http://chineseinput.net/에서 pinyin(병음)방식으로 중국어를 변환할 수 있습니다.
변환된 중국어를 복사하여 사용하시면 됩니다.
- 中文 을 입력하시려면 zhongwen을 입력하시고 space를누르시면됩니다.
- 北京 을 입력하시려면 beijing을 입력하시고 space를 누르시면 됩니다.
RISS 인기검색어
- 검색키워드
- 저자 : Na Cheol-Hun (검색결과 81 건)
- 무료
- 기관 내 무료
- 유료
-
나철훈 木浦大學校 工業技術硏究所 2000 工業技術硏究誌 Vol.10 No.-
In this paper, a improved method of digital image analysis required in basic medical science for diagnosis of cells was proposed. The object image was the Thyroid Gland cell image, and the purpose was automatic discrimination of three classes cells(normal cells, follicular neoplastic cells, and papillary neoplastic cells) by difference of chromatic patterns. Feature parameter was obtained from discrete Fourier transformation of image. After construct a feature sample group of each cells, experiment of discrimination was executed. As a consequency of using features proposed in this paper, get a better recognition rate(70-90%) than previously repoted papers, and this method give shape to get objectivity and fixed quantity in diagnosis of cells.
-
최재익,나철훈 木浦大學校 工業技術硏究所 1997 工業技術硏究誌 Vol.7 No.-
A fuzzy classifier which needs various analyses of features using genetic algorithms is proposed. The fuzzy classifier has a simple structure, which contains a classification part based on fuzzy logic theory and a rule generation part using genetic algorithms. The rule generation part determines optimal fuzzy membership functions and inclusion or exclusion of each feature in fuzzy classification rules. We analyzed recognition rate of a specific object, then added finer features repetitively if necessary to the object which has large misclassification rate. And we introduce repetitive analyses method for the minimum size of strings and population, and for the improvement of recognition rates. This classifier is applied to three examples of the classification of iris data, the discrimination of thyroid gland cancer cells and the recognition of confusing handwritten and printed numerals, each sample numeral is classified into one of the groups which are diveded according to the sample structure. The fuzzy classifier proposed in this paper has recognition rates of 98.67% for iris data, 98.25% for thyroid gland cancer cells and 96.3% for confusing handwritten and printed numerals.
-
MRC 결합의 레이크 수신기에서 채널 추정 알고리즘의 성능분석
오동진,나철훈 국립7개대학공동논문집간행위원회 2005 공업기술연구 Vol.5 No.-
In this paper, we analyze channel estimation algorithms in a RAKE receiver with MRC. There are 3 popular channel estimation algorithms, which are WMSA(Weighted Multi-Slot Averaging) algorithm, EGE(Equal Gain Estimation) algorithm. and SSE(Symbol-to-Symbol Estimation) algorithm. We analyze asynchronous IMT-2000(3GPP) which employ 3 different channel estimation algorithms by using MATLAB. We used jakes fading channel model for the analysis. From simulation results, we could observe that the performance of WMSA algorithm is better than others in low Doppler effect(3km/h). However, in the case of high Doppler effect(120km/h), the EGE algorithm is more efficient. In this case the simple estimator with EGE algorithm seems to be more useful.
-
IEEE 802.11a 무선 LAN 시스템에서 주파수 오프셋 보상 및 채널 보상에 따른 성능 분석
오동진,나철훈 국립7개대학공동논문집간행위원회 2003 공업기술연구 Vol.3 No.-
In this paper, the simulator or WLAN system modem based on IEEE 802.11a is implemented. The performance of WLAN modem in the realistic indoor multipath channel models is analyzed, according to frequency offset compensation and channel estimation methods. The previous works for WLAN(Wireless Local Area Network) system based on OFDM(Orthogonal Frequency Division Multiplexing) is mainly individual study for independent frequency offset or symbol synchronization. For the performance evaluation of the WLAN system, indoor Rayleigh multipath channels are adopted, and the BER(Bit Error Rate) of WLAN system based on 1/2 code-rate QAM is calculated. From the simulation results, 2dB difference of Eb/No exists for on BER of 10-3 between the channel compensation case and ideal channel compensation, and zero frequency offset case.
-
무선통신채널에서 QAM신호의 전송과 채널 특성에 따른 신호점 배치에 관한 연구
柳尙進,崔在翼,羅哲勳 木浦大學校 工業技術硏究所 1998 工業技術硏究誌 Vol.8 No.-
최근 들어 새롭고 복잡해져가는 정보의 대량 전송과 정보 체계의 다양화에 따라 여러 방식의 전송 기법이 개발되고 있다. 그리고 보다 편리한 무선통신의 가입자 수요는 급증하고 있는데, 아날로그 방식보다는 다지틀 방식이 요구되고 스펙트럼 활용효율이 좋은 변조 기법이 또한 바람직하다. 본 연구에서는 활용가능성이 큰 16-ary QAM신호를 선정하여 신호점배치에 따라 여러 QAM신호의 전송신호생성에 관해 고찰하였으며, 가산성 백색 가우시안 잡음(Additive White Gaussian Noise : AWGN)이 더해진 전송채널과 직접파 성분이 없고 반사파들로만 수신신호가 이루어져 있다고 가정할 수 있는 레일리 페이딩(Ratleigh fading)이나 도플러 효과(Doppler effect)가 가미된 이동통신채널을 모델링하고, 이들 채널에서 신호의 왜곡을 보상하는 변.복조 방법을 살펴보았다. 결론적으로 이러한 페이딩 환경하에서 나타나는 시스템의 성능 열화를 최소화하여 좋은 성능을 발휘할 뿐만 아니라 복조단에서 야기되는 위상 모호성(Phase ambiguity)문제를 근본적으로 해결할 수 있는 Differential 방식의 QAM 변.복조 방식을 소개하고, 이동통신과 위성통신 채널에 적용가능한 16-ary QAM 신호의 최적 신호점 배치와 송.수신 방법을 제시하였다.
-
Cancer Cell Recognition by Fuzzy Logic in Medical Images
Na, Cheol-Hun 木浦大學校 工業技術硏究所 1999 工業技術硏究誌 Vol.9 No.-
A new method of digital image analysis technique for medical images of cancer cell was presented. The object image was the Thyroid Gland cell image that was diagnosed as normal and abnormal(two types of abnormal : follicula neoplastic cell, and papillary neoplastic cell), respectively, This paper propose a new discrimination method based on fuzzy logic algorithm. The nucleus were successfully diagnosed as normal and abnormal. The multiple feature parameters were used to extract the features of each nucleus. As a consequence of using fuzzy logic algorithm, proposed in this paper, average recognition rate of 93.08% was obtained.
-
Discrimination of Cancer Cell by Fuzzy Logic in Medical Images
Na Cheol-Hun The Korea Institute of Information and Commucation 2006 Journal of information and communication convergen Vol.4 No.1
A new method of digital image analysis technique for medical images of cancer cell is presented. This paper deals with the cancer cell discrimination. The object images were the Thyroid Gland cell images that were diagnosed as normal and abnormal. This paper proposes a new discrimination method based on fuzzy logic algorithm. The focus of this paper is an automatic discrimination of cells into normal and abnormal of medical images by dominant feature parameters method with fuzzy algorithm. As a consequence of using fuzzy logic algorithm, the nucleus were successfully diagnosed as normal and abnormal. As for the experimental result, average recognition rate of 64.66% was obtained by applying single parameter of 16 feature parameters at a time. The discrimination rate of 93.08% was obtained by proposed method.
-
-
Cancer Cell Recognition by Fuzzy Logic
Na, Cheol-Hun The Korea Institute of Information and Commucation 2011 Journal of information and communication convergen Vol.9 No.4
This paper proposes the new method based on fuzzy logic which recognizes between normal and abnormal. The object image was the Thyroid Gland cell image that was diagnosed as normal and abnormal(two types of abnormal : follicular neoplastic cell, and papillary neoplastic cell), respectively. The nuclei were successfully diagnosed as normal and abnormal. The multiple feature parameters (pre-obtained 16 feature parameters of image data) were used to extract the features of each nucleus. As a consequence of using fuzzy logic algorithm, proposed in this paper, average recognition rate of 98.25% was obtained.
-
연관 검색어 추천
이 검색어로 많이 본 자료
활용도 높은 자료
