• Journal of agricultural medicine and community health
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• v.47 no.2
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• pp.99-108
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• 2022

Objectives: This study aimed to identify the vaccination coverage for hepatitis B among aged 19 or older, and at the same time to determine the reasons for vaccination or non-vaccination. Methods: The survey was conducted through a Mixed-Mode Random Digit Dialing Survey (RDD) method. The survey included hepatitis B vaccination status, reasons of vaccination and non-vaccination, sources of information on vaccination, and other related factors. Results: The vaccination coverage for hepatitis B among adults 19 years of age and older were 38.0%, 32.5%, and 26.9% for the first, second, and third doses. A related factors with high rate of hepatitis B vaccination was women, younger than 65 years of age, rural residents, having a job, highly educated, health insurance subscribers, living with spouse, family members living together. In addition, the vaccination rate was higher in those who was aware of the states recommended adult vaccination, were explained by a doctor about the need for adult vaccination, kept their vaccination records, and recognized that it helped prevent infectious diseases, and had seen promotional materials. Conclusions: In the future, it is necessary to check the antibody retention rate along with the hepatitis B vaccination coverage of adults on a regular basis. In addition, in order to accurately and quickly identify the hepatitis B vaccination coverage, it is necessary to prepare a plan to improve the computerized registration rate to manage adult vaccination records.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.21 no.3
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• pp.18-29
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• 2022

Recently, cooperative intelligent transport systems (C-ITS) testbeds have been deployed in great numbers, and advanced autonomous driving research using V2X communication technology has been conducted actively worldwide. In particular, the broadcasting services in their beginning days, giving warning messages, basic safety messages, traffic information, etc., gradually developed into advanced network services, such as platooning, remote driving, and sensor sharing, that need to perform real-time. In addition, technologies improving these advanced network services' throughput and latency are being developed on many fronts to support these services. Notably, this research analyzed the network latency requirements of the advanced network services to develop a remote driving service for the droid type low-speed robot based on the 3GPP C-V2X communication technology. Subsequently, this remote driving service's performance was evaluated using system modeling (that included the operator behavior) and simulation. This evaluation showed that a respective core and access network latency of less than 30 ms was required to meet more than 90 % of the remote driving service's performance requirements under the given test conditions.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.21 no.5
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• pp.28-41
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• 2022

A road system with CV(Connected Vehicle)s, which is often referred to as a cooperative intelligent transportation system (C-ITS), provides various road information to drivers using an in-vehicle warning system. Road environments with CVs induce drivers to reduce their speed or change lanes to avoid potential risks downstream. Such avoidance maneuvers can be considered to improve driving behaviors from a traffic safety point of view. Thus, empirically evaluating how a given in-vehicle warning information affects driving behaviors, and monitoring of the correlation between them are essential tasks for traffic operators. To quantitatively evaluate the effect of in-vehicle warning information, this study develops a method to calculate compliance rate of drivers where two groups of speed profile before and after road information is provided are compared. In addition, conventional indexes (e.g., jerk and acceleration noise) to measure comfort of passengers are examined. Empirical tests are conducted by using PVD (Probe Vehicle Data) and DTG (Digital Tacho Graph) data to verify the individual effects of warning information based on C-ITS constructed in Seoul metropolitan area in South Korea. The results in this study shows that drivers tend to decelerate their speed as a response to the in-vehicle warning information. Meanwhile, the in-vehicle warning information helps drivers to improve the safety and comport of passengers.

• Journal of Korean Library and Information Science Society
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• v.54 no.1
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• pp.45-68
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• 2023

This study aims to investigate the awareness and experiences of domestic researchers regarding data publishing, which has been recognized as a new channel of data sharing as scholarly communication evolves in the open science environment. A survey is conducted among researchers from five government-funded research institutes in the field of science and technology and members of the GeoAI Data Society to confirm the awareness of data publishing. As a result of the study, domestic researchers recognized providing explanations for data, stable access to data, citation, and quality assurance through peer review as the advantages of data journals. On the contrary, a low level of recognition for data paper as one of the research outputs was presented. With regard to the properties of data publication, the respondents answered that the data description, metadata description, and permanent identifiers are highly related, however, their recognition of the relation between the properties of data publication and the data submission to a repository and data peer review was relatively low. Finally, to expand the data publication, the need for the development of an editorial system that supports data paper peer review and cross-linking to a data repository as well as the development of a repository that supports data citation was identified. This study on the domestic researchers' experience and awareness of data publishing can provide insights for the implementation of data publishing services and infrastructure in the future.

• Journal of Intelligence and Information Systems
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• v.29 no.3
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• pp.79-101
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• 2023

The current status of local road pavement management in Jeollabuk-do only relies on the accomplishments of the site construction company's pavement repair and is only managed through Microsoft Excel and word documents. Furthermore, the budget is irregular each year. Accordingly, a systematic maintenance plan for local roads is necessary. In this paper, data related to road damage and road environment were collected and processed to derive possible areas which could suffer from road damage. The effectiveness of the methodology was reviewed through the on-site inspection of the area. According to the Ministry of Land, Infrastructure and Transport, in 2018, the number of damages on general national roads were about 47,000. In 2019, it reached around 38,000. Furthermore, the number of lawsuits regarding the road damages were about 93 in 2018 and it increased to 119 in 2019. In the case of national roads, the number of damages decreased compared to 2018 due to pavement repairs. To measure the priorities in maintenance of local roads at Jeollabuk-do, data on maintenance history, local port hole occurrence site, overlapping business section, and emergency maintenance section were transformed into data. Eventually, it led to improvements in maintenance of local roads. Furthermore, spatial data were constructed using various current status data related to roads, and finally the data was processed into a new form that could be utilized in machine learning and predictions. Using the spatial data, areas requiring maintenance on pavement were predicted and the results were used to establish new budgets and policies on road management.

• Journal of Intelligence and Information Systems
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• v.29 no.3
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• pp.229-247
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• 2023

With the increasing emphasis on anomaly detection across various fields, diverse anomaly detection algorithms have been developed for various data types and anomaly patterns. However, the performance of anomaly detection algorithms is generally evaluated on publicly available datasets, and the specific performance of each algorithm on anomalies of particular types remains unexplored. Consequently, selecting an appropriate anomaly detection algorithm for specific analytical contexts poses challenges. Therefore, in this paper, we aim to investigate the types of anomalies and various attributes of data. Subsequently, we intend to propose approaches that can assist in the selection of appropriate anomaly detection algorithms based on this understanding. Specifically, this study compares the performance of anomaly detection algorithms for four types of anomalies: local, global, contextual, and clustered anomalies. Through further analysis, the impact of label availability, data quantity, and dimensionality on algorithm performance is examined. Experimental results demonstrate that the most effective algorithm varies depending on the type of anomaly, and certain algorithms exhibit stable performance even in the absence of anomaly-specific information. Furthermore, in some types of anomalies, the performance of unsupervised anomaly detection algorithms was observed to be lower than that of supervised and semi-supervised learning algorithms. Lastly, we found that the performance of most algorithms is more strongly influenced by the type of anomalies when the data quantity is relatively scarce or abundant. Additionally, in cases of higher dimensionality, it was noted that excellent performance was exhibited in detecting local and global anomalies, while lower performance was observed for clustered anomaly types.

• Journal of Platform Technology
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• v.11 no.2
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• pp.54-65
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• 2023

Due to the nature of electric vehicles, the batteries used for electric vehicles have a very large rated capacity. If an electric vehicle runs for a long time or an electric vehicle is abandoned due to a traffic accident, the electric vehicle battery becomes a waste battery. Even in vehicles that are being abandoned, the remaining capacity of waste batteries for electric vehicles is sufficient for other purposes. Waste batteries for automobiles are very expensive, so they need to be recycled and reused, but there was a problem that the standards for measuring the performance grade of waste batteries for recycling and reuse were insufficient. As a method for measuring the remaining capacity of waste battery, the most stable and reliable method is to measure the remaining capacity of battery using full charge and discharge. However, the inspection method by the full charging and discharging method varies depending on the capacity of the battery, but it takes more than a day to inspect, and many people are making great efforts to solve this problem. In this paper, an electric vehicle battery residual capacity analysis technique using voltage deviation between cells was studied and analyzed as a method to reduce inspection time for electric vehicle batteries. To this end, a full charging and discharging-based capacity measurement system was constructed, experimental data were collected using a nose or waste battery, and the correlation between the voltage deviation and the remaining capacity of the battery pack was analyzed to verify whether it can be used for battery inspection.

• Journal of Korean Society of Coastal and Ocean Engineers
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• v.35 no.1
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• pp.13-21
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• 2023

As problems such as difficulties in securing stable energy resources and global warming due to the emission of greenhouse gases due to the use of fossil fuels have emerged, interest in the development of renewable energy is increasing. Since the tidal phenomenon has a regularity that occurs regularly with a certain period, it is possible to predict accurately in advance, which has a advantage in terms of energy recovery. Therefore, various methods have been devised to utilize the tide as an energy source. Tidal power using barrages is a representative method that is widely operated, but the promotion of tidal power generation projects is being delayed or stopped due to the decrease in the level of water in the tidal basin, changes in water quality and in the ecosystem. In this study, a field experiment was conducted to develop and verify the performance of a tidal power device applicable to sea areas where dykes are already installed. As a result of carrying out four cases of experiments using two water tanks, pipe lines, open channels, weirs, and water turbine and generator, the possibility of developing a power generation system capable of 10 kW output or more and 60% efficiency or more was confirmed. These research results can be used for small-scale tidal power by utilizing the existing dykes.

• Journal of the Korean Geotechnical Society
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• v.22 no.9
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• pp.61-68
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• 2006

Recently the large scale civil engineering projects are being implemented by reclaiming the sea or utilizing seashore and river embankment areas. The reclaimed land and utilized seashore are mostly soft ground that doesn't have sufficient bearing capacity. This soft ground consists of fine-grained soil such as clayey and silty soils or large void soil like peat or loose sand. It has high ground water table and it may cause the failure and crock of building foundation by uplift pressure and ground water leakage. In this study, the permittivity and the transmissivity were evaluated with the applied normal pressure in the laboratory. The laboratory model tests were conducted by utilizing geocomposite drainage system for draining the water out to release the uplift pressure. The soil used in the laboratory drainage test was dredged soil from the reclaimed land where uplift pressure problems can arise in soil condition. Geocomposite drainage system was installed at the bottom of apparatus and dredged soil was layered with compaction. Subsequently the water pressure was supplied from the top of specimen and the quantities of drainage and the pore water pressure were measured at each step water pressure. The results of laboratory measurements were compared with theoretical values. For the evaluation of propriety of laboratory drainage test, 2-D finite elements analysis that can analyze the distribution and the transferring of pore water pressure was conducted and compared with laboratory test results.

• Journal of the Korean Geotechnical Society
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• v.26 no.1
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• pp.45-54
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• 2010

It is important to calculate the natural frequency of a piled structure in the design stage in order to prevent resonance-induced damage to the pile foundation and analyze the dynamic behavior of the piled structure during an earthquake. In this paper, a simple but relatively accurate method employing a mass-spring model is presented for the evaluation of the natural frequency of a pile-soil system. Greatly influencing the calculation of the natural frequency of a piled structure, the spring stiffness between a pile and soil was evaluated by using the coefficient of subgrade reaction, the p-y curve, and the subsoil elastic modulus. The resulting natural frequencies were compared with those of 1-g shaking table tests. The comparison showed that the natural frequency of the pile-soil system could be most accurately calculated by constructing a stiffness matrix with the spring stiffness of the Reese (1974) method, which utilizes the coefficient of the subgrade reaction modulus, and Yang's (2009) dynamic p-y backbone curve method. The calculated natural frequencies were within 5% error compared with those of the shaking table tests for the pile system in dry dense sand deposits and 5% to 40% error for the pile system in saturated sand deposits depending on the occurrence of excess pore water pressure in the soil.