• 한국벤처창업학회:학술대회논문집
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• 2019.04a
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• pp.45-49
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• 2019

매년 수많은 기업이 폐업하고 있으며 그 숫자만큼 폐업 기업의 대표가 실패하고 있다. 중소기업연구원의 재기성공요인 분석을 통한 중소 벤처기업의 재도전 활성화 연구(백필규,2011)에 의하면 폐업이나 부도의 형태로 실패하는 기업이 급격하게 증가한 시점은 외환위기가 발생했던 1997년과 1998년의 사이로 보고 있다. 부도 기업의 숫자가 외환위기때는 약 4만사, 1999년부터 2010년까지도 평균 4만 7천여사가 발생하였고 폐업기업수는 부도기업보다 훨씬 많아 매년 80~90만개 전후의 기업이 실패하고 있다. 최근 IBK경제연구소의 실패기업인의 재창업 지원제도 설문조사 결과(김나라,2017)에 의하면 최근 5년간 창업기업은 연평균 77만개사, 폐업기업은 69만개사로 조사되었으며 창업기업의 5년 생존율은 27.3%로 OECD 주요회원국 17개국중 최하위를 차지했다. 오랜시간 대한민국 사회는 사업실패는 곧 패가망신이라는 인식이 깊게 자리잡고 있다. 연대보증이나 재기가 어려운 구조로 인하여 폐업기업의 대표가 실패하면 가족들도 모두 힘들어지고 본인은 경제적, 심리적 어려움에 직면하고 있는 현실이다. 정부와 민간 기관들이 실패기업인들의 재기를 지원하기 위하여 다양한 제도를 운영하고 있지만 아직 시행 초기 단계라 보다 재기를 원하는 기업인들에게 맞춤형으로 도움을 줄 수 있는 실질적이고 효과적인 시스템이 구축되었다 할 수 없다. 창업강국인 미국과 중국의 기업가들은 평균 2.8회의 실패 경험을 가지고 있으나 한국의 기업가는 1.3회의 실패 경험을 보유 한다.(중기청, 2014) 폐업기업 대표의 재무적 손실의 규모와 관계없이 불안과 우울이 낮고 회복탄력성이 높은 기업가가 본인과 가족의 삶의 질과 재창업의지에 긍정적인 효과가 있음으로 나타났다. 연구 대상은 재기중소기업개발원의 재기 기업인과 정부 재창업 지원 프로그램에 지원한 재기 기업인을 대상으로 조사 하였으며 본 연구를 통해 폐업기업 대표에게 필요한 사회적 안전장치와 국가의 창업지원이 고용창출, 매출증가로 이어질 수 있는 선순환 구조의 재기 창업 생태계를 만드는 데 일조하고자 한다.

• Journal of Digital Convergence
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• v.19 no.4
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• pp.235-240
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• 2021

Recently, the number of users has risen sharply while the development speed of the Chinese game industry is rapidly developing. The game industry has already become a promising industry in China's cultural industry. With the rapid development of the Chinese game industry, the demand for specialized game designers and game development personnel is urgent. Still, at present, it is difficult for graduates to get a job at a game company every year even if a new game design department is established at a Chinese university. This may be due to a conflict between the education of the game major in the game market. In this paper, we present a customized development strategy while summarizing the problems that existed in the Chinese game design department in the rapidly developing background of the game industry, Try to provide a valuable opinion. and use it as a reference for the future development of education in the Chinese game major.

• Korean Journal of Construction Engineering and Management
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• v.22 no.1
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• pp.98-105
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• 2021

Recently, there have been many changes in the domestic construction industry. OSC (Off-Site Construction) is expected to solve these problems, and it is emerging as a way to inspire innovation in the domestic construction production system. OSC, which has only recently attracted attention again after previous studies have failed, is lacking in research on preception surveys and customized performance measurements compared to overseas. This study investigated the perceptions of construction industry workers on OSC through a survey, and examined differences in perceptions of each subject and the relative importance of performance indicators. In general, the need for introduction and development of OSC was recognized. Also, drivers and obstacles inhibiting more use of OSC were analyzed. The relative importance for performance indicators and differences in perceptions of each subject were identified. Then, this study suggests plans for diffusion and revitalization of OSC, and key performance indicator for OSC based PC structure apartment housing.

• Communications of Mathematical Education
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• v.34 no.4
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• pp.545-561
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• 2020

The purpose of this study is to investigate the applications and possibilities of major programs that provide services using artificial intelligence in mathematics education. For this study, related papers, reports, and materials were collected and analyzed, focusing on materials mostly published within the last five years. The researcher searched the keywords of "artificial intelligence", "artificial intelligence", "AI" and "mathematics education" independently or in combination. As a result of the study, artificial intelligence for mathematics education was mostly supporting learners' personalized mathematics learning, defining it as an auxiliary role to support human mathematics teachers, and upgrading the technology of not only cognitive aspects but also affective aspects. As suggestions, the researcher argued that followings are necessary: Research for the establishment of an elaborate artificial intelligence mathematical system, discovery of artificial intelligence technology for appropriate use to support mathematics education, development of high quality of mathematics contents for artificial intelligence, and the establishment and operation of a cloud-based comprehensive system for mathematics education. The researcher proposed that continuous research to effectively help students study mathematics using artificial intelligence including students' emotional or empathetic abilities, and collaborative learning, which is only possible in offline environments. Also, the researcher suggested that more sophisticated materials should be developed for designing mathematics teaching and learning by using artificial intelligence.

• Food Science and Industry
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• v.53 no.3
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• pp.307-315
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• 2020

The food R&D operating system needs to be changed according to the changes in the food industry as well as the domestic and overseas environments. In this aspect, a future-oriented food R&D operating strategy linked with the governmental policy are proposed to foster the promising food industry. The strategic R&D approaches are summarized on the basis of global mega-trends and food industry trend analysis, and current R&D status and issues are also reviewed to set the R&D operating direction for future food industry. To advance the R&D operating system of the food industry, some practical suggestions are given as follows: strengthening the research planning system for efficient R&D program operation, enhancing the role assignment and collaboration among the R&D organizations, reinforcing the support system tailored to industrial sites and securing the future technology bases as well as resolving present issues, and linking R&D programs with policies and improving the food R&D management system.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.25 no.1
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• pp.146-151
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• 2021

Currently, the demand for vehicles from one family is increasing in many countries at home and abroad, reducing the number of people on the vehicle and increasing the number of vehicles on the road. The multi-passenger lane system, which is available to solve the problem of traffic congestion, is being implemented. The system allows police to monitor fast-moving vehicles with their own eyes to crack down on illegal vehicles, which is less accurate and accompanied by the risk of accidents. To address these problems, applying deep learning object recognition techniques using images from road sites will solve the aforementioned problems. Therefore, in this paper, we compare and analyze the performance of existing deep learning models, select a deep learning model that can identify real-time vehicle occupants through video, and propose a vehicle occupancy detection algorithm that complements the object-ident model's problems.

• Journal of Platform Technology
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• v.10 no.1
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• pp.29-34
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• 2022

The emergence of new diseases such as the Covid 19 pandemic that occurs in the 21st century and the occurrence of health abnormalities according to the busy daily life of modern people are increasing. Accordingly, the importance of health care management and data-based health management is being highlighted, and in particular, interest in personal health management data based on personal health care data of patients is rapidly increasing. In this study, to solve the difficult problems of personal health management, we developed a personal health care platform incorporating IT for self-diagnosis and solution and developed an application that measures bio-signals generated in the human body and transmits them to the platform. A health management system was established. Through this, not only the health care of modern people, but also the psychological and emotional care support needs through psychological and emotional monitoring of the developmentally disabled and the vulnerable who have difficulty in expressing their opinions are to be addressed. In addition, the overall health and living environment data of the individual was integrated to develop an optimized medical and health management service for the individual.

• Journal of Broadcast Engineering
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• v.27 no.5
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• pp.738-750
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• 2022

In this study, we reviewed and discussed whether auditory stimuli with short length can evoke emotion-related neurological responses. The findings implicate that if personalized sound tracks are provided to XR users based on machine learning or probability network models, user experiences in XR environment can be enhanced. We also investigated that the arousal-relaxed factor evoked by short auditory sound can make distinct patterns in functional connectivity characterized from background EEG signals. We found that coherence in the right hemisphere increases in sound-evoked arousal state, and vice versa in relaxed state. Our findings can be practically utilized in developing XR sound bio-feedback system which can provide preference sound to users for highly immersive XR experiences.

• Journal of the Korea Society of Computer and Information
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• v.28 no.3
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• pp.119-126
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• 2023

This study attempted to find out the factors affecting the self-directed learning ability of nursing students who took online lectures. The research method was a structured questionnaire survey targeting 2nd to 4th grade nursing college students, and the analysis method was analyzed by t-test, ANOVA, and multiple regression analysis. As a result of the study, the self-directed learning ability of nursing college students was an average of 3.48 points out of 5 points, and it was found that learning immersion had the greatest effect on self-directed learning ability. Based on the results of this study, it will be necessary to establish a quality education system and the efforts of instructors who apply various lecture methods or customized lecture programs so that learners can immerse themselves in learning in order to improve learners' self-directed learning ability.

• Journal of Internet Computing and Services
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• v.24 no.2
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• pp.57-66
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• 2023

Currently, a new energy system is emerging that implements consumption reduction by improving energy efficiency. Accordingly, as smart grids spread, the rate system by timing is expanding. The rate system by timing is a rate system that applies different rates by season/hour to pay according to usage. In this study, external factors such as temperature/day/time/season are considered and the time series prediction model, LSTM, is used to predict energy power usage data. Based on this energy usage prediction model, energy usage charges are reduced by analyzing usage patterns for each device and transferring power energy from the maximum load time to the light load time. In order to analyze the usage pattern for each device, a clustering technique is used to learn and classify the usage pattern of the device by time. In summary, this study predicts usage and usage fees based on the user's power data usage, analyzes usage patterns by device, and provides customized demand transfer services based on analysis, resulting in cost reduction for users.