• Current Optics and Photonics
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• 제7권6호
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• pp.608-637
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• 2023

The initial motivation in colloid science and engineering was driven by the fact that colloids can serve as excellent models to study atomic and molecular behavior at the mesoscale or microscale. The thermal behaviors of actual atoms and molecules are similar to those of colloids at the mesoscale or microscale, with the primary distinction being the slower dynamics of the latter. While atoms and molecules are challenging to observe directly in situ, colloidal motions can be easily monitored in situ using simple and versatile optical microscopic imaging. This foundational approach in colloid research persisted until the 1980s, and began to be extensively implemented in optics and photonics research in the 1990s. This shift in research direction was brought by an interplay of several factors. In 1987, Yablonovitch and John modernized the concept of photonic crystals (initially conceptualized by Lord Rayleigh in 1887). Around this time, mesoscale dielectric colloids, which were predominantly in a suspended state, began to be self-assembled into three-dimensional (3D) crystals. For photonic crystals operating at optical frequencies (visible to near-infrared), mesoscale crystal units are needed. At that time, no manufacturing process could achieve this, except through colloidal self-assembly. This convergence of the thirst for advances in optics and photonics and the interest in the expanding field of colloids led to a significant shift in the research paradigm of colloids. Initially limited to polymers and ceramics, colloidal elements subsequently expanded to include semiconductors, metals, and DNA after the year 2000. As a result, the application of colloids extended beyond dielectric-based photonic crystals to encompass plasmonics, metamaterials, and metasurfaces, shaping the present field of colloidal optics and photonics. In this review we aim to introduce the research trajectory of colloidal optics and photonics over the past three decades; To elucidate the utility of colloids in photonic crystals, plasmonics, and metamaterials; And to present the challenges that must be overcome and potential research prospects for the future.

• 문화기술의 융합
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• 제9권6호
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• pp.947-955
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• 2023

본 연구의 목적은 Fisher(1995, 2003)의 다차원적 정책평가방법 중 상황적 타당성 평가를 활용하여 우리나라의 장애인 고용·일자리 정책을 평가하고 그에 따른 정책적 함의를 도출하는 것이다. 우리나라에서 진행된 다수의 장애인 고용·일자리 정책평가 연구들이 계량적인 연구방법에 치우쳐 균형 있고 종합적인 평가에는 소홀한 측면이 있었다. 본 연구에서는 기존의 실증주의적 방법론의 한계를 보완하는 질적 또는 현상학적 접근을 통해 균형 있는 정책평가를 시도하였다. 연구결과, 장애인 고용서비스·일자리의 개선을 위해 기관 간 연계·협력 강화, 고용서비스 사각지대 해소, 질적 개선, 맞춤형 고용서비스 확대, 프로그램 내실화, 정책·제도적 환경개선, 개인 심리정서적 지원강화가 향후 우리나라 장애인고용정책에서 중요한 것으로 나타났다.

• Composites Research
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• 제37권1호
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• pp.40-45
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• 2024

본 연구에서는 고분자 전해질막 연료전지용 가스확산층의 투과도를 예측하기 위해 삼차원 합성곱 신경망 모델을 사용하는 방법론을 소개한다. 먼저, 기계학습 모델을 학습시키기 위해 X-선 단층 촬영을 통해 얻은 실제 가스확산층 이미지에서 형태학적 특성을 추출해 가스확산층의 대표 체적 요소로 이루어진 인공 데이터셋을 생성한다. 이러한 형태학적 특성은 다공성, 섬유 배향, 직경의 통계적 분포가 포함된다. 구축한 인공 데이터셋 대표 체적 요소들의 투과도를 평가하기 위해 격자 볼츠만 방법이 사용되었으며 각각의 대표 체적 요소들의 투과도를 도출하였다. 이러한 인공 데이터셋을 통해 삼차원 합성곱 신경망 모델을 학습시켰으며 인공 데이터셋을 학습한 삼차원 합성곱 신경망 모델이 실제 가스확산층의 대표 체적 요소 투과도 또한 잘 예측하는 것을 확인하였다.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제18권2호
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• pp.263-283
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• 2024

Users' comments after online shopping are critical to product reputation and business improvement. These comments, sometimes known as e-commerce reviews, influence other customers' purchasing decisions. To confront large amounts of e-commerce reviews, automatic analysis based on machine learning and deep learning draws more and more attention. A core task therein is sentiment analysis. However, the e-commerce reviews exhibit the following characteristics: (1) inconsistency between comment content and the star rating; (2) a large number of unlabeled data, i.e., comments without a star rating, and (3) the data imbalance caused by the sparse negative comments. This paper employs Bidirectional Encoder Representation from Transformers (BERT), one of the best natural language processing models, as the base model. According to the above data characteristics, we propose the F_MixBERT framework, to more effectively use inconsistently low-quality and unlabeled data and resolve the problem of data imbalance. In the framework, the proposed MixBERT incorporates the MixMatch approach into BERT's high-dimensional vectors to train the unlabeled and low-quality data with generated pseudo labels. Meanwhile, data imbalance is resolved by Focal loss, which penalizes the contribution of large-scale data and easily-identifiable data to total loss. Comparative experiments demonstrate that the proposed framework outperforms BERT and MixBERT for sentiment analysis of e-commerce comments.

• 한국터널지하공간학회 논문집
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• 제25권6호
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• pp.495-507
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• 2023

지속해서 논의 중인 한일 해저터널 건설과 관련해 단층대에서 일어날 것으로 예상되는 대규모 지반 변위에 따른 터널의 변형에 대한 연구가 필요하다. 이 연구는 고무 재료 기반 면진라이닝에 관한 수치해석 결과를 제시한다. 변형 구배를 산정하기 위해 사용자정의 서브루틴을 이용했다. 또한 극 분해를 통해 데이터를 분석하였으며, 주 신축 방향으로 정렬된 여러 평면 좌표계를 이용해 데이터를 도시하여 재료 변형에 대한 심층적인 이해를 얻을 수 있었다. 터널 기술자는 초탄성 재료의 변형 관련 연구에 이 연구를 참고할 수 있다.

• 경영정보학연구
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• 제25권1호
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• pp.47-73
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• 2023

본 연구는 인공지능 기법 중 다중레이블 속성선택 방법을 적용하여 복잡한 경영환경에서 의사결정의 효과성을 증대시키는 방안을 설명한다. 인공지능 기반의 의사결정 시스템은 의사결정자의 선택과 판단을 돕거나, 대신하는 중요한 역할을 한다. 더욱이 최근 인공지능을 중심으로 한 비즈니스 의사결정은 기업의 성장 동력으로 평가받는데, 이를 위해서는 효과적인 의사결정 방법이 수반되어야 한다. 이에 본 연구는 의미 있는 속성값을 선별하는 CFS-BR(이진연관성 접근 기반의 상관관계 속성선택 모델)을 제안하여, 효과적인 의사결정을 지원하는 것을 돕는다. 예시데이터와 실증데이터의 분석 결과, CFS-BR은 유의미한 속성을 최상우선선별 알고리즘 기반으로 최상의 조합을 선별하므로 효율적 의사결정을 지원할 수 있고, 기존의 다중 레이블 속성선택 방법과 비교하였을 때 정확도가 높은 것으로 보아 효과적인 의사결정을 증대시키는 데 유용하다.

• Nuclear Engineering and Technology
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• 제56권1호
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• pp.132-140
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• 2024

In the event of a severe accident in Sodium Cooled Fast Reactors (SFR), the sodium combustion aerosols along with fission product aerosols would migrate to the environment through leak paths of the Reactor Containment Building (RCB) concrete wall under positive pressure. Understanding the characteristics of sodium aerosol transport through concrete leak paths is important as it governs the environmental source term. In this context, experiments are conducted to study the influence of various parameters like pressure, initial mass concentration, leak path diameter, humidity etc., on the transport and deposition of sodium aerosols in straight leak paths of concrete. The leak paths in concrete specimens are prepared by casting and the diameter of the leak path is measured using thermography technique. Aerosol transport experiments are conducted to measure the transported and plugged aerosol mass in the leak paths and corresponding plugging times. The values of differential pressure, aerosol concentration and relative humidity taken for the study are in the ranges 10-15 kPa, 0.65-3.04 g/m³ and 30-90% respectively. These observations are numerically simulated using 1-Dimensional transport equation. The simulated values are compared with the experimental results and reasonable agreement among them is observed. From the safety assessment view of reactor, the approach presented here is conservative as it is with straight leak paths.

• 복식문화연구
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• 제32권3호
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• pp.334-344
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• 2024

This study aimed to develop a new convergence course applying project-based learning (PBL) and collaborative teaching methods and identify its educational effects. The course development proceeded as follows: First, three instructors collaborated to define course goals, plan objectives, content, and methods, and create a syllabus for a PBL-based fashion studio course. Roles were divided to maximize expertise: one instructor focused on fashion design, another on three-dimensional cutting, and the third on flat cutting, and digital techniques. Second, the classes were conducted and feedback on student progress was shared, enhancing class quality and engagement. Third, teaching effectiveness was assessed through learner evaluation questionnaires, reflection journals, and performance assessments. Lastly, based on the results from these evaluations, positive aspects of the course were reviewed, and ways to modify it and enhance course quality for continuous improvement were explored. The results showed high satisfaction with the learning effects on major competencies, indicating that students not only effectively learned major skills but also improved their communication and teamwork. The students perceived the teaching methods positively allowing them to be more active in class. Instructors noted that the course produced higher-quality design and production outcomes compared to previous courses. Overall, the course applying PBL and collaborative teaching methods was found to improve educational quality and effectiveness, making it a valuable approach for learner-centered education.

• 전자통신동향분석
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• 제39권4호
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• pp.42-53
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• 2024

Mathematical modeling is the process of representing physical phenomena using equations, and it often describes various scientific phenomena through differential equations. Numerical analysis, which is capable of approximating solutions to partial differential equations representing physical phenomena, is widely utilized. However, in high-dimensional or nonlinear systems, computational costs can substantially increase, leading to potential numerical instability or convergence issues. Recently, Physics-Informed Neural Networks (PINNs) have emerged as an alternative approach. A PINN leverages physical laws even with limited data to provide highly reliable predictive performance and can address the convergence issues and high computational costs associated with numerical analysis. This paper analyzes the weak signals, research trends, patent trends, and case studies of PINNs. On the basis of this analysis, it proposes directions for the development of PINN techniques in the agricultural field. In particular, the application of PINNs in agriculture is expected to be more effective than in other industries because of their ability to reflect real-time changes in biological processes. While the technology readiness level of PINNs remains low, the potential for model training with minimal data and real-time prediction capabilities suggests that PINNs could replace traditional numerical analysis models. It is anticipated that the research and industrial applications of PINN will develop at an increasing pace while focusing on addressing the complexity of mathematical models in agriculture, mathematical modeling and the application of various biological processes; securing key patents related to PINNs; and standardizing PINN technology in the field of agriculture.

• 공업화학
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• 제35권3호
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• pp.155-181
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• 2024

최근, 기존 분리막의 성능을 향상시켜 CO₂ 분리를 효율적으로 수행하기 위한 중요한 연구가 진행되고 있다. 이는 탄소포집 공정에서의 활용을 확대하는 것을 목표로 하고 있다. 분리막 기술은 비용 및 에너지 효율성, 연속 운전, 작은 공정 크기 등의 장점으로 인해 탄소제로 이슈에 대처하는 유망한 탄소 포집 기술로 부상하고 있다. 연구된 여러 종류의 분리막 중 혼합기질막(mixed-matrix membrane, MMM)이 전반적인 가스 분리 공정의 효율을 향상시킬 수 있는 전통적인 분리막의 대안으로 제안되었다. 2D 나노소재는 쉬운 개질과 기능화, 다른 재료와의 결합 등 특징적인 성질로 인해 다양한 일반적인 2D 나노소재들이 가스 분리를 위한 효율적인 MMMs 제작에 사용되고 있다. 본 논문은 2D 나노소재를 사용한 MMMs 분야의 최근 발전을 검토하였다. 또한, CO₂ 분리 및 포집을 위한 2D 나노소재 기반 분리막의 현재 도전과 전망을 논의하였다.