• 한국해양공학회지
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• 제38권4호
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• pp.187-198
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• 2024

Autonomous underwater vehicles (AUVs) have a limited bandwidth for real-time communication, limiting rapid responses to unexpected obstacles. This study addressed how AUVs can navigate to a target without a pre-existing obstacle map by generating one in real-time and avoiding obstacles. This paper proposes using forward-looking sonar with an occupancy grid map (OGM) for real-time obstacle mapping and a potential field algorithm for avoiding obstacles. The OGM segments the map into grids, updating the obstacle probability of each cell for precise, quick mapping. The potential field algorithm attracts the AUV towards the target and uses repulsive forces from obstacles for path planning, enhancing computational efficiency in a dynamic environment. Experiments were conducted in coastal waters with obstacles to verify the real-time obstacle mapping and avoidance algorithm. Despite the high noise in sonar data, the experimental results confirmed effective obstacle mapping and avoidance. The OGM-based potential field algorithm was computationally efficient, suitable for single-board computers, and demonstrated proper parameter adjustments through two distinct scenarios. The experiments also identified some of challenges, such as dynamic changes in detection rates, propulsion bubbles, and changes in repulsive forces caused by sudden obstacles. An enhanced algorithm to address these issues is currently under development.

• The Journal of Korean Physical Therapy
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• 제24권4호
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• pp.262-267
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• 2012

Purpose: This study was designed to analyze the differences in cerebral cortex activity of the elderly after extracting the movement related cortical potentials (MRCPs) from electroencephalogram (EEG) during a concentric and eccentric contraction of the elbow joint flexors, and entering them into the brain-mapping program to make the images. Methods: Right-dominant normal elderly people were divided into an eccentric contraction group and a concentric contraction group. Then, their MRCPs were measured using EEG and sEMG, during an eccentric and concentric contraction. Then, they were converted into images using the brain-mapping program. Results: Eccentric contraction group's $C_3$ and Cz showed statistically higher mean values of MRCP positive potential than the concentric contraction group. Conclusion: Researching a cerebral cortex activity, using MRCP, would provide basic data for clinical neuro-physiological researches on aging or neural plasticity of patients with a central nervous system injury.

• 한국정보과학회:학술대회논문집
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• 한국정보과학회 2000년도 가을 학술발표논문집 Vol.27 No.2 (1)
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• pp.581-583
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• 2000

We are studied on the performance optimized synthesis and mapping of design on to one or more FPGA device. our multi-phased approach optimized the key parameters that affect performance by adequately modeling the impact on wire length, routability, and performance during technology mapping to produce designs that have high performance and high routability potential.

• 대한수학회논문집
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• 제25권1호
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• pp.27-36
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• 2010

We give a simple proof of certain mapping properties of the p-adic Riesz potential and Bessel potential, and the p-adic version of the Sobolev embedding theorem obtained in [6].

• 대한화학회지
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• 제61권1호
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• pp.12-15
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• 2017

We presented a mapping the work function of the vanadium pentoxide ($V_2O_5$) nanonet structures by scanning Kelvin probe microscopy (SKPM). In this measurement, the $V_2O_5$ nanonet was self-assembled via dropping the solution of $V_2O_5$ nanowires (NWs) onto the $SiO_2$ substrate and drying the solvent, resulting in the networks of $V_2O_5$ NWs. We found that the SKPM signal as a surface potential of $V_2O_5$ nanonet is attributed to the contact potential difference (CPD) between the work functions of the metal tip and the $V_2O_5$ nanonet. We generated the histograms of the CPD signals obtained from the SKPM mapping of the $V_2O_5$ nanonet as well as the highly ordered pyrolytic graphite (HOPG) which is used as a reference for the calibration of the SKPM tip. By using the histogram peaks of the CPD signals, we successfully estimated the work function of ~5.1 eV for the $V_2O_5$ nanonet structures. This work provides a possibility of a nanometer-scale imaging of the work function of the various nanostructures and helps to understand the electrical characteristics of the future electronic devices.

• Annals of Clinical Neurophysiology
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• 제23권2호
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• pp.69-81
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• 2021

Cortico-cortical evoked potential (CCEP) mapping is a rapidly developing method for visualizing the brain network and estimating cortical excitability. The CCEP comprises the early N1 component the occurs at 10-30 ms poststimulation, indicating anatomic connectivity, and the late N2 component that appears at < 200 ms poststimulation, suggesting long-lasting effective connectivity. A later component at 200-1,000 ms poststimulation can also appear as a delayed response in some studied areas. Such delayed responses occur in areas with changed excitability, such as an epileptogenic zone. CCEP mapping has been used to examine the brain connections causally in functional systems such as the language, auditory, and visual systems as well as in anatomic regions including the frontoparietal neocortices and hippocampal limbic areas. Task-based CCEPs can be used to measure behavior. In addition to evaluations of the brain connectome, single-pulse electrical stimulation (SPES) can reflect cortical excitability, and so it could be used to predict a seizure onset zone. CCEP brain mapping and SPES investigations could be applied both extraoperatively and intraoperatively. These underused electrophysiologic tools in basic and clinical neuroscience might be powerful methods for providing insight into measures of brain connectivity and dynamics. Analyses of CCEPs might enable us to identify causal relationships between brain areas during cortical processing, and to develop a new paradigm of effective therapeutic neuromodulation in the future.

• Journal of Biosystems Engineering
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• 제24권2호
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• pp.135-144
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• 1999

An yield monitoring system plays a key role in precision farming. An yield monitoring system and a DGPS were implemented to a widely used domestic combine for yield mapping of a small sized paddy field, and yield mapping algorithms were investigated in this study. The yield variation in the 0.1ha rice paddy field was measured by installing a yield flow sensor and a grain moisture sensor at the end of the clean grain elevator discharging grains into a grain tank. Yield map of the test filed was drawn in a point map and a linear interpolated map based on the result of the field test. The size of a unit yield grid in yield mapping was determined based on the combine traveling speed, effective harvesting width and data storing period. It was possible to construct the yield map of a small sized paddy field.

• Investigative Magnetic Resonance Imaging
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• 제25권4호
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• pp.300-312
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• 2021

Compressed sensing (CS) has been investigated in magnetic resonance (MR) parametric mapping to reduce scan time. However, the relatively long reconstruction time restricts its widespread applications in the clinic. Recently, deep learning-based methods have shown great potential in accelerating reconstruction time and improving imaging quality in fast MR imaging, although their adaptation to parametric mapping is still in an early stage. In this paper, we proposed a novel deep learning-based framework DEMO for fast and robust MR parametric mapping. Different from current deep learning-based methods, DEMO trains the network in an unsupervised way, which is more practical given that it is difficult to acquire large fully sampled training data of parametric-weighted images. Specifically, a CS-based loss function is used in DEMO to avoid the necessity of using fully sampled k-space data as the label, thus making it an unsupervised learning approach. DEMO reconstructs parametric weighted images and generates a parametric map simultaneously by unrolling an interaction approach in conventional fast MR parametric mapping, which enables multi-tasking learning. Experimental results showed promising performance of the proposed DEMO framework in quantitative MR T1ρ mapping.

• 자원환경지질
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• 제40권3호
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• pp.307-318
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• 2007

지열수의 부존은 화석열수계(fossil geothermal system)의 분포와 밀접한 연관성을 가지므로, 활발한 화석열수계에 의한 광역적인 열수변질대가 분포하는 경상분지 남부지역을 대상으로 GIS 공간통합기법을 적용한 지열 부존 잠재력을 탐사하였다. 연구방법은 화석열수계의 기원 및 분포와 관련된 지질 열수변질대, 열수형 광상 분포, 선구조 밀도, 항공자력도 등 주제도를 작성하고, 현행 온천 분포와의 상관성을 파악하여, 공간통합을 실시하였다. 그 결과 퍼지 연산자 중에서는 ${\gamma}$ 연산자(${\gamma}=0.1$)가 가장 높은 성공비율을 나타내었으며, 일부 지역에서 새로운 지열수 부존 가능성이 예상된다.

• 한국산림과학회지
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• 제86권1호
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• pp.25-34
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• 1997

지구상의 잠재삼림면적을 추정하기 위한 일련의 단계로서, 적정한 식생도제작(Global Natural Vegetation Mapping, GNVM) 시스템을 선발하기 위해, Light Climatic Dataset(LCD)에 지형을 고려하지 않은 단순 시스템, LCD에 지형을 고려한 시스템, Heavy Climatic Dataset(HCD)에 지형을 고려한 시스템을 구축하고 상호 비교하였다. 3종류의 GNVM시스템은, 세계에서 관찰된 기후데이타를 구면보간법에 의해 지구면 전체의 $1^{\circ}{\times}1^{\circ}$의 격자점에 대하여 이것을 추정하고, 그 추정치로부터 식생을 구분하며, 구분의 결과를 가지고 잠재자연식생도의 출력 및 잠재자연식생의 면적을 산출한다. 3종류의 GNVM시스템을 비교한 결과, LCD에 지형을 고려한 GNVM 시스템이 잠재자연식생의 분포를 가장 잘 표현하였으며, 단순 시스템은 지형을 고려한 시스템들에 비해 온난한 지역을 과대평가하고 한랭지 및 사막지역을 과소평가하는 경향을 나타냈다. 한편, 측후소의 수에 따른 시스템간에 있어서는 HCD에 지형을 고려한 시스템이 측후소의 과밀분포로 인해 LCD에 지형을 고려한 시스템보다 습윤지역의 과대평가와 건조지역의 과소평가를 나타냈다.