• 산업기술연구
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• 제39권1호
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• pp.41-45
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• 2019

Hydrogen sulfide ($H_2S$) is mainly produced along with methane and hydrocarbons in many gas fields as well as hydrodesulfurization processes of crude oils containing sulfur compounds and the emission of $H_2S$ has a considerable effect on both environmental problem and human health aspects due to formation of, e.g. acid rain and smog. In recent years, ionic liquids (ILs) have been proposed as the most promising solvents for $CO_2$ and hazardous pollutants capture, such as $H_2S$ and sulfur dioxide ($SO_2$). In this work, we demonstrate the use of the predictive COSMO-SAC model for the prediction of Henry's law constant of $H_2S$ in ILs. Furthermore, the method is used to screen for potential IL candidates for $H_2S$ capture from a set of 2,624 ILs formed from 82 cations and 32 anions. The effects of cation on the Henry's law constant of $H_2S$ such as (i) the variation of the alkyl chain length on cation, (ii) the substituent of methyl group ($-CH_3$) for H in C(2) position and (iii) the change of ring structure for cation family are clearly predicted by COSMO-SAC model.

• 한국방사선학회논문지
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• 제13권5호
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• pp.785-790
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• 2019

인공지능, 빅데이터, 사물인터넷 등 기술간 융합과 고도화가 지역주력산업에도 큰 영향을 미치고 있다. 모든 기술분야가 기술간-산업간 연결이 되어 융합된 기술로 활용되고 있다. 최근 기술동향을 파악하기 위해 특허정보를 이용한 키워드검색을 통해 기술동향 조사 및 분석으로 쉽게 파악이 가능하게 되었다. 본 연구는 방사선 기술발전에서 4차 산업혁명시대 융합기술을 적용한 특허동향을 파악하고 방사선 관련 산업기술경쟁력 강화 및 활용방안을 위한 특허동향 및 분석을 제시하여 수요기술 발굴과 미래 유망기술 예측에 활용하고자 한다.

• 대한금속재료학회지
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• 제48권5호
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• pp.462-468
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• 2010

Carbon Nanotubes (CNTs) have recently emerged as a material with outstanding properties. It has shown promising potential for applications in many engineering fields as electronic devices, thermal conductors, and light-weight composites. Researchers have investigated their use as reinforcements in themetal matrix composites of CNTs. In the present work, we decorated CNTs with Ni particles by electroless plating. The CNTs were wet-ball milled for various milling times with a nickel sulfate solution. The precipitated Ni particles were observed mainly by FESEM. In this study, the dispersion of the CNTs and Ni particles was improved with the addition of the surfactant. Also, as the CNTs were shortened and widened by an increased ball milling time, the size of the precipitated Ni particles increased. It was estimated that the CNTs were deformed and caused some defects on their surface during the ball milling process. Those defects were assumed to be heterogeneous nucleation sites for the Ni particles.

• 한국분말재료학회지
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• 제28권6호
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• pp.509-517
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• 2021

Smart materials capable of changing their characteristics in response to stimuli such as light, heat, pH, and electric and magnetic fields are promising for application to flexible electronics, soft robotics, and biomedicine. Compared with conventional rigid materials, these materials are typically composed of soft materials that improve the biocompatibility and allow for large and dynamic deformations in response to external environmental stimuli. Among them, smart magnetic materials are attracting immense attention owing to their fast response, remote actuation, and wide penetration range under various conditions. In this review, we report the material design and fabrication of smart magnetic materials. Furthermore, we focus on recent advances in their typical applications, namely, soft magnetic actuators, sensors for self-assembly, object manipulation, shape transformation, multimodal robot actuation, and tactile sensing.

• International Journal of Computer Science & Network Security
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• 제22권10호
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• pp.271-281
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• 2022

Manual seed classification challenges can be overcome using a reliable and autonomous seed purity identification and classification technique. It is a highly practical and commercially important requirement of the agricultural industry. Researchers can create a new data mining method with improved accuracy using current machine learning and artificial intelligence approaches. Seed classification can help with quality making, seed quality controller, and impurity identification. Seeds have traditionally been classified based on characteristics such as colour, shape, and texture. Generally, this is done by experts by visually examining each model, which is a very time-consuming and tedious task. This approach is simple to automate, making seed sorting far more efficient than manually inspecting them. Computer vision technologies based on machine learning (ML), symmetry, and, more specifically, convolutional neural networks (CNNs) have been widely used in related fields, resulting in greater labour efficiency in many cases. To sort a sample of 3000 seeds, KNN, SVM, CNN and CNN-SVM hybrid classification algorithms were used. A model that uses advanced deep learning techniques to categorise some well-known seeds is included in the proposed hybrid system. In most cases, the CNN-SVM model outperformed the comparable SVM and CNN models, demonstrating the effectiveness of utilising CNN-SVM to evaluate data. The findings of this research revealed that CNN-SVM could be used to analyse data with promising results. Future study should look into more seed kinds to expand the use of CNN-SVMs in data processing.

• 한국정보시스템학회지:정보시스템연구
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• 제31권2호
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• pp.19-43
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• 2022

Purpose Due to the COVID-19 pandemic, many companies are building virtual workplaces based on virtual reality technology. Through this study, we intend to identify the trend of convergence and convergence research between virtual reality technology and work space, and suggest future promising fields based on this. Design/methodology/approach For this purpose, 12,250 bibliographic data of research papers related to Virtual Reality (VR) and Workplace were collected from Scopus from 1982 to 2021. The bibliographic data of the collected papers were analyzed using Text Mining and Pathfinder Network, Parallel Neighbor Clustering, Nearest Neighbor Centrality, and Triangle Betweenness Centrality. Through this, the relationship between keywords by period was identified, and network analysis and visualization work were performed for virtual reality-based workplace research. Findings Through this study, it is expected that the main keyword knowledge structure flow of virtual reality-based workplace convergence research can be identified, and the relationship between keywords can be identified to provide a major measure for designing directions in subsequent studies.

• 한국인공지능학회지
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• 제11권1호
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• pp.17-24
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• 2023

With the continuous growth in the amount of data collected and analyzed, deep learning has become increasingly popular for extracting meaningful insights from various fields. However, hardware limitations pose a challenge for achieving meaningful results with limited data. To address this challenge, this paper proposes an algorithm that leverages the characteristics of convolutional neural networks (CNNs) to reduce the size of image datasets by 20% through smoothing and shrinking the size of images using color elements. The proposed algorithm reduces the learning time and, as a result, the computational load on hardware. The experiments conducted in this study show that the proposed method achieves effective learning with similar or slightly higher accuracy than the original dataset while reducing computational and time costs. This color-centric dataset construction method using image smoothing techniques can lead to more efficient learning on CNNs. This method can be applied in various applications, such as image classification and recognition, and can contribute to more efficient and cost-effective deep learning. This paper presents a promising approach to reducing the computational load and time costs associated with deep learning and provides meaningful results with limited data, enabling them to apply deep learning to a broader range of applications.

• 한국표면공학회지
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• 제56권2호
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• pp.115-124
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• 2023

Anodization is an electrochemical process that electrochemically converts a metal surface into an oxide layer, resulting in enhanced corrosion resistance, wear resistance, and improved aesthetic appearance. Local anodization, also known as selective anodization, is a modified process that enables specific regions or patterns on the metal surface to undergo anodization instead of the entire surface. Several methods have been attempted to produce oxide layers via localized anodic oxidation, such as using a mask or pre-patterned substrate. However, these methods are often intricate, time-consuming, and costly. Conversely, the direct writing or patterning approach is a more straightforward and efficient way to fabricate the oxide layers. This review paper intends to enhance our comprehension of local anodization and its potential applications in various fields, including the development of nanotechnologies. The application of anodization is promising in surface engineering, where the anodic oxide layer serves as a protective coating for metals or modifies the surface properties of materials. Furthermore, anodic oxidation can create micro- and nano-scale patterns on metal surfaces. Overall, the development of efficient and cost-effective anodic oxidation methods is essential for the advancement of various industries and technologies.

• 한국정보통신학회:학술대회논문집
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• 한국정보통신학회 2021년도 추계학술대회
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• pp.432-433
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• 2021

가상의 세계인 메타버스를 구축하는 기술은 가상증강현실과 전자통신기술이 기반을 이루며, 하드웨어와 소프트웨어 등 여러 학문분야가 융합된 기술적 특성을 가지고 있고, 4차 산업혁명 발전에 주도적 역할을 할 기술이다. 메타버스는 아바타를 통해 사용자들이 놀이, 업무, 소비, 소통 등 각종 활동을 할 수 있는 플랫폼으로 비대면 사회에 새로운 산업으로 자리매김을 하고 있다. 본 논문에서는 메타버스에 대한 관심이 증가하면서 신 시장을 창출할 미래 유망 산업으로 발전이 기대되고 있는 가운데 메타버스의 활용분야를 살펴보고 미래 메타버스 산업에 대한 발전방향에 대한 고찰을 하고자한다.

• Nuclear Engineering and Technology
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• 제55권7호
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• pp.2567-2571
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• 2023

Scintillator materials are widely used in the medical and industrial fields for imaging systems using gamma cameras. In this study, image evaluation is performed by modeling a gamma camera system based on a lutetium-yttrium oxyorthosilicate (LYSO) scintillation detector using a pinhole collimator that can improve the spatial resolution. A LYSO detector-based gamma camera system is modeled using a Monte Carlo simulation tool. The geometric concept of the pinhole collimator is designed using various magnification factors, and the spatial resolution is measured using the acquired source image. To evaluate the resolution, the full width at half maximum (FWHM) and natural image quality assessment (NIQE), a no-reference-based parameter, are used. We confirm that the FWHM and NIQE values decrease simultaneously when the diameter of the pinhole collimator increases. Additionally, we confirm that the spatial resolution improves as the magnification factor increases under the same pinhole diameter condition. Particularly, a 0.57 mm FWHM value is obtained using the modeled gamma camera system with a LYSO scintillation detector. In conclusion, our results demonstrate that a pinhole collimator with a LYSO scintillation detector is a promising gamma camera imaging system.