코드린나방은 사과, 배, 복숭아 등의 과실류를 비롯한 다양한 작물의 해충으로써, 국내에서는 검역 대상으로 금지해충에 속해있다. 코드린나방이 속한 잎말이나방의 유충은 과실 속으로 파고 들어가 살기 때문에 살충제로 방제하기가 어려운 해충이다. 따라서 철저한 수입식물 검역과 예찰을 통해 국내로의 유입을 막는 것이 최선이다. 현재 잎말이나방류에 대한 예찰용 페로몬트랩이 사용되고 있지만 개별 종에 대한 표적 예찰은 이뤄지지 않고 있다. 본 연구에서는 코드린나방의 성페로몬을 이용한 유인제 개발을 위한 기초연구로써, 현재 상용화되어 미국, 유럽, 중국 등에서 사용하고 있는 다양한 유인제의 조성성분을 분석하였다. 전세계적에서 대표적으로 사용되는 4종류의 코드린나방 루어를 GC-MS/MS를 이용하여 물질의 종류와 구성비율을 분석하였다. 본 연구의 결과는 향후 코드린나방의 최적 예찰을 위한 성페로몬 유인제 선발의 기초자료로 활용될 예정이다.

Root-knot nematode (RKN), Meloidogyne incognita, inflicts significant greenhouse crop damage, causing over 40% economic losses. While chemical agents effectively control RKN, they leave harmful residue in soil and crops. To address this issue, we investigated soil-derived entomopathogenic fungi (EPF) in this study. We assessed the nematicidal impact of ten EPF species through in vivo and in vitro tests. Beauveria bassiana JEF-503 exhibited nematicidal effectiveness exceeding 65% in both experimental settings. In a semi-field test using greenhouse pots, we experimented with the application of B. bassiana JEF-503 suspension during tomato growth, which is an uncommon practice in comparison to chemical treatments due to residue concerns. B. bassiana JEF-503 was applied during transplantation, and the same application was repeated four weeks later. JEF-503 One-time and abamectin treatments were used as control groups. The JEF-503 two-time application notably reduced root damage compared to single JEF-503 or abamectin treatment. In conclusion, JEF-503 offers a promising, residue-free, and environmentally friendly alternative to chemical agents for RKN management.

최근 우리는 Hg2+에 대한 높은 선택성을 가지며 Hg2+와 결합하여 밝은 녹색 형광을 보이는 tetraphenylethylene-bis(thiophen-2-ylmethyl)amine (TPE-BTA)의 착화합물(TPE-BTA-2Hg2+)의 구조를 밝혀내기 위해 시 간 의존적(time-dependent, TD) 밀도 함수 이론(DFT)을 이용하였다. 그러나 우리는 이 과정 속에서 Hg2+ 이온에 대한 모든 전자(all electron, AE) basis set인 x2c-TZVPPall만이 실험 스펙트럼에 가까운 흡수 및 형광 스펙트럼을 성공적으 로 재현한다는 것을 발견했다. 많이 알려져 있는 effective core potential (ECP) 기반인 LANL2DZ는 형광스펙트럼 계산 과 관련된 들뜬 상태의 구조 최적화 계산을 모두 실패했으며 또한, LANL2DZ는 첫 번째 들뜬 상태의 최적화 과정에서 너무 작은 형광 에너지를 제공했다. 이때 LANL2DZ는 리간드와 Hg2+ 사이의 거리가 증가함에 따라 빠르게 감소하는 HOMO-LUMO gap을 제공하는 반면, x2c-TZVPPall은 점진적으로 감소하는 안정적인 HOMO-LUMO gap을 보여줬다. 우리는 적어도 Hg2+ 이온을 포함하는 착화합물 시스템에서 ECP에서 발생하는 기하학적 문제들을 피하기 위해서는 모 든 전자 기본 세트를 사용하거나 새로운 ECP를 만들어야 된다고 조심스럽게 제안한다.

In today's fast-evolving technological environment, the growth of mobile devices has provided businesses with additional knowledge on how to effectively communicate with their targeted audience. As big data generated by mobile users has become a valuable source for improving communication, users’ location data has provided an additional parameter to take into account while trying to enhance the effectiveness of digital marketing campaigns. This paper presents a comparative study of the location-based marketing field and tools. It provides an overview of different exploitation methods of location-based mobile services and data for effective digital marketing campaigns and guidelines for future research.

The popularity of the Korean entertainment industry has been growing worldwide. Various forms of media, such as movies, TV series, music, radio and many more, have been used as a platform to launch and promote new products of many brands. For instance, Laneige – a Korean cosmetic company was successfully placed in the Korean drama – Descendants of the Sun. Previous studies have accounted for various factors in analysing product placement in movies, such as brand familiarity, brand fit, and movie genre. However, the effect of the emotional context of where the product is placed remains unclear. The purpose of the present research is to investigate whether the effectiveness of product placement is influenced by the emotions depicted in the scene, and whether the ethicality of the product matters.

This study explores the effectiveness of marketing data analytics learning and outcomes for marketing students in courses with data analysis components at a U.S. business school. The study considers various moderating factors, such as software adaptability, grades, class type, data interest, statistical analysis method, and perceived time- and cost-effectiveness. The findings have implications for marketing education in data analytics.

Companies frequently rely on pricing algorithms to automate their price-setting in online markets; thereby, algorithmic dynamic pricing (ADP) has become a common pricing practice in the digital era, with retailers regularly tweaking products’ prices in their online shops. On Amazon.com alone, millions of price changes occur within a day, which corresponds to a price change approximately every ten minutes for each product. Yet, so far, the effects of such pricing algorithms on consumers are unclear. Since ascertaining consumer reactions is essential for retailers’ pricing strategies and retailers need to know how to mitigate negative reactions, our focal research questions are: How do consumers respond to ADP? How can retailers mitigate negative consumer reactions to ADP?

This study examines the impact of others' reviews (reviews, product ratings) on consumer responses (helpfulness & buying intention) in an online shopping platform. We propose that review features, such as review message construal and review inconsistency between review message valence and rating, determine review credibility as product-related information, which in turn influences helpfulness of review and buying intention toward the product. Specifically, low- level construal review messages will be perceived as more credible than high-level construal review messages, which affect helpfulness and buying intention. In addition, the effect of review message construal will be moderated by review inconsistency. The effect of the review message construal will be enhanced in the condition of review consistency (positive content-high rating & negative content-low rating), but it will be disappeared or attenuated in the condition of inconsistency (positive content-low rating, negative content-high rating).

In this research, we investigate the effectiveness of bleed brand logos for the metaverse shopping travelers from the viewpoint of a container metaphor. Bleed is a technique that enlarges parts of a logo while omitting others. Many firms use a bleed logo to improve visibility and allow the metaverse shopping travelers to retrieve the brand-related information quickly. Regarding the issue, we conducted three studies and found that in a metaverse space not filled with other traveler avatars, travelers would feel that the environment is in their control, and they could enjoy the experience. In this instance, firms could earn a high brand evaluation with a high bleed logo. However, when the metaverse space is crowded with other traveler avatars and, thus, travelers experience negative feelings brought up by their sense of being out of control, a high bleed logo results in their low evaluations of the brand because shopping travelers feel like some contents in the logo are out of the frame.

We investigated an emerging magnetic loop dynamically formed on the Sun, which has the effective footpoint heating source that may play a key role in heating a solar atmosphere with free magnetic energy in it. It is suggested that the heating source could be related to local compression of a plasma in the emerging loop by means of Lorentz force, which converts the magnetic energy to the internal energy of the plasma that is used to reaccelerate a decelerated downflow along the loop, eventually generating the source when the kinetic energy of the downflow is thermalized. By analyzing very high-cadense data obtained from a magnetohydrodynamic simulation, we demonstrate how the local compression is activated to trigger the generation of the heating source. This reveals a characteristic of the emerging loop that experiences a dynamic loop-loop interaction, which causes the local compression and makes the plasma gain the internal energy converted from the magnetic energy in the atmosphere. What determines the characteristic that could distinguish an illuminated emerging loop from a nonilluminated one is discussed.

The potential impact of hypothetical accidents that occur during the immediate and deferred dismantling of the Kori Unit 1 steam generator has been comprehensively evaluated. The evaluation includes determining the inventory of radionuclides in the Steam Generator based on surface contamination measurements, assuming a rate of release for each accident scenario, and applying external and internal exposure dose coefficients to assess the effects of radionuclides on human health. The evaluation also includes calculating the atmospheric dispersion factor using the PAVAN code and analyzing three years of meteorological data from Kori NPP to determine the degree of diffusion of radionuclides in the atmosphere. Overall, the effective dose for residents living in the Exclusion Area Boundary (EAB) of Kori NPP is predicted, an it is found that the maximum level of the dose is 0.034% compared to the annual dose limit of 1 mSv for the general public. This implies that the potential impact of hypothetical accidents on human health discussed above is within acceptable limits.

본 논문은 언리얼 엔진(Unreal Engine) 기반의 가상환경에서 인공지능 시각화의 대표적인 시스템인 Stable Diffusion을 이용하여 다양한 형태의 인터렉티브 레벨 디자인 구현 방법을 분석하고 제안한다. Stable Diffusion 은 Midjourney와 함께 대표적인 인공지능 시각화 시스템이며 다양한 프로그램 및 툴에 응용되고 있으며 프롬 프트 입력 기반으로 Text to Image, Image to Image는 물론이며 간단한 추가 작업으로 바디 모션 변화까지 자 연스럽게 적용되는 인공지능 시각화 시스템이다. Unreal engine은 현재 5.2까지 업데이트 된 대표적인 게임 엔 진이며 본 연구에서는 5.1을 사용하였다. Unreal Engine은 게임은 물론 애니메이션, 영화CG, 건축, 디지털 트윈 까지 광범위하게 사용되고 있으며 게임 엔진이지만 게임 이외의 콘텐츠 저작 툴로써 점점 더 많이 이용되고 있는 프로그램이다. 본 논문은 이 Stable Diffusion과 Unreal engine을 접목시켜 효과적인 인터랙티브 레벨 구현 을 할 수 있는 프로세스에 관해 분석하고 제안한다. 이미 인공지능은 다양한 2D, 3D콘텐츠에 접목이 시도되 어 실제 퍼블리싱가지 이어지고 있는 시대라고 할 수 있다. 본 연구는 현재 Unreal Engine과 인공지능을 효과 적으로 융합하여 시각적 결과물을 구현하는 방법론을 분석하였으며 효과적으로 구축할 수 있는 토대를 확인 하였다.

This study investigates the behavior of the thermal conductivity among material properties in order to develop a thermal evaluation methodology of spent fuel assembles in a transport cask. It is inefficient to model each element of the spent fuel assembly in detail, and it is generally calculated by modeling the effective thermal conductivity (ETC). The ETC model was developed to allow a much simpler representation of a spent fuel assembly within a fuel compartment by treating the entire spent fuel rod array and the surrounding fill gas within the confines of the compartment as a homogenous solid material. The fuel rod assembly and surrounding gas are modeled with an effective conductivity that is designed to yield an overall conduction heat transfer rate that is equivalent to the combined effect of local conduction and radiation heat transfer in a plane through the assembly. When this model is applied to the transport cask, it tends to predict the cladding peak temperature lower than the results of detailed model in which the fuel rod arrangement and shape of the fuel assembly are simulated. As for the tendency of the error, the model tended to under-predict when basket temperature was lower than a certain temperature, and over-predict when it was higher. The purpose of this study is to investigate the attenuation effect of the cladding peak temperature on the related variables when the ETC model is applied to the transport cask. In addition, based on the thermal characteristics of this model, a correction factor that can compensate for this attenuation effect is presented. This correction factor is obtained by finding the difference between a separate ETC homogeneous model and a separate detailed fuel model, rather than directly applying the ETC calculated from the detailed fuel model to the transport cask.

Surveillance plays a crucial role in safeguards. Reviewing surveillance data requires a significant number of inspection manpower. As the number of surveillance cameras increases, the demand for such manpower is expected to grow even more. Recently, in the field of security, there has been a development of deep learning models that automatically detect abnormal events from video images, and their usage is expanding. In this study, we used an AutoEncoder-based semi-supervised learning model, which can detect unexpected abnormal events, to detect anomalies in the UCSDped2 dataset and in simulating safeguards-related event videos taken at Dry Mockup facility of KAERI. To improve the model performance, we transformed the video images into two parts: the appearance part, which are sequences of video image frames, and the motion part, which are the pixel value differences of consecutive video frames. In addition, we added memory module to the bottle neck of the AutoEncoder model, and skip connection to enhance the model performance. To evaluate the model performance, we proposed a new evaluation index, which is adequate to the video images of safeguards surveillance in addition to the widely used AUC (Area Under the ROC Curve).

The electrical connection between zinc metal and iron in contact with water prevents oxidation of iron until all zinc is dissolved, which is called a zinc sacrificial anode phenomenon. In the case of water pipes, zinc is often attached to the outside of the pipe, but examples of mounting zinc inside the pipe to prevent iron corrosion are not well known. Zinc devices sold for water pipes vary in the amount of zinc installed depending on the diameter of the pipe and the conditions of use, but the life of the product is generally expected to be 10-20 years until all zinc dissolves and disappears. Zinc ions dissolved from zinc to water in the pipe react with the calcium carbonate scale generated inside the pipe to consume zinc ions, and it was confirmed that the needle-shaped aragonite was converted into highly crystalline calcium after observing the scale crystal through an electron microscope. In addition, it is estimated that calcium ions of scale are replaced by zinc ions, gradually losing crystallinity, being deintercalated into the pipe, and oxygen in the water is consumed during the dissolution of zinc ions from zinc metals, turning red rust hematite (Fe2O3) into magnetite (Fe3O4). In addition, zinc ions were expected to move hundreds to thousands of meters depending on the diameter of the pipe in the new pipe, but it was confirmed that the travel distance was shortened in the case of pipes with many corrosion products.

With a rapid expansion in electric vehicles, a huge amount of the spent Li-ion batteries (LIBs) could be discharged in near future. And thus, the proper handling of the spent LIBs is essential to sustainable development in the industry of electrical vehicles. Among various approaches such as pyrometallurgy, hydrometallurgy, and direct recycling, the hydrometallurgical manner has gained interest in recycling the spent LIBs due to its high effectiveness in recycling raw materials (e.g., lithium, nickel, cobalt, and manganese). However, the hydrometallurgical process not only requires the use of large amounts of acids and water resources but also produces toxic gases and wastewater leading to environmental and economic problems, considering potential economic and environmental problems. Thus, this review aims to provide an overview of conventional and state-of-the-art hydrometallurgical processes to recover valuable metals from spent LIBs. First, we briefly introduce the basic principle and materials of LIBs. Then, we briefly introduce the operations and pros-and cons- of hydrometallurgical processes. Finally, this review proposes future research directions in hydrometallurgy, and its potential opportunities in the fundamental and practical challenges regarding its deployment going forward.

본 연구는 교실에서 말하기 수업을 진행할 때 효과적인 수업 진행을 위한 Techniques들을 알아보고자 하는 것에 목적을 두었다. 연구 방법으로는 부산외국어대학교에서 말하기 수업을 수강하고 있는 고급 학습자 50명을 대 상으로 설문조사를 하여 효과적인 말하기 수업의 진행 Techniques에 대한 해답을 얻고자 하였다. 연구문제 1)에 대한 문제는 6문항으로 말하기 수업을 할 때 효과적인 자리배치, 강의실의 크기, 강의실의 밝기 그리고 1:1로 시험을 볼 때 평가자와의 거리에 대해 질문이다. 연구문제 2)에 대한 문제는 3문항으 로 고급 말하기 수업에서 선호하는 발표 준비 유형과 발표 방법 유형에 대한 질문이다. 연구문제 3)에 대한 문제는 4문항으로 효과적인 교실 활동의 유형, 교실에서 활동을 할 때 학습자 간 국적 및 친밀도가 수업 중 학습자의 심리 및 학습의 효과에 영향을 미치는가에 대한 질문이다. 연구문제 4)에 대한 문제는 4문항으로 교수자의 몸짓언어, 교수자의 발화 크기와 속도가 수업 중 학습자의 심리 및 학습의 효과에 영향을 미치는가에 대한 질문이다. 이러 한 연구문제를 가지고 총 17문항의 설문을 작성하여 설문조사를 하였으며 그 결과 다양한 답변이 나왔다. 이러한 답변이 차후 현장 교실 수업에서 적용 되기를 바라고, 그러므로 현장 한국어 말하기 수업에 기여할 것이라는 교육적 시사점을 제안하였다.