• Resources Recycling
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• v.32 no.6
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• pp.54-66
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• 2023

Titanium's importance as a mineral resource is increasing, but the Korean industry depends on imports. Ilmenite is the principal titanium ore. However, research and development from raw materials have not been investigated yet in detail. Hence, measures to secure a stable titanium supply chain are urgently needed. Accordingly, through beneficiation technology, we evaluated the possibility of technological application for the efficient recovery of valuable minerals. As a result of the experiments, we confirmed that mineral particles existed as fine particles due to weathering, making recovery through classification difficult. Consequently, applying beneficiation technologies, i.e., specific gravity separation, magnetic separation, and flotation, makes it possible to recover valuable minerals such as hematite and rutile. However, there are limitations in increasing the quality and yield of TiO₂ due to the mineralogical characteristic of the hematite and rutile contained in titanium ore. Hametite is combined with rutile even at fine particles. Therefore, it is essential to develop mineral processing routes, to recover iron, vanadium, and rare earth elements as resources. On that account, we used grinding technology that improves group separation between constituent minerals and magnetic separation technology that utilizes the difference in magnetic sensitivity between fine mineral particles. The development of beneficiation technology that can secure the economic feasibility of valuable materials after reforming iron oxide and titanium oxide components is necessary.

• Journal of Service Research and Studies
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• v.13 no.4
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• pp.191-205
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• 2023

Artificial Intelligence (AI), especially in the domain of text-generative services, has witnessed a significant surge, with forecasts indicating the AI-as-a-Service (AIaaS) market reaching a valuation of $55.0 Billion by 2028. This research set out to explore the quality dimensions characterizing synthetic text media software, with a focus on four key players in the industry: ChatGPT, Writesonic, Jasper, and Anyword. Drawing from a comprehensive dataset of over 4,000 reviews sourced from a software evaluation platform, the study employed the Latent Dirichlet Allocation (LDA) topic modeling technique using the Gensim library. This process resulted the data into 11 distinct topics. Subsequent analysis involved comparing these topics against established AI service quality dimensions, specifically AICSQ and AISAQUAL. Notably, the reviews predominantly emphasized dimensions like availability and efficiency, while others, such as anthropomorphism, which have been underscored in prior literature, were absent. This observation is attributed to the inherent nature of the reviews of AI services examined, which lean more towards semantic understanding rather than direct user interaction. The study acknowledges inherent limitations, mainly potential biases stemming from the singular review source and the specific nature of the reviewer demographic. Possible future research includes gauging the real-world implications of these quality dimensions on user satisfaction and to discuss deeper into how individual dimensions might impact overall ratings.

• Journal of Environmental Impact Assessment
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• v.32 no.6
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• pp.407-418
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• 2023

This study conducted an analysis of terrain change indicators in major development projects in Korea, examining the correlation between terrain change indicators to derive foundational terrain change metrics based on different land use and slope types. The aim is to contribute to sustainable development by enhancing the efficiency of land utilization and landscaping, while minimizing environmental impacts in future development endeavors. Additionally, to apply the research findings in practical contexts, domestic regulations related to terrain were surveyed, and the compatibility and usability between these regulations and research analysis results were discussed. Based on this, the study seeks to explore strategies for more accurate and useful utilization of terrain change indicators in future research. As a result, in the tourism development, terrain changes predominantly occur in the order of flat land, hillly land, and mountain land, with the analysis indicating higher terrain changes in undulating hilly and mountainous lands compared to flat land. Furthermore, in industrial complex development, very steep (20°-30°) and extreme (30°-40°) slopes; in urban development projects, steep slope (15°-20°); in athletic service facility and tourist development, steep (15°-20°) and very steep (20°-30°) exhibit higher average terrain change indicators compared to other slope categories. The findings of our study can contribute to the formulation of strategies aimed at minimizing terrain disturbance in future domestic development projects and serve as foundational data for environmental impact assessments.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.22 no.5
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• pp.148-162
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• 2023

The objective of this study is to derive the appropriate perception location for changes in driving behavior of autonomous vehicles in urban road environments based on traffic safety signs. For this purpose, 32 types of signs that induce changes in driving behavior were selected from currently used traffic safety signs and classified as three types according to changes in driving behavior. Based on this, three scenarios were designed: stop, speed change, and lane change scenarios. These were used to confirm the impact on traffic flow. As a result of the analysis, it was found that each scenario needs to receive information on traffic safety signs in advance to ensure changes in traffic flow and safety. Consequently, the appropriate perception location can be used as a basis for establishing standards for delivering message sets to autonomous vehicles or revising traffic safety signs for them. In addition, this study is expected to contribute to the establishment of safe and efficient driving strategies on urban roads as autonomous vehicles are introduced in the future.

• Journal of the Korea Society of Computer and Information
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• v.28 no.11
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• pp.1-11
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• 2023

Breast cancer is the disease that affects women the most worldwide. Due to the development of computer technology, the efficiency of machine learning has increased, and thus plays an important role in cancer detection and diagnosis. Deep learning is a field of machine learning technology based on an artificial neural network, and its performance has been rapidly improved in recent years, and its application range is expanding. In this paper, we propose a DNN-SVM hybrid model that combines the structure of a deep neural network (DNN) based on transfer learning and a support vector machine (SVM) for breast cancer classification. The transfer learning-based proposed model is effective for small training data, has a fast learning speed, and can improve model performance by combining all the advantages of a single model, that is, DNN and SVM. To evaluate the performance of the proposed DNN-SVM Hybrid model, the performance test results with WOBC and WDBC breast cancer data provided by the UCI machine learning repository showed that the proposed model is superior to single models such as logistic regression, DNN, and SVM, and ensemble models such as random forest in various performance measures.

• Proceedings of the Plant Resources Society of Korea Conference
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• 2020.08a
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• pp.68-68
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• 2020

최근 농촌진흥청과 기상청에서 발표한 연구자료에 따르면 2020년 기준으로 국내 경지면적의 10% 가량이 이미 아열대 기후대에 속하고 있을 뿐 현재 추세대로 온실가스가 배출될 경우 2100년경 우리나라의 대부분 지역은 아열대 기후대에 속하게 될 것으로 전망되고 있다. 이에 국가 기관뿐만 아니라 많은 지자체에서 기후변화에 대응하여 아열대 작물을 도입하기 위한 시도를 활발하게 추진하고 있다. 아열대 작물 중 국내에서 3번째로 많이 활용되고 있는 삼채는 기능성 물질을 다량으로 함유하고 있어 수요도가 지속적으로 증가하고 있다. 하지만, 삼채의 경우 일반적인 원예 작물과는 달리 실생 종자를 상업적으로 이용하고 있어 종자들의 발아율이 균일하지 못할 뿐만 아니라 발아율이 낮은 문제가 있는 것으로 보고되고 있다. 이에 삼채의 경우 농가에서 정식 시기를 맞추기 어려울 뿐만 아니라 대규모 생산을 위한 공정육묘 시스템의 적용이 어려운 상황에 있다. 종자 프라이밍 기술은 잠재적으로 종자 발아와 식물 생장을 빠르고 균일하게 해줄 수 있는 방법으로 알려져 있지만, 현재 삼채에서는 프라이밍 처리가 종자 발아에 미치는 영향에 대해서 검토한 사례가 없다. 따라서 본 연구는 삼채의 파종 효율을 증진시키기 위한 목적으로 몇 가지 프라이밍 처리 방법이 삼채의 발아특성에 미치는 영향을 검정하고자 하였다. 삼채 종자는 (주)아람종묘사의 종자를 구매하여 강릉원주대학교 생명과학대학에서 수행하였다. 프라이밍 처리는 Hydropriming은 증류수, Osmopriming은 CaCl2 1.0%, Halopriming은 Polyrthylene glycol 6000(PEG) 13.5%의 3가지를 사용하였으며, 각 프라이밍 처리 시간은 6시간, 12시간, 18시간, 24시간, 48시간 총 5가지 방법으로 처리되어 대조구를 포함 총 16개의 처리를 하였다. 프라이밍 처리 된 종자는 페트리디쉬 (50mm)에 30립씩 치상하였다. 프라이밍 각 처리구별 4반복으로 하였으며 24시간 암(Black), 온도 20℃의 조직배양실에서 치상 후 10일간 조사하였다. 본 실험 결과 대조구는 38% 발아율을 가졌으며, 프라이밍 처리 시간에 따른 각 처리구들은 대조구에 비해 발아율이 높아짐을 확인할 수 있었다. 그 중 Hydropriming 12시간 발아율 51%, Osmopriming 18시간 발아율 68%, Halopriming 48시간 발아율 65%로 각 프라이밍 처리구별 가장 좋은 발아율을 확인할 수 있었다. 결론적으로 삼채에서 프라이밍 처리 기술의 적용은 발아율의 향상과 발아기간의 정형화를 유도할 수 있어 농가에서의 일반 육묘는 물론이고 대규모 공정육묘를 위한 저렴하고 안전한 방법 중 하나로써 이용될 수 있을 것으로 기대되어 진다.

• Proceedings of the Plant Resources Society of Korea Conference
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• 2020.08a
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• pp.40-40
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• 2020

들깨(Perilla frutescens L.)는 꿀풀과 1년생 초본으로 한국, 중국 등의 동부 아시아가 원산지로 식용, 약용 및 공업용 등 다양한 용도로 이용되고 있다 들깨는 우리나라에서 오랜시간 재배해 왔으나 체계적인 연구기간이 짧아, 다른 유료작물에 비해 육성품종이 적고 유전자원의 체계적인 수집평가가 이루어지지 않았다. 특히 외국에서는 들깨와 근연종을 이용하여 색소 및 정유성분에 대한 연구를 하는데 비해 우리나라에서는 주로 식용으로만 연구가 진행되고 있다. 들깨 육종에 있어서 중요한 것은 유전자원 확보와 이를 정리 보존하여 우량한 육종재료를 효율적으로 이용하는 것이다. 본 연구에서는 국내에서 수집한 들깨 44자원의 형태적 특성을 조사하여 품종 육성을 위한 기초자료를 제공하고자 하였다. 본 연구에 사용된 들깨 자원은 경북 수집 10자원으로 가장 많았으며 전북 8자원, 경남 7자원, 강원과 경기에서 각각 6자원, 충남 3자원, 전남과 충북에서 각각 2자원이었다. 화색은 들깨 44자원 모두 흰색이었으며 줄기색은 연녹색이 29자원, 녹색 9자원, 자주색 4자원으로 조사되었다. 잎의 앞면은 녹색 27자원, 연녹색 10자원, 진녹색 7자원이었으며 뒷면색은 녹색 26자원, 연녹색 18자원으로 조사되었다. 잎의 모양은 장타원형 21자원, 피침형 15자원, 심장형 7자원이었으며 잎의 모용은 23자원이 적음, 14자원이 보통, 6자원이 많게 조사되었다. 잎의 길이는 35자원이 15.1cm이상으로 조사되었고 잎넓이는 11.1cm이상인 자원이 37자원으로 조사되었다. 종피색은 갈색이 28자원, 회색이 6자원, 암갈색이 3자원 순으로 조사되었다. 본 실험에서 조사된 들깨 유전자원의 형태적 특성은 들깨 선발에 있어 기초 정보로 활용 가능할 것이며 추가적으로 농업형질, 기능성 물질 분석등의 들깨 육종 프로그램을 위한 다양한 평가 및 선발이 필요할 것이다.

• Journal of the Korea institute for structural maintenance and inspection
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• v.27 no.6
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• pp.30-38
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• 2023

As the number of old buildings subject to safety inspection increases, the burden on designated institutions and management entities that are responsible for safety management is increasing. Accordingly, when selecting buildings subject to safety inspection, appropriate safety inspection standards and appropriate technology are essential. The current safety inspection standards for old buildings give low scores when it is difficult to confirm damage such as cracks in structural members due to finishing materials. This causes the evaluation results to be underestimated regardless of the actual safety status of the structure, resulting in an increase in the number of aging buildings subject to safety inspection. Accordingly, this study proposed a thermal imaging technique, a non-destructive and non-contact inspection, to detect cracks inside finishing materials. A concrete specimen was produced to observe cracks inside the finishing material using a thermal imaging camera, and thermal image data was measured by exciting a heat source on the concrete surface and cracked area. As a result of the measurement, it was confirmed that it was possible to observe cracks inside the finishing material with a width of 0.3mm, 0.5mm, and 0.7mm, but it was difficult to determine the cracks due to uneven temperature distribution due to surface peeling and peeling of the wallpaper. Accordingly, as a result of performing data analysis by deriving the amplitude and phase difference of the thermal image data, clear crack measurement was possible for 0.5mm and 0.7mm cracks. Based on this study, we hope to increase the efficiency of field application and analysis through the development of technology using big data-based deep learning in the diagnosis of internal crack damage in finishing materials.

• Journal of the Korea institute for structural maintenance and inspection
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• v.27 no.6
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• pp.22-29
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• 2023

In the evaluation of seismic performance for structural materials and components, the loading rate and axial force can have a significant impact. Due to time-delay effects between input and output displacements, It is difficult to apply high-rate displacement in cyclic tests and hybrid simulations. Additionally, the difficulty of maintaining a consistent vertical load in the presence of lateral displacement has limited fast and real-time tests performed while maintaining a constant vertical load. In this study, slow, fast cyclic tests and real-time hybrid simulations were conducted to investigate the rate dependency and the influence of vertical loads of Isolation Bearing. In the experiment, the FLB System including an Adaptive Time Series (ATS) compensation and a state estimator was constructed for real-time control of displacement and vertical load. It was found that the vertical load from the superstructure and loading rate can have a significant impact on the strength of the seismic isolation bearing and its behavior during an earthquake. When conducting experiments for seismic performance evaluation, they must be implemented to be similar to reality. This study demonstrates the excellent performance of the system built and used for seismic performance evaluation and enables accurate and efficient seismic performance evaluation.

• Applied Chemistry for Engineering
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• v.34 no.6
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• pp.603-607
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• 2023

Aqueous film forming foam (AFFF) is a critical fire suppression agent used in combating hydrocarbon fires. This type of fire suppressant is highly effective due to its ability to form a protective film, dissipate heat, inhibit combustion, and utilize a blend of chemical substances to extinguish fires. While these properties offer significant advantages in responding to hydrocarbon fires, AFFF is distinct in its deployment as it is dispensed in the form of foam. Therefore, the rheological analysis of AFFF foam using a rheometer plays a crucial role in predicting the spray characteristics of AFFF for combating hydrocarbon fires, and this is closely associated with effective fire suppression. In this study, we conducted rheometer experiments to confirm the non-Newtonian behavior (shear-thinning) of AFFF foam and obtained data on the form's stability. These experimental data are expected to contribute to enhancing the efficiency of fire suppression systems utilizing AFFF.