This study was conducted to calculate the damage of Italian ryegrass (IRG) by abnormal climate using machine learning and present the damage through the map. The IRG data collected 1,384. The climate data was collected from the Korea Meteorological Administration Meteorological data open portal.The machine learning model called xDeepFM was used to detect IRG damage. The damage was calculated using climate data from the Automated Synoptic Observing System (95 sites) by machine learning. The calculation of damage was the difference between the Dry matter yield (DMY)normal and DMYabnormal. The normal climate was set as the 40-year of climate data according to the year of IRG data (1986~2020). The level of abnormal climate was set as a multiple of the standard deviation applying the World Meteorological Organization (WMO) standard. The DMYnormal was ranged from 5,678 to 15,188 kg/ha. The damage of IRG differed according to region and level of abnormal climate with abnormal temperature, precipitation, and wind speed from -1,380 to 1,176, -3 to 2,465, and -830 to 962 kg/ha, respectively. The maximum damage was 1,176 kg/ha when the abnormal temperature was -2 level (+1.04℃), 2,465 kg/ha when the abnormal precipitation was all level and 962 kg/ha when the abnormal wind speed was -2 level (+1.60 ㎧). The damage calculated through the WMO method was presented as an map using QGIS. There was some blank area because there was no climate data. In order to calculate the damage of blank area, it would be possible to use the automatic weather system (AWS), which provides data from more sites than the automated synoptic observing system (ASOS).

This study was aimed to isolate bacterial inoculants producing chitinase and evaluate their application effects on corn silage. Four corn silages were collected from four beef cattle farms to serve as the sources of bacterial inoculants. All isolates were tested against Fusarium graminearum head blight fungus MHGNU F132 to confirm their antifungal effects. The enzyme activities (carboxylesterase and chitinase) were also measured to isolate the bacterial inoculant. Based on the activities of anti-head blight fungus, carboxylesterase, and chitinase, L. buchneri L11-1 and L. paracasei L9-3 were subjected to silage production. Corn forage (cv. Gwangpyeongok) was ensiled into a 10 L mini silo (5 kg) in quadruplication for 90 days. A 2 × 2 factorial design consists of F. graminearum contamination at 1.0104 cfu/g (UCT (no contamination) vs. CT (contamination)) and inoculant application at 2.1 × 105 cfu/g (CON (no inoculant) vs. INO (inoculant)) used in this study. After 90 days of ensiling, the contents of CP, NDF, and ADF increased (p<0.05) by F. graminearum contamination, while IVDMD, acetate, and aerobic stability decreased (p<0.05). Meanwhile, aerobic stability decreased (p<0.05) by inoculant application. There were interaction effects (p<0.05) on IVNDFD, NH3-N, LAB, and yeast, which were highest in UCT-INO, UCT-CON, CT-INO, and CT-CON & INO, respectively. In conclusion, this study found that mold contamination could negatively impact silage quality, but isolated inoculants had limited effects on IVNDFD and yeast.

Extensive research and testing continue to be conducted for the development of vaccines targeting zoonotic diseases such as brucellosis. In this study, the potential of the DapB as a recombinant protein vaccine to effectively combat Brucella abortus 544 infection in BALB/c mice was evaluated. Western blotting assay results showed that recombinant protein DapB reacted with Brucella-positive serum, indicating its potential immunoreactivity. In vivo results showed that the peripheral blood CD4+ and CD8+ T cell population significantly increased in the DapB-immunized mice group after the first, second and third blood collection, compared to the control group that received PBS. Additionally, at the fourth blood collection, an increase in CD4+ T cell activation was observed in three vaccination groups compared to PBS negative control group. These results indicate the potential of DapB in stimulating cellular immunity. Fourteen days after infection, the bacterial load in the spleen was evaluated. The reduction in bacterial replication in the spleen by both DapB and RB51 highlights their protective efficacy against Brucella infection. These findings contribute to the ongoing efforts in developing effective vaccines against brucellosis and provide valuable insights for further research in this field.

Although the proportion of coal-fired power generation is decreasing, efficient operating technology is needed to continuously invest in facilities and reduce maintenance costs until it is abolished. Boilers, one of the main facilities of power plants, operate for a long time in harsh environments of high temperature and high pressure. In addition, damage due to deterioration is likely to occur depending on the fuel and tube material used. It is very important to judge soundness because damage caused by deterioration adversely affects facility operation. Previously, replication method was used to analyze the progress of deterioration. In the replication method, pre-treatment such as chemical treatment is performed on the boiler tube in the field, the area is reproduced by attaching a film, and the replicated film is determined by an expert in the laboratory with an expensive microscope. However, this method involves substantial costs and time requirements, as well as the possibility of human errors. To address these issues, we developed a mobile health assessment system in this research. Since it is detachable and takes images in real time, this system enables swift evaluations across a broad range and facilitates the assessment of preprocessing quality. In addition, it was intended to reduce existing human mistakes by developing a degradation classification algorithm using the merger cluster method.

이번에 제시할 화상 사례 보고는 환자와 검사를 시행하는 방사선사의 부주의로 인한 화상 안전사고가 아니라 환자 가운 의 치수 구별을 하기 위하여 사용한 녹색 염료가 착색된 파이핑 라인에서 발생한 복부 부위 화상 안전사고에 대한 MRI 인공물 영상과 사례를 보고하고자 함이다. 화학 착색염료는 다양한 금속을 사용하여 만들어지고 주로 금속 염화물로 이루 어져 있으며 이번에 화상 사례로 발생한 녹색 염료는 열 전도성이 높은 구리와 크롬, 철 성분이 많이 함유된 염화물이 주로 사용되고 있다. 이러한 화상 안전사고를 막기 위해서는 염료의 성분에 대해서 알아보고 열 전도성이 없는 스펀지나 면으로 된 포 등을 피부와 환자 가운 사이에 끼워 간격을 두어야 할 것이다. 이번 화상 사례는 철저한 검사 전 선별 절차에도 불구 하고 화상 안전사고가 발생할 수 있음을 보여 주고 있으며 MRI 인공물 영상을 확인하여 조치하면 화상 안전사고를 미리 예방할 수 있는 정보로 가치가 있을 것으로 생각된다.

In the realm of dental prosthesis fabrication, obtaining accurate impressions has historically been a challenging and inefficient process, often hindered by hygiene concerns and patient discomfort. Addressing these limitations, Company D recently introduced a cutting-edge solution by harnessing the potential of intraoral scan images to create 3D dental models. However, the complexity of these scan images, encompassing not only teeth and gums but also the palate, tongue, and other structures, posed a new set of challenges. In response, we propose a sophisticated real-time image segmentation algorithm that selectively extracts pertinent data, specifically focusing on teeth and gums, from oral scan images obtained through Company D's oral scanner for 3D model generation. A key challenge we tackled was the detection of the intricate molar regions, common in dental imaging, which we effectively addressed through intelligent data augmentation for enhanced training. By placing significant emphasis on both accuracy and speed, critical factors for real-time intraoral scanning, our proposed algorithm demonstrated exceptional performance, boasting an impressive accuracy rate of 0.91 and an unrivaled FPS of 92.4. Compared to existing algorithms, our solution exhibited superior outcomes when integrated into Company D's oral scanner. This algorithm is scheduled for deployment and commercialization within Company D's intraoral scanner.

There are many types of foam molding methods. The most commonly used methods are the pressure foaming method, in which foam resin is mixed with a foaming agent at high temperature and high pressure, and the normal pressure foaming method, which foams at high temperature without pressure. The polymer resins used for foaming have different viscosities. For foaming under normal pressure, they need to be designed and analyzed for optimal foaming conditions, to obtain resins with low melt-viscosity or a narrow optimal viscosity range. This study investigated how changes in viscosity, molding temperature, and cross-link foaming conditions affected the characteristics of the molded foam, prepared by blending rubber polymer with biodegradable resin. The morphologies of cross sections and the cell structures of the normal pressure foam were investigated by SEM analysis. Properties were also studied according to cross-link/foaming conditions and torque. Also, the correlation between foaming characteristics was studied by analyzing tensile strength and elongation, which are mechanical properties of foaming composites.

The thermoelectric effect, which converts waste heat into electricity, holds promise as a renewable energy technology. Recently, bismuth telluride (Bi2Te3)-based alloys are being recognized as important materials for practical applications in the temperature range from room temperature to 500 K. However, conventional sintering processes impose limitations on shape-changeable and tailorable Bi2Te3 materials. To overcome these issues, three-dimensional (3D) printing (additive manufacturing) is being adopted. Although some research results have been reported, relatively few studies on 3D printed thermoelectric materials are being carried out. In this study, we utilize extrusion 3D printing to manufacture n-type Bi1.7Sb0.3Te3 (N-BST). The ink is produced without using organic binders, which could negatively influence its thermoelectric properties. Furthermore, we introduce graphene oxide (GO) at the crystal interface to enhance the electrical properties. The formed N-BST composites exhibit significantly improved electrical conductivity and a higher Seebeck coefficient as the GO content increases. Therefore, we propose that the combination of the extrusion 3D printing process (Direct Ink Writing, DIW) and the incorporation of GO into N-BST offers a convenient and effective approach for achieving higher thermoelectric efficiency.

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).

A ‘brand’ metaverse is a virtual space where customers experience the brand via digital avatars. With the advancement of augmented and virtual reality technologies, a brand metaverse is an important medium for communicating the brand with customers. In this study, we focus on the resemblance between a customer’s self and his/her avatar (i.e., self-avatar resemblance) in the brand metaverse and examine its influence on brand attitude. Prior studies examine self-avatar resemblance exclusively in non-brand-related virtual gaming platforms and test its effect on identity perception and immersion in the platforms. However, few studies probe the extent to which self-avatar resemblance influences customers' exploration in a brand metaverse and their attitude toward the brand. We fill this research gap by uncovering the positive effects of self-avatar resemblance on brand attitude and purchase intentions. Moreover, we proffer that the customers’ engagement toward the brand metaverse platform mediates the relationship between self-avatar resemblance and brand attitude. In addition, based on the interactive nature of metaverse, we hypothesize copresence―the number of avatars exploring the brand metaverse at the same time―to be a moderator, which strengthens the mediation. We conduct an experiment using a fashion brand’s virtual world positioned in a popular metaverse platform. In this experiment, participants create an avatar and freely roam around in the brand metaverse with their avatars. By reviewing the screen recording of each participant’s brand exploration in the metaverse, we measure self-avatar resemblance and other constructs. We also collect responses from questionnaires designed to measure attitudinal and behavioral variables. With the accumulated data, we test the hypotheses using partial least square structural equation model and find the results largely consistent with the hypotheses. With the findings, we provide important and interesting implications to marketing practitioners considering and doing ‘metaverse marketing.’

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.

With the development of information technology, online food delivery services have significantly changed people’s food consumption patterns. The outbreak of COVID-19 has further facilitated the development due to restaurant restrictions and social distancing measures. Due to the emergence of online food delivery services, scholars have paid increasing attention to this popular topic, and a large number of studies have examined which factors are related to consumers’ intention to use online food delivery services. However, previous studies showed inconsistent findings, and relationships between variables lack a comprehensive understanding. Therefore, this study aimed to develop a research model and examine the factors influencing consumers’ intention to use online food delivery services. By reviewing and analyzing 52 studies with 53 independent samples (N = 22,937), the meta-analytic structural equation modeling approach was carried out to assess the research model. The findings indicate that two attributes of online food delivery services (i.e., convenience and price-saving orientation) play different roles in the research model. Specifically, convenience significantly impacted perceived ease of use but had no direct impact on perceived usefulness. Price-saving orientation significantly influenced both perceived ease of use and perceived usefulness. Moreover, relationships between perceived ease of use, perceived usefulness, and perceived trust were significant, and these factors ultimately significantly led to the intention to use food delivery services. The findings contribute to theoretical advancement in the extant literature on food delivery services and help firms develop to provide better food delivery services for consumers’ continuous usage.

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.

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.

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.

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.

목적 : 본 연구의 목적은 녹내장의 예방 및 조기진단을 위해 진단되지 않은 녹내장의 특징과 관련 인자의 상관 관계를 알아내는 데 있다. 방법 : 국민건강영양조사 제7기 2017∼2018년 안검진을 받은 만 40세 이상 성인 7,546명을 대상으로 하였다. 참가자는 빛간섭단층촬영, 시야검사, 안저사진 촬영 검사를 통해 녹내장 판정을 받았다. 그리고, 자가 설문 응답 조사를 통해 사전 진단 여부를 파악하였다. 통계는 카이제곱 검정을 사용하였고, 관련성은 로지스틱 회귀분석을 이용하여 분석하였다. 결과 : 7,546명의 참가자 중 325명이 녹내장 진단을 받았으며 유병률은 4.3%였다. 이 중 47명은 사전 녹내장 진단을 받은 이력이 있고, 180명은 이전에 녹내장 치료를 받은 적이 없는 미진단 녹내장 환자로 79%를 차지했다. 연령과 성별을 보정한 관련성 분석에서는 안과를 방문한 지 1개월 이내 집단보다 1개월에서 1년 이내에 안과를 방문한 집단에서 관련성이 21배 높았다(p=0.002), 1년 이상 안과를 방문하지 않은 군에서는 1개월 이내 집단보 다 126배 높았다(p=0.001). 굴절이상과 관련도는 우안의 원시 굴절이상 환자군에서 녹내장 관련도가 8배 (p=0.043) 더 높았다. 다른 사회학적 및 건강 관련 요인에서는 진단되지 않은 녹내장과 진단된 녹내장에 대해 통 계적 유의성이 발견되지 않았습니다. 결론 : 안과 의사의 정기적인 방문과 원시 굴절이상 환자는 진단되지 않은 녹내장의 조기진단에 중요한 요소입 니다.

Ammonium (NH4 +) serves as a nitrogen source, but its elevated levels can hinder plant growth and production. Excess NH4 + with α-ketoglutarate is assimilated into glutamate, a precursor of proline and glutathione (GSH). This study aimed to investigate the effects of excessive NH4 + on the regulation of proline and GSH synthesis. Detached leaves from oilseed rape (Brassica napus L.) were fed with 0, 50, 100, 500, and 1000 mM NH4Cl for 16 h. As the NH4 + concentrations increased, the leaves exhibited progressive wilting and yellowing. Furthermore, total carotenoid and chlorophyll concentrations declined in response to all NH4 + treatments, with the lowest levels observed in 1000 mM NH4 + treatment. Hydrogen peroxide (H2O2) concentration showed a minor increase at low NH4 + concentration (50 and 100 mM) treatments but a significant increase at high NH4 + (500 and 1000 mM), which was consistent with the localization of H2O2. Amino acid concentrations increased with increasing in NH4 + concentration, while the protein concentration displayed the opposite trend. Proline and cysteine concentrations exhibited a gradual increase in response to increasing NH4 + concentrations. However, GSH concentrations rose only in the 50 mM NH4 + treatment and decreased in the 500 and 1000 mM NH4 + treatments. These results indicate that excessive NH4 + is primarily assimilated into proline, while GSH synthesis is adversely affected.

This study is to identify the maintenance service quality of eco-friendly cars, which are rapidly increasing recently. Research is conducted by synthesizing research from the perspectives of internal employees and external customers by using the service profit chain model. Specifically, it is to study the overall structural relationship between internal customer satisfaction, physical quality, interaction quality, outcome quality, external customer satisfaction and long-term orientation. For the study, 202 questionnaires were collected from internal employees and 204 questionnaires from external customers. The results of testing the research hypotheses targeting the internal employee group are as follows. As a result of testing hypothesis 1, internal customer satisfaction has a significant positive (+) effect on physical quality and interaction quality. As a result of testing hypothesis 2, the service quality of eco-friendly car maintenance has a significant positive (+) effect on each other. As a result of testing hypothesis 3, physical quality and outcome quality have a significant positive (+) effect on external customer satisfaction. The results of testing the research hypotheses targeting an external customer group are as follows. As a result of testing hypothesis 2, in the relationship between eco-friendly car maintenance service quality, physical quality has a significant positive (+) effect on interaction quality, and interaction quality has a significant positive (+) effect on outcome quality. As a result of testing hypothesis 3, interaction quality and outcome quality have a significant positive (+) effect on external customer satisfaction. As a result of testing Hypothesis 4, external customer satisfaction has a significant positive (+) effect only on intention to reuse. Finally, as a result of examining the difference in perception between the internal employee group and the external customer group in eco-friendly car maintenance service quality and external customer satisfaction, it was verified that there was a significant difference only in outcome quality and external customer satisfaction.