• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.17 no.4
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• pp.321-330
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• 1999

Automation of observation and positioning of fiducial marks is made possible with the application of image matching technique, developed through the cooperative research effort of computer vision and digital photogrammetry. The major problem in such automation effort is to minimize the computing time and to increase the positional accuracy. Except for scanning and ground control surveying, the interior orientation process was automated in this study, through the development of an algorithm which applies the image matching and image processing techniques. The developed system was applied to close-range photogrammetry and the analysis of the results showed 54% improvement in processing time. For fiducial mark observation during interior orientation, the Laplacian of Gaussian transformation and the Hough transformation were applied to determine the accurate position of the center point, and the correlation matching and the least squares matching method were then applied to improve the accuracy of automated observation of fiducial marks. Image pyramid concept was applied to reduce the computing time of automated positioning of fiducial mark.

• Journal of Institute of Control, Robotics and Systems
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• v.14 no.9
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• pp.916-924
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• 2008

In this paper dynamic modeling parameters were estimated using a frequency domain estimation method. A systematic flight test method was employed using preprogrammed multistep excitation of the swashplate control input. In addition when one axis is excited, the autopilot is engaged in the other axis, thereby obtaining high-quality flight data. A dynamic model was derived for a small scale unmanned helicopter (CNUHELI-020, developed by Chungnam National University) equipped with a Bell-Hiller stabilizer bar. Six degree of freedom equations of motion were derived using the total forces and moments acting on the small scale helicopter. The dynamics of the main rotor is simplified by the first order tip-path plane, and the aerodynamic effects of fuselage, tail rotor, engine, and horizontal/vertical stabilizer were considered. Trim analysis and linearized model were used as a basic model for the parameter estimation. Doublet and multistep inputs are used to excite dynamic motions of the helicopter. The system and input matrices were estimated in the frequency domain using the equation error method in order to match the data of flight test with those of the dynamic modeling. The dynamic modeling and the flight test show similar time responses, which validates the consequence of analytic modeling and the procedures of parameter estimation.

• Journal of Biomedical Engineering Research
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• v.40 no.3
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• pp.97-104
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• 2019

To examine different types of influenza diagnostic test kits automatically, automated rapid influenza diagnostic test method based on image recognition is proposed in this paper. First, the proposed methods classify a variety of the rapid influenza diagnostic test kit based on support vector machine that analyzes the kits' feature point. Then, to improve the accuracy of test, the proposed methods match the histogram of both the target image of influenza kit and the input image of influenza kit for minimizing the effect of environment factors, such as lighting and exposure variations. And, to minimize the effect from composition of the hand-helds devices, the proposed methods extract the feature point and match point-by-point between target image of influenza kit and input image of influenza kit. Experimental results of 124 experimental group show that the proposed methods significantly have effectiveness, which shows 90% accuracy in moderate antigen, for the preliminary examination of influenza, and provides the opportunity for taking action against influenza.

• Journal of Animal Science and Technology
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• v.64 no.1
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• pp.155-165
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• 2022

As pork consumption increases, rapid and accurate determination of porcine carcass grades at abattoirs has become important. Non-destructive, automated inspection methods have improved slaughter efficiency in abattoirs. Furthermore, the development of a calibration equation suitable for non-destructive inspection of domestic pig breeds may lead to rapid determination of pig carcass and more objective pork grading judgement. In order to increase the efficiency of pig slaughter, the correct estimation of the automated-method that can accommodate the existing pig carcass judgement should be made. In this study, the previously developed calibration equation was verified to confirm whether the estimated traits accord with the actual measured traits of pig carcass. A total of 1,069,019 pigs, to which the developed calibration equation, was applied were used in the study and the optimal estimated regression equation for actual measured two traits (backfat thickness and hot carcass weight) was proposed using the estimated traits. The accuracy of backfat thickness and hot carcass weight traits in the estimated regression models through stepwise regression analysis was 0.840 (R²) and 0.980 (R²), respectively. By comparing the actually measured traits with the estimated traits, we proposed optimal estimated regression equation for the two measured traits, which we expect will be a cornerstone for the Korean porcine carcass grading system.

• ETRI Journal
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• v.45 no.1
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• pp.105-118
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• 2023

We tested the feasibility of automated discrimination of patients with panic disorder (PD) from healthy controls (HCs) based on multimodal physiological responses using machine learning. Electrocardiogram (ECG), electrodermal activity (EDA), respiration (RESP), and peripheral temperature (PT) of the participants were measured during three experimental phases: rest, stress, and recovery. Eleven physiological features were extracted from each phase and used as input data. Logistic regression (LoR), k-nearest neighbor (KNN), support vector machine (SVM), random forest (RF), and multilayer perceptron (MLP) algorithms were implemented with nested cross-validation. Linear regression analysis showed that ECG and PT features obtained in the stress and recovery phases were significant predictors of PD. We achieved the highest accuracy (75.61%) with MLP using all 33 features. With the exception of MLP, applying the significant predictors led to a higher accuracy than using 24 ECG features. These results suggest that combining multimodal physiological signals measured during various states of autonomic arousal has the potential to differentiate patients with PD from HCs.

• Journal of Platform Technology
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• v.11 no.6
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• pp.13-20
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• 2023

Regularly inspecting vehicle tires' condition is imperative for driving safety and comfort. Poorly maintained tires can pose fatal risks, leading to accidents. Unfortunately, manual tire visual inspections are often considered no less laborious than employing an automatic tire inspection system. Nevertheless, an automated tire inspection method can significantly enhance driver compliance and awareness, encouraging routine checks. Therefore, there is an urgency for automated tire inspection solutions. Here, we focus on developing a deep learning (DL) model to predict cracked tires. The main idea of this study is to demonstrate the comparative analysis of DenseNet121, VGG-19 and EfficientNet Convolution Neural Network-based (CNN) Transfer Learning (TL) and suggest which model is more recommended for cracked tire classification tasks. To measure the model's effectiveness, we experimented using a publicly accessible dataset of 1028 images categorized into two classes. Our experimental results obtain good performance in terms of accuracy, with 0.9515. This shows that the model is reliable even though it works on a dataset of tire images which are characterized by homogeneous color intensity.

• Design & Manufacturing
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• v.12 no.2
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• pp.11-15
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• 2018

In this study, we proposed three analysis methods to calculate the flatness of torque-angle sensors (TAS). We introduced two statistical and one geometrical methods in evaluating the precision of the flat plane in the axis direction for TAS. To verified the results, we fabricated TAS and a reference sample using a injection molding machine, mold, polyester as a raw material. We measured ($x_i$, $y_i$) position using 3D contact automated system and applied three analysis methods developed for TAS and a reference sample to see the feasibility. While each analysis method has its own pros and cons, the analysis using the shortest optimal distance was the most precise technique for the flatness evaluation of TAS components.

• Journal of Korean Society for Atmospheric Environment
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• v.21 no.4
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• pp.439-458
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• 2005

An automated analysis system for water soluble constituents in $PM_{2.5}$ has been developed. The system consists of a high capacity multi tube diffusion scrubber (MTDS), a low temperature particle impactor (LTPI), and two ion (anion and cation) chromatography (IC) systems. Atmospheric particles have been collected by passing sample air through a thermostated MTDS followed by a LTPI. This system allows simultaneous measurements of soluble ions in $PM_{2.5}$ at 30 minutes interval. At the air sampling flow rate of 1.0L/min, the detection limits of the overall system are in the order of tens of $ng/m^3$. This system has been successfully used for the measurement of particulate components of Seoul air from April 2003 to January 2004. $SO_4^{2-},\;NO_3^-,\;NH_4^+,\;NO_2^-,\;Cl^-,\;Na^+,\;K^+,\;Ca^{2+},\;and\;Mg^{2+}$ are the major ionic species for $PM_{2.5}$ at Seoul. Among them, $SO_4^{2-},\;NO_3^-\;and\;NH_4^+$ are the most abundant ions, contributed up to $86\%$ of the total and the concentrations were higher than those in any other urban sites in the world except for Chinese cities. There are high pollutant episodes which contribute about $15\~20\%$ of annual average values of the major ions. During the episode, the all parcels were transported from the asian continent and $PM_{2.5}$ were significantly neutralized. This suggests that aged and long range transported pollutants caused the high pollutant episodes. They showed a distinct daily and seasonal variations:they showed a peak in the early morning caused by the night-time accumulation of particulate matters. Atmospheric reactions including gas-to-particle reactions and inter-particle reactions and meteorological parameters including relative humidity and ambient temperature were described with related to the $PM_{2.5}$ 5 concentrations. All of the ionic species showed higher concentrations during the spring than those for summer and winter.

• Transactions of the Korean Society for Noise and Vibration Engineering
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• v.12 no.12
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• pp.986-993
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• 2002

The equations of motion for an automated guide-way transit(AGT) system running on a path with roughness have been derived to investigate dynamic responses and wheel loads of moving vehicles of the AGT system. A vehicle of the AGT system is idealized as three-dimensional model with 11 degree-of-freedom. The computer program is developed to solve the dynamic equations, and anlatical results are verified by comparing the results with experimental oness. Parametric studies are carried out to investigate the dynamic responses of an AGT vehicle according to vehicle speeds, surface roughness, damping and stiffness of suspension systems. The parametric study demonstrates that amplitudes of dynamic responses and the wheel loads have a tendency to increase according to travel speeds, the stiffness of suspension system and surface roughness. On the other hand. those amplitudes tend to decrease according to increase of damping of the suspension system.

• Nuclear Engineering and Technology
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• v.49 no.2
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• pp.335-341
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• 2017

The main control room (MCR) in advanced nuclear power plants (NPPs) has changed from analog to digital control system (DCS). Operation and control have become more automated, centralized, and accurate due to the digitalization of NPPs, which has improved the efficiency and security of the system. New issues associated with human reliability inevitably arise due to the adoption of new accident procedures and digitalization of main control rooms in NPPs. The LingAo II NPP is the first digital NPP in China to apply the state-oriented procedure. In order to address issues related to human reliability analysis for DCS and DCS + state-oriented procedure, the Hunan Institute of Technology conducted a research project based on a cooperative agreement with the LingDong Nuclear Power Co. Ltd. This paper is a brief introduction to the project.