• Journal of Convergence for Information Technology
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• v.12 no.4
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• pp.260-269
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• 2022

In this paper, We propose an anomaly detection model using deep neural network to automate the identification of outliers of the national air pollution measurement network data that is previously performed by experts. We generated training data by analyzing missing values and outliers of weather data provided by the Institute of Environmental Research and based on the BeatGAN model of the unsupervised learning method, we propose a new model by changing the kernel structure, adding the convolutional filter layer and the transposed convolutional filter layer to improve anomaly detection performance. In addition, by utilizing the generative features of the proposed model to implement and apply a retraining algorithm that generates new data and uses it for training, it was confirmed that the proposed model had the highest performance compared to the original BeatGAN models and other unsupervised learning model like Iforest and One Class SVM. Through this study, it was possible to suggest a method to improve the anomaly detection performance of proposed model while avoiding overfitting without additional cost in situations where training data are insufficient due to various factors such as sensor abnormalities and inspections in actual industrial sites.

• Korean Journal of Heritage: History & Science
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• v.57 no.1
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• pp.82-108
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• 2024

With the transition of archaeological recording method's transition from analog to digital, the 3D scanning technology has been actively adopted within the field. Research on the digital archaeological digital data gathered from 3D scanning and photogrammetry is continuously being conducted. However, due to cost and manpower issues, most buried cultural heritage organizations are hesitating to adopt such digital technology. This paper aims to present a digital recording method of relics utilizing open-source software and photogrammetry technology, which is believed to be the most efficient method among 3D scanning methods. The digital recording process of relics consists of three stages: acquiring a 3D model, creating a joining map with the edited 3D model, and creating an digital drawing. In order to enhance the accessibility, this method only utilizes open-source software throughout the entire process. The results of this study confirms that in terms of quantitative evaluation, the deviation of numerical measurement between the actual artifact and the 3D model was minimal. In addition, the results of quantitative quality analysis from the open-source software and the commercial software showed high similarity. However, the data processing time was overwhelmingly fast for commercial software, which is believed to be a result of high computational speed from the improved algorithm. In qualitative evaluation, some differences in mesh and texture quality occurred. In the 3D model generated by opensource software, following problems occurred: noise on the mesh surface, harsh surface of the mesh, and difficulty in confirming the production marks of relics and the expression of patterns. However, some of the open source software did generate the quality comparable to that of commercial software in quantitative and qualitative evaluations. Open-source software for editing 3D models was able to not only post-process, match, and merge the 3D model, but also scale adjustment, join surface production, and render image necessary for the actual measurement of relics. The final completed drawing was tracked by the CAD program, which is also an open-source software. In archaeological research, photogrammetry is very applicable to various processes, including excavation, writing reports, and research on numerical data from 3D models. With the breakthrough development of computer vision, the types of open-source software have been diversified and the performance has significantly improved. With the high accessibility to such digital technology, the acquisition of 3D model data in archaeology will be used as basic data for preservation and active research of cultural heritage.

• Korean Journal of Construction Engineering and Management
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• v.13 no.6
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• pp.94-106
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• 2012

In recent years, the risks and uncertainties associated with mixed used development in urban regeneration projects which have actively been implemented at home and abroad have been on the rise due to the uncertainties of the initial business plan, difficulty of financing, increase in total cost and schedule delay. To cope with rapid social and economic changes and optimize benefits, a risk-based configuration management process that considers life cycle is required, along with accurate planning in the early stage of the business. In addition, it is necessary to prepare measures that can respond to the evaluation and measurement of the configuration factors in relation to the business process. However, the focus of previous studies on configuration management in the field of construction was mainly on humanities and the sociological aspects such as organization, leadership, ideology and similar concepts. There has been limited research on the process and measurement and evaluation methods for configuration factors required in decision-making on the risks and changes that can occur in the actual project implementation phase. Accordingly, in this study, we defined risk-based configuration factors and developed a process and MECA/3DAM/CII methodology to measure and evaluate these factors so as to carry out systematic configuration management of mixed used development in urban regeneration projects.

• The Journal of Industrial Distribution & Business
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• v.10 no.6
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• pp.39-50
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• 2019

Purpose - Since the local liquor industry uses the agricultural products produced in the region as the main raw material, cultivation of the industry can be a way to expand the demand for domestic agricultural products and can contribute to the income increase of the farmers. In addition, the local liquor industry can be developed into a region-specific industry differentiated from other regions by linking with the region's tourism resources. Therefore, in order to achieve various derivative effects through promotion of the local liquor industry, it is necessary to precisely understand the factors related to the purchase and consumption of local liquor which then will lead to an increase in consumption. This study analyzes the current status and problems of local liquor industries and examines the determinants of consumers' purchasing decisions of regional specialties through questionnaires. We will then propose a strategy to promote consumption of locally produced alcoholic beverages. Research design, data, and methodology - An online Domestic Consumer Survey was conducted to identify the actual purchases and uses of local liquors for 500 consumers nationwide. Based on the questionnaire results, the analysis uses an ordered probit model. Results - As a result of analyzing the effect of consumer characteristics on the purchase of local liquors, it was found that the average cost of drinking, income, local specialty, brewery experience, and health concerns have a significant effect on gender, drinking frequency. All the variables except the participation in the training of the special provincial manufacturing method were found to be statistically significant. The statistical significance was at a 1% significance level for the remaining factors excluding the bottle design. This shows that the higher taste, quality, price, and harmony with food, the higher the probability of purchasing local liquors. Conclusions - In the analysis of factors influencing the purchase intention of local liquors, it was found that factors such as taste, quality, price, and harmony with food had a significant effect. Given the diversity of purchasing factors, the importance of diversification strategies is emphasized again. In particular, it will be important to secure wide publicity for local liquors through various PR strategies.

• Proceedings of the Korean Institute Of Construction Engineering and Management
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• 2006.11a
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• pp.98-102
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• 2006

This study was conducted to derive a priority of investment in educational facilities by collecting and analyzing investment records from elementary, middle, and high schools in Chung Nam area. In addition, the AHP survey and analysis were performed in order to draw the priority item in the educational facility improvement. Students, parents, teachers and a educational facility managers from those schools provided their opinions and data for the AHP study. As a result of the study, the actual investment-cost and a lack of educational facilities were found. A priority item based on the above study was derived which can be used to increase user's satisfaction in the educational facilities. The result of this study can be used as a basis to improve the environment of the educational facilities.

• Cartoon and Animation Studies
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• s.49
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• pp.1-23
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• 2017

3D animation production has had a pivotal position in current animation industry and the necessity of professional management tool for 3D animation production has claimed due to its sophisticated pipeline from advance of technology and global production partnership trend. Shotgun and Ftrack are providing the most appropriate management toolset for 3D animation management among the extant management tools and the efficiency of Shotgun & Ftrack is identified compared with the traditional document oriented management style. The biggest strength of production management using Shotgun is that all of the production staff can directly participate in the communication on the tools therefore they can share the information on Shotgun & Ftrack in real time without constraint of time and location. Moreover, all the process of the production and the history of the discussion on certain production issues are systematically accrue on the tool so that the production history can be easily tracked. Finally, the production management using tools contributes collecting and analysing the production information for the production management team in studios. However, Shotgun & Ftrack has metadata based retrieval method which cost huge amount of effort by human's manual annotation and it also has the limitation of accuracy. In addition, the fact that studios has to have technical professionals first in order to institute the tools into their studios is the actual difficulty of Korean studios when they want to use management tools for their project. Thus, this paper suggests adopting the content-based retrieval system on the tools and tools' expanded technical service for the studios as the solution of the identified issues.

• KIPS Transactions on Software and Data Engineering
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• v.10 no.10
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• pp.391-398
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• 2021

Since the leased line is a structure that exclusively uses two connected areas for data transmission, a stable quality level and security are ensured, and despite the rapid increase in the number of switched lines, it is a line method that is continuously used a lot in companies. However, because the cost is relatively high, one of the important roles of the network operator in the enterprise is to maintain the optimal state by properly arranging and utilizing the resources of the network leased line. In other words, in order to properly support business service requirements, it is essential to properly manage bandwidth resources of leased lines from the viewpoint of data transmission, and properly predicting and managing leased line usage becomes a key factor. Therefore, in this study, various prediction models were applied and performance was evaluated based on the actual usage rate data of leased lines used in corporate networks. In general, the performance of each prediction was measured and compared by applying the smoothing model and ARIMA model, which are widely used as statistical methods, and the representative models of deep learning based on artificial neural networks, which are being studied a lot these days. In addition, based on the experimental results, we proposed the items to be considered in order for each model to achieve good performance for prediction from the viewpoint of effective operation of leased line resources.

• Journal of Navigation and Port Research
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• v.46 no.6
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• pp.562-569
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• 2022

The alarm monitoring technology applied to existing operating ships manages data items such as temperature and pressure with AMS (Alarm Monitoring System) and provides an alarm to the crew should these sensing data exceed the normal level range. In addition, the maintenance of existing ships follows the Planned Maintenance System (PMS). whereby the sensing data measured from the equipment is monitored and if it surpasses the set range, maintenance is performed through an alarm, or the corresponding part is replaced in advance after being used for a certain period of time regardless of whether the target device has a malfunction or not. To secure the reliability and operational safety of ship engine operation, it is necessary to enable advanced diagnosis and prediction based on real-time condition monitoring data. To do so, comprehensive measurement of actual ship data, creation of a database, and implementation of a condition diagnosis monitoring system for condition-based predictive maintenance of auxiliary equipment and piping must take place. Furthermore, the system should enable management of auxiliary equipment and piping status information based on a responsive web, and be optimized for screen and resolution so that it can be accessed and used by various mobile devices such as smartphones as well as for viewing on a PC on board. This update cost is low, and the management method is easy. In this paper, we propose CBM (Condition Based Management) technology, for autonomous ships. This core technology is used to identify abnormal phenomena through state diagnosis and monitoring of pumps and purifiers among ship auxiliary equipment, and seawater and steam pipes among pipes. It is intended to provide performance diagnosis and failure prediction of ship auxiliary equipment and piping for convergence analysis, and to support preventive maintenance decision-making.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.43 no.6
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• pp.841-849
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• 2023

Construction projects have risks due to various factors such as construction delays and construction accidents. Based on these construction risks, the method of calculating the construction period of the construction project is mainly made by subjective judgment that relies on supervisor experience. In addition, unreasonable shortening construction to meet construction project schedules delayed by construction delays and construction disasters causes negative consequences such as poor construction, and economic losses are caused by the absence of infrastructure due to delayed schedules. Data-based scientific approaches and statistical analysis are needed to solve the risks of such construction projects. Data collected in actual construction projects is stored in unstructured text, so to apply data-based risks, data pre-processing involves a lot of manpower and cost, so basic data through a data classification model using text mining is required. Therefore, in this study, a document-based data generation classification model for risk management was developed through a data classification model based on SVM (Support Vector Machine) by collecting construction project documents and utilizing text mining. Through quantitative analysis through future research results, it is expected that risk management will be possible by being used as efficient and objective basic data for construction project process management.

• Journal of Intelligence and Information Systems
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• v.20 no.4
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• pp.25-41
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• 2014

Recently, the number of social media users has increased rapidly because of the prevalence of smart devices. As a result, the amount of real-time data has been increasing exponentially, which, in turn, is generating more interest in using such data to create added value. For instance, several attempts are being made to analyze the relevant search keywords that are frequently used on new portal sites and the words that are regularly mentioned on various social media in order to identify social issues. The technique of "topic analysis" is employed in order to identify topics and themes from a large amount of text documents. As one of the most prevalent applications of topic analysis, the technique of issue tracking investigates changes in the social issues that are identified through topic analysis. Currently, traditional issue tracking is conducted by identifying the main topics of documents that cover an entire period at the same time and analyzing the occurrence of each topic by the period of occurrence. However, this traditional issue tracking approach has two limitations. First, when a new period is included, topic analysis must be repeated for all the documents of the entire period, rather than being conducted only on the new documents of the added period. This creates practical limitations in the form of significant time and cost burdens. Therefore, this traditional approach is difficult to apply in most applications that need to perform an analysis on the additional period. Second, the issue is not only generated and terminated constantly, but also one issue can sometimes be distributed into several issues or multiple issues can be integrated into one single issue. In other words, each issue is characterized by a life cycle that consists of the stages of creation, transition (merging and segmentation), and termination. The existing issue tracking methods do not address the connection and effect relationship between these issues. The purpose of this study is to overcome the two limitations of the existing issue tracking method, one being the limitation regarding the analysis method and the other being the limitation involving the lack of consideration of the changeability of the issues. Let us assume that we perform multiple topic analysis for each multiple period. Then it is essential to map issues of different periods in order to trace trend of issues. However, it is not easy to discover connection between issues of different periods because the issues derived for each period mutually contain heterogeneity. In this study, to overcome these limitations without having to analyze the entire period's documents simultaneously, the analysis can be performed independently for each period. In addition, we performed issue mapping to link the identified issues of each period. An integrated approach on each details period was presented, and the issue flow of the entire integrated period was depicted in this study. Thus, as the entire process of the issue life cycle, including the stages of creation, transition (merging and segmentation), and extinction, is identified and examined systematically, the changeability of the issues was analyzed in this study. The proposed methodology is highly efficient in terms of time and cost, as it sufficiently considered the changeability of the issues. Further, the results of this study can be used to adapt the methodology to a practical situation. By applying the proposed methodology to actual Internet news, the potential practical applications of the proposed methodology are analyzed. Consequently, the proposed methodology was able to extend the period of the analysis and it could follow the course of progress of each issue's life cycle. Further, this methodology can facilitate a clearer understanding of complex social phenomena using topic analysis.