• Journal of the Institute of Electronics Engineers of Korea SC
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• v.37 no.3
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• pp.63-71
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• 2000

Infrared (IR) detector chip, which detects the IR radiation from all of the objects and converts to image signal, is usually fabricated using hybrid bonding technology with detector away and readout integrated circuit (ROIC). In this study, we designed the readout circuit and simulated its operations. Fabricating readout circuit chips, we measured operation results satisfying its design requirements in 6V supply voltage. After we mount the IR detector chip in the manufactured thermal image system, thermal images were implemented. The obtained thermal images for high and room temperature target objects are sufficiently recognizable. Using the low noise thermal Image system, we expect to obtain thermal images with higher temperature resolution.

• The Bulletin of The Korean Astronomical Society
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• v.39 no.1
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• pp.62.2-62.2
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• 2014

We compiled near-infrared photometric and polarimetric catalog of sources in ~3 $9^{\prime}{\times}69^{\prime}$ size field in the eastern side of the Large Magellanic Cloud (LMC). This catalog lists all 1969 sources which are brighter than 14 mag and which signal to noise ratio of degree of polarization is greater than 3 in the J, H, and Ks bands. The photometric and polarimetric data were simultaneously obtained in J, H, and Ks bands using SIRPOL, an imaging polarimeter of the InfraRed Survey Facility (IRSF), in 2008 December and 2011 December. We classified the objects into several groups based on their locations on the color-magnitude diagram and compared their general properties of polarization. We measured wavelength dependence of this field to verify interstellar polarization of the LMC which occurred from the dichroic extinction. We also discuss the polarization structure in this field with the results from molecular cloud studies.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.8 no.6
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• pp.1135-1141
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• 2004

In this study, this system makes use of the analog infrared rays sensor and converts the feature of fish outline when sensor is operating with CPU(80C196KC). Then, after signal processing, this feature is classified a special feature and a outline of fish by using the neural network, one of the artificial intelligence scheme. This neural network classifies fish pattern of very simple and short calculation. This has linear activation function and the error back propagation is used as a teaming algorithm. And the neural network is learned in off-line process. Because an adaptation period of neural network is too long when random initial weights are used, off-line teaming is induced to decrease the progress time.

• Proceedings of the Korean Powder Metallurgy Institute Conference
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• 2006.09a
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• pp.399-400
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• 2006

M390 microclean(R) of $B{\ddot{o}}hler$ Edelstahl is a powder metallurgical plastic mould steel with a high level of corrosion and wear resistance and therefore often used in the plastics processing industry. But as a consequence of rapidly advancing developments in the plastics processing industry the required level of wear resistance of tool steels in this field is constantly rising. For that reason a new PM tool steel with higher hardness values and an increased amount of primary carbides has been developed to improve the resistance against abrasive and adhesive wear. The wear resistance of both steels against adhesive situations for components of the plastification unit of injection moulding machines has been tested with a novel method. In case of processing polyolefins with an injection moulding machine it was found that there is adhesive wear between the check-ring and the flights of the screw tip of the non-return valve under certain circumstances. The temperature in that region was measured with an infrared temperature sensor. The existence of significant peaks of that signal was used as an indicator for an adhesive wear situation.

• Journal of Biosystems Engineering
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• v.26 no.5
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• pp.475-480
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• 2001

Sensing soil organic matter is crucial for precision farming and environment friendly agriculture. Near infra-red(NIR) was utilized to measure the soil organic matter. Multivariate calibration methods, including stepwise multiple linear regression(MLR), principal components recession(PCR) and partial least squares regression(PLS), were applied to soil spectral reflectance data to predict the organic matter content. The effect of soil particle size and water content was studied. The range of soil organic matter contents was from 0.5 to 11%. Near infrared (NIR) region from 700 to 2,500nm was applied. For uniform soil particle size, result had good correlation (R$\^$2/ = 0.984, standard error of prediction= 0.596). The effect of soil particle size could be eliminated with 1st order derivative of the NIR signal. However. moist soil had a little lower correlation. R$\^$2/ was 0.95 and standard error of prediction was 0.94% using the PLS method. The results showed the possibility of soil organic matter measurement using NIR reflectance on the field.

• Proceedings of the KSRS Conference
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• 2003.11a
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• pp.72-74
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• 2003

Forest canopy density is an ideal representative of the forest habitat situations. It can directly or indirectly depict the canopy structure and gap size in the forestland, thus could be applied to assessment of wildlife’s diversit y. Since population survey of vegetation and wildlife diversities is a key issue for sustainable forest ecosystem management, many research efforts have been focused on forest canopy density using multispectral data in the last two decades. Unfortunately, prediction of canopy density using large scaling remote sensing data remains a challenging issue. Due to recent advances in hyperspectral image sensors hyperspectral imagery is now available for environmental monitoring. In this paper, we conduct experiments to monitor complicated environments of forestland that can be captured by using hyperspectral imagery and further be analyzed to test a prediction model of forest canopy density. The results show that 95% of canopy density could be well described by using 2 difference vegetation indices (DVIs), which are difference of blue and green reflectances rband_100-rband_150 and difference of 2 short wave infrared reflectancse rband_406-rband_410 With the wavelengths of band no. 100, 150, 406, and 410 specified by 462.39 nm, 534.40 nm, 918.22 nm and 924.41 nm respectively.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.15 no.3
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• pp.186-191
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• 2015

Hand gesture is the most common tool used to interact with and control various electronic devices. In this paper, we propose a novel hand gesture recognition method using fuzzy logic based classification with a new type of sensor array. In some cases, feature patterns of hand gesture signals cannot be uniquely distinguished and recognized when people perform the same gesture in different ways. Moreover, differences in the hand shape and skeletal articulation of the arm influence to the process. Manifold features were extracted, and efficient features, which make gestures distinguishable, were selected. However, there exist similar feature patterns across different hand gestures, and fuzzy logic is applied to classify them. Fuzzy rules are defined based on the many feature patterns of the input signal. An adaptive neural fuzzy inference system was used to generate fuzzy rules automatically for classifying hand gestures using low number of feature patterns as input. In addition, emotion expression was conducted after the hand gesture recognition for resultant human-robot interaction. Our proposed method was tested with many hand gesture datasets and validated with different evaluation metrics. Experimental results show that our method detects more hand gestures as compared to the other existing methods with robust hand gesture recognition and corresponding emotion expressions, in real time.

• Current Optics and Photonics
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• v.3 no.1
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• pp.8-15
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• 2019

We describe a common optical system that merges a LADAR system, which generates a point cloud, and a more traditional imaging system operating in the LWIR, which generates image data. The optimum diameter of the entrance pupil was determined by analysis of detection ranges of the LADAR sensor, and the result was applied to design a common optical system using LADAR sensors and LWIR sensors; the performance of these sensors was then evaluated. The minimum detectable signal of the $128{\times}128-pixel$ LADAR detector was calculated as 20.5 nW. The detection range of the LADAR optical system was calculated to be 1,000 m, and according to the results, the optimum diameter of the entrance pupil was determined to be 15.7 cm. The modulation transfer function (MTF) in relation to the diffraction limit of the designed common optical system was analyzed and, according to the results, the MTF of the LADAR optical system was 98.8% at the spatial frequency of 5 cycles per millimeter, while that of the LWIR optical system was 92.4% at the spatial frequency of 29 cycles per millimeter. The detection, recognition, and identification distances of the LWIR optical system were determined to be 5.12, 2.82, and 1.96 km, respectively.

• Journal of Convergence for Information Technology
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• v.9 no.3
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• pp.30-35
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• 2019

An unattended recording system based on smartphone based image image tracking is rapidly developing. Among the existing products, a system that automatically tracks and rotates the object to be photographed using an infrared signal is very expensive for general users. Therefore, this paper proposes a mobile unattended recording system that enables automatic recording by anyone who uses a smartphone. The system consists of a commercial mobile camera, a servomotor that moves the camera from side to side, a microcontroller to control the motor, and a commercial wireless Bluetooth Earset for video audio input. In this paper, we designed a system that enables unattended recording through image tracking using smartphone.

• Journal of Astronomy and Space Sciences
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• v.39 no.4
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• pp.127-139
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• 2022

Irregular mare patches (IMPs), recently discovered on the Moon, are eruptions of magma on the lunar surface, and their origins are still in question. While prior studies on IMPs have mainly focused on optical image analysis, in this study, an analysis of the characteristics of minerals is performed exemplary for the first time. Modified Gaussian model (MGM) deconvolution was applied to the infrared spectrum to confirm the properties of the mafic mineral. Mafic minerals were analyzed for 6 olivine-rich (Ol-rich) IMPs out of 91 currently reported, and only 4 of them yielded results of significance. All four sites showed more abundance of Fe than Mg, and manifested a weak relationship with Mg-suite rock. However, a problem was discovered during the MGM application process due to pilot implementation. In order to solve this problem, it is required to adjust the MGM initial condition settings more precisely and to increase the signal to noise ratio of the observation data. Moreover, it is necessary to analyze the mineral properties for all IMPs considering minerals other than Ol and utilize them to deduce the origin of the IMPs.