• The KIPS Transactions:PartD
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• v.11D no.6
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• pp.1247-1258
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• 2004

The LBS(Location-Based Service), which is based on individual's mobility, is required increasingly as mobile telecommunication and various infrastructures have developed rapidly. The technologies for LBS are location determination technology, service platform technology, contents provider technology and moving object database technology generally. Among these, service platform must be interoperable with location gate-way server and provide common function of billing, authentification, protect location information, privacy control, location trigger and intelligent acquisition and so on. The TTA(Telecommunications Technology Association) published specification that defines a standard protocol for safe and simple interface between LBS client and LBS platform and the OpenLS(Open Location Service) in OGC (Open GIS Consortium) released implementation specifications for providing Location based core services. In this paper, we implemented service platform for LBS which is able to interoperable with location gateway server and contents provider and is caracterized as follows. First, it could require and response location information from different types of location gateway server with same interface. Second, it complies with the standard interfaces with OpenLS 4 contents providers for core LBS. Third, it could provide location of wired phone as well as wireless mobile terminal compling with the standard protocol. Last, it could provide trajectorH information based past location as well as current location, because it is able to interoperable with moving object DBMS. This paper contributes to the construction and practical use of LBS by providing the method of implementation of service platform for LBS.

• Journal of Korean Society for Geospatial Information Science
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• v.12 no.1 s.28
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• pp.69-77
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• 2004

Since there are a lot of changes in climate on domestic and natural disasters owing to the disturbance-development of the land, damages of properties and human life frequently occur due to the coastal floodings. Accordingly, it is necessary to find the area where the danger of flooding coasts is relatively high and to inform resident the characteristics of the area As a part of preventive land management to minimize the flooding damages of the coastal area, this study suggested the generation of the coastal flood hazard map that provides detailed information such as refuge path, a place of refuge, and the location of medical supplies, food, and main rescue equipment, etc. This study selected the southern region of Daebu-do as an exemplary area, conducted a document study to establish GIS data, secured pre-structured data, and suggested the method of establishing GIS data fit to the study area. In particular, it emphasized the efficient construction of the geographical spatial data that were accurate, economic, objective, and realistic in supporting the modeling to predict the flooding zone. The specific type of established database was divided into flooding risk area, flooding warning area, and flooding-volume area. The prototype of coastal flood hazard map can be widely used for efficient disaster management. Furthermore, it is considered that the map could be applied for arousing residents' attentions to the flooding, prior education, and local governments' management actions against the danger of flooding.

• Journal of Food Hygiene and Safety
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• v.27 no.4
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• pp.339-348
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• 2012

The purpose of this study is to predict the economic size of foods-for-elderly market, which will be valuable information for establishing related policy and backup system. After setting the scope of related industry, detailed information for current market situation was investigated and a systematic forecast for market changes in the future was performed. Economic growth, changes in consumer expenditure and economic status of the elderly, current subscription of medical insurance and saving for pension were reflected. In addition, a survey toward related firms was completed and changes in aged population and incidence of chronic disease in the elderly were taken into account. Results show that the annual growth rate of the market was predicted to be the minimum 4.54% through the maximum 8.32% from 2010 to 2025 and its market size was forecasted to be the minimum 7,073 ten million won through the maximum 10,976 ten million won. It is expected that the market of foods-for-elderly will grow rapidly with development of foods technology and fast increase of aged population. Especially, growth of health functional foods and foods for special dietary uses for elderly will be distinguished. However, it seems that related firms are on the hedge, watching current trend of the related industry. This may results in insufficient supply against the demand. Therefore, policy for foods-for-elderly should be introduced and systematically administered, including R&D support, standardization and authentication for foods-for-elderly, construction of related database system.

• Journal of KIISE:Databases
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• v.33 no.1
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• pp.12-31
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• 2006

The n-gram inverted index has two major advantages: language-neutral and error-tolerant. Due to these advantages, it has been widely used in information retrieval or in similar sequence matching for DNA and Protein databases. Nevertheless, the n-gram inverted index also has drawbacks: the size tends to be very large, and the performance of queries tends to be bad. In this paper, we propose the two-level n-gram inverted index (simply, the n-gram/2L index) that significantly reduces the size and improves the query performance while preserving the advantages of the n-gram inverted index. The proposed index eliminates the redundancy of the position information that exists in the n-gram inverted index. The proposed index is constructed in two steps: 1) extracting subsequences of length m from documents and 2) extracting n-grams from those subsequences. We formally prove that this two-step construction is identical to the relational normalization process that removes the redundancy caused by a non-trivial multivalued dependency. The n-gram/2L index has excellent properties: 1) it significantly reduces the size and improves the Performance compared with the n-gram inverted index with these improvements becoming more marked as the database size gets larger; 2) the query processing time increases only very slightly as the query length gets longer. Experimental results using databases of 1 GBytes show that the size of the n-gram/2L index is reduced by up to 1.9${\~}$2.7 times and, at the same time, the query performance is improved by up to 13.1 times compared with those of the n-gram inverted index.

• Korean Journal of Remote Sensing
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• v.22 no.6
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• pp.621-626
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• 2006

Today's commercial high resolution satellite imagery such as IKONOS and QuickBird, offers the potential to extract useful spatial information for geographical database construction and GIS applications. Extraction of 3D building information from high resolution satellite imagery is one of the most active research topics. There have been many previous works to extract 3D information based on stereo analysis, including sensor modelling. Practically, it is not easy to obtain stereo high resolution satellite images. On single image performance, most studies applied the roof-bottom points or shadow length extracted manually to sensor models with DEM. It is not suitable to apply these algorithms for dense buildings. We aim to extract 3D building information from a single satellite image in a simple and practical way. To measure as many buildings as possible, in this paper, we suggested a new way to extract building height by triangular vector structure that consists of a building bottom point, its corresponding roof point and a shadow end point. The proposed method could increase the number of measurable building, and decrease the digitizing error and the computation efficiency.

• Journal of IKEEE
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• v.23 no.1
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• pp.112-119
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• 2019

In this paper, we propose a deep learning structure suitable for embedded system. The flame detection process of the proposed deep learning structure consists of four steps : flame area detection using flame color model, flame image classification using deep learning structure for flame color specialization, $N{\times}N$ cell separation in detected flame area, flame image classification using deep learning structure for flame shape specialization. First, only the color of the flame is extracted from the input image and then labeled to detect the flame area. Second, area of flame detected is the input of a deep learning structure specialized in flame color and is classified as flame image only if the probability of flame class at the output is greater than 75%. Third, divide the detected flame region of the images classified as flame images less than 75% in the preceding section into $N{\times}N$ units. Fourthly, small cells divided into $N{\times}N$ units are inserted into the input of a deep learning structure specialized to the shape of the flame and each cell is judged to be flame proof and classified as flame images if more than 50% of cells are classified as flame images. To verify the effectiveness of the proposed deep learning structure, we experimented with a flame database of ImageNet. Experimental results show that the proposed deep learning structure has an average resource occupancy rate of 29.86% and an 8 second fast flame detection time. The flame detection rate averaged 0.95% lower compared to the existing deep learning structure, but this was the result of light construction of the deep learning structure for application to embedded systems. Therefore, the deep learning structure for flame detection proposed in this paper has been proved suitable for the application of embedded system.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.22 no.1
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• pp.409-414
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• 2021

Tightness performance that blocks compartments is important for surface ships to achieve superior mission performance and survivability in combat environments. To meet the above requirements, airtightness of the structural elements and the appropriate strength to specific areas are checked during a test run after ship construction. In particular, air tests of compartments adjacent to the water surface are performed. In an air test, air is injected into the compartment up to the test pressure of the test memo. The pressure drop value is checked after 10 minutes to determine if the requirements of the corresponding area are satisfied. In summer, however, when the influence of the outside temperature is large, a phenomenon in which the internal pressure increases during the air test was identified. This phenomenon reduces the reliability of the test result. Therefore, a system was designed to compensate for temperature changes in the compartments through this study. The developed system calculates the amount of pressure change caused by a temperature change in the compartment and outputs a correction value. The pressure change was calculated using the ideal gas equation, reflecting the maintenance, increase, and decrease in temperature during the test process. A comparison of the calculated pressure correction value with the database of NIST REFPROP revealed a difference of 0.126% to a maximum of 0.253%.

• Korean Journal of Remote Sensing
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• v.38 no.6_2
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• pp.1643-1652
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• 2022

Deposited Marine Debris(DMD) can negatively affect marine ecosystems, fishery resources, and maritime safety and is mainly detected by sonar sensors, lifting frames, and divers. Considering the limitation of cost and time, recent efforts are being made by integrating underwater images and artificial intelligence (AI). We conducted a comparative study of You Only Look Once Version 5 (YOLOv5) and You Only Look Once Version 7 (YOLOv7) models to detect DMD from underwater images for more accurate and efficient management of DMD. For the detection of the DMD objects such as glass, metal, fish traps, tires, wood, and plastic, the two models showed a performance of over 0.85 in terms of Mean Average Precision (mAP@0.5). A more objective evaluation and an improvement of the models are expected with the construction of an extensive image database.

• Journal of Korean Society of Disaster and Security
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• v.16 no.1
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• pp.1-11
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• 2023

The comprehensive natural disaster reduction plan, the highest plan in the disaster prevention field, was implemented by local governments. second plan is currently being formulated. In order to minimize human and property damage, structural and non-structural measures for each of the nine disaster types are established and implemented for 10 years. Structural measures are based on engineering and quantitative analysis, and the criteria for setting reduction measures are clear. Non-structural measures, however, currently lack the set criteria. the basic disaster and safety management law included the safety vulnerable class in 2018. Currently, the safety vulnerable class of the detailed establishment criteria of the comprehensive natural disaster reduction plan is being established, including children, the elderly, and the disabled. However, due to the lack of data securing and database construction by local governments, it is difficult to prepare a location map for establishing reduction measures for the safety vulnerable. Therefore, in this study, OPEN API data of the safety vulnerable class were collected and statistical information and GIS of SGIS information services were used. The distribution diagram of the safety vulnerable class in Samcheok, Gangwon-do, which is a sample area, and the distribution diagram of the safety vulnerable class in units of the output area (OA) in Geundeok-myeon were prepared.

• Journal of Internet of Things and Convergence
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• v.9 no.3
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• pp.27-33
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• 2023

In this study, it was analyzed with the dyeing pattern of Diospyros kaki Thunb (persimmon) and was tried to numerically evaluate how the dyeing pattern in silk fabrics and cells was changed by different mordants. When the dyed silk fabrics were sufficiently dried, the silk fabrics were found to have a pale yellow color. Interestingly, iron II sulfate mordant changed the color change the most, silk fabrics were dyed with a color close to brown or dark purple. For numerical analysis, 19% and 62.5% color changes could be induced by sodium tartrate plus citric acid and copper acetate, respectively. Iron II sulfate induced the greatest difference than that of untreated mordants at 88%. About 5% and 10% of Chinese hamster ovary (CHO) cells were stained by sodium tartrate plus citric acid and copper acetate, respectively. The staining effect induced by iron II sulfate was about 2.4 times higher than the staining effect by sodium tartrate plus citric acid. In previous studies, staining results have been visually confirmed. However, this results not only visually confirmed the dyeing, but also quantified the color change. In particular, if numerical results are continuously integrated into big data, any researcher will be able to easily obtain similar results even if the method, time, volume, etc. are changed. In addition, the numerical data of this study is considered to be an important basis for building a database for IoT construction and computer analysis.