• 컴퓨터교육학회논문지
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• 제16권5호
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• pp.39-47
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• 2013

자기 통제력이 약한 청소년의 경우, 감각 추구 성향 및 현실탈출의 대안으로 인터넷을 사용하다 인터넷중독에 빠지는 경우가 많다. 이러한 인터넷중독 문제점을 해결하기 위해, 인터넷중독 척도 기준에 따른 인터넷 자가진단 기법이 개발되어 사용되고 있다. 하지만 기존의 방식들은 중복적인 척도기준과 설문지 형식의 진단방식을 이용하고 있어, 체계적으로 중독의 상관성 및 환경의 영향성을 평가하고 있지 못하고 있다. 따라서 본 논문에서는 보다 체계적인 인터넷중독 자가진단을 위하여 새로운 형식개념분석 기법을 활용한 인터넷중독 자가진단 기법을 제안하고 자가진단 시스템으로 구현하고자 한다. 또한 가정환경, 가족과의 관계, 교우관계, 학교생활 등 다양한 관점 기반의 분석을 통해 측정된 데이터의 상관성을 분석하고자 한다.

• 데이타베이스연구회지:데이타베이스연구
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• 제34권3호
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• pp.58-68
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• 2018

분산 컴퓨팅이란 다수의 서버로 구성된 분산 시스템에서 데이터를 효율적으로 저장 및 처리하는 기술이다. 따라서 분산 시스템을 구성하는 서버의 상태에 따라 분산 컴퓨팅의 성능에 큰 영향을 미친다. 본 논문은 분산 시스템에서 실시간으로 발생하는 시스템 자원의 로그 데이터를 수집하고 이상을 탐지하여 결과를 시각화하는 자가 진단 시스템을 제안한다. 먼저, 자가 진단 과정을 수집, 전달, 분석, 저장, 시각화의 다섯 단계로 구분한다. 다음으로, 자가 진단 과정이 실시간성, 확장성, 고가용성의 목표를 만족하도록 실시간 자가 진단 시스템을 설계한다. 본 시스템은 대표적인 실시간 분산 기술인 Apache Flume, Apache Kafka, Apache Storm을 기반으로 구현되어 실시간성, 확장성, 고가용성의 세 가지 목표를 만족할 수 있다. 또한, 자가 진단 과정에서 로그 데이터 처리의 지연을 최소화하도록 간단하지만 효과적인 이동 평균 및 3-시그마 기반 이상 탐지 기법을 사용한다. 본 논문의 결과를 통해, 분산 시스템 내에서 서버 상태를 실시간으로 진단할 수 있는 분산 실시간 자가 진단 시스템을 구축할 수 있다.

• Clinical Endoscopy
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• 제57권3호
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• pp.283-292
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• 2024

We developed three e-learning systems for endoscopists to acquire the necessary skills to improve the diagnosis of early gastric cancer (EGC) and demonstrated their usefulness using randomized controlled trials. The subjects of the three e-learning systems were "detection", "characterization", and "preoperative assessment". The contents of each e-learning system included "technique", "knowledge", and "obtaining experience". All e-learning systems proved useful for endoscopists to learn how to diagnose EGC. Lecture videos describing "the technique" and "the knowledge" can be beneficial. In addition, repeating 100 self-study cases allows learners to gain "experience" and improve their diagnostic skills further. Web-based e-learning systems have more advantages than other teaching methods because the number of participants is unlimited. Histopathological diagnosis is the gold standard for the diagnosis of gastric cancer. Therefore, we developed a comprehensive diagnostic algorithm to standardize the histopathological diagnosis of gastric cancer. Once we have successfully shown that this algorithm is helpful for the accurate histopathological diagnosis of cancer, we will complete a series of e-learning systems designed to assess EGC accurately.

• 제어로봇시스템학회논문지
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• 제17권10호
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• pp.967-982
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• 2011

This paper presents a FTNCS (Fault-Tolerant Networked Control System) that can tolerate control surface failure and packet delay/loss in an UAV (Unmanned Aerial Vehicle). The proposed method utilizes the benefits of self-diagnosis by smart actuators along with the control allocation technique. A smart actuator is an intelligent actuation system combined with microprocessors to perform self-diagnosis and bi-directional communications. In the event of failure, the smart actuator provides the system supervisor with a set of actuator condition data. The system supervisor then compensate for the effect of faulty actuators by re-allocating redundant control surfaces based on the provided actuator condition data. In addition to the compensation of faulty actuators, the proposed FTNCS also includes an efficient algorithm to deal with network induced delay/packet loss. The proposed algorithm is based on a Lagrange polynomial interpolation method without any mathematical model of the system. Computer simulations with an UAV show that the proposed FTNCS can achieve a fast and accurate tracking performance even in the presence of actuator faults and network induced delays.

• 보건행정학회지
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• 제33권2호
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• pp.173-184
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• 2023

Background: The coronavirus disease 2019 pandemic has been challenging the healthcare service, i.e., the vitalization of the point of care accompanying self-testing in vitro diagnostic medical devices (IVDs). This study aims to suggest priority criteria to classify self-testing IVDs using the analytic hierarchy process technique. Methods: Two dimensions of the characteristics embedded in the IVDs and the diseases to be diagnosed with self-testing IVDs were parallelly considered and independently investigated. In addition, three expert panels consisting of laboratory medical doctors (n=11), clinicians (n=10), and citizens (n=11) who have an interest in the selection of self-testing IVDs were asked to answer to questionnaires. Priorities were derived and compared among each expert panel. Results: First of all, ease of specimen collection (0.241), urgency of the situation (0.224), and simplicity of device operation (0.214) were found to be the most important criteria in light of the functional characteristics of self-testing IVDs. Medical doctors valued the ease of specimen collection, but the citizen's panel valued self-management of the disease more. Second, considering the characteristics of the diseases, the priority criteria were shown in the order of prevalence of diseases (0.421), fatality of disease (0.378), and disease with stigma (0.201). Third, medical doctors responded that self-testing IVDs were more than twice as suitable for non-communicable diseases as compared to communicable diseases (0.688 vs. 0.312), but the citizen's group responded that self-testing IVDs were slightly more suitable for infectious diseases (0.511 vs. 0.489). Conclusion: Our findings suggested that self-testing IVDs could be primarily classified as the items for diagnosis of non-communicable diseases for the purpose of self-management with easy specimen collection and simple operation of devices, taking into account the urgency of the situation as well as prevalence and fatality of the disease.