• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2021.10a
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• pp.194-198
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• 2021

LoRa is a physical layer technology that is designed to provide a reliable long-range communication with introducing CSS and with introducing a loco parentis tree network. Since a leaf can utilize multiple parents at the same time with a single transmission, PDR increases logarithmically as the number of gateways increases. Because of the ALOHA-like MAC of LoRa, however, the PDR degrades even under the loco parentis tree topology similarly to the single-gateway environment. Our proposed method is aimed to achieve SDMA approach to reuse the same frequency in different areas. For that purpose, it elaborately controls each TxPower of the senders for each message in concurrent transmission to survive the collision at each different gateway. The gain from this so-called capture effect increases the capacity of resource-hungry LPWAN. Compared to a typical collision-free controlled-access scheme, our method outperforms by 10-35% from the perspective of the total count of the consumed time slots. Also, due to the power control mechanism in our method, the energy consumption reduced by 20-40%.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.26 no.6B
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• pp.613-622
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• 2006

In this study, a fully distributed physical-based rainfall-runoff model called Vflo$^{TM}$ is applied to Junglang-cheon basin for simulating runoff. Geo-spatial data are used to parameterize the model to account for the characteristics of soils, landuse/cover, and topograph. 300m resolution DEM is used to compute slope and drainage network connectivity. Spatially distributed rainfall data is interpolated by ordinary kriging method. In this study, hydrograph from HEC-HMS and Vflo$^{TM}$ without/with calibration of parameters was compared to evaluate the accuracy of rainfall-runoff model From the results, a fully distributed physical-based rainfall-runoff model reproduce the peak time and shape of hydrograph much better than HEC-HMS.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.26 no.5B
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• pp.481-488
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• 2006

This paper suggests a novel approach of integrating the quasi-distributed watershed model SWAT with the fully-distributed groundwater model MODFLOW. Since the SWAT model has semi distributed features, its groundwater components hardly considers distributed parameters such as hydraulic conductivity and storage coefficient. Generating a detailed representation of groundwater recharge, head distribution and pumping rate is equally difficult. To solve these problems, the method of exchanging the characteristics of the hydrologic response units (HRUs) in SWAT with cells in MODFLOW by fully combined manner is proposed. The linkage is completed by considering the interaction between the stream network and the aquifer to reflect boundary flow. This approach is provisionally applied to Gyungancheon basin in Korea. The application demonstrates a combined model which enables an interaction between saturated zones and channel reaches. This interaction plays an essential role in the runoff generation in the Gyungancheon basin. The comprehensive results show a wide applicability of the model which represents the temporal-spatial groundwater head distribution and recharge.

• Smart Media Journal
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• v.12 no.5
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• pp.28-35
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• 2023

In this study, we propose a new light-weight model RoutingConvNet with fewer parameters to improve the applicability and practicality of speech emotion recognition. To reduce the number of learnable parameters, the proposed model connects bidirectional MFCCs on a channel-by-channel basis to learn long-term emotion dependence and extract contextual features. A light-weight deep CNN is constructed for low-level feature extraction, and self-attention is used to obtain information about channel and spatial signals in speech signals. In addition, we apply dynamic routing to improve the accuracy and construct a model that is robust to feature variations. The proposed model shows parameter reduction and accuracy improvement in the overall experiments of speech emotion datasets (EMO-DB, RAVDESS, and IEMOCAP), achieving 87.86%, 83.44%, and 66.06% accuracy respectively with about 156,000 parameters. In this study, we proposed a metric to calculate the trade-off between the number of parameters and accuracy for performance evaluation against light-weight.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.26 no.5D
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• pp.731-738
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• 2006

Facing congestion, people want to know traffic information about their routes, especially real-time link travel time (LTT). In this paper, as a sequel paper of the previous non-taxi based LTT generating study by Choi et al. (1998), taxi based GPS probes have been tried to produce LTT for urban arterials. Taxis in itself are good deployment mode of GPS probes although it by nature experiences boarding and alighting time noises which should be accounted. A heuristic real-time dynamic outlier filter algorithm for taxi GPS probe has been developed focusing on urban arterials. An actual traffic survey for dynamic link travel times has been conducted using license plate method for the test arterials of Seoul city transportation network. With the algorithm, it is estimated that 70% of outliers have been filtered and the relative error has been improved by 73.7%. The filtering algorithm developed here would be expected to be in use for other spatial sites with some calibration efforts. Some limitations and future research agenda have also been discussed.

• International conference on construction engineering and project management
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• 2022.06a
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• pp.792-799
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• 2022

Building Information Modeling (BIM) technology is a key component of modern construction engineering and project management workflows. As-is BIM models that represent the spatial reality of a project site can offer crucial information to stakeholders for construction progress monitoring, error checking, and building maintenance purposes. Geometric methods for automatically converting raw scan data into BIM models (Scan-to-BIM) often fail to make use of higher-level semantic information in the data. Whereas, semantic segmentation methods only output labels at the point level without creating object level models that is necessary for BIM. To address these issues, this research proposes a hybrid semantic-geometric approach for clutter-resistant floorplan generation from laser-scanned building point clouds. The input point clouds are first pre-processed by normalizing the coordinate system and removing outliers. Then, a semantic segmentation network based on PointNet++ is used to label each point as ceiling, floor, wall, door, stair, and clutter. The clutter points are removed whereas the wall, door, and stair points are used for 2D floorplan generation. A region-growing segmentation algorithm paired with geometric reasoning rules is applied to group the points together into individual building elements. Finally, a 2-fold Random Sample Consensus (RANSAC) algorithm is applied to parameterize the building elements into 2D lines which are used to create the output floorplan. The proposed method is evaluated using the metrics of precision, recall, Intersection-over-Union (IOU), Betti error, and warping error.

• Journal of Cadastre & Land InformatiX
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• v.54 no.1
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• pp.103-115
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• 2024

Trilateral adjustment can complement the problem of transforming cadastral maps into World Geodetic Coordinate system. First, it is possible to determine adjusted coordinate of common points that match each other over a wide area. Second, calculations that focus on specific points can be performed. Third, a solution that maintains the shape of the regional network can be obtained through constraints. Thus, the point coordinates can be determined appropriately for the survey system. In addition, heterogeneous survey results that span regions with different coordinate origins can be calculated on a single origin coordinate. This improves the efficiency of the workflow in tranforming cadastral maps into World Geodetic Coordinate System.

• The Journal of the Convergence on Culture Technology
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• v.10 no.1
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• pp.453-458
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• 2024

Due to global issues such as climate crisis and rising energy costs, there is an increasing focus on energy conservation and management. In the case of South Korea, approximately 53.5% of the total energy consumption comes from industrial complexes. In order to address this, we aimed to improve issues through the 'Shared Network Utility Plant' among companies using similar energy utilities to find energy-saving points. For effective energy conservation, various techniques are utilized, and stable data supply is crucial for the reliable operation of factories. Many anomaly detection and alert systems for checking the stability of data supply were dependent on Energy Management Systems (EMS), which had limitations. The construction of an EMS involves large-scale systems, making it difficult to implement in small factories with spatial and energy constraints. In this paper, we aim to overcome these challenges by constructing a data collection system and anomaly detection alert system on embedded devices that consume minimal space and power. We explore the possibilities of utilizing anomaly detection alert systems in typical institutions for data collection and study the construction process.

• IEMEK Journal of Embedded Systems and Applications
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• v.19 no.1
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• pp.47-55
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• 2024

We spend a lot of time in indoor space, and the space has a huge impact on our lives. Interior design plays a significant role to make an indoor space attractive and functional. However, it should consider a lot of complex elements such as color, pattern, and material etc. With the increasing demand for interior design, there is a growing need for technologies that analyze these design elements accurately and efficiently. To address this need, this study suggests a deep learning-based design analysis system. The proposed system consists of a semantic segmentation model that classifies spatial components and an image classification model that classifies attributes such as color, pattern, and material from the segmented components. Semantic segmentation model was trained using a dataset of 30000 personal indoor interior images collected for research, and during inference, the model separate the input image pixel into 34 categories. And experiments were conducted with various backbones in order to obtain the optimal performance of the deep learning model for the collected interior dataset. Finally, the model achieved good performance of 89.05% and 0.5768 in terms of accuracy and mean intersection over union (mIoU). In classification part convolutional neural network (CNN) model which has recorded high performance in other image recognition tasks was used. To improve the performance of the classification model we suggests an approach that how to handle data that has data imbalance and vulnerable to light intensity. Using our methods, we achieve satisfactory results in classifying interior design component attributes. In this paper, we propose indoor space design analysis system that automatically analyzes and classifies the attributes of indoor images using a deep learning-based model. This analysis system, used as a core module in the A.I interior recommendation service, can help users pursuing self-interior design to complete their designs more easily and efficiently.

• Spatial Information Research
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• v.4 no.1
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• pp.21-42
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• 1996

The Anyang-cheon is one of the Han River tributaries in Seoul Metropolitan area. It is 35.1km long, has a basin area of 287km2 and touches seven cities of Kyounggi Province and part of Seoul. The purpose of this study were 1) to reconstruct the ancient stream network and to investigate the change of landuse in Anyang-cheon watershed between 1957 and 1991,2) to measure the change of the hydrologic ¬acteristics with urbanization, 3) to suggest the institutional solutions to reduce natural hazard as the area has urbanizedThe main results are as follows: 1.Anyang-cheon river basin has experienced the rapid urbanization and industrialization since 1957. Anyang-cheon stream network was oversimplified in the watershed. The total stream length decreased atributaries in the upper part of river basin have eliminated or buried undergrolmd in pipes. 2.Urbanization impacted to all of the area of Anyang-cht'On watershed. Urbanization in Anyang-cheon watershed corresponds to the large portion of flat area, especially flood - prone zone of river side, and the small portion of Greenbelt to constrain urban expantion in cities. 3.The urbanization of Anyang-cheon watershed produces fundamental changes in watershed hydrology. As infiltration is reduced by the creation of extensive pavement, concrete surface, and sewer pipe, runoff moves more quickly from upland to stream. As a result, runoff from the watershed is flashier, increasing flood hazardAs urban area continue to grow we will need to better utilize stream by protecting and enhancing stream systems.otecting and enhancing stream systems.tems.