• The Korean Journal of Applied Statistics
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• 제33권1호
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• pp.11-23
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• 2020

Sampling design should provide statistics to meet a given accuracy while saving cost and time. However, a large number of non-responses are occurring due to the deterioration of survey circumstances, which significantly reduces the accuracy of the survey results. Non-responses occur for a variety of reasons. Chung and Shin (2017, 2019) and Min and Shin (2018) found that the accuracy of estimation is improved by removing the bias caused by non-response when the response rate is an exponential or linear function of variable of interests. For that case they assumed that the error of the super population model follows normal distribution. In this study, we proposed a non-response bias adjusted estimator in the case where the error of a super population model follows the gamma distribution or the log-normal distribution in a business survey. We confirmed the superiority of the proposed estimator through simulation studies.

• Journal of the Korea Institute of Information and Communication Engineering
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• 제25권3호
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• pp.478-485
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• 2021

An injection locking technology of a semiconductor laser is a promising technology to generate optical complex signals by adjusting optical injection parameters. The extraction of the precise injection parameters plays a key role in the generation of the optical complex signal. Rate equations of semiconductor lasers under optical injection are commonly used to map the injection parameters and the corresponding optical complex signal. The accuracy of the generated optical complex signal on the injection parameters is limited since the rate equations require a locking map-based interpolation method. We propose a novel analytic method, namely rate equation-based direct extraction method, to directly calculate the injection parameters without relying on the locking map-based interpolation method. We achieved 103-times improvement of the signal accuracy by using the proposed method compared to locking-map based interpolation method.

• The Journal of the Korea institute of electronic communication sciences
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• 제17권1호
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• pp.111-118
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• 2022

In computer vision research, the two-dimensional human pose is a very extensive research direction, especially in pose tracking and behavior recognition, which has very important research significance. The acquisition of human pose targets, which is essentially the study of how to accurately identify human targets from pictures, is of great research significance and has been a hot research topic of great interest in recent years. Human pose recognition is used in artificial intelligence on the one hand and in daily life on the other. The excellent effect of pose recognition is mainly determined by the success rate and the accuracy of the recognition process, so it reflects the importance of human pose recognition in terms of recognition rate. In this human body gesture recognition, the human body is divided into 17 key points for labeling. Not only that but also the key points are segmented to ensure the accuracy of the labeling information. In the recognition design, use the comprehensive data set MS COCO for deep learning to design a neural network model to train a large number of samples, from simple step-by-step to efficient training, so that a good accuracy rate can be obtained.

• Computers and Concrete
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• 제32권3호
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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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• 제13권9호
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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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• 제11권2호
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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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• 제34권11호
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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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• 제2권6호
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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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• 제13권12호
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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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• 제47권2호
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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.