• Korean Journal of Cognitive Science
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• v.15 no.1
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• pp.13-24
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• 2004

This paper deals with the anaphoric usage of demonstratives when they refer to what are already mentioned in the context. We examine syntactic, semantic and pragmatic factors that contribute to the choice of demonstratives. As for anaphoric usage, English and Spanish show the even distribution between proximal and distal demonstratives with the meaning of their deictic counterparts. Korean and Russian, however, show the uneven distribution of the more prevalent form (unmarked on) and the lesser one (market one). This study aims at a typological explanation for the anaphoric usage of demonstratives through comparison and contrast with such factors as the distance to the antecedent, cognitive status, psychological distance and the center of attention.

• Journal of Korea Multimedia Society
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• v.24 no.11
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• pp.1580-1587
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• 2021

Currently, the development and sale of various emoticons has given users a wider range of choices, but a systematic and specific approach to the recognition and use of emoticons by actual users is lacking. Therefore, this study tried to investigate the subjective perception and visual attention concentration of actual users on negative emotional expression emoticons through a survey and eye tracking experiment. First, as a result of subjective recognition analysis, it was found that emoticons are frequently used because their appearance is important, and they can express various emotions in a fun and interesting way. In particular, it was found that emoticons that express negative emotions are often used because they can indirectly express negative emotions through various and concretely expressed visual elements. Next, as a result of the eye tracking experiment, it was found that the negative emotional expression emoticons focused on the large elements that visually emphasized or emphasized the emotional expression elements, and it was found that the focus was not only on the facial expression but also on the physical behavioral responses and language of expression of emotions. These results will be used as basic data to understand users' perceptions and utilization of the diversified emoticons. In addition, for the long-term growth and activation of the emoticon industry market in the future, continuous research should be conducted to understand the various emotions of real users and to develop differentiated emoticons that can maximize the empathy effect appropriate to the situation.

• The Journal of Korean Association of Computer Education
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• v.12 no.1
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• pp.57-69
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• 2009

Generally, teaching in computer Labs is more difficult than teaching in a normal class for teachers to give students systematic learning. One of the reasons is that the students who participate in the class tend to use the programs that are not related to the practice included in the curriculum. Therefore, the students cannot focus on the subjects that they should do. To solve this problem, there are many kinds of systems that can control the students' computers. However, they cannot help teachers to manage the students and computers due to the inconvenience of usage and the lack of functions. In this study, we analyzed the problems in the computer-practice classwork and designed a new system to support that the students can participate in the computer classes with more attention. In addition, it is offered that the computer teachers can manage the classes and the students more efficiently with this new system. For these purposes, the effects mentioned were approved before in the real lab situations. Experimental results showed that the proposed system can improve the rate of the students attention, leading them to get better grades on the achievement test.

• Journal of Physiology & Pathology in Korean Medicine
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• v.27 no.5
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• pp.540-552
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• 2013

This study focuses on discussing several issues that we encounter when we 'modernize' the fundamental theories of Korean Medicine(KM): It is pertinent to set the boundaries of the "fundamental theories" of the KM. The boundaries can be set based on: a) setting the medicine and the philosophy of medicine apart and b) re-evaluating the traditional theories of KM based on the needs of the modern practitioners of KM. The fundamental theories of KM should focus on how effectively they can observe, explain, and predict the clinical cases. The clinical cases and observations should not be distorted in order to satisfy the theory. "The modernization of KM" can be defined as the change in traditional medicine to fit the needs of the contemporary world, while not losing the focus and the nature of the KM. The fundamental theories of KM will play a key role in modernizing the KM, as the focus and the inherent nature of the KM comes from these fundamental theories. The modernization of the fundamental theories of KM will be crucial to both possible models of future healthcare system-the plural healthcare system, or the western medicine-centric integrated healthcare system. The modernization will also help in advancing the future medical studies. The key to modernization of the fundamental theories of the KM is in translating the key terms of KM in modern light. As a solution, this study suggests paying attention to the 'scientific metaphors', and especially to the 'theory-constitute metaphors' among those. More in-depth studies need to be done on these.

• Journal of the Korea Computer Graphics Society
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• v.25 no.3
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• pp.1-9
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• 2019

The image obtained from systems such as autonomous driving cars or fire-fighting robots often suffer from several degradation such as noise, motion blur, and compression artifact due to multiple factor. It is difficult to apply image recognition to these degraded images, then the image restoration is essential. However, these systems cannot recognize what kind of degradation and thus there are difficulty restoring the images. In this paper, we propose the deep neural network, which restore natural images from images degraded in several ways such as noise, blur and JPEG compression in situations where the distortion applied to images is not recognized. We adopt the channel attention modules and skip connections in the proposed method, which makes the network focus on valuable information to image restoration. The proposed method is simpler to train than other methods, and experimental results show that the proposed method outperforms existing state-of-the-art methods.

• Korea journal of population studies
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• v.29 no.3
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• pp.139-157
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• 2006

This study presents limitations of the old family supported system for the elderly being surfaced in the face of the changing life style of the people in today's industrialized, urban Korean society. The qualitative data used for this study are collected from the focus group discussions(FGD). The FGD data numbered a total of 43 participants who were divided into 8 different groups, each consisting of 5-6 respondents sorted out by sex and age as well as by their current cohabitation with their parents or having such experience in the past. The study paid special attention focusing on the values and the expectations regarding the elderly support and the family relationship. A critical reexamination of the old family support system for the elderly at this particular juncture is also a step forward necessary for the eventual formulation of policy measures by the state and the society to produce a new viable support system for the elderly in the future.

• Smart Structures and Systems
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• v.29 no.1
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• pp.1-16
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• 2022

Despite recent breakthroughs in deep learning and computer vision fields, the pixel-wise identification of tiny objects in high-resolution images with complex disturbances remains challenging. This study proposes a modified U-net for tiny crack segmentation in real-world steel-box-girder bridges. The modified U-net adopts the common U-net framework and a novel Self-Attention-Self-Adaption (SASA) neuron as the fundamental computing element. The Self-Attention module applies softmax and gate operations to obtain the attention vector. It enables the neuron to focus on the most significant receptive fields when processing large-scale feature maps. The Self-Adaption module consists of a multiplayer perceptron subnet and achieves deeper feature extraction inside a single neuron. For data augmentation, a grid-based crack random elastic deformation (CRED) algorithm is designed to enrich the diversities and irregular shapes of distributed cracks. Grid-based uniform control nodes are first set on both input images and binary labels, random offsets are then employed on these control nodes, and bilinear interpolation is performed for the rest pixels. The proposed SASA neuron and CRED algorithm are simultaneously deployed to train the modified U-net. 200 raw images with a high resolution of 4928 × 3264 are collected, 160 for training and the rest 40 for the test. 512 × 512 patches are generated from the original images by a sliding window with an overlap of 256 as inputs. Results show that the average IoU between the recognized and ground-truth cracks reaches 0.409, which is 29.8% higher than the regular U-net. A five-fold cross-validation study is performed to verify that the proposed method is robust to different training and test images. Ablation experiments further demonstrate the effectiveness of the proposed SASA neuron and CRED algorithm. Promotions of the average IoU individually utilizing the SASA and CRED module add up to the final promotion of the full model, indicating that the SASA and CRED modules contribute to the different stages of model and data in the training process.

• Journal of Korean Elementary Science Education
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• v.41 no.4
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• pp.754-770
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• 2022

For teachers, noticing refers to paying attention to something, indicating they interpret it and how they are willing to react to it in the context of their own instruction. Analysis of noticing features enables us to understand the overall characteristics of the teacher's lesson design, practice, and reflection, which are core agents in the educational design and implementation. This can also be taken to be the basis of education design for competency reinforcement for teachers. Therefore, in this study, the characteristics of noticing shown in teachers' reflections after class design and demonstration were identified. For this purpose, the self-reflection journals of 106 elementary pre-service teachers enrolled in the College of Education in Gangwon-do were analyzed. In particular, the journals were gathered that were written after the demonstration dealing with the change of gas volume by temperature in science class. After designing a noticing analysis frame consisting of the five dimensions 'agent', 'stage', 'topic', 'focus', and 'stance', the frequency and ratio of noticing by each dimension's components were derived. The frequency and ratio of noticing for the dimension of 'focus' were analyzed for the dimensions of 'stage' and 'topic'. The results of the study were as follows. For the dimension of 'agent', the frequency of teacher and student was the highest, and for the dimension of 'stage', inquiry activity was the highest. For the 'topic' dimension, class design according to the teaching strategy appeared most frequently, and in the 'focus' dimension, the cases that did not specify the goal of the class and the competencies to be achieved by the students appeared most frequently. In the 'stance' dimension, description showed the highest frequency. From the analysis of how the 'focus' changes according to the 'stage' and 'topic', it was found that a characteristic focus appeared for each component of the dimension. From these results, the implications of the noticing characteristics of pre-service teachers for the design and implementation of teacher education were discussed.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.10 no.6
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• pp.215-223
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• 2015

Recently, in OECD countries, youth unemployment has become one of the most serious problems in society. Entrepreneurship creates innovative new companies that create more jobs than big traditional companies. In addition, entrepreneurship develops creative human resources leading to fertile ground for new technology and business innovation. Recently, regulatory theory has drawn a lot of attention and interest in the literature of psychology and marketing management. However, the theory has not been applied to the study of entrepreneurship. In this article, we try to examine the relationship among regulatory focus, entrepreneurial orientation, and entrepreneurial intentions of korean college students who show their interests in entrepreneurship. From our empirical study, we find the followings. First, promotion focus thriving on optimism, taking risks, and trying new actively affect positively on entrepreneurial orientation and entrepreneurial intention. Second, prevention focus concentrating on security, fulfilling responsibilities and maintaining efficiency does not always affect negatively on entrepreneurial orientation and entrepreneurial intention. In other words, prevention-focused students do not always have bad impression on entrepreneurship and may consider entrepreneurship as viable career path similar to average college students. Third, our empirical findings are consistent with previous studies that entrepreneurial intention is positively affected by entrepreneurial orientation.

• Journal of Intelligence and Information Systems
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• v.22 no.2
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• pp.81-96
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• 2016

As the internet has become widespread and easy to access everywhere, it is common for people to search information via online search engines such as Google and Naver in everyday life. Recent studies have used online search volume of specific keyword as a measure of the internet users' attention in order to predict disease outbreaks such as flu and cancer, an unemployment rate, and an index of a nation's economic condition, and etc. For stock traders, web search is also one of major information resources to obtain data about individual stock items. Therefore, search volume of a stock item can reflect the amount of investors' attention on it. The investor attention has been regarded as a crucial factor influencing on stock price but it has been measured by indirect proxies such as market capitalization, trading volume, advertising expense, and etc. It has been theoretically and empirically proved that an increase of investors' attention on a stock item brings temporary increase of the stock price and the price recovers in the long run. Recent development of internet environment enables to measure the investor attention directly by the internet search volume of individual stock item, which has been used to show the attention-induced price pressure. Previous studies focus mainly on Dow Jones and NASDAQ market in the United States. In this paper, we investigate the relationship between the individual investors' attention measured by the internet search volumes and stock price changes of individual stock items in the KOSDAQ market in Korea, where the proportion of the trades by individual investors are about 90% of the total. In addition, we examine the difference between industries in the influence of investors' attention on stock return. The internet search volume of stocks were gathered from "Naver Trend" service weekly between January 2007 and June 2015. The regression model with the error term with AR(1) covariance structure is used to analyze the data since the weekly prices in a stock item are systematically correlated. The market capitalization, trading volume, the increment of trading volume, and the month in which each trade occurs are included in the model as control variables. The fitted model shows that an abnormal increase of search volume of a stock item has a positive influence on the stock return and the amount of the influence varies among the industry. The stock items in IT software, construction, and distribution industries have shown to be more influenced by the abnormally large internet search volume than the average across the industries. On the other hand, the stock items in IT hardware, manufacturing, entertainment, finance, and communication industries are less influenced by the abnormal search volume than the average. In order to verify price pressure caused by investors' attention in KOSDAQ, the stock return of the current week is modelled using the abnormal search volume observed one to four weeks ahead. On average, the abnormally large increment of the search volume increased the stock return of the current week and one week later, and it decreased the stock return in two and three weeks later. There is no significant relationship with the stock return after 4 weeks. This relationship differs among the industries. An abnormal search volume brings particularly severe price reversal on the stocks in the IT software industry, which are often to be targets of irrational investments by individual investors. An abnormal search volume caused less severe price reversal on the stocks in the manufacturing and IT hardware industries than on average across the industries. The price reversal was not observed in the communication, finance, entertainment, and transportation industries, which are known to be influenced largely by macro-economic factors such as oil price and currency exchange rate. The result of this study can be utilized to construct an intelligent trading system based on the big data gathered from web search engines, social network services, and internet communities. Particularly, the difference of price reversal effect between industries may provide useful information to make a portfolio and build an investment strategy.