• Journal of the Korean Geographical Society
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• v.42 no.5
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• pp.788-807
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• 2007

To better publish geographical information on the Web, it is important to capture how Web technologies are changing. For a recent decade, Semantic Web has been developed by incorporating ontologies into the current Web, with an aim to make computers understand rather than simply display. Ontology, an explicit specification of a conceptualization, and the Semantic Web grounded on the ontology, have the potential for effective sharing and appropriate retrieval of geographical information. This paper describes a Semantic Web Service over the mobile Web that can offer pertinent tourism information according to user contexts. To do this, a tourism ontology was formalized in the PARA(Place-Attraction-Resource-Activity) ontology model by organizing tourist places, tourist attractions, tourism resources, and activities. Locational relationships between tourist places were also included in the PARA ontology model to take into account the movements of tourists on a railway network. The XML(Extensible Markup Language) Web Service in the middle tier manages the client-side request for information retrieval and the corresponding server-side response from the data provider. The PARA ontology was integrated into the XML Web Service for the concept-based discovery of tourism information. The applicability of the proposed system was tested through a simulation experiment for Tokyo tourism.

• Journal of Korea Water Resources Association
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• v.52 no.spc2
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• pp.855-863
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• 2019

The efficiency of fishway installed in rivers can be directly evaluated by means of fish monitoring. On the other hand, when it is difficult to monitor the fish in certain conditions, or when planning a fishway, the efficiency can be evaluated indirectly through the hydraulic analysis. In this study, the hydraulic analysis technique for evaluating the efficiency of a fishway was presented. The River-2D model with the fish physical habitat module was used for the analysis of the attraction efficiency, and the weighted usable area was proposed as an index of the efficiency. In the analysis of passage efficiency, the three-dimensional model, Flow-3D, was used as an evaluation tool to describe the fluid behavior on a hydraulic structure with free surface. The ice-harbor type fishway at Baekgok weir in the Deokcheon River was selected as a test-site, and the efficiency was estimated using the hydraulic analysis. And then it was compared with fish monitoring data acquired from the river. As a result, it is difficult to replace the hydraulic analysis results with the efficiency quantitatively, but it can help to grasp the general tendency.

• Journal of the Society of Disaster Information
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• v.20 no.2
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• pp.257-269
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• 2024

Purpose: The purpose of this study is to explain the pivotal role of the travel forecasting process in urban transportation planning. This study emphasizes the use of travel forecasting models to anticipate future traffic. Method: This study examines the methodology used in urban travel demand modeling within transportation planning, specifically focusing on the Urban Transportation Modeling System (UTMS). UTMS is designed to predict various aspects of urban transportation, including quantities, temporal patterns, origin-destination pairs, modal preferences, and optimal routes in metropolitan areas. By analyzing UTMS and its operational framework, this research aims to enhance an understanding of contemporary urban travel demand modeling practices and their implications for transportation planning and urban mobility management. Result: The result of this study provides a nuanced understanding of travel dynamics, emphasizing the influence of variables such as average income, household size, and vehicle ownership on travel patterns. Furthermore, the attraction model highlights specific areas of significance, elucidating the role of retail locations, non-retail areas, and other locales in shaping the observed dynamics of transportation. Conclusion: The study methodically addressed urban travel dynamics in a four-ward area, employing a comprehensive modeling approach involving trip generation, attraction, distribution, modal split, and assignment. The findings, such as the prevalence of motorbikes as the primary mode of transportation and the impact of adjusted traffic patterns on reduced travel times, offer valuable insights for urban planners and policymakers in optimizing transportation networks. These insights can inform strategic decisions to enhance efficiency and sustainability in urban mobility planning.

• 한국지형공간정보학회:학술대회논문집
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• 2004.10a
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• pp.5-10
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• 2004

The purpose of this research is to measure a gravitational attraction about urban pulbic service facilities and to evaluate the location of public service facilities. It is important in that these facilities should provide more inexpensive and convenience public service to users. To do this, the GIS's spatial analysis and gravity model were used to analyze the efficiency of the public facilities. The gravity model was conducted as the main analysis method, and another model for this analysis was the discrete model. The gravity model is originally to anticipate migration flows, traffic flows and other types of movements so that this model compares the gravitational attraction between places. The discrete model is to find the optimal location and to evaluate a location of facility regarding urban areas as the combination of node and link. In this research, these two models were adopted to compare and analyze location of Mapo-Gu Office. The results of this research indicated that the locational evaluation of urban public service facilities discovered the appropriateness of those facilities, and the public facilities was necessary to displace to other site.

• Journal of the Korean Institute of Landscape Architecture
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• v.50 no.6
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• pp.42-57
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• 2022

This study aims to create a basic model for classifying the activity photos that urban park users shared on social media using Deep Learning through Artificial Intelligence. Regarding the social media data, photos related to urban parks were collected through a Naver search, were collected, and used for the classification model. Based on the indicators of Naturalness, Potential Attraction, and Activity, which can be used to evaluate the characteristics of urban parks, 21 classification categories were created. Urban park photos shared on Naver were collected by category, and annotated datasets were created. A custom CNN model and a transfer learning model utilizing a CNN pre-trained on the collected photo datasets were designed and subsequently analyzed. As a result of the study, the Xception transfer learning model, which demonstrated the best performance, was selected as the urban park user activity image classification model and evaluated through several evaluation indicators. This study is meaningful in that it has built AI as an index that can evaluate the characteristics of urban parks by using user-shared photos on social media. The classification model using Deep Learning mitigates the limitations of manual classification, and it can efficiently classify large amounts of urban park photos. So, it can be said to be a useful method that can be used for the monitoring and management of city parks in the future.

• Journal of Korean Society of Transportation
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• v.23 no.2
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• pp.143-150
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• 2005

Estimation of trip distribution, estimated O-D matrix must satisfy the condition that the sum of trips in a row should equal the trip production, and the sum of trips in a column should equal the trip attraction. In most cases the iterative calculation for convergence is needed to satisfy this condition. Most of all present convergence of iterative methods may results a big difference between estimated value and converged value, and from this, the trip distribution patterns may be changed. This paper presents a new convergence of iterative method that comes closer to meeting the convergence condition and gives the maximum likelihood estimation for calculating a distribution patterns from the trip distribution estimation model. The newly developed method differs from existing methods in three important ways. First, it simultaneously considers both the convergence condition and the distribution patterns. Second, it computers simultaneous convergence of rows and columns instead of iterating respectively. Third, instead of using the growth rates to the trip production, trip attraction, it uses the differences between trip production and sum of trips in a row, and trip attraction and sum of trips in a column. Using 38 by 38 O-D matrix, this paper compared the Fratar method and the Furness method to the newly developed method and found that this method was superior to the other two methods.

• International Journal of Highway Engineering
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• v.12 no.4
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• pp.93-100
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• 2010

Trip generation is the first step in the conventional four-step model and has great effects on overall demand forecasting, so accuracy really matters at this stage. A linear regression model is widely used as a current trip generation model for such plans as urban transportation and SOC facilities, assuming that the relationship between each socio-economic index and trip generation stays linear. But when rapid urban development or an urban planning structure has changed, socio-economic index data for trip estimation may be lacking to bring many errors in estimated trip. Hence, instead of assuming that a socio-economic index widely used for a general purpose, this study aims to develop a new trip generation model by type based on the market separation for the variables to reflect the characteristics of various zones. The study considered the various characteristics (land use, socio-economic) of zones to enhance the forecasting accuracy of a trip generation model, the first-step in forecasting transportation demands. For a market separation methodology to improve forecasting accuracy, data mining (CART) on the basis of trip generation was used along with a regression analysis. Findings of the study indicated as follows : First, the analysis of zone characteristics using the CART analysis showed that trip production was under the influence of socio-economic factors (men-women relative proportion, age group (22 to 29)), while trip attraction was affected by land use factors (the relative proportion of business facilities) and the socio-economic factor (the relative proportion of third industry workers). Second, model development by type showed as a result that trip generation coefficients revealed 0.977 to 0.987 (trip/person) for "production" 0.692 to 3.256 (trip/person) for "attraction", which brought the necessity for type classifications. Third, a measured verification was conducted, where "production" and "attraction" showed a higher suitability than the existing model. The trip generation model by type developed in this study, therefore, turned out to be superior to the existing one.

• Journal of Korean Society of Transportation
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• v.17 no.5
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• pp.99-110
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• 1999

This study deals with the adaptability questions of O-D table estimation models. Its objectives are two-fold; (1) to estimate the characteristics of various O-D table estimation models(i.e. linear regression models. entropy models and statistic models) and (2) to find the model which estimates the O-D table with the best accuracy under the various data conditions. In Pursuing the above, this study gives the particular attentions to the test of the models, using the Sioux Falls network and equilibrium assignment method of MINUTP. The major findings are the followings. Firstly. it finds that the statistic models have the most goodness of fat among all models, if the required data are all Prepared. But it Presents that statistic models are the most sensitive against the underspecification and inconsistency problems of link data. Secondly, It shows that the linear regression models have the worst goodness of fat among all models. But the linear regression models are the most insensitive to the underspecification and inconsistency problems. Thirdly, THE/1 model of entropy model is sensitive against the underspecification and incon-sistency problems, but THE/2 model is insensitive. Finally, other informations like total volume, zonal Production and attraction volumes in 0-D table, help models to gain the better goodness of fit. Especially, in the statistic models. both the zonal production and attraction volume data are helpful to estimate the link volumes. It can be expected that the results dive some implications not only to the selection of optimal model under the various given data, but also to the development or modification of model.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.17 no.10
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• pp.2609-2626
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• 2023

The hotel industry is an example of experiential services. As consumers cannot fully evaluate the online review content and quality of their services before booking, they must rely on several online reviews to reduce their perceived risks. However, individuals face information overload owing to the explosion of online reviews. Therefore, consumer cognitive fluency is an individual's subjective experience of the difficulty in processing information. Information complexity influences the receiver's attitude, behavior, and purchase decisions. Individuals who cannot process complex information rely on the peripheral route, whereas those who can process more information prefer the central route. This study further discusses the influence of the complexity of review information on hotel ratings using online attraction review data retrieved from TripAdvisor.com. This study conducts a two-level empirical analysis to explore the factors that affect review value. First, in the Peripheral Route model, we introduce a negative binomial regression model to examine the impact of intuitive and straightforward information on hotel ratings. In the Central Route model, we use a Tobit regression model with expert reviews as moderator variables to analyze the impact of complex information on hotel ratings. According to the analysis, five-star and budget hotels have different effects on hotel ratings. These findings have immediate implications for hotel managers in terms of better identifying potentially valuable reviews.

• Journal of the Korean Society of Industry Convergence
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• v.27 no.3
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• pp.535-546
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• 2024

This research aims to develop a model to objectively and quantitatively measure the skill level of aircraft body assembly workers. Because aircraft body assembly is predominantly a manual process, skills management is a key factor of manufacturing competitiveness. Currently, skills management relies on the subjective judgment of supervisors, which lacks objectivity and reliability. As a remedy, this study proposed a systematic skill management model based on objective and quantitative evaluation criteria. By considering prior research, we developed an evaluation model that takes into account both expertise and versatility of a worker. The model selected five major tasks required for aircraft body assembly and established evaluation criteria considering the difficulty and maturity of each task. We then conducted a pilot evaluation with over 200 workers in four SMEs to validate the practicality and effectiveness of the model. Consequently, we identified and addressed the limitations of the existing evaluation method, subdivided the skill levels based on the performance capabilities of each task, and proposed a career growth path. The developed evaluation model offers critical data for executives and managers to determine work assignments, education, training, performance incentives, and wages. It is expected to enhance the attraction of new talent and systematize skills management in aviation manufacturing in the future.