• Proceeding of EDISON Challenge
• /
• 2016.03a
• /
• pp.183-189
• /
• 2016

In this paper, an optimization study on a helicopter rotor blade cross-section was made. Generalization was made to the baseline cross-section to simplify the analysis. To have better performance in aeroelastic response, with the aerodynamic center being the origin of the baseline, the distance between aerodynamic center and shear center, and the distance between mass center and shear center of the blade were minimized. For efficient searching of optimum solutions over the design space, grid search method, which is a method of graphical search was used. Two design variables, radius of balancing weight at leading edge, and offset of the spar from leading edge were selected for the study. Cubic spline interpolation method was used to accommodate searching of the optimum solution. 2-Leveled searching system was devised in accordance with the interpolation method. Optimum solution was found to show 6% decrease in both distance between aerodynamic center and shear center, and mass center and shear center to the baseline.

• 제어로봇시스템학회:학술대회논문집
• /
• 2001.10a
• /
• pp.61.1-61
• /
• 2001

This paper describes an efficient ambiguity searching method using additional constraints in 3-dimentional attitude finding GPS receiver design. For determining the integer ambiguity, the baseline length constraint, the angle constraint, the velocity constraint and the attitude constraint can be used for reducing the searching space. This paper describes the searching space algebraically and graphically. It is confirmed that the described restrictions are reasonable and the speed and the probability of ambiguity fixing are improved when the restricted searching spaces are applied Moreover, it is possible to design receivers of better quality by applying the method proposed in this paper.

• Journal of Korea Multimedia Society
• /
• v.10 no.2
• /
• pp.218-225
• /
• 2007

This paper presents a technique to detect a document skew that often occurs during document scanning. To correct a skewed document is essential for automatic processing system including character segmentation, character recognition and so on. The proposed algorithm can detect a skew angle exactly by searching characters baselines that have slant information of the document within a candidated area. To reduce processing time, we resized the image small and then established a ROI (region of interest) by morphology operations and connected components analysis. We compared our method with the existing method based on morphology operations and proved correctness and efficiency of the proposed algorithm through experiments and analysis with various kind of document images.

• Journal of Electrical Engineering and Technology
• /
• v.13 no.5
• /
• pp.2080-2085
• /
• 2018

There have been numerous studies that extract the R-peak from electrocardiogram (ECG) signals. All of these studies can extract R-peak from ECG. However, these methods are complicated and difficult to implement in a real-time portable ECG device. After filtration choosing a threshold value for R-peak detection is a big challenge. Fixed threshold scheme is sometimes unable to detect low R-peak value and adaptive threshold sometime detect wrong R-peak for more adaptation. In this paper, a simple and robustness algorithm is proposed to detect R-peak with less complexity. This method also solves the problem of threshold value selection. Using the adaptive filter, the baseline drift can be removed from ECG signal. After filtration, an appropriate threshold value is automatically chosen by using the minimum and maximum value of an ECG signals. Then the neighborhood searching scheme is applied under threshold value to detect R-peak from ECG signals. Proposed method improves the detection and accuracy rate of R-peak detection. After R-peak detection, we calculate heart rate to know the heart condition.

• Journal of the Korea Society of Computer and Information
• /
• v.25 no.7
• /
• pp.57-64
• /
• 2020

In this paper, we propose an scalable re-detection for correlation filter in visual tracking. In real world, there are lots of target disappearances and reappearances during tracking, thus failure detection and re-detection methods are needed. One of the important point for re-detection is that a searching area must be large enough to find the missing target. For robust visual tracking, we adopt kernelized correlation filter as a baseline. Correlation filters have been extensively studied for visual object tracking in recent years. However conventional correlation filters detect the target in the same size area with the trained filter which is only 2 to 3 times larger than the target. When the target is disappeared for a long time, we need to search a wide area to re-detect the target. Proposed algorithm can search the target in a scalable area, hence the searching area is expanded by 2% in every frame from the target loss. Four datasets are used for experiments and both qualitative and quantitative results are shown in this paper. Our algorithm succeed the target re-detection in challenging datasets while conventional correlation filter fails.

• International journal of advanced smart convergence
• /
• v.5 no.4
• /
• pp.1-9
• /
• 2016

In order to reconstruct a 3D model in video sequences, to select key frames that are easy to estimate a geometric model is essential. This paper proposes a method to easily extract informative frames from a handheld video. The method combines selection criteria based on appropriate-baseline determination between frames, frame jumping for fast searching in the video, geometric robust information criterion (GRIC) scores for the frame-to-frame homography and fundamental matrix, and blurry-frame removal. Through experiments with videos taken in indoor space, the proposed method shows creating a more robust 3D point cloud than existing methods, even in the presence of motion blur and degenerate motions.

• The Transactions of The Korean Institute of Electrical Engineers
• /
• v.62 no.6
• /
• pp.825-832
• /
• 2013

In this study, Independent Component Analysis (ICA) algorithms are suggested to extract the original ECG part from the mixed signal contaminated with the unwanted frequency components and especially 60Hz power line disturbances. With this aim, we implement a novel method to suppress the baseline-wandering disturbances and power line artefacts contained in patch-electrodes sensory ECG data by separating the unmixed signal with finding the optimal weight W based on Kurtosis value. With applying brutal force and gradient ascent searching algorithm to find W, we can conclude that the unwanted frequency components especially in the ambulatory ECG data can be eliminated by Independent Component Analysis.

• ETRI Journal
• /
• v.42 no.6
• /
• pp.899-911
• /
• 2020

The data in tables are accurate and rich in information, which facilitates the performance of information extraction and question answering (QA) tasks. TableQA, which is based on tables, solves problems by understanding the table structure and searching for answers to questions. In this paper, we introduce both novice and intermediate Korean TableQA tasks that involve deducing the answer to a question from structured tabular data and using it to build a question answering pair. To solve Korean TableQA tasks, we use S3-NET, which has shown a good performance in machine reading comprehension (MRC), and propose a method of converting structured tabular data into a record format suitable for MRC. Our experimental results show that the proposed method outperforms a baseline in both the novice task (exact match (EM) 96.48% and F1 97.06%) and intermediate task (EM 99.30% and F1 99.55%).

• Journal of Korean Academy of Nursing
• /
• v.30 no.4
• /
• pp.995-1005
• /
• 2000

This study was performed to identify the physiological and psychological variables related to successful weaning from a mechanical ventilator. The subjects of this study were 22 patients who received mechanical ventilation therapy for more than 3 days in intensive care units. Before the weaning trial, baseline data for following physiologic variables were obtained: spontaneous respiration rate, blood pressure, pulse rate, PaO2, PaCO2, PEEP, static compliance, minute ventilation, tidal volume, rapid shallow breathing index(f/VT), SaO2, PaO2/FiO2 and mean arterial pressure. During spontaneous breathing, physiologic and psychologic variables such as vital signs, ABG, perspiration, chest retraction, paradoxical respiration, dyspnea, anxiety, confidence and efficacy were measured. Successful weaning was defined as sustaining spontaneous respiration over 24 hours after extubation. Weaning failure was defined as the development of more than one of following signs: (1) hypoxemia, (2) CO2 retention or (3) perspiration, tachypnea, chest retraction, tachycardia, arrhythmia, hypotension or hypertension. Subjects (N=18) who successfully weaned from mechanical ventilator were compared with subjects (N=4) who failed. The results are as follows; Eighteen percents of the subjects failed during the weaning trial. Most subjects in the failed group were mechanically ventilated for long-time. This result shows that the success of weaning is more difficult in long-term ventilation patients. In the baseline data that was measured before weaning trial, the mean score of PaO2 in the successfully weaned group was 121mmHg. This is significantly higher than the mean score of PaO2 in the failed group(95mmHg). However, the scores of pH, tidal volume, f/VT, pulse rates, blood pressure, mean airway pressure, SaO2, and PaCO2 were similar between the two groups. Specially the scores of f/VT index as a predominant predictor for successful weaning were not significant (f/VT=44.4) and (f/VT=47). During spontaneous breathing, the scores of dyspnea and anxiety level in the successfully weaned group were less than those of the failed group. On the contrary, the scores of confidence and efficacy in the successful group were greater than those of the failed group. In conclusion, the baseline data that were measured before weaning trial were similar between the both groups, therefore future studies are needed to focus on searching other variables besides physiological parameters related to weaning outcome.

• Industrial Engineering and Management Systems
• /
• v.12 no.4
• /
• pp.380-388
• /
• 2013

Large variation in electrocardiogram (ECG) waveforms continues to present challenges in defining R-wave locations in ECG signals. This research presents a procedure to extract the R-wave locations by forward-backward (FB) algorithm and classify the arrhythmic beat conditions by using RR intervals. The FB algorithm shows forward and backward searching rules from QRS onset and eliminates lower-amplitude signals near the baseline using a statistical process control concept. The proposed algorithm was trained the optimal parameters by using MIT-BIH arrhythmia database (MITDB), and it was verified by actual Holter ECG signals from a local hospital. The signals are classified into normal (N) and three arrhythmia beat types including premature ventricular contraction (PVC), ventricular flutter/fibrillation (VF), and second-degree heart block (BII) beat. This work produces 98.54% accuracy in the detection of R-wave location; 98.68% for N beats; 91.17% for PVC beats; and 87.2% for VF beats in the collected Holter ECG signals, and the results are better than what are reported in literature.