• Title/Summary/Keyword: Background noise level

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The Design of Wireless Underwater Telephone -Analysis of Underwater Background Noise for Wireless Underwater Telephone Design - (수중 무선 전화기의 설계 - 수중무선전화기 설계를 위한 수중소음분석을 중심으로-)

  • 박문갑;윤갑동;김석제;윤종락
    • Journal of the Korean Society of Fisheries and Ocean Technology
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    • v.37 no.4
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    • pp.302-307
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    • 2001
  • The underwater background noise measured in Geoje and Tongyoung diving fishing ground from May to December, 2000 and analyzed to get optimum carrier frequency and transmitter power level for underwater wireless telephone design. The results obtained are summarized as follows: 1. At the Geoje and Tongyoung diving fishing ground, the lowest ambient noise band was 25~30kHz with 57dB and 52dB re 1$\mu$Pa, respectively. 2. At the Geoje and Tongyoung diving fishing ground, the lowest noise band during fishing activity was 67dB and 62dB re 1$\mu$Pa, respectively. 3. At the Geoje diving fishing ground, the noise of water jetter which is a digging machine for subbottom shells was 102dB re 1$\mu$Pa. 4. Considering the design parameters of underwater wireless telephone, it is found that the optimum carrier frequency band is around 30kHz and the transmitter source level should be at least 131dB re 1$\mu$Pa for 500m range telephone.

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Change of Cerebrovascular Reactivity by Prandial State in Women with Migraine without Aura: Transcranial Doppler Ultrasonography (TCD) with Breath-Holding Method (두개경유도플러초음파를 이용한 성인 여성 무조짐편두통 환자의 식사 상태에 따른 뇌혈관반응성 변화)

  • Park, Jeong-Ho;Park, Sun-Ah;Lee, Tae-Kyeong;Sung, Ki-Bum
    • Annals of Clinical Neurophysiology
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    • v.14 no.1
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    • pp.20-24
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    • 2012
  • Background: Migraine patients can be sensitive to external or internal stimuli, such as light, noise, or hormonal changes. Using transcranial Doppler ultrasonography (TCD) with breath-holding method, we evaluated the changes of cerebrovascular reactivity (CVR) to hypercapnia in women with migraine without aura between fasting and postprandial period. Methods: Twelve women with migraine without aura and the same number of age and sex-matched healthy controls with no significant history of headache participated in this study. Using TCD examinations, we studied mean flow velocity in middle cerebral artery with better temporal window. Each subject was examined consecutively before and after a standard meal, together with serum glucose level and blood pressure. CVR was evaluated with breath-holding index (BHI). Results: Postprandial-BHI (mean+SD) was significantly higher than fasting-BHI (mean+SD) in patients group but not in controls (in patient group; postprandial-BHI=1.38, fasting-BHI=1.08, in control group; postprandial-BHI=1.25, fasting-BHI=1.18, P=0.021 and 0.239, respectively). After meal, serum glucose level was significantly enhanced but blood pressure was not in both groups. Serum glucose level of patients showed a tendency of mild positive correlation with BHIs (${\gamma}$=0.448, P=0.032). Conclusions: Although exact mechanisms are unclear, cerebrovascular reactivity of some women with migraine without aura may be influenced by prandial state.

Pixel-level Current Mirroring Injection with 2-step Bias-current Suppression for 2-D Microbolometer FPAs (이차원 마이크로볼로미터 FPA를 위한 이 단계 바이어스 전류 억제 방식을 갖는 픽셀 단위의 전류 미러 신호취득 회로)

  • Hwang, Chi Ho;Woo, Doo Hyung
    • Journal of the Institute of Electronics and Information Engineers
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    • v.52 no.11
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    • pp.36-43
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    • 2015
  • A pixel-level readout circuit is studied for 2-dimensional microbolometer focal plane arrays (FPAs). A current mirroring injection (CMI) input circuit with 2-step current-mode bias suppression is proposed for a pixel-level architecture with high responsivity and long integration time. The proposed circuit has been designed using a $0.35-{\mu}m$ 2-poly 4-metal CMOS process for a $320{\times}240$ microbolometer array with a pixel size of $50{\mu}m{\times}50{\mu}m$. The proposed 2-step bias-current suppression has sufficiently low calibration error with wide calibration range, and the calibration range and error can be easily optimized by controlling some design parameters. Due to high responsivity and a long integration time of more than 1 ms, the noise equivalent temperature difference (NETD) of the proposed circuit can be improved to 26 mK, which is much better than that of the conventional circuits, 67 mK.

A Study on the Preprocessing Method Using Construction of Watershed for Character Image segmentation

  • Nam Sang Yep;Choi Young Kyoo;Kwon Yun Jung;Lee Sung Chang
    • Proceedings of the IEEK Conference
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    • 2004.08c
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    • pp.814-818
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    • 2004
  • Off-line handwritten character recognition is in difficulty of incomplete preprocessing because it has not dynamic and timing information besides has various handwriting, extreme overlap of the consonant and vowel and many error image of stroke. Consequently off-line handwritten character recognition needs to study about preprocessing of various methods such as binarization and thinning. This paper considers running time of watershed algorithm and the quality of resulting image as preprocessing For off-line handwritten Korean character recognition. So it proposes application of effective watershed algorithm for segmentation of character region and background region in gray level character image and segmentation function for binarization image and segmentation function for binarization by extracted watershed image. Besides it proposes thinning methods which effectively extracts skeleton through conditional test mask considering running time and quality. of skeleton, estimates efficiency of existing methods and this paper's methods as running time and quality. Watershed image conversion uses prewitt operator for gradient image conversion, extracts local minima considering 8-neighborhood pixel. And methods by using difference of mean value is used in region merging step, Converted watershed image by means of this methods separates effectively character region and background region applying to segmentation function. Average execution time on the previous method was 2.16 second and on this paper method was 1.72 second. We prove that this paper's method removed noise effectively with overlap stroke as compared with the previous method.

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DEEP-South: Performance of Moving Object Detection Program in Different Observation Modes

  • Oh, Young-Seok;Bae, Yeong-Ho;Kim, Myung-Jin;Roh, Dong-Goo;Jin, Ho;Moon, Hong-Kyu;Park, Jintae;Lee, Hee-Jae;Yim, Hong-Suh;Choi, Young-Jun
    • The Bulletin of The Korean Astronomical Society
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    • v.41 no.2
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    • pp.48.3-49
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    • 2016
  • We have five different types of observation modes with regard to the Deep Ecliptic Patrol of the Southern Sky (DEEP-South); Opposition Census (OC) for targeted photometry, Sweet Spot Survey (S1) for discovery and orbit characterization of Atens and Atiras, Ecliptic Survey (S2) for asteroid family studies and comet census, NEOWISE follow-up (NW) for near simultaneous albedo measurements in the visible bands, and Target of Opportunity (TO) observation for follow-up either for unpredictable events or targets of special interests. Different exposures with such different modes result in a wide range of background noise level, the number of background stars and the mover's projected speed in each image. The Moving Object Detection Program (MODP) utilizes multiple mosaic images being taken for the same target fields at different epochs at the three KMTNet sites. MODP employs existing software packages such as SExtractor (Source-Extractor) and SCAMP (Software for Calibrating Astrometry and Photometry); SExtractor generates object catalogs, while SCAMP conducts precision astrometric calibration, then MODP determines if a point source is moving. This package creates animated stamp images for visual inspection with MPC reports, the latter for checking whether an object is known or unknown. We evaluate the astrometric accuracy and efficiency of MODP using the year one dataset obtained from DEEP-South operations.

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Facial Image Recognition Based on Wavelet Transform and Neural Networks (웨이브렛 변환과 신경망 기반 얼굴 인식)

  • 임춘환;이상훈;편석범
    • Journal of the Institute of Electronics Engineers of Korea TE
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    • v.37 no.3
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    • pp.104-113
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    • 2000
  • In this study, we propose facial image recognition based on wavelet transform and neural network. This algorithm is proposed by following processes. First, two gray level images is captured in constant illumination and, after removing input image noise using a gaussian filter, differential image is obtained between background and face input image, and this image has a process of erosion and dilation. Second, a mask is made from dilation image and background and facial image is divided by projecting the mask into face input image Then, characteristic area of square shape that consists of eyes, a nose, a mouth, eyebrows and cheeks is detected by searching the edge of divided face image. Finally, after characteristic vectors are extracted from performing discrete wavelet transform(DWT) of this characteristic area and is normalized, normalized vectors become neural network input vectors. And recognition processing is performed based on neural network learning. Simulation results show recognition rate of 100 % about learned image and 92% about unlearned image.

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A MULTI-DIMENSIONAL REDUCTION METHOD OF LARGE-SCALE SURVEY DATABASE

  • Lee, Y.;Kim, Y.S.;Kang, H.W.;Jung, J.H.;Lee, C.H.;Yim, I.S.;Kim, B.G.;Kim, H.G.;Kim, K.T.
    • Publications of The Korean Astronomical Society
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    • v.28 no.1
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    • pp.7-13
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    • 2013
  • We present a multi-dimensional reduction method of the surveyed cube database obtained using a single- dish radio telescope in Taeduk Radio Astronomy Observatory (TRAO). The multibeam receiver system installed at the 14 m telescope in TRAO was not optimized at the initial stage, though it became more stabilized in the following season. We conducted a Galactic Plane survey using the multibeam receiver system. We show that the noise level of the first part of the survey was higher than expected, and a special reduction process seemed to be definitely required. Along with a brief review of classical methods, a multi-dimensional method of reduction is introduced; It is found that the 'background' task within IRAF (Image Reduction and Analysis Facility) can be applied to all three directions of the cube database. Various statistics of reduction results is tested using several IRAF tasks. The rms value of raw survey data is 0.241 K, and after primitive baseline subtraction and elimination of bad channel sections, the rms value turned out to be 0.210 K. After the one-dimensional reduction using 'background' task, the rms value is estimated to be 0.176 K. The average rms of the final reduced image is 0.137 K. Thus, the image quality is found to be improved about 43% using the new reduction method.

A Computer Vision-based Method for Detecting Rear Vehicles at Night (컴퓨터비전 기반의 야간 후방 차량 탐지 방법)

  • 노광현;문순환;한민홍
    • Journal of the Institute of Convergence Signal Processing
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    • v.5 no.3
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    • pp.181-189
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    • 2004
  • This paper describes the method for detecting vehicles in the rear and rear-side at night by using headlight features. A headlight is the outstanding feature that can be used to discriminate a vehicle from a dark background. In the segmentation process, a night image is transformed to a binary image that consists of black background and white regions by gray-level thresholding, and noise in the binary image is eliminated by a morphological operation. In the feature extraction process, the geometric features and moment invariant features of a headlight are defined, and they are measured in each segmented region. Regions that are not appropriate to a headlight are filtered by using geometric feature measurement. In region classification, a pair of headlights is detected by using relational features based on the symmetry of a pair of headlights. Experimental results show that this method is very applicable to an approaching vehicle detection system at nighttime.

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Design of Readout Circuit With Smart Reset Control for Improving Dynamic Range of LWIR FPAs (초점면 배열 원적외선 검출기의 동작범위 향상을 위한 리셋 조정 회로)

  • Woo, Doo-Hyung
    • Journal of the Institute of Electronics Engineers of Korea SD
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    • v.47 no.1
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    • pp.38-45
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    • 2010
  • A new readout circuit involving a pixel-level reset control was studied for 2-D long wavelength infrared focal plane arrays. The integration time of each pixel can be optimized individually and automatically. Hence, the readout circuit has a wide dynamic range and good signal-to-noise ratio characteristics. The readout circuit was fabricated with a $0.35{\mu}m$ 2-poly 4-metal CMOS process for a $128{\times}128$ long wavelength infrared HgCdTe array with a pixel size of $50{\mu}m{\times}50{\mu}m$. The smart reset control with two-step background suppression improves the signal-to-noise ratio to 87dB and the dynamic range to 95.8dB.

Role of linking parameters in Pulse-Coupled Neural Network for face detection

  • Lim, Young-Wan;Na, Jin-Hee;Choi, Jin-Young
    • 제어로봇시스템학회:학술대회논문집
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    • 2004.08a
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    • pp.1048-1052
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    • 2004
  • In this work, we have investigated a role of linking parameter in Pulse-Coupled Neural Network(PCNN) which is suggested to explain the synchronous activities among neurons in the cat cortex. Then we have found a method to determine the linking parameter for a satisfactory face detection performance in a given color image. Face detection algorithm which uses the color information is independent on pose, size and obstruction of a face. But the use of color information encounters some problems arising from skin-tone color in the background, intensity variation within faces, and presence of random noise and so on. Depending on these conditions, PCNN's linking parameters should be selected an appropriate values. First we obtained the mean and variance of the skin-tone colors by experiments. Then, we introduced a preprocess that the pixel with a mean value of skin-tone colors has the highest level value (255) and the other pixels have values between 0 and 255 according to normal distribution with a variance. This preprocessing leads to an easy decision of the linking parameter of the Pulse-Coupled Neural Network. Through experiments, it is verified that the proposed method can improve the face detection performance compared to the existing methods.

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