• Journal of the Institute of Electronics Engineers of Korea SC
• /
• v.38 no.5
• /
• pp.42-51
• /
• 2001

Vehicle detection is the basic of traffic monitoring. Video based systems have several apparent advantages compared with other kinds of systems. However, In video based systems, shadows make troubles for vehicle detection, especially active shadows resulted from moving vehicles. In this paper, a new method that combines background subtraction and edge detection is proposed for vehicle detection and shadow rejection. The method is effective and the correct rate of vehicle detection is higher than 98% in experiments, during which the passive shadows resulted from roadside buildings grew considerably. Based on the proposed vehicle detection method, vehicle tracking, counting, classification and speed estimation are achieved so that traffic parameters concerning traffic flow is obtained to describe the load of each lane.

• Smart Media Journal
• /
• v.5 no.3
• /
• pp.49-53
• /
• 2016

Related researches are progressing that method of non-contact method using the electromagnetic field on the human body by detecting the motion recognition signal is the limitations of time and space, so less than the existing systems. In this paper, we designed the circuit system that can implement the hardware that can detect the electric field signal of the human body non-contact method to increase the recognition rate to screen this digital waveform. The PCB design Used to automatically increase of composition of the circuit and the linkage of the comparator digital waveform with circuit simulation of the system. At same time for evaluate the characteristics of the whole circuit system.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
• /
• 2006.05a
• /
• pp.410-414
• /
• 2006

In the present, Orthogonal Frequency Division Multiple Access (OFDMA) that wireless access scheme for high speed data transmission is noticed in mobile communication market and OFDMA/TDD scheme will be used combining Time Division Duplex (TDD) scheme based on OFDMA. The Base Station's receiver synchronizes the symbol timing to anyone user's symbol and the other user's symbols have some Symbol Timing Offset (STO). Linear phase shift is occurred by each user's STO in an OFDMA symbol and the Multiple Access Interference (MAI) caused by the summation of each user's linear phase shift degrades the performance of ranging code detection. In this paper, we analyze the ranging code detection performance for each users STO in OFDMA/TDD system. Simulation results show that the more users access and mobile speed increase, the more ranging code detection performance degrades.

• The Journal of Korean Institute of Communications and Information Sciences
• /
• v.37 no.7A
• /
• pp.535-544
• /
• 2012

Multi-Input Multi-Output (MIMO) transmission is now considered as one of essential techniques enabling high rate data transmissions in wireless communication systems. In addition, severe channel impairments in wireless systems should be compensated by using highly efficient forward error correction (FEC) codes. Turbo codes or low density parity check (LDPC) codes, using iterative decoding with soft decision detection information (SDDI), are the most common examples. The excellent performance of these codes should be conditioned on accurate estimation of SDDI from the MIMO detection process. In this paper, we propose a soft MIMO detection scheme using QR decomposition of channel matrices as an efficient means to provide accurate SDDI to the iterative decoder. The proposed method employed a two sequential soft MIMO detection process in order to reduce computational complexity. Compared to the soft ZF method calculating the direct inverse of the channel matrix, the complexity of the proposed method can be further reduced as the number of antennas is increased, without any performance degradation.

• Proceedings of the Korean Institute of Surface Engineering Conference
• /
• 2017.05a
• /
• pp.110-110
• /
• 2017

마이크로 플루이딕 디바이스는 화학, 생물학 실험 및 생체 의학 진단을 위한 플랫폼으로 지난 20년간 그 사용 및 연구가 증가되어 왔다. 마이크로 플루이딕 디바이스를 제작하는 데 있어 가장 일반적으로 사용되는 재료는 실리콘이지만 비용이 많이 들고 불투명하므로 광학 검출이 필요한 곳에 적용이 제한된다. 이러한 측면에서 열가소성 플라스틱은 상업화의 중요한 요소인 대량 생산에 있어 큰 잠재력을 가지고 있으며 저렴하고, 가공이 쉽고, 유연하고, 광학적으로 투명하고, 화학적으로 불활성이며, 생체적합성을 가진다. 본 연구에서는 열가소성 플라스틱의 일종인 PMMA Poly(methylmethacrylate)를 효율적으로 접합하기 위해 비교적 낮은 온도와 낮은 압력에서 에탄올을 활용한 접착방식을 개발하였다. 먼저, PMMA 기판의 전체 표면을 $80^{\circ}C$에서 20 분 동안 에탄올로 처리한 후, $60^{\circ}C$에서 20 분간 열 압착하는 방식으로 영구적인 결합이 이루어졌다. 결합 강도 및 채널의 sealing 정도를 확인하기 위해, 인장 강도, 누수 및 파열 테스트를 수행하였다. 결합강도는 약 12.4 MPa로 타 연구와 비교할 때 매우 높았으며 마이크로 채널의 전체 내부 체적보다 거의 450 배 높은 강한 액체 흐름을 견딜 정도로 견고한 결합이 유지되었다. 열가소성 플라스틱의 본딩에 사용되는 유기 용매는 광학 특성을 희생시키지 않으면서 결합 속도를 높일 수 있지만, 결합 공정 중에 용매로 인해 마이크로 채널이 막히는 현상이 발생될 수 있다. 따라서, 견고한 본딩을 유지하면서 채널 막힘을 방지하기 위해 마이크로 채널을 소수성으로 선택적으로 처리하여 내벽의 표면 특성을 튜닝해 주는 기법을 추가로 적용하였다. 본 연구에서 사용한 방법은 아민-PDMS (polydimethylsiloxane) 링커를 적용하여 기판 표면의 극성을 변경시켜 주었다. 아민-PDMS 링커는 PC (polycarbonate), PET (polyethylene terephthalate), PVC (polyvinyl chloride) 및 PI (polyimide)와 같은 다양한 열가소성 플라스틱의 표면 소수성을 현저히 증가시키며 화학적, 열적 안정성이 뛰어나다. 아민-PDMS 링커는 PMMA의 카보닐 그룹과 반응할 수 있는 아민 사이드 그룹을 포함하는 PDMS 백본으로 구성되며 처리된 대상표면을 소수성으로 만든다. 아민-PDMS 링커 처리 이후 채널은 소수성으로 변화되었으며 이는 접촉각(contact angle)의 증가로 확인되었다. 코팅된 채널을 에탄올로 30분간 80도에서 처리하여도 소수성은 그대로 유지되어 마이크로 채널의 선택적인 소수성 코팅이 성공적으로 수행되었다.

• Journal of KIISE:Software and Applications
• /
• v.31 no.7
• /
• pp.949-958
• /
• 2004

race detection using a boosting based algorithm requires a very large size of face and nonface data. In addition, the fact that there always occurs a need for adding additional training data for better detection rates demands an efficient incremental teaming algorithm. In the design of incremental teaming based classifiers, the final classifier should represent the characteristics of the entire training dataset. Conventional methods have a critical problem in combining intermediate classifiers that weight updates depend solely on the performance of individual dataset. In this paper, for the purpose of application to face detection, we present a new method to combine an intermediate classifier with previously acquired ones in an optimal manner. Our algorithm creates a validation set by incrementally adding sampled instances from each dataset to represent the entire training data. The weight of each classifier is determined based on its performance on the validation set. This approach guarantees that the resulting final classifier is teamed by the entire training dataset. Experimental results show that the classifier trained by the proposed algorithm performs better than by AdaBoost which operates in batch mode, as well as by ${Learn}^{++}$.

• Proceedings of the KIEE Conference
• /
• 2011.07a
• /
• pp.1690-1691
• /
• 2011

본 논문에서는 H1N1 인플루엔자 A 바이러스(influenza A H1N1 virus) 검출을 위한 산화아연 나노구조(zinc oxide nano structure) 기반의 전기화학적 면역센서를 제작하고 그 특성을 분석하였다. H1N1 인플루엔자 A 바이러스는 빠른 전파 속도 때문에 정확하고 빠른 검출이 필요하다. 먼저, 2 $mm^2$의 표면적을 갖는 패턴된 금 전극 위에 열수방식(hydrothermal method)으로 성장시킨 산화아연 나노구조가 선택적으로 형성되도록 리프트-오프(lift-off) 방법을 사용하였다. 0.01 M phosphate buffered saline(pH 7.4)에서 2 ${\mu}g$/mL 농도의 1차 항체를 정전기력에 의해 산화아연 나노구조에 고정화한 후, 10 pg/mL ~ 5ng/mL 농도의 H1N1 항원을 적용하여 포획 항체에 결합시키고 HRP(horseradish peroxidase) 효소가 결합된 검출 항체를 항원에 결합시키는 샌드위치 ELISA법을 이용하였다. HRP와 반응하는 TMB(3,3', 5,5'-tetramethylbenzidine)와 과산화수소가 포함된 acetate buffered 용액(pH 5)을 전해질로 사용하고 순환전압전류 측정법(cyclic voltammetry)으로 센서의 특성을 분석하였다. 측정된 순환전압전류그래프(cyclic voltammogram)에서 H1N1 항원 농도 10 pg/mL ~ 5 ng/mL의 응답 전류는 276.47 ${\pm}$ 21.72 nA (평균 ${\pm}$ 표준편차, n=4) ~ 478.89 ${\pm}$ 6.21 nA로 측정되었고, logarithmic하게 증가하는 응답 전류 특성을 보였다.

• The Journal of Korean Institute of Communications and Information Sciences
• /
• v.35 no.5A
• /
• pp.423-430
• /
• 2010

The performances of turbo-coded space-time block coding (STBC) schemes are subject to how soft decision detection (SDD) information are generated from the STBC decoder. For this reason, we have to pay particular attention to estimation of SDD. In this paper, we evaluate the performance of a turbo coded STBC scheme depending on the accuracy of the SDD. Recently, a new quasi orthogonal STBC (QO-STBC) scheme using a noise whitened filter was proposed in order to reduce noise enhancing effect of zero forcing detection process. This QO-STBC scheme was proven to be efficient in computational complexity compared to the other conventional QO-STBC schemes. In this paper, we first present detailed mathematical analysis on the noise whitened QO-STBC scheme, and by using the result we propose the optimum SDD method.

• Journal of Satellite, Information and Communications
• /
• v.11 no.3
• /
• pp.119-122
• /
• 2016

Feature detection is recognized as an accurate spectrum sensing approach when the information of the desired signal is partly known at the receiver. This type of detection was proposed to overcome large noise environment. Cyclostationary detection is an example of feature detection in spectrum sensing technique in cognitive radio. However, the cyclostationary process calculation requires a lot of processing time and information about the designed signals. On the other hand, energy detection spectrum sensing is widely known as a simple and compact spectrum sensing technique. However, energy detection is highly affected by large noise and lead to high detection error probability. In this paper, the combination of energy detection and cyclostationary is proposed in order to increase the accuracy and decrease the calculation and processing time. The two-layer threshold is utilized in order to reduce the complexity of computation and processing time in cyclostationary which can lead to the improved throughput of the system. The simulation result shows that the implementation of energy-based cyclostationary detector can help to improve the performance of the system while it can considerably reduce the required time for signal detection.

• The Journal of the Acoustical Society of Korea
• /
• v.28 no.2
• /
• pp.112-118
• /
• 2009

This paper proposes a rapid detection algorithm of a salient region for music video browsing system, which can be applied to mobile device and digital video recorder (DVR). The input music video is decomposed into the music and video tracks. For the music track, the music highlight including musical chorus is detected based on structure analysis using energy-based peak position detection. Using the emotional models generated by SVM-AdaBoost learning algorithm, the music signal of the music videos is classified into one of the predefined emotional classes of the music automatically. For the video track, the face scene including the singer or actor/actress is detected based on a boosted cascade of simple features. Finally, the salient region is generated based on the alignment of boundaries of the music highlight and the visual face scene. First, the users select their favorite music videos from various music videos in the mobile devices or DVR with the information of a music video's emotion and thereafter they can browse the salient region with a length of 30-seconds using the proposed algorithm quickly. A mean opinion score (MOS) test with a database of 200 music videos is conducted to compare the detected salient region with the predefined manual part. The MOS test results show that the detected salient region using the proposed method performed much better than the predefined manual part without audiovisual processing.