• Journal of the Institute of Electronics and Information Engineers
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• v.52 no.10
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• pp.148-158
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• 2015

It is difficult to test a detection system in underwater acoustics channel environments. The system can be evaluated by using simulation analysis tool. In this paper, a simulation tool is proposed to analyze the effectiveness of underwater acoustics detection based on database for real environments. First, the underwater environment is built based on HYCOM underwater environment database. Then, a multipath characteristic is considered through calculating underwater acoustics propagation path/pressure based on the ray theory. Also, hydrophone thermal noise and underwater ambient noise are considered to reflect underwater noise characteristics.

• 한국HCI학회:학술대회논문집
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• 2008.02a
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• pp.384-389
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• 2008

Recently, the necessity of systems which effectively store and retrieve video data has increased. Conventional video retrieval systems retrieve data using menus or text based keywords. Due to the lack of information, many video clips are simultaneously searched, and the user must have a certain level of knowledge to utilize the system. In this paper, we suggest a natural language based conversational video retrieval system that reflects users' intentions and includes more information than keyword based queries. This system can also retrieve from events or people to their movements. First, an event database is constructed based on meta-data which are generated by domain analysis for collected video in an office environment. Then, a script database is also constructed based on the query pre-processing and analysis. From that, a method to retrieve a video through a matching technique between natural language queries and answers is suggested and validated through performance and process evaluation for 10 users The natural language based retrieval system has shown its better efficiency in performance and user satisfaction than the menu based retrieval system.

• The Journal of Information Systems
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• v.18 no.3
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• pp.327-349
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• 2009

Traditional keyword-based searching methods suffer from low accuracy and high complexity due to the rapid growth in the amount of information. Accordingly, many researchers attempt to implement a so-called semantic search which is based on the semantics of the user's query. Semantic information can be described using a semantic modeling language, such as Topic Map. In this paper, we propose a new method to map a topic map to a traditional Relational Database (RDB) without any information loss. Although there have been a few attempts to map topic maps to RDB, they have paid scant attention to handling multi-role topics. In this paper, we propose a new storage structure to map multi-role topics to traditional RDB. The proposed structure consists of a mapping table, role tables, and content tables. Additionally, we devise a query translator to convert a user's query to one appropriate to the proposed structure.

• Proceedings of the Korean Information Science Society Conference
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• 2001.04b
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• pp.157-159
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• 2001

교환기 시스템(switching system)과 같은 통신 시스템 환경에서는 매우 제한적인 시간제약하에서 명시된 이벤트들이 반드시 완료되어야 한다. 따라서, 시스템내에 유지되는 응용데이터에 대해, 매우 빠르고 균일한 접근 시간을 제공하여야 한다. 또한, 최근들어 통신 운용 환경과 교환기 소프트웨어의 복잡성의 증가로 다중테이블 죠인과 객체지향 특성과 같은 고급 기능을 포함한 보다 향상된 데이터 모델링이 요구되고 있다. 이를 위해, 본 논문에서는 1) 통신 응용 환경을 보다 쉽게 모델링하도록 다양한 설계 모델링 개념을 제공하고, 2) 죠인과 같은 연산을 위해 추가의 메모리공간이나 시간을 사용하지 않고, 객체식별자의 항해를 통해 직접 결과를 추출하는 방법에 대해 설명한다.

• Proceedings of the Korea Inteligent Information System Society Conference
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• 2003.05a
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• pp.239-245
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• 2003

15년에 걸쳐 수행된 게놈프로젝트의 완성으로 인류는 본격적으로 프로테옴 시대로 접어들게 되었다. 90년대 중반 이후 전세계적으로 다량의 단백질 구조정보 및 예측을 위한 방법들이 소개되고 있지만 각 자원들마다 저장, 관리 형식이 다를 뿐만아니라 이용하는 방법도 어렵다. 또한 결과적으로 컴퓨터기술을 이용한 단백질의 구조예측작업을 제대로 지원하기 어렵다. 본 논문에서는 개방형다중 에이전트 시스템을 통해 이를 해결하고자 했으며 특히 단백질 자원 데이터베이스를 효과적으로 이용하기 위한 에이전트 설계방법에 대하여 기술하고자 한다. 단백질 구조 예측 지원을 위해 효과적인 에이전트 내부 구조를 설계함으로써 점차로 요구되는 온톨로지 기술이나, 자동 예측 기능과 같은 다양한 요구사항들을 충족시킬 수 있을 것이다.

• Proceedings of the Korea Information Processing Society Conference
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• 2012.11a
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• pp.393-395
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• 2012

다양한 스마트 기기의 출현과 함께 정보보호를 위한 보다 강건한 사용자 인증 시스템에 대한 요구도 증대되고 있다. 하지만 스마트 기기별로 호환성을 유지하면서도 사용자 인증을 수행하기 위해서는 각 기기에서 공통적으로 제공되는 센서의 활용이 필요하며, 영상 기반 다중 생체 인식에 기반을 둔 사용자 인증 시스템은 이에 대한 대안이 될 수 있다. 본 논문에서는 전통적으로 사용자 인증에 사용되고 있는 얼굴 인식과 더불어 영상 기반의 제스처 인식을 함께 사용함으로서 호환성을 유지하면서도 강건한 사용자 인증 시스템을 제안하였다. 그리고 제스처 인식 데이터베이스의 하나인 ChaLearn 데이터에 적용하여 인식 성능을 평가하였다. 그 결과 기존의 스마트 기기에서 가속도계, 자이로스코프 또는 터치 패널에 의한 제스처 인식이 아니라 영상 기반의 제스처 인식을 사용하여 호환성의 확보뿐만 아니라 사용자 인증 성능 또한 개선할 수 있음을 확인하였다.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• 2009.10a
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• pp.62-63
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• 2009

A monitoring system of collision risk among multiple ships is newly-designed in order to reduce human error and make vessel traffic control more effective. By using AIS data as ships' navigational information, an estimation algorithm of collision risk among multiple ships is newly-designed. To consider ships' course of now and future, collision risks of multiple ships can be calculated by using fuzzy algorithm. To test the performance of new algorithm, replay simulations are carried out on actual AIS data collected from VTS center of Ulsan harbor in Korea. The AIS data include 25 ships' information for two hours. In this paper, the features of newly-designed estimation algorithm of collision risk and the results of replay simulation are discussed.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.5 no.1
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• pp.45-51
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• 2012

In this paper, it's a system which recognize the user's emotions after obtaining the biological informations(pulse sensor, blood pressure sensor, blood sugar sensor etc.) about user's bio informations through wireless sensors in accordance of previously collected informations about user's stress index and classification the Colors & Music. This system collects the inputs, saves in the database and finally, classifies emotions according to the stress quotient by using multiple SVM(Support Vector Machine) algorithm. The experiment of multiple SVM algorithm was conducted by using 2,000 data sets. The experiment has approximately 87.7% accuracy.

• Spatial Information Research
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• v.7 no.2
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• pp.271-282
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• 1999

In this paper, we derived an efficient indexing scheme, SJ tree, which handles multi-attribute data and spatial join operations efficiently. In addition, a number of algorithms for manipulating multi-attribute data are given , together with their computational and I/O complexity . Moreover , we how that SJ tree is a kind of generalized B-tree. This means that SJ-tree can be easily implemented on existing built-in B-tree in most storage managers in the sense that the structure of SJ tree is like that of B-tree. The spatial join operation with spatial output is benchmarked using R-tree, B-tree, K-D-B tree, and SJ tree. Results from the benchmark test indicate that SJ tree out performance other indexing schemes on spatial join with point data.

• Journal of the Korea Society of Computer and Information
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• v.27 no.9
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• pp.49-57
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• 2022

Currently, the problem of food shortage is emerging in our society due to climate problems and an increase population in the world. As a solution to this problem, we propose a multi-remote control smart farm that combines artificial intelligence (AI) and information and communication technology (ICT) technologies. The proposed smart farm integrates ICT technology to remotely control and manage crops without restrictions in space and time, and to multi-control the growing environment of crops. In addition, using Arduino and deep-learning technology, a smart farm capable of multiple control through a smart-phone application (APP) was proposed, and Ai technology with various data securing and diagnosis functions while observing crop growth in real-time was included. Various sensors in the smart farm are controlled by using the Arduino, and the data values of the sensors are stored in the built database, so that the user can check the stored data with the APP. For multiple control for multiple crops, each LED, COOLING FAN, and WATER PUMP for two or more growing environments were applied so that the user could control it conveniently. And by implementing an APP that diagnoses the growth stage through the Tensor-Flow framework using deep-learning technology, we developed an application that helps users to easily diagnose the growth status of the current crop.