• Korean Journal of Air-Conditioning and Refrigeration Engineering
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• v.15 no.6
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• pp.533-542
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• 2003

This study aims to propose a simplified mathematical model for calculating vertical air temperature distribution in a four-sided atrium. In the first stage of the mathematical modeling, the computer model combined zonal model and solar radiation model using Monte Carlo method and Ray tracing technique went through a computer simulation with architectural variables applied to a four-sided atrium in summer. In the next stage, Curve Expert, a computer program that gets the most suitable solution ac-cording to the least squares method, is used to analyze the results of the computer simulation and to derive the mathematical model. The accuracy of the mathematical model was evaluated through a comparison of calculation results from a mathematical model and computer simulation. In this validation step using the least square method, the R2 value of the Zones 1, 2 and 3 showed higher than 0.945. Zone 4 has an R2 value of 0.911, lower than the previous three zones. However the relative error was below 0.5%, which is considered very small.

• Journal of Biomedical Engineering Research
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• v.28 no.6
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• pp.713-720
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• 2007

In image-guided surgery, automatic bone segmentation of Computed Tomography (CT) images is an important but challenging step. Previous attempts include intensity-, edge-, region-, and deformable curve-based approaches [1], but none claims fully satisfactory performance. Although active contour (AC) techniques possess many excellent characteristics, their applications in CT image segmentation have not worthily exploited yet. In this study, we have evaluated the automaticity and performance of the model of Chan-Vese Multiphase AC Without Edges towards knee bone segmentation from CT images. This model is suitable because it is initialization-insensitive and topology-adaptive. Its segmentation results have been qualitatively compared with those from four other widely used AC models: namely Gradient Vector Flow (GVF) AC, Geometric AC, Geodesic AC, and GVF Fast Geometric AC. To quantitatively evaluate its performance, the results from a commercial software and a medical expert have been used. The evaluation results show that the Chan-Vese model provides superior performance with least user interaction, proving its suitability for automatic bone segmentation from CT images.

• Proceedings of the KIEE Conference
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• 2003.04a
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• pp.179-181
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• 2003

Conventional P/PI speed controller of today's servo drives should be manually tuned the controller switching set-point by trial-and-errors, which may translate the drive system down-time and loss of productivity. The adjustable drive performance is heavily dependent on the qualify of the expert knowledge and becomes inadequate in applications where the operating conditions change in a wide range, i.e., tracking command, cceleration/deceleration time, and load disturbances. In this paper, the demands on simple controls/setup are discussed for industry servo drives. Analyzing the frequency content of motor torque command, P/PI control mode switching is automatically peformed with some prior knowledge of the mechanical dynamics. The dynamic performance of the proposed scheme assures a desired tracking response curve with minimal oscillation and settling time over the whole operating conditions. For comprehensive comparison of traditional P/PI control scheme, extensive test is carried out on actual servo system.

• Journal of Construction Engineering and Project Management
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• v.7 no.2
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• pp.34-44
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• 2017

The use of Unmanned Aircraft Systems (UASs) in the construction and agriculture industries continues to gain in popularity and use. Firms within these industries have begun to utilize UASs to perform many of the traditional processes and procedures, which can result in a reduction in total work force and costs needed for a task. However, as with any technology, there is a learning curve and UASs do change the way certain activities are completed. Due to this, there exist firms and individuals that have not or are not willing to invest in UASs yet. The objective of this study is to explore the applications of UASs in construction and agricultural industries to discuss the benefits, challenges, and reasons of investing in UASs. This paper conducted an in-depth literature review of current topics on UASs in construction and agriculture. Additionally, six expert interviews were conducted with individuals from construction and agricultural industries in the southeastern United States. Ultimately, this study successfully found several benefits and challenges to using UASs and discussed the reasons that some firms invest in UASs while other still do not.

• ETRI Journal
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• v.39 no.5
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• pp.662-671
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• 2017

Coronary artery disease (CAD) is a major cause of death in the world. As a non-invasive imaging modality, computed tomography angiography (CTA) is now usually used in clinical practice for CAD diagnosis. Precise quantification of coronary stenosis is of great interest for diagnosis and treatment planning. In this paper, a novel cluster method based on a Modified Student's t-Mixture Model is applied to separate the region of vessel lumen from other tissues. Then, the area of the vessel lumen in each slice is computed and the estimated value of it is fitted with a curve. Finally, the location and the level of the most stenoses are captured by comparing the calculated and fitted areas of the vessel. The proposed method has been applied to 17 clinical CTA datasets and the results have been compared with reference standard degrees of stenosis defined by an expert. The results of the experiment indicate that the proposed method can accurately quantify the stenosis of the coronary artery in CTA.

• Proceedings of the Korean Society of Computer Information Conference
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• 2022.07a
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• pp.57-58
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• 2022

Sleep apnea (SA) is a common chronic sleep disorder that disrupts breathing during sleep. Clinically, the standard for diagnosing SA involves nocturnal polysomnography (PSG). However, this requires expert human intervention and considerable time, which limits the availability of SA diagnoses in public health sectors. Therefore, ECG-based methods for SA detection have been proposed to automate the PSG procedure and reduce its discomfort. We propose a preprocessing method to convert the one-dimensional time series of ECG into two-dimensional images using the Gramian Angular Field (GAF) algorithm, extract temporal features, and use a two-dimensional convolutional neural network for classification. The results of this study demonstrated that the proposed method can perform SA detection with specificity, sensitivity, accuracy, and area under the curve (AUC) of 88.89%, 81.50%, 86.11%, and 0.85, respectively. Our experimental results show that SA is successfully classified by extracting preprocessing transforms with temporal features.

• Journal of Bio-Environment Control
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• v.30 no.1
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• pp.27-36
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• 2021

A capacitive water sensor was developed to measure the capacitance over a wide part of a substrate using an insulated electrode plate (30 cm × 10 cm) with copper and Teflon attached on either side of the substrate. This study aimed to convert the capacitance output obtained from the condenser-type capacitance sensor into the substrate water content. The quantification experiment was performed by measuring the changes in substrate water weight and capacitance while providing a nutrient solution and by subsequently comparing these values. The substrate water weight and capacitance were measured every 20 to 30 seconds using the sensor and load cell with a software developed specifically for this study. Using a curve-fitting program, the substrate water content was estimated from the output of the capacitance using the water weight and capacitance of the substrate as variables. When the amount of water supplied was increased, the capacitance tended to increase. Coefficient of variation (CV) in capacitance according to the water weight in substrate was greater with the 1.0 kg of water weight, compared with other weights. Thus, the fitting was performed with higher than 1.0 kg, from 1.7 to 6.0 kg of water weight. The correlation coefficient between the capacitance and water weight in substrate was 0.9696. The calibration equation estimated water content from the capacitance, and it was compared with the substrate water weight measured by the load cell.

• Journal of the Korean Society of Safety
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• v.35 no.1
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• pp.1-11
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• 2020

Article 325 (Prevention of Fire Explosion due to Electrostatic) of the Rule for Occupational Safety and Health Standard specifies that in order to prevent the risk of disasters caused by static electricity, fire, explosion and static electricity in the production process, However, in order to do this, it is absolutely necessary to use a pre-detection technology and a detector for antistatic discharge prediction, which is a precautionary measure by static electricity in a fire / explosion hazard place, but in Korea, And there is no technical standard for the application of the technology of the explosion proof structure of the related equipment. Research methods include domestic and overseas electrostatic discharge detection technology and literature investigation of related equipment explosion proofing technology, domestic and foreign electrostatic discharge detection device production and use situation investigation, advanced foreign technology data analysis and benchmarking. In particular, we sought to verify the results of empirical experiments using electrostatic discharge detection technology through sample purchase and analysis of related major products, development of optimization technology through prototype production, evaluation, and supplementation, and expert knowledge through expert consultation. The results of this study were developed and fabricated two prototypes of electrostatic discharge detector based on the technology / standard related to electrostatic discharge detection technology in Korea and abroad through development of electrostatic discharge detection technology and development and production of detector. In addition, based on the development of electrostatic discharge detection technology, we developed an intrinsic safety explosion proof ib class explosion proof technology applicable to the process of using and handling flammable gas and flammable liquid vapor and combustible dust. In the case of the over voltage and minimum voltage are supplied to the explosion-proof structure ESD detector, check the state of the circuit and the transient and transient currents generated by the coil and capacitor elements during the input and standby of the signal pulse voltage. Explosion-proof equipment-Part 11: Intrinsically safe explosion proof structure The comparative evaluation with the reference curve in Annex A of "i" confirms that the characteristics of the intrinsically safe explosion protection structure are met.

• Journal of Intelligence and Information Systems
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• v.21 no.4
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• pp.17-35
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• 2015

Demand forecasting is the activity of estimating the quantity of a product or service that consumers will purchase for a certain period of time. Developing precise forecasting models are considered important since corporates can make strategic decisions on new markets based on future demand estimated by the models. Many studies have developed market growth curve models, such as Bass, Logistic, Gompertz models, which estimate future demand when a market is in its early stage. Among the models, Bass model, which explains the demand from two types of adopters, innovators and imitators, has been widely used in forecasting. Such models require sufficient demand observations to ensure qualified results. In the beginning of a new market, however, observations are not sufficient for the models to precisely estimate the market's future demand. For this reason, as an alternative, demands guessed from those of most adjacent markets are often used as references in such cases. Reference markets can be those whose products are developed with the same categorical technologies. A market's demand may be expected to have the similar pattern with that of a reference market in case the adoption pattern of a product in the market is determined mainly by the technology related to the product. However, such processes may not always ensure pleasing results because the similarity between markets depends on intuition and/or experience. There are two major drawbacks that human experts cannot effectively handle in this approach. One is the abundance of candidate reference markets to consider, and the other is the difficulty in calculating the similarity between markets. First, there can be too many markets to consider in selecting reference markets. Mostly, markets in the same category in an industrial hierarchy can be reference markets because they are usually based on the similar technologies. However, markets can be classified into different categories even if they are based on the same generic technologies. Therefore, markets in other categories also need to be considered as potential candidates. Next, even domain experts cannot consistently calculate the similarity between markets with their own qualitative standards. The inconsistency implies missing adjacent reference markets, which may lead to the imprecise estimation of future demand. Even though there are no missing reference markets, the new market's parameters can be hardly estimated from the reference markets without quantitative standards. For this reason, this study proposes a case-based expert system that helps experts overcome the drawbacks in discovering referential markets. First, this study proposes the use of Euclidean distance measure to calculate the similarity between markets. Based on their similarities, markets are grouped into clusters. Then, missing markets with the characteristics of the cluster are searched for. Potential candidate reference markets are extracted and recommended to users. After the iteration of these steps, definite reference markets are determined according to the user's selection among those candidates. Then, finally, the new market's parameters are estimated from the reference markets. For this procedure, two techniques are used in the model. One is clustering data mining technique, and the other content-based filtering of recommender systems. The proposed system implemented with those techniques can determine the most adjacent markets based on whether a user accepts candidate markets. Experiments were conducted to validate the usefulness of the system with five ICT experts involved. In the experiments, the experts were given the list of 16 ICT markets whose parameters to be estimated. For each of the markets, the experts estimated its parameters of growth curve models with intuition at first, and then with the system. The comparison of the experiments results show that the estimated parameters are closer when they use the system in comparison with the results when they guessed them without the system.

• Asian Pacific Journal of Cancer Prevention
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• v.17 no.3
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• pp.1493-1498
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• 2016

Background: Breast cancer is the most common cancer in women worldwide with a rising incidence rate in most countries. Considering the increase in life expectancy and change in lifestyle of Iranian women, this study investigated the age-adjusted trend of breast cancer incidence during 2000-2009 and predicted its incidence to 2020. Materials and Methods: The 1997 and 2006 census results were used for the projection of female population by age through the cohort-component method over the studied years. Data from the Iranian cancer registration system were used to calculate the annual incidence rate of breast cancer. The age-adjusted incidence rate was then calculated using the WHO standard population distribution. The five-year-age-specific incidence rates were also obtained for each year and future incidence was determined using the trend analysis method. Annual percentage change (APC) was calculated through the joinpoint regression method. Results: The bias adjusted incidence rate of breast cancer increased from 16.7 per 100,000 women in 2000 to 33.6 per 100,000 women in 2009. The incidence of breast cancer had a growing trend in almost all age groups above 30 years over the studied years. In this period, the age groups of 45-65 years had the highest incidence. Investigation into the joinpoint curve showed that the curve had a steep slope with an APC of 23.4% before the first joinpoint, but became milder after this. From 2005 to 2009, the APC was calculated as 2.7%, through which the incidence of breast cancer in 2020 was predicted as 63.0 per 100,000 women. Conclusions: The age-adjusted incidence rate of breast cancer continues to increas in Iranian women. It is predicted that this trend will continue until 2020. Therefore, it seems necessary to prioritize the prevention, control and care for breast cancer in Iran.