• Journal of the Korea Academia-Industrial cooperation Society
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• v.22 no.1
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• pp.123-130
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• 2021

With the recent developments in computer technology, there has been an increasing interest in the field of machine learning. This also has led to a significant increase in real business cases of machine learning theory in various sectors. In finance, it has been a major challenge to predict the future value of financial products. Since the 1980s, the finance industry has relied on technical and fundamental analysis for this prediction. For future value prediction models using machine learning, model design is of paramount importance to respond to market variables. Therefore, this paper quantitatively predicts the stock price movements of individual stocks listed on the KOSPI market using machine learning techniques; specifically, the reinforcement learning model. The DQN and A2C algorithms proposed by Google Deep Mind in 2013 are used for the reinforcement learning and they are applied to the stock trading strategies. In addition, through experiments, an input value to increase the cumulative profit is selected and its superiority is verified by comparison with comparative algorithms.

• Journal of Korea Society of Digital Industry and Information Management
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• v.18 no.4
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• pp.67-75
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• 2022

Recently, e-learning has been attracting significant attention due to COVID-19. However, while e-learning has many advantages, it has disadvantages as well. One of the main disadvantages of e-learning is that it is difficult for teachers to continuously and systematically monitor learners. Although services such as personalized e-learning are provided to compensate for the shortcoming, systematic monitoring of learners' concentration is insufficient. This study suggests a method to evaluate the learner's concentration by applying machine learning techniques. In this study, emotion and gaze data were extracted from 184 videos of 92 participants. First, the learners' concentration was labeled by experts. Then, statistical-based status indicators were preprocessed from the data. Random Forests (RF), Support Vector Machines (SVMs), Multilayer Perceptron (MLP), and an ensemble model have been used in the experiment. Long Short-Term Memory (LSTM) has also been used for comparison. As a result, it was possible to predict e-learners' concentration with an accuracy of 90.54%. This study is expected to improve learners' immersion by providing a customized educational curriculum according to the learner's concentration level.

• Information and Communications Magazine
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• v.33 no.2
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• pp.66-72
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• 2016

지난해 12월 3일, 금융위원회(이하"금융위")는 금융개혁 정례 기자간담회에서 그 동안의 금융개혁 성과를 발표하였다. 지난 3월 금융개혁 추진방향 마련 시 50개의 금융개혁 실천과제를 선정하고, 규제개혁 과정에서 20개 과제를 추가 발굴하여 총 70개의 금융개혁 실천과제를 선정하였고, 그 중 (1) 제도개선이 완료되어 시행중인 과제가 24건, (2) 일부 시행중인 과제가 17건, (3) 방안은 발표했으나, 법령 개정 등 제도개선 중인 과제가 16건, 마지막으로 (4) 방안을 마련중인 과제 즉 미발표 과제가 총 13건인 것으로 밝혀졌다. 금융개혁 실천과제 중, 핀테크 생태계 구축과 관련된 과제는 5건, 인터넷 전문은행 도입과 관련된 과제는 2건 그리고 빅데이터 활성화와 관련된 과제는 2건으로 직접적인 핀테크 산업 활성화와 관련된 과제는 총 9개라고 볼 수 있다. 이 중에서 6건의 과제는 이미 제도개선이 완료되어 시행되고 있으며, 나머지 3건은 방안은 발표되었으나, 법령 개정 등 제도개선이 필요한 상태이다. 여전히 은산분리 규제 완화를 위한 은행법 개정 이슈, 신용정보법 개정을 통한 빅데이터 산업 활성화 등은 여전히 제도개선 과제나 규제 완화 방안이 구체화되지 않은 단계이다. 금융당국은 금융산업에 대해서 오프라인 산업으로서 규제마인드를 갖고 있다. 국경을 넘나들며 금융서비스가 제공되는 시대에 오프라인 산업 관점의 전통적 금융규제들을 재검토해야 한다. 금융산업에서 핀테크와 쉽게 결합하여 서비스를 창출하고, 시장에서 경쟁할 수 있도록 하는 관점에서 기존의 규제들을 재평가해야 한다. 인터넷에서는 국경을 넘어선 서비스를 막을 수 없으므로 국내형 규제에 얽매인 국내 금융회사들은 혁신적 서비스를 도입할 수 없어 궁극적으로 글로벌 인터넷 거인들이 결국 국내 금융회사들의 사업 기회를 빼앗아 가게 될 것이다. 글로벌 인터넷 기업들이 국내 금융기관을 지배하게 될 것이라는 숙명을 빨리 깨닫고 과거의 관점에서 벗어나 온라인 서비스로 기존의 서비스를 변경하는 노력이 필요하다. 결국 금융산업은 핀테크 기업들과 협업하여 기존의 규제를 완화하거나 서비스에 맞게 변화시키고, 과감하게 폐지하는 것이 필요하다.

• The Transactions of the Korea Information Processing Society
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• v.7 no.2
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• pp.488-496
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• 2000

this paper describes the design and implementation of node scheduling for MX Server that is CC-NUMA System COMSIX, the operating system of MX Server, is designed to suit for CC-NUMA Architecture. MX Server consists of up to 8 nodes, and each node is connected by SCI ring. This node scheduling scheme considers data locality for performance improvement of Oracle8i DBMS on the CC-NUMA architecture. For DBMS such as Oracle8i, a multi-threaded process may be run to tie on particular disk. We have developed a CG binding function that the multi-threaded process bound the node. Currently, We don't have an available CC-NUMA Platform. Instead of MX Server, we developed the Node scheduling scheme for multi-threaded process to suit server platform on the PC test-bed and tested completely.

• Korean Journal of Psychosomatic Medicine
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• v.31 no.2
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• pp.118-124
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• 2023

Objectives : Depressive disorder and anxiety disorder frequently co-occur, even at sub-threshold level. This study aims to identify network structure of co-morbid depression and anxiety at symptom level in nonclinical population and to reveal the central symptoms and bridge symptoms of the co-morbidity. Methods : This study was based on 2022 Asan Youth Mental Health Screening. Patient health questionnaire (PHQ-9) and Generalized anxiety disorder scale (GAD-7) were used to assess depressive and anxiety symptoms of 810 young adult participants from community sample. Network structure of co-morbid depressive and anxiety symptoms was estimated by Isingfit model. Results : Depressed mood, Restlessness and Nervousness were the most central symptoms in the network. Bridge symptoms between anxiety and depression were Restlessness and Irritability. Conclusions : This study revealed key central symptoms and bridge symptoms of co-morbid depression and anxiety in nonclinical population and provided potential insight for treatment targets to reduce co-morbidity.

• Proceedings of the Korean Institute Of Construction Engineering and Management
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• autumn
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• pp.164-170
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• 2003

This paper is to evaluate the informational direction, current situations and ERP establishment concerning constructing industry, to present the right directions, implemented cases for implementing constructional ERP, also to suggest the effect, influence, problems and shootings in constructional ERP arena. The constructing industries in korea are facing great turning point because of the huge corruptions currently happened and forcing to open the market in 1997. Attempting to establish Computer Integrated construction system (ERP) by breaking down constructing cost, improving quality, operating rapid and effective construction to enhance productivity, it is hard to achieve the goal with only inter-contractor's establishment. Constructing industries are integrated ones, consisted of many organizations for instance ordering agencies, contractors, subcontractors, material vendors, etc. and use various information formats such as texts, graphics, drawings. I dare suggest that implementation of constructional CALS including EDI/EC, GIS is tile only solution to control the information systematically generated in whole stages from planing, designing, constructing through maintenance, and to supply or switch the information.

• Korean Journal of School Psychology
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• v.18 no.2
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• pp.153-174
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• 2021

The purpose of this study is to verify antecedent variables that positively influence behavioural engagement during school engagement, which is critical to adolescent socialization. The antecedent variable was categorized into the personal characteristics of adolescents who are the main agents of socialization and peer support and teacher support, which can be called social support at school sites. Individual characteristics include strength recognition, strength utilization, and learning goal orientation, and, peer supports include the supports for personality strength and academy, and, teacher supports include the supports for personality strength and perspective change. For this study, a survey was conducted on 539 high school students nationwide, collected data, 33 of them were removed, and 506 data were analyzed. Analysis shows that only learning goal orientation set as a sub-factor of individual characteristics has a static significant effect on behavioral engagement. Finally, based on the findings, we discuss the implications, limitations, and future research tasks of the study.

• The Journal of the Convergence on Culture Technology
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• v.10 no.4
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• pp.305-310
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• 2024

With the emergence of generative AI, a new era of coexistence with humanity has begun. The vast data-driven learning capabilities of AI are being utilized in various industries to achieve a level of productivity distinct from human learning. However, AI also manifests societal phenomena such as technophobia. This study aims to analyze collaborative AI models based on an understanding of AI and identify areas within the jewelry industry where these models can be applied. The utilization of collaborative AI models can lead to the acceleration of idea development, enhancement of design capabilities, increased productivity, and the internalization of multimodal functions. Ultimately, AI should be used as a collaborative tool from a utilitarian perspective, which requires a proactive, human-centric mindset. This research proposes collaborative AI strategies for the jewelry business, hoping to enhance the industry's competitiveness.

• Journal of Industrial Convergence
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• v.22 no.8
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• pp.115-125
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• 2024

The purpose of this study was to verify the mediating effect of self-esteem in the relationship between family conflict, self-esteem, and life satisfaction perceived by multicultural adolescent. The analysis data used the data of the '2nd MAPS (Multicultural Adolescents Panel Study) 2020' surveyed by the Korea Youth Policy Institute. At the time of the survey, 1,533 multicultural adolescents enrolled in the fifth grade of elementary school were selected as samples. The analysis method was verified for the significance of the indirect effect by technical analysis, correlation analysis, and PROCESS MACRO Model Number 4 with mediating effect and bootstrapping. As a result of the study, first, family conflict perceived by multicultural adolescent negatively affected life satisfaction. Second, self-esteem was partially mediated in the relationship between family conflict and life satisfaction. In other words, it is significant in that it presented policy alternatives and practical programs to improve life satisfaction of multicultural youth.

• Smart Media Journal
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• v.11 no.11
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• pp.17-24
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• 2022

With the spread of smart speakers based on voice recognition technology and deep learning technology, not only non-disabled people, but also the blind or physically handicapped can easily control home appliances such as lights and TVs through voice by linking home network services. This has greatly improved the quality of life. However, in the case of speech-impaired people, it is impossible to use the useful services of the smart speaker because they have inaccurate pronunciation due to articulation or speech disorders. In this paper, we propose a personalized voice classification technique for the speech-impaired to use for some of the functions provided by the smart speaker. The goal of this paper is to increase the recognition rate and accuracy of sentences spoken by speech-impaired people even with a small amount of data and a short learning time so that the service provided by the smart speaker can be actually used. In this paper, data augmentation and one cycle learning rate optimization technique were applied while fine-tuning ResNet18 model. Through an experiment, after recording 10 times for each 30 smart speaker commands, and learning within 3 minutes, the speech classification recognition rate was about 95.2%.