• Computers and Concrete
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• v.32 no.3
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• pp.327-337
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• 2023

Concrete is the most widely used building material, with various types including high- and ultra-high-strength, reinforced, normal, and lightweight concretes. However, accurately predicting concrete properties is challenging due to the geotechnical design code's requirement for specific characteristics. To overcome this issue, researchers have turned to new technologies like machine learning to develop proper methodologies for concrete specification. In this study, we propose a highly accurate deep learning-based predictive model to investigate the compressive strength (UCS) of lightweight concrete with natural aggregates (pumice). Our model was implemented on a database containing 249 experimental records and revealed that water, cement, water-cement ratio, fine-coarse aggregate, aggregate substitution rate, fine aggregate replacement, and superplasticizer are the most influential covariates on UCS. To validate our model, we trained and tested it on random subsets of the database, and its performance was evaluated using a confusion matrix and receiver operating characteristic (ROC) overall accuracy. The proposed model was compared with widely known machine learning methods such as MLP, SVM, and DT classifiers to assess its capability. In addition, the model was tested on 25 laboratory UCS tests to evaluate its predictability. Our findings showed that the proposed model achieved the highest accuracy (accuracy=0.97, precision=0.97) and the lowest error rate with a high learning rate (R2=0.914), as confirmed by ROC (AUC=0.971), which is higher than other classifiers. Therefore, the proposed method demonstrates a high level of performance and capability for UCS predictions.

• Asian Pacific Journal of Cancer Prevention
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• v.13 no.9
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• pp.4695-4698
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• 2012

Objective: To analyze differential diagnostic accuracy of urinary human epidydimis secretory protein 4 (HE4) in patients with ovarian tumors. Materials and methods: In the case-control study 23 patients with ovarian cancer, 37 patients with benign ovarian tumors and 18 women in the control group were included. Serum CA125 values and urinary concentrations of HE4were assessed quantitatively. Urinary creatinine concentrations and glomerular filtration rate were also determined and used to calculate ratios to HE4. Results: Higher urinary HE4 concentrations were observed in patients with late stage ovarian cancer (p=0.001) and also in patients with early stage ovarian cancer when compared to patients with benign ovarian tumors (p=0.044). On analysis where all ovarian cancer patients were included, higher diagnostic accuracy was observed with calculated ratio of HE4 to glomerular filtration rate (GFR) to unchanged urinary HE4 concentrations -AUC 0.861 vs. 0.858. When discriminatory accuracy was calculated for urinary HE4/GFR ratio and unchanged urinary HE4 concentrations, the last demonstrated a higher area under the curve - 0.701 vs. 0.602. The urinary HE4/creatinine ratio had lower discriminatory characteristics than unchanged concentrations of urinary HE4. However, HE4 serum concentration was more accurate for discrimination of patients with benign and malignant ovarian tumors when compared to urinary HE4 and CA125 in sera (AUCs were 0.868 for serum HE4 and 0.856 and 0.653 for urinary HE4 and CA125, respectively). Conclusions: Ovarian cancer patients have higher urinary concentrations of human epidydimis secretory protein 4 than patients with benign ovarian tumors. Urinary HE4 has comparable discriminatory accuracy with serum HE4 for benign and malignant ovarian tumors and can be recommended as a non-invasive ovarian cancer risk assessment method.

• Journal of Korea Spatial Information System Society
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• v.11 no.2
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• pp.89-98
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• 2009

As data stream is entered into system continuously and the memory space is limited, the data exceeding the memory size cannot be processed. In order to solve the problem, load shedding methods which drop a part of data to prevent exceeding the storage space have been researched. Generally, a traditional load shedding method uses random sampling with optimized rate according to data deviation. The method samples data not to distinguish those used in spatial query because the method uses only a random sampling with optimized rate according to data deviation. Therefore, the accuracy of query was reduced in u-GIS environment including spatial query. In this paper, we researched a new load shedding method improving accuracy of the query in u-GIS environment which runs spatial query and aspatial query simultaneously. The method uses a new sampling method that samples data having low probability used in query. Therefore proposed method improves spatial query accuracy and query processing speed as applying spatial filtering operation to sampling operator.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.34 no.11
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• pp.61-69
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• 2006

Position determination accuracy is strongly depending on how much precisely and frequently satellite receiver measures transmitted signals from terminals on target animals when Doppler effect is applied for position determination. ARGOS satellite system has shown relatively high position determination accuracy by operating multiple satellites, which enable operator to get more Doppler shift data from terminals. In case of animal tracking mission with single satellite, however, it is difficult for the satellite receiver to receive transmitted signals from terminals frequently during short period that satellite passes over ground terminals. This is one of the main sources to decrease position accuracy on target animals. In this paper, the Doppler rate estimation is implemented to increase the number of Doppler shift data received by single satellite. It is proved that the relatively high position determination accuracy with increased number of estimated data can be obtained. We also suggest that the Doppler rate estimation is applicable for position determination system with single satellite.

• KIPS Transactions on Computer and Communication Systems
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• v.2 no.6
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• pp.257-264
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• 2013

In this study, we have designed the variable amplitude threshold algorithm that can enhance the accuracy of step count using variable amplitude. This algorithm converts the x, y, z sensor values into a single energy value($E_t$) by using SVM(Signal Vector Magnitude) algorithm and can pick step count out over 99% of accuracy through the peak data detection algorithm and fixed peak threshold. To prove the results, We made the noise filtering with the fixed amplitude threshold from the amplitude of energy value that found out the detection error was increasing, and it's the key idea of the variable amplitude threshold that can be adapted on the continuous data evaluation. The experiment results shows that the variable amplitude threshold algorithm can improve the average step count accuracy up to 98.9% at 10 Hz sampling rate and 99.6% at 20Hz sampling rate.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.13 no.12
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• pp.5950-5957
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• 2012

CPR with minimized hands-off time is one of integral factors for the improvement of the survival rate of patients. The purpose of this study was to examine the relationship of the installation of C-steps on the main stretcher to CPR accuracy and errors. The subjects in this study were 70 paramedics in 10 firehouses in the province of C(35 for control group, 35 for experimental group), and their CPR accuracy on the main stretchers was checked. As a result, it's found that the main stretchers equipped with the C-steps served to boost the accuracy of chest compression by creating suitable environments for that in terms of height and posture(t=65.104, p=.000), to improve the accuracy of artificial respiration by providing a proper amount of ventilation(t=5.207, p=.000), and to bolster the self-confidence of the paramedics about CPR(t=-10.612, p=.000). In conclusion, the mounting of C-steps on the main stretcher is expected to be of use for the improvement of the survival rate of cardiac-arrest patients by ensuring the precise performance of high-quality CPR.

• Journal of the Institute of Electronics Engineers of Korea TC
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• v.47 no.2
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• pp.34-39
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• 2010

This paper proposes S/W Watch-Dog method between Dual CPU using the different OS. The proposed watch-dog method performs that it distinguishes the status of channel between dual CPU and status of processor itself. We find out the ideal value of threshold and priority for load test task. and we evaluate the accuracy of the proposed S/W Watch-Dog Method at the result of evaluation. We figure out that the accuracy of proposed method is higher than the accuracy of general S/W Watch-Dog Method in case of variable data rate. Therefore we confirm that the proposed Method has high accuracy of watch-dog function with the ideal value of threshold and priority for load test task through the performance evaluation.

• The Journal of the Korea Contents Association
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• v.15 no.10
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• pp.587-596
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• 2015

3D scanners are applied to many industries, such as manufacturing, construction, and shipbuilding. Recently, 3D scanner is used in 3D imaging of worksite in order to control and guide earthmoving heavy equipments, which provides basic information for intelligent excavation. This study compares the accuracy and productivity between total stations and high-resolution 3D scanners. The analysis results show that 3D scanner has high accurate rate of greater than 99 percent and has low error rate of less than 2.0mm compared to total stations. In terms of productivity, 3D scanner saves 71 percent of measuring time compared to the total station. This study confirms that 3D scanner can measure the earthwork sites with high accuracy and better productivity.

• Asian Pacific Journal of Cancer Prevention
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• v.13 no.4
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• pp.1583-1588
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• 2012

Fine needle aspiration (FNA) cytology is well accepted as a safe, reliable, minimal invasive and cost-effective method for diagnosis of salivary gland lesions. This study evaluated the accuracy and diagnostic performance of FNA cytology in Thailand. A consecutive series of 290 samples from 246 patients during January 2001-December 2009 were evaluated from the archive of the Anatomical Pathology Department of our institution and 133 specimens were verified by histopathologic diagnoses, obtained with material from surgical excision or biopsy. Cytologic diagnoses classified as unsatisfactory, benign, suspicious for malignancy and malignant were compared with the histopathological findings. Among the 133 satisfactory specimens, the anatomic sites were 70 (52.6%) parotid glands and 63 (47.4 %) submandibular glands. FNA cytological diagnoses showed benign lesions in 119 cases (89.5 %), suspicious for malignancy in 3 cases (2.2 %) and malignant in 11 cases (8.3%). From the subsequent histopathologic diagnoses, 3/133 cases of benign cytology turned out to be malignant lesions, the false negative rate being 2.2 % and 1/133 case of malignant cytology turned out to be a benign lesion, giving a false positive rate was 0.8%. The overall accuracy, sensitivity, specificity, positive predictive value and negative predictive value were 97.0% (95% CI, 70.6%-99.4%), 81.3% (95% CI, 54.4%-96.0%), 99.1% (95% CI, 95.4%-100%), 92.9% (95% CI, 66.1%-99.8), 97.5% (95% CI, 92.8%-99.5%), respectively. This study indicated that FNA cytology of salivary gland is a reliable and highly accurate diagnostic method for diagnosis of salivary gland lesions. It not only provides preoperative diagnosis for therapeutic management but also can prevent unnecessary surgery.

• Nutrition Research and Practice
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• v.13 no.3
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• pp.256-262
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• 2019

BACKGROUND/OBJECTIVES: The objectives of this study were to evaluate the accuracy of the Dietary Reference Intakes (DRI) for estimating the energy requirements of older adults, and to develop and validate new equations for predicting the energy requirements of this population group. MATERIALS/METHODS: The study subjects were 25 men and 23 women with a mean age of $72.2{\pm}3.9\;years$ and $70.0{\pm}3.3\;years$, and mean BMI of $24.0{\pm}2.1$ and $23.9{\pm}2.7$, respectively. The total energy expenditure (TEE) was measured by using the doubly labeled water (DLW) method, and used to validate the DRI predictive equations for estimated energy requirements (EER) and to develop new EER predictive equations. These developed equations were cross-validated by using the leave-one-out technique. RESULTS: In men, the DRI equation had a -7.2% bias and accurately predicted the EER (meaning EER values within ${\pm}10%$ of the measured TEE) for 64% of the subjects, whereas our developed equation had a bias of -0.1% and an accuracy rate of 84%. In women, the bias was -6.6% for the DRI equation and 0.2% for our developed equation, and the accuracy rate was 74% and 83%, respectively. The predicted EER was strongly correlated with the measured TEE, for both the DRI equations and our developed equations (Pearson's r = 0.915 and 0.908, respectively). CONCLUSIONS: The DRI equations provided an acceptable prediction of EER in older adults and these study results therefore support the use of these equations in this population group. Our developed equations had a better predictive accuracy than the DRI equations, but more studies need to be performed to assess the performance of these new equations when applied to an independent sample of older adults.