• Korean Journal of Materials Research
• /
• v.29 no.1
• /
• pp.37-42
• /
• 2019

This study investigates Ag coated $Cu_2O$ nanoparticles that are produced with a changing molar ratio of Ag and $Cu_2O$. The results of XRD analysis reveal that each nanoparticle has a diffraction pattern peculiar to Ag and $Cu_2O$ determination, and SEM image analysis confirms that Ag is partially coated on the surface of $Cu_2O$ nanoparticles. The conductive paste with Ag coated $Cu_2O$ nanoparticles approaches the specific resistance of $6.4{\Omega}{\cdot}cm$ for silver paste(SP) as $(Ag)/(Cu_2O)$ the molar ratio increases. The paste(containing 70 % content and average a 100 nm particle size for the silver nanoparticles) for commercial use for mounting with a fine line width of $100{\mu}m$ or less has a surface resistance of 5 to $20{\mu}{\Omega}{\cdot}cm$, while in this research an Ag coated $Cu_2O$ paste has a larger surface resistance, which is disadvantageous. Its performance deteriorates as a material required for application of a fine line width electrode for a touch panel. A touch panel module that utilizes a nano imprinting technique of $10{\mu}m$ or less is expected to be used as an electrode material for electric and electronic parts where large precision(mounting with fine line width) is not required.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
• /
• 2019.05a
• /
• pp.169-170
• /
• 2019

Lately, as artificial intelligence becomes a source of global competitiveness, the government is strategically fostering artificial intelligence that is the base technology of future new industries such as autonomous vehicles, drones, and robots. Domestic artificial intelligence research and services have been launched mainly in Naver and Kakao, but their size and level are weak compared to overseas. Recently, deep learning has been conducted in recent years while recording innovative performance in various pattern recognition fields including speech recognition and image recognition. In addition, deep running has attracted great interest from industry since its inception, and global information technology companies such as Google, Microsoft, and Samsung have successfully applied deep learning technology to commercial products and are continuing research and development. Therefore, we will look at artificial intelligence which is attracting attention based on previous research.

• Journal of IKEEE
• /
• v.25 no.1
• /
• pp.180-192
• /
• 2021

One widely used algorithm for image recognition and pattern detection is the convolution neural network (CNN). To efficiently handle convolution operations, which account for the majority of computations in the CNN, we use hardware accelerators to improve the performance of CNN applications. In using these hardware accelerators, the CNN fetches data from the off-chip DRAM, as the massive computational volume of data makes it difficult to derive performance improvements only from memory inside the hardware accelerator. In other words, data communication between off-chip DRAM and memory inside the accelerator has a significant impact on the performance of CNN applications. In this paper, a simulator for the CNN is developed to analyze the main memory or DRAM access with respect to the size of the on-chip memory or global buffer inside the CNN accelerator. For AlexNet, one of the CNN architectures, when simulated with increasing the size of the global buffer, we found that the global buffer of size larger than 100kB has 0.8x as low a DRAM access count as the global buffer of size smaller than 100kB.

• Journal of Digital Convergence
• /
• v.19 no.1
• /
• pp.343-348
• /
• 2021

This study investigated the method of constructing and combining blocks based on the atomic design system in order to propose a framework for rescue of a reusable design system. For that, I first looked at the necessity of a design system and examples of snow white, skeuomorphic design, flat design, and material design. In addition, molecules, atoms, organisms, templates and pages of atomic design using the principles of chemistry as metaphors were defined through literature studies. In order to implement a new framework, an interface inventory was constructed, and among them, font, color, image and control elements were extracted as core visual elements, and guidelines were defined, and molecular elements were classified and composed of atoms based on them. Blocks are constructed in the form of blocks based on the design pattern most used in the content inventory, and the framework is constructed to implement a layout based on a visual grid and design a page through a combination of blocks. The significance of this paper is that the new framework helps team consistency and collaboration by reusing blocks and supports file sharing and updating.

• Journal of Broadcast Engineering
• /
• v.25 no.6
• /
• pp.911-921
• /
• 2020

Recently, MPEG-I (Immersive) has been exploring compression performance through standardization projects for immersive video. The MPEG Immersion Video (MIV) standard technology is intended to provide limited 6DoF based on depth map-based image rendering (DIBR). MIV is a model that processes the Basic View and the residual information into an Additional View, which is a collection of patches. Atlases have the unique characteristics depending on the kind of the view they are included, requiring consideration of the compression efficiency. In this paper, the performance comparison analysis of screen content coding tools such as intra block copy (IBC) is conducted, based on the pattern of various views and patches repetition. It is demonstrated that the proposed method improves coding performance around -15.74% BD-rate reduction in the MIV.

• Journal of the Korea Institute of Information Security & Cryptology
• /
• v.17 no.5
• /
• pp.39-53
• /
• 2007

The purpose of this paper is the development of a compensation algorithm by which the interoperability of fingerprint recognition can be improved among various different fingerprint sensor. In order to compensate for the different characteristics of fingerprint sensor, an initial evaluation of the sensors using both the ink-stamped method and the flat artificial finger pattern method was undertaken. This paper proposes Common resolution method and Relative resolution method for compensating different resolution of fingerprint images captured by disparate sensors. Both methods can be applied to image-level and minutia-level. In order to compensate the direction of minutiae in minutia-level, Unit vector method is proposed. The EER of the proposed method was improved by average 64.8% better than before compensation. This paper will make a significant contribution to interoperability in the system integration using different sensors.

• Journal of Biomedical Engineering Research
• /
• v.42 no.1
• /
• pp.25-30
• /
• 2021

Objective: The aim of this study is to consider the effect of skin tissue necrosis by improving blood flow in animal skin models for low frequency pulsed electromagnetic fields (LF_PEMF) stimulation. Methods: Twenty rats (Wistar EPM-1 male, 280-320 g) were randomly divided into control groups (n=10) and the PEMF groups (n=10). To induce necrosis of the skin tissue, skin flap was treated in the back of the rat, followed by isolation film and skin flap suturing. Subsequently, the degree of necrosis of the skin tissue was observed for 7 days. The control group did not perform any stimulation after the procedure. For the PEMF group, LF_PEMF (1 Hz, 10 mT) was stimulated in the skin flap area, for 30 minutes a day and 7 days. Cross-polarization images were acquired at the site and skin tissue necrosis patterns were analyzed. Results: In the control group, skin tissue necrosis progressed rapidly over time. In the PEMF group, skin tissue necrosis was slower than the control group. In particular, no further skin tissue necrosis progress on the day 6. Over time, a statistically significant difference from the continuous necrosis progression pattern in the control group was identified (p<0.05). Conclusions: It was confirmed that low frequency pulsed electromagnetic fields (LF_PEMF) stimulation can induce relaxation of skin tissue necrosis.

• Journal of Korean Society of Industrial and Systems Engineering
• /
• v.43 no.4
• /
• pp.93-106
• /
• 2020

This research explores how imported automobile companies can develop their strategies to improve the outcome of their recalls. For this, the researchers analyzed patterns of recall demand, classified recall types based on the demand patterns and examined response strategies, considering plans on how to procure parts and induce customers to visit workshops, recall execution capacity and costs. As a result, recalls are classified into four types: U-type, reverse U-type, L- type and reverse L-type. Also, as determinants of the types, the following factors are further categorized into four types and 12 sub-types of recalls: the height of maximum demand, which indicates the volatility of recall demand; the number of peaks, which are the patterns of demand variations; and the tail length of the demand curve, which indicates the speed of recalls. The classification resulted in the following: L-type, or customer-driven recall, is the most common type of recalls, taking up 25 out of the total 36 cases, followed by five U-type, four reverse L-type, and two reverse U-type cases. Prior studies show that the types of recalls are determined by factors influencing recall execution rates: severity, the number of cars to be recalled, recall execution rate, government policies, time since model launch, and recall costs, etc. As a component demand forecast model for automobile recalls, this study estimated the ARIMA model. ARIMA models were shown in three models: ARIMA (1,0,0), ARIMA (0,0,1) and ARIMA (0,0,0). These all three ARIMA models appear to be significant for all recall patterns, indicating that the ARIMA model is very valid as a predictive model for car recall patterns. Based on the classification of recall types, we drew some strategic implications for recall response according to types of recalls. The conclusion section of this research suggests the implications for several aspects: how to improve the recall outcome (execution rate), customer satisfaction, brand image, recall costs, and response to the regulatory authority.

• Journal of the Korea Convergence Society
• /
• v.12 no.11
• /
• pp.27-33
• /
• 2021

With increasing interest in key areas of the 4th industrial revolution such as artificial intelligence, deep learning and big data, scientific approaches have developed in order to overcome the limitations of traditional decision-making methodologies. These scientific techniques are mainly used to predict the direction of financial products. In this study, the factors of apartment prices, which are of high social interest, were analyzed through SOM. For this analysis, we extracted the real prices of the apartments and selected a total of 16 input variables that would affect these prices. The data period was set from 1986 to 2021. As a result of examining the characteristics of the variables during the rising and faltering periods of the apartment prices, it was found that the statistical tendencies of the input variables of the rising and the faltering periods were clearly distinguishable. I hope this study will help us analyze the status of the real estate market and study future predictions through image learning.

• Journal of the Korea Institute of Information and Communication Engineering
• /
• v.25 no.12
• /
• pp.1874-1881
• /
• 2021

Black ice, which occurs mainly on the road, vehicle traffic bridges and tunnel entrances due to the sub-zero temperature due to the slip of the road due to heavy snow, is not recognized because the image of asphalt is transmitted in the driver's view, so the vehicle loses braking power because it causes serious loss of life and property. In this paper, we propose a method to identify the black ice by using infrared camera and to identify the road condition by using deep learning to compensate for the disadvantages of existing black ice detection methods (artificial satellite imaging, checking the pattern of slip by ultrasonic reception, measuring the temperature of the road surface, and checking the difference in friction force of the tire during vehicle driving) and to reduce the size of the sensor to detect black ice.