• The Korean Journal of Applied Statistics
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• v.32 no.2
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• pp.229-263
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• 2019

The Korean fertility rate has been declining rapidly since 2000 with the fertility rate among provinces following a uniform tendency. In particular, the province-specific fertility rate is an essential tool for local governments to prepare local policies for low fertility aging policy, education and welfare policies. However, there is limitation on how to reflect different trends on the province-specific fertility rate because the KOSTAT's (2017) province-specific fertility rate projection estimates information use the national average birth rate date of vital statistics for the last 10 years (5 years). In this study, we propose an improvement plan that simultaneously considers important stable pattern maintenance and provincial fertility rate differentiation for an annual birth rate estimation. The method proposed in this study (proposal 1 and 2) can reflect birth rate changes from past to present and national and provincial differences by age that use time series data of the annual fertility rate. Proposal 3 also reflects the unique fertility rate trend from the past to the present by age according to province regardless of the relationship with the national trend. Therefore, it is preferable to use a relationship to the national rate when predicting the birth rate, as in proposals 1 and 2 because the national and the provincial fertility rate pattern are similar. These proposals show improved stability in terms of age-specific fertility rates.

• Industry Promotion Research
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• v.4 no.1
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• pp.79-86
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• 2019

The quality of service delivery by governments to their citizens is a subject of concern in the contemporary society. E-governance is a critical aspect that is transforming government operation and service delivery to citizens and other bodies through application of information technology. This research explores the state of e-governing focusing on nations that are developing with special attention to Pakistan. The difficulties and benefits encountered are identified. The results are vital for implementers of e-governing systems in these countries. The methodology applied entails a secondary research that involves analysis and synthesis of literature relating the research topic. The results reveal that Pakistan has made incredible steps in setting up e-governance systems with growth in internet use and access of data from a digital platform. The findings reveal that e-government is associated with multiple benefits including enhanced quality of services, cost efficiency in service provision, enhance transparency and elimination of corruption, provide the basis for eradication of poverty, boost economic stability of a country, and provide room for direct democracy. The research also found that developing countries experience challenges in form of financial constraints, poor ICT infrastructure, illiteracy on e-government, political consensus constraints, legal obstacles, social and cultural constraints. E-government has the capability to transform the quality of governance provided by governments, and policymakers and implementers should address the constraints that act as a hindrance to its implementation.

• Journal of the Korean Society for Environmental Technology
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• v.19 no.6
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• pp.550-555
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• 2018

International Maritime Organization (IMO) is one of the most effective organizations in evolving international law for the protection and conservation of the marine environment. The IMO, MARPOL(Marine Pollution) 73/78 contains six Annexes that provide an overarching framework for the objectives of the international marine pollution. Annex IV was regulated by 64 th resolution in 2012 to control sea pollution from sewage. In 2014 large-scale wastewater treatment and nutrient removal device was developed with a grant from the Ministry of Oceans and Fisheries. A combined new process of Sequence Batch Reactor (SBR) and Membrane Bioreactor(MBR) was developed to overcome the pollution caused by shipboard sewage. In the present study, shipboard sewage wastewater was treated by mixing and aeration cycle in the newly developed SBR process. Furthermore, during analysis by NGS technique(Macrogen Co., Ltd.), dominant species of bacteria were found in the aeration tank of the Bench-scale wastewater treatment facility. Bacteroidetes and Gammaproteobacteria accounted for 27.1 % of the aerobicbacteria and 16.8 % of the anaerobicbacteria, respectively. Microorganisms play a vital role in shipboard wastewater treatment. A further detailed study is required to understand the precise role of the microorganisms in the wastewater treatment.

• Journal of Apiculture
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• v.34 no.1
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• pp.47-55
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• 2019

Honey bees are a vital part of the food chain as the most important pollinators for a broad palette of crops and wild plants. The climate change and colony collapse disorder (CCD) phenomenon make it challenging to develop ICT solutions to predict changes in beehive and alert about potential threats. In this paper, we report the test results of the bee-counting system which stands out against the previous analogues due to its comprehensive components including an improved dual infrared sensor to detect honey bees entering and leaving the hive, environmental sensors that measure ambient and interior, a wireless network with the bluetooth low energy (BLE) to transmit the sensing data in real time to the gateway, and a cloud which accumulate and analyze data. To assess the system accuracy, 3 persons manually counted the outgoing and incoming honey bees using the video record of 360-minute length. The difference between automatic and manual measurements for outgoing and incoming scores were 3.98% and 4.43% respectively. These differences are relatively lower than previous analogues, which inspires a vision that the tested system is a good candidate to use in precise apicultural industry, scientific research and education.

• Korean journal of applied entomology
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• v.61 no.1
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• pp.229-238
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• 2022

Animal pollination is an important ecosystem service provided mostly by diverse insect groups such as bees and hover flies. Maintaining agricultural productivity and securing the nutritional balance are closely tied to human wellbeing. This study aimed to estimate the pollination dependent food production in Korean agricultural system. Crop production data were obtained from Korean statistical information service (KOSIS) data of 2015. By implementing pollination dependency, crop production and market price, contribution of insect pollination to crop production increase were estimated from total 71 crops including 12 cereals, 19 fruits, 18 field vegetables, 13 greenhouse vegetables and 9 specialty crops. Mean pollination dependency of all crops were 29.2% and it was higher on fruits, specialty crops and greenhouse vegetables as well, but low (7.5%) in cereal crops. Pollination dependent (PD) production was estimated as 17.8% of total agricultural crop production with the economic value of 6,850 (6,508-7,193) billion won. Especially, PD production of greenhouse vegetables accounted 49.2% followed by fruits of 42.9%. Even specialty crop also showed higher PD production (35.9%). It was obvious that pollination is the vital service for agricultural production as well as nutritional security in Korea. Further protection and enhancing the pollination service were discussed with integrated pollinator-pest management (IPPM) strategies.

• International conference on construction engineering and project management
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• 2009.05a
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• pp.30-31
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• 2009

Early detection of schedule delay in field construction activities is vital to project management. It provides the opportunity to initiate remedial actions and increases the chance of controlling such overruns or minimizing their impacts. This entails project managers to design, implement, and maintain a systematic approach for progress monitoring to promptly identify, process and communicate discrepancies between actual and as-planned performances as early as possible. Despite importance, systematic implementation of progress monitoring is challenging: (1) Current progress monitoring is time-consuming as it needs extensive as-planned and as-built data collection; (2) The excessive amount of work required to be performed may cause human-errors and reduce the quality of manually collected data and since only an approximate visual inspection is usually performed, makes the collected data subjective; (3) Existing methods of progress monitoring are also non-systematic and may also create a time-lag between the time progress is reported and the time progress is actually accomplished; (4) Progress reports are visually complex, and do not reflect spatial aspects of construction; and (5) Current reporting methods increase the time required to describe and explain progress in coordination meetings and in turn could delay the decision making process. In summary, with current methods, it may be not be easy to understand the progress situation clearly and quickly. To overcome such inefficiencies, this research focuses on exploring application of unsorted daily progress photograph logs - available on any construction site - as well as IFC-based 4D models for progress monitoring. Our approach is based on computing, from the images themselves, the photographer's locations and orientations, along with a sparse 3D geometric representation of the as-built scene using daily progress photographs and superimposition of the reconstructed scene over the as-planned 4D model. Within such an environment, progress photographs are registered in the virtual as-planned environment, allowing a large unstructured collection of daily construction images to be interactively explored. In addition, sparse reconstructed scenes superimposed over 4D models allow site images to be geo-registered with the as-planned components and consequently, a location-based image processing technique to be implemented and progress data to be extracted automatically. The result of progress comparison study between as-planned and as-built performances can subsequently be visualized in the D4AR - 4D Augmented Reality - environment using a traffic light metaphor. In such an environment, project participants would be able to: 1) use the 4D as-planned model as a baseline for progress monitoring, compare it to daily construction photographs and study workspace logistics; 2) interactively and remotely explore registered construction photographs in a 3D environment; 3) analyze registered images and quantify as-built progress; 4) measure discrepancies between as-planned and as-built performances; and 5) visually represent progress discrepancies through superimposition of 4D as-planned models over progress photographs, make control decisions and effectively communicate those with project participants. We present our preliminary results on two ongoing construction projects and discuss implementation, perceived benefits and future potential enhancement of this new technology in construction, in all fronts of automatic data collection, processing and communication.

• KIPS Transactions on Software and Data Engineering
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• v.12 no.4
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• pp.159-172
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• 2023

In general, social problem-solving research aims to create important social value by offering meaningful answers to various social pending issues using scientific technologies. Not surprisingly, however, although numerous and extensive research attempts have been made to alleviate the social problems and issues in nation-wide, we still have many important social challenges and works to be done. In order to facilitate the entire process of the social problem-solving research and maximize its efficacy, it is vital to clearly identify and grasp the important and pressing problems to be focused upon. It is understandable for the problem discovery step to be drastically improved if current social issues can be automatically identified from existing R&D resources such as technical reports and articles. This paper introduces a comprehensive dataset which is essential to build a machine learning model for automatically detecting the social problems and solutions in various national research reports. Initially, we collected a total of 700 research reports regarding social problems and issues. Through intensive annotation process, we built totally 24,022 sentences each of which possesses its own category or label closely related to social problem-solving such as problems, purposes, solutions, effects and so on. Furthermore, we implemented four sentence classification models based on various neural language models and conducted a series of performance experiments using our dataset. As a result of the experiment, the model fine-tuned to the KLUE-BERT pre-trained language model showed the best performance with an accuracy of 75.853% and an F1 score of 63.503%.

• Informatization Policy
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• v.30 no.4
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• pp.40-61
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• 2023

The adoption of smart factories and smart manufacturing as strategies to enhance competitiveness and stimulate growth in the manufacturing sector is vital for a country's future competitiveness and industrial transformation. The government has consistently pursued smart manufacturing innovation policies starting with the Manufacturing Innovation 3.0 strategy in the Ministry of Industry. This study aims to identify policy areas for smart factories and smart manufacturing based on technical standards. Analyzing policy areas at the current stage where the establishment and support of domestic standards aligning with international technical standards are required is crucial. By prioritizing smart manufacturing process areas within the industry, policymakers can make well-informed decisions to advance smart manufacturing without blindly following international standardization in already well-established areas. To achieve this, the study utilizes a hierarchical analysis method including expert interviews and importance-performance analysis for the five major process areas. The findings underscore the importance of proactive participation in standardization for emerging technologies, such as data and security, instead of solely focusing on areas with extensive international standardization. Additionally, policymakers need to consider carbon emissions, energy costs, and global environmental challenges to address international trends in export and digital trade effectively.

• Journal of Life Science
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• v.33 no.10
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• pp.767-775
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• 2023

Sulfasalazine is a disease-modifying antirheumatic abiotic agent. It is a derivative of aminosalicylic acid and has been used for the treatment of various inflammatory diseases, such as rheumatoid arthritis, ulcerative colitis, and Crohn's disease, since it was first synthesized in 1941 and approved as a medicine in the United States in 1950. However, its mechanism of action has not yet been clearly identified. In this study, the effects of sulfasalazine on cell survival, apoptosis, and cell cycle progression in macrophages, which are major immune cells that regulate inflammatory responses, were investigated using mouse macrophage RAW 264.7 cells. Sulfasalazine inhibited the viability of RAW 264.7 cells in a dose-dependent manner, starting at a concentration of 0.25 mM. Annexin-V staining was used to confirm that the decrease in cell viability was due to apoptosis, and the number of Annexin-V-positive cells increased significantly at a concentration of 0.25 mM or higher. The effect of sulfasalazine on the expression of key proteins that regulate the G0/G1 phase of the cell cycle was also investigated. Sulfasalazine treatment significantly increased the expression of the cyclin-dependent kinase inhibitors p21 and p27 in RAW 264.7 cells. Although sulfasalazine is frequently used as a control drug in studies on inflammatory diseases, such as inflammatory colitis and rheumatoid arthritis, studies on its effect on macrophages are very limited. Therefore, the results of this study are expected to provide vital information on the use of sulfasalazine as a disease treatment.

• Journal of Korean Society of Archives and Records Management
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• v.24 no.2
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• pp.89-112
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• 2024

Metadata is a crucial component of record management, playing a vital role in properly managing and understanding the record. In cases where automatic metadata assignment is not feasible, manual input by records professionals becomes necessary. This study aims to alleviate the challenges associated with manual entry by proposing a method that harnesses ChatGPT technology for extracting records management metadata elements. To employ ChatGPT technology, a Python program utilizing the LangChain library was developed. This program was designed to analyze PDF documents and extract metadata from records through questions, both with a locally installed instance of ChatGPT and the ChatGPT online service. Multiple PDF documents were subjected to this process to test the effectiveness of metadata extraction. The results revealed that while using LangChain with ChatGPT-3.5 turbo provided a secure environment, it exhibited some limitations in accurately retrieving metadata elements. Conversely, the ChatGPT-4 online service yielded relatively accurate results despite being unable to handle sensitive documents for security reasons. This exploration underscores the potential of utilizing ChatGPT technology to extract metadata in records management. With advancements in ChatGPT-related technologies, safer and more accurate results are expected to be achieved. Leveraging these advantages can significantly enhance the efficiency and productivity of tasks associated with managing records and metadata in archives.