• The Journal of Industrial Distribution & Business
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• v.9 no.8
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• pp.51-60
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• 2018

Purpose - Civil affairs are increasing in various forms, but civil servants who are able to handle them want to reduce the complaints and provide keywords that will help in the future due to their lack of time. While various ideas are presented and implemented as policies in solving civil affairs, there are many cases that are not policies that people can sympathize with. Therefore, it is necessary to analyze the complaints accurately and to present correct solutions to the analyzed civil complaint data. Research design, data, and methodology - We analyzed the complaints data for the last three years and found out how to solve the problems of Yongin City and alleviate the burdens of civil servants. To do this, the Hadoop platform and Design Thinking process were reviewed, and proposed a new process to fuse it. The big data analysis stage focuses on civil complaints - Civil data extraction - Civil data analysis - Categorization of the year by keywords analyzing them and the needs of citizens were identified. In the forecast analysis for deriving insights, - The case of innovation case study - Idea derivation - Idea evaluation - Prototyping - Case analysis stage used. Results - Through this, a creative idea of providing free transportation cards to solve the major issues of construction, apartment, installation, and vehicle problems was discovered. There is a specific problem of how to provide these services to certain areas, but there is a pressing need for a policy that can contribute as much as it can to the citizens who are suffering from various problems at this moment. Conclusions - In the past, there were many cases in which free traffic cards were issued mainly to the elderly or disabled. In other countries, foreign residents of other area visit the areas for accommodation, and may give out free transportation cards as well. In this case, the local government will be able to set up a framework to present with a win-win scenario in various ways. It is necessary to reorganize the process in future studies so that the actual solution will be adopted, reduce civil complaints, help establish policies in the future, and be applied in other cities as well.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• 2023.05a
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• pp.204-205
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• 2023

This study studied a prediction model for sending collision alarms for small fishing boats based on semi-supervised learning(SSL). The supervised learning (SL) method requires a large number of labeled data, but the labeling process takes a lot of resources and time. This study used service data collected through a data pipeline linked to 'intelligent maritime traffic information service' and data collected from real-sea experiment. The model accuracy was improved as a result of learning not only real-sea experiment data with labeling determined based on actual user satisfaction but also service data without label determined together.

• Journal of Korea Port Economic Association
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• v.39 no.4
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• pp.1-21
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• 2023

This study analyzed workers' residence and home-based work(HBW) trip by utilizing data from mobile carrier base stations of Gwangyang Port and terminal workers. In the past, research on port-related traffic or trip patterns mainly focused on cargo-based movement patterns for estimating cargo volume and port facilities, but this study analyzed trip patterns for workers in Gwangyang Port ports and related industries. As a result of the analysis, the average number of regular workers in the port hinterland Gwangyang Port was 1,295 per month, and the residence of workers was analyzed in Gwangyang City (66.1%)>Suncheon City (26.6%)>Yeosu City (3.1%). The average number of temporary workers in the hinterland was 2,645 per month, and Gwangyang City (45.8%)>Suncheon City (20.1%)>Yeosu City (5.7%). Next, the average number of regular workers at Gwangyang Port terminals was 753 per month, and Gwangyang City (66.1%)>Suncheon City (28.9%)>Yeosu City (3.3%) was analyzed. The average number of temporary workers at Gwangyang Port terminals was 1,893 per month, and Gwangyang City (50.8%)>Suncheon City (19.7%)>Yeosu City (9.8%). This study is expected to calculate the number of workers based on individual traffic using actual mobile carrier data to estimate the actual number of workers if the workplace address and actual work place are different, such as in port-related industries. This study is the first to be conducted on workers at Gwangyang Port. It is expected to be used as basic data for settlement conditions and urban planning, as well as transportation policies for port workers, by identifying the population coming from areas other than Gwangyang, where Gwangyang Port is located.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.38 no.1
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• pp.167-174
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• 2018

This study attempts to construct a model of optimal headway, focusing on a practical applicability to bus transit operation. Examining the existing bus operation and scheduling plans imposed by Busan City, we found that the plans failed to reasonably take into account such realities as varying traffic and operational conditions. The model is thus developed to derive the hourly optimal headway by routes satisfying the real-world conditions: varying hourly demand and cycle time, applying the model to routes 10 and 27 as examples. To do so, we collect big-dataset generated by smart card system and BIMS (Bus Inforamtion Management System). It is expected that the results of this study wil be a basis for further refined research in this field as well as for preparing practical timetables for bus operation.

• Journal of Information Technology Services
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• v.19 no.2
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• pp.125-138
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• 2020

Currently, subway crowding is estimated by observing a specific point at specific hours once or twice every 1 or 2 years. Given the extensive subway network in Seoul Metropolitan Area covering 588 stations, 11 lines and 80 transfer stations as of 2017, implementing crowding mitigation policy may have its limitations due to data uncertainty. A proposal has recently been made to effectively use smart card data, which generates big data on the overall subway traffic related to an estimated 8 million passengers per day. To mitigate subway crowding, this study proposes two viable options based on data related to smart card used in Seoul Metropolitan Area. One is to create a subway passenger pattern model to accurately estimate subway crowding, while the other is to prove effectiveness of early bird policy to distribute subway demand that is concentrated at certain stations and certain time. A subway passenger pattern model was created to estimate the passenger routes based on subway terminal ID at the entrance and exit and data by hours. To that end, we propose assigning passengers at the routes similar to the shortest routes based on an assumption that passengers choose the fastest routes. In the model, passenger flow is simulated every minute, and subway crowding level by station and line at every hour is analyzed while station usage pattern is identified by depending on passenger paths. For early bird policy, highly crowded stations will be categorized based on congestion level extracted from subway passenger pattern model and viability of a policy which transfers certain traveling demands to early commuting hours in those stations will be reviewed. In particular, review will be conducted on the impact of policy implemented at certain stations on other stations and lines from subway network as a whole. Lastly, we proposed that smart card based subway passenger pattern model established through this study used in decision making process to ensure effective implementation of public transport policy.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.22 no.3
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• pp.116-130
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• 2023

Expressways play pivotal roles in cargo transportation because of their superior accessibility and mobility compared to rail and air. On the other hand, there is a limit to the accurate calculation of cargo transportation performance using existing highways owing to the mixture of vehicle types and difficulty in identifying cargo loads of individual cargo vehicles. This paper presents an algorithm for calculating more reliable cargo transportation performance using big data. The traffic performance (veh·km/day) was derived using the data collected from Toll Collecting System. The average tolerance weight for each vehicle type and the cargo load unit (ton/unit) considering it was calculated using vehicle specification information data and high-speed and low-speed axis data. This study calculated the cargo transportation performance by section and type using various online integrated highway data and presented a method for calculating the transportation performance by linking open business offices and private highways.

• Journal of the Korea Society for Simulation
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• v.28 no.4
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• pp.57-65
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• 2019

Recently, the Korean military has been drastically reducing its active-duty troops due to rapid demographic changes and the reconciliatory mode between the two Koreas. Under these circumstances, the wartime reserve forces play an important role. In times of war, a successful personal mobilization is critical especially in early combat stage. Previous research has been carried out using insufficient data collected only within the military and there have been limitations on empirical analysis due to changes in the designation methods for personal mobilization. This study analyzes how much of the reserve forces can be filled at the prescribed time by analyzing the transportation route of the reserve forces in wartime by utilizing military-related data and credit card usage data of the reserve forces residing in Yong-in city. The analysis showed that all reserve forces could not be called up within the prescribed time. In particular, Gangwon Province has shown results of less than 70 percent call-ups, and could cause serious weakening of combat capabilities in the early stages of the war. The main reasons could be the difference between the actual residence and the residence address and the excessive time caused by the traffic congestion.

• Journal of the Korean Society of Marine Environment & Safety
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• v.29 no.7
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• pp.843-856
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• 2023

The global surge in maritime traffic has resulted in an increased number of ship collisions, leading to significant economic, environmental, physical, and human damage. The causes of these maritime accidents are multifaceted, often arising from a combination of crew judgment errors, negligence, complexity of navigation routes, weather conditions, and technical deficiencies in the vessels. Given the intricate nuances and contextual information inherent in each incident, a methodology capable of deeply understanding the semantics and context of sentences is imperative. Accordingly, this study utilized the SentenceBERT model to analyze maritime safety tribunal decisions over the last 20 years in the Busan Sea area, which encapsulated data on ship collision incidents. The analysis revealed important keywords potentially responsible for these incidents. Cluster analysis based on the frequency of specific keyword appearances was conducted and visualized. This information can serve as foundational data for the preemptive identification of accident causes and the development of strategies for collision prevention and response.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2017.10a
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• pp.395-398
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• 2017

The Smart Ship is considered one of the most discussed and novel topics in developing technological period. In this reason, the amount of running researches on it is evolving so fast. As a proof, the faced drawbacks such as the departure of ships, their safety, exchanging data, traffic and data monitoring system are being solved by presenting advanced technologies and innovations like Cloud, BigData, IoT and etc. Expanding the utilization of these technologies in the Marine world emphasizes not only the departure of the ships in the water but also they focus on solving the problems of the ships connected with the communication to the ports. In this paper, we present an IoT based smart reporting and mooring system for vessels and ports. In the proposed system, the ships automatically send all the data about themselves to the port and after getting the data, ports automatically send the information about possible spaces to moor for the ships using the sensors at the port. The intended system gives an amenity to minimize the time, effort and the cost while mooring the vessels.

• Journal of the Korean Society for information Management
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• v.36 no.3
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• pp.149-174
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• 2019

This study analyzes the actual use data of the websites of university libraries, analyzes the users' usage behavior, and proposes improvement measures for the websites. The study analyzed users' traffic and analyzed their usage behavior from January 2018 to December 2018 on the C University website. The website's analysis tool used 'Google Analytics'. The web traffic variables were analyzed in five categories: user general characteristics, user environment analysis, visit analysis, inflow analysis, site analysis, and site analysis based on the metrics of sessions, users, page views, pages per session, average session time, and bounce rate. As a result, 1) In the analysis results of general characteristics of users, there was some access to the website not only in Korea but also in China. 2) In the user experience analysis, the main browser type appeared as Internet Explorer. The next place was Chrome, with a bounce rate of Safari, third and fourth, double that of the Explore or Chrome. In terms of screen resolution, 1920x1080 resolution accounted for the largest percentage, with access in a variety of other environments. 3) Direct inflow was the highest in the inflow media analysis. 4) The site analysis showed the most page views out of 4,534,084 pages, followed by the main page, followed by the lending/extension/history/booking page, the academic DB page, and the collection page.