• 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.

• Journal of the Korean Society of Radiology
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• v.15 no.1
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• pp.85-91
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• 2021

The purpose of this study is to derive an equation to verify the accuracy of the dose rate for each component calculated at the measurement point outside the maze door when designing the maze door of 6 MV X-ray beam. Based on the component-specific dose rate calculation formula for the measurement point outside the maze door described in NCRP Report 151 and IAEA Safety Report Series 47, the dose rate calculation formula for each component when applying the values of the drawing-based parameters and the dose rate calculation formula for each component when applying the values of conservative parameters are derived. From the two dose rate calculation formulas for each component, the dose rate verification formula for each component at the measurement point outside the maze door was derived. The resulting dose rate verification formula for each component at the measurement point outside the maze door can be compared and analyzed whether the dose rate for each component at the measurement point outside the maze door calculated by the designer falls within the range of the dose rate obtained from the derived dose rate verification formula for each component. This verification formula is considered to be practically useful in verifying the accuracy of the dose rate for each component calculated by the designer.

• 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.

• Journal of Korea Multimedia Society
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• v.14 no.9
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• pp.1125-1137
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• 2011

Recently, there have been previous research about the iris recognition in mobile device to increase portability, whose accuracy is affected by the quality of iris image. Iris image is affected by illumination environment during the image acquisition. The existing system has high accuracy in indoor environment. However the accuracy is degraded in outdoor environment, because the gray levels of iris patterns in image are changed, and ghost and eyelash shading regions are produced by the sunlight of various wavelengths into iris region. To overcome these problems, we propose new mobile iris camera system which uses the near-infrared (NIR) light illuminator of 850 nm and band pass filter (BPF) of 850 nm. To measure the performance of the proposed system, we compared it to the existing one with the iris images captured in indoor and outdoor sunlight environments in terms of the equal error rates (EER) based on false acceptance rate (FAR) and false rejection rate (FRR). The experimental result showed that the proposed system had the lower EERs than those of previous system by 0.96% (with frontal light in indoors), 4.94% (with frontal light in outdoor), 9.24% (with side light in outdoor), and 7% (with back light in outdoor), respectively.

• Journal of the Korea Society of Computer and Information
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• v.17 no.1
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• pp.211-218
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• 2012

Fossil fuel is used all over the world and it produces greenhouse gases due to fossil fuel use. Therefore, it cause global warming and is serious environmental pollution. In order to decrease the environmental pollution, we should use renewable energy which is clean energy. Among several renewable energy, wind energy is the most promising one. Wind power generation is does not produce environmental pollution and could not be exhausted. However, due to wind power generation has irregular power output, it is important to predict generated electrical energy accurately for smoothing wind energy supply. There, we consider use ramp characteristic to forecast accurate wind power output. The ramp increase and decrease rapidly wind power generation during in a short time. Therefore, it can cause problem of unbalanced power supply and demand and get damaged wind turbine. In this paper, we make prediction models using power ramp rate as well as wind speed and wind direction to increase prediction accuracy. Prediction model construction algorithm used multilayer neural network. We built four prediction models with PRR, wind speed, and wind direction and then evaluated performance of prediction models. The predicted values, which is prediction model with all of attribute, is nearly to the observed values. Therefore, if we use PRR attribute, we can increase prediction accuracy of wind power generation.

• Journal of the Korean Association of Oral and Maxillofacial Surgeons
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• v.26 no.5
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• pp.462-469
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• 2000

Positron Emission Tomography(PET) is a new diagnostic method that can create functional images of the distribution of positron emitting radionuclides, which when administered intravenously in the body, makes possible anatomical and functional analysis by quantity of biochemical and physiological process. After genetic and biochemical changes in initial stage, malignant tumor undergoes functional changes before undergoing anatomical changes. So, early diagnosis of malignant tumors by functional analysis with PET can be achieved, replacing traditional anatomical analysis, such as computed tomography(CT) and magnetic resonance image(MRI), etc. Similarly, PET can identify malignant tumor without confusion with scar and fibrosis in follow up check. In the Korea Cancer Center Hospital(KCCH) from October 1997 to September 1999, clinical study was performed in 79 cases that underwent 89 times PET evaluation with [18F]-Fluorodeoxyglucose for diagnosis of oral and maxillofacial tumors, and the data was analysed by Bayesian $2{\times}2$ Classification Table. The results were as follows : Evaluation for initial diagnosis with FDG-PET (P<0.005) 1. Agreement rate or accuracy rate is 88.9%. 2. Sensitivity is 95.2%, and specificity 66.7%. 3. Positive predictive rate is 90.9%, and negative predictive rate 80.0%. 4. In consideration of tumor stage, diagnostic rate in less than stage II was 90% and in greater than stage III 100%. 5. In consideration of tumor size, diagnostic rate in less than T2 was 92.3% and in greater than T3 100%. After primary treatment, evaluation for follow up check with FDG-PET (P < 0.001) 1. Agreement rate or accuracy rate is 85.4%. 2. Sensitivity is 87.5%, and specificity 82.4%. 3. Positive predictive rate is 87.5%, and negative predictive rate 82.4%. 4. In 24 recurred cases, 6 had distant metastasis, and 5 of them were diagnosed with FDG-PET, resulting in diagnostic rate of FDG-PET of 83.3%. From the above results, Positron Emission Tomography with [18F]- Fluorodeoxyglucose appears to be more sensitive and accurate for detecting the presence of oral and maxillofacial tumors, and has various clinical applications such as early diagnosis of tumor in initial and follow up check and detection of distant metastasis.

• Science of Emotion and Sensibility
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• v.23 no.2
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• pp.51-60
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• 2020

This study aimed to develop a modular smart clothing system for heart rate monitoring that reduces the inconvenience caused by battery charging and the large size of measurement devices. The heart rate monitoring system was modularized into a temporary device and a continuous device to enable heart rate monitoring depending on the requirement. The temporary device with near-field communication (NFC) and heart rate sensors was developed as a clothing attachment type that enables heart rate monitoring via smart phone tagging when required. The continuous device is based on Bluetooth Low Energy (BLE) communication and batteries and was developed to enable continuous heart rate measurement via a direct connection to the temporary device. Furthermore, the temporary device was configured to connect with a textile electrode made of a silver-based knitted fabric designed to be located below the pectoralis major muscle for heart rate measurement. Considering the user-experience factors, key functions, and the ease of use, we developed an application to automatically log through smart phone tagging to improve usability. To evaluate the accuracy of the heart rate measurement, we recorded the heart rate of 10 healthy male subjects with a modular smart clothing system and compared the results with the heart rate values measured by the Polar RS800. Consequently, the average heart rate value measured by the temporary system was 85.37, while that measured by the reference device was 87.03, corresponding to an accuracy of 96.73%. No significant difference was found in comparison with the reference device (T value = -1.892, p = .091). Similarly, the average heart rate measured by the continuous system was 86.00, while that measured by the reference device was 86.97, corresponding to an accuracy of 97.16%. No significant difference was found in terms of the heart rate value between the two signals (T value = 1.089, p = .304). The significance of this study is to develop and validate a modular clothing system that can measure heart rates according to the purpose of the user. The developed modular smart clothing system for heart rate monitoring enables dual product planning by reducing the price increase due to unnecessary functions.

• Journal of the Korea Institute of Military Science and Technology
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• v.9 no.3
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• pp.12-19
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• 2006

A gun barrel of infantry fighting vehicle is supported like a type of cantilever. Temperature of a gun barrel is increased by heat transfer due to the combustion of propellant charge during the firing. Thus, the muzzle of a gun barrel is deflected in accordance with its temperature and the accuracy rate is decreased by deflection of the muzzle. In this study, deflection of a gun barrel is estimated by measuring its restoration rate because measuring the deflection rate is difficult due to the vibration of the gun barrel during the firing. In order to obtain the relations between deflection rate and restoration rate of the 40mm gun barrel of Next Infantry Fighting Vehicle(NIFV) under varying temperature, measurement of deflection rate and restoration rate is carried out using 5.56mm Remington rifle barrel. Effect of the estimated deflection rate of a gun barrel of NIFV on the hit probability is also analyzed.