• 제어로봇시스템학회:학술대회논문집
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• 1990.10a
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• pp.575-579
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• 1990

This paper describes an algorithm that can efficiently analyze the multichannel ECG signal using the frame. The input is a set of significant features (points) which have been extracted from an original sampled signal by using the split-and-merge algorithm. A signal from each channel can be hierarchical ADN/OR graph on the basis of the priori knowledge for ECG signal. The search mechanisms with some heuristics and the mixed paradigms of data-driven hypothesis formation are used as the major control mechanisms. The mutual relations among features are also considered by evaluating a score based on the relational spectrum. For recognition of morphologies corresponding to OR nodes, an hypothesis modification strategy is used. Other techniques such as instance, priority update of prototypes, and template matching facility are also used. This algorithm exactly recognized the primary points and supporting points from the multichannel ECG signals.

• Proceedings of the Korean Information Science Society Conference
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• 2007.10b
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• pp.379-382
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• 2007

지능형로봇 산업은 큰 성장 잠재력을 가진 신산업이다. 하지만 로봇을 개발하기 위해서 설계, 구현 단계에서 실제 로봇을 사용하기 어려워 시뮬레이션 환경이 많이 사용된다. Pyro 프로젝트는 파이썬 언어로 작성된 로봇 시뮬레이션 및 제어 환경이다. Player/Stage 프로젝트는 C와 C++로 작성된 로봇 시뮬레이션 및 제어 환경이다. Pyro 프로젝트는 Player/Stage 통합환경을 제공하여 Pyro를 사용하는 것과 같이 Player/Stage를 사용할 수 있다. 본 논문에서는 Pyro와 Stage 시뮬레이터를 이용한 시뮬레이션 환경을 구축하고 적용사례 등을 서술한다.

• The Journal of Korea Robotics Society
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• v.16 no.2
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• pp.172-178
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• 2021

The COVID-19 pandemic has been reshaping the world by accelerating non-contact services and technologies in various domains. Hospitals as a healthcare system lie at the center of the dramatic change because of their fundamental roles: medical diagnosis and treatments. Leading experts in health, science, and technologies have predicted that robotics and artificial intelligence (AI) can drive such a hospital transformation. Accordingly, several government-led projects have been developed and started toward smarter hospitals, where robots and AI replace or support healthcare personnel, particularly in the diagnosis and non-surgical treatment procedures. This article inspects the remaining element of healthcare services, i.e., surgical treatment, focusing on evaluating whether or not currently available laparoscopic surgical robotic systems are sufficiently preparing for the era of post-COVID-19 when contactless is the new normal. Challenges and future directions towards an effective, fully non-contact surgery are identified and summarized, including remote surgery assistance, domain-expansion of robotic surgery, and seamless integration with smart operating rooms, followed by emphasis on robot tranining for surgical staff.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.21 no.4
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• pp.103-108
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• 2021

It is difficult to predict an increase or decrease of stock price because of uncertainty. Researches for prediction of stock price using AI technology have been done for a long time. Recently stock buy/sell recommend programs called by Robot Advisor using AI machine learning technology are used. In this paper, to develop a stock buy/sell recommend system using AI technology, an core engine of this system is designed. An analysis and design method of a stock buy/sell recommend system software using AI machine learning technology will be presented by showing user requirement analysis using object-oriented analysis method, flowchart and screen design.

• Journal of Engineering Education Research
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• v.25 no.6
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• pp.23-37
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• 2022

This study evaluated the engineering students' ethical sensitivity to an AI emotion recognition robot scenario and explored its characteristics. For data collection, 54 students (27 majoring in Convergence Electronic Engineering and 27 majoring in Computer Software) were asked to list five factors regarding the AI robot scenario. For the analysis of ethical sensitivity, it was checked whether the students acknowledged the AI ethical principles in the AI robot scenario, such as safety, controllability, fairness, accountability, and transparency. We also categorized students' levels as either informed or naive based on whether or not they infer specific situations and diverse outcomes and feel a responsibility to take action as engineers. As a result, 40.0% of students' responses contained the AI ethical principles. These include safety 57.1%, controllability 10.7%, fairness 20.5%, accountability 11.6%, and transparency 0.0%. More students demonstrated ethical sensitivity at a naive level (76.8%) rather than at the informed level (23.2%). This study has implications for presenting an ethical sensitivity evaluation tool that can be utilized professionally in educational fields and applying it to engineering students to illustrate specific cases with varying levels of ethical sensitivity.

• The Journal of Bigdata
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• v.7 no.1
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• pp.37-47
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• 2022

Autonomous delivery operation data is the key to driving a paradigm shift for last-mile delivery in the Corona era. To bridge the technological gap between domestic autonomous delivery robots and overseas technology-leading countries, large-scale data collection and verification that can be used for artificial intelligence training is required as the top priority. Therefore, overseas technology-leading countries are contributing to verification and technological development by opening AI training data in public data that anyone can use. In this paper, 326 objects were collected to trainn autonomous delivery robots, and artificial intelligence models such as Mask r-CNN and Yolo v3 were trained and verified. In addition, the two models were compared based on comparison and the elements required for future autonomous delivery robot research were considered.

• Journal of Practical Engineering Education
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• v.12 no.2
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• pp.339-351
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• 2020

In response to changes in Fourth Industrial Revolution in recent years, the field of education has focused on development of the human resources in the areas of artificial intelligence (AI: Artificial Intelligence) and industrial robot. Due to particular interest in these areas, the importance of developing integrated human resources equipped with artificial intelligence technology is emphasized in higher education and vocational competence development. In regards to rapid changing environment, this study created a program "Fostering personalized AI integrated human resource" and established an operational model correspond to latest personalized education trend. The established operational model was conducted twice using Delphi survey with experts in AI and innovative education in order to verify the suitability of program's basic structure, training process, and the sub-components of the operational strategy. The final training model was applied to the online vocational training platform (STEP) and a plan was proposed to establish a personalized training model to foster an AI integrated competent individual.

• 제어로봇시스템학회:학술대회논문집
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• 1992.10b
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• pp.296-300
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• 1992

This paper deals with a dual mode control system design for the starching work robot. From the feature of this work, the robot has redundant degree of freedom. In this paper, we try to split the whole movement the robot into a gross motion part ai. a fine motion part so as to achieve a good tracking performance. The preview learning control is applied to the gross motion part. The validity of the dual mode control architecture is demonstrated.

• Proceedings of the Korea Information Processing Society Conference
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• 2023.11a
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• pp.836-837
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• 2023

정보서비스와 업무의 무인·자동화를 통해 대중들이 쉽게 이용할 수 있도록 공공장소에 설치한 무인단말기를 말한다. 그러나 현재의 키오스크는 정보의 방대함과 선택의 다양성으로 어렵고 복잡하다. 이러한 키오스크 사용상 단점을 극복하기 위하여 AI 기반 대화형 인터페이스 웨이터 로봇을 개발하였다.

• 한국정보교육학회:학술대회논문집
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• 2010.08a
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• pp.227-233
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• 2010

Graph is applied to GIS, Network, AI and so on. We use graph concept in our daily life unconsciously. So this paper describe how graph concept is used when robot searches shortest path between two distinct vertices. It is performed in real world. For this, it consists of three step; maze traverse, graph generation, and shortest path search. Maze traverse steps is that robot navigates maze. It is most difficult step. Graph generation step is to represent structural information into graph. Shortest path search step is to that robot move between two vertices. It is not implemented yet. So we introduce process in design level.