• 한국작물학회:학술대회논문집
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• 한국작물학회 2022년도 추계학술대회
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• pp.297-297
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• 2022

Wheat is the staple food crop in the word, but wheat products have a low bioavailability of iron and zinc. So in the developing world, where wheat is a staple food, it suffers from micronutrients deficiency. This study was conducted to generate wheat varieties with enhanced grain Zn and Fe contents. Sixty wheat resource were cultivated over 2 years (2019-2021) in the field of NICS, Jeonju, Republic of Korea, to identify agronomic traits. Wheat grains were ground using grinder and analyzed whole wheat flour protein contents and Fe and Zn contents using ICP-OES. The average contents of Zn and Fe grain were 4.6 mg/100g (2.4~8.8 mg/100g) and 4.5 mg/100g (2.4~7.9 mg/100g), respectively. The contents of Fe and Zn in the wheat grain had a positive correlation with the protein content of whole wheat flour, but there was no correlation with heading date (4.22~5.27) and the thousand kernel weight (21.3~57.5 g). Although there was year variation, six resources with high contents of Fe (>5.2 mg/100 g) and Zn (>5.3 mg/100 g) grain in 2 years were selected. These results provide information for selecting breeding materials for biofortified wheat, and further studies on germplasms genetic variations and bioavailability are needed.

• 마이크로전자및패키징학회지
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• 제30권3호
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• pp.88-93
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• 2023

고대역폭 메모리(HBM)에 대한 수요가 증가하고 직경이 더 큰 웨이퍼의 핸들링 기술이 발전함에 따라 본딩 웨이퍼의 두께 균일성에 대해 신뢰성을 확보할 수 있는 측정 방법이 요구되고 있다. 본 연구에서는 300mm 웨이퍼를 대상으로 웨이퍼의 전 영역에 대해 TTV를 측정할 수 있는 모듈을 설계 제직하고, 측정 모듈의 설계를 바탕으로 발생할 수 있는 측정 오차를 분석하였으며, 웨이퍼의 처짐과 척의 기구적 오차를 고려한 모델 해석을 통해 예측된 기울기 값에 따른 측정 오차를 추정하였다. TTV 측정 모듈은 웨이퍼 지지를 위한 센터 척과 리프트 핀을 활용하여 웨이퍼의 전체 영역에 대해 측정이 가능하도록 하였다. 모달 해석을 통해 모듈의 구조적 안정성을 예측하였으며, 구동부와 측정부 모두 100Hz 이상의 강성을 갖는 것을 확인하였다. 설계된 모듈의 측정 오차를 예측한 결과 두께 1,500um의 본딩 웨이퍼를 측정할 경우 예측된 측정 오차는 1.34nm로 나타났다.

• 한국초전도ㆍ저온공학회논문지
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• 제6권1호
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• pp.12-17
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• 2004

High critical current density. $J_c$ over $1MA/cm^2$ at 77 K in a self field was successfully achieved from the YBCO film prepared on (100) $SrTiO_3$ single-crystal substrates by the TFA-MOD process. Unlike a normal TFA-MOD process, we prepared the TFA precursor solution by dissolving YBCO powder into the trifluoroacetic acid. A significant amount of the second phases, including $BaF_2$, was observed in the films fired at $700-725^{\circ}C$ for 2 h under $P(O_2)=10^{-3}$ atm and $P(H_2O)=4.2%$, most probably due to an insufficient reaction time, and hence $T_c$ was greatly degraded. However the films fired at $750-800^{\circ}C$ for 2 h were composed of strongly c-axis oriented YBCO grams without any second phases. and exhibited the $T_c$ values of 89.5 ~ 91 K with a sharp transition. With increasing the firing temperature from 750 to $800^{\circ}C$ average grain size of YBCO was increased and grain connectivity was enhanced. The highest $J_c$ value of $1.1MA/cm^2$ was obtained from the YBCO film fired at $800^{\circ}C$.

• 사물인터넷융복합논문지
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• 제9권6호
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• pp.1-9
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• 2023

최근 MS Office 파일 내에 악성 스크립트 등이 은닉된 멀웨어 파일이 발견되고 있다. 이에 본 논문에서는 머신러닝 기법을 적용하여 악성 디지털 파일을 자동으로 검출할 수 있는 시스템을 설계 및 구현하였다. MS Office 파일 내 OLE VBA 매크로 기능을 악용하여 악성 스크립트를 검출하거나, OOXML 구조 분석을 통해 CDH/LFH/ECDH 내부 필드 값에 악성 스크립트를 탐지하고, OOXML 구조에서 참조되지 않는 비정상적인 CDH/LFH 정보를 추가한 경우 이를 검출할 수 있는 메커니즘을 제시하였다. 그리고 VirusTotal 악성 스크립트 판별 기능을 이용하여 MS Office 파일에 대한 악의적 손상 여부 자동 판별하는 기능을 이용하여 머신러닝 기반 통합 소프트웨어를 설계 및 구현하였다. 실험 결과 파일 손상 여부를 자동 판별할 수 있으며 최적의 머신러닝 모델을 이용하여 임의의 MS Office 파일에 대해 향상된 검출 성능을 제공하는 것을 확인하였다.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제17권10호
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• pp.2768-2787
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• 2023

As an important research direction of the application of computer science in the medical field, the automatic generation technology of radiology report has attracted wide attention in the academic community. Because the proportion of normal regions in radiology images is much larger than that of abnormal regions, words describing diseases are often masked by other words, resulting in significant feature loss during the calculation process, which affects the quality of generated reports. In addition, the huge difference between visual features and semantic features causes traditional multi-modal fusion method to fail to generate long narrative structures consisting of multiple sentences, which are required for medical reports. To address these challenges, we propose a multi-feature optimization Transformer (MFOT) for generating radiology reports. In detail, a multi-dimensional mapping attention (MDMA) module is designed to encode the visual grid features from different dimensions to reduce the loss of primary features in the encoding process; a feature pre-fusion (FP) module is constructed to enhance the interaction ability between multi-modal features, so as to generate a reasonably structured radiology report; a detail enhanced attention (DEA) module is proposed to enhance the extraction and utilization of key features and reduce the loss of key features. In conclusion, we evaluate the performance of our proposed model against prevailing mainstream models by utilizing widely-recognized radiology report datasets, namely IU X-Ray and MIMIC-CXR. The experimental outcomes demonstrate that our model achieves SOTA performance on both datasets, compared with the base model, the average improvement of six key indicators is 19.9% and 18.0% respectively. These findings substantiate the efficacy of our model in the domain of automated radiology report generation.

• 멤브레인
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• 제33권5호
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• pp.240-247
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• 2023

가스 분리 방법 중에서도, 멤브레인을 이용한 CO₂ 포집 및 분리는 지속적으로 개발되고 있는 꾸준히 성장하는 분야이다. 이온성 액체(IL) 기반 복합 막은 CO₂를 분리하는 데 있어 우수한 성능값을 보여준다. 유사하게, 다양한 공중합체/IL 복합막 또한 향상된 성능을 보여준다. 이러한 공중합체/IL 복합만에 산화그래핀과 같은 필러를 첨가하면 IL과 유기 필러 사이에서 발생하는 강한 상호작용으로 인해 필러의 효과가 더욱 향상되며, 이는 결과적으로 CO₂의 친화도, 선택도 및 흡착과 같은 요소를 향상시킨다. 금속-유기 구조체(MOF)를 사용하는 공중합체/IL 복합 막은 향상된 CO₂ 투과도를 보여주었다. 이 총설에서는 이온성 액체와 공중합체복합막의 다양한 조합에 따른 이산화탄소분리성능에 대한 상관관계를 논의한다.

• Journal of Korean Neurosurgical Society
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• 제66권6호
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• pp.632-641
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• 2023

Central nervous system tumors are identified as tumors of the brain and spinal cord. The associated morbidity and mortality of cerebrospinal tumors are disproportionately high compared to other malignancies. While minimally invasive techniques have initiated a revolution in neurosurgery, artificial intelligence (AI) is expediting it. Our study aims to analyze AI's role in the neurosurgical management of cerebrospinal tumors. We conducted a scoping review using the Arksey and O'Malley framework. Upon screening, data extraction and analysis were focused on exploring all potential implications of AI, classification of these implications in the management of cerebrospinal tumors. AI has enhanced the precision of diagnosis of these tumors, enables surgeons to excise the tumor margins completely, thereby reducing the risk of recurrence, and helps to make a more accurate prediction of the patient's prognosis than the conventional methods. AI also offers real-time training to neurosurgeons using virtual and 3D simulation, thereby increasing their confidence and skills during procedures. In addition, robotics is integrated into neurosurgery and identified to increase patient outcomes by making surgery less invasive. AI, including machine learning, is rigorously considered for its applications in the neurosurgical management of cerebrospinal tumors. This field requires further research focused on areas clinically essential in improving the outcome that is also economically feasible for clinical use. The authors suggest that data analysts and neurosurgeons collaborate to explore the full potential of AI.

• International Journal of Computer Science & Network Security
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• 제23권10호
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• pp.199-208
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• 2023

The emergence of COVID-19 virus has shaken almost every aspect of human life including but not limited to social, financial, and economic changes. One of the most significant impacts was obviously healthcare. Now though the pandemic has been over, its aftereffects are still there. Among them, a prominent one is people lifestyle. Work from home, enhanced screen time, limited mobility and walking habits, junk food, lack of sleep etc. are several factors that have still been affecting human health. Consequently, diseases like diabetes, high blood pressure, anxiety etc. have been emerging at a speed never witnessed before and it mainly includes the people at young age. The situation demands an early prediction, detection, and warning system to alert the people at risk. AI and Machine learning has been investigated tremendously for solving the problems in almost every aspect of human life, especially healthcare and results are promising. This study focuses on reviewing the machine learning based approaches conducted in detection and prediction of diabetes especially during and post pandemic era. That will help find a research gap and significance of the study especially for the researchers and scholars in the same field.

• 한국결정성장학회지
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• 제33권6호
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• pp.268-275
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• 2023

적층제조 기술의 지속적 발전 및 적용 산업의 확대에 따라 제조된 금속 부품의 전반적인 품질 및 성능을 향상 시키기 위한 서포트 최적 설계 수행은 필수적이 되었다. 따라서 본 논문은 금속 적층제조 공정에서의 서포트 설계변수가 서포트 강성에 미치는 영향을 분석하였다. 대표적인 서포트 설계변수인 서포트 종류, 간격, 침투 깊이를 다양하게 적용한 인장시편을 적층제조를 통해 제작하고, 이에 대한 인장시험을 통해 변위-하중 곡선의 차이를 분석하였다. 그 결과를 바탕으로 서포트 설계변수가 지지 강성에 미치는 영향에 대한 포괄적인 분석을 제시하였다. 이를 통해 적층제조 공정 중 금속 부품의 열 변형을 억제하기 위한 서포트 최적설계 수행을 효과적으로 할 수 있을 것이라 기대된다.

• 한국표면공학회지
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• 제56권6호
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• pp.420-426
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• 2023

We prepared a highly sensitive hydrogen (H₂) sensor based on Indium oxides (In₂O₃) porous nanoparticles (NPs) loaded with Platinum (Pt) nanoparticle in the range of 1.6~5.7 at.%. In₂O₃ NPs were fabricated by microwave irradiation method, and decorations of Pt nanoparticles were performed by electroless plating on In₂O₃ NPs. Crystal structures, morphologies, and chemical information on Pt-loaded In₂O₃ NPs were characterized by grazing-incident X-ray diffraction, field-emission scanning electron microscopy, energy-dispersive X-ray spectroscopy, respectively. The effect of the Pt nanoparticles on the H₂-sensing performance of In₂O₃ NPs was investigated over a low concentration range of 5 ppm of H₂ at 150-300 ℃ working temperatures. The results showed that the H₂ response greatly increased with decreasing sensing temperature. The H₂ response of Pt loaded porous In₂O₃ NPs is higher than that of pristine In₂O₃ NPs. H₂ gas selectivity and high sensitivity was explained by the extension of the electron depletion layer and catalytic effect. Pt loaded porous In₂O₃ NPs sensor can be a robust manner for achieving enhanced gas selectivity and sensitivity for the detection of H₂.