The Journal of Korean Institute of Communications and Information Sciences
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v.36
no.4B
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pp.422-428
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2011
In this paper, we introduce system and channel modeling for an underwater ad hoc acoustic network with n regularly located nodes, and then analyze capacity scaling laws based on the model. A narrow-band model is assumed where the carrier frequency is allowed to scale as a function of n. In the network, we characterize in attenuation parameter that depends on the frequency scaling as well as the transmission distance. A cut-set upper bound on the throughput scaling is then derived in extended networks having unit node density. Our result indicates that the upper bound is inversely proportional to the attenuation parameter, thus resulting in a power-limited network. Furthermore, we describe an achievable scheme based on the simple nearest-neighbor multi-hop (MH) transmission. It is shown under extended networks that the MH scheme is order-optimal for all the operating regimes expressed as functions of the attenuation parameter.
Three-dimensional information of submarine topography was acquired by assembling DGPS and Echo Sounder, which is mainly used in the marine survey. However, the features of submarine topography, derived according to mechanical data, were confirmed using human eyes. Because the dredging capacity using a submarine surveying data influences harbor public affairs, analysis and the process method of surveying data is a very special element in construction costs. In this study, information on submarine topography is acquired by assembling DGPS and Echo Sounder. Moreover, the dredging capacity in harbor public affairs has been analyzed by the interpolation method: inverse distance to a power, kriging, minimum curvature, nearest neighbor, and radial basis function. Also, utilization of DGPS and Echo Sounder method in calculation of the dredging capacity have been confirmed by comparing and analyzing the dredging capacity and the actual one, as per each interpolation. According to this comparison result, in the case of applying Radial basis function interpolation and Kriging, 3.94 % and 4.61 % of error rates have been shown, respectively. In the case of the study for application of the proper interpolation, as per characteristics of submarine topography, is preceded in calculation of the dredging capacity relevant to harbor public affairs, it is expected that more speedy and correct calculation for the dredging capacity can be made.
Kim, Jin-Hyo;Ra, Jung-Hwa;Lee, Soon-Ju;Kwon, Oh-Sung;Cho, Hyun-Ju;Lee, Eun-Jae
Journal of the Korean Society of Environmental Restoration Technology
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v.19
no.3
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pp.29-44
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2016
The purpose of this study is to quantitatively and visually analyze the degree of green biotope fragmentation caused by road construction and other development work using FRAGSTATS and GUIDOS tool. Moreover, linking of the endangered species research, we mapped "Biotope Fragmentation Map" of Daejeon-city. The findings of the study are summarized as follows: First, as the result of FRAGSTATS, landscape indices : number of patch(NP), mean patch size (MPS), edge length(TE), mean nearest neighbor distance(MNN), edge shape(LSI) showed meaningful change from fragmentation. Moreover, the result of GUIDOS analysis, middle core-small core-bridge-branch-edge-islet-perforation showed increase of area percentage without large core. Lastly, analysis result of 'Biotope Fragmentation Map' revealed that changing site of large core's size appeared eighteen-site and designated as the special protection area appeared forty-one site. As the result of the two data, overlapping areas that showed both change of core size and revealed special protection areas revealed four site. For example, five species of endangered species appeared on the NO. 4 site in 'Biotope Fragmentation Map'. The findings of this study as summarized above are considered to play an important role in basic data preventing green biotope fragmentation at the planned level from various development work.
KSII Transactions on Internet and Information Systems (TIIS)
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v.12
no.5
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pp.2313-2326
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2018
The method of operating a game could determine the psychological distance between the player and the game character, and thus, in the Virtual Reality, players' control methodologies are important to enhance their immersion. This study has the objective of examining the difference in games according to the method of operation based on the player's movements. This study researched the effect of the method of operating movement conforming to the movement of the character and the physical operation of the body on forming game experiences for the player. The result of performing an experiment increased reality for the game player through a controller in the shape of the actual control, to increase focus in the game. As so, game play through movements, including actual movements by the player displayed to enhance game satisfaction. In the part of media remediation field, Game can be defined as media which has their own unique hypermediacy. Especially, in the motion based game, players' movement mediates players and the game, therefore, players' movement could make players' experience augmented or immediate in accordance with the characteristics of movements. Even though sports and dances genres of motion-based games are common, RPG or adventure genres are rare. It can be explained that the characteristics of the action have been explained in the immediacy. In a game of fantasy, which is difficult to experience in real-life situations, the nature of the player's motion can increase the immersion of the game, which can contribute to utilization of players' motion and experience design in the various genres and suggestion of grounds theory. In addition, through this study, it is able to design motion-based games of various genres.
The existing indoor localization method using Wi-Fi fingerprinting has a high collection cost and relatively low accuracy, thus requiring integrated correction of convergence with other technologies. This paper proposes a new method that significantly reduces collection costs compared to existing methods using Wi-Fi fingerprinting. Furthermore, it does not require labeling of data at collection and can estimate pedestrian travel paths even in large indoor spaces. The proposed pedestrian movement path estimation process is as follows. Data collection is accomplished by setting up a feature area near an indoor space intersection, moving through the set feature areas, and then collecting data without labels. The collected data are processed using Kernel Linear Discriminant Analysis (KLDA) and the valley point of the Euclidean distance value between two data is obtained within the feature space of the data. We build learning data by labeling data corresponding to valley points and some nearby data by feature area numbers, and labeling data between valley points and other valley points as path data between each corresponding feature area. Finally, for testing, data are collected randomly through indoor space, KLDA is applied as previous data to build test data, the K-Nearest Neighbor (K-NN) algorithm is applied, and the path of movement of test data is estimated by applying a correction algorithm to estimate only routes that can be reached from the most recently estimated location. The estimation results verified the accuracy by comparing the true paths in indoor space with those estimated by the proposed method and achieved approximately 90.8% and 81.4% accuracy in two experimental spaces, respectively.
Proceedings of the Korea Water Resources Association Conference
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2011.05a
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pp.185-185
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2011
Mapping of artificial levee lines, one of major tasks in river zone mapping, is critical to prevention of river flood, protection of environments and eco systems in river zones. Thus, mapping of artificial levee lines is essential for management and development of river zones. Coastal mapping including river zone mapping has been historically carried out using surveying technologies. Photogrammetry, one of the surveying technologies, is recently used technology for national river zone mapping in Korea. Airborne laser scanning has been used in most advanced countries for coastal mapping due to its ability to penetrate shallow water and its high vertical accuracy. Due to these advantages, use of LiDAR data in coastal mapping is efficient for monitoring and predicting significant topographic change in river zones. This paper introduces a method for construction of a 3D artificial levee line using a set of LiDAR points that uses normal vectors. Multiple steps are involved in this method. First, a 2.5-dimensional Delaunay triangle mesh is generated based on three nearest-neighbor points in the LiDAR data. Second, a median filtering is applied to minimize noise. Third, edge selection algorithms are applied to extract break edges from a Delaunay triangle mesh using two normal vectors. In this research, two methods for edge selection algorithms using hypothesis testing are used to extract break edges. Fourth, intersection edges which are extracted using both methods at the same range are selected as the intersection edge group. Fifth, among intersection edge group, some linear feature edges which are not suitable to compose a levee line are removed as much as possible considering vertical distance, slope and connectivity of an edge. Sixth, with all line segments which are suitable to constitute a levee line, one river levee line segment is connected to another river levee line segment with the end points of both river levee line segments located nearest horizontally and vertically to each other. After linkage of all the river levee line segments, the initial river levee line is generated. Since the initial river levee line consists of the LiDAR points, the pattern of the initial river levee line is being zigzag along the river levee. Thus, for the last step, a algorithm for smoothing the initial river levee line is applied to fit the initial river levee line into the reference line, and the final 3D river levee line is constructed. After the algorithm is completed, the proposed algorithm is applied to construct the 3D river levee line in Zng-San levee nearby Ham-Ahn Bo in Nak-Dong river. Statistical results show that the constructed river levee line generated using a proposed method has high accuracy in comparison to the ground truth. This paper shows that use of LiDAR data for construction of the 3D river levee line for river zone mapping is useful and efficient; and, as a result, it can be replaced with ground surveying method for construction of the 3D river levee line.
In this paper, we propose a new method utilizing only raw corpus without additional human effort for disambiguation of target word selection in English-Korean machine translation. We use two data-driven techniques; one is the Latent Semantic Analysis(LSA) and the other the Probabilistic Latent Semantic Analysis(PLSA). These two techniques can represent complex semantic structures in given contexts like text passages. We construct linguistic semantic knowledge by using the two techniques and use the knowledge for target word selection in English-Korean machine translation. For target word selection, we utilize a grammatical relationship stored in a dictionary. We use k- nearest neighbor learning algorithm for the resolution of data sparseness Problem in target word selection and estimate the distance between instances based on these models. In experiments, we use TREC data of AP news for construction of latent semantic space and Wail Street Journal corpus for evaluation of target word selection. Through the Latent Semantic Analysis methods, the accuracy of target word selection has improved over 10% and PLSA has showed better accuracy than LSA method. finally we have showed the relatedness between the accuracy and two important factors ; one is dimensionality of latent space and k value of k-NT learning by using correlation calculation.
The Transactions of the Korea Information Processing Society
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v.13
no.4
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pp.189-198
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2024
Lipreading is one of the important parts of speech recognition, and several studies have been conducted to improve the performance of lipreading in lipreading systems for speech recognition. Recent studies have used method to modify the model architecture of lipreading system to improve recognition performance. Unlike previous research that improve recognition performance by modifying model architecture, we aim to improve recognition performance without any change in model architecture. In order to improve the recognition performance without modifying the model architecture, we refer to the cues used in human lipreading and set other regions such as chin and cheeks as regions of interest along with the lip region, which is the existing region of interest of lipreading systems, and compare the recognition rate of each region of interest to propose the highest performing region of interest In addition, assuming that the difference in normalization results caused by the difference in interpolation method during the process of normalizing the size of the region of interest affects the recognition performance, we interpolate the same region of interest using nearest neighbor interpolation, bilinear interpolation, and bicubic interpolation, and compare the recognition rate of each interpolation method to propose the best performing interpolation method. Each region of interest was detected by training an object detection neural network, and dynamic time warping templates were generated by normalizing each region of interest, extracting and combining features, and mapping the dimensionality reduction of the combined features into a low-dimensional space. The recognition rate was evaluated by comparing the distance between the generated dynamic time warping templates and the data mapped to the low-dimensional space. In the comparison of regions of interest, the result of the region of interest containing only the lip region showed an average recognition rate of 97.36%, which is 3.44% higher than the average recognition rate of 93.92% in the previous study, and in the comparison of interpolation methods, the bilinear interpolation method performed 97.36%, which is 14.65% higher than the nearest neighbor interpolation method and 5.55% higher than the bicubic interpolation method. The code used in this study can be found a https://github.com/haraisi2/Lipreading-Systems.
Korean Journal of Agricultural and Forest Meteorology
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v.23
no.2
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pp.122-133
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2021
Cultivar parameter calibration can be affected by the reliability of the input data to a crop growth model. In South Korea, two sets of weather stations, which are included in the automated synoptic observing system (ASOS) or the automatic weather system (AWS), are available for preparation of the weather input data. The objectives of this study were to estimate the cultivar parameter using those sets of weather data and to compare the uncertainty of these parameters. The cultivar parameters of CERES-Rice model for Shindongjin cultivar was calibrated using the weather data measured at the weather stations included in either ASO S or AWS. The observation data of crop growth and management at the experiment farms were retrieved from the report of new cultivar development and research published by Rural Development Administration. The weather stations were chosen to be the nearest neighbor to the experiment farms where crop data were collected. The Generalized Likelihood Uncertainty Estimation (GLUE) method was used to calibrate the cultivar parameters for 100 times, which resulted in the distribution of parameter values. O n average, the errors of the heading date decreased by one day when the weather input data were obtained from the weather stations included in AWS compared with ASO S. In particular, reduction of the estimation error was observed even when the distance between the experiment farm and the ASOS stations was about 15 km. These results suggest that the use of the AWS stations would improve the reliability and applicability of the crop growth models for decision support as well as parameter calibration.
The amount of hydrogen adsorbed in arrays of single walled carbon nanotubes (SWNTs) was studied as a function of nanotube diameter and distance between the nearest-neighbor nanotubes on square arrangements using a grand canonical Monte Carlo simulation. The influence of the geometry of a triangle array with the same diameters and distances was also studied. Hydrogen-carbon and hydrogen-hydrogen interactions were modeled with Lennard-Jones potentials for short range interactions and electrostatic interactions were added for hydrogen-hydrogen pairs to consider quantum contributions at low temperatures. At 194.5 K, Type I isotherms for large-diameter SWNTs and Type IV isotherms without hysteresis between adsorption and desorption processes for wider tube separations were observed. At 200 bars, the gravimetric hydrogen storage capacity of the SWNTs was reached or exceeded the US Department of Energy (DOE) target, but the volumetric capacity was about 70% of the DOE target. At 77 K, a two-step adsorption was observed, corresponding to a monolayer formation step followed by a condensation step. Hydrogen was adsorbed first to the inner surface of the nanotubes, then to the outer surface, intratubular space and the interstitial channels between the nanotube bundles. The simulation indicated that SWNTs of various diameters and distances in a wide range of configurations exceeded the DOE gravimetric and volumetric targets at under 1 bar.
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