU is suggested in terms of workplace learning, which is the overlapping field of HRD and AdEd. Ultimately, to promote participatory AdEd in the workplace, nations should play crucial roles in providing administrative and financial support to CUs

Nonchaotic Nonlinear Motion Visualized in Complex Nanostructures by Stereographic 4D Electron Microscopy

Direct electron imaging with sufficient time resolution is a powerful tool for visualizing the three-dimensional (3D) mechanical motion and resolving the four-dimensional (4D) trajectories of many different components of a nanomachine, e.g., a NEMS device. Here, we report a nanoscale nonchaotic motion of a nano- and microstructured NiTi shape memory alloy in 4D electron microscopy. A huge amplitude oscillatory mechanical motion following laser heating is observed repetitively, likened to a 3D motion of a conductor’s baton. By time-resolved 4D stereographic reconstruction of the motion, prominent vibrational frequencies (3.0, 3.8, 6.8, and 14.5 MHz) are fully characterized, showing evidence of nonlinear behavior. Moreover, it is found that a stress (fluence)−strain (displacement) profile shows nonlinear elasticity. The observed resonances of the nanostructure are reminiscent of classical molecular quasi-periodic behavior, but here both the amplitude and frequency of the motion are visualized using ultrafast electron microscopy

Sum-rates of asynchronous GFDMA and SC-FDMA for 5G uplink

The fifth generation (5G) of mobile communication envisions ultralow latency less than 1 ms for radio interface. To this end, frameless asynchronous multiple access may be needed to allow users to transmit instantly without waiting for the next frame start. In this paper, generalized frequency division multiple-access (GFDMA), one of the promising multiple-access candidates for 5G mobile, is compared with the conventional single-carrier FDMA (SC-FDMA) in terms of the uplink sum rate when both techniques are adapted for the asynchronous scenario. In particular, a waveform windowing technique is applied to both schemes to mitigate the inter-user interference due to non-zero out-of-band emission.ope

Weakly- and Self-Supervised Learning for Content-Aware Deep Image Retargeting

This paper proposes a weakly- and self-supervised deep convolutional neural network (WSSDCNN) for content-aware image retargeting. Our network takes a source image and a target aspect ratio, and then directly outputs a retargeted image. Retargeting is performed through a shift map, which is a pixel-wise mapping from the source to the target grid. Our method implicitly learns an attention map, which leads to a content-aware shift map for image retargeting. As a result, discriminative parts in an image are preserved, while background regions are adjusted seamlessly. In the training phase, pairs of an image and its image-level annotation are used to compute content and structure losses. We demonstrate the effectiveness of our proposed method for a retargeting application with insightful analyses.Comment: 10 pages, 11 figures. To appear in ICCV 2017, Spotlight Presentatio

Unsupervised Pre-Training For Data-Efficient Text-to-Speech On Low Resource Languages

Neural text-to-speech (TTS) models can synthesize natural human speech when trained on large amounts of transcribed speech. However, collecting such large-scale transcribed data is expensive. This paper proposes an unsupervised pre-training method for a sequence-to-sequence TTS model by leveraging large untranscribed speech data. With our pre-training, we can remarkably reduce the amount of paired transcribed data required to train the model for the target downstream TTS task. The main idea is to pre-train the model to reconstruct de-warped mel-spectrograms from warped ones, which may allow the model to learn proper temporal assignment relation between input and output sequences. In addition, we propose a data augmentation method that further improves the data efficiency in fine-tuning. We empirically demonstrate the effectiveness of our proposed method in low-resource language scenarios, achieving outstanding performance compared to competing methods. The code and audio samples are available at: https://github.com/cnaigithub/SpeechDewarpingComment: ICASSP 202

Baryonic Matter in the Hidden Local Symmetry Induced from Holographic QCD Models

Baryonic matter is studied in the Skyrme model by taking into account the roles of $\pi,$ $\rho$, and $\omega$ mesons through the hidden local symmetry up to $\mathcal{O}(p^4)$ terms including the homogeneous Wess-Zumino (hWZ) terms. Using the master formulas for the low energy constants derived from holographic QCD models the skyrmion matter properties can be quantitatively calculated with the input values of the pion decay constant $f_\pi$ and the vector meson mass $m_\rho^{}$. We find that the hWZ terms are responsible for the repulsive interactions of the $\omega$ meson. In addition, the self-consistently included $\mathcal{O}(p^4)$ terms with the hWZ terms is found to increase the half skyrmion phase transition point above the normal nucleon density.Comment: Contribution to SCGT12 "KMI-GCOE Workshop on Strong Coupling Gauge Theories in the LHC Perspective", 4-7 Dec. 2012, Nagoya Universit