• Journal of Digital Convergence
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• v.16 no.12
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• pp.163-173
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• 2018

This study examined the difference between the information asymmetry in pre- and post K-IFRS adoption used each samples. Efficient market assumption suggests that capital markets already have recognized real value of PP&E and applied those values for estimating the item, in which case PP&E revaluation is not additional information in the capital market but simply an activity to makes costs. This study examined whether the information asymmetry had reduced significantly after adopting K-IFRS or not, verified each period samples those are pre- and post-adopting the asset revaluation since it could have been adopted in advance from 2008. As study results, I confirmed PP&E revaluation affected to reduce the information asymmetry in pre- adopting K-IFRS, but not in post- adopting K-IFRS. These results could be one of proofs which are supported that capital market have been judging PP&E revaluation as the window dressing.

• Journal of the Korea Convergence Society
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• v.12 no.1
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• pp.327-340
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• 2021

This is nonequivalent control group pretest-posttest quasi-experimental study to develop a sexual education program for improving sexual confidence of men with spinal cord injury disabled and assess the effect of the program. The program was based on Dick & Carey's systematic design of instruction, literature review, focus group, in-depth interview, expert meeting, and preliminary study and formative evaluation. Subjects were conveniently assigned to experimental group of 30 and control group of 29, and the program was provided to experimental group once a week for 90~120 minutes, 3 sessions total. Sexual knowledge, attitude, and marriage intention were measured before, after, and after 4 weeks of intervention, and there was a significant difference in sexual knowledge(p<.001) and attitude(p=.020). The program positively changed sexual knowledge and attitude of men with spinal cord injury, and was useful nursing intervention. This study is considered to be significant as a basic data for social awareness ventilation and health education for the disabled.

• International Area Studies Review
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• v.14 no.2
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• pp.205-227
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• 2010

Where should a plant or service facility be located? The decision is crucial since the capital investment in land, factory construction, and facility is enormous. Once a firm has sunk a large sum of money into a factory, it lives with the decision for a long time. In this age of global markets and global production, this is a key decision problem for contemporary manufacturing and/or service. Using data from Korean and Chinese managers and the AHP (Analytic Hierarchy Process), this paper did study on the actual condition for identifying the differences of opinion between the two group's(Shanghai and Shenyang managers) in how to make decisions on the location problems. Since this study was carried out during recent global economy recession, and the limitation of the collected questionnaires, it is hard to avoid the possibility for those managers to show different view from their ordinary times. Nevertheless, this paper will provide managers with useful informations on successful facility location in China.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.21 no.12
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• pp.494-501
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• 2020

This study is aimed at exploring the effects of forest experience activities on promoting children's community spirit. To achieve this, a pre-post survey was empirically carried out with 40 children at Kindergarten A in the city of Chungnam. The comprehensive findings showed a significant difference between the experimental group, which had forest experience activities, and the control group, which had outdoor activities based on the existing Nuri curriculum. Based on a pre-test for intimacy, emotion, mutual public awareness, and participation consciousness as sub-factors of community spirit, which adopted all the research hypotheses, the results suggest that the forest kindergarten will become an educational place for children. Consequently, personality education using nature in forest kindergartens can become an excellent goal, helping to boost the development of children's sensitivity and emotional stability through awakening the five senses; building up self-awareness, self-reliance, and trust; learning consideration and respect for others; and developing positive attitudes, sociality, potential, imagination, and creativity through forest activities with their peers.

• Journal of Korea Entertainment Industry Association
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• v.14 no.4
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• pp.57-65
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• 2020

The purpose of this study is to analyze the problem solving ability of occupational therapy students by applying PBL classes using social networks. Data were collected from 35 students in the third year of occupational therapy at K University from March to June 2019. The results were as follows: First, PBL application using social networks showed a significant improvement in problem solving ability. Seconds, there was a significant difference in problem solving ability according to the preference of mobile device use and major satisfaction. Therefore, as a learning tool for improving the problem-solving ability of occupational therapy students, we proposed a way to increase satisfaction with learning by activating PBL using social networks.

• The Journal of the Korea Contents Association
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• v.22 no.9
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• pp.283-297
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• 2022

This study analyzed to strategy and structure of outward foreign direct investment(OFDI) by Chinese Enterprises in 'one belt, one load' countries along the line from the perspective of Dunning's OLI paradigm. Chinese enterprises' investment in 'one belt, one road' countries was largely promoted for two strategic purposes. One is an investment to secure energy resources due to the nature of resource holdings in 'one belt, one road' countries, and the other is a transfer investment to solve the problem of surplus facilities, a problem in China's domestic economy. Chinese enterprises' investments in these 'one belt, one road' countries is evaluated to have been made with Dunning's investment decision conditions in the OLI paradigm, namely, Ownership specific advantages, Location specific advantages, and Internalization specific advantages. only if there is a difference, investment country, investment method, and investment industry are different due to the structure of international relations, religious conflict and cultural heterogeneity, institutional investment environment of the region, and awareness of Chinese enterprises.

• Journal of The Korean Association of Information Education
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• v.25 no.6
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• pp.995-1003
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• 2021

As the need for artificial intelligence (AI) education, which will become the core of the upcoming intelligent information society rises, the national level is also focusing attention by including artificial intelligence-related content in the curriculum. In this study, the PASPA education program was presented to enhance students' creative problem-solving ability in the process of solving problems in daily life through supervised machine learning. And Micro:bit, a physical computing tool, was used to enhance the learning effect. The teaching and learning process applied to the PASPA education program consists of five steps: Problem Recoginition, Argument, Setting data standard, Programming, Application and evaluation. As a result of applying this educational program to students, it was confirmed that the creative problem-solving ability improved, and it was confirmed that there was a significant difference in knowledge and thinking in specific areas and critical and logical thinking in detailed areas.

• Proceedings of the Korea Water Resources Association Conference
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• 2023.05a
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• pp.120-120
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• 2023

본 연구에서는 CCTV 영상 내 빗줄기의 특성을 바탕으로 강우강도를 산정하기 위한 합성곱 신경망(CNNs, Convolutional Neural Networks) 기반 강우강도 산정 모형을 제안하였다. 중앙대학교 및 한국건설생활환경시험연구원 내 대형기후환경시험실에서 얻은 CCTV 영상들을 대상으로 연구를 수행하고, 우적계 등과 같은 지상 관측자료와 강우강도 산정 결과를 비교·검증하였다. 먼저, CCTV 영상 내 빗줄기의 미세한 변동 특성을 반영하기 위해 데이터 전처리 작업을 진행하였다. 이는 원본 영상으로부터 빗줄기 층을 분리해내는 과정, 빗줄기 층에서 빗물 입자를 분리해내는 과정, 그리고 빗물 입자를 인식하는 과정 등 총 세 단계로 구분된다. 합성곱 신경망 기반 강우강도 산정 모형 구축을 위해 영상 전처리가 완료된 데이터들을 입력값으로 설정하고, 촬영 시점에 대응되는 지상관측 자료를 출력값으로 고려하여 강우강도 산정모형을 훈련시켰다. CCTV 원자료 내 특정 영역에 편향되어 강우강도를 산정하는 과적합 현상의 발생을 방지하기 위해 원자료 내 5개의 관심 영역(ROI, Region of Interest)을 설정하였다. 추가로, CCTV의 해상도를 총 4개(2560×1440, 1920×1080, 1280×720, 720×480)로 구분함으로써 해상도 변화에 따른 학습 결과의 차이를 분석·평가하였다. 이는 기존 사례들과 비교했을 때, CCTV 영상을 기반으로 빗줄기의 거동 특성과 같은 물리적인 현상을 직간접적으로 고려하여 강우강도를 산정했다는 점과 더불어 머신러닝을 적용하여 강우 이미지가 갖는 본질적인 특징들을 파악했다는 측면에서, 추후 본 연구에서 제안한 모형의 활용 가치가 극대화될 수 있을 것으로 판단된다.

• Korean Journal of Social Welfare Studies
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• v.41 no.4
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• pp.345-368
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• 2010

The purpose of this study is to develop the School Multicultural Climate(SMC) scale for students and to evaluate its reliability and validity. This study comprises of both qualitative and quantitative research. Preliminary items were developed based on the theoretical literature and interviews with students. The scale was evaluated with students in grades 4 through 6 in the seven elementary schools. Exploratory factor analysis was determined that the scale was composed of four components: Equal Status, Mutual Cooperation, Friendly Relations, Supportive Norms. The scale demonstrated that Cronbach's alpha=.943 for the internal consistency of total items. And the standard error of the measurement, another way of evaluating reliability, was 3.33. Criteria-related validity was evaluated by showing that the differences of the students' recognition of the school multicultural climate level, which depend on the availability of the multiculture-related policy, was statistically significant. The correlation analysis for the convergent validity was performed with the theoretically related variables such as self esteem and school adjustment. It was found that the SMC scale was a reliable and valid measure for evaluating the multicultural climate level of elementary school.

• Journal of Intelligence and Information Systems
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• v.25 no.1
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• pp.163-177
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• 2019

As smartphones are getting widely used, human activity recognition (HAR) tasks for recognizing personal activities of smartphone users with multimodal data have been actively studied recently. The research area is expanding from the recognition of the simple body movement of an individual user to the recognition of low-level behavior and high-level behavior. However, HAR tasks for recognizing interaction behavior with other people, such as whether the user is accompanying or communicating with someone else, have gotten less attention so far. And previous research for recognizing interaction behavior has usually depended on audio, Bluetooth, and Wi-Fi sensors, which are vulnerable to privacy issues and require much time to collect enough data. Whereas physical sensors including accelerometer, magnetic field and gyroscope sensors are less vulnerable to privacy issues and can collect a large amount of data within a short time. In this paper, a method for detecting accompanying status based on deep learning model by only using multimodal physical sensor data, such as an accelerometer, magnetic field and gyroscope, was proposed. The accompanying status was defined as a redefinition of a part of the user interaction behavior, including whether the user is accompanying with an acquaintance at a close distance and the user is actively communicating with the acquaintance. A framework based on convolutional neural networks (CNN) and long short-term memory (LSTM) recurrent networks for classifying accompanying and conversation was proposed. First, a data preprocessing method which consists of time synchronization of multimodal data from different physical sensors, data normalization and sequence data generation was introduced. We applied the nearest interpolation to synchronize the time of collected data from different sensors. Normalization was performed for each x, y, z axis value of the sensor data, and the sequence data was generated according to the sliding window method. Then, the sequence data became the input for CNN, where feature maps representing local dependencies of the original sequence are extracted. The CNN consisted of 3 convolutional layers and did not have a pooling layer to maintain the temporal information of the sequence data. Next, LSTM recurrent networks received the feature maps, learned long-term dependencies from them and extracted features. The LSTM recurrent networks consisted of two layers, each with 128 cells. Finally, the extracted features were used for classification by softmax classifier. The loss function of the model was cross entropy function and the weights of the model were randomly initialized on a normal distribution with an average of 0 and a standard deviation of 0.1. The model was trained using adaptive moment estimation (ADAM) optimization algorithm and the mini batch size was set to 128. We applied dropout to input values of the LSTM recurrent networks to prevent overfitting. The initial learning rate was set to 0.001, and it decreased exponentially by 0.99 at the end of each epoch training. An Android smartphone application was developed and released to collect data. We collected smartphone data for a total of 18 subjects. Using the data, the model classified accompanying and conversation by 98.74% and 98.83% accuracy each. Both the F1 score and accuracy of the model were higher than the F1 score and accuracy of the majority vote classifier, support vector machine, and deep recurrent neural network. In the future research, we will focus on more rigorous multimodal sensor data synchronization methods that minimize the time stamp differences. In addition, we will further study transfer learning method that enables transfer of trained models tailored to the training data to the evaluation data that follows a different distribution. It is expected that a model capable of exhibiting robust recognition performance against changes in data that is not considered in the model learning stage will be obtained.