• Journal of The Korean Society of Agricultural Engineers
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• v.65 no.1
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• pp.15-26
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• 2023

This study aimed to evaluate the performance of water level classification from CCTV images in agricultural facilities such as reservoirs. Recently, the CCTV system, widely used for facility monitor or disaster detection, can automatically detect and identify people and objects from the images by developing new technologies such as a deep learning system. Accordingly, we applied the ResNet-50 deep learning system based on Convolutional Neural Network and analyzed the water level of the agricultural reservoir from CCTV images obtained from TOMS (Total Operation Management System) of the Korea Rural Community Corporation. As a result, the accuracy of water level detection was improved by excluding night and rainfall CCTV images and applying measures. For example, the error rate significantly decreased from 24.39 % to 1.43 % in the Bakseok reservoir. We believe that the utilization of CCTVs should be further improved when calculating the amount of water supply and establishing a supply plan according to the integrated water management policy.

• International conference on construction engineering and project management
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• 2022.06a
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• pp.1220-1220
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• 2022

Constructionarium Ltd is a not-for-profit organisation which delivers a residential, experiential, immersive learning opportunity to university students from across the built environment education sector. Since 2002, the Constructionarium education model has been available to students in engineering, construction management and architecture at a purpose built, 19-acre multi-disciplinary training facility in Bircham Newton, England simulating real site life and reflecting site processes, practices and health and safety requirements. The unique approach of Constructionarium puts experiential learning and sustainability at the heart of everything. In a week, students develop a practical understanding of the construction process, develop transferable skills, build a team and are exposed to the latest in sustainable technologies. Experiential learning is what differentiates a Constructionarium project from regular field trips or site visits. At Constructionarium the focus is on learning by participation rather than learning through theory or watching a demonstration. The projects cannot be replicated in a classroom or on campus. Using the hands-on construction of scaled down versions of iconic structures from around the world, students learn that it requires the involvement of the whole construction team to successfully complete their project. Skills such as communication, planning, budgeting, time management and decision making are woven into a week-long interrelationship with industry professionals, academic mentors and trades workers. Working together to enhance transferable skills brings the educational environment into the reality of completing an actual construction project handled by the students. Constructionarium has used this transformational learning model to educate thousands of students from all over the United Kingdom, Europe and Asia. Texas A&M University in the United States has sent multiple teams of students from its Department of Construction Science every operational year since 2016.

• Clinical and Experimental Vaccine Research
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• v.12 no.4
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• pp.313-318
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• 2023

Purpose: Globally, 25 million children were either unvaccinated or under-vaccinated in year 2021. Among them, India had the highest number of children unvaccinated. Studies have shown impact of coronavirus disease 2019 (COVID-19) pandemic on routine health-care services. Present study aimed to estimate the impact of COVID-19 on utilization of routine immunization services during years 2020 and 2021 in tertiary-care facility. Materials and Methods: Record based descriptive analytic study was conducted at pediatric tertiary-care hospital, Jaipur. Data of children vaccinated as per the National Immunization Schedule for the period January 2019 to December 2021 were retrieved from the immunization records. Doses administered were assessed as a proxy measure of vaccine coverage. The vaccination trends of 2020 and 2021 were compared assuming base year 2019. Unpaired t-test of significance and Pearson correlation was used for correlation analysis. Results: There was significant drop in the vaccine counts after emergence of COVID-19 pandemic. In year 2020 and 2021, mean monthly vaccine count was 2,190±715.1 and 2,305±393.2, respectively, in which maximum drop was in April 2020 (-79.12%) and May 2021 (-57.16%) when it was compared with matched month of base year. There was negative correlation between percent change in vaccine count and COVID-19 cases in 2020 (r=-0.057, p=0.861) and 2021 (r=-0.827, p=0.001) as compared to year 2019. Conclusion: Study concludes that there was a significant gap in utilization of routine immunization services during the COVID-19 pandemic. This necessitates planning and management of routine immunization services in-case of future pandemics to avoid resurgence of vaccine-preventable diseases in the Rajasthan.

• Fisheries and Aquatic Sciences
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• v.26 no.10
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• pp.628-636
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• 2023

Stomach contents of three commercially important species, anchovy (Engraulis japonica), small yellow croaker (Larimichthys polyactis) and yellow goosefish (Lophius litulon) were analyzed to investigate difference of prey between Spring and Fall. Trawl surveys for target fishes were conducted at 12 stations by the RV Tamgu-8 in the Yellow Sea-Korean side in Spring and Fall 2008 as a part of the United Nations Development Programme/Global Environment Facility (UNDP/GEF), Yellow Sea Large Marine Ecosystem (YSLME) survey. Stomach contents of 50 individuals of each species were analyzed to species level of prey, if the number of specimens was more than 50 for each species. Fullness and digestion condition of stomach contents were determined by five and six levels, respectively. In anchovy stomachs, 23 species in Spring and 15 species in Fall were identified, respectively. Stomach contents were mostly occupied by copepods and euphausiids, mostly Euphausia spp., calyptopis in Spring while by copepods and amphipods in Fall. In small yellow croaker stomachs, 23 species in Spring and 11 species in Fall were identified. Stomach contents were mostly occupied by copepods and euphausiids in Spring, but by only euphausiids in Fall. Total 368 yellow goosefish (151 in Spring and 217 in Fall) were captured, but stomach contents only in Fall were analyzed. Most of stomach contents were anchovy with small proportion of Hakodate sand shrimp, Tanaka's snailfish, Pacific cod, and miscellaneous things. The present research unveiled that main food items of plankton feeder were distinctly different by species and seasons in the Yellow Sea-Korean side, as coincided with previous reports.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.44 no.3
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• pp.375-383
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• 2024

The size of the construction industry is increasing, and its impact on the entire national industry is also significant. However, construction cost increases, construction period delays, safety accidents, and quality problems occur during the construction process. This paper analyzed the construction cost, construction period, and change order performance for civil infrastructures for which post evaluation was performed. The analysis was conducted by dividing civil engineering facilities by type, construction nature, construction cost, contract nature, and delivery method. Planned and actual construction cost and period were compared during the planning, design, and construction process of civil engineering facilities. There is a possibility of input errors in project performance data, this paper proposes to the post-evaluation center should perform post-evaluation. Also, post-evaluation implementation guidelines for change orders should be revised. Additionally, further analysis of each facility was proposed through continuous data collection.

• The Korean Journal of Air & Space Law and Policy
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• v.27 no.2
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• pp.67-106
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• 2012

Today air traffic at the airport is complicated including a significant increase in the volume of air transport, so aviation accidents are constantly occurring. Therefore, we should newly recognize importance of the Air Traffic Safety, the core values of the Air Traffic. The location of airport that is the basic infrastructure of the air traffic and the security of safety for facilities and equipments are more important than what you can. From this dimension, I analyze the step-by-step safety factors that are taken into account in the airport development projects from the construction or improvement of the airport within the current laws and institutions and give my opinion on the enhancement of safety in the design and construction of airport. The safety of air traffic, as well as airport, depends on location, development, design, construction, inspection and management of the airport including airport facilities because we have to carry out the national responsibility that prevents the risk of large social overhead capital for many and unspecified persons in modern society through legislation regarding intervention of specialists and locational criteria for aviation safety from the planning stage of airport development. In addition, well-defined installation standards of airports and air navigation facilities, the key points of the airport development phase, can ensure the safety of the airport and airport facilities. Of course, the installation standards of airport and air navigation facilities are based on the global standard due to the nature of air traffic. However, to prevent the chaos for the safety standards in design, construction, inspection of them and to ensure the aviation safety, the safety standards must be further subdivided in the course of domestic legislation. The criteria for installation of the Air Navigation facilities is regulated most specifically. However, to ensure the safety of the operation for Air Navigation Facilities, performance system proved suitable for the Safety of Air Navigation Facilities must change over from arbitrary restrictions to mandatory restrictions and be applied for foreign producers as well as domestic producers. Of course, negligence of pilots and defective aircraft maintenance lead to a large portion of the aviation accidents. However, I think that air traffic accidents can be reduced if the airport or airport facility is perfect enough to ensure the safety. Therefore, legal and institutional supplement to prioritize the aviation safety from the stage of airport development may be necessary.

• Journal of the Korean Institute of Landscape Architecture
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• v.37 no.6
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• pp.12-18
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• 2010

This study was carried out in order to propose a planning index for improved school forests in Gyeonggido. For the purpose of this study we selected 42 out of 75 school forests established during 2005 in Gyeonggido. All 42 school forests were surveyed and analyzed by frequency, cross tabulation, and group average analysis with SPSS 12.0 version. The present condition of the school forests was analyzed with in conjunction with items such as the surrounding environment, centralization, and locational characteristics as nominal points. Other items: trees, shrubs, pavement, fruit trees, transplantation, evergreen trees, and recreation facility content percentage were analyzed as a proportion point. After reviewing the literature and analyzing the present condition of school forests, we constructed a conceptual framework and formulated a hypothesis for this research. Data were obtained through a questionnaire, given to 98 students majoring in landscape architecture at Hankyong University in 2007. Results showed that the primary variables for tree health were soil compaction and the depth of soil filling. They were the most serious factors that deteriorate the health of trees. Based on the relationship between tree health and growing conditions, trees inside the school forest should be managed to provide more growing space and less abuse. The minimum area for trees inside the school forest for good growth conditions should be within the drip lines. We have found that the minimum percentage of tree content is 0.13, which means that more than 130 trees need to be planted over $1,000m^2$ green space. More than 3,580 shrubs need to be planted over $1,000m^2$ green space. The pavement area should be controlled to less than 19% of the total size of the school forest area. Finally, more than 39 trees out of 100 trees planted should be evergreen. The research results suggest that the construction planning index of Gyeonggido school forest be recommended in the planning and development process of the construction project carried out every year.

• Journal of the Korean Institute of Landscape Architecture
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• v.42 no.5
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• pp.31-40
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• 2014

The importance of green spaces in the city is growing each day. Local governments are taking charge of park development works that are having difficulty in developing and managing urban parks due to high land value as well as a shortage in finances. This is even though an urban park is defined as an urban planning facility and the law provides park area per person. Civil residents, meanwhile, are using not only urban parks provided by law but also other green areas such as rivers, reservoirs, and school playgrounds because they recognize urban green areas by the concept of use. In this study, accordingly, urban green areas were sorted into two types, urban parks, parks provided by law, and other green areas, and the difference in use pattern and use satisfaction by type was analyzed. As a result of analysis, there was no remarkable difference between the two types. According to such results, it was found that it is necessary to include other green areas, such as rivers, reservoirs, school green areas, and apartment green areas in addition to the current park green areas provided by law when park area per person is calculated, and such calculation of urban green areas reflecting local characteristics can reduce local governments' financial burden and improve the effectiveness of future urban park policies. It is judged that such results can become a plan against the cancellation of unexecuted urban facilities. The fact that accessibility factors, such as road satisfaction, access convenience, and convenient movement, are affecting satisfaction with the use of urban parks suggests that it is important to improve urban park accessibilities rather than to quantitatively expand park area in order to improve satisfaction with urban parks. Considering that people travel to urban green areas mostly by walking, it is necessary for access convenience to conduct follow-up studies such as barrier-free and securing walking stability through analysis of routes to urban green areas.

• Journal of the Korean Institute of Landscape Architecture
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• v.51 no.3
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• pp.70-82
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• 2023

The recent surge of IT and data acquisition is shifting the paradigm in all aspects of life, and these advances are also affecting academic fields. Research topics and methods are being improved through academic exchange and connections. In particular, data-based research methods are employed in various academic fields, including landscape architecture, where continuous research is needed. Therefore, this study aims to investigate the possibility of developing a landscape preference evaluation and prediction model using machine learning, a branch of Artificial Intelligence, reflecting the current situation. To achieve the goal of this study, machine learning techniques were applied to the landscaping field to build a landscape preference evaluation and prediction model to verify the simulation accuracy of the model. For this, wind power facility landscape images, recently attracting attention as a renewable energy source, were selected as the research objects. For analysis, images of the wind power facility landscapes were collected using web crawling techniques, and an analysis dataset was built. Orange version 3.33, a program from the University of Ljubljana was used for machine learning analysis to derive a prediction model with excellent performance. IA model that integrates the evaluation criteria of machine learning and a separate model structure for the evaluation criteria were used to generate a model using kNN, SVM, Random Forest, Logistic Regression, and Neural Network algorithms suitable for machine learning classification models. The performance evaluation of the generated models was conducted to derive the most suitable prediction model. The prediction model derived in this study separately evaluates three evaluation criteria, including classification by type of landscape, classification by distance between landscape and target, and classification by preference, and then synthesizes and predicts results. As a result of the study, a prediction model with a high accuracy of 0.986 for the evaluation criterion according to the type of landscape, 0.973 for the evaluation criterion according to the distance, and 0.952 for the evaluation criterion according to the preference was developed, and it can be seen that the verification process through the evaluation of data prediction results exceeds the required performance value of the model. As an experimental attempt to investigate the possibility of developing a prediction model using machine learning in landscape-related research, this study was able to confirm the possibility of creating a high-performance prediction model by building a data set through the collection and refinement of image data and subsequently utilizing it in landscape-related research fields. Based on the results, implications, and limitations of this study, it is believed that it is possible to develop various types of landscape prediction models, including wind power facility natural, and cultural landscapes. Machine learning techniques can be more useful and valuable in the field of landscape architecture by exploring and applying research methods appropriate to the topic, reducing the time of data classification through the study of a model that classifies images according to landscape types or analyzing the importance of landscape planning factors through the analysis of landscape prediction factors using machine learning.

• International Journal of Highway Engineering
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• v.8 no.4 s.30
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• pp.49-62
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• 2006

The republic of korea has put a great emphasis on the role of the road as widening a social infra-structural facility. Thus, vast amount of money has been invested on the road establishment. As a result, there has been fruitful outcomes in establishing the road system of the nation especially for the flat road with ease. However, in order to have more systematic and sustainable road system, we should turn our attention to more painful and high-cost regions such as mountainous districts and those are to be developed effectively. The configuration of the road is an important factor to be considered in making a decision for the road planning. Nevertheless, current road planning criterion has no such clarified and objective judging standard for figuring the configuration of the road out and, as a result, speed planning can be decided incorrectly. our research has acknowledged the necessity of estimating the configuration of the road and aimed to make it organized and sorted according to the height, slope, and the vehicle's speed. The results are as follows. First, our research made use of GIS data and classified the road into 9 different areas according to the height and the slope. Also, road classification being matched to the data of vehicle's speed, it has been shown that those characteristics of different areas have made an influence on vehicle's speed. Secondly, based on the results of the similarity between geographical classification and, vehicle's speed of sorted groups according to the height and the slope, conclusively we have classified as flat, rolling region and mountain. Since our research has made use of vehicle's speed for National Highway, it is not applicable to different functional highways. However, for the highway to be established hereafter, it can be a standard for reflection geographical characteristics.