• Proceedings of the KSRS Conference
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• 2008.10a
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• pp.224-227
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• 2008

Land cover and its changes, affecting multiple aspects of the environmental system such as energy balance, biogeochemical cycles, hydrological cycles and the climate system, are regarded as critical elements in global change studies. Especially in arid and semiarid regions, the observation of ecosystem that is sensitive to climate change can improve an understanding of the relationships between climate and ecosystem dynamics. The purpose of this research is analyzing the ecosystem surrounding the Gobi desert in North Asia quantitatively as well as qualitatively more concretely. We used Normalized Difference Vegetation Index (NDVI) derived from SPOT-VEGETATION (VGT) sensor during 1999${\sim}$2007. Ecosystem monitoring of this area is necessary because it is a hot spot in global environment change. This study will allow predicting areas, which are prone to the rapid environmental change. Eight classes were classified and compare with MODerate resolution Imaging Spectrometer (MODIS) global land cover. The time-series analysis was carried out for these 8 classes. Class-1 and -2 have least amplitude variation with low NDVI as barren areas, while other vegetated classes increase in May and decrease in October (maximum value occurs in July and August). Although the several classes have the similar features of NDVI time-series, we detected a slight difference of inter-annual variation among these classes.

• Proceedings of the Korean Geotechical Society Conference
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• 2001.03a
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• pp.105-112
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• 2001

The purpose of this study is to assess the stability of tunnel for a high speed railway crossing the fault zone. The area where the tunnel crossed the fault zone can be unstable during construction and operation. Geotechnical investigations have been conducted to determine an optimum excavation method by obtaining the material properties around the fault zone and to check the stability of the tunnel. For the numerical analysis, the FLAC, numerical analysis code based on finite difference method, was utilized to analyze the behavior of the fault at three points having typical ground conditions. Based on the results of numerical analysis, the combinations of compaction grouting and LW grouting were determined as suitable methods for pre-excavation Improvement of the ground surrounding the tunnel opening. In conclusion, the stability of the tunnel construction for the high speed railway within the fault zone may be obtained by adopting the optimum excavation method and the reinforcement method. The numerical analysis based on FLAC program contains errors caused by assumptions used in numerical analysis, therefore constant monitoring with respect to the change of ground condition and groundwater is highly recommended to minimize the numerical error and the possibility of damage to tunnel.

• International Journal of Contents
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• v.16 no.3
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• pp.1-17
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• 2020

Human motion recognition is essential for user-centric services such as surveillance-based security, elderly condition monitoring, exercise tracking, daily calories expend analysis, etc. It is typically based on the movement data analysis such as the acceleration and angular velocity of a target user. The existing motion recognition studies are only intended to measure the basic information (e.g., user's stride, number of steps, speed) or to recognize single motion (e.g., sitting, running, walking). Thus, a new mechanism is required to identify the transition of single motions for assessing a user's consecutive motion more accurately as well as recognizing the user's body and surrounding situations arising from the motion. Thus, in this paper, we collect the human movement data through Android smartphones in real time for five targeting single motions and propose a mechanism to recognize a consecutive motion including transitions among various motions and an occurred situation, with the state transition model to check if a vulnerable (life-threatening) condition, especially for the elderly, has occurred or not. Through implementation and experiments, we demonstrate that the proposed mechanism recognizes a consecutive motion and a user's situation accurately and quickly. As a result of the recognition experiment about mix sequence likened to daily motion, the proposed adoptive weighting method showed 4% (Holding time=15 sec), 88% (30 sec), 6.5% (60 sec) improvements compared to static method.

• Journal of Korean Society for Atmospheric Environment
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• v.20 no.3
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• pp.345-360
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• 2004

The late sea-breeze and its impacts on ozone distributions were investigated during April to September from 1998 to 2002, in the Busan metropolitan area (including surrounding areas) using the surface ozone concentrations (obtained at 9 monitoring sites), local meteorological variables (obtained near the shore), together with synoptic data. The urban scale ozone concentration was also simulated using the MM5/UAM-V to better understand the role of late sea-breeze in Busan. The results from observation study showed that most of the late sea-breeze occurred when weak offshore synoptic flow (northwesterly) suppressed development of sea - breeze, and the ozone concentration level and frequencies exceeding ozone standard increased with the onset time of sea breeze. We also found that the late sea-breeze clearly induces relatively weak wind speed and high temperature during the daytime As a result it enhances the photochemical ozone accumulation and delays the occurrence time of the averaged maximum ozone concentrations. The results of simulation for high ozone episode (24 August, 2001) by MM5/UAM -V revealed that the late sea-breeze interacted with weak offshore synoptic wind can contribute significantly to high ozone concentration in the coastal urban area. The simulated horizontal and vertical distribution of ozone concentration indicated that ozone can be accumulated over the sea under stagnant condition and return to the land in the late afternoon with the sea breeze, suggesting both the relationship between late sea-breeze and recirculation and the importance of late sea -breeze effects influencing severe ozone pollution in Busan.

• Journal of the Korean Society of Environmental Restoration Technology
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• v.14 no.6
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• pp.87-95
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• 2011

This study investigates Youl Chon Industrial Complex 1 by dividing into three regions : the drainage site, the area inside the complex, and the seaside. Then each region was subdivided into three areas resulting in a total of nine areas for soil sampling and analysis. After analyzing the physical and chemical properties of the soil, all nine area's pH and EC readings indicated that the soil condition is not suitable for vegetation growth (according to the previous study, the pH level was 5.8 and EC was 2.0dS/m). Therefore, for Youl Chon Industrial Complex 1 to become green, the neutralization and reduction of pH and EC level is needed; first, vegetation through dredging soil, and second, introduction of halophytes is suggested. This study finds out that vertical changes in physical and chemical properties of soils in reclaimed sites are very variable and the result depends on surrounding environments, so it suggested the basic data for building vegetation or reclaimed sites. However, the additional study aiming at various reclaimed sites is required as this study was conducted only to limited areas, and this study has left monitoring analysis as the follow-up task to check the relations between a plant community and soils.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.43 no.1
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• pp.16-25
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• 2020

Vegetation segmentation in a field color image is a process of distinguishing vegetation objects of interests like crops and weeds from a background of soil and/or other residues. The performance of the process is crucial in automatic precision agriculture which includes weed control and crop status monitoring. To facilitate the segmentation, color indices have predominantly been used to transform the color image into its gray-scale image. A thresholding technique like the Otsu method is then applied to distinguish vegetation parts from the background. An obvious demerit of the thresholding based segmentation will be that classification of each pixel into vegetation or background is carried out solely by using the color feature of the pixel itself without taking into account color features of its neighboring pixels. This paper presents a new pixel-based segmentation method which employs a multi-layer perceptron neural network to classify the gray-scale image into vegetation and nonvegetation pixels. The input data of the neural network for each pixel are 2-dimensional gray-level values surrounding the pixel. To generate a gray-scale image from a raw RGB color image, a well-known color index called Excess Green minus Excess Red Index was used. Experimental results using 80 field images of 4 vegetation species demonstrate the superiority of the neural network to existing threshold-based segmentation methods in terms of accuracy, precision, recall, and harmonic mean.

• Journal of Institute of Control, Robotics and Systems
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• v.18 no.8
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• pp.780-786
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• 2012

Surveillance has become one of promising application areas of wireless sensor networks which allow for pervasive monitoring of concerned environmental phenomena by facilitating context awareness through sensor fusion. Existing systems that depend on a postmortem context analysis of sensor data on a centralized server expose several shortcomings, including a single point of failure, wasteful energy consumption due to unnecessary data transfer as well as deficiency of scalability. As an opposite direction, this paper proposes an energy-efficient distributed context-aware surveillance in which sensor nodes in the wireless sensor network collaborate with neighbors in a distributed manner to analyze and aware surrounding context. We design and implement multi-modal sensor stations for use as sensor nodes in our wireless sensor network implementing our distributed context awareness. This paper presents an initial experimental performance result of our proposed system. Results show that multi-modal sensor performance of our sensor station, a key enabling factor for distributed context awareness, is comparable to each independent sensor setting. They also show that its initial performance of context-awareness is satisfactory for a set of introductory surveillance scenarios in the current interim stage of our ongoing research.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.19 no.1
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• pp.119-126
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• 2015

In this paper, we propose a 3D visualization system that expresses the simulation results of port container operation monitoring and planning in terms of the movements of the surrounding environment including static and dynamic objects. It also enables us to objectively evaluate the operation model by way of animating the actual port operations. With XML-based design of object states, the port simulator visualization system (PSVS) that we propose has been implemented so as to maximize the interoperability with the existing port operation simulation (CATOS), and express the realtime animation of large-scale objects. The design method of PSVS system is explained, and its validity is experimentally examined.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2010.05a
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• pp.547-549
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• 2010

In this paper, we propose context-aware system for semiconductor equipment that acquires information from multiple sensors in indoor environment. This proposed system acquires information from acceleration, pressure, temperature and gas sensors then the acquired information send to server. The data transmitted to server generates an alarm via context-aware algorithm of unit event and multi event. From that result, high-quality real-time monitoring is possible because of the reduced unnecessary alarms, and the efficient management is possible because the surrounding information is recognized at once.

• Proceedings of the KSRS Conference
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• 2003.11a
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• pp.1409-1411
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• 2003

The application of simulated KOMPSAT-2 imagery to monitor graveyards is to be developed. Positions calculated from image were compared with those obtained from Geographic Positioning System. With 24 checkpoints, the position of graveyards showed within 5-meter range. Unsupervised classification, supervised classification, and objected-orientation classification algorithms were used to extract the graveyard. Unsupervised classification with masking processes based on National topographic data gives the best result. The graveyards were categorized with four types in field studies while the two types of graveyards were shown in descriptive statistics. Cluster Analysis and discriminant analysis showed the consistency with two types of tombs. It was hard to get a specific spectral signature of graveyards, as they are covered with grasses at different levels and shaded from the surrounding trees. The slopes and aspects of location of graveyards did not make any difference in the spectral signatures. This study gives the basic spectral characteristics for further development of objected-oriented classification algorithms and plausibility of KOMPSAT-2 images for management of mountainous areas in the aspect of position accuracy and classification accuracy.