대벌레(Ramulus mikado)는 1990년 이후부터 2000년대 초반까지 경북을 중심으로 대발생을 하였던 돌발 해충 으로 2020~2023년에 수도권에서 대발생 사례가 다수 보고 되었다. 대벌레의 대발생 원인으로 기후변화가 지목되 고 있지만, 대벌레 개체군과 생물적·비생물적 환경 조건과의 관계를 이해하기 위한 연구는 매우 부족한 실정이 다. 본 연구에서는 주요 기주식물과 대벌레 발생 양상에 대한 관계를 이해하고자 수행하였다. 2022년부터 2023년 까지 대벌레 대발생 지역 중 하나인 청계산 일대 등산로를 따라 조사구를 선정한 뒤 주요 기주식물이자 우점종인 신갈나무, 아까시나무, 잔털벚나무를 대상으로 대벌레의 발생 밀도를 조사하였다. 그 결과, 조사지점 간의 대벌 레 평균 밀도는 유의한 차이가 발견되지 않았지만, 기주식물에 따른 밀도의 차이는 뚜렷하게 나타났다.

In 2020, severe defoliation was reported in Abies holophylla plantations located in Hwacheon-gun, Gangwon-do. This damage was attributed to an outbreak of an unidentified sawfly species from the genus Cephalcia (Hymenoptera: Pamphiliidae). The larvae of this sawfly caused significant defoliation of the leaves. This pest has been identified as Cephalcia koreana Park & Jung, sp. nov., described as a new species in 2023. To investigate the occurrence pattern and density of C. koreana, we set up emergence traps and analyzed samples from affected branches. Our results showed that the density peaks for adults, eggs, and larvae were in mid-May, late May, and early June of 2021, respectively. However, their density decreased sharply after a notably cold spring period in 2022. Here, I aim to discuss the outbreaks of insect pests and their population dynamics.

This study (1) explored spatio-temporal population distribution patterns in Jeonju by using emerging hot spot analysis and (2) identified the influential factors to determine the spatio-temporal patterns by using multinomial logit model. The major findings are as follows. First, the results of emerging hot spot analysis indicated that the 100*100m grid in the urban area of Jeonju was found to have a category of hot spots, whereas most of the cold spot series was concentrated in the outskirts of the city. Also, new towns such as Jeonju Eco City, Jeonbuk Innovation City, and Hyocheon District were persistent or intensifying hot spots, Third, the results of multinomial logit model revealed that the factors influencing deterrmining the spatio-temporal patterns were accessibility to schools, hospitals, parks, and walfare services. This study offered a deeper understanding of urbanization and regional changes in Jeonju, and important information for urban planning.

The Fourth Industrial Revolution and sensor technology have led to increased utilization of sensor data. In our modern society, data complexity is rising, and the extraction of valuable information has become crucial with the rapid changes in information technology (IT). Recurrent neural networks (RNN) and long short-term memory (LSTM) models have shown remarkable performance in natural language processing (NLP) and time series prediction. Consequently, there is a strong expectation that models excelling in NLP will also excel in time series prediction. However, current research on Transformer models for time series prediction remains limited. Traditional RNN and LSTM models have demonstrated superior performance compared to Transformers in big data analysis. Nevertheless, with continuous advancements in Transformer models, such as GPT-2 (Generative Pre-trained Transformer 2) and ProphetNet, they have gained attention in the field of time series prediction. This study aims to evaluate the classification performance and interval prediction of remaining useful life (RUL) using an advanced Transformer model. The performance of each model will be utilized to establish a health index (HI) for cutting blades, enabling real-time monitoring of machine health. The results are expected to provide valuable insights for machine monitoring, evaluation, and management, confirming the effectiveness of advanced Transformer models in time series analysis when applied in industrial settings.

The bitterling (Cyprinidae, Acheilongnathinae) is a temperate freshwater fish with a unique spawning symbiosis with host mussels. Female bitterlings use their extended ovipositors to lay eggs on the gills of mussels through the mussel's exhalant siphon. In the present study, in April of 2020, we investigated spawning frequencies and patterns of three bitterling fish species in host mussel species in the Nakdong River basin (Hoecheon). During field surveys, a total of four bitterling and three mussel species were found. We observed bitterling's spawning eggs/larvae in the three mussel species: Anodonta arcaeformis (proportion spawned: 45.5%), Corbicula fluminea (12.1%), and Nodularia douglasiae (45.2%). The number of bitterlings’ eggs/larvae per mussel ranged from 1 to 58. Using our developed genetic markers, we identified the eggs/ larvae of each bitterling species in each mussel species (except for A. macropterus): A. arcaeformis (spawned by Acheilognathus yamatsutae), C. fluminea (A. yamatsutae and Tanakia latimarginata), and N. douglasiae (A. yamatsutae, Rhodeus uyekii, and T. latimarginata). Approximately 57.6% of N. douglasiae mussel individuals had eggs/ larvae of more than one bitterling species, suggesting that interspecific competition for occupying spawning grounds is intense. This is the first report on bitterling’s spawning events in the Asian clam C. fluminea from Korea; however, it should be ascertained whether bitterling’s embryo undergoes successful development inside the small mussel and leaves as a free-swimming juvenile. In addition, the importance of its conservation as a new host mussel species for bitterling fishes needs to be studied further.

The purpose of this study is to review the discourse on vaccination from a critical perspective by considering coronavirus disease 2019 (COVID-19) news on web portals to be practical arguments advocating for certain actions. For this purpose, this study analyzed the argument patterns of the discourse on vaccination with the keyword COVID-19 vaccine side effects and examined discourse characteristics highlighted by media reports to evaluate their meaning. Contrasting patterns were observed between pro- and anti-vaccine arguments, which consisted of the necessity of vaccination and medical evidence and which focused on personal choice and vaccine side effects, respectively. The characteristics of the political discourse were observed in the contest between these arguments. Rhetorical phrases, which are often used in the political discourse, represented the misleading arguments that lacked evidential accuracy and argumentative validity by maximizing fear, instead of alleviating fear about a health crisis with scientific information and discussion. As fake news trending on social media was introduced to online news portals, which are regarded as public discourse platforms, and undermined trust in the public discourse, it served as an opportunity to politicize the discourse on vaccination.

The objective of this study was to explore the symbolism associated with phoenix patterns in China and the temporal aesthetic characteristics of these patterns found in Dunhuang Mogao Grottoes. The study involved collecting examples of clothing designs featuring phoenix patterns from China Fashion Week and the Vogue website, spanning from spring and summer of 2016 to fall and winter of 2022. After collecting and organizing these examples, representative cases were selected for analysis. The objective was to identify effective techniques for incorporating phoenix patterns within the context of Dunhuang Mogao Grottoes and provided insights for future clothing design and textile pattern design research. Phoenix patterns boasted a lengthy history and were laden with symbolic meaning. Early renditions of phoenix patterns found at Mogao Grottoes in Dunhuang were relatively simplistic in design, mainly employing elements like rhythm, coordination, balance and symmetry to convey a sense of nature and gravity. Over time, these patterns evolved under the influence of the prevailing cultural backdrop, employing repeated emphasis to portray notions of abundance and tenacity. Furthermore, regarding the use of phoenix patterns in clothing, there were four prevalent expression techniques: embroidery, beading, printing, and knitting. Traditional techniques like embroidery and beadwork often prioritized aesthetic features like coordination, emphasis, and symmetry, thereby showcasing the opulent characteristics of phoenix patterns. On the other hand, printing and knitting techniques used a single phoenix pattern or a modified version to simplify designs by emphasizing or repeating aesthetic characteristics while adhering to a modern artistic approach.

본 연구는 혁신 생태계 조성을 통한 경제성장 뿐만 아니라 자기고용을 통한 실업해소, 성장 단계별 적절한 인재 채용을 통한 고용창출 등 작금에 우리가 직 면한 사회·경제적 문제를 해결하기 위한 수단으로 창업이 매력적인 대안이 될 수 있음을 전제하였다. 나아가, 이와 같은 전제를 바탕으로 실질창업 활성화에서 중요한 것은 기회인식임을 제안하였고 기회인식에 영향을 미치는 변수들을 규명 하였다. 구체적으로, 기업가정신이 기회발견행동 및 창업기회인식에 미치는 영향 과 기회발견행동이 창업기회인식에 미치는 영향을 구조방정식 모델을 통해 실증 하였다. 또한 기업가정신과 창업기회인식의 관계에서 기회발견행동의 매개효과를 실증하였다. 연구결과 첫째, 기업가정신은 창업기회인식은 물론 기회발견행동을 구성하는 4개의 하위변수에 모두 통계적으로 매우 유의미한 영향을 미치는 것으 로 나타났다. 둘째, 기회발견행동의 하위 변수 중 관찰과 아이디어 네트워킹은 창업기회인식에 통계적으로 유의미한 영향을 미치는 것으로 나타났다. 셋째, 기 업가정신이 창업기회인식에 미치는 영향에서 아이디어 네트워킹의 매개효과가 검증되었다. 본 연구는 이상의 실증분석 결과를 바탕으로 기업가정신 및 창업교 육 혁신을 중심으로 이론적·실무적 시사점을 제안하였음에 의의가 있다.

This study aimed to provide fundamental data that could guide high school students' night eating behavior by investigating habits of their night eating consumption during COVID-19 pandemic (From 2021/5/13 to 5/20). Association between their eating habits and the Nutrition Quotient for Korean Adolescents (NQ-A) were also explored. This study included a total of 604 students, among whom 441 students were identified as night eating consumers. Among all subjects, 30.5% consumed night eating 3~4 times a week, 27.3% consumed 1-2 times a week, and 27.0% did not consume any night eating at all. The high-night eating group had a higher score of total NQ-A than the non-night eating group for both male (p<0.05) and female (p<0.001) students. This was because male students in the high-night eating group reported significantly higher rates of daily dinner consumption compared to non-night eating group. Furthermore, both male (p<0.05) and female (p<0.001) students showed a significant increase in ‘Moderation’. ‘Diversity’ was also significantly increased in female studies (p<0.05) as subcategories of dietary habits according to night eating frequency. These findings highlight the need for practical research to develop nutritional guidelines for night eating that reflect preferences of students while providing adequate nutritional habits.

본고는 언중들이 사용하고 있는 구어와 문어를 전사한 말뭉치에 나타 난 ‘-겠-’의 분포 양상을 기술하고 구어 말뭉치와 문어 말뭉치에서 분포 양상의 차이점을 제시하는 데 목적이 있다. 본고는 21세기 세종 계획의 결과물들 중 590만 어절 구어 말뭉치에서 선어말어미 ‘-겠-’이 나타나 는 200개의 텍스트, 4313개의 문장과 2364만 어절 문어 말뭉치에서 선어말어미 ‘-겠-’이 나타나는 200개의 텍스트, 13083개의 문장을 연 구 대상으로 삼았다. 연구 방법으로는 선어말어미 ‘-겠-’이 사용되는 문장을 통해 어떤 용언 뒤에 분포하는지를 면밀하게 살펴서 첫째, 구어 말뭉치와 문어 말뭉치에서 ‘-겠-’과 결합하는 빈도수가 가장 많은 용언 10개를 뽑았으며 둘째, 문장에서 ‘-겠-’이 어떤 선어말어미 뒤에 가장 많이 분포하는지를 하나씩 조사하며 셋째, 선어말어미 ‘-겠-’ 뒤에 어 떤 어말어미가 많이 결합하는지를 찾아내고자 한다. 본고는 구어 말뭉 치와 문어 말뭉치에 나타난 ‘-겠-’의 분포 양상을 정리하고 두 말뭉치에 서 나타난 차이점을 밝혔으며, 이 연구가 한국어 교육 현장에 기초 자료 로 활용될 수 있다는 점에 의의가 있다.

이 연구는 팬데믹(pandemic) 전후 국제항공여객 운송시장을 대상으로 항공편 운항에 의한 CO2 배출 특성과 변화를 체계적으 로 파악하는 것을 주요 목적으로 한다. 이를 위해 2019년과 2021년 2분기 전 세계 국제여객 항공편 스케줄 데이터를 기반으로 ICAO(International Civil Aviation Organization)의 CERT(CO2 Estimation and Reporting Tool) 인벤토리를 이용하여 노선 단위의 CO2 배출량을 추정한 후, 노선의 대권 거리와 항공기의 크기를 기준으로 구분된 하부시장에 따른 CO2 배출량과 배출 효율성의 분포와 변화를 비교분석하였다. 주요 분석 결과는 다음과 같다. 첫째, 2021년 2분기 전 세계 국제항공여객 운송시장의 CO2 배출량은 약 31.6백만 톤으로 추정되었으며. 2019년 동 분기(117.95백만 톤) 대비 약 73.21% 감소하였다. 두 시기 모두 5,000km 이상의 장거리 시장, 그리고 100~400석 항공기 운용 시장에서의 배출량 비중이 높게 나타났다. 다만 팬데믹 기간에는 5,000km 이상, 그리고 400석 이상 항공기 시장에서 CO2 배출량의 감소가 두드러지게 나타났다. 둘째, 2021년 2분기 시장의 CO2 배출 효율성은 2019년 동 분기 대비 약 4% 향상되었다. 두 시기 모두 노선의 대권 거리와 항공기의 크기가 증가할수록 배출 효율성이 감소하는 경향이 존재하였으며, 팬데믹 기간 중 일부 하부시장에서는 구형 및 초대형 기종들의 운항 감축(혹은 중단)이 두드러짐에 따라 배출 효율성이 향상되기도 하였다. 마지막으로 팬데믹 전후 주요 국제노선들의 CO2 배출 효율성 변화를 탐색한 결과, 글로벌 허브 공항들을 연결하는 대륙 간 장거리 노선들을 중심으로 효율성이 낮게 나타난 반면, 차상위 계층 공항들과 연결된 일부 노선들, 그리고 동남아･동북아의 주요 공항들을 연결하는 역내 노선들은 상대적으로 효율성이 높게 나타났다. 본 연구는 팬데믹 전후 전 세계 국제항공여객 운송시장의 운영 실적과 CO2 배출에 대한 세부 특성과 변화를 실증적으로 분석했다는 점에서 의의가 있다.

This study proposes a new collaborative filtering model that integrates Restricted Boltzmann Machines. The proposed two-stage model is applied to household-level supermarket purchase data. Results show that our model fits the data better and outperforms existing collaborative filtering methods in predicting shopping patterns. The proposed model also improves interpretations of market complexity and common causes of coincidence associated with customers’ multi-category purchases.

A new type of food created in laboratories – lab grown meat (LGM) is an alternative to traditional animal farming and attracting attention of media, industry experts and consumers. Why is this new product so controversial? It is claimed that cell-based meat production is more environmentally friendly, ethical and sustainable than traditional methods that involve animals. Hence, being less harmful and potentially slowing down environmental degradation that leads to climate change. However, consumers have concerns regarding product quality, sourcing of cells used for production and use of growth serums. So many differing views are present, even before LGM is introduced as a marketable product. This paper examines what drives public discourse regarding how this new industry can be regulated, technology and how social media posts, fake news and publicly available rhetoric address consumer concerns and consumer acceptance regarding this new food category.

While metadiscourse use has been well-attended in second language (L2) writing research, relatively less effort has been made in documenting changing patterns of metadiscourse use among L2 writers. The present study addressed this gap by probing a diachronic change of interactive metadiscourse in research articles published in English Teaching across a span of 40 years. Using the corpus of 931 articles written by Korean L2 writers, we examined whether, and to what extent, interactive metadiscourse use in academic writing had changed over time. Our findings revealed an overall increase in the frequency of interactive resources mainly driven by a significant increase of evidentials. The observed pattern of change in interactives suggests that academic discourse within the applied linguistics community in Korea is becoming more persuasive and reader-oriented over time, consistent with Hyland and Jiang (2018) who reported a dramatic rise in interactive metadiscourse in the global discourse community of applied linguistics.

To make semiconductor chips, a number of complex semiconductor manufacturing processes are required. Semiconductor chips that have undergone complex processes are subjected to EDS(Electrical Die Sorting) tests to check product quality, and a wafer bin map reflecting the information about the normal and defective chips is created. Defective chips found in the wafer bin map form various patterns, which are called defective patterns, and the defective patterns are a very important clue in determining the cause of defects in the process and design of semiconductors. Therefore, it is desired to automatically and quickly detect defective patterns in the field, and various methods have been proposed to detect defective patterns. Existing methods have considered simple, complex, and new defect patterns, but they had the disadvantage of being unable to provide field engineers the evidence of classification results through deep learning. It is necessary to supplement this and provide detailed information on the size, location, and patterns of the defects. In this paper, we propose an anomaly detection framework that can be explained through FCDD(Fully Convolutional Data Description) trained only with normal data to provide field engineers with details such as detection results of abnormal defect patterns, defect size, and location of defect patterns on wafer bin map. The results are analyzed using open dataset, providing prominent results of the proposed anomaly detection framework.

Recently, a novel cast-in specialty insert was developed in Korea as an anchor for lightweight pipe supports, including fire-protection pipes. As these pipe supports and anchors play a critical role in transferring loads of fire-protection pipes to structural members, it is crucial to evaluate their seismic performance before applying the newly developed insert. In this study, the seismic shear performance of the insert anchors was evaluated through cyclic loading tests based on the loading protocols of ACI 355.2 and FEMA 461. Initially, five monotonic loading tests were conducted on the insert anchors in cracked concrete, followed by cyclic loading tests based on the monotonic test results. The findings revealed that the insert anchors exhibited negligible decrease in shear strength even after cyclic loading. Furthermore, a comparison of the maximum load and displacement of the insert anchors obtained under the loading protocols of ACI 355.2 and FEMA 461 was performed to investigate the applicability of the FEMA 461 loading protocol for anchor performance evaluation.