• Korean Journal of Soil Science and Fertilizer
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• v.44 no.5
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• pp.944-958
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• 2011

Soil hydraulic properties such as hydraulic conductivity or water retention which are costly to measure can be indirectly generated by soil pedotransfer function (PTF) using easily obtainable soil data. The field soil structure description which is routinely recorded could also be used in PTF as an input to reduce the uncertainty. The purposes of this study were to use qualitative morphological soil structure descriptions and soil structural index into PTF and to evaluate their contribution in the prediction of soil hydraulic properties. We transformed categorical morphological descriptions of soil structure into quantitative values using categorical principal component analysis (CATPCA). This approach was tested with a large data set from the US National Pedon Characterization database with the aid of a categorical regression tree analysis. Six different PTFs were used to predict the saturated hydraulic conductivity and those results were averaged to quantify the uncertainty. Quantified morphological description was successively used in multiple linear regression approach to predict the averaged ensemble saturated conductivity. The selected stepwise regression model with only the transformed morphological variables and structural index as predictors predicted the $K_{sat}$ with $r^2$ = 0.48 (p = 0.018), indicating the feasibility of CATPCA approach. In a regression tree analysis, soil structure index and soil texture turned out to be important factors in the prediction of the hydraulic properties. Among structural descriptions size class turned out to be an important grouping parameter in the regression tree. Bulk density, clay content, W33 and structural index explained clusters selected by a two step clustering technique, implying the morphologically described soil structural features are closely related to soil physical as well as hydraulic properties. Although this study provided relatively new method which related soil structure description to soil structure index, the same approach should be tested using a datasets containing the actual measurement of hydraulic properties. More insight on the predictive power of soil structure index to estimate hydraulic properties would be achieved by considering measured the saturated hydraulic conductivity and the soil water retention.

• Journal of Nuclear Fuel Cycle and Waste Technology(JNFCWT)
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• v.16 no.4
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• pp.441-454
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• 2018

Since the permanent shutdown of Kori Unit 1 in 2017, a full-scale decommissioning project for a commercial nuclear reactor has been approaching. It is estimated that about 160,000 t of low-activity concrete waste will be produced from decommissioning of one unit of this commercial nuclear power reactor. Accordingly, it is necessary to review whether the effectiveness of the current regulatory framework for clearance waste (i.e. waste stream that meets activity concentration guidelines or dose criteria for clearance set forth in NSSC Notice No. 2017-65) can be maintained for the clearance of a bulk amount of concrete waste. In this regard, the IAEA SRS No. 44, which was used as a basis for revision of the Korean clearance regulations, is thoroughly analyzed and the radiological effects from four different clearance scenarios, along with input values and parameters derived from industrial practices in Korea, were evaluated. Though it is shown that the maximum annual dose from most recycling scenarios will be less than the clearance dose criterion for the normal scenario (i.e. an order of magnitude of $0.01mSv{\cdot}y^{-1}$), the radiation dose, estimated with conservative assumptions for the banking scenario, may exceed the above clearance dose criteria. Therefore, for safe and sustainable clearance of the bulk amount of concrete waste, it is required to diversify the concrete waste processors, perform more detailed site-specific assessment, and apply limiting conditions to the banking scenario.

• Journal of IKEEE
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• v.22 no.4
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• pp.1006-1011
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• 2018

This paper proposes a three level buck converter utilizing multi-bit flying capacitor voltage control. The conventional three-level buck converter can not control the flying capacitor voltage, so that the operation is unstable or the circuit for controlling the flying capacitor voltage can not be applied to the PWM mode. Also when the load current is increased, an error occurs in the inductor voltage. The proposed structure can control the flying capacitor voltage in PWM mode by using differential difference amplifier and common mode feedback circuit. In addition, this paper proposes a 3bit flying capacitor voltage control circuit to optimize the operation of the three level buck converter depending on the load current, and a triangular wave generation circuit using the schmitt trigger circuit. The proposed 3-level buck converter is designed in $0.18{\mu}m$ CMOS process and has an input voltage range of 2.7V~3.6V and an output voltage range of 0.7V~2.4V. The operating frequency is 2MHz, the load current range is 30mA to 500mA, and the output voltage ripple is measured up to 32.5mV. The measurement results show a maximum power conversion efficiency of 85% at a load current of 130 mA.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2014.10a
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• pp.565-568
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• 2014

This paper presents a 0.2V DC/DC boost converter with regulated output for thermoelectric energy harvesting. To use low voltages from a thermoelectric device, a start-up circuit consisting of native NMOS transistors and resistors boosts an internal VDD, and the boosted VDD is used to operate the internal control block. When the VDD reaches a predefined value, a detector circuit makes the start-up block turn off to minimize current consumption. The final boosted VSTO is achieved by alternately operating the sub-boost converter for VDD and the main boost converter for VSTO according to the comparator outputs. When the VSTO reaches 2.4V, a buck converter starts to operate to generate a stabilized output VOUT. Simulation results shows that the designed converter generates a regulated 1.8V output from an input voltage of 0.2V, and its maximum power efficiency is 60%. The chip designed using a $0.35{\mu}m$ CMOS process occupies $1.1mm{\times}1.0mm$ including pads.

• Journal of IKEEE
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• v.23 no.1
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• pp.35-43
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• 2019

A capacitor self-calibration is proposed to improve the linearity of the capacitor digital-to-analog converter (CDAC) for an asynchronous successive approximation register (SAR) analog-to-digital converter (ADC) with 10-bit resolution. The proposed capacitor self-calibration is performed so that the value of each capacitor of the upper 5 bits of the 10-bit CDAC is equal to the sum of the values of the lower capacitors. According to the behavioral simulation results, the proposed capacitor self-calibration improves the performances of differential nonlinearity (DNL) and integral nonlinearity (INL) from -0.810/+0.194 LSBs and -0.832/+0.832 LSBs to -0.235/+0.178 LSBs and -0.227/+0.227 LSBs, respectively, when the maximum capacitor mismatch of the CDAC is 4%. The proposed 10-bit 20-MS/s asynchronous SAR ADC is implemented using a 110-nm CMOS process with supply of 1.2 V. The area and power consumption of the proposed asynchronous SAR ADC are $0.205mm^2$ and 1.25 mW, respectively. The proposed asynchronous SAR ADC with the capacitor calibration has a effective number of bits (ENOBs) of 9.194 bits at a sampling rate of 20 MS/s about a $2.4-V_{PP}$ differential analog input with a frequency of 96.13 kHz.

• Journal of the Korea Computer Graphics Society
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• v.27 no.3
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• pp.65-74
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• 2021

3D reconstruction means that reconstructing the 3D shape of the object in an image and a video. We proposed a progressive occupancy network architecture that can recover not only the overall shape of the object but also the local details. Unlike the original occupancy network, which uses a feature vector embedding information of the whole image, we extract and utilize the different levels of image features depending on the receptive field size. We also propose a novel network architecture that applies the image features sequentially to the decoder blocks in the decoder and improves the quality of the reconstructed 3D shape progressively. In addition, we design a novel decoder block structure that combines the different levels of image features properly and uses them for updating the input point feature. We trained our progressive occupancy network with ShapeNet. We compare its representation power with two prior methods, including prior occupancy network(ONet) and the recent work(DISN) that used different levels of image features like ours. From the perspective of evaluation metrics, our network shows better performance than ONet for all the metrics, and it achieved a little better or a compatible score with DISN. For visualization results, we found that our method successfully reconstructs the local details that ONet misses. Also, compare with DISN that fails to reconstruct the thin parts or occluded parts of the object, our progressive occupancy network successfully catches the parts. These results validate the usefulness of the proposed network architecture.

• Smart Media Journal
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• v.9 no.4
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• pp.102-108
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• 2020

In this paper, we propose a real-time method of detecting hand motions and extracting the signal frame induced by EF(Electric Field) sensors. The signal induced by hand motion includes not only noises caused by various environmental sources as well as sensor's physical placement, but also different initial off-set conditions. Thus, it has been considered as a challenging problem to detect the motion signal and extract the motion frame automatically in real-time. In this study, we remove the PLN(Power Line Noise) using LPF with 10Hz cut-off and successively apply MA(Moving Average) filter to obtain clean and smooth input motion signals. To sense a hand motion, we use two thresholds(positive and negative thresholds) with offset value to detect a starting as well as an ending moment of the motion. Using this approach, we can achieve the correct motion detection rate over 98%. Once the final motion frame is determined, the motion signals are normalized to be used in next process of classification or recognition stage such as LSTN deep neural networks. Our experiment and analysis show that our proposed methods produce better than 98% performance in correct motion detection rate as well as in frame-matching rate.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.26 no.8
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• pp.1213-1221
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• 2022

In Electronic Warfare, the need to develop a jamming system that protects our location information from enemy radar is constantly increasing. The jamming system normally uses wide-band DRFM(Digital Radio Frequency Memory) that processes the entire bandwidth at once. However, it is difficult to jam if there is a CW(Continuous Wave) interference signal in the band. Recently, instead of wide-band signal processing, a structure using a filter bank that divides the entire band into several sub-bands and processes each sub-band independently has been proposed. Although it is possible to handle interference signal through the filter bank structure, spurious signal occurs when the signal is received at a boundary frequency between sub-bands. Spurious signal makes a output power of jamming signal distributed, resulting in lower JSR(Jamming to Signal Ratio) and less jamming effect. This paper proposes an over-sampled channelized DRFM structure that enables interference response and prevents spurious signal for sub-band boundary frequency input.

• Journal of the Korea Society for Simulation
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• v.31 no.4
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• pp.23-31
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• 2022

The development of innovative technology through the 4th Industrial Revolution is actively used in the defense field. In particular, surveillance and reconnaissance capabilities using drones will be of great help to the development of military combat capabilities, such as preparing for future military personnel reductions and reinforcing alert capabilities. In this study, we analyze the combat efficiency of drones how helpful drones can be to the military operations through simulations. Drones and enemy move in the efficient shortest path within a two-dimensional space in which operational areas are mapped into number such as detection probability. Based on the detection probability of an enemy infiltrating along the path with the lowest detection probability, the detection probability change that occurs whenever a drone is additionally deployed is presented, and we analyze the combat efficiency according to the additional drone input. Simulation proves that the increase in combat efficiency decreases as more drones are added in small operational areas such as company-level operational areas. This study is expected to contribute to the efficient operation of a limited number of drones in company-level units and to help determine the most desirable quantity of drones for additional combat power improvement.

• Ecology and Resilient Infrastructure
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• v.10 no.1
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• pp.11-19
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• 2023

Alien species are known to threaten regional biodiversity globally, which has increased global interest regarding introduction of alien species. The Ministry of Environment of Korea designated species that have not yet been introduced into the country with potential threat as alert alien species to prevent damage to the ecosystem. In this study, potential habitats of Esox lucius and Maccullochella peelii, which are predatory and designated as alert alien fish, were predicted on a national basis. Habitat suitability was evaluated using EHSM (Ecological Habitat Suitability Model), and water temperature data were input to calculate Physiological Habitat Suitability (PHS). The prediction results have shown that PHS of the two fishes were mainly controlled by heat or cold stress, which resulted in biased habitat distribution. E. lucius was predicted to prefer the basins at high latitudes (Han and Geum River), while M. peelii preferred metropolitan areas. Through these differences, it was expected that the invasion pattern of each alien fish can be different due to thermal preference. Further studies are required to enhance the model's predictive power, and future predictions under climate change scenarios are required to aid establishing sustainable management plans.