• Journal of the Korean Geotechnical Society
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• v.25 no.5
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• pp.53-64
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• 2009

Many slope failures are induced by rainfall infiltration. A lot of recent researches are therefore focused on rainfall-induced slope instability and the rainfall infiltration is recognized as the important triggering factor. The rainfall infiltrates into the soil slope and makes the matric suction lost in the slope and even the positive pore water pressure develops near the surface of the slope. They decrease the resisting shear strength. In Korea, a few public institutions suggested conservative slope design guidelines that assume a fully saturated soil condition. However, this assumption is irrelevant and sometimes soil properties are misused in the slope design method to fulfill the requirement. In this study, a more relevant slope stability evaluation method is suggested to take into account the real rainfall infiltration phenomenon. Unsaturated soil properties such as shear strength, soil-water characteristic curve and permeability for Korean weathered soils were obtained by laboratory tests and also estimated by artificial neural network models. For real-time assessment of slope instability, failure warning criteria of slope based on deterministic and probabilistic analyses were introduced to complement uncertainties of field measurement data. The slope stability evaluation technique can be combined with field measurement data of important factors, such as matric suction and water content, to develop an early warning system for probably unstable slopes due to the rainfall.

• Asia-pacific Journal of Multimedia Services Convergent with Art, Humanities, and Sociology
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• v.7 no.4
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• pp.193-202
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• 2017

With the growth of Chinese manufacturing industry and strengthening of manufacturing industry in advanced countries, the competitiveness of Korean manufacturing industry has become weak. Accordingly, it is time when energy for new growth is required very strongly. This research is the basic research to construct a cognitive and emotional information system to support sound design in manufacturing industry, and aims to develop AUI (Auditory User Interface) guideline. To fulfill research aims, this research conducted interviews to persons belonging to the manufacturing industry, and analyzed contexts and major characteristics related with AUI design. In addition, this research conducted survey on 269 persons on user preference on representative function of products. By analyzing survey data, this research examined the most suitable melody method for each sound, and difference in user preference between men and women. Based on beep sound, it performed analysis focusing on the number of sounds, melody types, and code. It also extracted AUI guidelines usable when users of the product into male and female. This research has significance in the sense that it built the basic guide data which can support AUI design in manufacturing industry.

• Journal of Korean Tunnelling and Underground Space Association
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• v.11 no.1
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• pp.11-22
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• 2009

Tunnel excavation with several sections and appropriate auxiliary measures such as face bolt and pre-grouting are widely used in case of weak and less rigid ground for the stability of a tunnel face during excavation. This papers first described the evaluation methods proposed in technical literature to maintain the tunnel face stable, and then studied by FEM analysis whether face reinforcement is need in what degree of ground deformation and strength features for the stability of a tunnel face when excavating by full excavation with sub-bench. Lastly, a three dimensional FEM analysis was performed to study how the tunnel face itself and the ground around the tunnel behave depending on different bolt layouts, length of bolts, number of bolts. There were relative differences in comparison of results on the stability of a tunnel face by a theoretical evaluation methods and FEM analysis, but the same in reinforced effect of face. It was found that the stability of a tunnel face can be obtained with face bolt installed longer than 1.0D (tunnel width), bolt density of about 1 bolt per every $1.5\;m^2$ (layout of grid type), and reinforcement area of $120^{\circ}$ arch area of upper section.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.28 no.3D
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• pp.317-323
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• 2008

Mass transit information can contribute many benefits to users. Especially, transportation information technology is developing highly with information technology in Korea recently. Hereafter, it is expected to give customized transportation information to users individually with the advent of ubiquitous age in earnest. This public transportation information service can be realized by path finding algorithm in public transportation networks including travel and transfer attributes. In this research, constraints are constructed with the primary facts influencing users. Moreover, the method reducing user's path finding condition arbitrarily is proposed by making the maximum value as variables. In this study, transfer frequency, total travel time, seat confirmation, transfer time and travel time become constraint condition based on k path finding algorithm considering service time constraint condition. Moreover, case study about user customized transfer information is performed in Seoul and metropolitan subway networks.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.28 no.5A
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• pp.699-707
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• 2008

For most structural evaluation of bridge integrity, it is very important to measure the geometric profile, which is a major factor representing the global behavior of civil structures, especially bridges. In the past, because of the lack of appropriate methods to measure the deflection profile of bridges on site, the measurement of deflection has been restricted to just a few discrete points along the bridge, and the measuring points have been limited to the locations installed with displacement transducers. Thus, some methods for predicting the static deflection by using fiber optic strain sensors has been applied to simply supported bridges. In this study, a method of estimating the static deflection profile by using strains measured from suspension bridges was proposed. Based on the classical deflection theory of suspension bridges, an equation of deflection profile was derived and applied to obtain the actual deflection profile on Namhae suspension bridge. Field load tests were carried out to measure strains from FBG strain sensors attached inside the stiffening girder of the bridge. The predicted deflection profiles were compared with both precise surveying data and numerical analysis results. Thus, it is found that the equation of predicting the deflection profiles proposed in this study could be applicable to suspension bridges and the FBG strain sensors could be reliable on acquiring the strain data from bridges on site.

• Journal of Korean Society of Disaster and Security
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• v.16 no.2
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• pp.49-56
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• 2023

Impact based forecast refers to providing information on potential socioeconomic risks according to weather conditions, away from the existing weather factor-oriented forecast. Developed weather countries are investing manpower and finances in technology development to provide and spread impact information, but awareness of impact based forecasts has not spread in Korea. In addition, the focus is on disasters such as floods and typhoons, which cause a lot of damage to impact based forecasts, and research on evaluating the impact of vehicle risks due to strong winds in the transportation sector with relatively low damage is insufficient. In Korea, there are not many cases of damage to vehicle conduction caused by strong winds, but there are cases of damage and the need for research is increasing. Road vulnerability is required to evaluate the risk of vehicles caused by strong winds, and the purpose of this study was to calculate the criteria for road vulnerability. The road vulnerability evaluation was evaluated by the altitude of the road, the number of lanes, the type of road. As a result of the analysis, it was found that the vulnerable area was well reproduced. It is judged that the results of this study can be used as a criterion for preparing an objective evaluation of potential risks for vehicle drivers.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.24 no.2
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• pp.15-21
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• 2024

The purpose of this study is to propose a framework for the introduction and evaluation of artificial intelligence (AI) services not only in general applications but also in public policies. To achieve this, the study explores AI service management and governance toolkits, providing insights into how to introduce AI services in public policies. Firstly, it offers guidelines on the direction of AI service development and what aspects to avoid. Secondly, in the development phase, it recommends using the AI governance toolkit to review content through checklists at each stage of design, development, and deployment. Thirdly, when operating AI services, it emphasizes the importance of adhering to principles related to 1) planning and design, 2) the lifecycle, 3) model construction and validation, 4) deployment and monitoring, and 5) accountability. The governance perspective of AI services is crucial for mitigating risks associated with service provision, and research in risk management aspects should be conducted. While embracing the advantages of AI, proactive measures should be taken to address limitations and risks. Efforts should be made to efficiently formulate policies using AI technology to create high value and provide meaningful societal impacts.

• The Journal of Bigdata
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• v.9 no.1
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• pp.31-47
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• 2024

With the advancement of artificial intelligence, the travel and hospitality industry is also adopting AI and machine learning technologies for various purposes. In the tourism industry, demand forecasting is recognized as a very important factor, as it directly impacts service efficiency and revenue maximization. Demand forecasting requires the consideration of time-varying data flows, which is why statistical techniques and machine learning models are used. In recent years, variations and integration of existing models have been studied to account for the diversity of demand forecasting data and the complexity of the natural world, which have been reported to improve forecasting performance concerning uncertainty and variability. This study also proposes a new model that integrates various machine-learning approaches to improve the accuracy of hotel sales demand forecasting. Specifically, this study proposes a new time series forecasting model based on XGBoost that selectively utilizes a local model by clustering with DTW K-means and a global model using the entire data to improve forecasting performance. The hotel demand forecasting model that selectively utilizes global and regional models proposed in this study is expected to impact the growth of the hotel and travel industry positively and can be applied to forecasting in other business fields in the future.

• Korean Journal of Construction Engineering and Management
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• v.13 no.4
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• pp.152-163
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• 2012

At the conceptual phase of a construction project, estimated construction cost is very important as it significantly influences the owner's decision-making. Accurate cost estimating, in the early stage of a public construction project, serves as a critical factor because initial decision-making effects the final cost of a construction project. However in the cases of Korean public apartment projects, excluding a few of the public owners, there is a problem in properly estimating construction cost due to the lack of construction cost estimating system. Thus, this research developed a public apartment cost estimating system using case-based reasoning that was suggested by a previous research with 66 cases of Korean public apartment projects. Based on the system experiments involving 19 public officers and 10 cases of Korean public apartment projects, the effectiveness of the system in terms of estimation accuracy and user-friendly was confirmed. As a result, the developed system has an error range of 1.47% to 13.74% and mean of 6.15%. In addition, the system was evaluated that it could greatly improve the current estimation task of public officers. Consequently, the results of this research can be used as a foundation for a technological advance in estimating construction cost and improving the accuracy and consistency of construction cost estimation.

• Journal of Digital Contents Society
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• v.13 no.1
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• pp.1-11
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• 2012

The BBS of Web Site is a space of informational communication to share information. At the moment, countless information is shared through various kinds of BBS. The shared information through the Web BBS can be gains to someone and losses to the other. Thus, for a long time, there have been many researches about technologies, which monitor information uploaded to Web BBS in real-time and inform the results to subjects. For BBS monitoring, existing methods have utilized direct approaches to DB or open API. Also, e-mail addresses have been utilized to inform results to subjects. However, there are two main problems for these methods. The one is a problem on closed BBS, which cannot be accessed, and the other is impossibility of supporting real-time alarm to e-mail. Especially, the real-time support for services, such as monitoring, is extremely important, since the main purpose of monitoring is based on the counter action for the result. The mobile Web has a merit to be accessed in anywhere, so that it is quite suitable for services requiring real-time support. However, the real-time support of mobile device has not been utilized enough, because each mobile phone has different standards of contents so that the contents should be pre-created. This paper suggests a technology that overcomes pitfalls of mobile Web while it is out of standard, and shows how the effect can be maximized through services such as monitoring, which requires the real-time support.