• Land and Housing Review
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• v.12 no.2
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• pp.13-32
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• 2021

Rapid urbanization has resulted in the unprecedented growth of population in Metro Manila, the Philippines and has led to a 'dual' housing crisis - vacant/unoccupied socialized housing and a chronic housing shortage or delayed housing supply. By developing two GIS-based statistical models, this study is to examine socialized housing in comparison with private housing with respect to location patterns, integration, accessibility, social and economic aspects, and vulnerability to environmental hazards. Multiple regression analysis was integrated with the GIS to identify significant variables that influence the spatial distribution of socialized housing. The comparison between the two regression models has shown that socialized housing is located in areas with inappropriate land use and poor accessibility to transportation facilities and built urban resources. Moreover, both regression models have proven the statistical significance of the vulnerability of socialized housing to environmental hazards. The finding explains how the current housing policies do not address the country's housing crisis, especially for the marginalized and low-income households. Thus, the findings provide implications for urban planners and local decision-makers in reforming the current policy interventions.

• Korean Chemical Engineering Research
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• v.59 no.2
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• pp.209-218
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• 2021

First principle-based modeling studies have been performed to improve the heat exchange efficiency of ORV and optimize operation, but the heat transfer coefficient of ORV is an irregular system according to time and location, and it undergoes a complex modeling process. In this study, FNN, LSTM, and AutoML-based modeling were performed to confirm the effectiveness of data-based modeling for complex systems. The prediction accuracy indicated high performance in the order of LSTM > AutoML > FNN in MSE. The performance of AutoML, an automatic design method for machine learning models, was superior to developed FNN, and the total time required for model development was 1/15 compared to LSTM, showing the possibility of using AutoML. The prediction of NG and seawater discharged temperatures using LSTM and AutoML showed an error of less than 0.5K. Using the predictive model, real-time optimization of the amount of LNG vaporized that can be processed using ORV in winter is performed, confirming that up to 23.5% of LNG can be additionally processed, and an ORV optimal operation guideline based on the developed dynamic prediction model was presented.

• The Journal of Engineering Geology
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• v.30 no.4
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• pp.649-661
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• 2020

Cut-slope management system (CSMS) has been investigated all slopes on the road of the whole country to evaluate risk rating of each slope. Based on this evaluation, the decision-making for maintenance can be conducted, and this procedure will be helpful to establish a consistent and efficient policy of safe road. CSMS has updated the database of all slopes annually, and this database is constructed based on a basic and detailed investigation. In the database, there are two type of data: first one is an objective data such as slopes' location, height, width, length, and information about underground and bedrock, etc; second one is subjective data, which is decided by experts based on those objective data, e.g., degree of emergency and risk, maintenance solution, etc. The purpose of this study is identifying an data application plan to utilize those CSMS data. For this purpose, logistic regression, which is a basic machine-learning method to construct a prediction model, is performed to predict a judging-type variable (i.e., subjective data) based on objective data. The constructed logistic model shows the accurate prediction, and this model can be used to judge a priority of slopes for detailed investigation. Also, it is anticipated that the prediction model can filter unusual data by comparing with a prediction value.

• Journal of Gastric Cancer
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• v.21 no.4
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• pp.368-378
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• 2021

Purpose: When patients with early gastric cancer (EGC) undergo non-curative endoscopic submucosal dissection requiring gastrectomy (NC-ESD-RG), additional medical resources and expenses are required for surgery. To reduce this burden, predictive model for NC-ESD-RG is required. Materials and Methods: Data from 2,997 patients undergoing ESD for 3,127 forceps biopsy-proven differentiated-type EGCs (2,345 and 782 in training and validation sets, respectively) were reviewed. Using the training set, the logistic stepwise regression analysis determined the independent predictors of NC-ESD-RG (NC-ESD other than cases with lateral resection margin involvement or piecemeal resection as the only non-curative factor). Using these predictors, a risk-scoring system for predicting NC-ESD-RG was developed. Performance of the predictive model was examined internally with the validation set. Results: Rate of NC-ESD-RG was 17.3%. Independent pre-ESD predictors for NC-ESD-RG included moderately differentiated or papillary EGC, large tumor size, proximal tumor location, lesion at greater curvature, elevated or depressed morphology, and presence of ulcers. A risk-score was assigned to each predictor of NC-ESD-RG. The area under the receiver operating characteristic curve for predicting NC-ESD-RG was 0.672 in both training and validation sets. A risk-score of 5 points was the optimal cut-off value for predicting NC-ESD-RG, and the overall accuracy was 72.7%. As the total risk score increased, the predicted risk for NC-ESD-RG increased from 3.8% to 72.6%. Conclusions: We developed and validated a risk-scoring system for predicting NC-ESD-RG based on pre-ESD variables. Our risk-scoring system can facilitate informed consent and decision-making for preoperative treatment selection between ESD and surgery in patients with EGC.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.21 no.2
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• pp.33-43
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• 2022

The number of car crashes increases along with the increasing number of vehicles. Hence, diverse initiatives on traffic accidents have been implemented, targeting zero crash fatalities. According to the 3rd Traffic Safety Master Plan of 2016, the current standard selecting road accident black spots prioritizes locations with the high cumulative death toll. While this standard is suitable for roads that a city government manages to some extent, it is not suitable for roads less than 20 meters that a borough (Gu) handles. The roads under the supervision of a borough do not have enough death toll, and thus improvements on its road accident black spots are highly limited. In addition, discovering the causes of traffic accidents is not easy when the number of car accidents is obtained by considering only fatal accidents, which are relatively low in number. Therefore, including all traffic accidents might identify causes of accidents and result in better advancements. Therefore, this research follows rational decision-making and suggests new National Traffic Safety Master Plan standards. These new standards are obtained by comparing accident costs between the location of fatal crashes and road accident black spots. The analysis result shows that considering all types of accidents yields better results. For example, a Three-way Intersection in front of Zion Day Care Center, one of the selected spots under the current standard, has lower road crash costs than Sinchon Intersection, a selected spot under a new standard. Therefore, the study concludes that the standards to select road accident black spots need to include traffic accident severity and road crash costs.

• Korean Journal of Remote Sensing
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• v.38 no.5_1
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• pp.535-543
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• 2022

A drone is used to diagnose crop growth and to provide information through images in the agriculture field. In the case of using high spatial resolution drone images, growth information for each object can be produced. However, accurate object detection is required and adjacent objects should be efficiently classified. The purpose of this study is to develop a Chinese cabbage object detection algorithm using multispectral reflectance images observed from drone and computer vision techniques. Drone images were captured between 7 and 15 days after planting a Chinese cabbage from 2018 to 2020 years. The thresholds of object detection algorithm were set based on 2019 year, and the algorithm was evaluated based on images in 2018 and 2019 years. The vegetation area was classified using the characteristics of spectral reflectance. Then, morphology techniques such as dilatation, erosion, and image segmentation by considering the size of the object were applied to improve the object detection accuracy in the vegetation area. The precision of the developed object detection algorithm was over 95.19%, and the recall and accuracy were over 95.4% and 93.68%, respectively. The F1-Score of the algorithm was over 0.967 for 2 years. The location information about the center of the Chinese cabbage object extracted using the developed algorithm will be used as data to provide decision-making information during the growing season of crops.

• International conference on construction engineering and project management
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• 2009.05a
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• pp.30-31
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• 2009

Early detection of schedule delay in field construction activities is vital to project management. It provides the opportunity to initiate remedial actions and increases the chance of controlling such overruns or minimizing their impacts. This entails project managers to design, implement, and maintain a systematic approach for progress monitoring to promptly identify, process and communicate discrepancies between actual and as-planned performances as early as possible. Despite importance, systematic implementation of progress monitoring is challenging: (1) Current progress monitoring is time-consuming as it needs extensive as-planned and as-built data collection; (2) The excessive amount of work required to be performed may cause human-errors and reduce the quality of manually collected data and since only an approximate visual inspection is usually performed, makes the collected data subjective; (3) Existing methods of progress monitoring are also non-systematic and may also create a time-lag between the time progress is reported and the time progress is actually accomplished; (4) Progress reports are visually complex, and do not reflect spatial aspects of construction; and (5) Current reporting methods increase the time required to describe and explain progress in coordination meetings and in turn could delay the decision making process. In summary, with current methods, it may be not be easy to understand the progress situation clearly and quickly. To overcome such inefficiencies, this research focuses on exploring application of unsorted daily progress photograph logs - available on any construction site - as well as IFC-based 4D models for progress monitoring. Our approach is based on computing, from the images themselves, the photographer's locations and orientations, along with a sparse 3D geometric representation of the as-built scene using daily progress photographs and superimposition of the reconstructed scene over the as-planned 4D model. Within such an environment, progress photographs are registered in the virtual as-planned environment, allowing a large unstructured collection of daily construction images to be interactively explored. In addition, sparse reconstructed scenes superimposed over 4D models allow site images to be geo-registered with the as-planned components and consequently, a location-based image processing technique to be implemented and progress data to be extracted automatically. The result of progress comparison study between as-planned and as-built performances can subsequently be visualized in the D4AR - 4D Augmented Reality - environment using a traffic light metaphor. In such an environment, project participants would be able to: 1) use the 4D as-planned model as a baseline for progress monitoring, compare it to daily construction photographs and study workspace logistics; 2) interactively and remotely explore registered construction photographs in a 3D environment; 3) analyze registered images and quantify as-built progress; 4) measure discrepancies between as-planned and as-built performances; and 5) visually represent progress discrepancies through superimposition of 4D as-planned models over progress photographs, make control decisions and effectively communicate those with project participants. We present our preliminary results on two ongoing construction projects and discuss implementation, perceived benefits and future potential enhancement of this new technology in construction, in all fronts of automatic data collection, processing and communication.

• Korea Science and Art Forum
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• v.24
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• pp.143-157
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• 2016

Focusing on the Gwangheemun that have a history of spatial specificity. Gwangheemun increase the value of space in the surrounding area, focused to derive a plan that can be activated. Research method was to analyze the characteristics and advantages and disadvantages of the surrounding space and the associated cultural content through SWOT analysis around the base of Gwangheemun. After considering the potential of the current location of physical characteristics and spatial resources, the possibility Gwangheemun development were mainly fashion and art content for the Space Vitalization in the surrounding area. Fashion and art space of Gwangheemun activated based on the possibility of Gwangheemun cultural meaning and value in the history of the past and the present time presented the main directions and strategic approach. The results of this research suggested Fashion art Hotel in applying urban regeneration methodologies, Cheongguro-16 plan for content development, arts and culture fashion street planning. Through this research, we want to establish the strategic control strategy between the policy decision making structures for the successful development of the fashion arts content.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.30 no.2D
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• pp.153-161
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• 2010

The city planning of a local government is a continuous process that does not end with the creation of a plan but proceeds through decision-making, monitoring and evaluation phases. As a new city planning is changed and confirmed, there is a chance to construct a large scale road that is connected with an under constructed road. In this case, the expansion of the width and length of road, the addition of bridges or tunnels, and the change of the size and location of interchanges lead to many changes on road design and construction. In the past, the consignment contracts for a road construction have been made in limited numbers and for limited civil works. Now, it is growing in numbers and is making for large scale multi-works. However, the standard process and guidelines for the consignment contracts have not been suggested yet, so there is difficulty in performing the consigned road construction effectively. In this paper, the important factors for the consignment contracts are determined by construction document reviews and expert interviews. Based on these results, a standard process for the consigned contracts and a guideline for agreeing on construction cost are suggested. The costs that should be paid by a consignor are also defined.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.26 no.3D
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• pp.385-391
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• 2006

It is very important to make a decision for locating public facility site in a objectively way people in general agree with. This is because public facility affects not only daily life of people in there but also a regional development. This paper sets up a site selection model which utilize an accessibility theory and GIS spatial analysis techniques. This model has been applied to all the twelve alternatives of Chungnam Provincial Office (CPO) sites which are well known to the public. On the criterion of average access time from all the other areas in Chungnam Province, CH alternative is found to be the best one followed by CH/AS, AS alternatives. On the basis of total people-travel time CH/AS alternative turns out to be the best one followed by CH, AS alternatives. In conclusion top three best locations for CPO are CH and AS area where transportation facility are in good condition and population density is highest in Chungnam Province. This fact implies that a transportation accessibility and population density are the primary key in determining the location of public facility.