• 정보처리학회논문지D
• /
• 제11D권4호
• /
• pp.765-774
• /
• 2004

이질의 생물 정보원을 통합하기 위해서는 각 정보원의 이질적인 내용을 숨기고 하나의 관점으로 표현하는 뷰를 정의해야 한다. 본 논문은 생물 정보원 통합 미들웨어를 설계함에 있어서 XML 기반의 뷰 정의모델을 제시하고 그 동작 원리를 보인다. 제시된 모델은 통합시스템 구축을 위한 융통성을 증대시키고, 보다 추상화된 수준에서 통합 질의를 수행할 수 있도록 하기 위하여 사용자 정의 XML 뷰를 지원한다. 제시된 뷰 정의 모델을 기반으로 관계형 데이터베이스와 웹 자원에 대한 랩핑 모델을 제시하고, 아울러 응용 프로그램에 대해서도 같은 모델을 사용한 램핑 결과를 제시한다.

• 한국지능시스템학회:학술대회논문집
• /
• 한국퍼지및지능시스템학회 2003년도 ISIS 2003
• /
• pp.11-15
• /
• 2003

Amount of biological data information has been increasing exponentially. In order to cope with this bio-information explosion, it is necessary to construct a biological data information integration system. The integration system could provide useful services for bio-application developers by answering general complex queries that require accessing information from heterogeneous bio data sources, and easily accommodate a new database into the integrated systems. In this paper, we analyze architectures and mechanisms of existing integration systems with their advantages and disadvantages. Based on this analysis and user requirement studies, we propose an integration system framework that embraces advantages of the existing systems. More specifically, we propose an integration system architecture composed of a mediator and wrappers, which can offer a service interface layer for various other applications as well as independent biologists, thus playing the role of database management system for biology applications. In other words, the system can help abstract the heterogeneous information structures and formats from the application layer. In the system, the wrappers send database-specific queries and report the result to the mediator using XML. The proposed system could facilitate in silico knowledge discovery by allowing combination of numerous discrete biological information databases.

• 한국멀티미디어학회논문지
• /
• 제10권1호
• /
• pp.102-116
• /
• 2007

XML 기반의 미디에이터 시스템은 분산된 이질의 정보원들을 가상적으로 통합하는 방법 중의 하나이다. 이는 각 정보원을 하나의 가상의 XML 데이터베이스로 간주하고 XML 질의어로써 정보원에 접근한다. 본 논문은 사용자가 각 생물 정보원에 대한 XML 뷰를 융통성 있게 정의하고, 또한 정의한 XML 뷰를 기반으로 통합된 XML 질의를 쉽게 생성할 수 있는 사용자 인터페이스에 대한 설계 개념과 개발 결과를 제시한다. 개발된 인터페이스는 통합 스키마에 대하여 XML 뷰나 XML 질의를 손쉽게 생성할 수 있을 뿐 아니라, 하나 이상의 생물 정보원에 대한 질의 결과의 일부를 다른 생물 정보원의 입력 자료로 사용하는 워크플로우 형태의 질의 인터페이스 기능을 제공한다.

• Genomics & Informatics
• /
• 제2권1호
• /
• pp.7-18
• /
• 2004

Integrated genomics refers to the use of large-scale, systematically collected data from various sources to address biological and biomedical problems. A critical ingredient to a successful research program in integrated genomics is the establishment of an effective computational infrastructure. In this review, we suggest that the computational infrastructure challenges include developing tools for heterogeneous data organization and access, innovating techniques for combining the results of different analyses, and establishing a theoretical framework for integrating biological and quantitative models. For each of the three areas - data integration, analyses integration, and model integration - we review some of the current progress and suggest new topics of research. We argue that the primary computational challenges lie in developing sound theoretical foundations for understanding the genome rather than simply the development of algorithms and programs.

• 한국정보과학회논문지:데이타베이스
• /
• 제35권2호
• /
• pp.132-142
• /
• 2008

현재 생물학 분야에는 단백질이라는 동일한 대상에 대해 각기 고유한 의미를 지니고 있는 다양한 형태의 단백질 분석 데이타베이스들이 존재한다. 이렇게 산재되어 있는 이종의 단백질 정보들을 효과적으로 통합한다면 개개의 데이터베이스로부터는 얻을 수 없는 유용한 정보를 도출해낼 수 있다. 생물학 데이타의 특성상 이 각각의 정보들은 자신만의 고유한 형태와 의미를 지니는데, 시맨틱 웹 기술의 표준인 RDF(S) 모델을 이용하여 데이타를 기술하면 형태론적인 통합뿐만 아니라 의미론적인 통합까지 이루어낼 수 있다. 이에 본 논문에서는 RDF 통합 스키마에 기반한 새로운 통합 레이어(layer)를 제안하였다. 이를 위해 개념적 모델 차원으로서는 단백질 정보를 중심으로 통합 스키마를 구축하였고, 표현적 모델 차원으로 서는 래퍼(wrapper)가 해당 데이터베이스들로부터 필요한 정보를 취하여 동적으로 RDF 인스턴스를 구축하는 방법을 제안하였다. 실제로 이 통합 레이어는 연구자들이 필요로 하는 통합 질의 예제를 성공적으로 처리하여 그 결과를 보여줄 수 있음을 확인하였다.

• 한국정보처리학회:학술대회논문집
• /
• 한국정보처리학회 2005년도 춘계학술발표대회
• /
• pp.77-80
• /
• 2005

생물정보원은 이질성이 높고 사용자의 요구사항이 다양하다. 본 논문은 이러한 이질성을 해결하고 사용자의 다양한 요구사항에 쉽게 대처할 수 있는 XML 기반의 생물정보원 통합시스템의 설계개념과 구조 및 구현결과를 제시한다. 제시하는 통합시스템은 관계형테이블, 객체, XML, 플랫파일 등 다양한 자료형을 지원하면서, 관계형, 객체관계형, 웹자원, 응용프로그램 등 데이터 관리모델에 무관한 뷰 정의 및 질의처리모델이다. 그리고 사용자정의 XML 뷰 기반의 뷰 관리 및 질의처리를 통하여 사용자의 다양한 요구사항에 쉽게 적응할 수 있는 미디에이터 질의처리 기반의 생물정보원 통합시스템을 제시한다.

• Asian-Australasian Journal of Animal Sciences
• /
• 제12권3호
• /
• pp.449-459
• /
• 1999

Non-conventional roughage (NCR) is shrub and tree fodders, crop residues and agroindustrial oy-products which is not commonly used as livestock feed traditionally and commercially. Eventhough many sources of NCR is available, the farmers perceptions on NCR not only vary from country to country in tropical and sub-tropical Asian-Australasian countries, but also vary from region to region within the country. Chemical composition and nutritive value of NCR are not only vary from species to species but also vary between species within the genera, between provenances/cultivars within the species and such variations are affected by season, climatic zone, topography and land utilization. The nutritive value of NCR can be improved by physical, chemical and biological treatments and conservation. Feeding NCR to ruminant and non-ruminant is not only improve performance of the livestock but also economically feasible. Future direction of NCR is inventarization, exchange information through NCR information centre, integration with either agrisilvicultural, agrisilvipastoral or silvipastoral system, and use of genetic engineering to produce high quality NCR that ultimately become conventional roughage for agroindustry and agribissiness.

• Genomics & Informatics
• /
• 제4권1호
• /
• pp.40-44
• /
• 2006

Toxicogenomics combines transcriptome, proteome and metabolome profiling with conventional toxicology to investigate the interaction between biological molecules and toxicant or environmental stress in disease caution. Toxicogenomics faces the problems of comparison and integration across different sources of data. Cause of unusual characteristics of toxicogenomic data, researcher should be assisted by data analysis and annotation for getting meaningful information. There are already existing repositories which claim to stand for toxicogenomics database. However, those just contain limited abilities for toxicogenomic research. For supporting toxicologist who comes up against toxicogenomic data flood, now we propose novel toxicogenomics knowledgebase system, XPERANTO-TOX. XPERANTO-TOX is an integrated system for toxicogenomic data management and analysis. It is composed of three distinct but closely connected parts. Firstly, Data Storage System is for reposit many kinds of '-omics' data and conventional toxicology data. Secondly, Data Analysis System consists of analytical modules for integrated toxicogenomics data. At last, Data Annotation System is for giving extensive insight of data to researcher.

• 대한원격탐사학회지
• /
• 제35권1호
• /
• pp.93-115
• /
• 2019

The availability of high-resolution laser scanning data and advanced machine learning algorithms has enabled an accurate potential rockfall source identification. However, the presence of other mass movements, such as landslides within the same region of interest, poses additional challenges to this task. Thus, this research presents a method based on an integration of Gaussian mixture model (GMM) and ensemble artificial neural network (bagging ANN [BANN]) for automatic detection of potential rockfall sources at Kinta Valley area, Malaysia. The GMM was utilised to determine slope angle thresholds of various geomorphological units. Different algorithms(ANN, support vector machine [SVM] and k nearest neighbour [kNN]) were individually tested with various ensemble models (bagging, voting and boosting). Grid search method was adopted to optimise the hyperparameters of the investigated base models. The proposed model achieves excellent results with success and prediction accuracies at 95% and 94%, respectively. In addition, this technique has achieved excellent accuracies (ROC = 95%) over other methods used. Moreover, the proposed model has achieved the optimal prediction accuracies (92%) on the basis of testing data, thereby indicating that the model can be generalised and replicated in different regions, and the proposed method can be applied to various landslide studies.

• Applied Microscopy
• /
• 제50권
• /
• pp.25.1-25.11
• /
• 2020

Scanning acoustic microscopy (SAM) or Acoustic Micro Imaging (AMI) is a powerful, non-destructive technique that can detect hidden defects in elastic and biological samples as well as non-transparent hard materials. By monitoring the internal features of a sample in three-dimensional integration, this technique can efficiently find physical defects such as cracks, voids, and delamination with high sensitivity. In recent years, advanced techniques such as ultrasound impedance microscopy, ultrasound speed microscopy, and scanning acoustic gigahertz microscopy have been developed for applications in industries and in the medical field to provide additional information on the internal stress, viscoelastic, and anisotropic, or nonlinear properties. X-ray, magnetic resonance, and infrared techniques are the other competitive and widely used methods. However, they have their own advantages and limitations owing to their inherent properties such as different light sources and sensors. This paper provides an overview of the principle of SAM and presents a few results to demonstrate the applications of modern acoustic imaging technology. A variety of inspection modes, such as vertical, horizontal, and diagonal cross-sections have been presented by employing the focus pathway and image reconstruction algorithm. Images have been reconstructed from the reflected echoes resulting from the change in the acoustic impedance at the interface of the material layers or defects. The results described in this paper indicate that the novel acoustic technology can expand the scope of SAM as a versatile diagnostic tool requiring less time and having a high efficiency.