• Journal of KIISE:Computer Systems and Theory
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• v.33 no.10
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• pp.709-721
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• 2006

The traditional broadcasting services over terrestrial, satellite and cable media have been unidirectional mass media regardless of TV viewer's preferences. Recently ich media streaming has become possible via the broadb and networks. Furthermore, since bidirectional communication is possible, personalcasting such as personalized streaming services has been emerging by taking into account the user's preference on content genres, viewing times and actors/actresses etc. Accordingly, personal media becomes an important means for content provision service in addition to the traditional broadcasting service as mass media. In this paper, we introduce a user profile reasoning method for target advertisement which is considered an important application in personalcasting service. The proposed user profile reasoning method predicts an unknown TV viewer's gender and ages by analyzing TV Viewing history data. Based on the estimated user's gender and ages, a target advertisement is provided with TV Anytime metadata. A proposed target advertisement system is developed based on the user profile reasoning and the target advertisement selection method. To show the effectiveness of our proposed methods, we present a plenty of experimental results by using realistic TV viewing history data.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.17 no.5
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• pp.1083-1088
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• 2013

Detection and classification of undersea mines in shallow waters using active sonar returns is a difficult task due to complexity of underwater environment. Support vector machine(SVM) is a binary classifier that is well known to provide a global optimum solution. In this paper, classification experiments of sonar returns from mine-like objects and non-mine-like objects are carried out using the SVM, and classification performance is analyzed and presented with discussions depending on parameter values of SVM kernel functions.

• Proceedings of the Korea Information Processing Society Conference
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• 2019.10a
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• pp.272-275
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• 2019

랜섬웨어는 더욱 지능화되고 표적화된 공격이 예상되고 클라우드와 사물인터넷 기기의 확산으로 공격의 범위 또한 지속적으로 확대될 것으로 보인다. 특히, 이러한 사물인터넷 기기들은 스마트 시티를 위한 기본 구성요소로 인식되므로 다양한 보안을 위한 연구가 진행되어야 한다. 본 논문에서는 데이터 중심의 스마트 시티를 위한 보안 요구사항 분석을 통해 다양한 스마트 시티 관련 공격을 살펴본다. 또한, 이러한 공격을 보안 서비스에 초점을 맞춰 분류한다. 이렇게 제시된 분류는 다양한 데이터 중심의 스마트 시티를 위한 보안 시스템 구축에 도움이 될 수 있을 것으로 기대한다.

• Defense and Technology
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• no.9 s.295
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• pp.72-79
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• 2003

Northrop Grumman은 코만치의 TASS(Taget Acqusition System Software)를 책임지고 있는데 4가지 주요 기능을 가지고 있다. 즉 열상으로부터 목표물과 같은 물체를 찾는 목표물 감지/분류 지원, 'imager'나 TV FOV에 있는 1개의 주 목표와 5개의 2차 목표를 추적하는 자동 목표 추적기, 탑재 및 미탑재 신호원으로부터 모든 상대적 정보를 상호 연관시키는 목표물 위협 관리기 그리고 레이더 및 열상장비 출력상의 무언가를 비교하는 센서 융합이 바로 그것이다.

• Journal of Korean Library and Information Science Society
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• v.39 no.2
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• pp.493-514
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• 2008

The paper analyzes local children's libraries' status of application of classification scheme and problems and difficulties in its application in order to be used as basic material for development of classification scheme for exclusive use of children's libraries. Through survey, the paper researched 96 local children's libraries, and the results showed that KDC-applied libraries numbered 53 and were the highest, libraries which developed their own classification scheme numbered 22, and libraries which applied classification scheme for children's library numbered 13. Further, many asserted that there needs to be a development of standard classification scheme to be used in children's library. On problems and difficulties in applying classification scheme, notes such as difficulty of accommodating various forms of children's books(such as comic books and picture books), placing too much emphasis on collection of books on certain topic, and lack of topic categories appropriate for characteristics of collected books were voiced, and by holding additional discussion on these, the paper raised the usefulness of the dissertation to be used as basic materials for developing classification scheme for exclusive use of children's library in the future.

• Korean Journal of Remote Sensing
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• v.33 no.6_1
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• pp.1019-1027
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• 2017

As high resolution satellite images can be used, numerous studies have been carried out for exploiting these images in various fields. This paper proposes horse hoof shaped object detection method based on mathematical morphology to extract interesting targets. Interesting targets have conceptually similar shapes such as a horse hoof, not having exact size or shape. Detection of an object with the similar shapes is possible by applying mathematical morphology processes. The proposed method allows an automatic object detection system to detect the meaningful object in a large satellite image rapidly. The mathematical morphology process can be applied to binary images, and thus this method is very simple. Therefore, this method can easily extract a "horse hoof shaped object" from any image that has indistinct edges of the interesting object and different image qualities depending on the filming location, filming time, and filming environment. Using the proposed method by which a "horse hoof shaped object" can be rapidly extracted, the performance of the automatic object detection system can be improved.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.29 no.6
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• pp.1447-1461
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• 2019

Evaluating battle damage after conducting an attack on selected targets during warfare is essential. However, regarding the assessment of battle damage caused by cyber-attacks, some methods available under limited circumstances have been suggested so far. Accordingly, this paper suggests a militarily applicable, comprehensive, and specific method of battle damage assessment from battle damage assessment methods in combat assessment theories from the understanding of cyberspace. By using cyberspace components, this paper classifies cyber targets, suggests the assessment methods of data damage, social cognitive damage, derived damage, and the existing battle damage assessment methods such as physical damage, functional damage, and target systems, and provides an example to demonstrate that this method is applicable to the actual past cyberattack cases.

• Journal of the Korea Institute of Military Science and Technology
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• v.20 no.6
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• pp.758-766
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• 2017

In this paper, we propose a robust duality of CNN(Du-CNN) method which can classify the target and clutter in coastal environment for IR Imaging Sensor. In coastal environment, there are various clutter that have many similarities with real target due to diverse change of air temperature, water temperature, weather and season. Also, real target have various feature due to the same reason. Thus, the proposed Du-CNN method adopts human's multiple personality utilization and CNN technique to learn and classify target and clutter. This method has an advantage of the real time operation. Experimental results on sampled dataset of real infrared target and clutter demonstrate that the proposed method have better success rate to classify the target and clutter than general CNN method.

• Journal of the Korean Institute of Intelligent Systems
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• v.17 no.5
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• pp.668-673
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• 2007

We propose the design of the warfighting experiment process for software intensive systems using the intelligent maturity model and suggest the application results of the target searching capability in smart UAV. For this, we design the intelligent maturity model to evaluate the intelligent degree of the software intensive systems considering the domain and intelligent level. Then we classify the IS0/1EC-12207 process and CMMI process as LITO domain for designing the warfighting experiment process, map the classifed process to the five factors of the warfighting experiment and derive the process as warfighting experiment element and phase. Based on the derived process, we design the warfighting experiment process using the IDEF0. Finally we apply the proposed process to the target search capability and suggest the results which are required to develop and acquire the smart UAV.

• Proceedings of the Korean Society of Computer Information Conference
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• 2022.07a
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• pp.61-62
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• 2022

알츠하이머성 치매는 현존하는 치료법이 없어 경도인지장애 단계에서의 예방이 중요하다. 지금까지의 알츠하이머 연구는 대부분이 뇌영상 마커와 뇌척수액 마커에 집중되어 있었으며, 경도 인지 장애 단계에서의 탐색은 더욱 적었다. 이러한 점에서 혈액 유전자 발현을 이용한 경도 인지장애 단계 예측은 인지 능력에 따른 관련 유전자 식별과 접근 가능한 진단 및 치료 바이오 마커 탐색에 기여할 수 있다. 그러나 유전자 발현 데이터의 경우 환자 수에 비해 높은 차원을 가지기 때문에 과적합을 막고 질병 관련 유전자를 식별하기 위해서는 데이터에서의 의미 있는 차원만을 뽑아내는 차원 축소가 선행되야 한다. 본 연구는 유전자 발현데이터에서의 인지장애 분류를 위해 차원 축소기법과 신경망을 적용하여 인지 장애 정도를 예측하였다. 그 결과, Lasso 이용 차원축소와 신경망을 이용하여 97%의 정확도로 정상과 조기 경도 인지장애, 후기 경도 인지장애 환자를 분류 할 수 있었으며, 더 적은 차원에서도 분류가 가능했다. 이는 혈액 유전자 발현을 이용해 경도 인지장애 단계를 예측한 첫 번째 연구이며, 인지능력 저하에 따른 혈액 유전자 발현의 연관성을 확인하고 향후 조기 진단, 치료 표적 탐색에 기여한다.