• Journal of IKEEE
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• v.28 no.2
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• pp.199-203
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• 2024

In this paper, we propose variations in the kernel size of 1D convolutional layers for single-frame supervised temporal action localization. Building upon the existing method, which utilizes two 1D convolutional layers with kernel sizes of 3 and 1, we introduce an approach that adjusts the kernel sizes of each 1D convolutional layer. To validate the efficiency of our proposed approach, we conducted comparative experiments using the THUMOS'14 dataset. Additionally, we use overall video classification accuracy, mAP (mean Average Precision), and Average mAP as performance metrics for evaluation. According to the experimental results, our proposed approach demonstrates higher accuracy in terms of mAP and Average mAP compared to the existing method. The method with variations in kernel size of 7 and 1 further demonstrates an 8.0% improvement in overall video classification accuracy.

• Journal of the Korea Society of Computer and Information
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• v.24 no.10
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• pp.11-23
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• 2019

This paper designs and proposes a file conversion process to IFC file, the international standard file format for BIM, in order to ensure mutual compatability and manageability among users of commercial BIM modeling and design softwares in the civil engineering area. The proposed process insert additional properties consisting of the properties of quantity calculation codes and properties of CBS/OBS/WBS standard classification scheme, to the three dimensional object shape information of the converted IFC files, using add-in converters for commercial BIM modeling softwares. In addition, a process of integrated use of IFC files for open web-based quantity, process(4D), and construction cost(5D) management is additionally designed and implemented. Based on these works, the ultimate goal of this study is to propose a novel process for integrated use of open web-based quantity, process(4D), and construction cost(5D), from the design stage of BIM modeling to the final construction stage in the civil engineering area.

• Journal of the Korea Institute of Building Construction
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• v.20 no.3
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• pp.245-252
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• 2020

Synthetic resin formwork is made of lightweight high-density polyethylene(HDPE). This study used a process flow chart that satisfies the system boundary (such as Cradle-to- Product shipmen ) required by ISO FDIS 13352 to evaluate the entire process of synthetic resin foam using. The entire life cycle inventory (LCI) database calculated from input energy sources, materials used, transportation methods, and manufacturing processes at the system boundary was analyzed. Based on the environmental impact assessment index methodology of the Ministry of Environment from the LCI data analysis of synthetic resin formwork, the environmental impact assessment was carried out through classification, normalization, characterization, and weighting process. The experimental results are as follows the amount of CO₂ (carbon) emission considering the number of conversions was about 32% lower than that of the Euroform. This shows that the use of synthetic resin formwork reduces material production by half compared to Euroform and reduces CO₂ (carbon) emissions.

• Journal of the Korean Society of Environmental Restoration Technology
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• v.8 no.3
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• pp.53-66
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• 2005

The objective of this study is the classification of priority areas for the implementation of green roof by evaluating environmental deterioration in Seoul. Non-permeable pavement, air pollution, habitual floods, energy use, heat island and green space are considered in this assessment indicators. The expert questionnaire survey was conducted in order to determine the most important indicators. These indicators were then, thoroughly evaluated. As a result, high priority areas for the implementation of green roof were deduced in the following order of the districts : Jung, Sungdong, Jungrang, Youngdungpo, Jongro and Kangnam. The highest priority areas were determined to be crowded business-commercial areas. Low priority areas are analyzed in the following order of the districts : Kwanak, Nowon, Seocho and Dobong. The result of this study can be utilized for environmental planning and decision of related policies. Additionally, it can be promoted that awareness of implementing green roof of citizens, policy makers and building owners and effect of green networking between inside and outside Seoul can be increased.

• Proceedings of the KSRS Conference
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• v.2
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• pp.868-871
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• 2006

Mortality of domestic people from cardiovascular disease ranked second, which followed that of from cancer last year. Therefore, it is very important and urgent to enhance the reliability of medical examination and treatment for cardiovascular disease. Heart Rate Variability (HRV) is the most commonly used noninvasive methods to evaluate autonomic regulation of heart rate and conditions of a human heart. In this paper, our aim is to extract a quantitative measure for HRV to enhance the reliability of medical examination for cardiovascular disease, and then develop a prediction method for extracting multi-parametric features by analyzing HRV from ECG. In this study, we propose a hybrid Bayesian classifier called FP-based Bayesian. The proposed classifier use frequent patterns for building Bayesian model. Since the volume of patterns produced can be large, we offer a rule cohesion measure that allows a strong push of pruning patterns in the pattern-generating process. We conduct an experiment for the FP-based Bayesian classifier, which utilizes multiple rules and pruning, and biased confidence (or cohesion measure) and dataset consisting of 670 participants distributed into two groups, namely normal and patients with coronary artery disease.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.24 no.11
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• pp.2875-2882
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• 2000

Typically, the ultrasonic sensors can be used in navigation systems for modeling of the enviornment, obstacle avoidance, and map building. In this paper, we tried to approach an object classification method using the range data of the ultrasonic sensors. A characterization of the sonar scan is described that allows the differentiation of planes, corners, edges, cylindrical and rectangular pillars by processing the scanned data from three sonars. To use the data from the ultrasonic sensors as input to the neural networks, we have introduced a clustering, threshold, and bit operation algorithm for the obtained raw data, After repeated training of the neural network, the performance of the proposed method was obtained through experiments. Also, the recognition ranges of the proposed method were investigated. As a result of experiments, we found that the proposed method successfully recognized the objects within the accuracy of 78%.

• Journal of the Korean Institute of Landscape Architecture
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• v.29 no.6
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• pp.27-36
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• 2002

The objective of this study is to improve the quality of the atmospheric environment by incorporating the factors of meteorology and urban climate into the field of urban and environmental planning. To this end, we have conducted a study on CLIMATOP and the mapping of urban climate, which are basic data used to analyze changes in climatic factors and the stagnation and accumulation of air pollutants. In particular, we focused on understanding the formation and movement of cold fresh air and its influx into urban areas by measuring and analyzing climatic factors. As a study result, classification criteria far CLIMATOP and a urban climatic map were made. In addition, we analyzed a digital elevation model, climatic data, and isothermal curves. As a result, we identified the corridor through which cold fresh air moves. We also observed that the temperature of the fluxed cold fresh air increased as land use changed. When the results of this study are applied to urban re-development and re-building projects, which require preliminary environmental assessment and environmental impact assessment, the practice proposed by this study is expected to contribute to the natural purification of air pollution activating the movement of cold fresh air and its influx into urban areas.

• Knowledge Management Research
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• v.19 no.4
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• pp.59-76
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• 2018

With the arrival of the big data era, customer data and data mining analysis have gradually dominated the process of Customer Relationship Management (CRM). This phenomenon indicates that customer data along with the use of information techniques (IT) have become the basis for building a successful CRM strategy. However, some companies can not discover valuable information through a large amount of customer data, which leads to the failure of making appropriate business strategy. Without suitable strategies, the companies may lose the competitive advantage or probably go bankrupt. The purpose of this study is to propose CRM strategies by segmenting customers into VIPs and Non-VIPs and identifying purchase patterns using the the VIPs' transaction data and data mining techniques (K-means clustering and association rules) of online shopping mall in Korea. The results of this paper indicate that 227 customers were segmented into VIPs among 1866 customers. And according to 51,080 transactions data of VIPs, home product and women wear are frequently associated with food, which means that the purchase of home product or women wears mainly affect the purchase of food. Therefore, marketing managers of shopping mall should consider these shopping patterns when they build CRM strategy.

• Smart Structures and Systems
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• v.30 no.4
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• pp.385-395
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• 2022

Detecting cracks on a concrete structure is crucial for structural maintenance, a crack being an indicator of possible damage. Conventional crack detection methods which include visual inspection and non-destructive equipment, are typically limited to a small region and require time-consuming processes. Recently, to reduce the human intervention in the inspections, various researchers have sought computer vision-based crack analyses: One class is filter-based methods, which effectively transforms the image to detect crack edges. The other class is using deep-learning algorithms. For example, convolutional neural networks have shown high precision in identifying cracks in an image. However, when the objective is to classify not only the existence of crack but also the types of cracks, only a few studies have been reported, limiting their practical use. Thus, the presented study develops an image processing procedure that detects cracks and classifies crack types; whether the image contains a crazing-type, single crack, or multiple cracks. The properties and steps in the algorithm have been developed using field-obtained images. Subsequently, the algorithm is validated from additional 227 images obtained from an open database. For test datasets, the proposed algorithm showed accuracy of 92.8% in average. In summary, the developed algorithm can precisely classify crazing-type images, while some single crack images may misclassify into multiple cracks, yielding conservative results. As a result, the successful results of the presented study show potentials of using vision-based technologies for providing crack information with reduced human intervention.

• Korean Journal of Construction Engineering and Management
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• v.24 no.4
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• pp.60-73
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• 2023

The need for adopting automation technologies to improve inefficiencies in interior finishing modeling work is increasing during the Building Information Modeling (BIM) design stage. As a result, the use of visual programming languages (VPL) for practical applications is growing. However, undefined or incorrect space designations in BIM models can hinder the development of automated finishing modeling processes, resulting in erroneous corrections and rework. To address this challenge, this study first developed a rule-based automated interior finishing detailing module for floors, walls, and ceilings. In addition, an automated space integrity checking module with 86.69% ACC using the Multi-Layer Perceptron (MLP) model was developed. These modules were integrated into a design automation module for interior finishing, which was then verified for practical utility. The results showed that the automation module reduced the time required for modeling and integrity checking by 97.6% compared to manual work, confirming its utility in assisting BIM model development for interior finishing works.