• Journal of Korean Society of Industrial and Systems Engineering
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• v.38 no.3
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• pp.64-77
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• 2015

An effective method for produce munitions effectiveness data is to calculate weapon effectiveness indices in the US military's Joint Munitions Effectiveness Manuals (JMEM) and take advantage of the damage evaluation model (GFSM) and weapon Effectiveness Evaluation Model (Matrix Evaluator). However, a study about the Range Safety that can be applied in the live firing exercises is very insufficient in the case of ROK military. The Range Safety program is an element of the US Army Safety Program, and is the program responsible for developing policies and guidance to ensure the safe operation of live-fire ranges. The methodology of Weapon Danger Zone (WDZ) program is based on a combination of weapon modeling/simulation data and actual impact data. Also, each WDZ incorporates a probability distribution function which provides the information necessary to perform a quantitative risk assessment to evaluate the relative risk of an identified profile. A study of method to establish for K-Range Safety data is to develop manuals (pamphlet) will be a standard to ensure the effective and safe fire training at the ROK military education and training and environmental conditions. For example, WDZs are generated with the WDZ tool as part of the RMTK (Range Managers Tool Kit) package. The WDZ tool is a Geographic Information System-based application that is available to operational planners and range safety manager of Army and Marine Corps in both desktop and web-based versions. K-Range Safety Program based on US data is reflected in the Korean terrain by operating environments and training doctrine etc, and the range safety data are made. Thus, verification process on modified variables data is required. K-Range Safety rather than being produced by a single program, is an package safety activities and measures through weapon danger zone tool, SRP (The Sustainable Range Program), manuals, doctrine, terrain, climate, military defence M&S, weapon system development/operational test evaluation and analysis to continuously improving range safety zone. Distribution of this K-range safety pamphlet is available to Army users in electronic media only and is intended for the standing army and army reserve. Also publication and distribution to authorized users for marine corps commands are indicated in the table of allowances for publications. Therefore, this study proposes an efficient K-Range Safety Manual producing to calculate the danger zones that can be applied to the ROK military's live fire training by introducing of US Army weapons danger zone program and Range Safety Manual

• Journal of the Korea Institute of Information and Communication Engineering
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• v.22 no.7
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• pp.1021-1029
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• 2018

The marine buoys are operated in various domains, which are navigation route and danger maker, weather and environment monitoring, military strategical element, etc. If the marine buoy is damaged, there consumes many cost and time for recovery or replacement, because of severe environmental condition, and causes a risk possibility of secondary accident. In this paper, we developed an active monitoring and approach alarm providing system using trail cameras and AIS for protection for the marine buoys. To do this, we analyzed existing researches and similar systems, extracted requirements for enhancement, and designed the system architecture that applied the enhanced elements. The main considerations of system enhancement are: integration of AIS and trail cameras, adopting of phased alarm technique by approaching ships, applying of selective communication module, conducting the image processing of ships for providing alarm, and applying thermal cameras. After that, we developed the system using designed architecture and verified effectiveness of the system based on laboratory or field-level tests.

• Korean Journal of Remote Sensing
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• v.22 no.6
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• pp.575-579
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• 2006

The land use in suburban area has been changed rapidly due to the urban expansion in Korea during the last few decades. And such land use changes result in various environmental problems such as biodiversity decrease, habitat fragmentation, air pollution and urban heat island. Remote Sensing (RS) and Geographical Information Systems (GIS) can be used for land cover change detection to understand the impact and trend of the land use change. Change detection is the process of identifying differences in the state of an object or phenomenon by observing it at different times and it can provide quantitative and comparative information for the land use/cover change. RS is less expansive than field survey for producing land use maps, and can be accessed quickly and repetitively for large area. Also it can be used for change detection using multi-temporal land use/cover by accumulated data. Therefore, the purpose of this study is to detect and quantitatively evaluate urban land cover change in urban stream watershed area for the last few decades and ultimately to provide the basic data for urban land use planning and management.

• Korean Journal of Remote Sensing
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• v.37 no.6_3
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• pp.2027-2034
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• 2021

Using multi-temporal KOMPSAT-3/3A high-resolution satellite images, the Normalized Difference Vegetation Index (NDVI) for the area around the Fukushima daiichi nuclear power plant was determined, and the pattern of vegetation changes was analyzed. To calculate the NDVI, surface reflectance from the KOMPSAT-3/3A satellite image was used. Satellite images from four years were used, and the zones where the images overlap was designated as the area of interest (AOI) for the study, and by setting a profile passing through highly vegetated area as a data analysis method, the changes by year were examined. In addition, random points were extracted within the AOI and displayed as a box plot to quantitatively indicate change of NDVI distribution pattern. The main results of this study showed that the NDVI in 2014 was low within AOI in the vicinity of the nuclear power plant, but vegetated area continued to expand until 2021. These results were also confirmed in the change monitoring results shown in a profile or box plot. In disaster areas where access is restricted, such as the Fukushima nuclear power plant area, where it is difficult to collect field data, obtaining land cover classification products with high accuracy using satellite images is challenging, so it is appropriate to analyze them using primary outputs such as vegetation indices obtained from high-resolution satellite imagery. It is necessary to establish an international cooperation system for jointly utilizing satellite images. Meanwhile, to periodically monitor environmental changes in neighboring countries that may affect the Korean peninsula, it is necessary to establish utilization models and systems using high-resolution satellite images.

• Atmosphere
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• v.31 no.2
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• pp.241-249
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• 2021

A smart city utilizes data collected from various sensors through the internet of things (IoT) and improves city operations across the urban area. Recently substantial research is underway to examine all aspects of data that requires for the smart city operation. Atmospheric data are an essential component for successful smart city implementation, including Urban Air Mobility (UAM), infrastructure planning, safety and convenience, and traffic management. Unfortunately, the current level of conventional atmospheric data does not meet the needs of the new city concept. New and innovative approaches to developing high spatiotemporal resolution of observational and modeling data, resolving the complex urban structure, are expected to support the future needs. The geographic information system (GIS) integrates the atmospheric data with the urban structure and offers information system enhancement. In this study we proposed the necessity and applicability of the high resolution urban meteorological dataset based on heavy fog cases in the smart city region (e.g., Sejong and Pusan) in Korea.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.15 no.5
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• pp.1666-1689
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• 2021

The red line of Permanent Basic Farmland is the most important part in the "three-line" demarcation of China's national territorial development plan. The scientific and reasonable delineation of the red line is a major strategic measure being taken by China to improve its ability to safeguard the practical interests of farmers and guarantee national food security. The delineation of Permanent Basic Farmland zoning (DPBFZ) is essentially a multi-objective optimization problem. However, the traditional method of demarcation does not take into account the synergistic development goals of conservation of cultivated land utilization, ecological conservation, or urban expansion. Therefore, this research introduces the idea of artificial immune optimization and proposes a multi-objective model of DPBFZ red line delineation based on a clone selection algorithm. This research proposes an objective functional system consisting of these three sub-objectives: optimal quality of cropland, spatially concentrated distribution, and stability of cropland. It also takes into consideration constraints such as the red line of ecological protection, topography, and space for major development projects. The mathematical formal expressions for the objectives and constraints are given in the paper, and a multi-objective optimal decision model with multiple constraints for the DPBFZ problem is constructed based on the clone selection algorithm. An antibody coding scheme was designed according to the spatial pattern of DPBFZ zoning. In addition, the antibody-antigen affinity function, the clone mechanism, and mutation strategy were constructed and improved to solve the DPBFZ problem with a spatial optimization feature. Finally, Tongxu County in Henan province was selected as the study area, and a controlled experiment was set up according to different target preferences. The results show that the model proposed in this paper is operational in the work of delineating DPBFZ. It not only avoids the adverse effects of subjective factors in the delineation process but also provides multiple scenarios DPBFZ layouts for decision makers by adjusting the weighting of the objective function.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.13 no.6
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• pp.556-561
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• 2020

The aging and declining agricultural population in the modern society requires improvement of the agricultural environment and is one of the representative problems. And since most of the work systems always require a transport work, the ratio of labor consumed in the transport work is very high. Accordingly, many types of transport vehicles are being developed and sold, and in the early days, most of them are powered transport vehicles using fossil fuels. However, it is paying attention to next-generation eco-friendly energy such as hydrogen, fuel cells, solar power, and bio due to the strengthening of international environmental regulations such as global warming and the Convention on Climate Change and the depletion of fossil fuels. Therefore, in this study, the ultimate goal is to develop an eco-friendly, easy-to-operate, safe agricultural electric vehicle that replaces fossil fuels. It was designed with a focus on controlling a wide range of vehicle speeds and securing stability of electric agricultural vehicles. Considering the performance and design, it is composed of a frame, a driving part, a steering part, and a controller system, and we are going to review and manufacture each part. It is believed that the manufactured electric vehicle for agriculture can be easily and conveniently operated in an agricultural society where young manpower is scarce, and can be helpful to the agricultural society through high efficiency.

• Korean Journal of Remote Sensing
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• v.36 no.6_3
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• pp.1711-1720
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• 2020

Particulate matter (PM) that has been artificially generated during the recent of rapid industrialization and urbanization moves and disperses according to weather conditions, and adversely affects the human skin and respiratory systems. The purpose of this study is to predict the PM10 concentration in Seoul using meteorological factors as input dataset for multiple linear regression (MLR), support vector machine (SVM), and random forest (RF) models, and compared and evaluated the performance of the models. First, the PM10 concentration data obtained at 39 air quality monitoring sites (AQMS) in Seoul were divided into training and validation dataset (8:2 ratio). The nine meteorological factors (mean, maximum, and minimum temperature, precipitation, average and maximum wind speed, wind direction, yellow dust, and relative humidity), obtained by the automatic weather system (AWS), were composed to input dataset of models. The coefficients of determination (R2) between the observed PM10 concentration and that predicted by the MLR, SVM, and RF models was 0.260, 0.772, and 0.793, respectively, and the RF model best predicted the PM10 concentration. Among the AQMS used for model validation, Gwanak-gu and Gangnam-daero AQMS are relatively close to AWS, and the SVM and RF models were highly accurate according to the model validations. The Jongno-gu AQMS is relatively far from the AWS, but since PM10 concentration for the two adjacent AQMS were used for model training, both models presented high accuracy. By contrast, Yongsan-gu AQMS was relatively far from AQMS and AWS, both models performed poorly.

• Journal of Intelligence and Information Systems
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• v.29 no.3
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• pp.383-400
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• 2023

Air pollution-related diseases are escalating worldwide, with the World Health Organization (WHO) estimating approximately 7 million annual deaths in 2022. The rapid expansion of industrial facilities, increased emissions from various sources, and uncontrolled release of odorous substances have brought air pollution to the forefront of societal concerns. In South Korea, odor is categorized as an independent environmental pollutant, alongside air and water pollution, directly impacting the health of local residents by causing discomfort and aversion. However, the current odor management system in Korea remains inadequate, necessitating improvements. This study aims to enhance the odor management system by analyzing 1,010,749 data points collected from odor sensors located in Osong, Chungcheongbuk-do, using an Ensemble-Based Multi-Region Integrated Odor Concentration Prediction Model. The research results demonstrate that the model based on the XGBoost algorithm exhibited superior performance, with an RMSE of 0.0096, significantly outperforming the single-region model (0.0146) with a 51.9% reduction in mean error size. This underscores the potential for increasing data volume, improving accuracy, and enabling odor prediction in diverse regions using a unified model through the standardization of odor concentration data collected from various regions.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.26 no.1D
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• pp.115-123
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• 2006

Recently, construction claims have been increased for protecting the rights of construction participants and effectively adjusting the changes under the contract. Thus, the importance of claim management has been emphasized in the construction industry. In domestic construction industry, some claim issues involved in construction activities are often being developed into disputes and even litigations because of the absence of methods or systems for the dispute resolution, and the lack of judicial precedents which can be provided as the references for resolving a particular dispute. In general, the judicial precedents related to the disputes and litigations occurred among construction participants would be extremely valuable in evaluating and analyzing current claims issues. However, such useful information has not been effectively accumulated and utilized in resolving the similar or sometimes identical types of disputes, thus requiring a large amount of additional costs, time and efforts. The primary objective of this study is to propose a web-based decision support system for construction claim management, which enables contractual participants to easily access and use the information of the judicial precedents related to the current construction claims. The decision support system is composed of 'prevention' and 'settlement' modules for avoiding and systematically resolving the construction claims.