• 전자공학회논문지A
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• 제28A권10호
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• pp.782-790
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• 1991

In this paper, we implement the function of the IEEE802.2LLC(logical link control) sublayer one of the 7layers in MAP(manufacturing automation protocol), a standard communication protocol for manufacturing automation. With the assembly language we designed the class 3 function based on the IEEE standards and verified on the network adaptor hardware. In this experiment, we tested the function using the simplified variables considering that the retransmission value was chosen to be 1 and the life-time of the transmission variable infinite. According to the result of the service procedures, we confirmed that user data were transmitted to the corresponding station without any error.

• 대한전기학회:학술대회논문집
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• 대한전기학회 1998년도 하계학술대회 논문집 G
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• pp.2189-2192
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• 1998

The objective of this paper is, based upon the principles of artificial life, to induce emergent behaviors of multiple autonomous mobile robots which form from simple local rules to complex global intelligence. Here, we propose an architecture of neural network learing with reinforcement signals which perceives the neighborhood information and decides the direction and the velocity of movement as mobile robots navigates in a group. As results of the simulations, the optimum weights are obtained in real time, which not only prevent from the collisions between agents and obstacles in the dynamic environment, but also have the mobile robots move and keep in various patterns.

• Journal of information and communication convergence engineering
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• 제5권1호
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• pp.7-11
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• 2007

The aim of this paper is to design and implement a new ECG signal monitoring and analysis method for the home care of elderly persons or patients, using wireless sensor network (WSN) technology. The wireless technology for home-care purpose gives new possibilities for monitoring of vital parameter with wearable biomedical sensors and will give the patient freedom to be mobile and still be under continuously monitoring. Developed platform for portable real-time analysis of ECG signals can be used as an advanced diagnosis and alarming system. The ECG features are used to detect life-threatening arrhythmias, with an emphasis on the software for analyzing the P-wave, QRS complex, and T-wave in ECG signals at server after receiving data from base station. Based on abnormal ECG activity, the server transfer diagnostic results and alarm conditions to a doctor's PDA. Doctor can diagnose the patients who have survived from arrhythmia diseases.

• International Journal of Computer Science & Network Security
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• 제21권5호
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• pp.192-198
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• 2021

Trustless, depression, happiness is a normal human emotion that everyone experiences at times. People face problems and hard circumstances every day due to an environment, social life, or traumatic developments in their lives. This study focused on a particular type of inconsistency patterns of behavior that experiences' students during the school time. Some students find depression interferes with their learning and test taking to such an extent that their grades are seriously affected. This study examined the awareness and readiness of a sample of Saudi Arabian high school teachers to recognize, understand, and respond to the ways in which students may respond to testing situations with depression. Findings suggest teachers learn from experience to use both direct and indirect ways to identify students with depression; employ test preparation and test taking strategies to help students reduce depression; and reach out to parents for additional assistance where teacher strategies are not sufficient.

• E2M - 전기 전자와 첨단 소재
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• 제11권11호
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• pp.1-8
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• 1998

This paper presents an arificial neuro-fuzzy technique based prtial discharge (PD) pattern classifier to power system application. This may require a complicated analysis method employ -ing an experts system due to very complex progressing discharge form under exter-nal stress. After referring briefly to the developments of artificical neural network based PD measurements, the paper outlines how the introduction of new emerging technology has resulted in the design of a number of PD diagnostic systems for practical applicaton of residual lifetime prediction. The appropriate PD data base structure and selection of learning data size of PD pattern based on fractal dimentsional and 3-D PD-normalization, extraction of relevant characteristic fea-ture of PD recognition are discussed. Some practical aspects encountered with unknown stress in the neuro-fuzzy techniques based real time PD recognition are also addressed.

• 반도체디스플레이기술학회지
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• 제22권2호
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• pp.77-80
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• 2023

Since fires in uncontrolled environments pose serious risks to society and individuals, many researchers have been investigating technologies for early detection of fires that occur in everyday life. Recently, with the development of deep learning vision technology, research on fire detection models using neural network backbones such as Transformer and Convolution Natural Network has been actively conducted. Vision-based fire detection systems can solve many problems with physical sensor-based fire detection systems. This paper proposes a fire detection method using the latest YOLOv8, which improves the existing fire detection method. The proposed method develops a system that detects sparks and smoke from input images by training the Yolov8 model using a universal fire detection dataset. We also demonstrate the superiority of the proposed method through experiments by comparing it with existing methods.

• 한국산업정보학회논문지
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• 제16권1호
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• pp.31-36
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• 2011

유비쿼터스 네트워크와 더불어 무선 센서 네트워크는 다양한 분야에 응용되고 있다. 무선 센서 네트워크의 노드들은 목표 지역에 비치되어 동작하게 되는데 그 공급원으로 대부분 배터리를 사용하고 있다. 배터리는 센서 네트워크의 응용에 제한된 에너지를 가짐으로써 교체나 충전 등의 어려움을 가진다. 따라서 센서노드의 수명을 연장시키기 위해 주변 환경으로부터의 에너지 하베스팅 기술 등이 연구 개발되고 있다. 특히 태양에너지는 다른 환경 에너지에 비하여 방대하고 짧은 시간에 많은 에너지를 얻을 수 있어 최근 널리 연구되어지고 있다. 본 연구에서는 Solar Cell을 이용하여 배터리 충전 및 센서노드를 구동하는 실험을 하고, 수집된 데이터와 배터리의 전압에 대한 분석을 통하여 센서노드를 구동하기 위해 필요한 배터리 충전시간과 센서노드 농작 가능성에 대하여 확인하였다.

• 가족자원경영과 정책
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• 제9권4호
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• pp.81-93
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• 2005

The purpose of this study were to examine the time use of college students, and then to investigate the relationship between the satisfaction of the time use and the self identity. The subjects were 249 students in college. It was analyzed by using frequency, mean, ANOVA, Duncan's multiple range analysis. The results were as follows: 1. College students were used to employ many obligate time including studying. Their peak time was 10 a.m., 6 p.m. or 10 p.m., and their slump time was from 7 a.m. to 9, or from noon to 2 p.m.. They enjoyed on weekend, and then tired on Monday. 2. College students were satisfied with the future time use than the present. In survey of self-identity inventory, they lacked confidence in their future, but they oriented their goal and were familiar with the social network. 3. The more college students satisfied time use, the more the level of self-identity was high. This, it was suggested the program of time management for college students.

• 전자공학회논문지
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• 제50권12호
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• pp.98-106
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• 2013

에너지 수확 모바일 센서 망에서 센서 노드간의 듀티-사이클 동기화는 매우 중요한 의미를 갖는다. 제한된 에너지를 효율적으로 사용하여 협력해야 하기 때문에 각 노드의 듀티-사이클이 서로 유사하게 동작되어야 한다. 이때 망을 구성하는 노드분포는 노드간의 연결뿐만 아니라 동기화에 의한 노드의 활동 시간, 그리고 망의 수명에 영향을 준다. 본 논문에서는 자기-동기화 듀티-사이클 기법을 적용한 에너지 수확 모바일 센서 망에서 망의 토폴로지를 변화시킨다. 단순 랜덤 토폴로지 망보다는 망이 담당하는 영역과 노드 밀집도에 따라서 노드의 분포를 균일하게 유지하는 알고리즘을 제시한다. 제시된 토폴로지 변환 알고리즘을 위하여 유체 흐름과 군집 분산 모델을 적용하고 에이전트 기반 모델링을 이용하여 성능분석을 시행한다. 또한 제안된 알고리즘을 자기-동기화 듀티-사이클 기반 모바일 센서 망에 적용하여 노드 간 동기화 특성이 강화되고 에너지 소비 편차의 감소를 확인한다.

• 정보과학회 논문지
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• 제42권12호
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• pp.1495-1502
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• 2015

센서 네트워크에서 압축은 종단 간 지연시간과 에너지 사용량 사이의 이율배반적인 관계가 있다. 데이터의 크기를 줄이기 위해 압축을 하면, 추가적인 지연시간과 에너지 소비가 발생하지만, 전송으로 인한 에너지 소모는 감소하게 된다. 일반적으로, 배터리기반 센서 네트워크에서는 지연시간을 손해 보더라도 네트워크의 생존시간을 최대화하기위해 압축을 널리 사용하고 있다. 한편 태양 에너지 기반 센서 네트워크에서는 주기적으로 에너지 재생산이 이루어짐에 따라, 동작하는데 충분한 에너지양 이상의 에너지가 존재할 가능성이 있다. 본 논문에서는 여분의 에너지를 사용해 종단 간 지연시간을 감소시키는 에너지 적응형 선택적 압축 기법을 제안한다. 제안하는 기법은 노드의 에너지가 충분하지 않을 때, 에너지 소비를 줄이기 위해 압축을 사용하고, 에너지가 충분한 경우에는 종단 간 지연시간 감소를 위해 압축을 사용하지 않는다. 시뮬레이션을 통한 에너지와 지연시간의 성능평가를 통하여 제안하는 기법의 우수성을 증명하였다.