In recent years, with its amazing online interactive promotion ability, e-commerce live streaming has attracted the attention of theoretical scholars and practical experts. This study takes “co-presence (CP) ” and “social presence (SP) ”, which are the prominent features of e-commerce live streaming, as the breakthrough point to explore the mechanism of the influence of co-presence and social presence on purchase intention. In this study, consumers with e-commerce live streaming watching experience are taken as participants, and the method of structural equation modeling is used. It is found that: presence significantly impacts flow experience and consumer purchase intention, while the impact of the two kinds of presence (SP, CP) is variable. the promotion effect of the two kinds of presence (SP, CP) on consumer purchase intention is completely mediated by flow experience. The mediating effect of co-presence on consumer purchase intention through flow experience is regulated by e-commerce live streaming topicality, but social presence doesn’t.

Based on the metaverse situation, this paper explores the influence of perceived usefulness and usability on brand experience. The brand experience include two dimensions of sensory experience and behavioral experience. And then, based on 329 valid data collected through online experiment, it makes an empirical analysis by structural equation model and hierarchical regression. Results show that, metaverse situational perceived usefulness and usability have significant effects on customer sensory experience and behavioral experience, and sensory experience plays a mediating role in the effects of usefulness and usability on behavioral experience. Social presence plays a positive moderating role in the influence path of usefulness and usability on sensory experience and behavioral experience.

This research intends to examine whether these types of data – behavioral versus social networking data – affect consumer response to personalized ads. With the advancement in technology, marketers have access to various types of personal data, including their online/offline behaviors and social networking activities, and use those data to retarget consumers. Moreover, this research examines the moderating role of SNS privacy concerns on consumer response to different types of retargeted ads. The findings of this research may offer theoretical and practical implications to understand consumers' responses to retargeted ads that use social networking information.

Metaverse blends the physical and virtual worlds, transforming the customer's shopping experience. This study aims to identify the psychological mechanism in the metaverse environment and the relationship between metaverse experience and consumer happiness. To identify metaverse experiences, both behavioral and functional magnetic resonance imaging (fMRI) studies were conducted. In a behavioral study, we found that consumers' happiness increased when participants were in an immersive metaverse space. In the fMRI study, we found greater activation in the medial prefrontal cortex (MPFC) and lateral occipital cortex (LOC) regions in the high level of the immersive metaverse and found a positive relationship with consumers' happiness. This paper is the first attempt in marketing to provide an integrative brain map for the metaverse experience. This brain map helps marketers better understand the consumer experience. This study suggests that only in the immersive metaverse space where virtual and physical experiences interact can consumers become one with the virtual space and maximize customer experience values.

We propose a sales prediction model based on the number of new members, online advertising, and consumer reviews for a short period. Considering purchase behaviors of new and existing members, we predict reliable sales amounts, which can be monthly updated. Our study provides digital marketers with a feasible prediction approach.

This study aims to empirically investigate how corporate strategy mitigates consumer boycotts caused by animosity toward economic sanction. First, the study focuses on the cross-culture emotions (i.e., animosity and affinity) and explores the direct and indirect effect of animosity toward economic sanction on boycott attitude (via consumer affinity). Additionally, it focuses on the moderating effect of brand strength and corporate social contribution on boycott attitude. We conduct a longitudinal analysis of boycotts by South Koreans on the Japanese products, which started in South Korea in 2019; and additionally, we employ PROCESS macro to test the moderated mediation hypothesis, using the data collected from South Korea in 2020 and 2021. Our findings reveal that the data collected in 2020 and in 2021 have the same implications. The main findings are as follows. First, while animosity toward economic sanction directly increases boycott attitude, it also indirectly increases boycott attitude via consumer affinity. Second, the assumption that both brand strength and corporate social contribution weaken the positive and direct effects of animosity toward economic sanction on boycott attitude was not supported. Third, we find that corporate social contribution weakens the positive and indirect effect of animosity toward economic sanction on boycott attitude. However, unlike our prediction, brand strength strengthens the positive and indirect effects of animosity to economic sanction on boycott attitude. The three key theoretical implications are as follows. First, while many studies have examined the role of animosity as a cause of boycott, only a few studies have simultaneously addressed the conflicting emotions of affinity (Kim, Yan, Kim, Terasaki, & Furukawa, 2022). This study extends boycott research by exploring the relationship between animosity and boycott attitudes by considering the mediating effect of affinity. Second, to our best knowledge, only a few boycott studies have explored corporate strategies that adequately respond unanticipated country boycotts where the companies are not directly associated with the causes or motives of such boycotts (Kim & Kinoshita, 2023). This study extends boycott research by investigating brand strength and corporate social contribution as corporate strategies in the context of consumer boycotts. Third, although it is known that consumer boycotts change with time, only a few boycott studies are based on longitudinal analyses (Ettenson & Klein, 2005); hence, this study examines consumer boycotts longitudinally to improve the generalization of our findings. Our findings also present some managerial implications for global companies facing unexpected country boycotts by local consumers. When boycotts are caused by economic sanctions between countries, brand strength exerts a two-sided effect. Regarding consumer sentiment, the higher the brand strength, the higher the affinity for the country represented by the brand, and vice versa; however, consumers may also choose to boycott a brand with high strength. Consumers may feel angry and engage in boycotts when they feel betrayed by a brand with strong brand strength. However, corporate social contribution reinforces a sense of closeness in the country it presents and contributes toward mitigating the boycott attitude; this is because consumers consider their corporate social contribution as a beneficial activity for their country. Therefore, global companies that expand overseas should not only use their brand strength, but also engage in activities that are beneficial to the country and enhance the familiarity of the consumers of the country to develop a sense of cultural affinity. In addition, this study also has implications for policymakers. Economic sanctions against a specific country not only lower consumers’ affinity, but also leave a negative impact on the global companies with high brand strength. Therefore, policymakers must proceed with caution when they make an economic sanction for a certain country.

The propagation speed of a circumstellar pattern revealed in the plane of the sky is often assumed to represent the expansion speed of the wind matter ejected from a post-main-sequence star at the center. We point out that the often-adopted isotropic wind assumption and the binary hypothesis as the underlying origin for the circumstellar pattern in the shape of multilayered shells are, however, mutually incompatible. We revisit the hydrodynamic models for spiral-shell patterns induced by the orbital motion of a hypothesized binary, of which one star is losing mass at a high rate. The distributions of transverse wind velocities as a function of position angle in the plane of the sky are explored along viewing directions. The variation of the transverse wind velocity is as large as half the average wind velocity over the entire three dimensional domain in the simulated models investigated in this work. The directional dependence of the wind velocity is indicative of the overall morphology of the circumstellar material, implying that kinematic information is an important ingredient in modeling the snapshot monitoring (often in the optical and near-infrared) or the spectral imaging observations for molecular line emissions.

Evaporative emission generated through the fuel supply system of a gasoline automobile is prevented into the atmosphere through an activated carbon canister system. In this study, the oxygen functional group of activated carbon was controlled using a simple gas phase treatment to improve evaporative emission reduction performance, and the adsorption/desorption performance of evaporative emissions was evaluated according to microwave heating conditions. Microwave heating was used to remove the oxygen functional group of the activated carbon efficiently. Microwave heating was found to remove oxygen functional groups in a short treatment time (1–7 min). Fourier-transform infrared spectroscopy, X-ray photoelectron spectroscopy, and scanning electron microscope–energy-dispersive X-ray spectroscopy were employed to investigate modifying the oxygen functional group of the activated carbon. Using N2/ 77K adsorption/desorption isotherm, the textural properties of the activated carbon according to microwave heating conditions were examined. The Brunauer–Emmett–Teller (BET) equation was used to calculate the specific surface area of the activated carbon, and the Dubinin–Radushkevich (DR) equation was used to calculate the micropore volume of activated carbon. Microwave heating effectively increased the butane working capacity, which is the neat adsorption capacity of activated carbon, from 7.12 g/100 ml to a maximum of 8.04 g/100 ml.

본 연구는 아시아의 국제관계가 변화하는 맥락에서 "아시아 나토"의 실 행 가능성과 잠재적 영향을 검토한다. 아시아 버전 나토의 가능성을 분 석하기 위해 세 가지 목표를 추구한다: (1) 나토의 성격을 조사하고 아시 아에서의 잠재적 적용을 검토한다, (2) 세력균형이론과 위협균형이론의 관점에서 나토의 과거 실패를 검토한다, (3) 정치와 군사적 도전을 고려 한 아시아 나토의 실행 가능성을 평가한다. 이 연구는 미국과 일본을 중 심으로 아시아 나토에 대한 관심이 증가한 지정학적 변화를 탐구한다. 현재 미중 균형과 위협 사이의 균형은 양자 및 삼자 동맹을 설정하는 데 이르렀지만 아시아 나토의 가능성은 여전히 쉽지 않다. 그러나 중국이 지역 패권 추구로 인한 압도적인 외부 위협을 초래하면, 아세안 국가들 은 집단 안보 체제에 가입할 수 있다. 본 논문은 특히 이러한 상황에서 한국이 직면할 수 있는 문제점에 대해서도 지적한다.

To broaden the utilization of nuclear energy, uranium as a fuel should be mined indispensably. Mining accounts for the largest portion of the cost of producing the uranium assembly. Therefore, this study analyzes the trends of uranium prices, which have a significant impacts on the mining cost. Uranium production contributing to the price fluctuations is explained in five periods from 1945 to the present. Moreover, the series of events affecting uranium prices from the 1970s until the present are verified. Among them, the most recent incidents considered in this study are the following: COVID-19 pandemic, Kazakhstan unrest, and Russia-Ukraine war. European countries have started to reconsider the transition to nuclear power to reduce their dependence on Russian oil and gas, which has contributed to the surge in uranium prices. Based on the results of this study, various international issues have been closely associated with the nuclear power industry and uranium, affecting the production of uranium and its price.

APro, developed in KAERI for the process-based total system performance assessment (TSPA) of deep geological disposal systems, performs finite element method (FEM)-based multiphysics analysis. In the FEM-based analysis, the mesh element quality influences the numerical solution accuracy, memory requirement, and computation time. Therefore, an appropriate mesh structure should be constructed before the mesh stability analysis to achieve an accurate and efficient process-based TSPA. A generic reference case of DECOVALEX-2023 Task F, which has been proposed for simulating stationary groundwater flow and time-dependent conservative transport of two tracers, was used in this study for mesh stability analysis. The relative differences in tracer concentration varying mesh structures were determined by comparing with the results for the finest mesh structure. For calculation efficiency, the memory requirements and computation time were compared. Based on the mesh stability analysis, an approach based on adaptive mesh refinement was developed to resolve the error in the early stage of the simulation time-period. It was observed that the relative difference in the tracer concentration significantly decreased with high calculation efficiency.

A study was conducted on the vitrification of the rare earth oxide waste generated from the PyroGreen process. The target rare earth waste consisted of eight elements: Nd, Ce, La, Pr, Sm, Y, Gd, and Eu. The waste loading of the rare earth waste in the developed borosilicate glass system was 20wt%. The fabricated glass, processed at 1,200℃, exhibited uniform and homogeneous surface without any crystallization and precipitation. The viscosity and electrical conductivity of the melted glass at 1,200℃ were 7.2 poise and 1.1 S·cm−1, respectively, that were suitable for the operation of the vitrification facility. The calculated leaching index of Cs, Co, and Sr were 10.4, 10.6, and 9.8, respectively. The evaluated Product Consistency Test (PCT) normalized release of the glass indicated that the glass satisfied the requirements for the disposal acceptance criteria. Furthermore, the pristine, 90 days water immersed, 30 thermal cycled, and 10 MGy gamma ray irradiated glasses exhibited good compressive strength. The results indicated that the fabricated glass containing rare earth waste from the PyroGreen process was acceptable for the disposal in the repository, in terms of chemical durability and mechanical strength.

Compared to operational wastes, nuclear power plant (NPP) decommissioning wastes are generated in larger quantities within a short time and include diverse types with a wider range of radiation characteristics. Currently used 200 L drums and IP-2 type transport containers are inefficient and restrictive in packaging and transporting decommissioning wastes. Therefore, new packaging and transport containers with greater size, loading weight, and shielding performance have been developed. When transporting radioactive materials, radiological safety should be assessed by reflecting parameters such as the type and quantity of the package, transport route, and transport environment. Thus far, safety evaluations of radioactive waste transport have mainly targeted operational wastes, that have less radioactivity and a smaller amount per transport than decommissioning wastes. Therefore, in this study, the possible radiation effects during the transport from NPP to disposal facilities were evaluated to reflect the characteristics of the newly developed containers and decommissioning wastes. According to the evaluation results, the exposure dose to transport workers, handling workers, and the public was lower than the domestic regulatory limit. In addition, all exposure dose results were confirmed, through sensitivity analysis, to satisfy the evaluation criteria even under circumstances when radioactive materials were released 100% from the container.

In the design of HLW repositories, it is important to confirm the performance and safety of buffer materials at high temperatures. Most existing models for predicting hydraulic conductivity of bentonite buffer materials have been derived using the results of tests conducted below 100°C. However, they cannot be applied to temperatures above 100°C. This study suggests a prediction model for the hydraulic conductivity of bentonite buffer materials, valid at temperatures between 100°C and 125°C, based on different test results and values reported in literature. Among several factors, dry density and temperature were the most relevant to hydraulic conductivity and were used as important independent variables for the prediction model. The effect of temperature, which positively correlates with hydraulic conductivity, was greater than that of dry density, which negatively correlates with hydraulic conductivity. Finally, to enhance the prediction accuracy, a new parameter reflecting the effect of dry density and temperature was proposed and included in the final prediction model. Compared to the existing model, the predicted result of the final suggested model was closer to the measured values.

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.

With about 80% of the global economy expected to shift to the global market by 2030, exports of reverse direct purchase products, in which foreign consumers purchase products from online shopping malls in Korea, are growing 55% annually. As of 2021, sales of reverse direct purchases in South Korea increased 50.6% from the previous year, surpassing 40 million. In order for domestic SMEs(Small and medium sized enterprises) to enter overseas markets, it is important to come up with export strategies based on various market analysis information, but for domestic small and medium-sized sellers, entry barriers are high, such as lack of information on overseas markets and difficulty in selecting local preferred products and determining competitive sales prices. This study develops an AI-based product recommendation and sales price estimation model to collect and analyze global shopping malls and product trends to provide marketing information that presents promising and appropriate product sales prices to small and medium-sized sellers who have difficulty collecting global market information. The product recommendation model is based on the LTR (Learning To Rank) methodology. As a result of comparing performance with nDCG, the Pair-wise-based XGBoost-LambdaMART Model was measured to be excellent. The sales price estimation model uses a regression algorithm. According to the R-Squared value, the Light Gradient Boosting Machine performs best in this model.

In the era of the 4th Industrial Revolution, Logistic 4.0 using data-based technologies such as IoT, Bigdata, and AI is a keystone to logistics intelligence. In particular, the AI technology such as prognostics and health management for the maintenance of logistics facilities is being in the spotlight. In order to ensure the reliability of the facilities, Time-Based Maintenance (TBM) can be performed in every certain period of time, but this causes excessive maintenance costs and has limitations in preventing sudden failures and accidents. On the other hand, the predictive maintenance using AI fault diagnosis model can do not only overcome the limitation of TBM by automatically detecting abnormalities in logistics facilities, but also offer more advantages by predicting future failures and allowing proactive measures to ensure stable and reliable system management. In order to train and predict with AI machine learning model, data needs to be collected, processed, and analyzed. In this study, we have develop a system that utilizes an AI detection model that can detect abnormalities of logistics rotational equipment and diagnose their fault types. In the discussion, we will explain the entire experimental processes : experimental design, data collection procedure, signal processing methods, feature analysis methods, and the model development.

Large amounts of waste and wastewater from aquaculture have negatively impacted ecosystems. Among them, shrimp aquaculture wastewater contains large amounts of nitrogen contaminants derived from feed residues in an aerobic environment. This study isolated candidate strains from adult rockworms to treat shrimp aquaculture wastewater (SAW) in an aerobic environment. Among 87 strains isolated, 25 grew well at the same temperature as the shrimp aquaculture with excellent polymer degradation ability (>0.5 cm clear zone). Six isolates (strains AL1, AL4, AL5, AL6, LA10, and PR15) were finally selected after combining strains with excellent polymer degradation ability without antagonism. 16S rRNA sequencing analysis revealed that strains AL1, AL4, AL5, AL6, LA10, and PR15 were closely related to Bacillus paramycoides, Bacillus pumilus, Stenotrophomonas rhizophila, Bacillus paranthracis, Bacillus paranthracis, and Micrococcus luteus, respectively. When these six isolates were applied to SAW, they reached a maximum cell viability of 2.06×105 CFU mL-1. Their chemical oxygen demand (CODCr) and total nitrogen (TN) removal rates for 12 h were 51.0% and 44.6%, respectively, when the CODCr/TN ratio was approximately 10.0. Considering these removal rates achieved in this study under batch conditions, these six isolates could be used for aerobic denitrification. Consequently, these six isolates from rockworms are good candidates that can be applied to the field of aquaculture wastewater treatment.

채소는 여러 건강상의 이점을 주는 식이섬유를 다량 함 유하고 있다. 채소는 국내에서 다양한 형태로 섭취되고 있 으며, 특히 생으로 먹거나 나물의 형태로 가장 많이 섭취 되고 있다. 나물은 여러 조리 방법이 있는데, 가장 흔한 방법은 데치고 무치는 형식이다. 한국에서 나물로 흔히 섭 취되는 국내산 참나물, 깻잎, 곰취, 우엉, 마늘쫑을 데친 후, 데친 채소와 생 채소를 한국 식품공전에 따라서 식이 섬유와 유리당을 분석하고 비교하였다. 참나물, 우엉뿌리 와 깻잎은 데친 후에 총 식이섬유가 감소하였으나, 곰취 와 마늘쫑은 각각 6.09±0.49에서 6.43±0.01 g/100 g 과 4.52±0.35 에서 5.09±0.04 g/100 g으로 증가하였다. 유리당 분석 결과, 깻잎을 제외한 채소들에서 sucrose, glucose와 fructose가 검출되었으며, 깻잎은 sucrose가 검출되지 않았 다. 분석한 채소들 중에서 sucrose 함량이 가장 높은 채소 는 우엉 뿌리 (1.71±0.07 g/100 g) 였으며, glucose와 fructose는 각각 1.65±0.02 와1.73±0.02 g/100 g로 마늘쫑 이 가장 높게 나타났다. 채소를 데친 후, 곰취 (0.10±0.01 에서 0.14±0.01 g/100 g)와 마늘쫑 (0.76±0.00 에서0.83±0.01 g /100 g)에 함유된 sucrose를 제외한 다른 유리당 함량은 전 부 감소하였다. 이 연구를 통해 채소를 데치면 채소에 함 유된 유리당과 식이섬유의 함량이 증가하거나 감소할 수 있다는 것을 나타낼 수 있다. 또한, 이러한 영양 정보를 통해 소비자들에게 어떠한 조리 상태의 채소를 섭취할지 선택할 때에 도움을 줄 수 있을 것이다.

Parrots have been threatened by global trade to meet their high demand as pets. Controlling parrot trade is essential because parrots play a vital role in the ecosystem. Accurate species identification is crucial for controlling parrot trade. Parrots have been traded as eggs due to their advantages of lower mortality rates and more accessible transport than live parrots. A molecular method is required to identify parrot eggs because it is difficult to perform identification using morphological features. In this study, DNAs were obtained from 43 unidentified parrot eggs using a non-destructive sampling method. Partial cytochrome b (CYTB ) gene was then successfully amplified using polymerase chain reaction (PCR) and sequenced. Sequences newly obtained in the present study were compared to those available in the GenBank by database searching. In addition, phylogenetic analysis was conducted to identify species using available sequences in GenBank along with sequences reported in previous studies. Finally, the 43 parrot eggs were successfully identified as seven species belonging to two families and seven genera. This non-destructive sampling method for obtaining DNA and molecular identification might help control the trade of parrot eggs and prevent their illegal trade.