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송인찬,곽철은,민병구,Song, In-Chan,Kwack, Cheol-Eun,Min, Byoung-Goo 대한의용생체공학회 1990 의공학회지 Vol.11 No.2
As a part of the study on ultrasonic tissue characterization, conventional ultrasonic imaging system is interfaced to the personal computer to acquire raw ultrasonic signal. One approach for tissue charaterization is performed using the attenuation map to the conventional images and the resulting attenuation map images are compared and inspected inside the region of interest from the viewpoint of pattern analysis. Currently, these methods are applied and modified to effectively find out the differences between the normal control and the patients with liver cirrhosis.
범효,송인찬,장경희,신동범,이형섭,Fan, Xiao,Song, In-Chan,Chang, Kyung-Hi,Shin, Dong-Beom,Lee, Heyung-Sub The Korea Institute of Information and Commucation 2008 韓國通信學會論文誌 Vol.33 No.8A
Both EPCglobal Generation-2 (Gen2) for passive RFID systems and Intelleflex for semi-passive RFID systems use probabilistic slotted ALOHA with Q algorithm, which is a kind of dynamic framed slotted ALOHA (DFSA), as the tag anti-collision algorithm. A better tag anti-collision algorithm can reduce collisions so as to increase the efficiency of tag identification. In this paper, we introduce and analyze the estimation methods of the number of slots and tags for DFSA. To increase the efficiency of tag identification, we propose two new tag anti-collision algorithms, which are Chebyshev's inequality (CHI) algorithm and hybrid Q algorithm, and compare them with the conventional Q algorithm and adaptive adjustable framed Q (AAFQ) algorithm, which is mentioned in Part I. The simulation results show that AAFQ performs the best in Gen2 scenario. However, in Intelleflex scenario the proposed hybrid Q algorithm is the best. That is, hybrid Q provides the minimum identification time, shows the more consistent collision ratio, and maximizes throughput and system efficiency in Intelleflex scenario.
Auditory language task를 이용한 자기공명영상에 관한 고찰 : Visual language task와의 비교
구은회,김인수,정헌정,유병기,김동성,최천규,송인찬,Goo Eun Hoe,Kim In Soo,Jeong Heon Jeong,You Byung Ki,Kim Dong Sung,Choi Cheon Kyu,Song In Chan 대한방사선사협회 2002 대한방사선사협회지 Vol.28 No.1
Purpose: To make a comparison evaluated of the auditory instrument and visual instrument language generation task in the fMRI, on the adult volunteers. Materials and Methods: Total of 6 normal adult volunteers(men;4, women;2, mean age;24) performed in 1.5
ISO/IEC 18000-7 433MHz 능동형 RFID 시스템 기반의 인식거리 향상을 위한 멀티홉 릴레이 시스템
홍성현,송인찬,장홍,장경희,신동범,이형섭,Hong, Sung-Hyun,Song, In-Chan,Zhang, Hong,Chang, Kyung-Hi,Shin, Dong-Beom,Lee, Heyung-Sub 한국통신학회 2009 韓國通信學會論文誌 Vol.34 No.5
In this paper, we analyze the active RFID systems ISO/IEC 18000-7 and ISO/IEC 18000-4. In order to improve the coverage in sensor networks, which consist active RFID tag, we propose RFID multi-hop relay system using active RFID relay tag. To compare the performance between the existing ISO/IEC 18000-7 system and the proposed RFID multi-hop relay system, we introduce new system efficiency measure and sensitivity-based measure of achieved coverage. Also, we analyze the performance of the proposed system and compare it with that of the existing system through MCL (Minimum Coupling Loss) analysis and SLS (System Level Simulation) analysis. 본 논문에서는 능동형 RFID 시스템인 ISO/IEC 18000-7 및 ISO/IEC 18000-4 시스템에 대하여 살펴보고, 능동형 RFID 태그로 구성된 센서 네트워크에서 인식거리 향상을 위해 능동형 RFID 릴레이 태그를 사용하는 RFID 멀티홉 릴레이 시스템을 제안한다. 기존 ISO/IEC 18000-7 시스템과 제안된 RFID 멀티홉 릴레이 시스템의 성능평가를 위하여 Sensitivity에 의한 인식거리 및 시스템 효율과 같은 항목을 새롭게 정의하며, MCL (Minimum Coupling Loss) 분석과 SLS(System Level Simulation) 분석을 통해 제안된 시스템의 성능을 비교 및 분석한다.
Snake 모델에서의 개선된 Gradient Vector Flow: 캡쳐 영역의 확장과 요면으로의 빠른 진행
조익환(Ik-Hwan Cho),송인찬(In-Chan Song),오정수(Jung-Su Oh),엄경식(Kyong-Sik Om),김종효(Jong-Hyo Kim),정동석(Dong-Seok Jeong) 한국정보과학회 2006 정보과학회논문지 : 소프트웨어 및 응용 Vol.33 No.1
Gradient vector flow(GVF) snake 또는 active contour 모델은 영상 분할에서 훌륭한 성능을 보여준다. 그러나 기존의 snake 모델에는 제한된 캡쳐 영역과 요면으로의 느린 진행과 같은 문제점들이 존재한다. 본 논문은 주변의 필드로부터 외부장(external force field)을 확장시키고 변형된 평탄화기법을 이용하여 확장된 필드를 정규화 함으로서 GVF snake 모델의 성능을 개선시키는 새로운 방법을 제시한다. 시뮬레이션을 위해 사용된 U자 모양 이미지에서의 결과는 제안된 방법이 좀 더 큰 캡쳐 영역을 갖고 기존의 GVF snake 모델에 비하여 요면으로 빠르게 진행하는 것이 가능함을 보여준다. The Gradient Vector Flow (GVF) snake or active contour model offers the best performance for image segmentation. However, there are problems in classical snake models such as the limited capture range and the slow progress into concavity. This paper presents a new method for enhancing the performance of the GVF snake model by extending the external force fields from the neighboring fields and using a modified smoothing method to regularize them. The results on a simulated U-shaped image showed that the proposed method has larger capture range and makes it possible for the contour to progress into concavity more quickly compared with the conventional GVF snake model.