• 한국운동역학회지
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• 제32권3호
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• pp.69-79
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• 2022

Objective: The purpose of this study is to analyze trends related to sports and artificial intelligence (AI) to understand the trends and how they change according to time, and to establish methods to apply AI in sports. Both macro and micro perspectives related to sports utilization of AI were analyzed. Method: In this study, after analyzing and discussing various information related to the use of artificial intelligence in the sports through a search of academic journals, papers, books, and websites published recently at nationally and internationally, the application plan of artificial intelligence in the sports field was presented. Results: 1) Motion analysis technology using artificial intelligence is effective in sports where posture is important, and if it provides systematic feedback and training methods, it can help improve performance. 2) The introduction of a sports referee judgment system using artificial intelligence is expected to improve performance by restoring factual judgment and objective fairness in sports games. 3) Artificial intelligence will provide coaching staff and players with a variety of information to help improve performance through systematic coaching and improving feedback and enhanced training methods. 4) It is judged that artificial intelligence-related to sports ethics, sports ICT, sports marketing, sports prediction, etc. We think that based on the current AI research trends will have a positive impact on all sports-related areas, helping to revitalize sports. Conclusion: Motion analysis technology using artificial intelligence, sports referee judgment system, coaching using artificial intelligence, and artificial intelligence are judged to have a positive effect on all sports-related areas and help revitalize sports.

• International Journal of Computer Science & Network Security
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• 제22권11호
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• pp.357-366
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• 2022

Artificial intelligence (AI) is the replication of human intelligence by computer systems and machines using tools like machine learning, deep learning, expert systems, and natural language processing. AI can be applied in administrative settings to automate repetitive processes, analyze and forecast data, foster social communication skills among staff, reduce costs, and boost overall operational effectiveness. In order to understand how AI is being used for administrative duties in various organizations, this paper gives a critical dialogue on the topic and proposed a framework for using artificial intelligence in organizations. Additionally, it offers a list of specifications, attributes, and requirements that organizations planning to use AI should consider.

• 한국시뮬레이션학회논문지
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• 제30권3호
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• pp.1-9
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• 2021

전장에 있는 지휘관과 참모들은 상황을 인식하고 그 결과를 바탕으로 지휘결심을 통해 군사 활동을 수행하는데, 최근 정보기술의 발달과 함께 지휘결심을 지원하는 인공지능에 대한 요구가 증가하였다. 인공지능을 활용하기 위해서는 강화학습에 필요한 학습 data set의 식별, 수집 그리고 전처리가 필수적이다. 그러나 전술 C4I 체계에 저장된 적 data는 정확성, 적시성, 충분성 측면에서 인공지능 학습 data로 사용하기에 적절하지 않기 때문에 학습 data를 수집하고 훈련 시킬 수 있는 대안이 필요하다. 본 논문에서는 육군의 워게임 훈련 모델인 '창조 21 모델 훈련 data'를 활용하여 인공지능을 학습시키는 방법론을 제시하였다. 연구 범위는 군사결심수립과정과 연계하여 인공지능의 역할과 범위를 구체화하고, 그 역할에 맞추어 인공지능을 훈련 시키기 위해 창조 21 모델 연습 data를 활용하는 모델을 제시하였다. 공개가 제한되는 군사자료의 특성을 고려하여 가상의 sample data를 제작하였고, 공개가 제한되는 대한민국 육군의 교리는 인터넷에서 수집 가능한 미군 교리를 활용하였다.

• International journal of advanced smart convergence
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• 제9권4호
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• pp.132-138
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• 2020

Worldwide, the number of corona virus disease 2019 (COVID-19) confirmed cases is rapidly increasing. Although vaccines and treatments for COVID-19 are being developed, the disease is unlikely to disappear completely. By attaching a smart sensor to the respirator worn by medical staff, Internet of Things (IoT) technology and artificial intelligence (AI) technology can be used to automatically detect the medical staff's infection symptoms. In the case of medical staff showing symptoms of the disease, appropriate medical treatment can be provided to protect the staff from the greater risk. In this study, we design and develop a system that detects cough, a typical symptom of respiratory infectious diseases, by applying IoT technology and artificial technology to respiratory protection. Because the cough sound is distorted within the respirator, it is difficult to guarantee accuracy in the AI model learned from the general cough sound. Therefore, coughing and non-coughing sounds were recorded using a sensor attached to a respirator, and AI models were trained and performance evaluated with this data. Mel-spectrogram conversion method was used to efficiently classify sound data, and the developed cough recognition system had a sensitivity of 95.12% and a specificity of 100%, and an overall accuracy of 97.94%.

• Journal of information and communication convergence engineering
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• 제21권2호
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• pp.152-158
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• 2023

In recent years, as computer-generated imagery has been applied to more industries, realistic facial animation is one of the important research topics. The current solution for realistic facial animation is to create realistic rendered 3D characters, but the 3D characters created by traditional methods are always different from the actual characters and require high cost in terms of staff and time. Deepfake technology can achieve the effect of realistic faces and replicate facial animation. The facial details and animations are automatically done by the computer after the AI model is trained, and the AI model can be reused, thus reducing the human and time costs of realistic face animation. In addition, this study summarizes the way human face information is captured and proposes a new workflow for video to image conversion and demonstrates that the new work scheme can obtain higher quality images and exchange effects by evaluating the quality of No Reference Image Quality Assessment.

• 한국병원경영학회지
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• 제28권4호
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• pp.73-89
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• 2023

Purposes: The purpose of this study was to empirically analyze the effect of the attitude of medical staff providing medical services on the treatment satisfaction of the patients who experienced outpatient care at the hospitals and clinics. In particular, it was verified whether the courtesy of the medical staff to the outpatients has moderated the effect of the medical staff's explanation on the treatment satisfaction. Methodology: After controlling the socio-demographic factors of the outpatients with their treatment and waiting time, multiple regression analyses were conducted to figure out the effect of the attitude of the medical staff on the treatment satisfaction. And the covariance analyses were adopted to verify the moderating effect of the variables of the medical staff. Findings: At both hospitals and clinics, all attitudes of medical staff such as the way they explain to and communicate with the patients, and their courtesy showed positive effects on treatment satisfaction. Among them, the courtesy of the medical staff was the most influential variable on the satisfaction of the treatment, and it only had the control power over the effect of the way they explain on the treatment satisfaction. Practical Implication: Among the medical staff's attitudes toward patients at hospital or clinic level, the courtesy of doctors and nurses is an important factor in improving treatment satisfaction. In particular, if the level of their courtesy is low among the medical services rendered at the clinics, the satisfaction level will decrease even if the level of explanation of the medical staff is high. Therefore, in terms of hospital management, treatment satisfaction can be improved when doctors and nurses provide medical services to visitors with polite, humble and friendly manner in explaining to and communicating with the patients.

• 한국군사과학기술학회지
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• 제25권5호
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• pp.513-521
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• 2022

This study deals with an AI architecture model for collecting battlefield data using the tactical C4I system. Based on this model, the artificial staff can be utilized in tactical echelon. In the current structure of the Army's tactical C4I system, Servers are operated by brigade level and above and divided into an active and a standby server. In this C4I system structure, the AI server must also be installed in each unit and must be switched when the C4I server is switched. The tactical C4I system operates a server(DB) for each unit, so data matching is partially delayed or some data is not matched in the inter-working process between servers. To solve these issues, this study presents an operation concept so that all of alternate server can be integrated based on virtualization technology, which is used as an source data for AI Meta DB. In doing so, this study can provide criteria for the AI architectural model of the ground tactical echelon.

• 인터넷정보학회논문지
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• 제21권1호
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• pp.237-246
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• 2020

본 논문에서는 의사결심 지원체계인 전장관리체계의 지능화를 위해 의사결심 조건에 기초한 데이터 모델링 방안을 제시하였다. 인간처럼 보고 식별도 하고, 자유롭게 움직임을 통해 원하는 위치에 도달하는 모습은 쉽게 이해되거나 실생활에서 체감하고 있는데 비해, 원하는 위치에 도달한 이후 인간 인지 행위 중 가장 중요한 하나인 의사 결심 판단을 구현했다거나 혹은 그러한 예제를 아직은 찾아 볼 수 없는 실정이다. 도착을 원했던 회의실에 인간을 대신해 에이전트가 오기는 했지만 판단을 도와주거나 대신 해주어야 할 임무인 예컨대, 가격 정책을 올릴 것인지 내릴 것인지, 지휘관이 심사숙고하고 있는 예컨대, 역습을 하는 것이 현명한지 아닌지에 대한 판단을 지원해 주지 못하고 있다. 군 지휘 통제의 현상과 현안을 고찰하였고, 각 상황에 대한 판단을 내릴 때 기계참모의 조언이 가능하게하기 위한 많은 양의 데이터 확보가 가능하도록, 현 지휘통제 체계를 변경시킬 방안으로 의사결심 조건에 기초한 데이터 모델링 방안을 제시하였다. 또한 제시한 방안에 대해 기계가 하는 의사결정의 한 예시로써 의사결정 트리 방법론을 적용하였다. 이를 통해 향후 AI 상황 판단 참모가 어떠한 모습으로 우리에게 다가올지에 대한 혜안을 제공하고자 하였다.

• 해양환경안전학회지
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• 제2권1호
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• pp.143-143
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• 1996

Recent Class requirements and IMO recommendations concerning Hull Strength Monitoring (HSM) have prompted an increasing number of shipowner to adopt monitoring systems on bulk carriers and tanker. Such systems are designed to give warning when stress levels and the frequency and magnitude of ship motions approach levels which require corrective action. When fitted these systems provide enhanced operational safety and efficiency. This paper describes a development beyond the standard BMT HSM system through the integration of stress, motion and radar-based sea state monitoring with powerful, on-board, artificial intelligence (AI) tools. The latter utilises conceptual clustering techniques as an aid to pattern recognition in stress, fatigue. motion and sea state data clusters. This, in turn, provides additional operational guidance for ship's staff. Feedback from applications of the standard BMT HSM and extended HSM systems on board the British Steel Bulk Shipping fleet is described.

• 전자통신동향분석
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• 제36권1호
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• pp.89-98
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• 2021

The Ministry of National Defense aims to create an environment in which transparent and reasonable defense policies can be implemented in real time by establishing the vision of smart defense innovation based on the Fourth Industrial Revolution and promoting innovation in technology-based defense operation systems. Artificial intelligence (AI) based defense technology is at the level of basic research worldwide, includes no domestic tasks, and involves classified military operation data and command control/decision information. Further, it is needed to secure independent technologies specialized for our military. In the army, military power continues to decline due to aging and declining population. In addition, it is expected that there will be more than 500,000 units should be managed simultaneously, to recognize the battle situation in real time on the future battlefields. Such a complex battlefield, command decisions will be limited by the experience and expertise of individual commanders. Accordingly, the study of AI core technologies supporting real-time combat command is actively pursued at home and abroad. It is necessary to strengthen future defense capabilities by identifying potential threats that commanders are likely to miss, improving the viability of the combat system, ensuring smart commanders always win conflicts and providing reasonable AI digital staff based on data science. This paper describes the recent research trends in AI military staff technology supporting commander decision-making, broken down into five key areas.