• International conference on construction engineering and project management
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• 2024.07a
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• pp.311-318
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• 2024

Quality control in construction projects necessitates the detection of defects during construction. Currently, this task is performed manually by site supervisors. This manual process is inefficient, labor-intensive, and prone to human error, potentially leading to decreased productivity. To address this issue, research has been conducted to automate defect detection using computer vision-based object detection technologies. However, these studies often suffer from a lack of data for training deep learning models, resulting in inadequate accuracy. This study proposes a method to improve the accuracy of deep learning models through the use of virtual image data. The target building is created as a 3D model and finished with materials similar to actual components. Subsequently, a virtual defect texture is produced by layering three types of images: defect information, area information, and material information images, to fabricate materials with defects. Images are generated by rendering the 3D model and the defect, and annotations are created for segmentation. This approach creates a hybrid dataset by combining virtual data with actual site image data, which is then used to train the deep learning model. This research was conducted on the tile process of finishing construction projects, focusing on cracks and falls as the target defects. The training results of the deep learning model show that the F1-Score increased by 12.08% for falls and cracks when using the hybrid dataset compared to the real image dataset alone, validating the hybrid data approach. This study contributes not only to unmanned and automated smart construction management but also to enhancing safety on construction sites. To establish an integrated smart quality management system, it is necessary to detect various defects simultaneously with high accuracy. Utilizing this method for automatic defect detection in other types of construction can potentially expand the possibilities for implementing an integrated smart quality management system.

• Journal of Korean Society of Environmental Engineers
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• v.36 no.9
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• pp.629-640
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• 2014

In this study, the applicability of dynamic water quality model to TMDL system was examined, methods for setting of water quality goal and estimation of allocation loads were suggested and results of applying these methods were analyzed. HSPF model was applied for Miho stream basin as a dynamic water quality model. The model was calibrated using measurement data obtained in 2009~2010 and showed satisfactory performance in predicting daily variations of flow rate and BOD concentration. Methods for TMDL application were categorized into 3 cases; water quality management (1) considering low flow condition(Case I), (2) considering entire period of the year (Case II) and (3) considering the worst water quality condition (Case III). BOD water quality goals at the end of Miho stream watershed increased in the order of Case IICase I>Case III. If further researches on base precipitation and method for model input of nonpoint source pollutant were carried out, water quality could be managed more reasonably and scientifically by applying dynamic water quality model to TMDL. The result of this study is expected to be used as primary data for TMDL using dynamic water quality model.

• Journal of Korean Society for Quality Management
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• v.40 no.3
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• pp.278-285
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• 2012

Purpose: Weapon systems have the long life cycle unlike the consumer product. Thus, the reliability of weapon system is improved during the life cycle through the steady technical change. In this paper, we deal with the method of evaluating the reliability of weapon system with the field failure data. Methods: Especially, we present how to gather the field failure data and evaluate the reliability through the case of K-series weapon system. To evaluate reliability, the reliability growth model is used and the result is discussed. Results: It is steadily improved the reliability of K-series weapon system deployed from 2000 to 2004. The frequency of the failures that affect the mission is largely reduced and MTBMF(mean time between mission failure) is also improved. Conclusion: We can guess the trend of the reliability of weapon system with the field data through this study. Furthermore, it can be used to improve the reliability and make maintenance policy.

• Journal of Environmental Impact Assessment
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• v.18 no.2
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• pp.59-67
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• 2009

Water quality of the Lake Youngrang in the Sokcho City is eutrophic. Jangcheon is the largest inflow source to the lake. Major pollutant sources are stormwater runoff from resort areas and various land uses in the Jangcheon watershed. A storm sewer on the southern end of the lake is also an important pollution source. In this study, water quality modelling for Lake Youngrang was carried out considering the rainfall-runoff pollution loads from the watershed. The rainfall-runoff curves and the rainfall-runoff pollutant load curves were derived from the rainfall-runoff survey data during the recent 4 years. The rainfall-runoff pollution loads and flow from the Jangcheon watershed and the storm sewer were estimated using the two kinds of curves, and they were used as the flow and the boundary data of the WASP model. With the measured water quality data of the year 2005 and 2006, WASP model was calibrated. Non-point pollution control measures such as wet pond and infiltration trench were considered as the alternative for water quality management of the lake. The predicted water quality were compared with those under the present condition, and the improvement effect of the lake water quality were analyzed.

• Journal of Korean Society for Quality Management
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• v.39 no.1
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• pp.90-97
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• 2011

The purpose of this study is to analyze various factors comprising a job satisfaction; determine possible factors that affects job satisfaction. Job satisfaction model is designed to evaluate major factors, such as job stress and strength, and to assess relationship between these factors. Partial least squares algorithm is used to develop a job satisfaction measurement model. To evaluate validity of developed model, survey data of health insurance review and assessment service is to applied.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.23 no.8
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• pp.1915-1925
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• 1998

The switching system software is large scale, real-time multi-task system which requires high reliability. The reliability assessment of large-scale software is very important for the success of software development project. For this raeson, the software quality measurement is much more important. In this paper, we have learned about the software reliability, metho of the analysis of failure data and estimation of software quality. To estimate the software reliability, using the failure data found during of the system test. We apply the two software reliability growth models, named Goel-Okumoto(G-O) and S-shaped model, to estimate the software reliability. Also, we compared with the results and we reviewed fully not only development cycle but validation and verification of the test data, for each software versions. This paper presents a software reliability model that suitale the software development project and the activeity of quality control for the switching system.

• Proceedings of the Korea Water Resources Association Conference
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• 1992.07a
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• pp.443-447
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• 1992

This study describes the strategy for advanced decision support system (ADSS) development for integrated management of water resources and quality in reservoir systems. The developed ADSS consists of database that contain hydrologic data, observed operational data, and data to support specific reservoir operations simulation, optimization models, and water quality models. The optimization model, mass balance simulation model and water quality models are used in a general prototype ADSS, menu driven controlling framework that assists the user to specify and evaluate the alternative operational scenarios at one time. These alternative scenarios are evaluated by the models and the results are compared through the use of a graphical based display system. This graphical based system uses an icon based schematic representation of the system to organize the presentation of the results. The ADSS includes the ability to use monthly or weekly time periods of analysis for the models and it can use monthly historical or stochastically generated inflows.

• The Journal of Information Technology and Database
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• v.3 no.2
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• pp.97-118
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• 1996

Information systems quality engineering is one of the most problematic areas in practice and research, and needs cooperative efforts between practice and theory [Glass, 1996]. A model for evaluating the quality of system development process and ensuing success is proposed based on information processing theory of project unit design. A nomological net among a set of quality variables is identified from prior research in the areas of organization science, software engineering, and management information systems. More specifically, system development success was modelled as a function of project complexity, system development modelling environment, user participation, project unit structure, resource availability, and the level of iterative nature of development methodology. Based on the model developed from the information processing theory of project unit design in organization science. appropriate quality metrics for each variable in the proposed model are matched. In this way, a framework of relevant systems development and success quality metrics for controlling systems development processes and ensuing success is proposed. The causal relationships among the constructs in the proposed model are proposed as future empirical research for academicians and as managerial tools for quality managers. The framework and propositions help quality manager to select more parsimonious quality metrics for controlling information systems development processes and project success in an integrated way. Also this model can be utilized for evaluating software quality assurance programmes, which are developed and marketed by many vendors.

• Magazine of the Korean Society of Agricultural Engineers
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• v.45 no.7
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• pp.83-93
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• 2003

This research compared the observed and model predicted results that include; runoff, sediment yield, and nutrient losses from a 2.71 ha cattle grazing pasture field in North Alabama. Application of water quality computer simulation models can inexpensively and quickly assess the impact of pasture management practices on water quality. AGNPS single storm based model was applied to the three pasture species; Bermudagrass, fescue, and Ryegrass. While comparing model predicted results with observed data, it showed that model can reasonably predict the runoff, sediment yield and nutrient losses from the watershed. Over-prediction and under-prediction by the model occurred during very high and low rainfall events, respectively. The study concluded that AGNPS model can be reasonably applied to assess the impacts of pasture management practices and chicken litter application on water quality.

• Proceedings of the Korea Database Society Conference
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• 2002.10a
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• pp.3-21
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• 2002

The purpose of this study is to demonstrate individual's mobile Internet acceptance by extending the technology acceptance model (TAM) to the field of the mobile Internet. This research utilized the structural equation model to examine the research model on the mobile Internet use. System quality and information quality as external variables were examined, and playfulness as an intrinsic factor was tested. The research model was successfully validated in the environment of extension model for the mobile internet.