• The Journal of Bigdata
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• v.3 no.1
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• pp.55-62
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• 2018

In this study, we have developed a model for predicting the number of patients (flu, pneumonia, and outbreak) using Big Data, which has been mainly performed overseas. Existing patient number system by government adopt procedures that collects the actual number and percentage of patients from several big hospital. However, prediction model in this study was developed combing a real-time collection of disease-related words and various other climate data provided in real time. Also, prediction number of patients were counted by machine learning algorithm method. The advantage of this model is that if the epidemic spreads rapidly, the propagation rate can be grasped in real time. Also, we used a variety types of data to complement the failures in Google Flu Trends.

• The Journal of the Korea Contents Association
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• v.22 no.9
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• pp.29-45
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• 2022

This study aims to analyze how the public perceive the climate change in South Korea. The climate change has been highlighted due to its social and environmental impact on future society during decades. In recent, the outbreak of COVID-19 alerted the causal relationship between diseases and the climate change and forced decision-makers to cope with possible future epidemics. Along with the social and political importance of the climate change, the perception and actions of the public also become significant. Thus, this study analyzes the trends in the public perception of climate change before and after the COVID-19, using social media big data from March 1, 2019 through February 28, 2022. The results show that the negative perception dominated the public's perception, but a little positive perception implies that numerous policies on the climate change may help the public convert their negative perception to the positive. This study may help the decision-makers develop future policies and strategies on the climate change and carbon neutrality by considering the demand-side perception, such as South Korean perception.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2022.05a
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• pp.629-632
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• 2022

Education for sustainable development is an education that helps learners of all ages acquire the knowledge, skills, and attitudes necessary to solve interconnected international challenges such as climate change and environmental problems.It is an integral component of the Sustainable Development Goals (SDGs) #4 and contributes to the 17 SDGs. In order to find out the trend of ESD, 2718 news data from January 1, 2000 to December 31, 2021 were collected through 26 media outlets.As key keywords, international organizations leading sustainable development education such as the UN and UNESCO, local governments including Dobong-gu, and major issues such as climate change and ecological change could be identified. This can be used as basic data for various studies as it can explore trends for ESD.

• Journal of Animal Science and Technology
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• v.61 no.6
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• pp.324-332
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• 2019

This study aimed to identify the causality between climatic and soil variables affecting the yield of Italian ryegrass (Lolium multiflorum Lam., IRG) in the paddy field by constructing the pathways via structure equation model. The IRG data (n = 133) was collected from the National Agricultural Cooperative Federation (1992-2013). The climatic variables were accumulated temperature, growing days and precipitation amount from the weather information system of Korea Meteorological Administration, and soil variables were effective soil depth, slope, gravel content and drainage class as soil physical properties from the soil information system of Rural Development Administration. In general, IRG cultivation by the rice-rotation system in paddy field is important and unique in East Asia because it contributes to the increase of income by cultivating IRG during agricultural off-season. As a result, the seasonal effects of accumulated temperature and growing days of autumn and next spring were evident, furthermore, autumnal temperature and spring precipitation indirectly influenced yield through spring temperature. The effect of autumnal temperature, spring temperature, spring precipitation and soil physics factors were 0.62, 0.36, 0.23, and 0.16 in order (p < 0.05). Even though the relationship between soil physical and precipitation was not significant, it does not mean there was no association. Because the soil physical variables were categorical, their effects were weakly reflected even with scale adjustment by jitter transformation. We expected that this study could contribute to increasing IRG yield by presenting the causality of climatic and soil factors and could be extended to various factors.

• Electronics and Telecommunications Trends
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• v.36 no.1
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• pp.54-63
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• 2021

Since the recent COVID-19 pandemic, countries have been strengthening trade protection for their security, and the importance of securing strategic materials, such as food, is drawing attention. In addition to the cultural aspects, the global preference for food produced in Korea is increasing because of the Korean Wave. Thus, the Korean food industry can be developed into a high-value-added export food industry. Currently, Korea has a low self-sufficiency rate for foodstuffs apart from rice. Korea also suffers from problems arising from population decline, aging, rapid climate change, and various animal and plant diseases. It is necessary to develop technologies that can overcome the production structures highly dependent on the outside world of food and foster them into export-type system industries. The global agricultural industry-related technologies are actively being modified via data accumulation, e.g., environmental data, production information, and distribution and consumption information in climate and production facilities, and by actively expanding the introduction of the latest information and communication technologies such as big data and artificial intelligence. However, long-term research and investment should precede the field of living organisms. Compared to other industries, it is necessary to overcome poor production and labor environment investment efficiency in the food industry with respect to the production cost, equipment postmanagement, development tailored to the eye level of field workers, and service models suitable for production facilities of various sizes. This paper discusses the flow of domestic and international technologies that form the core issues of the site centered on the 4th Industrial Revolution in the field of agriculture, livestock, and fisheries. It also explains the environmental awareness production technologies centered on sustainable intelligence platforms that link climate change responses, optimization of energy costs, and mass production for unmanned production, distribution, and consumption using the unstructured data obtained based on detection and growth measurement data.

• Journal of Industrial Convergence
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• v.21 no.8
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• pp.43-49
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• 2023

Since 2018, due to climate change, heat waves and cold waves have caused gradual damage to social infrastructure. Since the damage caused by cold weather has increased every year due to climate change in recent 4 years, the damage that was limited to a specific area is now appearing all over the country, and a lot of efforts are being concentrated from experts in various fields to minimize this. However, it is not easy to study real-time observation of sudden abnormal low temperature in existing studies to reflect local characteristics in discontinuously measured data. In this study, based on the weather-related data that affects the occurrence of cold-weather damage, we developed an algorithm pattern that can identify the time when abnormal cold temperatures occurred after searching for weather patterns at the time of cold-weather damage. The results of this study are expected to be of great help to the related field in that it is possible to confirm the time when the abnormal low temperature occurs due to the data generated in real time without relying on the past data.

• Microbiology and Biotechnology Letters
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• v.49 no.3
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• pp.425-431
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• 2021

The use of big data may facilitate the recognition and interpretation of causal relationships between disease occurrence and climatic variables. Considering the immense contribution of rhinoviruses in causing respiratory infections, in this study, we examined the effects of various climatic variables on the seasonal epidemiology of rhinovirus infections in the temperate climate of Cheonan, Korea. Trends in rhinovirus detection were analyzed based on 9,010 tests performed between January 1, 2012, and December 31, 2018, at Dankook University Hospital, Cheonan, Korea. Seasonal patterns of rhinovirus detection frequency were compared with the local climatic variables for the same period. Rhinovirus infection was the highest in children under 10 years of age, and climatic variables influenced the infection rate. Temperature, wind chill temperature, humidity, and particulate matter significantly affected rhinovirus detection. Temperature and wind chill temperature were higher on days on which rhinovirus infection was detected than on which it was not. Conversely, particulate matter was lower on days on which rhinovirus was detected. Atmospheric pressure and particulate matter showed a negative relationship with rhinovirus detection, whereas temperature, wind chill temperature, and humidity showed a positive relationship. Rhinovirus infection was significantly related to climatic factors such as temperature, wind chill temperature, atmospheric pressure, humidity, and particulate matter. To the best of our knowledge, this is the first study to find a relationship between daily temperatures/wind chill temperatures and rhinovirus infection over an extended period.

• Journal of the Society of Disaster Information
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• v.18 no.1
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• pp.146-153
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• 2022

Purpose: In the case of domestic port facilities, port structures that have been in use for a long time have many problems in terms of safety performance and functionality due to the enlargement of ships, increased frequency of use, and the effects of natural disasters due to climate change. A big data analysis method was studied to develop an approximate model that can predict the aging pattern of a port facility based on the maintenance history data of the port facility. Method: In this study, member-level maintenance history data for caisson-type quay walls were collected, defined as big data, and based on the data, a predictive approximation model was derived to estimate the aging pattern and deterioration of the facility at the project level. A state-based aging pattern prediction model generated through Gaussian process (GP) and linear interpolation (SLPT) techniques was proposed, and models suitable for big data utilization were compared and proposed through validation. Result: As a result of examining the suitability of the proposed method, the SLPT method has RMSE of 0.9215 and 0.0648, and the predictive model applied with the SLPT method is considered suitable. Conclusion: Through this study, it is expected that the study of predicting performance degradation of big data-based facilities will become an important system in decision-making regarding maintenance.

• Journal of The Korean Astronomical Society
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• v.36 no.spc1
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• pp.125-133
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• 2003

New Jersey Institute of Technology (NJIT), in collaboration with the University of Hawaii (UH), is upgrading Big Bear Solar Observatory (BBSO) by replacing its principal, 65 cm aperture telescope with a modern, off-axis 1.6 m clear aperture instrument from a 1.7 m blank. The new telescope offers a significant incremental improvement in ground-based infrared and high angular resolution capabilities, and enhances our continuing program to understand photospheric magneto-convection and chromospheric dynamics. These are the drivers for what is broadly called space weather - an important problem, which impacts human technologies and life on earth. This New Solar Telescope (NST) will use the existing BBSO pedestal, pier and observatory building, which will be modified to accept the larger open telescope structure. It will be operated together with our 10 inch (for larger field-of-view vector magnetograms, Ca II K and Ha observations) and Singer-Link (full disk H$\alpha$, Ca II K and white light) synoptic telescopes. The NST optical and software control design will be similar to the existing SOLARC (UH) and the planned Advanced Technology Solar Telescope (ATST) facility led by the National Solar Observatory (NSO) - all three are off-axis designs. The NST will be available to guest observers and will continue BBSO's open data policy. The polishing of the primary will be done in partnership with the University of Arizona Mirror Lab, where their proof-of-concept for figuring 8 m pieces of 20 m nighttime telescopes will be the NST's primary mirror. We plan for the NST's first light in late 2005. This new telescope will be the largest aperture solar telescope, and the largest aperture off-axis telescope, located in one of the best observing sites. It will enable new, cutting edge science. The scientific results will be extremely important to space weather and global climate change research.

• Journal of Korean Society of Forest Science
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• v.110 no.3
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• pp.308-321
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• 2021

The purpose of this study was to analyze domestic research trends over the past 20 years and future direction of forest ecology using text mining. A total of 1,015 academic papers and keywords data related to forest ecology were collected by the "Research and Information Service Section" and analyzed using big data analysis programs, such as Textom and UCINET. From the results of word frequency and N-gram analyses, we found domestic studies on forest ecology rapidly increased since 2011. The most common research topic was "species diversity" over the past 20 years and "climate change" became a major topic since 2011. Based on CONCOR analysis, study subjects were grouped intoeight categories, such as "species diversity," "environmental policy," "climate change," "management," "plant taxonomy," "habitat suitability index," "vascular plants," and "recreation and welfare." Consequently, species diversity and climate change will remain important topics in the future and diversifying and expanding domestic research topics following global research trendsis necessary.