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Helicobacter pylori와 대장균의 Shuttle Vector 개발
조명제,이우곤,이상룡,김경희,안영숙,김성희,김현주,류복덕,최여정,윤영혜,백승철,전영석,이광호 경상대학교 유전공학연구소 1997 遺傳工學硏究所報 Vol.16 No.-
In this study, a vehicle vector using cryptic plasmids was constructed for gene transfer in Helicobacter pylori. pHP51(3.9 kb) and pHP489(1.2 kb) were selected for constructing vectors from cryptic plasmid of H. pylori isolates in Korea. The HindⅢ-digestedDNA fragment(1.2kb) of pHP489 and 1.6kb DNA fragment of pHP51 were ligated with a kanamycin resistance gene(aph3'-Ⅲ) from C. jejuni to produce the recombinant plasmids pHP489K and pHP51K, respectively. Transformation frequency of pHP51K by electroporation was low. But pHP489K could be effectively transformed into various H. pylori strains. In order to design an intermdiate vehicle vector for gene transfer into H. pylori, pBlueHP489K was prepared by recloning pHP489K DNA into pBluescript and pTZ19R vector. This vector permitted the DNA fragment containing pHP489 sequence, aph3'-Ⅲ, and cloned DNA to be cut and self-ligated in the SacⅠ site after cloning. ureA and ureB gene were inserted into pBlueHP489K, resulting in pBlueHP489K/AB. The DNA fragment containing pHP489, kanamycin resistance gene(aph3'-Ⅲ), and urease structural gene was cut away from pBlueHP489K/AB and self-ligated to generate pBlueHP489K/AB. pBlueHP489K/AB made urease-negative H. pylori strains restore their urease activity. By this experiment, pBlueHP489K was confirmed to be the vehicle system for transferring H. pylori genes.
An Energy-Efficient Distributed Clustering Approach in Wireless Sensor Networks
YEO, Myung Ho,KIM, Yu Mi,YOO, Jae Soo The Institute of Electronics, Information and Comm 2009 IEICE TRANSACTIONS ON COMMUNICATIONS - Vol.92 No.2
<P>Clustering the sensor nodes is one of the most popular and effective approaches for applications that must support hundreds or thousands of nodes. The conventional algorithms consider various parameters to evenly distribute the energy load. However, energy consumption problem of the cluster head still remains. In this paper, we propose a novel clustering approach that periodically elects cluster heads with assistant nodes. The assistant nodes substitute for each cluster head to transmit sensor readings to the base station. Performance evaluations show that our proposed clustering algorithm achieves about 10-40% better performance than the existing clustering algorithms in terms of lifetime.</P>
The Optimization of In-Memory Space Partitioning Trees for Cache Utilization
YEO, Myung Ho,MIN, Young Soo,BOK, Kyoung Soo,YOO, Jae Soo The Institute of Electronics, Information and Comm 2008 IEICE transactions on information and systems Vol.91 No.2
<P>In this paper, a novel cache conscious indexing technique based on space partitioning trees is proposed. Many researchers investigated efficient cache conscious indexing techniques which improve retrieval performance of in-memory database management system recently. However, most studies considered data partitioning and targeted fast information retrieval. Existing data partitioning-based index structures significantly degrade performance due to the redundant accesses of overlapped spaces. Specially, R-tree-based index structures suffer from the propagation of MBR (Minimum Bounding Rectangle) information by updating data frequently. In this paper, we propose an in-memory space partitioning index structure for optimal cache utilization. The proposed index structure is compared with the existing index structures in terms of update performance, insertion performance and cache-utilization rate in a variety of environments. The results demonstrate that the proposed index structure offers better performance than existing index structures.</P>
Design and Implementation of a Directory System for Disease Services
Yeo, Myung-Ho,Lee, Yoon-Kyeong,Roh, Kyu-Jong,Park, Hyeong-Soon,Kim, Hak-Sin,Park, Jun-Ho,Kang, Tae-Ho,Kim, Hak-Yong,Yoo, Jae-Soo The Korea Contents Association 2010 International Journal of Contents Vol.6 No.1
Recently, biological researches are required to deal with a large scale of data. While scientists used classical experimental approaches for researches in the past, it is possible to get more sophisticated observations easily with the convergence of information technologies and biology. The study on diseases is one of the most important issues of the life science. Conventional services and databases provide users with information such as classification of diseases, symptoms, and medical treatments through the Web. However, it is hard to connect or develop them for other new services because they have independent and different criteria. It may be a factor that interferes the development of biology. In this paper, we propose integrated data structures for the disease databases. We also design and implement a novel directory system for diseases as an infrastructure for developing the new diseases services.
Server-Based User-Created Contents Processing System
Yeo, Myung-Ho,Kim, Hak-Sin,Roh, Kyu-Jong,Cho, Yong-Jun,He, Li,Kim, Hak-Cheol,Bok, Kyung-Soo,Yoo, Jae-Soo The Korea Contents Association 2008 International Journal of Contents Vol.4 No.4
The web 2.0 is leading a rapid change of internet services. The UCC(User Created Contents) service is one of the representative internet services with web 2.0 paradigm. In this paper, we design and implement the UCC services prototype system for image and video. The proposed system does not need to install ActiveX and client programs on devices of users to edit their contents. All processes for editing UCC are conducted on the server. Our proposed system consists of the two components such as the multimedia editing subsystem and the metadata management system. They provide the API to UCC service developers or vendors. The multimedia editing subsystem supports editing for image and video, and the streaming services of video. The metadata management subsystem supports the metadata management and retrieval of image and video.
Design and Implementation of a Directory System for Disease Retrieval Services
Myung-ho Yeo,Yoon-kyeong Lee,Kyu-jong Roh,Hyoung-soon Park,Hak-sin Kim,Jun-ho Park,Tae-ho Kang,Chi-kwan Song,Chang-yong Yang,Hak-yong Kim,Jae-soo Yoo 한국콘텐츠학회 2009 ICCC International Digital Design Invitation Exhib Vol.2009 No.12
Recently, biological researches are required to deal with a large scale of data. While scientists used classical experimental approaches for researches in the past, it is possible to get more sophisticated observations easily with convergence of information technologies and biology. The study on diseases is one of the most important issues of the life science. Conventional services and databases provide users with information such as classification of diseases, symptoms, and medical treatments through the Web.. However, it is hard to connect or develop them for other new services because they have independent and different criteria. It may be a factor that interferes the development of biology. In this paper, we propose an integrated data structure for the disease databases. We also design and implement a novel directory system for diseases as an infrastructure for developing the new diseases services.
데이터 중심 저장구조에 기반한 스카이라인 질의 처리 기법
여명호(Myung-Ho Yeo),성동욱(Dong-Ook Seong),송석일(Seok-Il Song),유재수(Jae-Soo Yoo) 한국콘텐츠학회 2009 한국콘텐츠학회 종합학술대회 논문집 Vol.7 No.1
센서 네트워크를 위한 데이터 중심 저장구조는 다차원의 범위질의는 물론 정합질의를 효과적으로 처리하기 위해서 제안되었다. 하나의 센서 네트워크는 범위질의 하나만 처리하거나 스카이라인 질의 하나만을 처리하기 위해서 설치될 수도 있지만 일반적으로 다양한 질의를 같이 처리하기 위해서 사용된다. 따라서, 데이터 중심 저장구조에서 다차원의 범위질의 뿐만 아니라 스카이라인 질의도 효과적으로 처리될 필요가 있다. 기존에 제안된 스카이라인질의 처리 알고리즘들은 데이터 중심 저장구조의 존재를 고려하지 않고 있다. 일부 대표적인 데이터 중심 저장구조는 유사한 데이터를 지리적으로 인접한 센서노드에 저장하는 특징을 갖는다. 이 논문에서는 이러한 특징을 고려하여 데이터 중심 저장구조에서 보다 효과적으로 동작할 수 있는 스카이라인 질의 처리기법을 제안한다. Data centric storages for sensor networks have been proposed to efficiently process multi-dimensional range queries as well as exact matches. Usually, a sensor network does not process only one type of the query but supports various types of queries such as range queries, exact matches and skyline queries. Therefore, a sensor network based on a data centric storage for range queries and exact matches should process skyline queries efficiently. However, existing algorithms for skyline queries have not considered the features of data centric storages. Some of the data centric storages store similar data in sensor nodes that are placed on geographically similar locations. Consequently, all data are ordered in a sensor network. In this paper, we propose a new skyline query processing algorithm that exploits the above features of data centric storages.
무선 센서 네트워크를 위한 에너지 효율적인 이중 레이어 분산 클러스터링 기법
여명호(Myung Ho Yeo),김유미(Yu Mi Kim),유재수(Jae Soo Yoo) 한국정보과학회 2008 정보과학회논문지 : 데이타베이스 Vol.35 No.1
최근 무선 센서 네트워크는 다양한 응용분야의 플랫폼으로써 사용되고 있다. 무선 센서를 배치하고, 센서 네트워크를 구성함으로써 원격으로 어떤 영역에 포함된 객체들의 동작, 상태, 위치 등에 관한 정보를 얻을 수 있다. 일반적으로 센서 노드들은 제한된 배터리로 동작하기 때문에 센서 네트워크의 생명주기를 연장시키기 위한 에너지 효율적인 데이타 수집 메커니즘은 필수 조건이다. 본 논문에서는 클러스터 헤드의 에너지 소모를 분산할 수 있는 새로운 클러스터링 기법을 제안한다. 먼저 클러스터 헤드의 역할에 따른 에너지 소모를 분석하고, 클러스터를 수집과 전송을 위한 두 계층으로 분리한다. 그 다음 각 계층을 담당하는 센서 노드를 선출하여 단일 클러스터 헤드의 에너지 소모를 2개의 센서 노드로 분산한다. 제안하는 클러스터링 기법의 우수성을 보이기 위해 시뮬레이션을 통해 기존의 클러스터링 기법과 성능을 비교했다. 그 결과, 기존의 알고리즘에 비해 생명 주기(lifetime)가 10%~40% 향상되는 것을 확인할 수 있었다. Wireless sensor networks have recently emerged as a platform for several applications. By deploying wireless sensor nodes and constructing a sensor network, we can remotely obtain information about the behavior, conditions, and positions of objects in a region. Since sensor nodes operate on batteries, energy-efficient mechanisms for gathering sensor data are indispensable to prolong the lifetime of a sensor network as long as possible. In this paper, we propose a novel clustering algorithm that distirubtes the energy consumption of a cluster head. First, we analyze the energy consumption of cluster heads and divide each cluster into a collection layer and a transmission layer according to their roles. Then, we elect a cluster head for each layer to distribute the energy consumption of single cluster head. In order to show the superiority of our clustering algorithm, we compare it with the existing clustering algorithm in terms of the lifetime of the sensor network. As a result, our experimental results show that the proposed clustering algorithm achieves about 10%~40% performance improvements over the existing clustering algorithms.