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

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 1996.06a
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• pp.223-227
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• 1996

In this paper we propose an adaptive fast image restoration filter, which is suitable for reducing the blocking artifacts in the compressed image in real-time. The proposed restoration filter is based on the observation that quantization operation in a series of coding process is a nonlinear and many-to-one mapping operator. And then we propose an approximated version of constrained optimization technique as a restoration process for removing the nonlinear and space varying degradation operator. We also propose a novel block classification method for adaptively choosing the direction of a highpass filter, which serves as a constraint in the optimization process. The proposed classification method adopts the bias-corrected maximized likelihood, which is used to determine the number of regions in the image for the unsupervised segmentation. The proposed restoration filter can be realized either in the discrete Fourier transform domain or in the spatial domain in the form of a truncated finite impulse response (FIR) filter structure for real-time processing. In order to demonstrate the validity of the proposed restoration filter experimental results will be shown.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.9 no.7
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• pp.2667-2682
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• 2015

Due to the wide application of face recognition (FR) in information security, surveillance, access control and others, it has received significantly increased attention from both the academic and industrial communities during the past several decades. However, partial face occlusion is one of the most challenging problems in face recognition issue. In this paper, a novel method based on linear regression-based classification (LRC) algorithm is proposed to address this problem. After all images are downsampled and divided into several blocks, we exploit the evaluator of each block to determine the clear blocks of the test face image by using linear regression technique. Then, the remained uncontaminated blocks are utilized to partial occluded face recognition issue. Furthermore, an improved Distance-based Evidence Fusion approach is proposed to decide in favor of the class with average value of corresponding minimum distance. Since this occlusion removing process uses a simple linear regression approach, the completely computational cost approximately equals to LRC and much lower than sparse representation-based classification (SRC) and extended-SRC (eSRC). Based on the experimental results on both AR face database and extended Yale B face database, it demonstrates the effectiveness of the proposed method on issue of partial occluded face recognition and the performance is satisfactory. Through the comparison with the conventional methods (eigenface+NN, fisherfaces+NN) and the state-of-the-art methods (LRC, SRC and eSRC), the proposed method shows better performance and robustness.

• Proceedings of the KSRS Conference
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• v.1
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• pp.260-262
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• 2006

One of future remote sensing techniques for transportation application is vehicle detection from the space, which could be the basis of measuring traffic volume and recognizing traffic condition in the future. This paper introduces an approach to vehicle detection using image object segmentation approach. The object-oriented image processing is particularly beneficial to high-resolution image classification of urban area, which suffers from noisy components in general. The project site was Dae-Jeon metropolitan area and a set of true color aerial images at 10cm resolution was used for the test. Authors investigated a variety of parameters such as scale, color, and shape and produced a customized solution for vehicle detection, which is based on a knowledge-based hierarchical model in the environment of eCognition. The highest tumbling block of the vehicle detection in the given data sets was to discriminate vehicles in dark color from new black asphalt pavement. Except for the cases, the overall accuracy was over 90%.

• The KIPS Transactions:PartB
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• v.9B no.2
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• pp.231-236
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• 2002

The classification of the speech-sound block comes from the multi-resolution analysis property of the discrete wavelet transform, which is used to reduce the computational time for the pre-processing of speech recognition. The merging algorithm is proposed to extract vapid speech-sounds in terms of position and frequency range. It performs unvoiced/voiced classification and denoising. Since the merging algorithm can decide the processing parameters relating to voices only and is independent of system noises, it is useful for extracting valid speech-sounds. The merging algorithm has an adaptive feature for arbitrary system noises and an excellent denoising signal-to-noise ratio and a useful system tuning for the system implementation.

• Journal of Welding and Joining
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• v.16 no.3
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• pp.64-73
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• 1998

This paper is concerned with defects detection and evaluation of heat affected zone (HAZ) in austenitic stainless steel type 304 by ultrasonic wave and neural network. In experiment, the reflected ultrasonic defect signals from artificial defects (side hole, vertical hole, notch) of HAZ appears as beam distance of prove-defect, distance of probe-surface, depth of defect-surface on CRT. For defect classification simulation, neural network system was organized using total results of ultrasonic experiment. The organized neural network system was learned with the accuracy of 99%. Also it could be classified with the accuracy of 80% in side hole, and 100% in vertical hole, 90% in notch about ultrasonic pattern recognition. Simulation results of neural network agree fairly well with results of ultrasonic experiment. Thus were think that the constructed system (ultrasonic wave - neural network) in this work is useful for defects dection and classification such as holes and notches in HAZ of austenitic stainless steel 304.

• The Korean Journal of Pain
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• v.29 no.1
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• pp.3-11
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• 2016

A nerve block is an effective tool for diagnostic and therapeutic methods. If a diagnostic nerve block is successful for pain relief and the subsequent therapeutic nerve block is effective for only a limited duration, the next step that should be considered is a nerve ablation or modulation. The nerve ablation causes iatrogenic neural degeneration aiming only for sensory or sympathetic denervation without motor deficits. Nerve ablation produces the interruption of axonal continuity, degeneration of nerve fibers distal to the lesion (Wallerian degeneration), and the eventual death of axotomized neurons. The nerve ablation methods currently available for resection/removal of innervation are performed by either chemical or thermal ablation. Meanwhile, the nerve modulation method for interruption of innervation is performed using an electromagnetic field of pulsed radiofrequency. According to Sunderland's classification, it is first and foremost suggested that current neural ablations produce third degree peripheral nerve injury (PNI) to the myelin, axon, and endoneurium without any disruption of the fascicular arrangement, perineurium, and epineurium. The merit of Sunderland's third degree PNI is to produce a reversible injury. However, its shortcoming is the recurrence of pain and the necessity of repeated ablative procedures. The molecular mechanisms related to axonal regeneration after injury include cross-talk between axons and glial cells, neurotrophic factors, extracellular matrix molecules, and their receptors. It is essential to establish a safe, long-standing denervation method without any complications in future practices based on the mechanisms of nerve degeneration as well as following regeneration.

• Journal of the Korean Society of Fisheries and Ocean Technology
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• v.43 no.1
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• pp.1-11
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• 2007

It is the basic studies for productivity improvement and laborsaving of purse seine fishery. Because the seine shape is apt to be transformed in seine shooting process due to the effect of tide, this study is intended to establish 4 steps, whose flow velocity are 0, 2, 4 and 6cm/sec, in flume tank and perform the experiment to review the character. We used two model seines designed on the scale of 1 to 180 based on the power block seine, which is the mackerel purse seine generally used in the near sea of Jeju Island and triplex seine, which is the mackerel purse seine of one boat system fishing expected in the future, for the experiment, analyzed of the sinking movements on the two seines and its results are as follows. In the setting over the flow velocity 6cm/sec, experiment was impossible because of flying and transformation of seine were severe. The sinking movements of P seine and T seine generally showed linear phenomenon and the sinking speed showed gentle curve shape. Sinking tendency was distinguished by existence of flow velocity. When there is flow velocity, it showed the phenomenon that it sinking by similar type. Although sinking depth and sinking speed did not show distinguished classification, P seine shows bigger than T seine. When there was in flow velocity, the elapsed time(Et) and sinking depth (PDp, TDp) of P seine and T seine can be shown such experimental equations as PDp=(0.21V+4.96)Et-(0.62V-0.10) and TDp=(0.19V+4.95)Et-(0.72V+0.34). When there was in flow velocity, the elapsed time and siking speed (PSp, TSp) of P seine and T seine can be shown such experimental equations as $PSp=-0.11Et^2+1.42Et+1.75\;and\;TSp=-0.11Et^2+1.41Et+1.37$.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.22 no.5
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• pp.49-54
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• 2022

With the recent widespread adoption of general-purpose GPUs (GPGPUs) in cloud systems, maximizing the resource utilization through multitasking in GPGPU has become an important issue. In this article, we show that resource allocation based on the workload classification of computing-bound and memory-bound is not sufficient with respect to resource utilization, and present a new thread block scheduling policy for GPGPU that makes use of fine-grained resource utilizations of each workload. Unlike previous approaches, the proposed policy reduces scheduling overhead by separating profiling and scheduling, and maximizes resource utilizations by co-locating workloads with different bottleneck resources. Through simulations under various virtual machine scenarios, we show that the proposed policy improves the GPGPU throughput by 130.6% on average and up to 161.4%.

• Journal of Yeungnam Medical Science
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• v.40 no.2
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• pp.172-178
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• 2023

Background: Laparoscopic cholecystectomy (LC) is a noninvasive surgery, but postoperative pain is a major problem. Studies have indicated that erector spinae plane block (ESPB) has an analgesic effect after LC. We aimed to compare the efficacy of different ESPB anesthetic concentrations in pain control in patients with LC. Methods: This retrospective study included patients aged 20 to 75 years scheduled for LC with the American Society of Anesthesiologists physical status classification I or II. ESPB was administered using 0.375% bupivacaine in group 1 and 0.25% in group 2. Both groups received general anesthesia. Postoperative tramadol consumption and pain scores were compared and intraoperative and postoperative fentanyl requirements in the postanesthesia care unit (PACU) were measured. Results: Eighty-five patients were included in this analysis. Tramadol consumption in the first 12 hours, second 12 hours, and total 24 hours was similar between groups (p>0.05). The differences between postoperative numeric rating scale (NRS) scores at rest did not differ significantly. The postoperative NRS scores upon bodily movement were not statistically different between the two groups, except at 12 hours. The mean intraoperative and postoperative fentanyl requirements in the PACU were similar. The difference in the requirement for rescue analgesics was not statistically significant (p=0.788). Conclusion: Ultrasound-guided ESPB performed with different bupivacaine concentrations was effective in both groups for LC analgesia, with similar opioid consumption. A lower concentration of local anesthetic can be helpful for the safety of regional anesthesia and is recommended for the analgesic effect of ESPB in LC.