• Journal of the Korean Society for Precision Engineering
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• v.19 no.3
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• pp.152-159
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• 2002

SLA (Stereolithography Apparatus) it a process used to rapidly produce polymer components directly from a computer representation of the part. Though SLA is being recognized as an innovative technology, it still cannot be used to fully practical application since it lacks of dimensional accuracy compared to conventional process. If the shrinkage were perfectly uniform and no distortion took place, excellent part accuracy could still be achieved through and appropriate scaling factor when generating the build file. However, in certain geometries involving intersecting thick and thin sections, nonuniform retrain shrinkage becomes the engine of part distortion. In order to improve the part accuracy of SLA, this paper evaluates how largely each parameter of SLA contributes to the part accuracy and estimates the optimal set of parameter which minimizes the dimension error of the test part, "Slab (100mm$\times$100mm$\times$2mm)"and "scale bar"part. Three control parameters such as critical exposure, generation depth and fill cure depth are used.

• Journal of Multimedia Information System
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• v.3 no.2
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• pp.35-42
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• 2016

Electrocardiogram (ECG) signal gives a clear indication whether the heart is at a healthy status or not as the early notification of a cardiac problem in the heart could save the patient's life. Several methods were launched to clarify how to diagnose the abnormality over the ECG signal waves. However, some of them face the problem of lack of accuracy at diagnosis phase of their work. In this research, we present an accurate and successive method for the diagnosis of abnormality through Discrete Wavelet Transform (DWT), QRS complex detection and Support Vector Machines (SVM) classification with overall accuracy rate 95.26%. DWT Refers to sampling any kind of discrete wavelet transform, while SVM is known as a model with related learning algorithm, which is based on supervised learning that perform regression analysis and classification over the data sample. We have tested the ECG signals for 10 patients from different file formats collected from PhysioNet database to observe accuracy level for each patient who needs ECG data to be processed. The results will be presented, in terms of accuracy that ranged from 92.1% to 97.6% and diagnosis status that is classified as either normal or abnormal factors.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.68 no.3
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• pp.471-479
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• 2019

This research proposes a indoor magnetic map matching algorithm that improves the position accuracy by employing multiple magnetic sensors and probabilistic candidate weighting function. Since the magnetic field is easily distorted by the surrounding environment, the distorted magnetic field can be used for position mapping, and multiple sensor configuration is useful to improve mapping accuracy. Nevertheless, the position error is likely to increase because the external magnetic disturbances have repeated pattern in indoor environment and several points have similar magnetic field distortion characteristics. Those errors cause large position error, which reduces the accuracy of the position detection. In order to solve this problem, we propose a method to reduce the error using multiple sensors and likelihood boundaries that uses human walking characteristics. Also, to reduce the maximum position error, we propose an algorithm that weights according to their importance. We performed indoor walking tests to evaluate the performance of the algorithm and analyzed the position detection error rate and maximum distance error. From the results we can confirm that the accuracy of position detection is greatly improved.

• Current Optics and Photonics
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• v.4 no.6
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• pp.500-508
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• 2020

The rifling angle of artillery is an important parameter, and its determination plays a key role in the stability, hit rate, accuracy and service life of artillery. In this study, we propose an optical measurement method for the rifling angle based on angle error correction. The method is based on the principle of geometrical optics imaging, where the rifling on the inner wall of the artillery barrel is imaged on a CCD camera target surface by an optical system. When the measurement system moves in the barrel, the rifling image rotates accordingly. According to the relationship between the rotation angle of the rifling image and the travel distance of the measurement system, different types of rifling equations are established. Solving equations of the rifling angle are deduced according to the definition of the rifling angle. Furthermore, we added an angle error correction function to the method that is based on the theory of dynamic optics. This function can measure and correct the angle error caused by the posture change of the measurement system. Thus, the rifling angle measurement accuracy is effectively improved. Finally, we simulated and analyzed the influence of parameter changes of the measurement system on rifling angle measurement accuracy. The simulation results show that the rifling angle measurement method has high measurement accuracy, and the method can be applied to different types of rifling angle measurements. The method provides the theoretical basis for the development of a high-precision rifling measurement system in the future.

• Journal of the Korean Society of Clothing and Textiles
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• v.47 no.1
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• pp.137-151
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• 2023

Stationary 3D whole-body scanners generally require 5 to 20 seconds of scanning time and cannot effectively detect armpit and crotch areas. Therefore, this study aimed to analyze the accuracy of a photogrammetric technique using a multi-camera system. First, dimensional accuracy was analyzed using a mannequin scan, comparing the differences between the scan-derived measurements and the direct measurements, with an allowable tolerance of ISO 20685-1:2018. Only 2 of 59 measurement items (ankle height and upper arm circumference, specifically) exceeded the ISO 20685-1:2018 criteria. When compared with the results of the eight stationary whole-body scanners assessed by the literature, the photogrammetric technique was found to have the advantage of scanning the top of the head, armpit, and crotch areas clearly. Second, this study found the photogrammetric technique is suitable for obtaining the body scans because it can minimize the perform scanning, resulting in a reduction of measurement errors due to breathing and uncontrolled movements. The error rate of the photogrammetry method was much lower than that of stationary 3D whole-body scanners.

• International Journal of Computer Science & Network Security
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• v.24 no.2
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• pp.196-202
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• 2024

Currently, the second most devastating form of cancer in people, particularly in women, is Breast Cancer (BC). In the healthcare industry, Machine Learning (ML) is commonly employed in fatal disease prediction. Due to breast cancer's favorable prognosis at an early stage, a model is created to utilize the Dataset on Wisconsin Diagnostic Breast Cancer (WDBC). Conversely, this model's overarching axiom is to compare the effectiveness of five well-known ML classifiers, including Logistic Regression (LR), Decision Tree (DT), Random Forest (RF), K-Nearest Neighbor (KNN), and Naive Bayes (NB) with the conventional method. To counterbalance the effect with conventional methods, the overarching tactic we utilized was hyperparameter tuning utilizing the grid search method, which improved accuracy, secondary precision, third recall, and finally the F1 score. In this study hyperparameter tuning model, the rate of accuracy increased from 94.15% to 98.83% whereas the accuracy of the conventional method increased from 93.56% to 97.08%. According to this investigation, KNN outperformed all other classifiers in terms of accuracy, achieving a score of 98.83%. In conclusion, our study shows that KNN works well with the hyper-tuning method. These analyses show that this study prediction approach is useful in prognosticating women with breast cancer with a viable performance and more accurate findings when compared to the conventional approach.

• Current Optics and Photonics
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• v.8 no.3
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• pp.246-258
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• 2024

In aerospace and energy engineering, the reconstruction of three-dimensional (3D) temperature distributions is crucial. Traditional methods like algebraic iterative reconstruction and filtered back-projection depend on voxel division for resolution. Our algorithm, blending deep learning with computer graphics rendering, converts 2D projections into light rays for uniform sampling, using a fully connected neural network to depict the 3D temperature field. Although effective in capturing internal details, it demands multiple cameras for varied angle projections, increasing cost and computational needs. We assess the impact of camera number on reconstruction accuracy and efficiency, conducting butane-flame simulations with different camera setups (6 to 18 cameras). The results show improved accuracy with more cameras, with 12 cameras achieving optimal computational efficiency (1.263) and low error rates. Verification experiments with 9, 12, and 15 cameras, using thermocouples, confirm that the 12-camera setup as the best, balancing efficiency and accuracy. This offers a feasible, cost-effective solution for real-world applications like engine testing and environmental monitoring, improving accuracy and resource management in temperature measurement.

• Proceedings of the KOSOMBE Conference
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• v.1998 no.11
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• pp.127-128
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• 1998

It is necessary to maintain constant intravenous (IV) infusion rate. While infusion pump is able to control infusion rate with great accuracy, its rather large size and weight make it difficult for patients to move around. The most commonly used infusion device is gravity IV infusion set with its administration chamber being clamped according to the observed drip rate. In this case it may be easier and more accurate to maintain IV rate to given value if we automate the drip-counting process and tube-clamping work by electronic devices. We calculated volume infusion rate of specific fluid using optical drip rate meter which we had developed. To regulate fluid flow rate, we equipped the rate meter which we had developed with a miniaturized clamping apparatus using DC motor. Also, we Implemented drip detection and clamp control algorithm with PIC16C73 $\mu$-controller (Microchip). This system provides user interface through LCD display and key buttons.

• Journal of the Korea Society of Computer and Information
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• v.16 no.1
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• pp.133-142
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• 2011

When TCP operates in multi-hop wireless networks, it suffers from severe performance degradation due to the different characteristics of wireless networks and wired networks. This is because TCP reacts to wireless packet losses by unnecessarily decreasing its sending rate assuming the losses as congestion losses. Although several loss differentiation algorithms (LDAs) have been proposed to avoid such performance degradation, their detection accuracies are not high as much as we expect. In addition the schemes have a tendency to sacrifice the detection accuracy of congestion losses while they improve the detection accuracy of wireless losses. In this paper, we suggest a new sender-based loss differentiation scheme which enhances the detection accuracy of wireless losses while minimizing the sacrifice of the detection accuracy of congestion losses. Our scheme estimates the rate of queue usage which is highly correlated with the congestion in the network path between a TCP sender and a receiver, and it distinguishes congestion losses from wireless losses by comparing the estimated queue usage with a certain threshold. In the extensive experiments based on a network simulator, QualNet, we measure and compare each detection accuracy of wireless losses and congestion losses, and evaluate the performance enhancement in each scheme. The results show that our scheme has the highest accuracy among the LDAs and it improves the most highly TCP performance in multi-hop wireless networks.

• The Journal of Korean Society for Radiation Therapy
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• v.33
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• pp.25-33
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• 2021

Purpose : The purpose of this study is to evaluate the accuracy and usefulness of the Trigger mode for the Respiratory Gated Radiation Therapy (RGRT) Materials and methods : A QUASAR respiratory phantom that inserted a 3 mm fiducial marker (a gold marker) was used to estimate the accuracy of the Trigger mode. And the 20 bpm was used as reference respiration rate in this study. The marker that placed at the center of the phantom was contoured, and the lower threshold of a gating window was fixed at 2.0 mm using an OBI with Truebeam STx^TM. The upper threshold was measured every 0.5 mm from 1.0 mm to 3.0 mm. The respiration rates were changed every 10 bpm from 10 bpm to 60 bpm. We repeatedly measured five times to check the error rate of the trigger mode in the same condition. Result : The differences of a distance from a peak phase to upper threshold, 1.0 to 3.0 mm at a 20 bpm as a reference for 3 days in a row were 0.68±0.05 mm, 0.91±0.03 mm, 1.23±0.03 mm, 1.42±0.04 mm, and 1.66±0.06 mm, respectively. Measurement result of changes in respiratory rate compared to baseline respiratory rate in maximum absolute difference. The coefficient of determination (R2) to estimate the correlation between the respiration velocity and variation of absolute difference was on average 0.838, 0.887, 0.770, 0.850, and 0.906. The p-values of all the variables were below 0.05. Conclusion : Using Trigger mode during respiratory gated radiation therapy (RGRT), accuracy and usefulness of trigger mode at reference breathing rate were confirmed. However, inaccuracies depending on the rate of breathing it could be uncertain in case of respiration rate is faster than 20 bpm as a standard respiration rate compared to slower than 20 bpm. Consequently, when conducting a RGRT using the trigger mode, real time monitoring is required with well educated respiration.