• Journal of IKEEE
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• v.26 no.3
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• pp.364-372
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• 2022

This paper proposes the design and implementation results for human and object classification systems utilizing frequency modulated continuous wave (FMCW) radar sensor. Such a system requires the process of radar sensor signal processing for multi-target detection and the process of deep learning for the classification of human and object. Since deep learning requires such a great amount of computation and data processing, the lightweight process is utmost essential. Therefore, binary neural network (BNN) structure was adopted, operating convolution neural network (CNN) computation in a binary condition. In addition, for the real-time operation, a hardware accelerator was implemented and verified via FPGA platform. Based on performance evaluation and verified results, it is confirmed that the accuracy for multi-target classification of 90.5%, reduced memory usage by 96.87% compared to CNN and the run time of 5ms are achieved.

• Journal of the Korea Society of Computer and Information
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• v.14 no.2
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• pp.45-57
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• 2009

ETexture mapping is a technique used for adding reality to an image in 3D graphics. However. this technique becomes the bottleneck of the 3D graphics pipeline because it requires large processing power and high memory bandwidth. For reducing memory latency in texture mapping, texture cache is used. As portable devices become smaller and they have power constraint, it is important to reduce the area and the power consumption of the texture cache. In this paper we propose using a small texture cache to reduce the area and the power consumption of the texture cache. Furthermore, we propose techniques to keep a performance comparable to large texture caches by using prefetch techniques and a victim cache. Simulation results show the proposed small texture cache can reduce the area and the power consumption up to 70% and 60%, respectively, by using $1{\sim}2K$ bytes texture cache compared to the conventional 16K bytes cache while keeping the performance.

• The Journal of the Korea Contents Association
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• v.12 no.2
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• pp.30-39
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• 2012

In these day, some of IT venders already were going to cloud computing market, as well they are going to expand their territory for the cloud computing market through that based on their hardware and software technology, making collaboration between hardware and software vender. Distributed file system is very mainly technology for the cloud computing that must be protect performance and safety for high levels service requests as well data store. This paper introduced distributed file system for cloud computing and how to use this theory such as memory database, Hadoop file system, high availability database system. now In the market, this paper define a very large distributed processing architect as a reference by kind of distributed file systems through using technology in cloud computing market.

• Journal of KIISE:Software and Applications
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• v.26 no.8
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• pp.939-954
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• 1999

데이타마이닝 분야에서는 대용량의 트랜잭션 데이타베이스와 같은 하나의 데이타베이스로부터 연관 규칙을 찾는 연구가 많이 수행되어왔다. 그러나, 창고형 할인매장이나 백화점 같이 고객 카드를 이용하는 판매점의 등장으로, 단지 트랜잭션에 대한 분석 뿐만이 아니라, 트랜잭션과 고객과의 관계에 대한 분석 또한 요구되고 있다. 즉, 두 개의 데이타베이스로부터 연관 규칙을 찾는 연구가 필요하다. 이 논문에서는 두 데이타베이스 사이에 링크를 생성하여 연관 항목집합을 찾는 알고리즘을 제안한다. 실험 결과, 링크를 이용한 알고리즘은 고객 데이타베이스가 메모리에 거주가능한 크기라면 시간에 따른 분석에 유용함을 보여주었다.Abstract There have been a lot of researches of mining association rules from one database such as transaction database until now. But as the large discount store using customer card emerges, the analysis is not only required about transactions, but also about the relation between transactions and customer data. That is, it is required to search association rules from two databases. This paper proposes an efficient algorithm constructing links from one database to the other. Our experiments show the algorithm using link is useful for temporal analysis of memory-resident customer database.

• Journal of the Korean Institute of Intelligent Systems
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• v.15 no.1
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• pp.75-80
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• 2005

In this paper, a 3-dimensional analysis of magnetic road and a position sensing system for an autonomous vehicle system is described. Especially, a new position sensing system, end of the important component of an autonomous vehicle, is proposed. In a magnet based autonomous vehicle system, to sense the vehicle position, the sensor measures the field of magnetic road. The field depends on the sensor position of the vehicle on the magnetic road. As the rotation between the magnetic field and the sensor position is highly complex, it is difficult that the relation is stored in memory. Thus, a neural network is used to learn the mapping from th field to the position. The autonomous vehicle system with the proposed position sensing system is tested in experimental setup.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.39 no.1
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• pp.32-39
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• 2002

Vector quantization for image compression needs expensive encoding time to find the closest codeword to the input vector. This paper proposes a search algorithm for fast vector quantization encoding. Firstly, we derive a robust condition based on the efficient topological structure of the codebook to dramatically eliminate unnecessary matching operations from the search procedure. Then, we Propose a fast search algorithm using the elimination condition. Simulation results show that with little preprocessing and memory cost, the encoding time of the proposed algorithm is reduced significantly while the encoding quality remains the same with respect to the full search algorithm. It is also found that the Proposed algorithm outperforms the existing search algorithms.

• Journal of the Korea Society of Computer and Information
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• v.7 no.2
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• pp.95-100
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• 2002

By feedback channel, the decoder reports the addresses of corrupted macroblocks induced by transmission errors back to the encoder With these negative acknowledgements, the encoder can make the next frame having propagated errors by using forward dependency based on GOBs and MBs of the frame happening transmission errors. The encoder can precisely calculate and track the propagated errors by examining the backward motion dependency for each of four comer pixels in the current encoding frame until before-mentioned the next frame. The error-propagation effects can be terminated completely by INTRA refreshing the affected macroblocks. Such a fast algorithm further reduce the computation and memory requirements. The advantages of the low computation complexity and the low memory requirement are Particularly suitable for real-time implementation.

• Proceedings of the Korea Crystallographic Association Conference
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• 2002.11a
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• pp.38-39
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• 2002

Spectroscopic ellipsometer(SE)는 박막의 두께, 굴절률, 흡수율, 에너지 갭, 결정상태, 밀도, 표면 및 계면의 거칠기 등에 관한 유용한 정보들을 제공한다. (1-3) SE는 빛을 탐침으로 사용하기 때문에 비파괴적이고 비접촉식 박막물성 측정방법이며 편광변화에 대한 상대적 물리량을 측정함으로써 정밀도와 재연성이 매우 높은 장점들을 갖고 있다. 따라서 SE는 반도체 메모리 소자, 평판 디스플레이, DVD와 CD와 같은 데이터 저장장치 등을 제작하는 공정에서 박막에 관련된 공정계측장비로 사용되고 있다. 특히, 최근의 차세대 반도체 소자 개발에 관한 연구 등(4-6)에서는 수 nm 두께의 다양한 초박막들에 관한 물성연구가 주관심사이기 때문에 최고의 성능을 갖는 계측장비와 기술이 요구되고 있다. 따라서 본 연구에서는 그림과 같은 편광자(polarizer)-시료(sample)-검광자(analyzer)로 구성된 PSA구조의 표준기용 rotating-analyzer SE를 제작하게 되었다. 현재까지 개발된 ellipsometer의 수많은 종류들 중에서 null 형, rotating element 형, 그리고 phase modulation 형이 가장 많이 사용되고 있다. 여기서 element란 polarizer, analyzer, 또는 compensator와 같은 광 부품들을 지칭하는데 이 중 하나 또는 둘을 회전시키기 때문에 그 종류 또한 매우 많다. 이들 중에서 회전검광자형 ellipsometer는 입사각 정렬이 우수하고, 파장에 무관한 편광기만 사용하므로 비교적 넓은 광량자 에너지영역에서 정확도 높은 데이터를 얻을 수 있기 때문에 박막 상수의 정밀측정에 가장 적합하다. 특히, 본 연구에서 제작된 ellipsometer에는 간섭계 장치, polarizer tracking,(2) zone average,(1) 그리고 low-pass filter 등을 사용함으로써 측정오차를 최대한 줄이는 노력을 하였다.

• Journal of the Korean Institute of Intelligent Systems
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• v.15 no.3
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• pp.300-305
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• 2005

Context-aware intelligent services are essential in ubiquitous computing and intelligent robots environments, which make decisions on which services to start with the consideration of surrounding contexts. In the ubiquitous and intelligent environments, context-aware service engines should be light-weighted due to the resource restrictions on the devices. This paper presents a context-aware service engine which is designed for light-weighted devices. The context-aware service engine has been designed with special attention to improve the execution speed and to minimize the memory requirement.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.21 no.4
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• pp.884-892
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• 1996

An adaptive blind equalizer is used to combat the distortions caused by a nonideal channel without resorting to a training sequence, given the received signal and statistical information of the transmitted signal. Incidentally, a multipath channel may result in a fade which produces intersymbol interference in the received signal. Therefore, a new type of algorithm which can compenste the effects of this fade is required in the multipath channel environment. In this paper, a modified form of adaptive blind equalization algorithm using stop-and-go algorithm for multichannel system is proposed. It is demonstrated via computer simulations that the performance of the proposed multichannel stop-and-go algorithm is much better than that of the conventional multichannel algorithms.