• Journal of KIISE:Databases
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• v.28 no.3
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• pp.512-527
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• 2001

In a client-server spatial database, it is desirable to maintain the cached data in a client side to minimize the communication overhead across a network. This paper deals with the issues of concurrency and consistency of map updates in this environment. A client transaction to update map data is an interactive work and takes a long time to complete it. The map update in a client site may affect the other sites'updates because of dependencies between spatial data stored at different sites. The concurrent updates should be propagated to the other clients as well as the server to keep the consistency of map replicated in a client cache, and also the communication overhead of the update propagation should be minimized not to lose the benefit of caching. The newly proposed cache region locking with CR lock and CX lock controls the update dependency due to spatial relationships. CS lock and COD lock are suggested to use optimistic detection-based approaches for guaranteeing the consistency of cached client data. The cooperative update protocol uses these extended locking primitives and Spatial Relationship-based 2PC (SR-based 2PC). This paper argues that the concurrent updates of cached client spatial data can be achieved by deciding on collaborative updates or independent updates based on spatial relationships.

• Ecology and Resilient Infrastructure
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• v.2 no.2
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• pp.185-190
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• 2015

Greenhouse gas (GHG) emission from agricultural lands is recognized as one of important factors of global warming. The objective of this short communication was to evaluate the applicability of different soil GHG emission prediction models on agricultural systems in Korea. Four models, namely, DNDC, DAYCENT, EXPERT-N and COUP, were selected and the basic structure (e.g., components and sub-model), input variables, and output variables were compared. In particular, the availability and compilation of essential input variables were assessed. Major input variables needed for operating these predictive models were found to be available through database systems established by national organizations such as the Korea Meteorological Administration, the Korean Soil Information System, and the Rural Development Administration. However, in order to apply these models in Korea, it was necessary to calibrate and validate each of the models for the domestic landscape settings and climate conditions. In addition, field data of long-term monitoring of GHG emission from agricultural lands are limited and therefore should be measured.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.18 no.10
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• pp.2551-2561
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• 2014

Several algorithms have been developed to detect AFIB(Atrial Fibrillation) which either rely on the linear and frequency analysis. But they are more complex than time time domain algorithm and difficult to get the consistent rule of irregular RR interval rhythm. In this study, we propose algorithm for optimal value detection of irregular RR interval for AFIB classification based on linear analysis. For this purpose, we detected R wave, RR interval, from noise-free ECG signal through the preprocessing process and subtractive operation method. Also, we set scope for segment length and detected optimal value and then classified AFIB in realtime through liniar analysis such as absolute deviation and absolute difference. The performance of proposed algorithm for AFIB classification is evaluated by using MIT-BIH arrhythmia and AFIB database. The optimal value indicate ${\alpha}=0.75$, ${\beta}=1.4$, ${\gamma}=300ms$ in AFIB classification.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.12 no.4
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• pp.1982-1987
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• 2011

In this study, we proposed a new method that can estimate viscosity curves of unknown samples or high viscous resins like LFT(Long Fiber Thermoplastics). First, we built the system that could detect the pressure of melt during filling the cavity in a mold. It consists of both pressure sensors which are installed in a mold and the Kit which can convert analog signal to digital signal. The kit measures the melt pressure in mold cavity. We could also simulate the cavity pressure during filling process with commercialized CAE softwares(ex, Moldflow). If the viscosity data in CAE Database were correct, the simulated pressure profile coincided with the measured one. According to our proposed algorithm, we obtained correct viscosity data by iterating the process of comparing the simulated profile with the measured one until both coincided each other. In order to verify this algorithm, we selected well-defined PP resin and concluded that the experimental profile comply with the CAE profile. We could also estimate the optimized viscosity curves for PP-LFT by applying our method.

• The KIPS Transactions:PartD
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• v.9D no.3
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• pp.365-380
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• 2002

Temporal data mining, the incorporation of temporal semantics to existing data mining techniques, refers to a set of techniques for discovering implicit and useful temporal knowledge from large quantities of temporal data. Temporal knowledge, expressible in the form of rules, is knowledge with temporal semantics and relationships, such as cyclic pattern, calendric pattern, trends, etc. There are many examples of temporal data, including patient histories, purchaser histories, and web log that it can discover useful temporal knowledge from. Many studies on data mining have been pursued and some of them have involved issues of temporal data mining for discovering temporal knowledge from temporal data, such as sequential pattern, similar time sequence, cyclic and temporal association rules, etc. However, all of the works treated data in database at best as data series in chronological order and did not consider temporal semantics and temporal relationships containing data. In order to solve this problem, we propose a theoretical framework for temporal data mining. This paper surveys the work to date and explores the issues involved in temporal data mining. We then define a model for temporal data mining and suggest SQL-like mining language with ability to express the task of temporal mining and show architecture of temporal mining system.

• The Korean Journal of Mycology
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• v.42 no.4
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• pp.282-288
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• 2014

In this study, we attempted to isolate fungi from soybean fermented foods produced in Sunchang County and to identify Aspergillus oryzae from fungal isolates. Ten fungal isolates were identified with ${\beta}$-tubulin gene. According to the sequences of ${\beta}$-tubulin gene, ten fungal isolates were identified as A. oryzae/flavus complex. For further identification of the ten of fungal isolates, omtA gene, one gene of the aflatoxin biosynthesis gene cluster, was sequenced and the sequences were compared with those of A. oryzae and A. flavus strains from the GenBank database. In addition, identification of the ten fungal isolates was further confirmed using the PCR amplicon of norB and cypA intergenic region, in which a deletion was recognized relative to A. flavus and A. parasiticus. The amplicon size of the ten fungal isolate strains was smaller than those of A. flavus and A. parasiticus, but the same as that of the reference A. oryzae strain. These results indicated that the ten isolates should be identified as A. oryzae. The protease activity in rice koji made with 6, 13, 17, 27, 37 and 38 of strain, respectively was twice higher than that in control. The kojis made with nine of the A. oryzae isolates, respectively, did not produce aflatoxin, suggesting that the strains could possibly be used as starters for soybean products.

• Journal of Preventive Medicine and Public Health
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• v.35 no.2
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• pp.99-106
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• 2002

Objective : Until now, there have been no evidence-based guidelines produced for the mass screening of hyperlipidemia cases in Korea. This study was done to find the most efficient strategy for a hyperlipidemia-screening program among Korean adults, Method : Seven alternative strategies for hyperlipidemia screening were formulated and compared ir terms of cost-effectiveness. Cost and effectiveness were estimated from social perspectives and using a two-stage screening process (initial testing and additional testing for positives from the first test). A computerized database (based on persons who had visited a health promotion center in one teaching hospital for a routine health check-up) was used to determine the cost and the outcome of various strategies. Official data was used in calculating direct and indirect costs. Effectiveness was measured according to the number of persons who needed clinical intervention for hyperlipidemia. A stratified analysis, considering age group and sex, was then done. Sensitivity analyses, focusing on several uncertain parameters, were also done. Results : Of the seven test alternatives available, the most cost-effective strategy was a screening program, which consisted of an initial test of total cholesterol, high-density lipoprotein cholesterol and triglyceride. There was some variation in the rank of the cost-effectiveness ratios for the seven alternatives dependent on age group or gender. Conclusions : Current hyperlipidemia screening practice, for National Health Insurance beneficiaries, tests only the total cholesterol level with a cut-off value of 260mg/dl as an initial screening test. It is not the best strategy for cost-effectiveness, and should be modified. Different screening strategies taking age group and sex into account should be developed and used for the efficient mass screening of hyperlipidemia cases among Korean adults.

• Journal of Animal Environmental Science
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• v.18 no.2
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• pp.95-98
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• 2012

A normal body temperature data base for cattle was established to utilize for automatic monitoring of abnormal body condition of cattle by using sensor network and radio frequency identification technology. Three castrated Holstein cattle (mean body weight: $318{\pm}12kg$) were employed for body temperature measurement. Animals were adapted at the stanchion barn over 2 weeks, and 4 places (skins of ear, neck, head and subcutaneous tissue of neck) of body temperatures were continuously measured through thermocouples and recorder devices for 9 days. All places of body temperatures were fluctuated throughout the day and showed a cyclic pattern, with higher temperature in day time and lower temperature in nigh time. Normal subcutaneous tissue temperature (core temperature) in a day was ranged from $36.1^{\circ}C$ to $38.2^{\circ}C$. Skin temperatures were varied largely with environmental temperature change. Ear, head and neck temperatures varied with $36.3{\sim}28.5^{\circ}C$, $36.1{\sim}28.0^{\circ}C$ and $35.0{\sim}28.2^{\circ}C$, respectively. In this study, we established a basic data base for normal body temperature in cattle. For more effective data base, it would be needed further study.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.35 no.3
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• pp.133-144
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• 2017

Recently, weather information is getting closer to our real life, and it is a very important factor especially in the transportation field. Although the damage caused by the abnormal climate changes around the world has been gradually increased and the correlation between the road risk and the possibility of traffic accidents is very high, the domestic research has been performed at the level of basic research. The Purpose of this study is to develop a risk map for the road hazard forecasting service of weather situation by linking real - time weather information and traffic information based on accident analysis data by weather factors. So, we have developed a collection and analysis about related data, processing, applying prediction models in various weather conditions and a method to provide the road hazard map for national highways and provincial roads on a web map. As a result, the road hazard map proposed in this study can be expected to be useful for road managers and users through online and mobile services in the future. In addition, information that can support safe autonomous driving by continuously archiving and providing a risk map database so as to anticipate and preemptively prepare for the risk due to meteorological factors in the autonomous driving vehicle, which is a key factor of the 4th Industrial Revolution, and this map can be expected to be fully utilized.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.17 no.9
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• pp.533-542
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• 2016

The periodic maintenance of bridges is necessary once they have been constructed and its cost depends on various factors, such as their condition, environmental conditions and so on. To make a decision support system, it is essential to establish a basic reconstruction cost model. In this study, a regression model is suggested for calculating the reconstruction cost for typical cases and influential factors, depending on the type of bridge and its components, by analyzing the basic bridge specifications based on the data of the Bridge Management System (BMS). The details for each case were estimated in consideration of the cost calculation variables. The details for each case were estimated in consideration of the cost calculation variables. The cost model for the new construction of the superstructure, substructure and foundation and the temporary bridge construction and demolition costs were drawn from the regression analysis of the estimation results of typical cases according to the cost calculation variables. The reconstruction costs for different types of bridge were obtained using the cost model and compared with those in the literature. The cost model developed herein is expected to be utilized effectively in maintenance decision making.