• 생태와환경
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• 제56권2호
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• pp.161-171
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• 2023

Simocephalus spp.는 수생식물이 발달한 호소의 수변부 및 습지 서식처에서 우점 출현하는 중대형 지각류로, 해당 서식처의 동물플랑크톤 군집 생체량(biomass)에 기여하는 정도가 높아 먹이망 내 생물학적 상호작용을 기반으로 한 물질 순환을 이해하기 위해서는 Simocephalus종들의 생체량 산정이 중요하다. 본 연구에서는 S. serrulatus의 생체량 추정에 사용되어지고 있던 기존의 선행 산정식을 검토하고, 현미경 디지털 카메라와 미세 저울 같은 장비를 사용하여 개체의 다양한 체측값(체장, 너비 및 면적)과 생체량(건중량)을 직접 측정하여 상호 간 회귀 분석을 실시하였다. 국내 『생물측정망 조사 및 평가지침 - 보구간편』에서 제시하고 있는 Simocephalus spp.의 생체량 산정식(Kawabata and Urabe, 1998)을 사용하여 S. serrulatus 생체량을 추정했을 때, Lemke and Benke (2003)에 의해 개발된 S. serrulatus종 특이적 생체량 산정식 대비 추정치-실측치 간 오차가 상대적으로 크게 나타났으며, 두 산정식에서 모두 개체 체장 증가에 따른 오차 증가 및 유사 체장 개체 간 오차 편차 증가 경향이 보여졌다. 체측값별로 건중량과 회귀 분석을 실시한 결과, S. serrulatus 생체량 추정에 가장 적합한 산정식은 너비-건중량 지수 회귀식(R²=0.9555)으로 도출되었다. 이 같은 종 특이적 생체량 산정식의 검토 및 개발 연구는 수생태계 먹이망 내 동물플랑크톤 역할 및 기능 파악하는 데 도구(tool)로써 활용될 수 있다.

• 국제학술발표논문집
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• The 9th International Conference on Construction Engineering and Project Management
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• pp.752-759
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• 2022

The instantiation of spaces as a discrete entity allows users to utilize BIM models in a wide range of analyses. However, in practice, their utility has been limited as spaces are erroneously entered due to human error and often omitted entirely. Recent studies attempted to automate space allocation using artificial intelligence approaches. However, there has been limited success as most studies focused solely on the use of geometric features to distinguish spaces. In this study, in addition to geometric features, semantic relations between spaces and elements were modeled and used to improve space classification in BIM models. Graph Convolutional Networks (GCN), a deep learning algorithm specifically tailored for learning in graphs, was deployed to classify spaces via a similarity graph that represents the relationships between spaces and their surrounding elements. Results confirmed that accuracy (ACC) was +0.08 higher than the baseline model in which only geometric information was used. Most notably, GCN was able to correctly distinguish spaces with no apparent difference in geometry by discriminating the specific elements that were provided by the similarity graph.

• 대한전자공학회논문지TC
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• 제43권10호
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• pp.69-78
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• 2006

채널환경에 따라 변조방식이 가변되는 적응변조에 의해 높은 대역효율을 얻을 수 있다. 그러므로 시간에 따라 채널이 바뀌는 이동통신 채널에는 특히 적응변조가 적합하다. 이동체의 속도에 따라 적절하게 변조방법을 바꾸기 위해서는 신호대 잡음비의 최적 문턱값을 결정하여야 한다. 따라서 본 논문에서는 특정 이동체의 속도에 대하여 터보부호를 사용할 경우 요구 비트오율 $10^{-6}$을 얻을 수 있는 최적 문턱값을 결정한다. 이를 바탕으로 보간법에 의해서 이동체의 연속적인 속도에 대한 최적 문턱값을 제안한다. 그리고 다양한 이동체의 속도와 채널환경에 대해 그 오류성능 및 대역효율을 분석한다.

• 한국전자파학회논문지
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• 제21권3호
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• pp.321-330
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• 2010

본 논문에서는 컴프레시브 RFID 신호를 탐지하기 위한 컴프레시브 수신기의 이론적 배경과 구체적 구현 방법, 그리고 분산 지연선과 chirp LO의 설계 방안에 대해 기술하였다. 컴프레시브 수신기의 주요 구성품 중 하나인 분산 지연선을 대역폭 6 MHz, 분산 지연 시간 $13{\mu}s$으로 설계하여 $LiNbO_3$ 재질 기반의 SAW(Surface Acoustic Wave) 기술을 통해 구현하였고, DDS(Direct Digital Synthesizer)를 이용하여 chirp LO를 구현하였다. 또한 RFID 리더에 내장되어 연동될 수 있도록 컴프레시브 수신기를 구성하였다. 시험 결과, 단일 신호 입력시 주파수 오차는 최대 25 kHz, 수신 감도는 -44 dBm, 500 kHz 간격으로 동시에 입력되는 6개의 신호에 대한 주파수 오차는 최대 75 kHz로서 제작된 컴프레시브 수신기가 밀집된 RFID 운영 환경에 적합함을 보였다.

• 한국컴퓨터정보학회논문지
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• 제27권11호
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• pp.47-55
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• 2022

최근 우리나라에서도 인공지능 모델을 이용한 수온예측 관련 연구가 활발히 진행되고 있으나 한반도 주변 해역의 수온을 예측한 대부분의 연구는 주로 해수면 온도 예측에 중점을 두고 진행되었다. 반면 본 연구는 XBT(eXpendable Bathythermograph, 소모성 연직수온측정기) 데이터와 기계 학습 모델(RandomForest, XGBoost, LightGBM)을 사용하여 잠수함 작전 및 대잠전(Anti-Submarine Warfare)에 있어서 군사적으로 중요한 동해의 수직 수온분포를 예측하였다. 동해 특정해역의 해수면부터 수심 200m까지 측정된 XBT 데이터를 이용하여 모델을 학습시키고 절대 평균 오차(MAE, Mean Absolute Error)와 수직 수온분포 그래프를 통해 예측정확도를 평가하였다.

• 농업과학연구
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• 제51권1호
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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.

• 대한원격탐사학회지
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• 제26권3호
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• pp.297-304
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• 2010

Since the change in Doppler centroid according to moving targets brings alteration to the phase in azimuth differential signals of synthetic aperture radar (SAR) data, one can measure the velocity of the moving targets using this effect. In this study, we will investigate theoretically measuring the velocity of an object from azimuth differential signals by using range compressed data which is the interim outcome of treatment from the simulated SAR raw data of moving targets on the background of sea clutter. Also, it will provide evaluation for the elements that affect the estimation error of velocity from a single SAR sensor. By making RADARSAT-1 simulated image as a specific case, the research includes comparisons for the means of velocity measurement classified by the directions of movement in the four following cases. 1. A case of a single target without currents, 2. A case of a single target with tidal currents of 0.5 m/s, 1 m/s, and 3 m/s, 3. A case of two targets on a same azimuth line moving in a same direction and velocity, 4. A case of a single target contiguous to land where radar backscatter is strong. As a result, when two moving targets exist in SAR image outside the range of approximately 256 pixels, the velocity of the object can be measured with high accuracy. However, when other moving targets exist in the range of approximately 128 pixels or when the target was contiguous to the land of strong backscatter coefficient (NRCS: normalized radar cross section), the estimated velocity was in error by 10% at the maximum. This is because in the process of assuming the target's location, an error occurs due to the differential signals affected by other scatterers.

• BMB Reports
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• 제33권3호
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• pp.268-275
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• 2000

In contrast to the pyrimidine (6-4)pyrimidone photoproduct [(6-4) adduct], its Dewar valence isomer (Dewar product) is low mutagenic and produces a broad range of mutations with a 42 % replicating error frequency. In order to determine the origin of the mutagenic property of the Dewar product, we used experimental NMR restraints and molecular dynamics to determine the solution structure of a Dewar·lesion DNA decamer duplex, which contains a mismatched base pair between the 3'-T residue and an opposed G residue. The 3'-T of the Dewar lesion forms stable hydrogen bonds with the opposite G residue. The helical bending and unwinding angles of the DW/GA duplex, however, are much higher than those of the DW/AA duplex. The stable hydrogen bonding of the G 15 residue does not increase the thermal stability of the overall helix. It also does not restore the distorted backbone conformation of the DNA helix that is caused by the forming of a Dewar lesion. These structural features implicate that no thermal stability, or conformational benefits of G over A opposite the 3'-T of the Dewar lesion, facilitate the preferential incorporation of an A. This is in accordance with the A rule during translesion replication and leads to the low frequent $3'-T{\rightarrow}C$ mutation at this site.

• Food Science and Biotechnology
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• 제15권5호
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• pp.715-720
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• 2006

This study was performed to develop a predictive model for the growth kinetics of Listeria monocytogenes in tryptic soy broth (TSB) using a response surface model with a combination of potassium lactate (PL), temperature, and pH. The growth parameters, specific growth rate (SGR), and lag time (LT) were obtained by fitting the data into the Gompertz equation and showed high fitness with a correlation coefficient of $R^2{\geq}0.9192$. The polynomial model was identified as an appropriate secondary model for SGR and LT based on the coefficient of determination for the developed model ($R^2\;=\;0.97$ for SGR and $R^2\;=\;0.86$ for LT). The induced values that were calculated using the developed secondary model indicated that the growth kinetics of L. monocytogenes were dependent on storage temperature, pH, and PL. Finally, the predicted model was validated using statistical indicators, such as coefficient of determination, mean square error, bias factor, and accuracy factor. Validation of the model demonstrates that the overall prediction agreed well with the observed data. However, the model developed for SGR showed better predictive ability than the model developed for LT, which can be seen from its statistical validation indices, with the exception of the bias factor ($B_f$ was 0.6 for SGR and 0.97 for LT).

• 제어로봇시스템학회논문지
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• 제19권5호
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• pp.416-422
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• 2013

This paper suggests a hybrid path planning method of multi-robots, where a path deviation prevention for maintaining a specific formation is implemented by using repulsive function, $A^*$ algorithm and UKF (Unscented Kalman Filter). The repulsive function in potential field method is used to avoid collision among robots and obstacles. $A^*$ algorithm helps the robots to find optimal path. In addition, error estimation based on UKF guarantees small path deviation of each robot during navigation. The simulation results show that the swarm robots with designated formation successfully avoid obstacles and return to the assigned formation effectively.