• Journal of Broadcast Engineering
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• v.23 no.6
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• pp.768-779
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• 2018

In this paper, we propose a novel video quality function for video processing based on MSSSIM to select an appropriate video processing filter and to accommodate multiple processing filters to each pixel block in a picture frame by a mathematical selection law so as to maintain video quality and to reduce the bitrate of compressed video. In viewpoint of video compression, since the properties of video quality and bitrate is different for each picture of video frames and for each areas in the same frame, it is difficult for the video filter with single property to satisfy the object of increasing video quality and decreasing bitrate. Consequently, to maintain the subjective video quality in spite of decreasing bitrate, we propose the methodology about the MSSSIM as the measure of subjective video quality, the KL-Divergence as the measure of bitrate, and the combination method of those two measurements. Moreover, using the proposed combinatorial measurement, when we use the multiple image filters with mutually different properties as a pre-processing filter for video, we can verify that it is possible to compress video with maintaining the video quality under decreasing the bitrate, as possible.

• Korean Journal of Remote Sensing
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• v.37 no.3
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• pp.367-378
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• 2021

Field compost is a representative non-point pollution source for livestock. If the field compost flows into the water system due to rainfall, nutrients such as phosphorus and nitrogen contained in the field compost can adversely affect the water quality of the river. In this paper, we propose a method for detecting field compost using unmanned aerial vehicle images and deep learning-based semantic segmentation. Based on 39 ortho images acquired in the study area, about 30,000 data were obtained through data augmentation. Then, the accuracy was evaluated by applying the semantic segmentation algorithm developed based on U-net and the filtering technique of Open CV. As a result of the accuracy evaluation, the pixel accuracy was 99.97%, the precision was 83.80%, the recall rate was 60.95%, and the F1-Score was 70.57%. The low recall compared to precision is due to the underestimation of compost pixels when there is a small proportion of compost pixels at the edges of the image. After, It seems that accuracy can be improved by combining additional data sets with additional bands other than the RGB band.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.30 no.6
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• pp.1087-1101
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• 2020

Various security devices are used to protect internal networks and valuable information from rapidly evolving cyber attacks. Firewall, which is the most commonly used security device, tries to prevent malicious attacks based on a text-based filtering rule (i.e., access control policy), by allowing or blocking access to communicate between inside and outside environments. However, in order to protect a valuable internal network from large networks, it has no choice but to increase the number of access control policy. Moreover, the text-based policy requires time-consuming and labor cost to analyze various types of vulnerabilities in firewall. To solve these problems, this paper proposes a 3D-based hierarchical visualization method, for intuitive analysis and management of access control policy. In particular, by providing a drill-down user interface through hierarchical architecture, Can support the access policy analysis for not only comprehensive understanding of large-scale networks, but also sophisticated investigation of anomalies. Finally, we implement the proposed system architecture's to verify the practicality and validity of the hierarchical visualization methodology, and then attempt to identify the applicability of firewall data analysis in the real-world network environment.

• Journal of the Institute of Convergence Signal Processing
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• v.23 no.1
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• pp.28-36
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• 2022

Currently, the automation and intelligence of the shipbuilding industry have improved its work production capacity and cost competitiveness, but the reduction rate of safety accidents among industrial site workers is still low and the damage caused by safety accidents is very serious, so there is a need for improvement according to the workplace. This research aims to demonstrate the connectivity between smart safety helmets in the demonstration area to verify the effectiveness along with the development of smart helmets for worker protection and environmental safety in shipyards. For efficient communication between workers, impact noise of over 95dB was confirmed in the workplace, and noise reduction was required. To solve this problem, the filtering performance was compared and analyzed using the Butterworth, Chebyshev, and elliptic algorithms. The connectivity test and noise reduction method between smart helmets proposed in this study will increase the usability and safety of the field through the development of advanced smart helmets tailored to the shipbuilding workplace in the future.

• Journal of Korean Society of Occupational and Environmental Hygiene
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• v.32 no.2
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• pp.146-152
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• 2022

Objectives: The purpose of this study is to confirm whether there is a factor to affect the evaluation of fit test of a 2nd class half masks using a OPC test method. Methods: Total 34 adults including Males and Females were tested using OPC-based fit testing equipment while wearing a 2nd class half filtered mask. Results: 1. The result of measuring face dimensions using different tools such as a 3D scanner and digital calipers revealed that the variation of lip width was not statistically significant because there was only a difference of about 4 mm. However, it showed that a difference in face length was statistically significant enough with 10 mm(p<0.000). 2. The fit factor for each exercise stage according to gender was the highest at 124.54(p<0.001) in Step 3, and the fit factor was the lowest at 73.75 in Step 1. 3. In the evaluation of the degree of fit factor according to gender, female passed 67.44%, which was higher than the value in male(p<0.038). 4. The acceptance rate of the group having a face length of shorter than 110 mm was 91.67%. On the other hand, the acceptance rate of the group with a face length of longer than 110 mm was 47.27%(p<0.000). 5. The fit test was possible because the fit factor with 2nd class half masks corresponding to FFP1(Filtering Face Piece 1) was passed 55% or more. Conclusions: The test results showed that using a 2nd class half filtered mask, it is important to wear a properly designed mask so that face size does not affect the fit factor.

• The Journal of the Acoustical Society of Korea
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• v.41 no.3
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• pp.326-334
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• 2022

In this paper, we propose speech enhancement algorithm as a pre-processing for robust speech recognition in noisy environments. Auxiliary-function-based Independent Vector Analysis (AuxIVA) is performed with weighted covariance matrix using time-varying variances with scaling factor from target masks representing time-frequency contributions of target speech. The mask estimates can be obtained using Neural Network (NN) pre-trained for speech extraction or diffuseness using Coherence-to-Diffuse power Ratio (CDR) to find the direct sounds component of a target speech. In addition, outputs for omni-directional noise are closely chained by sharing the time-varying variances similarly to independent subspace analysis or IVA. The speech extraction method based on AuxIVA is also performed in Independent Low-Rank Matrix Analysis (ILRMA) framework by extending the Non-negative Matrix Factorization (NMF) for noise outputs to Non-negative Tensor Factorization (NTF) to maintain the inter-channel dependency in noise output channels. Experimental results on the CHiME-4 datasets demonstrate the effectiveness of the presented algorithms.

• Journal of Korean Society of Disaster and Security
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• v.15 no.3
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• pp.79-88
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• 2022

Cable-supported bridges, as important large infrastructures, require a long-term and systematic maintenance strategy. In particular, various methods have been proposed to secure safety for the bridges, such as installing various types of sensor on members in the bridges, and setting management thresholds. It is evidently necessary to propose a strategic plan to efficiently manage increasing number of cable-supported bridges and data collected from a number of sensors. This study aims to develop an analysis tool that can automatically remove abnormal signals and calculate statistical results for the purpose of efficiently analyzing a wide range of data collected from a long span bridge measurement system. To develop the tool, basic information such as the types and quantity of sensors installed in long span bridges and signal characteristics of the collected data were analyzed. Thereafter, the Humpel filtering method was used to determine the presence or absence of an abnormality in the signal and then filtered. The statistical results with filtered data were shown. Finally, one cable-stayed bridge and one suspension bridge currently in use were chosen as the target bridges to verify the performance of the developed tool. Signal processing and statistical analysis with the tool were performed. The results are similar to the results reported in the existing work.

• The Journal of the Acoustical Society of Korea
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• v.42 no.5
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• pp.403-411
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• 2023

Functional ultrasound imaging, such as elasticity imaging and micro-blood flow Doppler imaging, enhances diagnostic capability by providing useful mechanical and functional information about tissues. However, the implementation of functional ultrasound imaging poses limitations such as the storage of vast amounts of data in Radio Frequency (RF) data acquisition and processing. In this paper, we propose a sub-Nyquist approach that reduces the amount of acquired axial samples for efficient shear-wave elasticity imaging. The proposed method acquires data at a sampling rate one-third lower than the conventional Nyquist sampling rate and tracks shear-wave signals through RF signals reconstructed using band-pass filtering-based interpolation. In this approach, the RF signal is assumed to have a fractional bandwidth of 67 %. To validate the approach, we reconstruct the shear-wave velocity images using shear-wave tracking data obtained by conventional and proposed approaches, and compare the group velocity, contrast-to-noise ratio, and structural similarity index measurement. We qualitatively and quantitatively demonstrate the potential of sub-Nyquist sampling-based shear-wave elasticity imaging, indicating that our approach could be practically useful in three-dimensional shear-wave elasticity imaging, where a massive amount of ultrasound data is required.

• Journal of the Korean Society of Food Culture
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• v.22 no.5
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• pp.603-608
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• 2007

Optimal winterizing condition of com oil was cooling temperature of bleached oil from $105^{\circ}C$ to $40^{\circ}C$. Then, filtering it after keeping $1{\sim}2^{\circ}C$ by lowering the temperature gradually with treating perlite of 0.3%(w/w) amount about bleached oil and stirring. We could measure that triglyceride(TG) that extracted from lipid components from spent perlite(SP) obtained through filtration after winterizing by SACC method is major causing materials of clouding in com oil. The result of separating TG fraction by agentation TLC was that it classified into 4 kinds -U3, SU2, S2U, S3 type and the most were U3 type. From this, it's easy to identify cause of clouding in com oil is TG fraction and most of them form wax materials that can observed. The results were they kept clear appearance at $0^{\circ}C$ generally during 39.6 to 96.5 hours, especially the result of A sample that had the lowest temperature condition while they have some difference by condition of treating temperature.

• Korean Journal of Remote Sensing
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• v.39 no.6_3
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• pp.1747-1761
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• 2023

Wetlands, defined as lands periodically inundated or exposed during the year, are crucial for sustaining biodiversity and filtering environmental pollutants. The importance of mapping and monitoring their topographical changes is therefore paramount. This study focuses on the topographical variations at the Incheon River estuary wetland post-restoration, noting a lack of adequate prior measurements. Using a multi-temporal Sentinel-1 dataset from October 2014 to March 2023, we mapped long-term variations in water bodies and detected topographical change anomalies using a pixel-frequency approach. Our analysis, based on 196 Sentinel-1 acquisitions from an ascending orbit, revealed significant topography changes. Since 2020, employing the pixel-frequency technique, we observed area increases of +0.0195, 0.0016, 0.0075, and 0.0163 km² in water level sections at depths of 2-3 m, 1-2 m, 0-1 m, and less than 0 m, respectively. These findings underscore the effectiveness of the wetland restoration efforts in the area.