• Journal of the Semiconductor & Display Technology
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• v.19 no.4
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• pp.71-76
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• 2020

In this paper, we propose a super-resolution method that reconstructs compressed low-resolution images into high-resolution images. We propose a CNN model with a small number of parameters, and even if quantization is applied to the proposed model, super-resolution can be implemented without deteriorating the image quality. To further improve the quality of the compressed low-resolution image, a new degradation model was proposed instead of the existing bicubic degradation model. The proposed degradation model is used only in the training process and can be applied by changing only the parameter values to the original CNN model. In the super-resolution image applying the proposed degradation model, visual artifacts caused by image compression were effectively removed. As a result, our proposed method generates higher PSNR values at compressed images and shows better visual quality, compared to conventional CNN-based SR methods.

• Journal of the Institute of Electronics Engineers of Korea TC
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• v.49 no.5
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• pp.59-65
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• 2012

In this paper, we investigate the compressed sensing (CS) algorithms for modeling a super-resolution near-field structure (super-RENS) disc system with a sparse Volterra filter. It is well known that the super-RENS disc system has severe nonlinear inter-symbol interference (ISI). A nonlinear system with memory can be well described with the Volterra series. Furthermore, CS can restore sparse or compressed signals from measurements. For these reasons, we employ the CS algorithms to estimate a sparse super-RENS read-out channel. The evaluation results show that the CS algorithms can efficiently construct a sparse Volterra model for the super-RENS read-out channel.

• Geophysics and Geophysical Exploration
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• v.14 no.4
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• pp.335-341
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• 2011

Most sensing and instrumentation systems should have very higher sampling rate than required data rate not to miss important information. This means that the system can be inefficient in some cases. This paper introduces two new research areas about information acquisition with high accuracy from less number of sampled data. One is Compressed Sensing technology (which obtains original information with as little samples as possible) and the other is Super-Resolution technology (which gains very high-resolution information from restrictively sampled data). This paper explains fundamental theories and reconstruction algorithms of compressed sensing technology and describes several applications to geophysical exploration. In addition, this paper explains the fundamentals of super-resolution technology and introduces recent research results and its applications, e.g. FRI (Finite Rate of Innovation) and LIMS (Least-squares based Iterative Multipath Super-resolution). In conclusion, this paper discusses how these technologies can be used in geophysical exploration systems.

• Journal of Korea Multimedia Society
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• v.20 no.7
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• pp.1148-1155
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• 2017

This study examined the storytelling characteristics of the super-compressed web drama "72 seconds". By analyzing all seasonal episodes of "72 seconds" and applying the various storytelling methodologies and related theories, this paper derived the main storytelling characteristics of "72 seconds" as follows. First, through the composition of the microscopic non-plot, the story value of empathy and fun is maximized, even though there is no dramatic composition compared to the general movie or drama. Second, by the specialization of everyday life, it leads to the transition from everyday experience to the new context. In other words, it provides a consensus through the cognitive expansion and interest by unfamiliarity of the ordinary experience to the audience. Third, based on the characteristics of super-compression and short theme, it utilizes fully stylistic narration like rapping. This makes the audience feel novel and further enhances the branding effect of content. And finally, based on various hybridity and variation, it uses remediation actively in all respects, especially comedy genre and comic factor.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2018.11a
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• pp.59-61
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• 2018

Highly compressed images typically not only have low resolution, but are also affected by compression artifacts. Performing image super-resolution (SR) directly on highly compressed image would simultaneously magnify the blocking artifacts. In this paper, a SR method based on deep learning is proposed. The method is an end-to-end trainable deep convolutional neural network which performs SR on compressed images so as to reduce compression artifacts and improve image resolution. The proposed network is divided into compression artifacts removal (CAR) part and SR reconstruction part, and the network is trained by three-step training method to optimize training procedure. Experiments on JPEG compressed images with quality factors of 10, 20, and 30 demonstrate the effectiveness of the proposed method on commonly used test images and image sets.

• Proceedings of the Korea Information Processing Society Conference
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• 2023.05a
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• pp.479-481
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• 2023

Generative Adversarial Networks (GANs) have facilitated substantial improvement in single-image super-resolution (SR) by enabling the generation of photo-realistic images. However, the high memory requirements of GAN-based SRs (mainly generators) lead to reduced performance and increased energy consumption, making it difficult to implement them onto resource-constricted devices. In this study, we propose an efficient and compressed architecture for the SR-GAN (generator) model using the model compression technique Knowledge Distillation. Our approach involves the transmission of knowledge from a heavy network to a lightweight one, which reduces the storage requirement of the model by 58% with also an increase in their performance. Experimental results on various benchmarks indicate that our proposed compressed model enhances performance with an increase in PSNR, SSIM, and image quality respectively for x4 super-resolution tasks.

• Journal of the Korean Society of Manufacturing Process Engineers
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• v.1 no.1
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• pp.48-54
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• 2002

In industrially advanced countries, environmentally conscious machining was eagerly studied because of ecological and economical reasons. As the environmental regulations become stricter, new machining technologies which take environmental aspects into consideration are being developed Industry and research institutions established applications for dry, semi-dry, oil-mist and compressed cold air machining. This paper investigates the performance of new compressed cold air system for environmentally conscious machining and evaluates machinability of dry and new compressed cold air machining. A series of tests are carried out using measuring eqipments under dry and compressed cold air machining.

• 한국지구물리탐사학회:학술대회논문집
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• 2011.10a
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• pp.3-12
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• 2011

• Restorative Dentistry and Endodontics
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• v.24 no.1
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• pp.166-179
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• 1999

Apical sealing is essential for the success of surgical endodontic treatment. Root-end cavity is apt to be contaminated with moisture or blood, and is not always easy to be dried completely. The purpose of this study was to evaluate the influence of dry methods of retrocavity on the apical seal in endodontic surgery. Apical seal was investigated through the evaluation of apical leakage and adaptation of filling material over the cavity wall. To investigate the influence of various dry methods on the apical leakage, 125 palatal roots of extracted human maxillary molar teeth were used. The clinical crown of each tooth was removed at 10 mm from the root apex using a slow-speed diamond saw and water spray. Root canals of the all the specimens were prepared with step-back technique and filled with gutta-percha by lateral condensation method. After removing of the coronal 2 mm of filling material, the access cavities were closed with Cavit$^{(R)}$. Two coats of nail polish were applied to the external surface of each root. Apical three millimeters of each root was resected perpendicular to the long axis of the root with a diamond saw. Class I retrograde cavities were prepared with ultrasonic instruments. Retrocavities were washed with physiologic saline solution and dried with various methods or contaminated with human blood. Retrocavities were filled either with IRM, Super EBA or composite resin. All the specimens were immersed in 2% methylene blue solution for 7 days in an incubator at $37^{\circ}C$. The teeth were dissolved in 14 ml of 35% nitric acid solution and the dye present within the root canal system was returned to solution. The leakage of dye was quantitatively measured via spectrophotometric method. The obtained data were analysed statistically using one-way ANOVA and Duncan's Multiple Range Test. To evaluate the influence of various dry methods on the adaptation of filling material over the cavity wall, 12 palatal roots of extracted human maxillary molar teeth were used. After all the roots were prepared and filled, and retrograde cavities were made and filled as above, roots were sectioned longitudinally. Filling-dentin interface of cut surfaces were examined by scanning electron microscope. The results were as follows: 1. Cavities dried with paper point or compressed air showed less leakage than those dried with cotton pellet in Super EBA filled cavity (p<0.05). However, there was no difference between paper point- and compressed air-dried cavities. 2. When cavities were dried with compressed air, dentin-bonded composite resin-filled cavities showed less apical leakage than IRM- or Super EBA-filled ones (p<0.05). 3. Regardless of the filling material, cavities contaminated with human blood showed significantly more apical leakage than those dried with compressed air after saline irrigation (p<0.05). 4. Outer half of the cavity showed larger dentin-filling interface gap than inner half did when cavities were filled with IRM or Super EBA. 5. In all the filling material groups, cavities contaminated with blood or dried with cotton pellets only showed larger defects at the base of the cavity than ones dried with paper points or compressed air.

• Proceedings of the KSR Conference
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• 2011.10a
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• pp.2064-2071
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• 2011

We are developing an innovative super-speed land transportation system running in a partial vacuum in tunnels with small inside diameter to reduce the aerodynamic drag forces. This paper presents the experimental results obtained on a small scale model when a super-speed train model passing through a tunnel with small inside diameter and a partial vacuum to reduce the aerodynamic drag forces. The experiments were performed on a 1/52-scale moving model rig in which a train model with a diameter of 58 mm and a length of 603 mm was accelerated in a launching tube with 12.27 m length by means of the compressed air launcher and then passed through a tunnel model with 17.149 m length. The partial vacuum was maintained in the tunnel in order to reduce the energy consumption of the propulsion system of the super-speed tube train at super-speed of 700 km/h. In this study, the blockage ratio of train to tunnel model is 0.336. Experimental results show the nonlinear effects of the vacuum on the speed-up of the train model in the tunnel model under the partial vacuum up to 0.21 atm and at the velocity up to 684 km/h. This paper is first study for experiments on the speed-up of a super-speed train model in the partial vacuum tunnels.