• JSTS:Journal of Semiconductor Technology and Science
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• v.13 no.6
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• pp.608-616
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• 2013

This paper presents an adaptive sampling method for electrocardiogram (ECG) signal detection. First, by employing the strings matching process with compression dictionary, we recognize each segment of ECG with different characteristics. Then, based on the non-uniform sampling strategy, the sampling rate is determined adaptively. As the results of simulation indicated, our approach reconstructed the ECG signal at an optimized sampling rate with the guarantee of ECG integrity. Compared with the existing adaptive sampling technique, our approach acquires an ECG signal at a 30% lower sampling rate. Finally, the experiment exhibits its superiority in terms of energy efficiency and memory capacity performance.

• Proceedings of the IEEK Conference
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• 2002.07c
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• pp.1602-1605
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• 2002

Communication schemes are currently changing from circuit switched towards packet switched. These changes enable access to Internet and multimedia services in wireless network. Provision of real-time IP services in air interface introduces relatively large overhead in RTP/UDP/IP headers. To reduce the overhead, the header compression schemes are required. There exist two header compression schemes (CRTP, ROHC) which are IETF standards. We propose Context-ID detection method which reduces more efficiently the packet loss rate than two existing schemes. Its performance in WCDMA system environment is evaluated for CRTP and ROHC schemes.

• Journal of Communications and Networks
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• v.17 no.5
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• pp.517-524
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• 2015

The fast and accurate spectrum sensing over an ultra-wide bandwidth is a big challenge for the radio environment cognition. Considering sparse signal feature, two novel compressed sensing schemes are proposed, which can reduce compressed sampling rate in contrast to the traditional scheme. One algorithm is dynamically adjusting compression ratio based on modulation recognition and identification of symbol rate, which can reduce compression ratio. Furthermore, without priori information of the modulation and symbol rate, another improved algorithm is proposed with the application potential in practice, which does not need to reconstruct the signals. The improved algorithm is divided into two stages, which are the approaching stage and the monitoring stage. The overall sampling rate can be dramatically reduced without the performance deterioration of the spectrum detection compared to the conventional static compressed sampling rate algorithm. Numerous results show that the proposed compressed sensing technique can reduce sampling rate by 35%, with an acceptable detection probability over 0.9.

• Journal of the Korea Institute of Military Science and Technology
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• v.23 no.1
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• pp.28-36
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• 2020

Due to the continued demand for high-definition video, video compression technology is steadily developing and the High Efficiency Video Coding standard was established in 2013. However, despite the development of this compression technology, it is very difficult to smoothly transmit VGA-level videos in Ultra-narrowband environments. In this paper, the target information preprocessing algorithm is presented for smooth transmission of target images moving in forest or open-terrain in Ultra-narrowband environment. In addition, for algorithm verification, the target information preprocessing algorithm was simulated and the simulated results were compared with the video compression result without the algorithm being applied.

• Journal of Broadcast Engineering
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• v.25 no.7
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• pp.1081-1094
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• 2020

With the recent development of deep learning, most computer vision-related tasks are being solved with deep learning-based network technologies such as CNN and RNN. Computer vision tasks such as object detection or object segmentation use intermediate features extracted from the same backbone such as Resnet or FPN for training and inference for object detection and segmentation. In this paper, an experiment was conducted to find out the compression efficiency and the effect of encoding on task inference performance when the features extracted in the intermediate stage of CNN are encoded. The feature map that combines the features of 256 channels into one image and the original image were encoded in HEVC to compare and analyze the inference performance for object detection and segmentation. Since the intermediate feature map encodes the five levels of feature maps (P2 to P6), the image size and resolution are increased compared to the original image. However, when the degree of compression is weakened, the use of feature maps yields similar or better inference results to the inference performance of the original image.

• Journal of radiological science and technology
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• v.22 no.2
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• pp.9-15
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• 1999

The aim of this study is to measure the application of prone compression study using compression paddle for obese patients in upper gastrointestinal series. Prone compression study using compression paddle was performed in fifty patients, who were not examined completely erect compression study for obesity. The radiographs of stomach were classified into the lower, middle, and high body and then we gave five points included 'very poor', 'poor', 'suspicious', 'good', and 'complete' according to level of detection for area gastrica and mucosal fold. Statistic analysis was performed using T-test and ANOVA, and confidence rate was fixed in 95%(P<0.05) for the significance. The results were as follows : 1. The compression marks on high body was 'poor' grades in erect and prone compression study. The points were 1.64 and 1.86, respectively. 2. The compression marks on middle body was 1.68 in erect compression study, and 'suspicious' in prone compression study. 3. The compression marks on lower body was 'poor' in erect compression study, and 'good' in prone compression study. 4. There was a high statistic signification between the two study on middle and lower body except for high body(P<0.01). 5. The average abdominal thickness of subjects was 23.98 centimeter. There was no statistic signification between the difference of average marks by the abdominal thickness(P>0.05). As these results, the prone compression study in upper gastrointestinal serie seem to be an useful study for obese patients, because it decreases pain and the feeling of uneasiness, and improve compression efficiency remarkably.

• Journal of Korea Multimedia Society
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• v.8 no.7
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• pp.916-923
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• 2005

In recent times, mobile phones that play an important role in voice communication have became increasingly exciting due to the ability to transmit multimedia contents. However, user's communication cost and service usage fees for digital context exchange are still prohibitive. In this paper, we consider the task of transmitting a facial image in the context of mobile avatar generation. We present image compression as a useful technique to reduce service usage costs of data exchange in mobile communications. In view of this we propose an image compression algorithm that performs better than existing techniques. The suggested algorithm in this paper uses the location of significant coefficient on the wavelet image by detecting facial region as well as the spatial correlation between decomposed bands by wavelet transformation. The algorithm perform well and archives an efficient compression ratio. The proposed method recognizes location information of significant coefficient in advance, thus it is more suitable than existing general compression methods for mobile avatar generation systems.

• The Journal of the Acoustical Society of Korea
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• v.11 no.4
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• pp.36-44
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• 1992

To reduce the redundancy within samples that resulted from uniform sampling method, nonuniform sampling or nonredundant-sample coding methods can be considered. But it is well-known that when conventional nonuniform sampling methods are applied directly to speech signal, the amount of data required is comparable to or more than that required by uniform sampling method like PCM. To overcome this problem, we consider properties of speech signal in the sense of perception, and suggest a nonuniform sampling method at the maxima and minima of speech wave. To analyze the performance of the suggested method, compression ratio is considered. We show that compression ratio can be improved by silence detection, which can't be implemented by conventional methods based on uniform sampling. As experimental results, compression ratios of 1.54 without silence detection and 2.88 with silence detection for 8kHz 8-bit PCM signals are obtained.

• Journal of Korean Society of Transportation
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• v.22 no.6
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• pp.77-88
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• 2004

This study aims at developing the model that is able to detect the compression wave, which is included as a similar situation in incidents, that causes false applicable to the similar character such as incidents in the incident detection model for expressways. In this study, it has been checked whether the number of false alarms is decreased or not by modularizing this model for being able to applicable to other models such as DES and DELOS, etc. which do not perform the compression wave test based on the compression wave test process of APID model which has been being used in the expressway traffic management system currently. The evaluation in this study focuses on the sensitivity of the model and the results analysis is performed classified by each polling cycle. And how well these models are working is evaluated by each polling cycle. In addition to this, the detection rate, the false alarm rate and the average detection time in both the existing models and the model in this study are calcuated. As a result of appling the model in this study, it is found that the false alarm rate is improved through the reasonable decrease in the number of false alarm frequencies and there are not remarkable changes concerning the detection rate and the average detection time. To sum up, it is expected that a good number of improvement effects will be occurred when this model is applied to the actual expressway traffic management system.

• Korean Journal of Air-Conditioning and Refrigeration Engineering
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• v.17 no.1
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• pp.47-55
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• 2005

An experimental study has been peformed to develop a scheme for fault detection and diagnosis(FDD) in a vapor compression refrigeration system. This study is to analyze fault effect on the system performance and to find efficient diagnosis rules for easy determination of abnormal system operation. The refrigeration system was operated with a variable speed compressor to modulate cooling capacity. The FDD system was designed to consider transient load conditions. Four major faults were considered, and each fault was detected over wide operating load range by separating the system response to the load change. Rule-based method was used to diagnose and classify the system faults. From the experimental results, COP degradation due to the faults in a variable speed system is severer than that in a constant speed system. The method developed in this study can be used in the fault detection of refrigeration systems with a variable speed compressor.