This study presents a method for analyzing the surface temperatures of specific facilities, such as the 5 MWe reactor within the Yongbyon Nuclear Complex, to explore its potential utility in monitoring suspected nuclear-related activities in North Korea using thermal infrared (TIR) satellite imagery (Landsat series). TIR band data is utilized to derive surface temperatures in the specified areas, and the temperatures are analyzed on a monthly basis to examine any patterns within these regions. This research provides a pattern-of-life on temperature variation for the target areas through multiple TIR image datasets, offering additional information to analyze facilities’ operational status in remote and inaccessible regions.

유기농 생태농업단지 논에서 출현하는 수서곤충의 생태자원 분포 특성을 비교하고자 유기농 단지 논에 둠벙 이 있는 조건과 둠벙이 없는 조건에서의 수서곤충상을 조사하여 관행 논의 분포 특성을 비교하였다. 수서곤충 출현은 둠벙이 있는 유기농 논 5목 15과 26종 413개체, 둠벙이 없는 유기농 논 5목 14과 22종 236개체, 관행 논 5목 11과 16종 155개체로 유기농 논에서 관행 논에 비해 수서곤충의 출현 과, 종 및 출현 개체수가 많았고, 유기농 논에서도 둠벙이 있는 조건에서 종수 및 개체수가 많음을 확인하였다. 특히 잠자리목의 경우 유기농 논 4과 8종 134개체, 둠벙이 없는 유기농 논 3과 5종 35개체, 관행 논 2과 4종 12개체로 전체 출현 종의 발생특성과 유사한 경향을 보였는데, 유기농 재배의 특성상 농약의 피해로부터 수서곤충에 안전한 환경이 조성된 점과 둠벙의 담수 및 다양한 수서생물의 발생으로 수서곤충의 서식조건에 유리하게 작용되었다고 보인다. 반면 파리목에서는 둠벙이 있는 유기농 논 3과 3종 18개체, 둠벙이 없는 유기농 논 3과 3종 25개체로 관행 논 2과 2종 24개체보다 발생양상이 다른 수서곤충에 비해 상대적으로 낮고, 관행 논보다 깔다구류의 개체수 19개체보다 각각 6개체, 12개체로 적게 출현한 점에서 유기농 재배유형과 둠벙의 서식처 제공이 수서곤충의 출현 및 분포에 건전성을 조장하는 방안이라고 판단된다.

유기농 논이용 콩-밀 생산체계에서 재배유형별 밀 파종 전 경운여부에 따라 경운/무경운 처리, 콩 재배시 비닐 피복 여부에 따라 피복/무피복 처리, 논의 생태적 개선 여부에 따라 개선/대조구 처리로 시험구를 조성하여 밀 재배 중 곤충자원의 출현 및 분포특성을 조사 비교하였다. 출현 곤충의 총 종수는 20종으로 경운 14종, 무경운 14종으로 차이는 없었고 피복 14종, 무피복 16종이었으며 개선구 18종, 대조구 13종으로 개선처리에서 곤충 출현 종수가 많았다. 출현 곤충의 총개체수는 경운 124개체, 무경운 76개체로 경운처리에서 많았고, 피복 100개체, 무피복 100개체로 차이가 없었으며 경운-무피복-개선에서 40개체로 가장 많았다. 유기농 밀에 피해를 주는 해충 으로 노린재류는 갈색날개노린재가 가장 많이 발생하였고, 메추리노린재, 시골가시허리노린재도 출현하였으 며 재배유형별 발생 개체수는 경운 81마리, 무경운 39마리로 경운에서 많았고, 무경운-피복-대조(7) = 무경운-무 피복-대조(7) < 무경운-무피복-개선(9) < 경운-피복-개선(12) < 경운-무피복-대조(13) < 무경운-피복-개선(16) < 경운-피복-대조(27) < 경운-무피복-개선(29) 순으로 발생하였다.

The development of biochemical pesticides to replace existing chemical pesticides and the search for new substances with potential insecticidal ability are continuously required. The purpose of this study is to control myzus persicae with pyrethrum biochemical pesticide containing of high concentration of pyrethrin as an active ingredient. Pyrethrum dried powder was extracted with 95% ethanol for different periods of time and it was confirmed that the pyrethrin content increased as the extraction period increased and the extraction conditions for 20 days had the highest yield with 0.2% pyrethrin. We produced a prototype containing 0.13% pyrethrin content (pyrethrin II: 0.06%, pyrethrin I: 0.06%). and in 200 fold dilute spray condition. It showed a 77.2% corrected mortality against myzus persicae which is comparable to chemical pesticide. We are continuously researching to reduce the decomposition of active ingredients and look for additives to increase the insecticidal activity.

A survey of plant-parasitic nematodes (PPNs) was carried out in medicinal crop cultivated fields from July to August in 2023. Three-leaf ladybell, Adenophora triphylla var. japonica is a highly valued medicinal plant that is used to treat or prevent bronchitis, cough, cancer, and obesity in Korea. A. triphylla plants with small root-galls were observed in a field of Yeongju Agricultural Technology Center, which were identified as a root-knot nematode. Additional morphological and molecular analyses studies were performed and identified as Meloidogyne hapla, Northern root-knot nematode. Population densities of M. hapla ranged from 20~30 nematodes per 100 cm3 of soil. M. hapla was detected at lower densities in soil compared to other infected host crops, but there are concerns about damage to M. hapla since A. triphylla is cultivated for more than two years once planted. Our results indicate that A. triphylla roots damage by M. hapla were identifed, it is necessary to prepare control methods such as registration of applicable nematicides and crop rotation.

The family Asilidae(robber flies) is one of the representative predatory flies that hunts a variety of insects during the larval and adult stages. There are more than 7,500 known species distributed around the world, and 74 species in 30 genera are recorded in Korea. There are about 270 species of the genus Leptogaster recorded worldwide, and three species (L. augusta, L. basilaris, L. dorsopicta) are recorded in Korea. Through this study, three unrecorded species (L. abdominalis, L. furculata, L. spadix) were identified, and a total of six species were confirmed to be distributed in Korea. We would like to provide general information of the genus Leptogaster, a list of currently distributed species in Korea, photos, diagnostic traits, and so on.

As a result of our taxonomic study of the genus Epistrophe (Walker) in Korea, we recognized a total of 16 species including seven putative new species (code names are temporarily given from A to F). We also conducted a DNA barcoding analysis of 25 nominal species and 130 samples of Epistrophe. In our barcoding analysis, despite insufficient bootstrap support, Epistrophe formed a cluster with two genera, Epistrophella and Leucozona, topologically supporting their close relationships. Our analysis also showed some interesting results worthy of attention: First, at least two distinct cryptic species were found within the E. grossulariae cluster. Second, the taxon identified as E. nitidicollis seems to represent at least three distinct species. Third, three BOLD-deposited European samples listed as E. olgae showed almost identical barcode sequences with the European E. nitidicollis.

Background: Floor sit-to-stand (FSTS) places a higher load on the knees than chair sit-to-stand (CSTS). It is difficult to experimentally measure the maximum knee joint force during sit-to-stand motion. Objectives: This study's objectives were twofold: firstly, to quantify the differences in knee joint force between FSTS and CSTS, and secondly, to identify the angles at which the maximum knee joint force occurs during these motions. Design: Computer simulation study. Method: This study was conducted on 4 adult male subjects in their 20s. The FSTS and CSTS motion trajectories of the subjects were acquired using 3- dimensional motion analysis equipment. Using these, the human body mass model of the program was modified according to the subject, and the knee joint force was calculated. Also, the knee angle at which the maximum knee joint force occurs was found. Results: When the subjects performed the FSTS motion, a knee joint force that was up to about 160% higher than that of the CSTS motion occurred, and the angle at which the maximum knee joint force occurred was different between the sitting sequence(FSTS motion: 56~58 degree, CSTS motion: 78~82 degree) and the standing sequence(FSTS motion: 98~100 degree, CSTS motion: 70~74 degree). Conclusion: By comparing FSTS motion with CSTS motion, it is expected that it can be used as a quantitative guide for the effect of motion similar to FSTS motion on the knee when prescribing exercise for the elderly or patients with knee-related lesions.

In this study, we focus on the improvement of data quality transmitted from a weather buoy that guides a route of ships. The buoy has an Internet-of-Thing (IoT) including sensors to collect meteorological data and the buoy’s status, and it also has a wireless communication device to send them to the central database in a ground control center and ships nearby. The time interval of data collected by the sensor is irregular, and fault data is often detected. Therefore, this study provides a framework to improve data quality using machine learning models. The normal data pattern is trained by machine learning models, and the trained models detect the fault data from the collected data set of the sensor and adjust them. For determining fault data, interquartile range (IQR) removes the value outside the outlier, and an NGBoost algorithm removes the data above the upper bound and below the lower bound. The removed data is interpolated using NGBoost or long-short term memory (LSTM) algorithm. The performance of the suggested process is evaluated by actual weather buoy data from Korea to improve the quality of ‘AIR_TEMPERATURE’ data by using other data from the same buoy. The performance of our proposed framework has been validated through computational experiments based on real-world data, confirming its suitability for practical applications in real- world scenarios.

In this study, the Extended Theory of Planned Behavior (ETPB) was applied to analyze consumers’ intention to purchase meal kits. The perception of ESG management practiced by companies was used as a moderating variable to investigate its influence and moderating effects between each variable. An online survey was conducted over 4 days in January 2023 on consumers aged 20 years or older who had purchased meal kits within 6 months. Hypotheses were tested using IBM SPSS Statistics 22.0 and AMOS 24.0 programs with an effective sample size of 324 copies (100%). Attitude, subjective norm, perceived behavioral control, perceived sustainable package, and price sensitivity of the theory of planned behavior toward meal kit products had a significant positive effect on purchase intention, and all research hypotheses were accepted. The moderating effect of consumers' perceptions of ESG management practiced by companies had a positive and significant effect on attitude and perceived behavioral control.

The Covid-19 pandemic has caused unprecedented crises to societies and economies around the world and has brought drastic changes in the way consumers behave. Fashion business is one of the industries that has been significantly affected by Covid-19 as many consumers reduced their discretionary spending during the pandemic. While the world is entering the post-pandemic era and recovering from the pandemic, it is important to uncover and reflect on the reasons behind varying patterns of consumers’ coping behaviors associated with fashion shopping. However, current research on consumer fashion behavior during the pandemic primarily focuses on a particular type of shopping behavior, without addressing varying patterns of fashion consumption behaviors. In addition, most of these studies attributed such changes in behaviors to motivations toward protection against health-adverse threats based on the Protection Motivation Theory, which mostly focuses on protective behaviors and has limited power in understanding varying internal reasons toward various coping behaviors. Considering the varying adaptive and maladaptive patterns of fashion consumption behaviors observed in the market, it is important to address the psychological mechanism behind varying adaptive and maladaptive patterns of fashion consumption behaviors. Thus, drawing from the Stimulus-Organism-Response (SOR) framework, this study aims to investigate how cognitive appraisal of threats affects the affective/emotional state of consumers and consequently their intention to engage in various coping behaviors in the context of fashion shopping. Specifically, this study aims to investigate how individuals’ cognitive appraisals on risks and uncertainty induce varying emotional feelings (i.e., fear, anxiety, and hope), which further leads to their decisions to engage in problem vs. emotion-focused coping through fashion shopping during the pandemic.

While companies and brands have always collected and used customer data for multiple purposes, the advent of smart devices, Internet of Things (IoT), and big data has made it much easier to access and utilize consumers’ personal information. For consumers, however, such ease of access to their personal data and frequent cases of data breach have increased their concerns about data privacy (Harris & Associates, 1996; Milne et al., 2004). Nevertheless, consumers continue to share their personal information with companies and brands in the digital environment (Turow et al., 2015).

As the importance of online virtual spaces increases due to COVID-19, interest in online virtual spaces using 4th industrial technology is increasing. Accordingly, the metaverse that combines virtual and real is becoming an issue. In the fashion industry, marketing using online is gradually increasing, and various attempts are being made by converging with the metaverse to provide new and enjoyable experiences to customers. This study looked at the impact of customer experience of a luxury fashion brand pop-up store on customer satisfaction, affective commitment and brand loyalty in a metaverse environment where utilization is increasing due to COVID-19 and technological development. For the analysis data of this study, a survey was conducted on the users who experienced the metaverse platform Zepeto's ' BVLGARI World'. As a result of examining the effect of the customer experience of a luxury fashion brand pop-up store on customer satisfaction, affective commitment, and brand loyalty in a metaverse environment, some of the customer experiences affect customer satisfaction, and the proposed hypothesis was partially accepted. In addition, it was confirmed that customer satisfaction affects affective commitment and brand loyalty, and affective commitment affects brand loyalty. In this study, we examine the impact of the customer experience of a luxury fashion brand pop-up store on customer satisfaction, affective commitment, and brand loyalty in the metaverse environment, and identify what is needed for more active convergence and activation of the metaverse and fashion brands. Also, we provide practical implications to people who involved in the metaverse and the fashion industry.

There are a lot of brand experience in Metaverse. For example, we can participate in Samsung Galaxy Fan party, UC Berkeley graduation class, and even Ralph Lauren store in Metaverse. When the consumers experience such events in Metaverse, they have to use their avatar by making a user name. They have the option of using either their real or fictional name in Metaverse. There are two types of avatar in Metaverse. First, they can use actual self-avatar by using their real name. Second, they can create totally new avatars using made up name. The name is one of the symbols of self. Therefore, we can easily predict that consumer experience with avatar will affect the consumer perception differently. Which type of avatar will then enhance the brand engagement? Results show that the consumer experience with avatars affected brand attitudes differently. Also, the consumer's experience with avatars based on their actual images in the Metaverse affected the positive brand attitude. This study suggests that Metaverse avatars can also let people interact with themselves and with each other in parasocial ways. This study examines the role of avatar in virtual world; consumers experience with avatar can provide useful implications in terms of digital transformation.

The outbreak of COVID-19 has brought significant changes to today’s life. Human contact is regarded as a source of risk. Thus, the low-contact services provided by service robots have gained more attention in the hospitality industry. However, a relatively smaller proportion of empirical research exists about service robots on the consumer side. Moreover, technology acceptance theories were mostly used in the adoption of new technology products, but the psychological aspects of consumers were rarely explored. Therefore, the stimulus- organism-response model (SOR model) was applied to explore consumers’ acceptance of adopting service robots and to understand what factors will successfully stimulate consumers’ subsequent value and behavioral responses. Furthermore, we investigated the relationship among stimulus (coolness and affinity), organism (utilitarian value and hedonic value) and response (intention to use and word-of-mouth recommendation). This study used convenience sampling and tested the hypotheses with SPSS and Smart PLS.

This paper is written as a follow-up observations to reinterpret the radial velocity (RV) of HD 36384, where the existence of planetary systems is known to be ambiguous. In giants, it is, in general, difficult to distinguish the signals of planetary companions from those of stellar activities. Thus, known exoplanetary giant hosts are relatively rare. We, for many years, have obtained RV data in 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 M giant HD 36384. We have found two significant periods of 586 d and 490 d. Considering the orbital stability, it is impossible to have two planets at so close orbits. To determine the nature of the RV variability variations, we analyze the HIPPARCOS photometric data, some indicators of stellar activities, and line profiles. A significant period of 580 d was revealed in the HIPPARCOS photometry. H𝛼 EW variations also show a meaningful period of 582 d. Thus, the period of 586 d may be closely related to the rotational modulations and/or stellar pulsations. On the other hand, the other significant period of 490 d is interpreted as the result of the orbiting companion. Our orbital fit suggests that the companion was a planetary mass of 6.6 𝑀J and is located at 1.3 AU from the host.

한국에서 알스트로메리아(Alstroemeria)는 저온 작물로 난 방비 절감 효과가 있고 장식용 절화 소재로 꾸준히 소비되어, 일정 재배면적이 유지되고 있다. 본 연구는 알스트로메리아 ‘한에로스’의 기내 대량증식과 뿌리 발근 조건을 구명하고 무 균묘 생산 시스템을 구축하기 위해 수행했다. 기내 대량 증식 조건 구명 실험에는 Murashige and Skoog(MS) 배지(3% sucrose, 0.25% gelrite)에 BA 단용 처리(BA 0.25, 0.5, 0.75mg･L-1)와 NAA 0.2mg･L-1에 BA를 농도(BA 0.25, 0.5, 0.75mg･L-1)에 따라 혼용 처리하였다. 발근 조건 구명을 위 해 MS배지(3% sucrose, 0.25% gelrite)에 BA 0.25 mg･L-1 단용 처리와 BA 0.25mg･L-1에 NAA를 농도(NAA 0.1, 0.2, 0.3mg･L-1)에 따라 혼용 처리하였다. 뿌리줄기 증식 실험 결 과, 호르몬 첨가에 따른 생육차이는 뿌리줄기 수를 제외한 나 머지 부분에서 뚜렷하게 확인되었다. 단용 처리구 보다 혼용 처리구에서 많은 신초가 유도되었다. BA 0.5mg･L-1와 NAA 0.2mg･L-1 혼용 배지에서 가장 많은 1.43개의 신초가 유도되 었다. 발근 실험 결과, ‘한에로스’는 BA 0.25mg･L-1 와 NAA 0.3mg･L-1 혼용 배지에서 뿌리 수가 3.96개로 가장 많고, 뿌 리가 짧고 두꺼워 순화 과정 중에 뿌리 손실이 적었다. 또한, 순화 과정 중 묘가 고사하지 않았다. 종합적으로, ‘한에로스’ 는 BA 0.5mg･L-1와 NAA0.2 mg･L-1 혼용 배지에서 증식을 하는 것이 적절하며, BA 0.25mg･L-1와 NAA 0.3mg･L-1 혼 용 배지에서 발근 후 순화하는 것이 최적의 기내 배양 조건으 로 사료된다. 본 연구의 결과로 알스트로메리아 무균묘의 보 급 확대에 기여하고자 한다.

딥러닝(DL: Deep Learning)의 발전으로 오늘날 다양한 분야에서 AI 모델이 만들어지고 사용되고 있다. 오늘날, 컴퓨터의 발전과 DL 알고리즘의 발전에 의해, DL 기반 AI 모델은 수많은 데이터를 학습하고 스스로 규칙을 찾을 수 있다. DeepMind의 Alphago는 학습 데이터 만으로 게임의 규칙을 스스로 판단하고 고수준의 게임 플 레이를 할 수 있다는 가능성을 보여준다. 이런 다양한 DL 알고리즘이 게임 분야에 적용되고 있지만, 스포츠 게임 같이 팀의 전술과 개인 플레이가 공존하는 분야에서는 단일 AI 모델만으로 성공적인 플레이를 이끌어 내기에는 한계가 존재한다. 오늘날, 고품질의 스포츠 게임은 쉽게 접할 수 있다. 하지만, 게임 AI 연구자들이 이런 고품질의 스포츠 게임에 맞는 AI 모델을 개발하기 위해서는 게임 코드 소스를 받거나 게임 회사에서 테 스트용 시뮬레이터를 제공해줘야만 할 수 있다. 게임 AI 연구자들이 활발한 스포츠 게임 분야의 AI 모델을 개 발하기 위해서는 스포츠 게임의 규칙과 특징이 반영되고 접근하기 쉬운 테스트 환경(Test Environment)이 필요 하다. 본 논문에서는 팀의 전술과 개인 플레이가 중요한 스포츠 게임 분야에서 AI 모델을 만들고 테스트할 수 있는 규칙기반 축구 게임 프레임워크를 제안한다.

This research was conducted to analyze the cultivation performance and meteorological data of winter rye in Suwon, Gyeonggi Province, and Daegu for 11 years. The objective was to compare the growth and yield of domestically cultivated Korean rye cultivar “Gogu” and identify the factors influencing them, to determine suitable cultivation areas for Korean rye cultivar in the country. The results of the study showed that both Daegu and Suwon regions possess favorable climatic conditions for winter rye cultivation, with Suwon exhibiting a superior moisture supply compared to Daegu. Furthermore, the analysis of climate suitability revealed that rainfall days and precipitation were significant factors affecting rye cultivation. Through correlation and principal component analysis, the research evaluated the interrelationship between climate, cultivation factors, and winter rye crop performance, as well as identified variations among winter rye cultivation regions. This study provides valuable insights and information for winter rye cultivation in the country, thereby assisting in the decision-making process for selecting optimal cultivation areas.

Recently, small and medium-sized manufacturing companies have shown increased interest in and participation in smart factories in order to survive in market competition. However, many SMEs build smart factories without a systematic review or preparation, which leads to them not being able to use them properly. This study considers the main reason for the low utilization rate of smart factories to be a lack of sufficient reflection of user requirements. Therefore, a method and procedure for deriving the priority of smart factory requirement functions and operating performance indicators based on QFD is proposed as a solution to this issue.