• Journal of the Korea Concrete Institute
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• v.18 no.6 s.96
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• pp.759-767
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• 2006

This paper presents a method to estimate the setting time of concrete using super retarding agent(SRA) and fly ash(FA) under various curing temperature conditions by applying maturity based on equivalent age. To estimate setting time, the equivalent age using apparent activation energy($E_a$) was applied. Increasing SRA content and decreasing curing temperature leads to retard initial and final set markedly. $E_a$ at the initial set and final set obtained by Arrhenius function showed differences in response to mixture type. It is estimated to be from $24{\sim}35KJ/mol$ in all mixtures, which is smaller than that of conventional mixture ranging from $30{\sim}50KJ/mol$. Based on the application of $E_a$ to Freisleben-Hansen and Pederson's equivalent age function, equivalent age is nearly constant, regardless of curing temperature and SRA contents. This implies that the concept of maturity is applicable in estimating the setting time of concrete containing SRA. A high correlation between estimated setting time and measured setting time is observed. Multi-regression model to determine appropriate dosage of SRA reflecting FA contents and equivalent age was provided. Thus, the setting time estimation method studied herein can be applicable to the concrete containing SRA and FA in construction fields.

• Journal of Navigation and Port Research
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• v.39 no.6
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• pp.485-491
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• 2015

The technology review about risk of hypothermia of victim according to heat transfer characteristic of life raft and sea state can use accident correspondence of standing and sinking of ship. This study studied heat transfer characteristics required for the design of life raft and thermal insulation property analysis and evaluation methods. In addition, it is study for comprehend the risk of hypothermia and suggest analysis result that is experiment of thermal insulation property and body temperature property for decide of prediction the body temperature decline Thermal Analysis apply the finite element analysis method is comprehended the property of heat conductivity, convective effect of sea water and properties changes according to property of insulation material. it measure the heat flux with attach temperature sensor on body in order to comprehend the variation of body temperature with boarding a life raft experiment on a human body. This study validate results by comparing variation of temperature measured from experiment on a body with variation of temperature from finite element analysis model. Also, the criteria of hypothermia was discussed through result of finite element analysis.

• Korean Journal of Remote Sensing
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• v.22 no.6
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• pp.581-593
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• 2006

Various geological thematic maps have been generated by interpolating sparsely sampled ground survey data and geostatistical kriging that can consider spatial correlation between neighboring data has widely been used. This paper applies multi-variate geostatistical algorithms to integrate secondary information with sparsely sampled ground survey data for geological thematic mapping. Simple kriging with local means and kriging with an external drift are applied among several multi-variate geostatistical algorithms. Two case studies for spatial mapping of groundwater level and grain size have been carried out to illustrate the effectiveness of multi-variate geostatistical algorithms. A digital elevation model and IKONOS remote sensing imagery were used as secondary information in two case studies. Two multi-variate geostatistical algorithms, which can account for both spatial correlation of neighboring data and secondary data, showed smaller prediction errors and more local variations than those of ordinary kriging and linear regression. The benefit of applying the multi-variate geostatistical algorithms, however, depends on sampling density, magnitudes of correlation between primary and secondary data, and spatial correlation of primary data. As a result, the experiment for spatial mapping of grain size in which the effects of those factors were dominant showed that the effect of using the secondary data was relatively small than the experiment for spatial mapping of groundwater level.

• Journal of Advanced Navigation Technology
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• v.22 no.6
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• pp.602-609
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• 2018

Differential GPS (DGPS) is known as a positioning method using pseudo range correction (PRC) which is communicating between a refence receiver and moving receivers. In real world, a moving receiver loses communication with the reference receiver, resulting in loss of PRC real-time communication. In this paper, we assume that the transmission of the pseudo range correction isinterrupted in the middle of real-time positioning situations, in which calibration information is received in the DGPS method. Under the disconnected communication, we propose 'predict DGPS' that real-time virtual PRC model which is modeled by a machine learning algorithm with previously acquired PRC data from a reference receiver. To verify predict DGPS method, we compared and analyzed positioning solutions acquired from real PRC and the virtual PRC. In addition, we show that positioning using the DGPS prediction method on a real road can provide an improved positioning solution assuming a scenario in which PRC communication was cut off.

• Korean Journal of Agricultural and Forest Meteorology
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• v.23 no.4
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• pp.391-404
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• 2021

This study developed a long-term prediction model for the potential yield of garlic based on a genetic algorithm (GA) by utilizing global climate reanalysis data. The GA is used for digging the inherent signals from global climate reanalysis data which are both directly and indirectly connected with the garlic yield potential. Our results indicate that both deterministic and probabilistic forecasts reasonably capture the inter-annual variability of crop yields with temporal correlation coefficients significant at 99% confidence level and superior categorical forecast skill with a hit rate of 93.3% for 2 × 2 and 73.3% for 3 × 3 contingency tables. Furthermore, the GA method, which considers linear and non-linear relationships between predictors and predictands, shows superiority of forecast skill in terms of both stability and skill scores compared with linear method. Since our result can predict the potential yield before the start of farming, it is expected to help establish a long-term plan to stabilize the demand and price of agricultural products and prepare countermeasures for possible problems in advance.

• Journal of the Korean Association of Geographic Information Studies
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• v.27 no.2
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• pp.61-77
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• 2024

The purpose of this study was to develop a method for rapidly diagnosing urban thermal comfort using Unmanned Aerial Vehicle (UAV) based data. The research was conducted at Changwon National University's College of Engineering site and Yongji Park, both located in Changwon, Gyeongsangnam-do. Baseline data were collected using field measurements and UAVs. Specifically, the study calculated field measurement-based thermal comfort indices PET and UTCI, and used UAVs to create and analyze vegetation index (NDVI), sky view factor (SVF), and land surface temperature (LST) images. The results showed that UAV-predicted PET and UTCI had high correlations of 0.662 and 0.721, respectively, within a 1% significance level. The explanatory power of the prediction model was 43.8% for PET and 52.6% for UTCI, with RMSE values of 6.32℃ for PET and 3.16℃ for UTCI, indicating that UTCI is more suitable for UAV-based thermal comfort evaluation. The developed method offers significant time-saving advantages over traditional approaches and can be utilized for real-time urban thermal comfort assessment and mitigation planning

• Journal of Internet of Things and Convergence
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• v.10 no.4
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• pp.101-108
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• 2024

Indoor localization is a critical component for numerous applications, ranging from navigation in large buildings to emergency response. This paper presents an enhanced Pedestrian Dead Reckoning (PDR) scheme using smartphone sensors, integrating neural network-aided motion recognition, Kalman filter-based error correction, and multi-sensor data fusion. The proposed system leverages data from the accelerometer, magnetometer, gyroscope, and barometer to accurately estimate a user's position and orientation. A neural network processes sensor data to classify motion modes and provide real-time adjustments to stride length and heading calculations. The Kalman filter further refines these estimates, reducing cumulative errors and drift. Experimental results, collected using a smartphone across various floors of University, demonstrate the scheme's ability to accurately track vertical movements and changes in heading direction. Comparative analyses show that the proposed CNN-LSTM model outperforms conventional CNN and Deep CNN models in angle prediction. Additionally, the integration of barometric pressure data enables precise floor level detection, enhancing the system's robustness in multi-story environments. Proposed comprehensive approach significantly improves the accuracy and reliability of indoor localization, making it viable for real-world applications.

• Research in Plant Disease
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• v.17 no.3
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• pp.317-325
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• 2011

Bacterial pustule of soybean (Glycine max) caused by Xanthomonas axonopodis pv. glycines is one of the most prevalent bacterial diseases of soybean in Korea, where it causes considerable yield loss. This study was carried out to develop yield prediction model for bacterial pustule by analyzing correlation between the percentage of diseased leaf area and yield. The severe disease incidence of soybean bacterial pustule caused yield losses by 19.8% in 2006 and 16.8% in 2007, respectively. Severity of bacterial pustule greatly affected on 100 seed weight and yield, but did not on stem length, number of branches per plant, number of pods per plant, number of seeds per plant. On the other hand, correlation coefficients between diseased leaf area and yield were $-0.93^*$('06) and $-0.77^*$('07), respectively. The regression equation obtained by analyzing correlation between the percentage of diseased leaf area and yield loss in 2006 and in 2007 was y = -3.2914x + 348.19($R^2$ = 0.8603) and y = -2.9671x + 302.08($R^2$ = 0.9411), respectively. These results will be helpful in estimating losses on a field-scale and thereby predicting the production of soybean.

• Journal of KIISE:Software and Applications
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• v.36 no.9
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• pp.691-696
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• 2009

Introduction: There are two types of asthma according to aspirin hypersensitivity: aspirin intolerant asthma (AIA) and aspirin tolerant asthma (ATA). The genetic risk factors that are related with asthma have been investigated intensively and extensively. However the combinatory effects of single nucleotide polymorphisms (SNPs) have hardly been evaluated. In this paper we searched the best set of SNPs that are useful to diagnose the two types of asthma. Methods: We examined 246 asthmatic patients (94 having aspirin intolerant asthma and 152 having aspirin tolerant asthma) and analyzed 25 SNPs typed in them, which are suspected to be associated with asthma. Normalized mutual information values of combinations of typed SNPs are calculated, and those with high normalized mutual information values are selected. We use support vector machines to evaluate the prediction accuracy of the selected combinations. Results: The best combination model turns out four-locus and consists of ALOX5_p1_1708, B2ADR_q1_46, CCR3_p1_520, CysLTR1_p1_634. Its normalized mutual information value is 0.053 and the accuracy in predicting ATA disease risk among asthmatic patients is 71.14%.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.35 no.2
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• pp.307-318
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• 2015

In this study, the efficiency of two-dimensional inundation analysis using road network was demonstrated in order to reduce the simulation time of numerical model in urban area. For this objective, three simulation conditions were set up: Case 1 considered only inundation within road zone, while Case 2 and 3 considered inundation within road and building zone together. Accordingly, Case 1 used grids generated based on road network, while Case 2 and 3 used uniform and non-uniform grids for whole study area, respectively. Three simulation conditions were applied to Samsung drainage where flood damage occurred due to storm event on Sep. 21, 2010. The efficiency of suggested method in this study was verified by comparison the accuracy and simulation time of Case 1 and those of Case 2 and 3. The results presented that the simulation time was fast in the order of Case 1, 2 and 3, and the fit of inundation area between each case was more than 85% within road zone. Additionally, inundation area of building zone estimated from inundation rating index gave a similar agreement under each case. As a result, it is helpful for study on real-time inundation forecast warning to use a proposed method based on road network and inundation rating index for building zone.