Kim, Hoe-Geun;Song, Myeon-Gyu;Kim, Dong-U;Lee, Sang-Yul
Proceedings of the Korean Institute of Surface Engineering Conference
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2018.06a
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pp.62-62
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2018
Pt is still considered as one of the most active electrocatalysts for ORR in alkaline fuel cells. However, the high cost and scarcity of Pt hamper the widespread commercialization of fuel cells. As a strong candidate for the replacement of Pt catalyst, silver (Ag) has been extensively studied due to its high activity, abundance, and low cost. Ag is more stable than Pt in the pH range of 8~14 as the equilibrium potential of Ag/Ag+ being ${\approx}200mV$ higher than that of Pt/PtO. However, Ag is the overall catalytic activity of Ag for oxygen reduction reaction(ORR) is still not comparable to Pt catalyst since the surface Ag atoms are approximately 10 times less active than Pt atoms. Therefore, further enhancement in the ORR activity of Ag catalysts is necessary to be competitive with current cutting-edge Pt-based catalysts. We demonstrate the architectural design of Ag catalysts, synthesized using plasma discharge in liquid phase, for enhanced ORR kinetics in alkaline media. An attractive feature of this work is that the plasma status controlled via electric-field could form the Ag nanowires or dendrites without any chemical agents. The plasma reactor was made of a Teflon vessel with an inner diameter of 80 mm and a height of 80 mm, where a pair of tungsten(W) electrodes with a diameter of 2 mm was placed horizontally. The stock solutions were made by dissolving the 5-mM AgNO3 in DI water. For the synthesis of Agnanowires, the electricfield of 3.6kVcm-1 in a 200-ml AgNO3 aqueous solution was applied across the electrodes using a bipolar pulsed power supply(Kurita, Seisakusyo Co. Ltd). The repetition rate and pulse width were fixed at 30kHz and 2.0 us, respectively. The plasma discharge was carried out for a fixed reaction time of 60 min. In case of Ag nanodendrites, the electric field of 32kVcm-1 in a 200-ml AgNO3 aqueous solution was applied and other conditions were identical to the plasma discharge in water in terms of electrode configuration, repetition rate and discharge time. Using SEM and STEM, morphology of Ag nanowires and dendrites were investigated. With 3.6 kV/cm, Ag nanowire was obtained, while Ag dendrite was constructed with 32 kV/cm. The average diameter and legth of Ag nanowireses were 50 nm and 3.5 um, and thoes values of Ag dendrites were 40 nm and 3.0 um. As a results of XPS analysis, the surface defects in the Ag nanowires facilitated O2 incorporation into the surface region via the interaction between the oxygen and the electron cloud of the adjacent Ag atoms. The catalytic activity of Ag for oxygen reduction reaction(ORR) showed that the catalytic ORR activity of Ag nanowires are much better than Ag nanodendrites, and electron transfer number of Ag nanowires is similar to that of Pt (${\approx}4$).
Journal of Korean Society for Geospatial Information Science
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v.19
no.2
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pp.3-8
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2011
Recently, the demand for enterprise for service map providing and portal site services of a 3D virtual city model for public users has been expanding. Also, accuracy of the data, transfer rate and the update for the update for the lapse of time emerge are considered as more impertant factors, by providing 3D information with the web or mobile devices. With the latest technology, we have seen various 3D data through the web. With the VRML progressing actively, because it can provide a virtual display of the world and all aspects of interaction with web. It offers installation of simple plug-in without extra cost on the web. LiDAR system can obtain spatial data easily and accurately, as supprted by numerous researches and applications. However, in general, LiDAR data is obtained in the form of an irregular point cloud. So, in case of using data without converting, high processor is needed for presenting 2D forms from point data composed of 3D data and the data increase. This study expresses urban LiDAR data in 3D, 2D raster data that was applied by compressing algorithm that was used for solving the problems of large storage space and processing. For expressing 3D, algorithm that converts compressed LiDAR data into code Suited to VRML was made. Finally, urban area was expressed in 3D with expressing ground and feature separately.
This paper presents a method to segment the object of interest from a set of multi-view images with minimal user interaction. Specifically, after the user segments an initial image, we first estimate the transformations between foreground and background of the segmented image and the neighboring image, respectively. From these transformations, we obtain regions in the neighboring image that respectively correspond to the foreground and the background of the segmented image. We are then able to segment the neighboring image based on these regions, and iterate this process to segment the whole image set. Transformation of foregrounds are estimated by feature-based registration with free-form deformation, while transformation of backgrounds are estimated by homography constrained to affine transformation. Here, both are based on correspondence point pairs. Segmentation is done by estimating pixel color distributions and defining a shape prior based on the obtained foreground and background regions and applying them to a Markov random field (MRF) energy minimization framework for image segmentation. Experimental results demonstrate the effectiveness of the proposed method.
A recurring eddy which located at the terminal end of the Korean East Warm Current was captured on ocean color and sea surface temperature imagery from satellite in spring and autumn. During late April, 1997 thermal infrared imagery from the NOAA AVHRR sensor and ocean color data from the Japanese ADEOS-I OCTS sensor, revealed this feature. The cold core had elevated chlorophyll concentrations, based on OCTS estimates, of greater than 3 mg/m$^3$ while the warmer surrounding waters had chlorophyll concentrations of 1 mg/m$^3$ or less. The elevated cholophyll accociated with this eddy has not been previously described. The eddy is also evident in SST images from autumn, but the SST in the core is warmer than in spring, and the warm jet flowing to the west of the eddy is also warmer is autumn compared to spring. A reccurring eddy and the high chlorophyll_a concentration area which surround around the eddy show on NOAA and SeaWiFS images in March 2, 1998. The eddy forms at the northern extent of the Korean East Warm Current as those waters collide with the cold, south-flowing Liman Current over a topographic shelf about 1500 m deep. This region of the eddy formation appears to have a strong connection with the dynamics of the western part of the polar front eddy field that dominates surface mesoscale structure in the central East (Japan) Sea. Interaction of the eddy with ARGOW tracked drifters, and evidence for its persistence are discussed.
This study aimed to investigate speech motor control in adults who stutter (AWS) by testing whether articulation rate changes with practice and linguistic complexity. Eleven AWS and 11 adults who do not stutter (AWNS) repeated four sentences of different lengths and syntactic complexity [simple-short (SS), simple-long (SL), complex-long (CL), and faulty-long (FL) sentences]. Overall articulation rates of each sentence were measured and compared between groups. Practice effects were evaluated by comparing the articulation rates of the first three, middle four, and last three productions. Overall, the AWS had significantly slower articulation rates than AWNS across the four sentences. The longer sentences showed significantly slower articulation rates than the baseline sentence (SS). The articulation rates of the middle four and the last three productions were significantly faster than those of the first three productions of each sentence in both groups. The articulation rates of the SS, SL, and CL sentences indicated a consistent practice effect. The slower articulation rates of the AWS are consistent with a speech motor limitation. There was no interaction with linguistic complexity or practice, so a slower articulation rate may be a general feature of the speech of AWS. Both AWS and AWNS showed practice effects with faster articulation rates which may reflect a degree of adaptation to the stimuli.
KIPS Transactions on Software and Data Engineering
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v.10
no.11
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pp.457-464
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2021
The advent of the big data era has enabled the rapid development of deep learning that learns rules by itself from data. In particular, the performance of CNN algorithms has reached the level of self-adjusting the source data itself. However, the existing image processing method only deals with the image data itself, and does not sufficiently consider the heterogeneous environment in which the image is generated. Images generated in a heterogeneous environment may have the same information, but their features may be expressed differently depending on the photographing environment. This means that not only the different environmental information of each image but also the same information are represented by different features, which may degrade the performance of the image analysis model. Therefore, in this paper, we propose a method to improve the performance of the image color constancy model based on Adversarial Learning that uses image data generated in a heterogeneous environment simultaneously. Specifically, the proposed methodology operates with the interaction of the 'Domain Discriminator' that predicts the environment in which the image was taken and the 'Illumination Estimator' that predicts the lighting value. As a result of conducting an experiment on 7,022 images taken in heterogeneous environments to evaluate the performance of the proposed methodology, the proposed methodology showed superior performance in terms of Angular Error compared to the existing methods.
The purpose of this study is to propose the features of autonomous DRT UX design based on level 5 autonomous vehicle applicable in 2027. As the scope of the study, the system focused on the interaction between the elderly and the in/outside of the vehicle, and the level 5 autonomous vehicle was the subject of the study. As of 2021, the targets for application were set from 60s to 90s. This study is different from previous studies in that it is a study on the features of autonomous DRT UX design that derives practical insights through direct communication with the elderly. As a research method, autonomous vehicle and DRT were theoretically considered through literature research, and based on this, cases of autonomous vehicle and DRT were analyzed. As a case study, generalization was conducted through interviews with the elderly, test-drive of autonomous vehicle, video production, survey, and VR test-drive of autonomous vehicle for the elderly. Ten features of autonomous DRT UX design were derived through focus group interview(FGI), and the derived features were classified into reservation, get on, input, driving, emergency, and get off. Through this study, I hope that it will contribute to improving mobility of the elderly and further accelerate the practical use of autonomous DRT.
Journal of the Korean Society of Floral Art and Design
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no.41
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pp.93-114
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2019
The purpose of this study is to analyze the characteristics and problems of the content of flower design education videos on YouTube and to search for improvement direction. The subjects of analysis were 129 pieces of videos uploaded in the last one year including 'craftman floral design' as a search term. The result shows that contents covered were practical lectures, theory lectures, test related tips, job and character introduction, test work, educational guidance and publicity. The production format could be divided into studio lecture, classroom lecture, video feature, interview, Vlog, and television program. The hub-type programming strategy that periodically uploads the videos satisfying the target audiences' interests is mostly applied. The type of lecture covered 'practical skill test' got a good response from the users. Overall, content diversity, interaction between creators and users, and harmonious programming strategies are lacking. In order to improve this, it is necessary for emotional and expressive creators to pioneer differentiated fields and practice based on actual field. The introduction of interactive elements such as games and quizzes and the application of new media technologies such as VR and AR are worth trying. Three strategic types of 'hero', 'hub', and 'how to' should be applied complementary. As the demand for education content related to flower design is expected to expand in the future, it is required to develop content that can be used in various platforms, foster professional creators, and develop associated business models.
Journal of the Korean Association of Geographic Information Studies
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v.26
no.4
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pp.173-187
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2023
In an era of population decline, depopulated regions facing challenges in attracting inbound population migration must enhance urban vitality through the attraction of living populations. This study focuses on Busan, a city experiencing population decline, comparing the spatiotemporal distribution characteristics of registered residents and living populations in various administrative districts (Eup-Myeon-Dong) using mobile communication big data. Administrative districts are typified based on population change patterns, and regional characteristics are analyzed using indicators related to urban decline and vitality. Spatiotemporal distribution analysis reveals generally similar density patterns between registered residents and living populations; however, a distinctive feature is observed in the city center areas where the density of registered residents is low, while the density of living populations is high. Divergent trends in spatial patterns of change between registered residents and living populations show clusters of registered population decline in low-density areas and clusters of living population decline in high-density areas. Areas adjacent to declining living populations exhibit large clusters of population changes, indicating a spillover effect from high-density to neighboring areas. Typification results reveal that, even in areas with a decline in registered residents, there is active population influx due to commuting or visiting. These areas sustain an increase in the number of businesses, confirming the presence of industrial and economic growth. However, approximately 47% of administrative districts in Busan are experiencing a decline in both registered residents and living populations, indicating ongoing regional decline. Urgent measures are needed for enhancing urban vitality. The study emphasizes the necessity of utilizing living population data as an urban planning indicator, considering the increasing limit distance of urban activities and growing interregional interaction due to advancements in transportation and communication.
Ha-Je Park;Hee-Young Yang;So-Jin Choi;Dae-Yeon Kim;Choon-Sung Nam
Journal of Internet Computing and Services
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v.25
no.2
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pp.57-67
/
2024
This paper explores the potential of electromyography (EMG) as a means of gesture recognition for user input in gesture-based interaction. EMG utilizes small electrodes within muscles to detect and interpret user movements, presenting a viable input method. To classify user gestures based on EMG data, machine learning techniques are employed, necessitating the preprocessing of raw EMG data to extract relevant features. EMG characteristics can be expressed through formulas such as Integrated EMG (IEMG), Mean Absolute Value (MAV), Simple Square Integral (SSI), Variance (VAR), and Root Mean Square (RMS). Additionally, determining the suitable time for gesture classification is crucial, considering the perceptual, cognitive, and response times required for user input. To address this, segment sizes ranging from a minimum of 100ms to a maximum of 1,000ms are varied, and feature extraction is performed to identify the optimal segment size for gesture classification. Notably, data learning employs overlapped segmentation to reduce the interval between data points, thereby increasing the quantity of training data. Using this approach, the paper employs four machine learning models (KNN, SVC, RF, XGBoost) to train and evaluate the system, achieving accuracy rates exceeding 96% for all models in real-time gesture input scenarios with a maximum segment size of 200ms.
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