• The Transactions of The Korean Institute of Electrical Engineers
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• v.67 no.9
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• pp.1232-1238
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• 2018

This paper proposes methods for improving mass spectral resolution for a gas chromatograph mass spectrometer. The slope signs of the 1st and 2nd fitting functions for the ion signal block of each mass index are obtained, and the unnecessary element signals in the ion signal block are removed. The spectrum can be obtained by obtaining the second-order fitting function of the reconstructed ion signal block using only the effective ion signals. In addition, the resolution of the mass spectrum can be improved by correcting the error caused by the shift of the spectral peak position. To verify the performance of the proposed methods, computer simulations were performed using the actual ion signals obtained from the GC-MS system under development. Simulation results show that the proposed method is valid.

• Journal of Information Processing Systems
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• v.16 no.4
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• pp.991-1000
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• 2020

We propose a content-based image retrieval system that uses a combination of completed local binary pattern (CLBP) and color autocorrelogram. CLBP features are extracted on a multi-resolution multi-direction filtered domain of value component. Color autocorrelogram features are extracted in two dimensions of hue and saturation components. Experiment results revealed that the proposed method yields a lot of improvement when compared with the methods that use partial features employed in the proposed method. It is also superior to the conventional CLBP, the color autocorrelogram using R, G, and B components, and the multichannel decoded local binary pattern which is one of the latest methods.

• Korean Journal of Adult Nursing
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• v.25 no.1
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• pp.33-40
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• 2013

Purpose: The purpose of this study was to explore conflict resolution styles, marital intimacy and family functions among breast cancer patients and their spouses. Methods: The subjects were total 126 participants. Breast cancer patients who completed chemotherapy and or radiation along with their spouses. Data were collected using questionnaires with questions about conflict resolution styles, marital intimacy and family functions. Results: There were no differences between breast cancer patients and their spouses in verbal aggression, avoidance of conflict resolution styles and family functions. As patients reported using positive conflict resolution styles the spouse-perceived marital intimacy and family functions were higher. Those patients who perceived marital intimacy as lower they also reported more verbal aggression and avoidance. As breast cancer patients perceived family functions increasing, their spouses perception of both intimacy and family function increased. Conclusion: As these results, it should be considered as basic data to develop family intervention programs such as positive communication and effective stress management and improving of conflict resolution, intimacy and family functions among breast cancer patients and their spouses.

• Proceedings of the Korea Information Processing Society Conference
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• 2017.11a
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• pp.781-784
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• 2017

Face recognition systems are characterized by low invasiveness of acquisition, and increasingly better reliability. Such systems may not be applied effectively, when the images are in low resolution (LR) as in the case that photos are taken from long distances, typically public surveillance. In theory, the high resolution (HR) image reconstructed from an LR face image, applying a super resolution (SR) method, can be used for face recognition. However, existing face SR algorithms may not give satisfactory results in face recognition. This article investigates the very low resolution face recognition problem and introduces a partial differential equation (PDE)-based SR method for a face recognition system of convolutional neural network (CNN).

• Journal of the Institute of Electronics and Information Engineers
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• v.54 no.2
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• pp.38-43
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• 2017

Many studies about generating images of seabed using active sonar have been carried out but image resolution enhancement is still an important problem. Many methods have been proposed to improve sonar resolution and the approach using narrow beam width is commonly and widely applied to enhance azimuth resolution. Unfortunately, this has technical limitations to reduce the beam width. Therefore, signal processing techniques are essential to achieving higher azimuth resolution when an array with conventional beam width is employed. This paper proposes a new approach that utilizes overlapped beams to obtain higher resolution.

• 한국전자현미경학회:학술대회논문집
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• 2004.05a
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• pp.18-20
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• 2004

• Journal of KIISE
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• v.42 no.10
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• pp.1207-1221
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• 2015

This research was conducted both to analyze the determining factors of and to suggest resolution methods for the smart divide of adults over 65 years of age in the rapidly aging society of the 2000s and the smart society of the 2010s following the information society of the 1990s. The research model based on the Technology Acceptance Model (TAM) includes 6 determining factors derived from existing studies: Self Efficacy, Training, Accessibility, Playfulness, Cost Rationality, and Policy Support. Research data were collected through a survey given to a total of 243 older adults in 14 Senior Welfare Centers nationwide, and research hypotheses were verified by structural equation model (SEM) analysis. The results of this research that gives priority to the order of Political Support, Playfulness, Self Efficacy, Accessibility, Cost Rationality, and Training can be used to develop various resolution methods for the smart divide of adults over 65 years of age.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.14 no.9
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• pp.3745-3761
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• 2020

Low-rank representation methods already achieve many applications in the image reconstruction. However, for high-gradient image patches with rich texture details and strong edge information, it is difficult to find sufficient similar patches. Existing low-rank representation methods usually destroy image critical details and fail to preserve edge structure. In order to promote the performance, a new representation-based image super-resolution reconstruction method is proposed, which combines gradient domain guided image filter with the structure-constrained low-rank representation so as to enhance image details as well as reveal the intrinsic structure of an input image. Firstly, we extract the gradient domain guided filter of each atom in high resolution dictionary in order to acquire high-frequency prior information. Secondly, this prior information is taken as a structure constraint and introduced into the low-rank representation framework to develop a new model so as to maintain the edges of reconstructed image. Thirdly, the approximate optimal solution of the model is solved through alternating direction method of multipliers. After that, experiments are performed and results show that the proposed algorithm has higher performances than conventional state-of-the-art algorithms in both quantitative and qualitative aspects.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2020.11a
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• pp.205-207
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• 2020

This paper proposes a novel deep learning-based method to upsample a depth map. Most conventional methods estimate high-resolution depth map by modifying pixel value of given depth map using high-resolution color image and low-resolution depth map. However, these methods cause under- or over-shooting problems that restrict performance improvement. To overcome these problems, the proposed method iteratively performs grid warping scheme which shifts pixel values to restore blurred image for estimating high-resolution depth map. Experimental results show that the proposed method improves both quantitative and visual quality compared to the existing method.

• The Journal of the Acoustical Society of Korea
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• v.42 no.6
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• pp.529-535
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• 2023

Noise originating from incipient propeller cavitation is assumed to come from a limited number of sources emitting a broadband signal. Conventional methods for cavitation localization have limitations because they cannot distinguish adjacent sound sources effectively due to low accuracy and resolution. On the other hand, sparse Bayesian learning technique demonstrates high-resolution restoration performance for sparse signals and offers greater resolution compared to conventional cavitation localization methods. In this paper, an incipient propeller cavitation localization method using sparse Bayesian learning is proposed and shown to be superior to the conventional method in terms of accuracy and resolution through experimental data from a model ship.