• 한국진공학회:학술대회논문집
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• 한국진공학회 2014년도 제46회 동계 정기학술대회 초록집
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• pp.237.1-237.1
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• 2014

Etching is one of the most important steps in semiconductor manufacturing. In etch process control a critical task is to stop the etch process when the layer to be etched has been removed. If the etch process is allowed to continue beyond this time, the material gets over-etched and the lower layer is partially removed. On the other hand if the etch process is stopped too early, part of the layer to be etched still remains, called under-etched. Endpoint detection (EPD) is used to detect the most accurate time to stop the etch process in order to avoid over or under etch. The goal of this research is to develop a hardware and software system for EPD. The hardware consists of an Optical Plasma Monitor (OPM) sensor which is used to continuously monitor the plasma optical emission intensity during the etch process. The OPM software was developed to acquire and analyze the data to perform EPD. Our EPD algorithm is based on the following theory. As the etch process starts the plasma generated in the vacuum is added with the by-products from the etch reactions on the layer being etched. As the endpoint reaches and the layer gets completely removed the plasma constituents change gradually changing the optical intensity of the plasma. Although the change in optical intensity is not apparent, the difference in the plasma constituents when the endpoint has reached leaves a unique signature in the data gathered. Though not detectable in time domain, this signature could be obscured in the frequency spectrum of the data. By filtering and analysis of the changes in the frequency spectrum before and after the endpoint we could extract this signature. In order to do that, first, the EPD algorithm converts the time series signal into frequency domain. Next the noise in the frequency spectrum is removed to look for the useful frequency constituents of the data. Once these useful frequencies have been selected, they are monitored continuously in time and using a sub-algorithm the endpoint is detected when significant changes are observed in those signals. The experiment consisted of three kinds of etch processes; ashing, SiO2 on Si etch and metal on Si etch to develop and evaluate the EPD system.

• 한국소음진동공학회논문집
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• 제19권8호
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• pp.843-849
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• 2009

The reliable operation of a swing check valve in the main feed water system of a power plant is most essential for successful shout-down process. A failure to close the valve at proper time often leads to the instability of the main feed water system, or even to an emergency stop of the power plant. In reality it is a very difficult task to monitor the behavior of a swing check valve. Furthermore it is impossible to see the motion of the valve. In this work two measurements were carried out simultaneously to determine the precise valve closure time. The dynamic pressure measurements were made at the inlet and outlet regions of the swing check valve. The transient vibration of the valve housing in the direction of water flow was also measured, which enabled the measurement of the transient vibration of the valve housing near valve closure. By comparing the results produced from these measurements the precise valve closure time could be determined. By carrying out order tracking technique using the dynamic pressure signals and pump rpm signal, the complicated dynamic problems inside the main feed water system can be more easily dealt with. This measurement scheme might be implemented in a power plant on a real-time basis without much difficulty. If this could be implemented, valuable information essential for shut-down operations can readily be passed on to the main control room. The feasibility of this implementation was demonstrated by this experimental work.

• 한국컴퓨터정보학회논문지
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• 제19권10호
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• pp.55-62
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• 2014

배경과 현재 프레임 영상간의 차영상을 이용하여 이동 물체를 탐지하는 방법은 비디오 감시 시스템에서 가장 보편적인 방법 중 하나이지만 신뢰할 수 있는 배경의 생성은 여전히 쉽지 않은 문제이다. 본 논문에서는 정지 물체를 고려한 적응적 배경 생성 기법을 제안한다. 연속적으로 입력되는 영상들의 산술 평균을 이용하여 초기 배경을 생성한다. 배경과 현재 영상간의 차영상을 구하여 물체를 탐지한 다음, 탐지된 물체가 일정시간이상 계속 정지해 있는 경우에는 그 물체를 정지 물체로 간주하고 정지 물체 영역을 배경으로 갱신한다. 한편, 이동 물체인 경우에는 배경 갱신에서 현재 프레임을 배제함으로써 지속적으로 물체를 탐지할 수 있도록 한다. 제안된 방법은 점진적인 조명의 변화, 느리게 이동하는 물체, 정지 물체 등이 존재하는 동영상에서도 적응적으로 배경을 생성할 수 있으며 이는 실험을 통해 확인되었다.

• 재활복지공학회논문지
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• 제6권1호
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• pp.17-27
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• 2012

본 연구는 장애인 그리고 비장애인이 사용할 수 있는 미래형 전동스쿠터인 자율주행 탑승용 옴니 드라이브 라이더 로봇의 정보을 제공하는데 그 목적이 있다. 그러므로 자율주행 탑승용 옴니 드라이브 로봇 개발을 하기 앞서 49명의 장애인과 고령자의 욕구 조사의 결과를 요약하면 다음과 같다. 첫째, 전동스쿠터의 승하차 불편사항과 밧데리 충전문제 등의 불만족한 이유로 가장 시급히 해결해야 할 문제로 나타났다. 이를 위해 본 연구개발 시 고려되어야할 사항으로 밧데리 충전시간과 거리, 팔 받침대, 발 받침대, 시트각도 등이 요소가 개선되어야 할 것이다. 둘째, 인도, 차도, 경사도, 보도블럭 등과 같은 도로환경에 주행안전에 위험을 느끼고 있으며, 이를 위해 편의기능으로 조이스틱 핸들형, 네비게이션 기능, 장애물 회피기능, 옴니 드라이브 휠, 우천 시 사용할 수 있는 자동 오픈형 덮개 등 본 연구개발과 관련한 여러 요소를 포함하여 장애인과 고령자에 맞는 설계 방안을 제안하였다.

• 한국운동역학회지
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• 제24권3호
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• pp.287-293
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• 2014

The purpose of this study was to investigate the effects of Hoehn-Yahr scale on the activation of lower-extremity muscles during walking. Electromyography (EMG) analysis was carried out on 36 patients with Parkinson's disease in the off phase of the medication cycle. We recorded EMG signals of the tibialis anterior (TA), medial gastrocnemius (MG), lateral gastrocnemius (LG), soleus (SOL), rectus femoris (RF), vastus lateralis (VL), semitendinosus (ST) and biceps femoris (BF) using Noraxon 16 channels EMG system during walking at preferred speed. Rectified EMG signals were normalized to reference voluntary contractions (RVC) over a gait cycle at the preferred speed, allowing for an assessment of how the activity was distributed over the gait cycle. Compared to the H & Y Scale 1, H & Y Scale 3 exhibited greater activation of the vastus lateralis during mid-stance and greater activation of the medial gastrocnemius during terminal swing. Compared to the H & Y Scale 1, H & Y Scale 2 and 3 exhibited less activation of the tibialis anterior during initial swing. We conclude that the more Hoen & Yahr Scale increase, the more abnormal lower-extremity muscles activation.

• 대한간호학회지
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• 제29권1호
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• pp.34-47
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• 1999

This study evaluated the Comparison of the Effectiveness of Pelvic Floor Muscle exercise and Biofeedback treatment for Genuine Stress Incontinence I assigned 60 participants to 2 groups : 30 to the pelvic floor muscle exercise group and 30 to the biofeedback group. Treatment protocol lasted for 6 weeks. Peak pressure, and duration time of pelvic muscle contraction were evaluated by a perineometer. Lower urinary symptoms, sexual matter and life style scores were achieved by using Jackson's scale. The treatment efficacy of the pelvic floor muscle exercise is compared with the biofeedback group and the main results of the comparison are as follows : 1. Pelvic muscle contraction 1) The peak pressure in the biofeedback group was significantly increased(P＝0.000). 2. The frequency and quantity of incontinence 1) The frequency of incontinence in the biofeedback group was significantly decreased(P＝0.000). 2) The quantity of incontinence in the biofeedback group was significantly decreased(P＝0.000). 3. The lower urinary symptoms Daily frequency(P＝0.000), nocturia(P＝0.000), urgency(P＝0.000), bladder pain(P＝0.000), unexplained incontinence(P＝0.048), wearing protection(P＝0.022), changing outer clothing(P＝0.005), hesitancy(P＝0.008), intermittent stream(P＝0.000), abnormal strength of stream(P＝0.004), retention(P＝0.000), incomplete emptying(P＝0.000), and inability to stop mid stream(P＝0.006) of the lower urinary symptoms in the biofeedbatk group were significantly decreased. 4. The sexual matters The dry vagina (P＝0.004) and pain during sexual Intercourse (P＝0.002) in the biofeedback group was significantly decreased. 5. The life style The fluid intake restriction(P＝0.007), affected daily task(P＝0.003), avoidance of places & situation(P＝0.003), interference in Physical activity (P＝0.002), interference in relationship with other people(P＝0.01), and feeling about the rest of life with urinary symptom(P＝0.000) in the biofeedback group were significantly decreased. In conclusion, the biofeedback treatment was more effective than the pelvic floor muscle exercise in genuine stress incontinence.

• 한국정보과학회논문지:정보통신
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• 제33권1호
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• pp.59-75
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• 2006

본 논문에서는 유비쿼터스 컴퓨팅 환경에서 단말들의 이동성에 따른 네트워크의 혼잡 상태를 제어 할 수 있는 적응적인 혼잡 제어 기법을 제안한다. 제안하는 혼잡 제어 기법은 무선망의 특성상 발생할 수 있는 패킷 에러와 혼잡에 의한 패킷 손실을 구분하기 위해서 역 혼잡 회피 단계 및 혼잡 제어 시에 발생하는 비효율적인 대역폭 이용율을 최소화 할 수 있는 슬로우 스톱 단계를 기존의 혼잡 제어 정책에 새롭게 추가한다. 본 논문에서 제안하는 혼잡 제어 정책은 제 3의 전송 계층 프로토콜이라고 불리우는 DCCP(Datagram Congestion Control Protocol)를 기반으로 설계되었고 리눅스 커널 상에서 구현하였다. 제안된 혼잡 제어 정책은 기존의 혼잡 제어 정책보다 적응성 있게 혼잡 상태를 제어하며, 실험 결과 무선에서뿐만 아니라 유선에서도 우수한 대역폭 이용율을 보였다.

• 대한영양사협회학술지
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• 제27권4호
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• pp.232-247
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• 2021

This study attempted to examine the nutrition knowledge of caregivers for the elderly and the diet-related medical treatment and dietary assistance given by them. Thus, this research is a descriptive study focusing on the current nutritional knowledge of caregivers and the dietary assistance given by them. The survey included a questionnaire (nutritional knowledge level of digestive system diseases, diabetes, cardiovascular risk, brain disease, bone disease, and meal assistance performance status) for caregivers working in nursing homes for the elderly. Self-administered questionnaires were completed by 235 caregivers between February and March 2020. The results were analyzed using the SPSS 25.0, and the significance test of each question was verified by the Friedman test and the Chi-square independence test. The number of elderly people who needed meal assistance from caregivers was 4.4 more than the average. The most common types of meal assistance were partial assistance (59.20%) and the task of when to stop eating for the elderly (58.71%). Besides, the higher nutritional knowledge level of the caregivers, the more the time spent on services related to meal assistance (P<0.001), and the higher the meal assistance level. The disease state of the elderly was considered the most relevant (P<0.001). Caregivers with high levels of knowledge and offering significant meal assistance were found to have received nutrition education (P<0.001). Up to 80% of the respondents needed nutrition education, and most of them answered that they needed education on appropriate management methods for the specific disease state of the elderly (P<0.01). Accordingly, providing nutrition education for caregivers for the elderly should be a means to improve their ability to offer meal assistance.

• International Journal of Computer Science & Network Security
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• 제22권5호
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• pp.294-302
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• 2022

Detection of fake news is a complex and a challenging task. Generation of fake news is very hard to stop, only steps to control its circulation may help in minimizing its impacts. Humans tend to believe in misleading false information. Researcher started with social media sites to categorize in terms of real or fake news. False information misleads any individual or an organization that may cause of big failure and any financial loss. Automatic system for detection of false information circulating on social media is an emerging area of research. It is gaining attention of both industry and academia since US presidential elections 2016. Fake news has negative and severe effects on individuals and organizations elongating its hostile effects on the society. Prediction of fake news in timely manner is important. This research focuses on detection of fake news spreaders. In this context, overall, 6 models are developed during this research, trained and tested with dataset of PAN 2020. Four approaches N-gram based; user statistics-based models are trained with different values of hyper parameters. Extensive grid search with cross validation is applied in each machine learning model. In N-gram based models, out of numerous machine learning models this research focused on better results yielding algorithms, assessed by deep reading of state-of-the-art related work in the field. For better accuracy, author aimed at developing models using Random Forest, Logistic Regression, SVM, and XGBoost. All four machine learning algorithms were trained with cross validated grid search hyper parameters. Advantages of this research over previous work is user statistics-based model and then ensemble learning model. Which were designed in a way to help classifying Twitter users as fake news spreader or not with highest reliability. User statistical model used 17 features, on the basis of which it categorized a Twitter user as malicious. New dataset based on predictions of machine learning models was constructed. And then Three techniques of simple mean, logistic regression and random forest in combination with ensemble model is applied. Logistic regression combined in ensemble model gave best training and testing results, achieving an accuracy of 72%.

• 한국도서관정보학회지
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• 제53권4호
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• pp.101-121
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• 2022

본 연구는 국립세종도서관의 현재 서비스인 정책정보포털(POINT)에서 향후 제공할 신정부의 120대 국정과제서비스의 확장 및 개발을 위해 수행되었다. 이를 위해 정부부처 공무원 및 정책 연구원 등을 대상으로 국정과제 희망정보자료와 서비스 요구사항, 제공을 필요로 하는 정보, 역점사항 등에 대한 설문조사와 심층면담을 진행하였다. 설문조사와 심층면담 분석결과를 통해 향후 정책정보포털(POINT)의 국정과제 서비스 지원 시 고려해야 할 방향 등을 제시했다. 분석결과 현 정책정보포털 서비스 이용이 저조한 것으로 나타났으며 정보접근의 개선, 통합검색, 정보제공 자료의 확대등이 더욱 필요한 것으로 조사되었다. 국정과제 서비스 제공 활성화를 위한 방향으로 다양한 정보를 종합적으로 제공하는 원스톱 서비스 구현, 과제별 연관자료의 체계적 정보 제공, 해외 동향 관련 자료, 핵심서비스 제공, 재가공자료 제공, 홍보 활성화, 다양한 정부부처 및 연구기관과의 협력 강화를 통한 자료 연계, 편리한 자료제공 방식, 일반시민들도 쉽게 접근할 수 있는 정보제공 및 메뉴 구성 등이 필요함을 제안하였다.