본 연구는 영유아교육기관에서 부르는 노랫말에 담긴 공동체성을 살펴 봄으로써 유아교육을 통한 공동체성 회복과 확장의 가능성을 찾고자 하 였다. 이를 위해 자료 제공 협조가 가능한 P시의 유치원과 어린이집 10 개 기관에서 2020~2023학년도에 불렀던 457개 노래를 수집하였다. 연구 자 2인과 유아교육전문가 1인이 수집한 곡 중 최종 297곡을 선정하였고, 워드클라우드 분석과 전문가포커스면담을 통해 노랫말에 담긴 공동체성 을 범주화하였다. 그 결과 노랫말에 담긴 공동체성은 첫째, ‘일상생활 속 에서 함께 하는 나’, ‘함께 자라나는 나’의 상위범주를 통해 ‘공동체망 속 에 아이가 존재하다’였다. 둘째, ‘따뜻한 관계망 만들기’, ‘모든 생명 존 중하기’의 상위범주를 통해 ‘생명의 관계성을 만들어 가다’였으며, 셋째, ‘사랑과 평화의 세상 만들기’의 상위범주를 통해 ‘사랑과 평화의 공동체 를 꿈꾸다’로 분석되었다. 본 연구를 통해 영유아의 공동체성 함양과 회 복에 대한 중요성을 인식하고, 영유아교육기관은 공동체성 함양을 위한 최초의 역할과 책무성을 가지고 공동체성을 내포하는 노랫말을 담은 노 래 지도를 통해 미래 사회를 살아갈 영유아들의 공동체성 회복을 도모해 야 함을 논의하였다.

Recent advances in computer technology have made it possible to solve numerous challenges but require faster hardware development. However, the size of the classical computer has reached its physical limit, and researchers' interest in quantum computers is growing, and it is being used in various engineering fields. However, research using quantum computing in structural engineering is very insufficient. Therefore, in this paper, the characteristics of qubits, the minimum unit of quantum information processing, were grafted with the crow search algorithm to propose QCSA (quantum crow search algorithm) and compare the convergence performance according to parameter changes. In addition, by performing the optimal design of the example truss structure, it was confirmed that quantum computing can be used in the architectural field.

본 연구는 취업 준비 대학생 379명을 대상으로 설문조사를 실시하여 취업 불안과 구직효능감 수준에 따른 군집유형 분류 및 취업준비행동의 차이를 분석하였다. 수집된 자료는 SPSS 26.0을 사용하여 기술통계분 석, 2단계 군집분석, 일원배치분산분석을 실시하였고, 이를 통해 군집을 분류하고 군집 간 차이를 분석하였다. 연구결과는 다음과 같다. 첫째, 취 업불안과 구직효능감에 따른 군집은 4개의 군집으로 분류되었다. 군집1 은 ‘낮은불안-낮은효능감 집단’으로, 군집2는 ‘낮은 불안-높은 효능감 집 단’, 군집3은 ‘높은불안-중간효능감 집단’, 군집4는 ‘높은 불안-매우 낮 은 효능감 집단’으로 명명하였다. 둘째, 군집 간의 취업준비행동은 차이 가 있는 것으로 나타났다. 군집2(낮은 불안-높은 효능감 집단)와 군집3 (높은불안-중간효능감 집단)은 군집1(낮은 불안-낮은 효능감 집단)와 군 집4(높은 불안-매우 낮은 효능감 집단)에 비해 취업준비행동을 더 적극 적으로 하는 것으로 나타났다. 이러한 결과는 대학생 취업지도 분야에서 군집유형별 진단을 통해 맞춤형 취업 지원 방안이 필요함을 보여주고 있 다. 끝으로 연구의 시사점과 한계점, 향후 연구과제에 대해 논의하였다.

This study utilized text mining analysis to identify keywords used in the research of gray mold (Botrytis cinerea), taking into account horticultural crops, environmental or physical treatments, and chemical or material factors. Data spanning from 1980 to 2021 was gathered from ScienceON and interpreted using word cloud visualization analysis following post-processing. Morphological analysis and coding were conducted using the text mining packages library tm provided by the R program. Our review of B. cinerea included and analyzed 7,342 papers. Among the extracted words, those related to crops and ranking in the top 10 were tomato, strawberry, grape, apple, cucumber, bean, kiwifruit, rose, pepper, and pear. roses were the only flower in the top 10 horticultural crops. Research has explored environmental or physical treatment factors such as storage, temperature, cold, seasons, humidity, heat/hot UV-C, sprays, films, and coatings. Chemical or material words included fungicide, chitosan, ethylene, oil, ROS, ABA, VOC, glucose, carbon, and ethanol.

글로벌 경제위기, 저성장 기조의 장기화, 인구구조 변화에 따른 한국 노동시장의 구조적 변화로 실업자가 빠르게 증가하고 있다. 실업급여 수 급자의 증가와 더불어, 허위·형식적 구직활동도 동시에 증가하고 있다. 본 연구의 목적은 허위·형식적으로 구직활동을 하는 상황을 개선하기 위 한 것으로, 이를 위해 고용복지플러스센터 담당자를 대상으로 실업인정 을 받기 위한 주된 구직활동 대상자와 구직활동 행동 등을 유형에 따라 파악하고 이에 따른 증빙서류의 적절성 여부, 구직활동 참여 등 허위형 식적 구직활동에 대한 실태를 파악하여 정책적 시사점을 제시하였다. 연 구자료는 고용센터 담당자 설문조사, FGI, 전문가 자문을 실시하였고, 분 석방법은 컨조인트 분석을 실시하였다. 컨조인트 분석을 통해 허위·형식 적 구직활동의 잠재적인 대상자는 반복수급자, 중고령자, 장기실업자, 구 직활동 대상자로 나타났다. 정책 개선으로 구직활동 인정 범위에서 구직 활동 외 활동 사항만으로 인정되는 기준 개편과 실업인정 기준 외 연장 급여 부분의 개선을 제안하였다.

The study confirmed the "house search report(家宅搜索調書)" containing criminal records during the Japanese colonial period, as well as the production process and the way of expressing the illustrations contained in them. It also explored architectural values through analysis of the location and use of the building. This records the discovery of evidence by searching the residences of those involved in the crime from 1919 to 1922. The illustrations contained in this record were not standardized, so the contents of the article differed depending on the author's background and cultural experience. Nevertheless, this painting reflects the regional characteristics of traditional houses located throughout the Korean Peninsula. It is also evidence that the house was used for cultural, commercial, and industrial purposes, beyond the general assumption that it was used only for residential purposes. The "House Search Report(家宅搜索調書)" provides information on ordinary buildings that existed as the background of everyday life, rather than buildings with a specific purpose or exceptional design. It is evaluated as an important resource for understanding the diverse life and spatial structures of buildings during that time.

The Nuclear Export and Import Control System (NEPS) is currently in operation for nuclear export and import control. To ensure consistent and efficient control, various computational systems are either already in place or being developed. With numerous scattered systems, it becomes crucial to integrate the databases from each to maximize their utility. In order to effectively utilize these scattered computer systems, it is necessary to integrate the databases of each system and develop an associated search system that can be used for integrated databases, so we investigated and analyzed the AI language model that can be applied to the associated search system. Language Models (LM) are primarily divided into two categories: understanding and generative. Understanding Language Models aim to precisely comprehend and analyze the provided text’s meaning. They consider the text’s bidirectional context to understand its deeper implications and are used in tasks such as text classification, sentiment analysis, question answering, and named entity recognition. In contrast, Generative Language Models focus on generating new text based on the given context. They produce new textual content continuously and are beneficial for text generation, machine translation, sentence completion, and storytelling. Given that the primary purpose of our associated search system is to comprehend user sentences or queries accurately, understanding language models are deemed more suitable. Among the understanding language models, we examined BERT and its derivatives, RoBERTa and DeBERTa. BERT (Bidirectional Encoder Representations from Transformers) uses a Bidirectional Transformer Encoder to understand the sentence context and engages in pre-training by predicting ‘MASKED’ segments. RoBERTa (A Robustly Optimized BERT Pre-training Approach) enhances BERT by optimizing its training methods and data processing. Although its core architecture is similar to BERT, it incorporates improvements such as eliminating the NSP (Next Sentence Prediction) task, introducing dynamic masking techniques, and refining training data volume, methodologies, and hyperparameters. DeBERTa (Decoding-enhanced BERT with disentangled attention) introduces a disentangled attention mechanism to the BERT architecture, calculating the relative importance score between word pairs to distribute attention more effectively and improve performance. In analyzing the three models, RoBERTa and DeBERTa demonstrated superior performance compared to BERT. However, considering factors like the acquisition and processing of training data, training time, and associated costs, these superior models may require additional efforts and resources. It’s therefore crucial to select a language model by evaluating the economic implications, objectives, training strategies, performance-assessing datasets, and hardware environments. Additionally, it was noted that by fine-tuning with methods from RoBERTa or DeBERTa based on pre-trained BERT models, the training speed could be significantly improved.

PURPOSES : A model for minimizing cutting loss and determining the optimum layout of blocks in pavements was developed in this study. METHODS : Based on literature review, a model which included constraints such as the amount, volume, overlap, and pattern, was developed to minimize the cutting loss in an irregular pavement shape. The Stach bond, stretcher bond, and herringbone patterns were used in this model. The harmony search and particle swarm algorithms were then used to solve this model. RESULTS : Based on the results of the model and algorithms, the harmony search algorithm yielded better results because of its fast computation time. Moreover, compared to the sample pavement area, it reduced the cutting loss by 20.91%. CONCLUSIONS : The model and algorithms successfully optimized the layout of the pavement and they have potential applications in industries, such as tiling, panels, and textiles.

소비자의 감성과 다양한 섬유·패션 기술이 융합되는 하이테크 감성 섬유패션은 중요한 산업군이다. 섬유·패션 산 업의 환경 변화로 인해 감성과학 분야에서 학제간 협업을 통해 타 분야를 이해하고 아이디어를 교류함으로써 창의적 으로 실무에 적용할 수 있는 능력을 키우는 것이 중요하다. 학제간 연구와 협업을 통해 급변하는 미래사회에 필요한 창의적 융합형 지적 능력은 물론 타인과 공감하는 능력을 갖추어 4차 산업혁명 시대를 선도하는 인재를 양성하는 것이 필요하다. 이에 관련의 전문가 양성 방향을 수립하기 위하여 이를 모색하고자 기초 연구를 실시하였다. 국내외 감성섬유패션 산업의 현황과 교육 과정을 조사하였고 이를 바탕으로 융복합적으로 교육이 가능할 것으로 보이는 학 습내용을 구상해보았다. 섬유패션 감성과학 전문가를 양성하기 위한 방법으로 기초과정은 섬유·패션산업 분야의 감 성과학과 ICT 관련 내용 학습을 통해 기초지식을 습득하고, 심화로서는 감성을 바탕으로 한 PB방식의 아이디어 디자인의 도출부터 소비자 감성 분석 및 제품 개발까지의 과정을 스마트 키트 실습을 통해 체험할 수 있도록 하며, ICT 융합 제품 개발 과정에서 발생하는 지식재산권을 스타트업 및 신지식권으로 설정하는 다양한 방법들을 다루어 감성 섬유패션 기술에 대한 지식재산권을 확보하는 방안 내용을 제안하였다.

인구와 경제가 집중되고, 문화와 여가 등 다양한 분야에서 핵심적인 역할을 수행하는 서울시는 이면에 공간 불평등으로 인한 문제가 대두되고 있다. 이 연구는 서울시의 공간 불평등을 규명하기 위한 첫 단계로 상류층과 빈곤층의 주거지 분화를 탐색하는 데 목적을 두었다. 주거지 분화를 규명하기 위해 아파트와 연립다세대 실거래가･공동주택가격･개인 소득 자료가 활용되었으며, 분석 방법으로 커널밀도추정을 이용한 핫스팟 분석이 수행되었다. 분석 결과 상류층 주거지와 빈곤층 주거지는 계층 간 분리와 계층 내 집중이라는 공간적 분포 패턴이 확인되었다. 상류층 주거지는 강남구를 위시한 소위 강남3구에, 빈곤층 주거지는 도시 외곽에 집중되어 있었다. 주거지 분화와 이로 인해 발생하는 여러 분야의 불평등에 관한 연구가 지속적으로 이루어질 필요가 있으며, 이 연구가 주거지별 격차와 공간 불평등을 다루는 연구의 초석이 되길 기대해 본다.

Technosignature, previously known as SETI(search for extraterrestrial intelligence), is the scientic evidence of past or present extraterrestrial civilizations. Since NRAO's Project Ozma was performed in 1960, most of the noticeable technosignature searches have been done by radio telescopes, hoping to find strong and narrow bandwidth signals that cannot be explained by known natural processes. Recently, the Breakthrough Listen project has opened a new opportunity for technosignature by utilizing both optical telescopes, radio telescopes, and next-generation radio telescope arrays. In this review, mainly based on NASA Technosignatures Workshop (2018), we review the current trends of technosignature surveys, as well as other possible methods for detecting technosignature. Also, we suggest what the Korean community could contribute the technosignature research, including the new SETI project with Korea VLBI Network (KVN).

Since the farside of the moon is a place to avoid arti cial radio frequency interference (RFI) created byhuman civilization, it is a most suitable place for searching technosignature, which are signs of technolog-ical civilization in the universe, in the radio band. The RFI is a factor that makes the study of searchingtechnosignature quite complicated because it is di cult to distinguish between technological signals pro-duced by human and extraterrestrial civilizations. In this paper, we review why the farside of the moon isthe best place to detect technosignature and also introduce radio observatories on the farside of the moonthat have been proposed in radio astronomy. The SETI (Search for Extraterrestrial Intelligence) projecton the farside of the moon is expected to be one of the main candidates for international collaborationresearch topics on lunar surface observatory.

"Are we alone in the universe?" is the fundamental question of mankind. To search for the life signaturesin the universe, there have been a lot of researches and space explorations, especially in our solar system. In this review paper, we introduce the de nition and characteristics of the \biosignature". The currentsituations and future plans for searching for biosignatures in our solar system are reviewed, especially atVenus, Mars, and Ocean Worlds such as Europa and Enceladus where life signatures are more likely toexist than in other places in the solar system. Finally, we discuss the opportunities and strategies for theKorean scienti c society to participate in searching for biosignatures in the solar system.

Covid-19 pandemic has significantly affected online advertising market. The pandemic has changed customers’ shopping behavior by decreasing customer traffic in offline businesses but increasing customers’ online activities that has led to growth of online shopping and advertising. While the outbreak of Covid-19 has sparked growth of online advertising in general, its impact on various industries may not be the same, given the differences in product characteristics and consumer behavior across different products and services. This paper aims to address this question by empirically examining how Covid-19 has affected online search advertising market. First, we examine how Covid-19 has affected the behavior of online users and advertisers, the main stakeholders in the search advertising market, in terms of user traffic and clicks and advertiser bids and payments. Second, we examine if the impacts of Covid-19 on behavior of online users and advertisers would be different in various industries.

In this research, we investigate how sponsored listings on an online search engine influence the consumer’s final decision choices. In an era of digital transformation where companies very often opt for sponsored advertisements, we explore how an anchoring effect (exacerbated by other factors) impacts the evaluation process and final outcome. More specifically, using a mix of secondary data from a large hotel aggregator and experiments, this work empirically validates that sponsored results (i.e., the first paid result) on a search engine results page indeed acts as an anchor. In addition, we find evidence the anchoring effect increases as a) the results are more versus less homogeneous, and b) the screen size of the search device is larger. What’s more, the anchoring effect is largely stable and does not fluctuate based on the category or decision importance. The effect also remains intact whether or not search engine results are randomized through the history of the browser. We also find the anchor influences subsequent evaluations, and options similar to the anchor are more likely to be chosen irrespective of the anchor’s attractiveness despite industry convention that consumers ignore sponsored results (see Henderson 2019) and research indicating consumers routinely select organic over sponsored search results.

It is difficult to distinguish the pure signal produced by an orbiting planetary companion around giant stars from other possible sources, such as stellar spots, pulsations, or certain activities. Since 2003, we have obtained radial (RV) data from evolved stars using the high-resolution, fiber-fed Bohyunsan Observatory Echelle Spectrograph (BOES) at the Bohyunsan Optical Astronomy Observatory (BOAO). Here, we report the results of RV variations in the binary star HD 135438. We found two significant periods: 494.98 d with eccentricity of 0.23 and 8494.1 d with eccentricity of 0.83. Considering orbital stability, it is impossible to have two companions in such close orbits with high eccentricity. To determine the nature of the changes in the RV variability, we analyzed indicators of stellar spot and stellar chromospheric activity to find that there are no signals related to the significant period of 494.98 d. However, we calculated the upper limits of rotation period of the rotational velocity and found this to be 478–536 d. One possible interpretation is that this may be closely related to the rotational modulation of an orbital inclination at 67–90 degrees. The other signal corresponding to the period of 8494.1 d is probably associated with a stellar companion orbiting the giant star. A Markov Chain Monte Carlo (MCMC) simulation considering a single companion indicates that HD 135438 system hosts a stellar companion with 0.57+0.017 −0.017 M⊙ with an orbital period of 8498 d.