• Journal of Preventive Medicine and Public Health
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• 제43권6호
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• pp.472-478
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• 2010

Cancer is a leading cause of death around the world. Education is at the core of cancer prevention activities, especially programs targeting empowering existing public health workforce. In the past 10 years, researchers at the University of Pittsburgh have been building the Global Health Network Supercourse project, a library of over 4500 online lectures and a network of nearly 50000 public health professionals in 174 countries. As of November 2010, the overall number of Supercourse participants from Asia exceeds 7000 participants. The Supercourse network has been investigating methods for Internet based recruitment of cancer prevention professionals in order to network cancer experts locally and globally, including the use of mHealth technologies for cancer research education and for NCD registries. Supercourse is a tool that can offer a solution to the challenges of information sharing, especially in the field of NCDs and cancer. In this paper, we highlight the need for the development of Cancer Supercourse with Satellite in Asia and encourage faculty members from Asia to join the network.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2004년도 학술대회 논문집 전문대학교육위원
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• pp.107-109
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• 2004

본 논문에서는 상명대학교 통신망 구성과 그현황 자료를 수집하여 분석하였고, 통신망 트래픽 측정 분석도구를 이용하여 통신망의 트래픽 흐름과 각 장비들의 동작방식과 성능을 측정하였다. 수강신청 기간에 트래픽 흐름과 부하량에 대해 성능평가를 하였으며, 몇몇의 장비들을 추가/변경하여 트래픽을 분산시키는 방안을 제안하여 효율적인 통신망 설계 방안을 제시하였다.

• 한국산업정보학회:학술대회논문집
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• 한국산업정보학회 2002년도 춘계학술대회 논문집
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• pp.131-135
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• 2002

통신망을 통해서 동영상을 전송하는 기술은 다양한 응용이 가능하다. 하지만, 현재의 인터넷 환경에서는 저속과 대역폭의 큰 변화로 인하여 많은 제약이 따른다. 학교에서 동영상과 음성으로 이루어지는 강의 시스템을 구축함으로써 효율적인 강의로 학습 효과를 증대시키고, 전체 실습실의 활용도를 높일 수 있다. 본 논문은 실시간 전송을 위한 RTP(Real Time Protocol)를 사용하여 캠퍼스내에 강의 시스템을 구축하기 위한 것으로, 멀티캐스트 라우터로 구성된 인터라넷에서 Java와 JMF(Java Multimedia Framework)를 사용하여 개발이 이루어졌다.

• 정보처리학회논문지C
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• 제14C권3호
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• pp.199-208
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• 2007

유비쿼터스 네트워크 환경에서 개인정보의 유출은 다양한 사이버 범죄를 야기하며 개인정보의 상품화로 프라이버시의 침해가 증가하므로 개인정보의 유출을 탐지하는 것은 매우 중요하다. 본 논문은 네트워크의 트래픽 특성을 기반으로 한 개인정보 유출 탐지 기법을 제안하고자 한다. 실제 대학망에서 정상 상태의 트래픽을 수집하여 트래픽의 특성을 분석함으로써 네트워크 트래픽이 자기유사성을 지님을 확인하였다. 개인정보의 유출을 시도하는 악성코드의 사전정보수집단계를 모사한 비정상적인 트래픽에 대하여 정상 트래픽에서의 자기유사성과의 변화를 살펴봄으로써 이상을 조기 감지할 수 있었다.

• 조명전기설비학회논문지
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• 제26권10호
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• pp.89-94
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• 2012

This research is to apply the control of neuron networks for the real-time walking control of Multi-articulated robot. Multi-articulated robot is expressed with a complicated mathematical model on account of the mechanic, electric non-linearity which each articulation of mechanism has, and includes an unstable factor in time of walking control. If such a complex expression is included in control operation, it leads to the disadvantage that operation time is lengthened. Thus, if the rapid change of the load or the disturbance is given, it is difficult to fulfill the control of desired performance. This paper proposes a new mode to implement a neural network controller by installing a real object for controlling and an algorithm for this, which can replace the existing method of implementing a neural network controller by utilizing activation function at the output node. The proposed control algorithm generated control signs corresponding to the non-linearity of Multi-articulated robot, which could generate desired motion in real time.

• 한국항행학회논문지
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• 제21권3호
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• pp.294-299
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• 2017

홈네트워크 서비스는 가정내의 모든 가전기기가 유무선 네트워크로 연결되어 언제 어디서나 원격교육, 홈오토메이션, 원격 검침, 다양한 엔터테인먼트 등의 컨텐츠를 제공 받을 수 있는 서비스로 진화하고 있다. 본 논문에서는 기존의 홈네트워크의 문제점을 해결하고 사용자에게 보다 효율적으로 쾌적한 홈네트워크 환경을 구성 및 유지하기 위한 방안으로, 외부에서 이동통신 단말기로 댁내 설치된 지능형 홈게이트웨이를 접속하게 되고, 이동통신 단말기 디스플레이 창에는 사용자 접근권한을 확인하기 위해 로그인 페이지가 활성화 되며, 사용자는 자신의 로그인 정보를 통해 인증 절차를 진행하게 된다. 정상적인 인증 절차를 수행하면, 지능형 홈게이트웨이는 사용자와의 네트워크 연결만을 유지하는 기능을 하고, 사용자는 지능형 홈네트워크 시스템으로 접근하게 되는 RFID를 이용한 지능형 홈네트워크 시스템을 제시하였다.

• 한국IT서비스학회지
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• 제16권3호
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• pp.167-183
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• 2017

The rapid growth of information technology and mobile service platforms, i.e., internet, google, and facebook, etc. has led the abundance of data. Due to this environment, the world is now facing a revolution in the process that data is searched, collected, stored, and shared. Abundance of data gives us several opportunities to knowledge discovery and data mining techniques. In recent years, data mining methods as a solution to discovery and extraction of available knowledge in database has been more popular in e-commerce service fields such as, in particular, movie recommendation. However, most of the classification approaches for predicting the movie popularity have used only several types of information of the movie such as actor, director, rating score, language and countries etc. In this study, we propose a classification-based support vector machine (SVM) model for predicting the movie popularity based on movie's genre data and social network data. Social network analysis (SNA) is used for improving the classification accuracy. This study builds the movies' network (one mode network) based on initial data which is a two mode network as user-to-movie network. For the proposed method we computed degree centrality, betweenness centrality, closeness centrality, and eigenvector centrality as centrality measures in movie's network. Those four centrality values and movies' genre data were used to classify the movie popularity in this study. The logistic regression, neural network, $na{\ddot{i}}ve$ Bayes classifier, and decision tree as benchmarking models for movie popularity classification were also used for comparison with the performance of our proposed model. To assess the classifier's performance accuracy this study used MovieLens data as an open database. Our empirical results indicate that our proposed model with movie's genre and centrality data has by approximately 0% higher accuracy than other classification models with only movie's genre data. The implications of our results show that our proposed model can be used for improving movie popularity classification accuracy.

• IMMUNE NETWORK
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• 제15권2호
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• pp.91-99
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• 2015

Herpes simplex virus (HSV) is a common causative agent of genital ulceration and can lead to subsequent neurological disease in some cases. Here, using a genital infection model, we tested the efficacy of vinegar-processed flos of Daphne genkwa (vp-genkwa) to modulate vaginal inflammation caused by HSV-1 infection. Our data revealed that treatment with optimal doses of vp-genkwa after, but not before, HSV-1 infection provided enhanced resistance against HSV-1 infection, as corroborated by reduced mortality and clinical signs. Consistent with these results, treatment with vp-genkwa after HSV-1 infection reduced viral replication in the vaginal tract. Furthermore, somewhat intriguingly, treatment of vp-genkwa after HSV-1 infection increased the frequency and absolute number of $CD3^-NK1.1^+NKp46^+$ natural killer (NK) cells producing interferon (IFN)-${\gamma}$ and granyzme B, which indicates that vp-genkwa treatment induces the activation of NK cells. Supportively, secreted IFN-${\gamma}$ was detected at an increased level in vaginal lavages of mice treated with vp-genkwa after HSV-1 infection. These results indicate that enhanced resistance to HSV-1 infection by treatment with vp-genkwa is associated with NK cell activation. Therefore, our data provide a valuable insight into the use of vp-genkwa to control clinical severity in HSV infection through NK cell activation.

• 한국지반신소재학회논문집
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• 제19권1호
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• pp.11-23
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• 2020

본 본문에서는 도심지 지하굴착 및 터널현장의 예비설계 및 지반침하를 예측이 가능한 인공신경망 개발에 대한 내용을 다루었다. 인공신경망의 개발을 위해 먼저 다양한 도심지 터널 및 지하굴착 현장 계측자료를 수집하여 데이터베이스를 구축하고 이를 인공신경망 학습에 필용한 학습데이터를 구축하는데 활용하였다. 개발된 인공신경망은 학습에 활용되지 않은 검증 데이터 세트를 및 현장계측자료를 활용하여 결정계수(R²), 평균제곱근오차(Root Mean Square Error; RMSE), 절대평균오차(Mean Absolute Error; MAE) 등 통계적 파라메타를 근거로 하여 신뢰도를 검증하였다. 개발된 인공신경망은 도심지 굴착현장의 예비 설계 및 이에 따른 주변침하를 예측하는데 효율적으로 활용될 수 있는 것으로 평가되었다.

• 대한간호학회지
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• 제49권5호
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• pp.538-549
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• 2019

Purpose: This study aimed to explore and compare the knowledge structure of pain management nursing research, between Korea and other countries, applying a text network analysis. Methods: 321 Korean and 6,685 international study abstracts of pain management, published from 2004 to 2017, were collected. Keywords and meaningful morphemes from the abstracts were analyzed and refined, and their co-occurrence matrix was generated. Two networks of 140 and 424 keywords, respectively, of domestic and international studies were analyzed using NetMiner 4.3 software for degree centrality, closeness centrality, betweenness centrality, and eigenvector community analysis. Results: In both Korean and international studies, the most important, core-keywords were "pain," "patient," "pain management," "registered nurses," "care," "cancer," "need," "analgesia," "assessment," and "surgery." While some keywords like "education," "knowledge," and "patient-controlled analgesia" found to be important in Korean studies; "treatment," "hospice palliative care," and "children" were critical keywords in international studies. Three common sub-topic groups found in Korean and international studies were "pain and accompanying symptoms," "target groups of pain management," and "RNs' performance of pain management." It is only in recent years (2016~17), that keywords such as "performance," "attitude," "depression," and "sleep" have become more important in Korean studies than, while keywords such as "assessment," "intervention," "analgesia," and "chronic pain" have become important in international studies. Conclusion: It is suggested that Korean pain-management researchers should expand their concerns to children and adolescents, the elderly, patients with chronic pain, patients in diverse healthcare settings, and patients' use of opioid analgesia. Moreover, researchers need to approach pain-management with a quality of life perspective rather than a mere focus on individual symptoms.