• KSII Transactions on Internet and Information Systems (TIIS)
• /
• 제8권7호
• /
• pp.2261-2280
• /
• 2014

Recently, network traffic has become more complex and diverse due to the emergence of new applications and services. Therefore, the importance of application-level traffic classification is increasing rapidly, and it has become a very popular research area. Although a lot of methods for traffic classification have been introduced in literature, they have some limitations to achieve an acceptable level of performance in real-time application-level traffic classification. In this paper, we propose a novel application-level traffic classification method using payload size sequence (PSS) signature. The proposed method generates unique PSS signatures for each application using packet order, direction and payload size of the first N packets in a flow, and uses them to classify application traffic. The evaluation shows that this method can classify application traffic easily and quickly with high accuracy rates, over 99.97%. Furthermore, the method can also classify application traffic that uses the same application protocol or is encrypted.

• 방사선산업학회지
• /
• 제8권3호
• /
• pp.155-159
• /
• 2014

RI-Biomics is a new concept that combines radioisotopes (RI) and Biomics. For efficient collection of information, establishment of database for technical information system and its application to the system, there is an increasing need for constructing the standard classification system of technical information by its systematical classification. In this paper, we have summarized the development process of the standard classification system of technical information in the field of RI-Biomics and its application to the system. Constructing the draft version for the standard classification system of technical information was based on that standard classification one in national science and technology in Korea. The final classification system was then derived through the reconstruction and the feedback process based on the consultation from the 7 experts. These results were applied to the database of technical information system after transforming as standard code. Thus, the standard classification system were composed of 5 large classifications and 20 small classifications, and those classification are expected to establish the foundation of information system by achieving the circular structure of collection-analysis-application of information.

• 방사선산업학회지
• /
• 제9권1호
• /
• pp.29-35
• /
• 2015

Radiation technology is the one for developing new products or processes by applying radiation or for creating new functions in industry, research and medical fields, and its application is increasing consistently. For securing an advanced technology competitiveness, it is required to create a new added value by information consumer through providing an efficient system for supporting information, which is the infrastructure for research and development, contributed to its collection, analysis and use with a rapidity and structure in addition to some direct research and development. Provision of the management structure for information resources is especially crucial for efficient operating the system for supporting information in radiation technology, and then a standard classification structure of information must be first developed as the system for supporting information will be constructed. The standard classification structure has been analyzed by reviewing the definition of information resources in radiation technology, and those classification structures in similar systems operated by institute in radiation and other scientific fields. And, a draft version of the standard classification structure has been then provided as 7 large, 25 medium and 71 small classifications, respectively. The standard classification structure in radiation technology will be developed in 2015 through reviewing this draft version and experts' opinion. Finally, developed classification structure will be applied to the system for supporting information by considering the plan for constructing this system and database, and requirements for designing the system. Furthermore, this structure will be designed in the system for searching information by working to the individual need of information consumers.

• 대한한의학원전학회지
• /
• 제36권3호
• /
• pp.89-128
• /
• 2023

Objectives : This study aims to diachronically examine the classification systems of all materia medica, followed by categorization and analysis of each category to deduce each category's characteristic. This will provide foundation for further examining classifications of bencao in contemporary herbology. Methods : Classification systems from a total of 93 bencao related texts were collected and categorized. Each category's classification system was analyzed to determine its meaning. The classification systems were compared from a diachronic perspective, to further deduce each system's problem from a historical context. Results : The classification systems of materia medica could be summarized as following three standards: quality, origin, and medical application. In reality, bencao could be generally classified according to origin and medical application. The origin-based classification system provided a stable and flexible classification outline in the expansion process of bencao. The medical application-based classification strengthened the relationship between bencao and illness pattern, improving clinical applicability. Conclusions : In the history of herbology, the two classification systems created the current of herbology through mutual contribution and conflict. We hope that further discussion on the direction towards which classification system of bencao in contemporary herbology should head will proceed based on this study.

• 한국문헌정보학회지
• /
• 제50권2호
• /
• pp.101-118
• /
• 2016

문헌분류체계에서 복합주제의 전개를 위해서는 복수의 구분기준 혹은 특성(characteristics)을 적용해야 한다. 복합주제의 세분전개를 위해 채택된 복수의 특성들은 세분의 매 단계에서 하나씩 순차적으로 전개된다. 복합주제를 세분 전개하는 과정에서 복수의 구분기준을 적용하는 순서를 인용순(citation order)이라 한다. 주제를 세분하는 과정에 적용되는 구분기준의 전개순서인 인용순이 구체적이고 일관성을 가져야 문헌분류체계의 일관성과 논리성을 확보할 수 있다. 특히 열거식 분류체계의 경우에는 복합주제의 표현을 위한 인용순의 결정이 분류체계의 구성과 체계성에 큰 영향을 미친다. 인용순 및 그 적용과 관련된 분류이론상의 기본 원칙들은 실제 분류체계 구축과정에서 실용적인 이유로 완벽히 적용되기 어렵다. 이에 본고는 분류체계의 구축과정에서 적용되고 있는 인용순 관련 분류이론과 선행연구를 개괄해보고, 인용순 실제 적용상의 제반 사항을 고찰하였다.

• 한국통신학회논문지
• /
• 제36권8B호
• /
• pp.921-928
• /
• 2011

최근 인터넷 사용자의 증가와 다양한 인터넷 기반 응용프로그램의 증가로 네트워크 트래픽이 급증하고 있다. 효율적인 네트워크 트래픽 관리를 위해 기존의 많은 연구들 에서 다양한 분류 알고리즘을 제시하였고, 대부분의 제안된 방법들은 응용 단위로 트래픽을 분류하며 분류의 정확성을 높이는데 초점을 두고 있다. 하지만 트래픽 제어의 관점에서 보았을 때 응용단위의 트래픽 분류는 응용의 기능별 제어의 기회를 제공하지 못하고 네트워크 사용자가 각 응용의 어떤 기능을 사용하는지를 파악하지 못하게 되는 문제점을 가지고 있다 본 논문에서는 이러한 문제점들을 해결 하기 위해 NateOn, MSN, GoogleTalk의 인터넷 메신저 응용에 대하여 기능 오토마타를 설계하고 이를 통해 메신저 응용의 기능별 트래픽 분류를 위한 방법론을 제시한다.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• 제4권5호
• /
• pp.859-876
• /
• 2010

In this paper, we propose a hierarchical application traffic classification system as an alternative means to overcome the limitations of the port number and payload based methodologies, which are traditionally considered traffic classification methods. The proposed system is a new classification model that hierarchically combines a binary classifier SVM and Support Vector Data Descriptions (SVDDs). The proposed system selects an optimal attribute subset from the bi-directional traffic flows generated by our traffic analysis system (KU-MON) that enables real-time collection and analysis of campus traffic. The system is composed of three layers: The first layer is a binary classifier SVM that performs rapid classification between P2P and non-P2P traffic. The second layer classifies P2P traffic into file-sharing, messenger and TV, based on three SVDDs. The third layer performs specialized classification of all individual application traffic types. Since the proposed system enables both coarse- and fine-grained classification, it can guarantee efficient resource management, such as a stable network environment, seamless bandwidth guarantee and appropriate QoS. Moreover, even when a new application emerges, it can be easily adapted for incremental updating and scaling. Only additional training for the new part of the application traffic is needed instead of retraining the entire system. The performance of the proposed system is validated via experiments which confirm that its recall and precision measures are satisfactory.

• 한국문헌정보학회지
• /
• 제48권4호
• /
• pp.5-23
• /
• 2014

This study reports the first step in the Classification-based Search and Knowledge Discovery (CSKD) project, which aims to combine information organization and retrieval approaches for building digital library applications. In this study, we explored the generation and application of a faceted vocabulary as a potential mechanism to enhance knowledge discovery. The faceted vocabulary construction process revealed some heuristics that can be refined in follow-up studies to further automate the creation of faceted classification structure, while our concept search application demonstrated the utility and potential of integrating classification-based approach with retrieval-based approach. Integration of text- and classification-based methods as outlined in this paper combines the strengths of two vastly different approaches to information discovery by constructing and utilizing a flexible information organization scheme from an existing classification structure.

• 한국멀티미디어학회논문지
• /
• 제21권10호
• /
• pp.1150-1161
• /
• 2018

Classification is widely used in medical images to categorize patients and non-patients. However, conventional classification requires a complex procedure, including some rigid steps such as pre-processing, segmentation, feature extraction, detection, and classification. In this paper, we propose a novel convolutional neural network (CNN), called LeukemiaNet, to specifically classify two different types of leukemia, including acute lymphoblastic leukemia (ALL) and acute myeloid leukemia (AML), and non-cancerous patients. To extend the limited dataset, a PCA color augmentation process is utilized before images are input into the LeukemiaNet. This augmentation method enhances the accuracy of our proposed CNN architecture from 96.9% to 97.2% for distinguishing ALL, AML, and normal cell images.

• 한국통신학회논문지
• /
• 제34권11B호
• /
• pp.1234-1244
• /
• 2009

오늘날의 네트워크에서는 다양한 응용의 등장으로 인해 트래픽이 복잡 다양해지고 있다. 이러한 상황 속에서 트래픽의 응용 별 분류에 대한 중요성은 날이 갈수록 증가하고 있다. 트래픽의 응용 별 분류에 대한 요구에 따라 기존에도 많은 연구가 이루어졌었다. 포트 기반의 분류, 페이로드 기반의 분류, 머신러닝 기반의 분류 방법들이 제안되었는데 아직 트래픽을 완벽하게 분류해내는 방법론은 개발되지 않은 실정이다. 최근 연구 중에는 플로우의 통계 정보를 이용한 방법론이 많이 연구되고 있다. 본 논문에서는 통계 시그니쳐를 통한 응용 트래픽 분류 방법론을 제안하고자 한다. 플로우 중 첫 N개의 패킷의 페이로드 크기와 방향을 이용하여 통계 시그니쳐를 생성하고, 이를 이용하여 응용 트래픽을 분류한다. 그리고 검증 시스템을 통해 본 분류 방법론이 높은 정확도의 분류 방법론이라는 것을 보인다.