• Journal of Korean Society of Disaster and Security
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• v.17 no.1
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• pp.17-25
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• 2024

Recent climate change has led to an increase in the probability of forest disasters (forest fires, landslides). However, disaster systems providing information for forest disaster response lack unified information provision. Therefore, this study aims to provide essential disaster information from a unified system for swift disaster response. To achieve this goal, we conducted a fundamental study on the necessary components for designing a forest disaster platform, explored methods for visualizing platforms enabling swift response and information provision during forest disasters through case studies, and presented the findings. Our results indicate that both domestic and international forest disaster response platforms commonly utilize spatial information to provide location-specific information. Key components identified for designing a response platform for forest disasters include constructing forest disaster big data, including climate information for target areas, developing technology for integrated diagnosis of forest disasters at each stage, and designing tailored safety care services for disaster areas.

• Korean Journal of Agricultural and Forest Meteorology
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• v.15 no.2
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• pp.109-117
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• 2013

The Global Framework on Climate Services (GFCS) will guide the development of climate services that link science-based climate information and predictions with climate-risk management and adaptation to climate change. GFCS structure is made up of 5 pillars; Observations/Monitoring (OBS), Research/ Modeling/ Prediction (RES), Climate Services Information System (CSIS) and User Interface Platform (UIP) which are all supplemented with Capacity Development (CD). Corresponding to each GFCS pillar, the Commission for Agricultural Meteorology (CAgM) has been proposing "Global Initiatives in AgroMeteorology" (GIAM) in order to facilitate GFCS implementation scheme from the perspective of AgroMeteorology - Global AgroMeteorological Outlook System (GAMOS) for OBS, Global AgroMeteorological Pilot Projects (GAMPP) for RES, Global Federation of AgroMeteorological Society (GFAMS) for UIP/RES, WAMIS next phase for CSIS/UIP, and Global Centers of Research and Excellence in AgroMeteorology (GCREAM) for CD, through which next generation experts will be brought up as virtuous cycle for human resource procurements. The World AgroMeteorological Information Service (WAMIS) is a dedicated web server in which agrometeorological bulletins and advisories from members are placed. CAgM is about to extend its service into a Grid portal to share computer resources, information and human resources with user communities as a part of GFCS. To facilitate ICT resources sharing, a specialized or dedicated Data Center or Production Center (DCPC) of WMO Information System for WAMIS is under implementation by Korea Meteorological Administration. CAgM will provide land surface information to support LDAS (Land Data Assimilation System) of next generation Earth System as an information provider. The International Society for Agricultural Meteorology (INSAM) is an Internet market place for agrometeorologists. In an effort to strengthen INSAM as UIP for research community in AgroMeteorology, it was proposed by CAgM to establish Global Federation of AgroMeteorological Society (GFAMS). CAgM will try to encourage the next generation agrometeorological experts through Global Center of Excellence in Research and Education in AgroMeteorology (GCREAM) including graduate programmes under the framework of GENRI as a governing hub of Global Initiatives in AgroMeteorology (GIAM of CAgM). It would be coordinated under the framework of GENRI as a governing hub for all global initiatives such as GFAMS, GAMPP, GAPON including WAMIS II, primarily targeting on GFCS implementations.

• International Journal of Computer Science & Network Security
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• v.23 no.3
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• pp.57-66
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• 2023

Rice is an important food crop for most of the population in the world and it is largely cultivated in Pakistan. It not only fulfills food demand in the country but also contributes to the wealth of Pakistan. But its production can be affected by climate change. The irregularities in the climate can cause several diseases such as brown spots, bacterial blight, tungro and leaf blasts, etc. Detection of these diseases is necessary for suitable treatment. These diseases can be effectively detected using deep learning such as Convolution Neural networks. Due to the small dataset, transfer learning models such as vgg16 model can effectively detect the diseases. In this paper, vgg16, inception and xception models are used. Vgg16, inception and xception models have achieved 99.22%, 88.48% and 93.92% validation accuracies when the epoch value is set to 10. Evaluation of models has also been done using accuracy, recall, precision, and confusion matrix.

• Proceedings of the Korea Water Resources Association Conference
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• 2016.05a
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• pp.518-518
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• 2016

Agriculture is the lifeblood of the economy in Ghana, employs about 42% of the population work force and accounts for 30% of the Gross Domestic Product (GDP). Corn (maize) is the major cereal crop grown as staple food under rain fed conditions, covers over 92% of the total agricultural area, and contributes 54% of the caloric intake. Issues of hunger and food insecurity for the entire nation are associated with corn scarcity and low production. The climate changes are expected to affect corn production in Ghana. This study evaluated variations of corn yields based on different climate conditions of rain-fed area in the Dangbe East District of Ghana. AquaCrop model has been used to simulate corn growing cycles in study area for this purpose. The main goal for this study was to predict yield of corn using selected climatic parameters from 1992 to 2013 using different climate scenarios. The Model was calibrated and validated using observed field data, and the simulated grain yields matched well with observed values for the season under production giving an R squared (R2)of 0.93 and Nash-Sutcliff Error(NSE) of 0.21. Study results showed that rainfall reduction in the range of -5% to -20% would reduce the yield from 1.315ton/ha to 0.421ton/ha (-21. 3%) whereas increasing temperature from 1% to 7% would result in the maximum yield reduction of -20.6% (1.315 to 1.09 ton/ha.). On the other hand, increasing rainfall from 5-20% resulted in yield increment of 68% (1.315-2.209 ton/ha) and decreasing temperature produce 7% increase in yield ( 1.315 to 1.401ton/ha). These results provide useful information to adopt strategies by the Government of Ghana and farmers for improving national food security under climate change.

• KNOM Review
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• v.22 no.2
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• pp.39-47
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• 2019

There are several big data-driven advanced research activities such as meteorological climate information, high energy physics, astronomy research, satellite information data, and genomic research data on KREONET. Since the performance degradation occurs in the environment with the existing network security equipment, methods for preventing the performance degradation on the high-performance research-only network and for high-speed research collaboration are being studied. In addition, the recent issue of quantum computers has been a threat to security using the existing encryption system. In this paper, we construct quantum cryptography-based communication network through environment construction and high-performance transmission test that build physical security through quantum cryptography-based communication network in end-to-end high-speed research network. The purpose of this study is to analyze the effect on network performance when performing physical encryption and to use it as basic data for constructing high-performance research collaboration network.

• Journal of the Society of Disaster Information
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• v.18 no.1
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• pp.194-201
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• 2022

Purpose: This study investigated the relationship between climate factors and the catches in Korean offshore fisheries in recent three decades (1981 to 2010). Method: This study focused on seven types of fish species preferred in Korean cuisine. In the study, 10-year moving averages were used so that long-term trends could be easily identified. Results: Both air temperature and sea surface temperature (SST) on the coast of Korea rose in the period (p < 0.05). The rise in SST was significantly correlated with the rise in air temperature (p < 0.05), but not with precipitation. In the 2010s compared to in the 1981, catches of anchovy and squid greatly increased (p < 0.05), while catches of Alaska / walleye pollock has been almost extinct over the past 30 years. As such, cold-water fish species decreased or disappeared, and their fishing ground was replaced by warm-water fish species. Conclusions: These findings indicate that fish species caught in offshore fisheries of Korea have changed due to climate change, especially warming. This suggests that the warming of the Korean Peninsula may have a significant impact on the supply of fishery products and food security to Koreans in the near future.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.24 no.7
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• pp.904-913
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• 2020

As the data volumes and complexity rapidly increase, data-intensive science handling large-scale scientific data needs to investigate new techniques for intelligent storage and data distribution over networks. Recently, Named Data Networking (NDN) and data-intensive science communities have inspired innovative changes in distribution and management for large-scale experimental data. In this article, analysis on NDN testbeds for large-scale scientific data such as climate science data and High Energy Physics (HEP) data is presented. This article is the first attempt to analyze existing NDN testbeds for large-scale scientific data. NDN testbeds for large-scale scientific data are described and discussed in terms of status, NDN-based application, and features, which are NDN testbed instance for climate science, NDN testbed instance for both climate science and HEP, and the NDN testbed in SANDIE project. Finally various issues to prevent pitfalls in NDN testbed establishment for large-scale scientific data are analyzed and discussed, which are drawn from the descriptions of NDN testbeds and features on them.

• Journal of Digital Convergence
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• v.12 no.9
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• pp.219-223
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• 2014

In line with the advanced wireless communication technology, M2M (Machine-to-Machine) communication has drawn attention in industry. M2M communication features are installed and operated in the fields where human accessibility is highly limited such as disaster, safety, construction, health and welfare, climate, environment, logistics, culture, defense, medical care, agriculture and stockbreeding. In M2M communication, machine replaces people for automatic communication and countermeasures as part of unmanned information management and machine operation. Wireless M2M inter-device communication is likely to be exposed to intruders' attacks, causing security issues, which warrants proper security measures including cross-authentication of whether devices are legitimate. Therefore, research on multiple security protocols has been conducted. The present study applied SessionKey, HashFunction and Nonce to address security issues in M2M communication and proposed a safe protocol with reinforced security properties. Notably, unlike most previous studies arguing for the security of certain protocols based on mathematical theorem proving, the present study used the formal verification with Casper/FDR to prove the safety of the proposed protocol. In short, the proposed protocol was found to be safe and secure.

• 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 the Korea Society of Computer and Information
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• v.8 no.3
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• pp.179-187
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• 2003

This study investigate the reasons of organizational failure in detection and appropriate response to risk signal. The Crisis does not come true suddenly, there is some risk signals in crisis. If Organization detect the risk signals the crisis is come true opportunities, if not the crisis is come true disastrous outcome. This is use the system dynamics approach. System Dynamics assume the system as a collection of causal feedback loop, so we understand the dynamics around the problems. This investigate suggest that, the focus on growth is the a kind of promotional pressure and the pressure drive the organization to less attention the risk signal, so the risk is underestimate In proportion to real risk. Ultimate, the organization entrap the promotional climate and insensible to security. This study is a kind of hypothesis-discovering research, in the further study, the discovered hypothesis will be empirically tested.