• 한국IT서비스학회지
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• 제20권1호
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• pp.67-79
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• 2021

The advent of the 4th Industrial Revolution is also causing many changes in defense operations. Defense reform and the fourth industrial revolution promoted smart defense innovation, and attempts are being made to incorporate cutting-edge science and technology into various fields such as weapons systems and defense operations. Education and training is one of the areas in which information and intelligence are urgently needed in the spirit of defense operations. Due to the nature of defense education and training, which aims to fight against the enemy, there is no emphasis on psychological training in the field rather than informatization, but in developed countries with various experiences of modern warfare, investment and vitalization of education and training are vital. Through this, efforts are being made to foster soldiers with problem-solving skills in uncertain battlefields. The informatization and intelligence of defense education and training is no longer a matter that can be delayed, and the innovation of education and training using cutting-edge science and technology can be said to be an age-old task to improve the results of education and training in the fourth industrial revolution. The purpose of this is because the application of related technologies is not the goal itself as the 4th Industrial Revolution arrives, but it has been made possible through the rapid advancement of science and technology that has made it difficult to realize education and training, even though it has long been desired. Ultimately, education and training data will be integrated and artificial intelligence-based intelligent learning systems will maximize the performance of education and training, thereby improving the combat readiness.

• Clinical Psychopharmacology and Neuroscience
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• 제16권4호
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• pp.391-397
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• 2018

Objective: Meditation can elicit trait-like changes in psychological and social styles, as well as enhancement of emotional regulatory capacity. We investigated the relation between personality traits and emotional intelligence in meditation practitioners. Methods: Seventy-two long-term practitioners of mind-body training (MBT) and 62 healthy comparative individuals participated in the study. The participants completed emotional intelligence questionnaires and the Myers-Briggs Type Indicator (MBTI). Results: The MBT group revealed higher scores on all five emotional intelligence factors than did those in the control group, such as emotional awareness and expression, empathy, emotional thinking, emotional application, and emotional regulation (all $p{\leq}0.001$). MBT practitioners also had higher scores on the intuition of perceiving function (t=-2.635, p=0.010) and on the feeling of the judging function (t=-3.340, p=0.001) of the MBTI compared with those in the control group. Only the MBT group showed a robust relationship with every factor of emotional intelligence and MBTI-defined intuitive styles, indicating that higher scores of emotional intelligence were related to higher scores for intuition. Conclusion: Emotional intelligence of meditation practitioners showed notable relationships with some features of personality trait. In-depth associations between emotional intelligence and personality traits would help to foster psychological functions in meditation practitioners.

• 한국항공운항학회지
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• 제31권2호
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• pp.108-115
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• 2023

Alongside the rapid development of AI technology, which is stepping in to do tasks more quickly and less prone to error than humans can, the possibility for MI (multiple intelligence) development warrants equal attention and fervor. Recent theories of human intelligence point beyond standard cognitive capacity, IQ, and shine a light on the other unique potentials naturally endowed to humans. The applicability of MI to aviation is discussed, suggesting that it is important to consider ways to integrate MI development techniques into pilot education and training. Experiential starting points are discussed.

• International Journal of Computer Science & Network Security
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• 제22권6호
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• pp.25-32
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• 2022

The hypothesis of the study of the article is that the use of elements of artificial intelligence will increase the effectiveness of the educational process of the university if: a set of pedagogical conditions for the construction and use of an expert system with elements of artificial intelligence in the educational process of the university is revealed; a model for preparing a future teacher of vocational training for the use of elements of artificial intelligence has been developed; a special course has been developed that contributes to the implementation of the professional orientation of education. In accordance with this, the following tasks were studied in the article: An analysis of scientific and methodological research in the field of the current state, prospects for the development and use of elements of artificial intelligence in the preparation of a future teacher of vocational training and to determine the dynamics of the introduction of intelligent expert systems in education; A set of pedagogical conditions for the construction and use of an expert system with elements of artificial intelligence in the educational process of a university is revealed; It is substantiated to develop a model for preparing a teacher of vocational training to use elements of artificial intelligence.

• 아동학회지
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• 제21권2호
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• pp.33-44
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• 2000

In this study, a random sample of 111 six-year-old children were assigned to one of 3 experimental conditions: categorization training using cognitive apprenticeship, categorization training using metacognitive procedures, and no categorization training. Level of intelligence was measured by Raven's(1986) Coloured Progressive Matrics(CPM). No difference was found between apprenticeship and metacognitive training in the high CPM children. In the middle and low CPM levels, cognitive apprenticeship training was more efficient than metacognitive training. This indicates that cognitive apprenticeship, which emphasizes the thinkaloud procedure of both the experts and the novice though modeling and coaching for self-implementation, is a more effective approach than the metacognitive approach for categorization in middle and low CPM children.

• 한국산학기술학회논문지
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• 제19권6호
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• pp.280-290
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• 2018

본 연구는 의사소통 훈련을 받은 실험집단과 그렇지 않은 대조집단 사이의 의사소통능력, 감성지능, 자존감과 대인관계능력의 차이를 비교하는 비동등성 유사실험 연구이다. 연구대상은 C시 소재의 D대학병원에 근무하는 21명의 간호사를 실험집단으로, 21명의 간호사를 대조집단으로 구성하여 2017년 4월부터 5월까지, 실험집단에게는 의사소통능력, 감성지능, 자존감 및 대인관계능력 향상을 위한 의사소통 훈련 프로그램을 주 1회 2시간씩 총 4회기를 진행하였고, 연구의 효과성 검정을 위하여 사전, 사후 검사를 실시하였다. 자료 분석은 SPSS for Window 23을 이용하여 사전사후검사의 평균과 표준편차, 독립표본 Mann-Whitney의 U검증, 대응표본 Wilcoxon 부호 순위 검증을 실시하였다. 연구결과 실험집단과 훈련을 받지 않은 대조집단에서 의사소통능력(Z=-3.361, p<.05), 감성지능(Z=-2.209, p<.05), 자존감(Z=-1.633, p<.05), 대인관계능력(Z=-2.577, p<.05)으로 나타나, 의사소통훈련 프로그램 후 실험집단의 의사소통능력, 감성지능(EQ), 자존감 및 대인관계능력 점수가 모두 유의하게 증가하였으며, 모든 가설은 지지되었다. 이러한 결과를 볼 때 임상현장에서 간호업무 수행 시 의사소통 훈련프로그램을 활용한다면 의사소통능력, 감성지능(EQ), 자존감 및 대인관계능력의 향상으로 치료적인 의사소통과 효과적인 간호를 제공하여 환자의 만족감을 높이고 간호의 질 향상에도 기여할 것이다.

• 인터넷정보학회논문지
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• 제25권4호
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• pp.23-37
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• 2024

디지털 트윈은 현실세계의 물리적 객체를 디지털 세계의 가상객체로 모사하고 시뮬레이션을 통해 미래에 발생 가능한 현상을 예측함으로써, 현실세계의 문제를 해결 또는 최적화하기 위해 고안된 M&S(Modeling and Simulation) 기술이다. 디지털 트윈은 지금까지 도시, 산업 시설 등 대규모 환경에서 특정 목적을 달성하기 위해 수집된 다양한 데이터 기반으로 정교하게 설계되고 활용되어 왔다. 이러한 디지털 트윈 기술을 실생활에 적용하고 사용자 맞춤형 서비스 기술로 확장하기 위해서는 개인정보 보호, 시뮬레이션의 개인화 등 실질적이지만 민감한 문제를 해결해야 한다. 이러한 문제를 해결하기 위해 본 논문에서는 개인화 디지털 트윈을 위한 연합학습 기반의 클라이언트 훈련 가속 방식(FACTS)을 제안한다. 기본적인 접근 방식은 클러스터 기반의 적응형 연합학습 훈련 절차를 활용해 개인정보를 보호하면서 동시에 사용자와 유사한 훈련 모델을 선택하고 훈련을 가속하는 것이다. 다양한 통계적으로 이질적인 조건의 실험 결과 FACTS는 기존의 FL 방식에 비해 훈련 속도 및 자원 효율성 측면에서 우수한 것으로 나타난다.

• 보건행정학회지
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• 제28권3호
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• pp.294-300
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• 2018

The development and management of epidemiology intelligence service (EIS) officer with more specialized competence to cope with and prepare for health threats, including pandemic of emerging and re-emerging infectious diseases, is a high priority policy issue in Korea. First of all, we need to establish the training goal of EIS officer. It is necessary to establish manpower training and management system with at least three tiers including quantitative and qualitative targets. Second, at least 50% of all EIS officer must secure a physician and secure expertise and competence for epidemic. Third, for the ultimate purpose of EIS officer, the establishment of a public health expert should expand the scope of epidemiologist's work to health and medical care, occupational environment, and various disasters. Fourth, it is essential to expand the epidemiologist training and education program to the level of advanced countries. Especially, the training course should be expanded at least twice of current times. Fifth, it is necessary to independently install and operate the 'EIS Officer Training Center' as a mid- and long-term goal. Stewardship and governance are secured with the organization, personnel, etc. that can fully manage the planning, management, and evaluation of the EIS system. In the future, it will be necessary to establish a systematic and phased operational base of education and training programs for EIS officer, and establish a sustainable implementation system for strategy development. In addition, it is urgent to revise the guidelines for training public health professionals and strengthening competencies, and for establishing professional educational institutions.

• 정보교육학회논문지
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• 제25권6호
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• pp.1015-1024
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• 2021

엔트리, Machine Learning for Kids, Teachable Machine과 같이 블록 기반 프로그래밍 언어에서 활용할 수 있도록 인공지능을 간단히 학습시킬 수 있는 다양한 플랫폼들이 존재한다. 그러나 이와 같은 플랫폼들은 별도의 메뉴를 통해 인공지능 학습을 진행한 다음, 학습된 모델을 코드 에디터에서 활용하는 방식을 따르고 있다. 이와 같은 방식은 학습되는 과정을 학생들이 더 직관적으로 살펴볼 수 있다는 장점이 있지만, 학습 메뉴와 코드 에디터를 모두 활용해야 한다는 단점도 존재한다. 본 논문에서는 코드 에디터에서 인공지능 학습과 코딩을 모두 진행할 수 있는 인공지능 블록을 개발한다. 본 인공지능 블록은 스크래치 블록으로 제시되지만 실제 학습 과정은 파이썬 서버를 통해 수행된다. 파란색 펜과 빨간색 펜을 분류하는 모델, 덴탈 마스크와 KF94 마스크를 분류하는 모델을 학습하는 과정을 통해 본 블록에 대해 상세히 기술한다. 또, 학습 성능 면에서 Teachable Machine와 큰 차이가 없음을 실험적으로 나타내었다.

• 한국인공지능학회지
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• 제5권1호
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• pp.29-37
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• 2017

The range of problems that can be handled by the activation of big data and the development of hardware has been rapidly expanded and machine learning such as deep learning has become a very versatile technology. In this paper, mnist data set is used as experimental data, and the Cross Entropy function is used as a loss model for evaluating the efficiency of machine learning, and the value of the loss function in the steepest descent method is We applied the Gradient Descent Optimize algorithm to minimize and updated weight and bias via backpropagation. In this way we analyze optimal reliability value corresponding to the number of exercises and optimal reliability value without overfitting. And comparing the overfitting time according to the number of data changes based on the number of training times, when the training frequency was 1110 times, we obtained the result of 92%, which is the optimal reliability value without overfitting.