Rethinking South Korea's educational development in terms of students' agency in career choice making

Many scholars and policymakers interested in national development argue that education has been the driving force behind the rapid and unprecedented economic growth of South Korea. In terms of quantitative and qualitative development which is presented in entrance rates and PISA and TIMSS rankings, South Korean education has had many tangible achievements. South Korea’s education which has been on the path of growth and development for over 70 years, is now headed toward entering university. The education system and excessive education fever focus on university entrance. Today, at the end of high school education (nearly 100 per cent of teenagers complete high school courses), 7 out of 10 students choose to go to university as their following career path. This thesis aims to understand that choice and its implications by using the Capability Approach (CA) supplemented with a Self-determination Theory (SDT) to investigate students’ motivation and agency. The rationale for using the CA lies in its ability to offer an alternative analysis in which to scrutinise in a detailed manner what agency means in the choice issue. It focuses on what each individual’s valuable doings and beings in making meaningful choices from a range of options in their life. SDT, integrated alongside the CA, offers a measurement of an agency that reveals whether students’ exercised agency is indeed autonomous. The CA and SDT that this thesis develops will be contextualised with qualitative data collected from 81 1styear university students in South Korea in 2019. The analyses will demonstrate how students are motivated to choose and how they determine themselves as autonomous agents in choice-making. By understanding students’ choices in this way, holistic explanations of students’ perceptions of choice can be made, potentially suggesting future practices and policies regarding students’ agency issues in South Korea’s education development

KnobSlider:design of a shape-changing UI for parameter control

International audiencePhysical controls are widely used by professionals such as sound engineers or aircraft pilots. In particular knobs and sliders are the most prevalent in such interfaces. They have advantages over touchscreen GUIs, especially when users require quick and eyes-free control. However, their interfaces (e.g., mixing consoles) are often bulky and crowded. To improve this, we present the results of a formative study with professionals who use physical controllers. Based on their feedback, we propose design requirements for future interfaces for parameters control. We then introduce the design of our KnobSlider that combines the advantages of a knob and a slider in one unique shape-changing device. A qualitative study with professionals shows how KnobSlider supports the design requirements, and inspired new interactions and applications

Functional modulation of AMP-activated protein kinase by cereblon

AbstractMutations in cereblon (CRBN), a substrate binding component of the E3 ubiquitin ligase complex, cause a form of mental retardation in humans. However, the cellular proteins that interact with CRBN remain largely unknown. Here, we report that CRBN directly interacts with the α1 subunit of AMP-activated protein kinase (AMPK α1) and inhibits the activation of AMPK activation. The ectopic expression of CRBN reduces phosphorylation of AMPK α1 and, thus, inhibits the enzyme in a nutrient-independent manner. Moreover, AMPK α1 can be potently activated by suppressing endogenous CRBN using CRBN-specific small hairpin RNAs. Thus, CRBN may act as a negative modulator of the AMPK signaling pathway in vivo

AirLogic:Embedding Pneumatic Computation and I/O in 3D Models to Fabricate Electronics-Free Interactive Objects

Researchers have developed various tools and techniques towards the vision of on-demand fabrication of custom, interactive devices. Recentwork has 3D-printed artefacts like speakers, electromagnetic actuators, and hydraulic robots. However, these are non-trivial to instantiate as they require post-fabrication mechanical- or electronic assembly. We introduce AirLogic: a technique to create electronics-free, interactive objects by embedding pneumatic input, logic processing, and output widgets in 3D-printable models. AirLogic devices can perform basic computation on user inputs and create visible, audible, or haptic feedback; yet they do not require electronic circuits, physical assembly, or resetting between uses. Our library of 13 exemplar widgets can embed AirLogic-style computational capabilities in existing 3D models. We evaluate our widgets' performance-quantifying the loss of airfow (1) in each widget type, (2) based on printing orientation, and (3) from internal object geometry. Finally, we present fve applications that illustrate AirLogic's potential

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Sulfur dioxide (SO2) is primarily released through industrial, residential, and transportation activities, and creates secondary air pollutants through chemical reactions in the atmosphere. Long-term exposure to SO2 can result in a negative effect on the human body causing respiratory or cardiovascular disease, which makes the effective and continuous monitoring of SO2 crucial. In South Korea, SO2 monitoring at ground stations has been performed, but this does not provide spatially continuous information of SO2 concentrations. Thus, this research estimated spatially continuous ground-level SO2 concentrations at 1 km resolution over South Korea through the synergistic use of satellite data and numerical models. A stacking ensemble approach, fusing multiple machine learning algorithms at two levels (i.e., base and meta), was adopted for ground-level SO2 estimation using data from January 2015 to April 2019. Random forest and extreme gradient boosting were used as based models and multiple linear regression was adopted for the meta-model. The cross-validation results showed that the meta-model produced the improved performance by 25% compared to the base models, resulting in the correlation coefficient of 0.48 and root-mean-square-error of 0.0032 ppm. In addition, the temporal transferability of the approach was evaluated for one-year data which were not used in the model development. The spatial distribution of ground-level SO2 concentrations based on the proposed model agreed with the general seasonality of SO2 and the temporal patterns of emission sources

A comprehensive dataset for home appliance control using ERP-based BCIs with the application of inter-subject transfer learning

Brain-computer interfaces (BCIs) have a potential to revolutionize human-computer interaction by enabling direct links between the brain and computer systems. Recent studies are increasingly focusing on practical applications of BCIs—e.g., home appliance control just by thoughts. One of the non-invasive BCIs using electroencephalography (EEG) capitalizes on event-related potentials (ERPs) in response to target stimuli and have shown promise in controlling home appliance. In this paper, we present a comprehensive dataset of online ERP-based BCIs for controlling various home appliances in diverse stimulus presentation environments. We collected online BCI data from a total of 84 subjects among whom 60 subjects controlled three types of appliances (TV: 30, door lock: 15, and electric light: 15) with 4 functions per appliance, 14 subjects controlled a Bluetooth speaker with 6 functions via an LCD monitor, and 10 subjects controlled air conditioner with 4 functions via augmented reality (AR). Using the dataset, we aimed to address the issue of inter-subject variability in ERPs by employing the transfer learning in two different approaches. The first approach, “within-paradigm transfer learning,” aimed to generalize the model within the same paradigm of stimulus presentation. The second approach, “cross-paradigm transfer learning,” involved extending the model from a 4-class LCD environment to different paradigms. The results demonstrated that transfer learning can effectively enhance the generalizability of BCIs based on ERP across different subjects and environments

Outcomes after aortic aneurysm repair in patients with history of cancer: a nationwide dataset analysis

Synchronous cancer in patients with abdominal aortic aneurysm (AAA) increases morbidity and mortality after AAA repair. However, little is known about the impact of the history of cancer on mortality after AAA repair. Patients with intact AAA who were treated with endovascular aneurysm repair or open surgical repair were selected from the Health Insurance and Review Assessment data in South Korea between 2007 and 2016. Primary endpoints included the 30- and 90-day mortality and long-term mortality after AAA repair. The Cox proportional hazards models were constructed to evaluate independent predictors of mortality. A total of 1999 patients (17.0%, 1999/11785) were diagnosed with cancer prior to the AAA repair. History of cancer generally had no effect in short-term mortality at 30 and 90 days. However, short-term mortality rate of patients with a history of lung cancer was more than twice that of patients without it (3.07% vs. 1.06%, P = 0.0038, 6.14% vs. 2.69%, P = 0.0016). Furthermore, the mortality rate at the end of the study period was significantly higher in AAA patients with a history of cancer than in those without a history of cancer (21.21% vs. 17.08%, P < .0001, HR, 1.31, 95% CI, 1.17–1.46). The history of cancer in AAA patients increases long-term mortality but does not affect short-term mortality after AAA repair. However, AAA repair could increase both short- and long-term mortality in patients with lung cancer history, and those cases should be more carefully selected