• Korean Journal of Agricultural Science
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• v.51 no.1
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• pp.63-77
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• 2024

Yield monitoring systems have become integral to precision agriculture, providing insights into the spatial variability of crop yield and playing an important role in modern harvesting technology. This paper aims to review current research trends in yield monitoring systems, specifically designed for non-grain crops, including cabbages, radishes, potatoes, and tomatoes. A systematic literature survey was conducted to evaluate the performance of various monitoring methods for non-grain crop yields. This study also assesses both mass- and volume-based yield monitoring systems to provide precise evaluations of agricultural productivity. Integrating load cell technology enables precise mass flow rate measurements and cumulative weighing, offering an accurate representation of crop yields, and the incorporation of image-based analysis enhances the overall system accuracy by facilitating volumetric flow rate calculations and refined volume estimations. Mass flow methods, including weighing, force impact, and radiometric approaches, have demonstrated impressive results, with some measurement error levels below 5%. Volume flow methods, including paddle wheel and optical methodologies, yielded error levels below 3%. Signal processing and correction measures also play a crucial role in achieving accurate yield estimations. Moreover, the selection of sensing approach, sensor layout, and mounting significantly influence the performance of monitoring systems for specific crops.

• Journal of Intelligence and Information Systems
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• v.26 no.2
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• pp.1-25
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• 2020

In this paper, we suggest an application system architecture which provides accurate, fast and efficient automatic gasometer reading function. The system captures gasometer image using mobile device camera, transmits the image to a cloud server on top of private LTE network, and analyzes the image to extract character information of device ID and gas usage amount by selective optical character recognition based on deep learning technology. In general, there are many types of character in an image and optical character recognition technology extracts all character information in an image. But some applications need to ignore non-of-interest types of character and only have to focus on some specific types of characters. For an example of the application, automatic gasometer reading system only need to extract device ID and gas usage amount character information from gasometer images to send bill to users. Non-of-interest character strings, such as device type, manufacturer, manufacturing date, specification and etc., are not valuable information to the application. Thus, the application have to analyze point of interest region and specific types of characters to extract valuable information only. We adopted CNN (Convolutional Neural Network) based object detection and CRNN (Convolutional Recurrent Neural Network) technology for selective optical character recognition which only analyze point of interest region for selective character information extraction. We build up 3 neural networks for the application system. The first is a convolutional neural network which detects point of interest region of gas usage amount and device ID information character strings, the second is another convolutional neural network which transforms spatial information of point of interest region to spatial sequential feature vectors, and the third is bi-directional long short term memory network which converts spatial sequential information to character strings using time-series analysis mapping from feature vectors to character strings. In this research, point of interest character strings are device ID and gas usage amount. Device ID consists of 12 arabic character strings and gas usage amount consists of 4 ~ 5 arabic character strings. All system components are implemented in Amazon Web Service Cloud with Intel Zeon E5-2686 v4 CPU and NVidia TESLA V100 GPU. The system architecture adopts master-lave processing structure for efficient and fast parallel processing coping with about 700,000 requests per day. Mobile device captures gasometer image and transmits to master process in AWS cloud. Master process runs on Intel Zeon CPU and pushes reading request from mobile device to an input queue with FIFO (First In First Out) structure. Slave process consists of 3 types of deep neural networks which conduct character recognition process and runs on NVidia GPU module. Slave process is always polling the input queue to get recognition request. If there are some requests from master process in the input queue, slave process converts the image in the input queue to device ID character string, gas usage amount character string and position information of the strings, returns the information to output queue, and switch to idle mode to poll the input queue. Master process gets final information form the output queue and delivers the information to the mobile device. We used total 27,120 gasometer images for training, validation and testing of 3 types of deep neural network. 22,985 images were used for training and validation, 4,135 images were used for testing. We randomly splitted 22,985 images with 8:2 ratio for training and validation respectively for each training epoch. 4,135 test image were categorized into 5 types (Normal, noise, reflex, scale and slant). Normal data is clean image data, noise means image with noise signal, relfex means image with light reflection in gasometer region, scale means images with small object size due to long-distance capturing and slant means images which is not horizontally flat. Final character string recognition accuracies for device ID and gas usage amount of normal data are 0.960 and 0.864 respectively.

• Korean Journal of Remote Sensing
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• v.34 no.2_1
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• pp.237-248
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• 2018

The vertical distribution of hydrometeor before precipitation near the cloud base has been analyzed using a scanning lidar, rawinsonde data, and Cloud-Resolving Storm Simulator (CReSS). This study mostly focuses on 13 Desember 2016 only. The typical synoptic pattern of lake-effect snowstorm induced easterly in the Yeongdong region. Clouds generated due to high temperature difference between 850 hPa and sea surface (SST) penentrated in the Yeongdong region along with northerly and northeasterly, which eventually resulted precipitation. The cloud base height before the precipitation changed from 750 m to 1,280 m, which was in agreement with that from ceilometer at Sokcho. However, ceilometer tended to detect the cloud base 50 m ~ 100 m below strong signal of lidar backscattering coefficient. As a result, the depolarization ratio increased vertically while the backscattering coefficient decreased about 1,010 m~1,200 m above the ground. Lidar signal might be interpreted to be attenuated with the penetration depth of the cloud layer with of nonspherical hydrometeor (snow, ice cloud). An increase in backscattering signal and a decrease in depolarization ratio occured in the layer of 800 to 1,010 m, probably being associated with an increase in non-spherical particles. There seemed to be a shallow liquid layer with a low depolarization ratio (<0.1) in the layer of 850~900 m. As the altitude increases in the 680 m~850 m, the backscattering coefficient and depolarization ratio increase at the same time. In this range of height, the maximum value (0.6) is displayed. Such a result can be inferred that the nonspherical hydrometeor are distributed by a low density. At this time, the depolarization ratio and the backscattering coefficient did not increase under observed melting layer of 680 m. The lidar has a disadvantage that it is difficult for its beam to penetrate deep into clouds due to attenuation problem. However it is promising to distinguish hydrometeor morphology by utilizing the depolarization ratio and the backscattering coefficient, since its vertical high resolution (2.5 m) enable us to analyze detailed cloud microphysics. It would contribute to understanding cloud microphysics of cold clouds and snowfall when remote sensings including lidar, radar, and in-situ measurements could be timely utilized altogether.

• Journal of the Microelectronics and Packaging Society
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• v.24 no.3
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• pp.71-76
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• 2017

The electrical behavior and flexibility of the screen printed Ag circuits were investigated with infrared radiation sintering times and sintering temperatures. Electrical resistivity and radio frequency characteristics were evaluated by using the 4 point probe measurement and the network analyzer by using cascade's probe system, respectively. Electrical resistivity and radio frequency characteristics means that the direct current resistance and signal transmission properties of the printed Ag circuit. Flexibility of the screen printed Ag circuit was evaluated by measuring of electrical behavior during IPC sliding test. Failure mode of the Ag printed circuits was observed by using field emission scanning electron microscope and optical microscope. Electrical resistivity of the Ag circuits screen printed on Pl substrate was rapidly decreased with increasing sintering temperature and durations. The lowest electrical resistivity of Ag printed circuit was up to $3.8{\mu}{\Omega}{\cdot}cm$ at $250^{\circ}C$ for 45 min. The crack length arisen within the printed Ag circuit after $10{\times}10^4$ sliding numbers was 10 times longer than that of after $2.5{\times}10^4$ sliding numbers. Measured insertion loss and calculated insertion loss were in good agreements each other. Insertion loss of the printed Ag circuit was increased with increasing the number of sliding cycle.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.16 no.7
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• pp.4828-4834
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• 2015

From the moment that a firing pin triggers the detonator to the moment that a grenade leaves a barrel is called Action Time. Since a loading and percussion of 40mm grenade happens simultaneously, action time should be within a certain time in order to prevent a Jamming malfunction. Previously, unreliable action time device of 40mm grenade made it difficult to improve quality assurance of K4 Grenade Machine Gun. Here, various sensors were compared and a special device was designed to seek an accurate measurement on action time. In this device, the gap between a signal from an optical sensor in Firing Pin and that from Eddy current probe in the barrel was recorded and data were sent to a computer in real time. Confirming if action time is within the criteria, it is expected that action time plays an important role in quality assurance on 40mm grenade.

• Korean Journal of Optics and Photonics
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• v.7 no.3
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• pp.251-259
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• 1996

Two-Photon Fluorescence (TPF) experiment measures temporal width of an amplified short laser pulse which has passed through a four-pass Nd: glass amplifier, after selecting a single pulse from pulse train Q-switched and mode-locked(QSML) in Nd:YLF master oscillator. Determination of pulsewidth and pulseshape was also made with detection of autocorrelation trace of CW mode-locked pulse train by using noncollinear type I Second Harmonic Generation (SHG) method. The observed TPF track showed various patterns, depending on pulse-selecting position in QSML pulse train. That is, autocorrelation of a pulse extracted at front of the train displayed smooth pulse shape, while one from the trailing part of the train created many sharp spikes and substructure in the pulse. By TPF method, pulsewidth was measured to be 44.4 ps with contrast ratio of 2.86 which enabled us to find out energy fraction of a pulse to total energy, (sum of pulse and background); we obtain the value of 0.62. Pulsewidth of 46.6ps was also acquired in another SHG experiment with the help of only mode-locked pulse train. On the other hand, we confirmed that shape of the pulse is close to $sech^2$ one as a result of fitting the SHG autocorrelation signal with various functions. With simulation using this $sech^2$ type of pulse, pulsewidth reduction of the beam, having passed through four-pass amplifier, was also verified.

• Korean Journal of Optics and Photonics
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• v.7 no.3
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• pp.213-218
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• 1996

An improved crystal rotation method with increased accuracy and range is proposed and experimentally verified for simultaneous measurement of molecular tilt angle and thickness of LC (liquid crystal) layer of an LC cell. The improvement is brought about by direct determination of difference between phases instead of intensities of two components of orthogonal linear polarization of the light passing through an LC cell filled with uniformly oriented molecules. By comparing the experimental data with theoretical result the thickness and pretilt angle are determined more precisely. Further improvement is brought about by use of a liquid gate filled with an index matching liquid in which the LC cell is immersed. Because of the index matching liquid reflection of light at the surfaces of an LC cell almost completely disappears and the range of angle of refraction in the LC layer increases significantly, which gives rise to increased signal to noise ration as well as decreased statistical error. With this improvement precise measurement for either very thin (<10 ${\mu}{\textrm}{m}$) and/or higher pretilt angle($\geq$10$^{\circ}$) LC cells become possible.

• Proceedings of the KSRS Conference
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• 1999.11a
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• pp.148-153
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• 1999

Baikdu-san was a very active volcano during the Cenozoic era and is believed to be formed in late Cenozoic era. Recently it was also reported that there was a major eruption in or around 1002 A.D. and there are evidences which indicate that it is still an active volcano and a potential volcanic hazard. Remote sensing techniques have been widely used to monitor various natural hazards, including volcanic hazards. However, during an active volcanic eruption, volcanic ash can basically cover the sky and often blocks the solar radiation preventing any use of optical sensors. Synthetic aperture radar(SAR) is an ideal tool to monitor the volcanic activities and lava flows, because the wavelength of the microwave signal is considerably longer that the average volcanic ash particle size. In this study we have utilized several sets of SAR data to evaluate the utility of the space-borne SAR system. The data sets include JERS-1(L-band) SAR, and RADARSAT(C-band) data which included both standard mode and the ScanSAR mode data sets. We also utilized several sets of auxiliary data such as local geological maps and JERS-1 OPS data. The routine preprocessing and image processing steps were applied to these data sets before any attempts of classifying and mapping surface geological features. Although we computed sigma nought ($\sigma$$^{0}$) values far the standard mode RADARSAT data, the utility of sigma nought image was minimal in this study. Application of various types of classification algorithms to identify and map several stages of volcanic flows was not very successful. Although this research is still in progress, the following preliminary conclusions could be made: (1) sigma nought (RADARSAT standard mode data) and DN (JERS-1 SAR and RADARSAT ScanSAR data) have limited usefulness for distinguishing early basalt lava flows from late trachyte flows or later trachyte flows from the old basement granitic rocks around Baikdu-san volcano, (2) surface geological structure features such as several faults and volcanic lava flow channels can easily be identified and mapped, and (3) routine application of unsupervised classification methods cannot be used for mapping any types of surface lava flow patterns.

• The Journal of the Acoustical Society of Korea
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• v.30 no.1
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• pp.33-41
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• 2011

To substitute TLS in the hybrid system which is combined with Sagnac interferometer and fiber bragg grating (FBG) it is necessary to investigate how the laser source (TLS and CW) and sensor material variate the response of fiber optic sensor. Two different hollow cylinder type mandrel materials are proposed which are PTFE and PTFE+carbon and 18 m optical fiber is wounded at the mandrel surface. CW laser source experiments had been done in the oil tank which is filled with transformer oil in the 1 kHz~20 kHz frequency range. Also Sagnac interferometer fiber optic sensor is combined with FBG called hybrid system and TLS used as a light source. Based on the experimental results PTFE sensor showed more higher magnitude of detection signal rather than carbon sensor and this result is agreement with the McMahon's theoretical results. Phase variation is inversely proportional to the elastic modulus of the mandrel material. In PTFE fiber sensor, tunable laser source showed more higher performance rather than CW case. Therefore, TLS fiber optic sensor can be applied to the hybrid system which is combined with Sagnac and FBG.

• Current Optics and Photonics
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• v.4 no.1
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• pp.31-43
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• 2020

The feasibility of the application of terahertz electromagnetic waves in the diagnosis of prostate cancer was examined. Four samples of incomplete cancerous prostatic paraffin-embedded tissues were examined using terahertz spectral imaging (TPI) system and the results obtained by comparing the absorption coefficient and refractive index of prostate tumor, normal prostate tissue and smooth muscle from one of the paraffin tissue masses examined were reported. Three hundred and sixty cases of absorption coefficients from one of the paraffin tissues examined were used as raw data to classify these three tissues using the Principal Component Analysis (PCA) and Least Squares Support Vector Machine (LS-SVM). An excellent classification with an accuracy of 92.22% in the prediction set was achieved. Using the distribution information of THz reflection signal intensity from sample surface and absorption coefficient of the sample, an attempt was made to use the TPI system to identify the boundaries of the different tissues involved (prostate tumors, normal and smooth muscles). The location of three identified regions in the terahertz images (frequency domain slice absorption coefficient imaging, 1.2 THz) were compared with those obtained from the histopathologic examination. The tissue tumor region had a distinctively visible color and could well be distinguished from other tissue regions in terahertz images. Results indicate that a THz spectroscopy imaging system can be efficiently used in conjunction with the proposed advanced computer-based mathematical analysis method to identify tumor regions in the paraffin tissue mass of prostate cancer.