• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2009.10a
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• pp.742-745
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• 2009

This paper proposed indoor location recognition method based on RSSI (received signal strength indication) using the LVQ (Learning Vector Quantization) network. The LVQ inputs are the RSSI values measured by the fixed reference nodes and the output are the spatial sections. In order to verify the effectiveness of the proposed method, we performed experiments, and then compared to the conventional triangularity measurement method.

• Korean Journal of Remote Sensing
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• v.35 no.6_3
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• pp.1187-1195
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• 2019

We, for the first time, developed a Raman lidar system which can remotely detect surface CO₂ volume mixing ratio (VMR). The Raman lidar system consists of the Nd: YAG laser of wavelength 355 nm with 80 mJ, an optical receiver, and detectors. Indoor CO₂ cell measurements show that the accuracy of the Raman lidar system is calculated to be 99.89%. We carried out the field measurement using our Raman lidar at Pukyong National University over a seven-day period in October 2019. The results show good agreement between CO₂ VMRs measured by the Raman lidar (CO₂ Raman Lidar) and those measured by in situ instruments (CO₂ In situ) which located 300 m and 350 m away from the Raman lidar system. The correlation coefficient (R), mean absolute error (MAE), and root mean square error (RMSE) between CO₂ In situ and CO₂ Raman Lidar are 0.67, 2.78 ppm, and 3.26 ppm, respectively.

• Korean Journal of Remote Sensing
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• v.36 no.6_3
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• pp.1635-1641
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• 2020

Air pollution is one of the most severe threats to society globally due to the rapid expansion of urbanization and industrialization. Particularly, particulate matter (PM) pollution was recently designated as a social disaster by the Korean government because of increases in public concerns and the accumulation of scientific evidence that links high levels of PM2.5 (PM smaller than 2.5 ㎛ in diameter) to a long list of adverse health effects. Atmospheric PM concentrations can also affect the indoor PM levels to which people are exposed most of the time. Thus, understanding the characteristics of indoor and ambient PM pollution based on measurements, model simulations, risk assessments, and management technologies is inevitable in establishing effective policies to mitigate social, economic, and health costs incurred by PM pollution. In this special issue, we introduce several interesting studies concerning indoor and outdoor PM from the perspective of monitoring, assessment, and management being conducted by i-SEED (School of Integrated Science for Sustainable Earth & Environmental Disaster at Pukyong National University) and SPMC (School Particulate Matter Center for Energy and Environmental Harmonization). We expect that this special issue can improve our understanding of the current and future of indoor and outdoor PM pollution, integrating the results from interdisciplinary research groups from various academic fields.

• Journal of the Korean Association of Geographic Information Studies
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• v.20 no.1
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• pp.71-84
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• 2017

Radon, which enters the interior environment from soil, rocks, and groundwater, is a radioactive gas that poses a serious risk to humans. Indoor radon concentrations are measured to investigate the risk of radon gas exposure and reliable radon concentration mapping is then performed for further analysis. In this study, we compared the predictive performance of various univariate kriging algorithms, including ordinary kriging and three nonlinear transform-based kriging algorithms (log-normal, multi-Gaussian, and indicator kriging), for mapping radon concentrations with an asymmetric distribution. To compare and analyze the predictive performance, we carried out jackknife-based validation and analyzed the errors according to the differences in the data intervals and sampling densities. From a case study in South Korea, the overall nonlinear transform-based kriging algorithms showed better predictive performance than ordinary kriging. Among the nonlinear transform-based kriging algorithms, log-normal kriging had the best performance, followed by multi-Gaussian kriging. Ordinary kriging was the best for predicting high values within the spatial pattern. The results from this study are expected to be useful in the selection of kriging algorithms for the spatial prediction of data with an asymmetric distribution.

• Journal of Internet Computing and Services
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• v.20 no.3
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• pp.33-41
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• 2019

In this paper, we propose a method to learn the redesigned class with background and object for semantic segmentation of indoor scene image. Semantic image segmentation is a technique that divides meaningful parts of an image, such as walls and beds, into pixels. Previous work of semantic image segmentation has proposed methods of learning various object classes of images through neural networks, and it has been pointed out that there is insufficient accuracy compared to long learning time. However, in the problem of separating objects and backgrounds, there is no need to learn various object classes. So we concentrate on separating objects and backgrounds, and propose method to learn after class simplification. The accuracy of the proposed learning method is about 5 ~ 12% higher than the existing methods. In addition, the learning time is reduced by about 14 ~ 60 minutes when the class is configured differently In the same environment, and it shows that it is possible to efficiently learn about the problem of separating the object and the background.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.11 no.7
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• pp.3370-3392
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• 2017

Next Generation Beyond 4G/5G systems will rely on the deployment of small cells over conventional macrocells for achieving high spectral efficiency and improved coverage performance, especially for indoor and hotspot environments. In such heterogeneous networks, the expected performance gains can only be derived with the use of efficient interference coordination schemes, such as Fractional Frequency Reuse (FFR), which is very attractive for its simplicity and effectiveness. In this work, femtocells are deployed according to a spatial Poisson Point Process (PPP) over hexagonally shaped, 6-sector macro base stations (MeNBs) in an uncoordinated manner, operating in hybrid mode. A newly introduced intermediary region prevents cross-tier, cross-boundary interference and improves user equipment (UE) performance at the boundary of cell center and cell edge. With tools of stochastic geometry, an analytical framework for the signal-to-interference-plus-noise-ratio (SINR) distribution is developed to evaluate the performance of all UEs in different spatial locations, with consideration to both co-tier and cross-tier interference. Using the SINR distribution framework, average network throughput per tier is derived together with a newly proposed harmonic mean, which ensures fairness in resource allocation amongst all UEs. Finally, the FFR network parameters are optimized for maximizing average network throughput, and the harmonic mean using a fair resource assignment constraint. Numerical results verify the proposed analytical framework, and provide insights into design trade-offs between maximizing throughput and user fairness by appropriately adjusting the spatial partitioning thresholds, the spectrum allocation factor, and the femtocell density.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.36 no.3B
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• pp.297-304
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• 2011

MIMO wireless communication embedded systems, and for propagation prediction for indoor and outdoor propagation prediction program incorporates an indoor/outdoor propagation through the simulator can be predicted. This analysis technique developed by the interference between multiple transmitters and a maximum transmission distance issues, the frequency utilization efficiency for a variety of issues, including analysis and prediction becomes possible. Development of the prediction of the conventional methods, but I can consider the environmental characteristics of the ray tracing simulation software to develop and implement an efficient ray tracing, ray tracing techniques and are designed to enable tracked beam analysis of propagation characteristics using information technology by combining the theoretical characteristics of an efficient and well-reflected propagation prediction technique was employed. The frequency of domestic embedded systems, ensure the frequency characteristics and frequency of 3-5GHz band for propagation to investigate the development of local wireless communication technology-based skills needed for securing and jeonpaganseopdeung frequency management techniques to ensure the verification and verified through experiments.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.17 no.11
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• pp.3064-3082
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• 2023

During the last decade, several Electronic Orientation Aids devices have been proposed to solve the autonomy problems of visually impaired people. When hearing is considered the primary sense for Visually Impaired people (VI) and it is generally loaded with the environment, the use of tactile sense can be considered a solution to transmit directional information. This paper presents a new wearable haptic system based on four motors implemented in shoes, while six directions can be played. This study aims to introduce an interface design and investigate an appropriate means of spatial information delivery through haptic sense. The first experiment of the proposed system was performed with 15 users in an indoor environment. The results showed that the users were able to recognize, with high accuracy, the directions displayed on their feet. The second experiment was conducted in an outdoor environment with five blindfolded users who were guided along 120 meters. The users, guided only by the haptic system, successfully reached their destinations. The potential of tactile-foot stimulation to help VI understand Electronic Orientation Aids (EOA) instructions was discussed, and future challenges were defined.

• Journal of Korean Society for Geospatial Information Science
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• v.23 no.1
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• pp.129-135
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• 2015

The Ubiquitous City (U-City) spatial information technology aimed to provide services freely anytime and anywhere by converging high-tech information & communication technology in urban infrastructure has been available in diverse patterns. In particular, there have been studies on the development of 3D spatial information after selecting and matching key points with stereo images from the many Closed Circuit TV (CCTV) in the U-City. However, the data mostly used in extracting matching points haven't considered external environmental impacts such as illuminance. This study tested how much the matching points needed to construct 3D spatial information with the CCTV whose image quality is dependent upon changes in illuminance fluctuate under the same hardware performances. According to analysis on the number of matching points by illuminance, the number of matching points increased up to 3,000Lux in proportion to the illuminance when IRIS, shutter speed and ISO were fixed. In addition, a border between an object and background became more distinctive. When there was too much light, however, the page became brighter, and noise occurred. Furthermore, it was difficult to name key points because of the collapse of an inter-object border. It appears that if filmed with the study results, the number of matching points would increase.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.9 no.5
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• pp.1856-1869
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• 2015

This paper addresses the issues of 3D human activity detection, tracking and recognition from RGB-D video sequences using a feature structured framework. During human tracking and activity recognition, initially, dense depth images are captured using depth camera. In order to track human silhouettes, we considered spatial/temporal continuity, constraints of human motion information and compute centroids of each activity based on chain coding mechanism and centroids point extraction. In body skin joints features, we estimate human body skin color to identify human body parts (i.e., head, hands, and feet) likely to extract joint points information. These joints points are further processed as feature extraction process including distance position features and centroid distance features. Lastly, self-organized maps are used to recognize different activities. Experimental results demonstrate that the proposed method is reliable and efficient in recognizing human poses at different realistic scenes. The proposed system should be applicable to different consumer application systems such as healthcare system, video surveillance system and indoor monitoring systems which track and recognize different activities of multiple users.