• Journal of Korea Multimedia Society
• /
• v.12 no.9
• /
• pp.1288-1296
• /
• 2009

This paper is for multi-frequency thin film loop antenna used on smart phone, PMP and PDA like as a multi-media devices. We developed a loop pattern folding methods to reduce a thin film antenna dimension using that mutual coupling folding loop occurs the higher frequency resonation. To reduce the thin film size for loop antenna, we fold the loop pattern repeatedly control the coupling coefficient than generate a not only higher mode resonation but also basic resonation from loop pattern. To realization the thin film folded loop antenna, we used a $30mm{\times}9mm$ PI film the thickness is 20um so that we realize the CDMA850, GPS, DCS, PCS, WCDMA antenna simultaneously and it's radiation efficiency is over 50% and gain is 0dBi.

• KIISE Transactions on Computing Practices
• /
• v.23 no.2
• /
• pp.104-109
• /
• 2017

We propose a new machine learning algorithm which analyzes daily activity patterns of users from multi-modal wearable sensor data. The proposed model learns and extracts activity patterns using input from wearable devices in real-time. Inspired by cue integration of human's property, we constructed gated multi-modal neural networks which integrate wearable sensor input data selectively by using gate modules. For the experiments, sensory data were collected by using multiple wearable devices in restaurant situations. As an experimental result, we first show that the proposed model performs well in terms of prediction accuracy. Then, the possibility to construct a knowledge schema automatically by analyzing the activation patterns in the middle layer of our proposed model is explained.

• Proceedings of the Acoustical Society of Korea Conference
• /
• 1998.06c
• /
• pp.99-102
• /
• 1998

본 연구에서는 연속음 인식과 합성을 위한 경계강도 예측 모델을 제안한다. 운율 경계 강도는 음성 합성에서는 운율구 사이의 휴지기의 길이 조절로 합성음의 자연도에 기여를 하고 연속음 인식에서는 인식과정에서 나타나는 후보문장의 선별 과정에 특징변수가 되어 인식률 향상에 큰 역할을 한다. 음성학적으로 발화된 문장은 큰 경계 단위로 볼 때 운율구 형태로 이루어졌다고 볼 수 있으며 구의 경계는 문장의 문법적인 특징과 관련을 지을 수 있게 된다. 본 논문에서는 운율 경계 강도 수준을 4로 하고 문법적인 특징으로는 트리구조 방법으로 결정된 오른쪽 가지의 수식의 깊이(rd)와 link grammar방법으로 결정된 음절수(syl), 연결거리(torig)를 bigram 모형과 결합하여 운율적 경계 강도를 예측한다. 예측 모형으로는 다중 회귀 모형과 Marcov 모형을 제안한다. 이들 모형으로 낭독체 200 문장에 대해 실험한 결과 76%로 경계 강도를 예측할 수 있었다.

• Proceedings of the Korean Information Science Society Conference
• /
• 1998.10c
• /
• pp.219-221
• /
• 1998

네트워크 게임은 동시에 많은 참여자가 함께 게임에 참가하여 서로간의 상호작용을 통해 게임을 진행하는 새로운 방식으로, 내용이 어려운 전문교육에 네트워크 게임이 갖는 이와 같은 특징을 접목시킴으로써 학습자의 흥미를 유발시키고 교육효과를 높일 수 있다. 본 논문에서는 의학전문분야 중 심장학에 대해 게임과 교육을 결합시킨 에듀테인먼트 시스템 Cardio.NT를 개발하였다. 개발 시스템은 다중 사용자가 함께 게임에 참여하여 심장학 문제풀이를 통해 얻어지는 점수를 상호 공유하도록 함으로써 객관적이며 상대적인 학습평가를 제공한다.

• Journal of the Korea Society of Computer and Information
• /
• v.25 no.2
• /
• pp.49-58
• /
• 2020

In this study, we solve an online multi-object problem which finds object states (i.e. locations and sizes) while conserving their identifications in online-provided images and detections. We handle this problem based on a tracking-by-detection approach by linking (or associating) detections between frames. For more accurate online association, we propose novel online appearance learning with discrete fourier transform and partial least square analysis (PLS). We first transform each object image into a Fourier image in order to extract meaningful features on a frequency domain. We then learn PLS subspaces which can discriminate frequency features of different objects. In addition, we incorporate the proposed appearance learning into the recent confidence-based association method, and extensively compare our methods with the state-of-the-art methods on MOT benchmark challenge datasets.

• Journal of the Korea Society of Computer and Information
• /
• v.17 no.6
• /
• pp.37-48
• /
• 2012

Image registration is a process to establish the spatial correspondence between the images of same scene, which are acquired at different view points, at different times, or by different sensors. In this paper, we propose an effective registration method for images acquired by multi-sensors, such as EO (electro-optic) and IR (infrared) sensors. Image registration is achieved by extracting features and finding the correspondence between features in each input images. In the recent research, the multi-sensor image registration method that finds corresponding features by exploiting NMI (Normalized Mutual Information) was proposed. Conventional NMI-based image registration methods assume that the statistical correlation between two images should be global, however images from EO and IR sensors often cannot satisfy this assumption. Therefore the registration performance of conventional method may not be sufficient for some practical applications because of the low accuracy of corresponding feature points. The proposed method improves the accuracy of corresponding feature points by combining the gradient orientation as spatial information along with NMI attributes and provides more accurate and robust registration performance. Representative experimental results prove the effectiveness of the proposed method.

• Journal of the Korea Academia-Industrial cooperation Society
• /
• v.3 no.4
• /
• pp.319-324
• /
• 2002

The Integration of agent technology and security technology is needed to many application areas like electronic commerce. This paper suggests a model of extended multi-agent engine which supports privacy, integrity, authentication and non-repudiation on agent communication. Each agent which is developed with the agent engine is composed of agent engine layer and agent application layer. We describe and use the concepts self-to-self messages, secure communication channel, and distinction of KQML messages in agent application layer and messages in agent engine layer. The suggested agent engine provides an agent communication language which is extended to enable secure communication between agents without any modifications or restrictions to content layer and message layer of KQML. Also, in the model of our multi-agent engine, secure communication is expressed and processed transparently on the agent communication language.

• The KIPS Transactions:PartA
• /
• v.8A no.1
• /
• pp.9-15
• /
• 2001

영상에 관련된 다양한 응용 시스템들을 구현하는 많은 연구들이 진행되어 왔지만, 그러한 영상 관련 응용 시스템을 구현함에 있어서 처리속도의 저하로 인하여 많은 어려움을 겪고 있다. 이를 해결하기 위해 대두된 여러 방법들 중에서 최근 하드웨어 접근 방법에 고려한 많은 관심과 연구가 진행되고 있다. 본 논문은 영상을 실시간으로 처리하기 위하여 하드웨어 구조를 갖는 병렬처리시스템을 기술하며, 또한 병렬처리시스템을 얼굴 검색 시스템에 적용한 후 처리속도 및 실험 결과를 기술한다. 병렬처리시스템은 SIMD와 MIMD가 결합된 구조를 갖고 있기 때문에 다양한 영상 응용시스템에 대해서 융통성과 효율성을 제공하며, 144개의 처리기와 12개의 다중접근기억장치, 외부 메모리 모듈을 위한 인터페이스와 외부 프로세서 장치(i960Kx)와의 통신을 위한 인터페이스로 구성되어있다. 다중접근기억장치는 메모리 모듈선택회로, 데이터 라이팅회로, 그리고, 주소계산 및 라우팅회로로 구성되어 있다. 또한 얼굴 검색 시스템을 병렬처리 시스템에 적합한 병렬화를 제공하기 위해 메쉬방법을 이용하여 전처리, 정규화, 4개 특징값 추출, 그리고 분류화로 구성하였다. 병렬처리시스템은 하드웨어 모의실험 패키지인 CADENCE사의 Verilog-XL로 모의실험을 수행하여 기능과 성능을 검증하였다.

• Journal of the Korea Institute of Information and Communication Engineering
• /
• v.12 no.8
• /
• pp.1456-1462
• /
• 2008

In general, it is known a single biometric-based personal authentication has limitation to improve recognition rate due to weakness of individual recognition scheme. The recognition rate of face recognition system can be reduced by environmental factor such as illumination, while speaker verification system does not perform well with added surrounding noise. In this paper, a multi-modal biometric system composed of face and voice recognition system is proposed in order to improve the performance of the individual authentication system. The proposed empirical weight sum rule based on the reliability of the individual authentication system is applied to improve the performance of multi-modal biometrics. Since the proposed system is implemented using JAVA applet with security function, it can be utilized in the field of user authentication on the generic Web.

• The Journal of the Institute of Internet, Broadcasting and Communication
• /
• v.18 no.5
• /
• pp.171-177
• /
• 2018

Recently there are many image datasets which has variety of data class and point to extract general features. But in order to this variety data class and point, deep learning model trained this dataset has not good performance in heterogeneous data feature local area. In this paper, we propose the structure which use sub-category and openset object detection methods to train more robust model, named multi-branch tree using ASSL. By using this structure, we can have more robust object detection deep learning model in heterogeneous data feature environment.