• Journal of IKEEE
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• v.22 no.4
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• pp.1140-1146
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• 2018

Recently, a methodology for analyzing complex bio-signals using a deep learning model has emerged among studies that recognize human emotions. At this time, the accuracy of emotion classification may be changed depending on the evaluation method and reliability depending on the kind of data to be learned. In the case of biological signals, the reliability of data is determined according to the noise ratio, so that the noise detection method is as important as that. Also, according to the methodology for defining emotions, appropriate emotional evaluation methods will be needed. In this paper, we propose a wavelet -based noise threshold setting algorithm for verifying the reliability of data for multimodal bio-signal data labeled Valence and Arousal and a method for improving the emotion recognition rate by weighting the evaluation data. After extracting the wavelet component of the signal using the wavelet transform, the distortion and kurtosis of the component are obtained, the noise is detected at the threshold calculated by the hampel identifier, and the training data is selected considering the noise ratio of the original signal. In addition, weighting is applied to the overall evaluation of the emotion recognition rate using the euclidean distance from the median value of the Valence-Arousal plane when classifying emotional data. To verify the proposed algorithm, we use ASCERTAIN data set to observe the degree of emotion recognition rate improvement.

• Asia-pacific Journal of Multimedia Services Convergent with Art, Humanities, and Sociology
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• v.6 no.3
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• pp.383-391
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• 2016

Ballast water provides stability and manoeuvrability to a ship. Foreign harmful aquatic organisms, which were transferred by ballast water, cause disturbing ecosystem. In order to minimize transference of foreign harmful aquatic organisms, IMO(International Maritime Organization) adopted the International Convention for the Control and Management of Ship's Ballast Water and Sediments in 2004. If the convention take effect, a port authority might need to check that ballast water is properly disposed of. In this paper, we propose a method of counting harmful aquatic organisms in ballast water thorough image processing. We extracted three samples from the ballast water that had been collected at Busan port in Korea. Then we made three grey-scale images from each sample as experimental data. We made a comparison between the proposed method and CellProfiler which is a well known cell-counting program based on image processing. Setting of CellProfiler is empirically chosen from the result of cell count by an expert. After finding a proper threshold for each image at which the result is similar to that of CellProfiler, we used the average value as the final threshold. Our experimental results showed that the proposed method is simple but about ten times faster than CellProfiler without loss of the output quality.

• Korean Journal of Radiology
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• v.22 no.8
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• pp.1240-1252
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• 2021

Objective: To compare the accuracy for detecting breast cancer in the diagnostic setting between the use of digital breast tomosynthesis (DBT), defined as DBT alone or combined DBT and digital mammography (DM), and the use of DM alone through a systematic review and meta-analysis. Materials and Methods: Ovid-MEDLINE, Ovid-Embase, Cochrane Library and five Korean local databases were searched for articles published until March 25, 2020. We selected studies that reported diagnostic accuracy in women who were recalled after screening or symptomatic. Study quality was assessed using the Quality Assessment of Diagnostic Accuracy Studies-2 tool. A bivariate random effects model was used to estimate pooled sensitivity and specificity. We compared the diagnostic accuracy between DBT and DM alone using meta-regression and subgroup analyses by modality of intervention, country, existence of calcifications, breast density, Breast Imaging Reporting and Data System category threshold, study design, protocol for participant sampling, sample size, reason for diagnostic examination, and number of readers who interpreted the studies. Results: Twenty studies (n = 44513) that compared DBT and DM alone were included. The pooled sensitivity and specificity were 0.90 (95% confidence interval [CI] 0.86-0.93) and 0.90 (95% CI 0.84-0.94), respectively, for DBT, which were higher than 0.76 (95% CI 0.68-0.83) and 0.83 (95% CI 0.73-0.89), respectively, for DM alone (p < 0.001). The area under the summary receiver operating characteristics curve was 0.95 (95% CI 0.93-0.97) for DBT and 0.86 (95% CI 0.82-0.88) for DM alone. The higher sensitivity and specificity of DBT than DM alone were consistently noted in most subgroup and meta-regression analyses. Conclusion: Use of DBT was more accurate than DM alone for the diagnosis of breast cancer. Women with clinical symptoms or abnormal screening findings could be more effectively evaluated for breast cancer using DBT, which has a superior diagnostic performance compared to DM alone.

• Journal of Digital Contents Society
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• v.15 no.2
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• pp.147-154
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• 2014

There have been company researches for TCP-Westwood algorithms in wireless TCP environment with high packet loss rate. Because the TCP-Westwood algorithm adjusts the congestion window according to the ABE(Available Bandwidth Estimation), the algorithm has a problem which the accuracy of ABE decreases as the error rate increases. To solve such a problem, the proposed scheme in this paper adopts the existing packet pattern based algorithm that the ABE is ignored when the arriving interval time of ACK is longer than a given interval time and uses new algorithm that the ABE is reallocated to a given allowable ABE when the ABE is over the allowable range. The proposed scheme shows the simulation result that the ABE is closest to the setting bandwidth for simulation compared to the existing algorithms.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.19 no.12
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• pp.2924-2932
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• 2015

Image binarization is a process to divide the image into objects and backgrounds, widely applied to the fields of image analysis and its recognition. In the existing method of binarization, there is some uncertainty when there is insufficient brightness gap between objects and backgrounds in setting threshold. The method of fuzzy binarization has improved the features of objects efficiently. However, since this method sets ${\alpha}$-cut value statically, there remain some problems that important features of objects can be lost during binarization. Therefore, in this paper, we propose a binarization method which does not set ${\alpha}$-cut value statically. The proposed method uses fuzzy membership functions calculated by thresholds of mean, iterative, and Otsu binarization. Experiment results show the proposed method binaries various images with less loss than the existing methods.

• Journal of KIISE:Software and Applications
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• v.30 no.3_4
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• pp.239-250
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• 2003

Recent recommender system user a method of combining collaborative filtering system and content based filtering system in order to slove the problem of the Sparsity and First-Rater in collaborative filtering system. In this paper, to make up for the prediction accuracy in hybrid Recommender system, the harmonic mean weight(CBCF_harmonic_mean) is used for calculating the user similarity weight. After setting up the threshold as 45 considering the performance of content based filtering, we apply significance weight of n/45 to user similarity weight. To estimate the performance of the proposed method, it if compared with that of combing both the existing collaborative filtering system and the content- based filtering system. As a result, it confirms that the suggested method is efficient at improving the prediction accuracy as solving problems of the exiting collaborative filtering system.

• Journal of KIISE
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• v.45 no.2
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• pp.187-194
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• 2018

Recently, Hypertext Transfer Protocol (HTTP) adaptive streaming service is attracting attention. The existing quality adaptive scheme of HTTP adaptive streaming service adjusts the video quality according to the network bandwidth or the client buffer size. However, the problem with the existing quality adaptive scheme is the QoE (Quality of Experience) degradation caused by the unnecessary quality change that occurs due to frequent bandwidth change or fixed buffer threshold. We propose a video quality maintenance scheme that improves average video quality and minimizes unnecessary quality change in order to improve the QoE of HTTP adaptive streaming service in the changing network environment. The proposed scheme maintains high quality for a long time by setting the quality maintenance duration to be long when buffer occupancy and video quality are high. The experimental results show that the proposed scheme improves QoE by improving the average video quality and minimizing the quality change.

• Journal of Digital Contents Society
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• v.18 no.1
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• pp.159-165
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• 2017

In order to solve problems in automatic quality inspection of tablet capsules, computation-efficient image processing technique, appropriate threshold setting, edge detection and segmentation methods are required. And since existing automatic system for quality inspection of tablet capsules is of very high cost, it needs to be reduced through the realization of low-price hardware system. This study suggests a technique that uses low-cost camera module to obtain image and inspects dents on tablet capsules and sorting them by applying TLS curve fitting technique and edge-based image segmentation. In order to assess the performance, the major classifications algorithm of PCA, ICA and SVM are used to evaluate training time, test time and accuracy for capsule image area and curve fitting edge data sets.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.16 no.8
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• pp.1765-1772
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• 2012

Success rate of transplantation of body organs improved due to development of medical equipment and diagnostic technology. In particular, a liver transplant due to liver dysfunction has increased. With the development of image processing and analysis to obtain the volume for liver transplantation have increased the accuracy and efficiency. In this thesis, we try to reconstruct the regions of the liver within three dimensional images using the mevislab tool, which is effective in quick comparison and analysis of various algorithms, and in expedient development of prototypes. Liver is divided by applying threshold values and region growing method to the original image, and by removing noise and unnecessary entities through morphology and region filling, and setting of areas of interest. It is deemed that high temporal efficiency, and presentation of diverse range of comparison and analysis module application methods through usage of MeVisLab would make contribution towards expanding of baseline of medical image processing researches.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.34 no.5A
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• pp.381-390
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• 2009

In this paper, we propose a seamless intra MR-BS handover scheme based on IEEE802.16j transparent. The proposed scheme estimates the outage probability of mobile stations at a base station, finds the optimum relay user, and provides low handover latency for seamless data transmission. The simulation results show that the proposed scheme outperforms the conventional handover schemes in terms of the handover latency by 65% of conventional scheme. Moreover, the proposed scheme exhibits lower packet error rate compared with the conventional handover scheme when a mobile station moves to outside of the cell coverage and reduce both outage probability and the number of handover about 50% from setting forgetting factor and redundant threshold.