• Journal of the Korea Society of Computer and Information
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• v.29 no.1
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• pp.273-285
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• 2024

With the active utilization of Online Judge (OJ) systems in the field of education, various studies utilizing learner data have emerged. This research proposes a problem recommendation based on a user-based collaborative filtering approach with learner data to support learners in their problem selection. Assistance in learners' problem selection within the OJ system is crucial for enhancing the effectiveness of education as it impacts the learning path. To achieve this, this system identifies learners with similar problem-solving tendencies and utilizes their problem-solving history. The proposed technique has been implemented on an OJ site in the fields of algorithms and programming, operated by the Chungbuk Education Research and Information Institute. The technique's service utility and usability were assessed through expert reviews using the Delphi technique. Additionally, it was piloted with site users, and an analysis of the ratio of correctness revealed approximately a 16% higher submission rate for recommended problems compared to the overall submissions. A survey targeting users who used the recommended problems yielded a 78% response rate, with the majority indicating that the feature was helpful. However, low selection rates of recommended problems and low response rates within the subset of users who used recommended problems highlight the need for future research focusing on improving accessibility, enhancing user feedback collection, and diversifying learner data analysis.

• Journal of Korean Society of Transportation
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• v.30 no.1
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• pp.149-159
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• 2012

The evaluation of public transit service quality is more complicated than evaluating other aspects of transportation service. Although various measures of effectiveness [MOEs] for transit service have been studied and applied, a more comprehensive and accurate MOE is still required. In the past, either data from user surveys or the experience of bus agency administrators and/or engineers used to measure the quality of service. However, recently, with reliable and accurate real time data from BMS(Bus Management System) and BIS(Bus Information System), more reliable and accurate MOEs are available. This study develops a service evaluation model from users' perspectives, which is based on user' cost models that consider passenger access time, riding time, waiting time, and discomfort due to in-vehicle overcrowding, violation of traffic laws, and accident rate. For validating proposed model, data from the BMS and transit-fare cards (T-Money Card) for Seoul's No. 472 main bus line were used. Models developed in this study provided reliable results.

• Journal of Korean Society of Transportation
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• v.29 no.3
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• pp.31-40
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• 2011

Generally, inappropriate driving conditions including geometric, traffic environmental, and driver psychological problems may be critical reasons of traffic accidents. Under this circumstance, various types of facilities have been installed to improve traffic safety by itself or as a set consisting of several other traffic safety facilities. In general, traffic accidents occur by several reasons combined rather than only a single reason, and thus the safety effect of the safety facilities cannot be simply analyzed with only a single improvement. For the study, traffic accident data on the roadway segments of interest are collected along with field survey data. For the analysis, various alternative analysis methods were evaluated in terms of assessing accident reduction from various types of traffic safety improvements. Among the alternative methods tested including simple before-and-after evaluation method, before-and-after evaluation yoked comparison, and Comparison Group (C-G) method, it was found that the C-G method is the most effective method for analyzing the traffic safety improvement effect. Adopting the C-G method, both single and multiple safety improvements were analyzed. The results from this study can potentially be applied to decide the best type of treatments to improve traffic safety as well as to measure the accident reduction effects from the treatments.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.16 no.5
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• pp.72-84
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• 2017

Together with the Big Data of the 4th Industrial Revolution, the traffic information system has been changed to an section detection system by the point detection system. With DTG(Digital Tachograph) data based on Global Navigation Satellite System, the properties of raw data and data according to processing step were examined. We identified the vehicle trajectory, the link travel time of individual vehicle, and the link average travel time which are generated according to the processing step. In this paper, we proposed a application method for traffic management as characteristics of processing data. We selected the historical data considering the data management status of the center and the availability at the present time. We proposed a method to generate the Travel Time Index with historical link average travel time which can be collected all the time with wide range. We propose a method to monitor the traffic congestion using the Travel Time Index, and analyze the case of intersections when the traffic operation method changed. At the same time, the current situation which makes it difficult to fully utilize DTG data are suggested as limitations.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.15 no.4
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• pp.1-11
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• 2016

The purpose of this study is to analyze the effect of public transit accessibility on the Carsharing use demand. By utilizing the rental historical DB of Greencar which is operated in Suwon city and public transit GIS DB, the use demand models for Carsharing by rental offices are built and analyzed in accordance with public transit accessibility. The result indicates 73% of walking as a majority, 3% cycling, and 20% using buses and urban railways to access Carsharing rental offices. The goodness of fit of Carsharing use models reflecting accessibility to buses and railways is verified as 0.818 which proves that public transit accessibility is a significant variable. Therefore, it is verified that installing Carsharing rental offices where public transit transfer is convenient can possibly increase the use demand. Especially, while accessibility to buses is verified as a significant variable out of other public transit means, the accessibility to urban railways is verified as not significant. This suggests that a variety of complementary policies such as transfer discount policy and one-way transfer return policy are necessary in between urban railways and Carsharing in order to promote mutual use demand in accordance with the other public transit means. This study result is yet the basic research on Carsharing, however it is expected to contribute to improvement of transfer demand in between different public transit means.

• Journal of Intelligence and Information Systems
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• v.28 no.4
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• pp.1-25
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• 2022

After the first Covid-19 confirmed case occurred in Korea in January 2020, interest in personal transportation such as public bicycles not public transportation such as buses and subways, increased. The demand for 'Ddareungi', a public bicycle operated by the Seoul Metropolitan Government, has also increased. In this study, a demand prediction model of a GRU(Gated Recurrent Unit) was presented based on the rental history of public bicycles by time zone(2019~2021) in Seoul. The usefulness of the GRU method presented in this study was verified based on the rental history of Around Exit 1 of Yeouido, Yeongdengpo-gu, Seoul. In particular, it was compared and analyzed with multiple linear regression models and recurrent neural network models under the same conditions. In addition, when developing the model, in addition to weather factors, the Seoul living population was used as a variable and verified. MAE and RMSE were used as performance indicators for the model, and through this, the usefulness of the GRU model proposed in this study was presented. As a result of this study, the proposed GRU model showed higher prediction accuracy than the traditional multi-linear regression model and the LSTM model and Conv-LSTM model, which have recently been in the spotlight. Also the GRU model was faster than the LSTM model and the Conv-LSTM model. Through this study, it will be possible to help solve the problem of relocation in the future by predicting the demand for public bicycles in Seoul more quickly and accurately.

• Journal of the Korea Society of Computer and Information
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• v.28 no.10
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• pp.123-132
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• 2023

Git's commit messages manage the history of source changes during project progress or operation. By utilizing this historical data, project risks and project status can be identified, thereby reducing costs and improving time efficiency. A lot of research related to this is in progress, and among these research areas, there is research that classifies commit messages as a type of software maintenance. Among published studies, the maximum classification accuracy is reported to be 95%. In this paper, we began research with the purpose of utilizing solutions using the commit classification model, and conducted research to remove the limitation that the model with the highest accuracy among existing studies can only be applied to programs written in the JAVA language. To this end, we designed and implemented an additional step to standardize source change data into natural language using GPT. This text explains the process of extracting commit messages and source change data from Git, standardizing the source change data with GPT, and the learning process using the DistilBERT model. As a result of verification, an accuracy of 91% was measured. The proposed model was implemented and verified to ensure accuracy and to be able to classify without being dependent on a specific program. In the future, we plan to study a classification model using Bard and a management tool model helpful to the project using the proposed classification model.

• Journal of the Korean GEO-environmental Society
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• v.24 no.12
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• pp.47-52
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• 2023

In order to efficiently maintain heat pipes operated by district heating operators, the facility history and damage history data built by the operator are used to identify key independent variables that are related to the occurrence of damage. Afterwards, the correlation with the frequency of damage was analyzed, and a basic model for estimating the frequency of damage was derived. Considering the correlation with the estimation model based on the use time currently being used by domestic and foreign district heating operators, a simple regression analysis basic model was presented as the independent variable with the highest correlation between continuous variables such as the use time, pipe diameter, burial depth, and insulation level of monitoring system, and the frequency of damage. The remaining independent variables were reflected as factors that modify and supplement the basic model. As a result of the analysis, as in previous research cases, it was confirmed that the analysis model between use time and frequency of damage had the highest correlation between the two variables and could be used as a basic model. Pipe diameter, burial depth, and insulation level of monitoring system information have also been confirmed to have a correlation with the frequency of damage, so they can be used as factors to supplement the basic model.

• Journal of the Korean Geotechnical Society
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• v.36 no.11
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• pp.83-95
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• 2020

In order to evaluate the stability of the geo-structure of railway bridge, the response dominant frequency was analyzed based on a series of impact vibration load test results. The specifications of the experiment piers were obtained by referring to the completion design data, and when data was missing, a field study was conducted. The impact vibrations test according to the scouring progress was carried out at one pier scheduled to be abandoned, and it was confirmed that the response dominant frequency can be utilized as an evaluation index for scour. In addition, the response dominant frequency was measured through an impact load test at 46 piers in 5 bridges in operation, and the scour safety of the bridge was evaluated by comparing it with the japanese proposal formula.

• Journal of the Korean Geotechnical Society
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• v.29 no.10
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• pp.57-66
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• 2013

Societal interest on a faster transportation demands an increase of the train speed exceeding current operation speed of 350 km/h. To trace the pattern of variations in displacements and subsoil stresses in the concrete slab track system, finite element simulations were conducted. For a simple track-vehicle modeling, a mass-point system representing the moving train load was developed. Dynamic responses with various train speeds from 100 to 700 km/h were investigated. As train speeds increase the displacement at rail and subsoil increases nonlinearly, whereas significant dynamic amplification at the critical velocity has not been found. At low train speed, the velocity of elastic wave carrying elastic energy is faster than the train speed. At high train speed exceeding 400 km/h, however, the train speed is approximately identical to the elastic wave velocity. Nonlinearity in the stress history in subsoil is amplified with increasing train speeds, which may cause significant plastic strains in path-dependent subsoil materials.