This study proposes a mathematical model to optimize the fighter aircraft-weapon combinations for the ROKAF(Republic Of Korea Air Force). With the recent emergence of the population declining issue in Republic of Korea, there is an urgent need for efficient weapon system operations in light of decreasing military personnel. In order to solve these issues, we consider to reduce the workload of pilots and maintenance personnel by operating an optimal number of weapons instead of deploying all possible armaments for each aircraft type. To achieve this, various factors for optimizing the fighter-weapon combinations were identified and quantified. A model was then constructed using goal programming, with the objective functions based on the compatibility, CEP(Circular Error Probable), and fire range of the weapons, along with the planned wartime mission-specific weapon ratios for each aircraft type. The experimental result's analysis of the proposed model indicate a significant increase in mission performance efficiency compared to the existing system in both operational and maintenance aspects. We hope that our model will be reflected to help improve the operational capabilities of Republic of Korea Air Force.

Non-human primates, due to their high genetic similarity to humans, are used as laboratory animals in biotechnology researches. The growing demand has recently led to a shortage of primate resources, which has become a significant issue both domestically and internationally. This shortage has been further exacerbated by the COVID-19 pandemic. Consequently, the importance of resource conservation through effective primate management is increasing. This requires the establishment of proper quarantine procedures and infectious disease control. Quarantine is an important process that protects not only animal health but also public health significance. Non-human primate quarantine procedures were organized in order. We compared the differences in quarantine procedures not only in Korea but also in various countries such as the US, EU, and Australia. In addition, the etiology, clinical symptoms, diagnosis, and treatment methods of representative infectious diseases of quarantine concern (tuberculosis, monkeypox, monkey immunodeficiency virus, salmonellosis, and shigellosis) were summarized. A literature review of nonhuman primate quarantine procedures in other countries revealed minimal differences in the basic structure. The quarantine periods were similar around 30 days, but we found some differences in details such as legal requirements, documentation forms, and quarantine authorities. These findings are expected to contribute to the development of strategies for improving methods to prevent the spread of infectious diseases and enhancing quarantine management methods.

The study explores the relationship among teacher identity, teacher transparency, teacher self-efficacy, and teachers’ adaptation to digital change. Eighty-four English teachers participated in the study. For comparison between English and other subject teachers, 38 survey results of different subject teachers were included in the analysis. The results showed that English teachers’ scores were lower across all the constructs in terms of both transparency and self-efficacy compared to the scores of teachers in other subjects. For further analysis, the Structural Equation Modeling was run, and the results revealed that teacher transparency influences teacher self-efficacy, facilitating digital adaptation. Instructional Transparency and Peer Transparency were significant predictors of selfefficacy, directly influencing digital adaptation. This result illustrates the dynamic interplay between evolving teacher identity and self-efficacy in relation to digital adaptation through the relationship between teacher transparency and teacher selfefficacy. The findings indicate the need for targeted programs to enhance English teachers’ transparency and self-efficacy as a pathway to their digital adaptation.

This study proposes a weight optimization technique based on Mixture Design of Experiments (MD) to overcome the limitations of traditional ensemble learning and achieve optimal predictive performance with minimal experimentation. Traditional ensemble learning combines the predictions of multiple base models through a meta-model to generate a final prediction but has limitations in systematically optimizing the combination of base model performances. In this research, MD is applied to efficiently adjust the weights of each base model, constructing an optimized ensemble model tailored to the characteristics of the data. An evaluation of this technique across various industrial datasets confirms that the optimized ensemble model proposed in this study achieves higher predictive performance than traditional models in terms of F1-Score and accuracy. This method provides a foundation for enhancing real-time analysis and prediction reliability in data-driven decision-making systems across diverse fields such as manufacturing, fraud detection, and medical diagnostics.

이 연구는 여고생을 대상으로 외모관심도와 자기표현 욕구가 자아존중감 및 외모관리행동에 미치는 영향을 알아보기 위해 자 기기입식 설문조사 방법을 통해 이루어졌다. 조사 기간은 2024년 8월 1일부터 2024년 9월 20일까지 설문조사를 실시하였으며, 유효표본 200부를 최종 분석자료로 활용하였고 리커트 5점 척도 를 사용하였다. 첫째, 여고생의 외모 관심도와 자기표현 욕구는 모두 자아존중 감에 유의미한 정(+)의 영향을 미치는 것으로 나타나 외모관심도 와 자기표현 욕구가 높을수록 자아존중감도 높아지는 것으로 볼 수 있었다. 둘째, 여고생의 자기표현 욕구가 외모관리행동에 유의미한 정 (+)의 영향을 미치는 것으로 나타나 자기표현 욕구가 높을수록 외모관리행동도 높아지는 것으로 볼 수 있었다. 셋째, 여고생의 자아존중감이 외모관리행동에 유의미한 정(+)의 영향을 미치는 것으로 나타나 자아존중감이 높을수록 외모관리행 동도 높아지는 것으로 볼 수 있었다. 이상의 결과를 볼 때, 부모나 교육자는 여고생들이 외모관리행 동에 대한 올바른 판단하에 외모관심과 자기표현을 과하거나 지 나치지 않게 표출하여 자아존중감 및 외모관리를 할 수 있도록 지도하여야만 할 것이다. 결론적으로 여고생들은 질풍노도의 사춘기 단계에 있고 감정조 절이 미숙하기 때문에 자기표현 단계에서 부정적인 감정에 휘말 릴 수 있으며, 따라서 부모나 교육자는 솔직한 감정을 표출할 수 있는 열린 자세로 외모에 대한 건강한 인식과 올바른 개념을 정 립할 수 있도록 도와야 할 것이다.

Korean English medium instruction (EMI) classes aim to foster active discussions and communicative interactions in English between instructors and students. However, many Korean students in these classes struggle due to their limited English proficiency. This paper examines the challenges faced by Korean EFL students in EMI environments, highlighting the necessity for support in both English and their native language to facilitate effective learning. It also identifies teaching strategies that have proven effective in helping these students navigate language barriers. The findings indicate that participants had difficulty developing their writing skills for assignments in EMI settings and encountered limited opportunities to communicate their understanding of course material with instructors. To address these challenges, it is important to assess students’ language skills and find a balance between Korean and English. Implementing flexible teaching methods can enhance the learning experience, making it more effective and supportive. By providing multiple approaches to learning, such as interactive activities or peer support, learning gaps can be bridged and overall educational outcomes enhanced.

이 논문은 W. B. 예이츠의 유산과 멜리스 베스리의 소설 􋺷흩어진 사랑􋺸에 서 나타나는 뼈의 상징적 공명을 탐구한다. 소설에서 예이츠의 유령은 그의 삶, 예술, 그 리고 자신의 유해라는 수수께끼 같은 운명을 되새기며 지속적인 주제들을 반추한다. 뼈의 모티프는 사랑, 죽음, 그리고 기억의 교차점을 포괄하는 서사적이고 은유적인 축으로 기능한다. 이러한 관점에서 이 논문은 베스리가 예이츠의 미완의 열정, 특히 모드 곤에 대한 사랑을 어떻게 재구성하며 그의 정체성의 더 넓은 문화적, 역사적 차원을 어떻게 탐구하는지를 살펴본다. 예이츠의 유해 발굴과 재매장에 얽힌 논란은 예술적 불멸성과 신체의 덧없음 사이의 긴장을 심화시키며, 이는 아일랜드의 복잡하고 종종 단절된 역사 적 서사를 반영한다. 예이츠를 현대 문학적 맥락에 배치함으로써 베스리는 그의 비전을 확장하면서도 변모시키며, 사랑, 상실, 유산에 대한 예이츠의 사색을 현대적 맥락에 녹여 낸다. 이 논문은 베스리의 소설이 뼈를 기억의 매개체로 부각시키며 예이츠의 시적 상상 력과 그녀 자신의 재해석 사이의 다리를 놓는다고 주장한다. 궁극적으로, 이 연구는 예 이츠와 베스리가 공유하는 죽음, 역사, 그리고 예술과 감정의 초월적 힘에 대한 탐구가 여전히 중요한 의미를 가진다는 점을 강조한다. 􋺷흩어진 사랑􋺸 은 예이츠의 사랑의 유산 을 재구성하며, 그 자체로 그 유산의 본질적 일부가 된다.

Defective product data is often very few because it is difficult to obtain defective product data while good product data is rich in manufacturing system. One of the frequently used methods to resolve the problems caused by data imbalance is data augmentation. Data augmentation is a method of increasing data from a minor class with a small number of data to be similar to the number of data from a major class with a large number of data. BAGAN-GP uses an autoencoder in the early stage of learning to infer the distribution of the major class and minor class and initialize the weights of the GAN. To resolve the weight clipping problem where the weights are concentrated on the boundary, the gradient penalty method is applied to appropriately distribute the weights within the range. Data augmentation techniques such as SMOTE, ADASYN, and Borderline-SMOTE are linearity-based techniques that connect observations with a line segment and generate data by selecting a random point on the line segment. On the other hand, BAGAN-GP does not exhibit linearity because it generates data based on the distribution of classes. Considering the generation of data with various characteristics and rare defective data, MO1 and MO2 techniques are proposed. The data is augmented with the proposed augmentation techniques, and the performance is compared with the cases augmented with existing techniques by classifying them with MLP, SVM, and random forest. The results of MO1 is good in most cases, which is believed to be because the data was augmented more diversely by using the existing oversampling technique based on linearity and the BAGAN-GP technique based on the distribution of class data, respectively.

본 연구는 뇌 DWI에서 딥러닝 적용 시 48채널과 8채널 헤드 코일 간 영상 품질의 차이를 분석하는 것을 목표로 하였다. 3.0T MRI를 사용하여 두 종류의 코일을 비교하였으며, 딥러닝 알고리즘의 효과를 확인하기 위해 SNR(신호 대 잡음비), ADC(겉보기 확산 계수), SSIM(구조적 유사성 지수)을 측정하였습니다. 연구 결과에 따르면, 딥러닝 적용 후 b-value에 따른 두 코일 간의 차이가 나타났다. 특히 b-value 0 및 1000에서는 딥러닝 적용 전후에 두 코일 간 통계적으로 유의미한 차이가 없었지만, b-value 3000에서는 적용 전후 모두에서 유의미한 차이가 있었다. SSIM 분석에서도 딥러닝 적용 전후 차이는 없었으나, b-value에 따른 차이가 측정되었습니다. 이러한 차이는 영상 판독에 영향을 미칠 수 있으며, 이를 개선하기 위해서는 딥러닝 알고리즘이 부위별, 코일별, 펄스 시퀀스별로 최적화 될 필요가 있다. 따라서 본 연구는 향후 딥러닝 기반 MRI 영상의 정확도와 일관성을 높이기 위한 기초 정보를 제공 하며, 임상적 적용에서 부위별, 수신 코일별, 펄스 시퀀스별로 세분된 딥러닝의 최적화가 필요하다.

This paper is a quantitative follow-up study of Lee’s (2017) qualitative examination on the usage of Korean human nouns for inanimate/non-human referents. It investigated the usage of “demonstrative + human noun” construct (e.g., yay ‘this child,’ i-chinkwu ‘this friend’) referring to inanimate referents by examining various factors that were chosen based on findings and discussions from Lee (2017) and Kim (2018, 2021). Statistical results conformed to the findings of these earlier studies, showing that human nouns referring to inanimate referents were favored when referents were compared to other things or had concrete concept. In addition, it was also revealed that formality conditioned the realization of human noun usage as human nouns for inanimate/non-human referents were favored in less formal contexts. These results provided a quantitative verification of Lee’s (2017) findings and additional insights to Kim (2018, 2021) along with the usefulness of interdisciplinary approaches to understanding sociolinguistic variables.

자기공명영상은 인체 내부 구조와 병변을 비침습적으로 시각화하는 핵심 의료 영상 기법으로 자리 잡고 있으며, 특히 신경계 및 심혈관계 질환과 같은 복잡한 질병의 진단에서 필수적인 도구로 활용되고 있다. 기존의 자기공명영상 시스 템은 영상의 해상도와 신호대잡음비에서 한계가 있었으나, 최근의 기술 발전은 이러한 한계를 극복하고 진단 정확성 을 높이는 방향으로 나아가고 있다. 고자기장 자기공명영상 시스템의 도입은 해상도와 신호대잡음비를 개선하는 데 기여하고 있으며, 병렬 영상 기법은 촬영 속도를 향상시키면서도 영상 품질의 손실을 최소화한다. 또한, 압축 센싱 (compressed sensing) 기술은 데이터 획득 시간을 줄여 촬영 효율성을 높이는 데 중요한 역할을 하고 있다. 최근 인공지능(AI)의 발전으로, 자기공명영상 데이터에서 초해상도 복원(super-resolution) 및 노이즈 제거와 같은 영상 후처리 기술이 획기적으로 향상되었다. 인공지능 기반의 영상 향상 기술은 저해상도 데이터를 고해상도로 변환하고, 촬영 과정에서 발생할 수 있는 왜곡과 노이즈를 효과적으로 제거하여, 더 정확하고 명확한 진단 영상을 제공한다. 이러한 발전은 단순히 영상의 품질을 높이는 것을 넘어, 임상 진단의 정확성과 효율성을 크게 향상시키고 있으며, 특히 제한된 촬영 시간을 요구하는 응급 상황에서 유용성이 두드러진다. 본 논문에서는 자기공명영상 촬영 기법의 최신 발전과 인공지능 기반 영상 향상 기술의 동향을 여러모로 분석하고, 이들의 임상적 유용성을 조명함으로써 고해 상도 자기공명영상이 의료 분야에서 가지는 의미와 향후 발전 방향을 제시하고자 한다.

This study investigates the performance characteristics of electrodeposited (ED) silver nanowires (AgNWs) networks as transparent conducting electrodes (TCEs) considering Cu(In,Ga)Se2 (CIGS) thin-film solar cells. The electrodeposition process uniformly deposits silver onto a network of spin-coated AgNWs, resulting in the enlargement of individual nanowire diameters and the formation of stronger interconnections between the AgNWs. This structural enhancement significantly improves both the electrical conductivity and thermal stability of the ED AgNW networks, making them more efficient and robust for practical applications in solar cells. The study comprehensively examines the optoelectronic properties of the ED AgNW networks, encompassing total and specular transmittance, transmission haze values, and sheet resistance, with varying durations of silver electrodeposition. Additionally, this study presents the current density (J)-voltage (V) characteristics of CIGS thin-film solar cells employing the ED AgNW TCEs, revealing how electrodeposition duration impacts overall device performance. These findings offer valuable insights for optimizing TCEs in not only thin-film solar cells but also in other optoelectronic devices, highlighting the potential for improved long-term stability across various applications without compromising performance.

Airpower plays a key role in neutralizing military threats and securing victory in wars. This study analyzes newly introduced fighter forces by considering factors like performance, power index, operational environment, airbase capacity, survivability, and sustainment capability to devise an optimal deployment strategy that enhances operational efficiency and effectiveness. Using optimization methods like mixed integer programming (MIP), the study incorporates constraints such as survivability and mission criticality. The focus is on major Air Force operations, including air interdiction, defensive counter-air, close air support, and maritime operations. Experimental results show the proposed model outperforms current deployment plans in both wartime and peacetime in terms of operations and sustainment.

North Korea has repeatedly provoked using unmanned aerial vehicles (UAVs), and the threat posed by UAVs continues to escalate, as evidenced by recent directives involving the use of waste-laden balloons and the development of suicide drones. North Korea’s small UAVs are difficult to detect due to their low radar cross-section (RCS) values, necessitating the efficient deployment and operation of assets for effective response. Against this backdrop, this study aims to predict the infiltration routes of enemy UAVs by considering their perspective, avoiding key facilities and obstacles, and propose deployment strategies to enable rapid detection and response during provocations. Utilizing the Markov Decision Process (MDP) based on previous studies, this research presents a model that reflects both UAV flight characteristics and regional environments. Unlike previous models that designate a single starting point, this study addresses the practical challenge of uncertainty in initial infiltration points by incorporating multiple starting points into the scenarios. By aggregating and integrating the probability maps derived from these variations into a unified map, the model predicts areas with a high likelihood of UAV infiltration over time. Furthermore, based on case studies in the capital region, this research proposes deployment strategies tailored to the specifications of currently known anti-drone integrated systems. These strategies are expected to support military decision-making by enabling the efficient operation of assets in areas with a high probability of UAV infiltration.

This study proposes a mathematical model to optimize the fighter aircraft-weapon combinations for the Republic of Korea Air Force. With the recent emergence of the population cliff issue due to declining birth rates in Korea, there is an urgent need for efficient weapon system operations in light of decreasing military personnel. This study aims to enhance operational environments and mission efficiency within the military. The objective is to reduce the workload of pilots and maintenance personnel by operating an optimal number of weapons instead of deploying all possible armaments for each aircraft type. To achieve this, various factors for optimizing the fighter-weapon combinations were identified and quantified. A model was then constructed using goal programming, with the objective functions based on the compatibility, Circular Error Probable (CEP), and fire range of the weapons, along with the planned wartime mission-specific weapon ratios for each aircraft type. Experimental analysis of the proposed model indicated a significant increase in mission performance efficiency compared to the existing system in both operational and maintenance aspects. It is hoped that this model will be applied in military settings.