• 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.

• Journal of Convergence for Information Technology
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• v.12 no.5
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• pp.51-61
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• 2022

The purpose of this study was to identify whether need of cognition have a mediating effect on media multitasking on learning engagement in online education. The subjects were 168 university students who had received online education for more than one semester, and data were collected using questionnaires on media multitasking, need of cognition, and learning engagement. For data analysis, correlation, hierarchical regression and Sobel test were performed using SPSS WIN 20.0 program. As a result of the study, there was a significant positive correlation between media multitasking and learning engagement (r=.52, p<.001), and a between need of cognition and learning engagement(r=.39, p<.001). Media multitasking had a significant effect on learning participation (β=.52, p<.001), and explanatory power was 27%. When need of cognition was input, the effect of media multitasking on learning engagement decreased (β=.52 ⟶ .44), so it was found that need of cognition had a partial mediating effect in the effect of media multitasking on learning engagement(Z=2.77). p<.01). Therefore, it is suggested to use online contents with learning to organizing a g a lesson syllabus for distance education, and to organize activities promoting media multitasking activities. Also, it is proposed to develop and apply various teaching strategies to promoting the need of cognition in the distance education.

• KIPS Transactions on Software and Data Engineering
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• v.12 no.3
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• pp.133-140
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• 2023

The performance of lithium ion batteries depends on the usage environment and the combination ratio of cathode materials. In order to develop a high-performance lithium-ion battery, it is necessary to manufacture the battery and measure its performance while varying the cathode material ratio. However, it takes a lot of time and money to directly develop batteries and measure their performance for all combinations of variables. Therefore, research to predict the performance of a battery using an artificial intelligence model has been actively conducted. However, since measurement experiments were conducted with the same battery in the existing published battery data, the cathode material combination ratio was fixed and was not included as a data attribute. In this paper, we define a training data model required to develop an artificial intelligence model that can predict battery performance according to the combination ratio of cathode materials. We analyzed the factors that can affect the performance of lithium-ion batteries and defined the mass of each cathode material and battery usage environment (cycle, current, temperature, time) as input data and the battery power and capacity as target data. In the battery data in different experimental environments, each battery data maintained a unique pattern, and the battery classification model showed that each battery was classified with an error of about 2%.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2021.10a
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• pp.630-633
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• 2021

Microphones can convert received voice signals to electric signals. They have been widely used in various industries such as radios, smart devices and vehicles. Recently, the demands for small size and high sensitive microphones are increased according to the minimization of wireless earphone with the development of smart phone. A MEMS system is a good candidate for an ultra-small size microphone of a next generation and a read out IC for high sensitive MEMS sensor is researched from many industries and academies. Since the microphone system has a high sensitivity from environment noise and electric system noise, the system requires a low noise power supply and some low noise design techniques. In this paper, a low noise LDO is presented for small size MEMS microphone systems. The input supply voltage of the LDO is 1.5-3.6V, and the output voltage is 1.3V. Then, it can support to 5mA in the light load condition. The integrated output noise of proposed LDO form 20Hz to 20kHz is about 1.9uV. These post layout simulation results are performed with TSMC 0.18um CMOS technology and the size of layout is 325㎛ × 165㎛.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.26 no.5A
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• pp.901-908
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• 2006

The structural integrity of containment building in Nuclear Power Plants has to be verified by the ISI(In Service Inspection) because there are some variations on the structural behavior of it due to the change of the physical properties of concrete and tendon with the lapse of time. In this study, the program 'SAPONC-CANDU' which can monitor and analyze the structural behavior of the containment building with grouted tendon (CANDU-type, 'Wolsong unit-2, 3, and 4' in Korea) was developed. This program is based on the algorithm which can calculate the prediction values of the quantities of strain variation for the vibrating-wire strain gauges embedded into the concrete of the containment building under temperature and time dependent factors which are creep, shrinkage, and prestressing force. The readings of the strain gauges are used as input data for the operation of the program. And it finally provides graphically a prediction value, line and band of the quantity of strain variation for the respective strain gauges, therefore, it is thought that the site engineers are able to assess the structural integrity of the domestic containment building with grouted tendon with easy using this program.