• Journal of The Korean Institute of Defense Technology
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• v.5 no.4
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• pp.16-21
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• 2023

Although the global number of landmines is on a declining trend, the damages caused by previously buried landmines persist. In light of this, the present study contemplates solutions to issues and constraints that may arise due to the improvement of mine detection equipment and the reduction in the number of future soldiers. Current mine detectors lack data storage capabilities, posing limitations on data collection for research purposes. Additionally, practical data collection in real-world environments demands substantial time and manpower. Therefore, in this study, gprMax simulation was utilized to generate data. The lightweight CNN-based model, MobileNet, was trained and validated with real data, achieving a high identification rate of 97.35%. Consequently, the potential integration of technologies such as deep learning and simulation into geographical detection equipment is highlighted, offering a pathway to address potential future challenges. The study aims to somewhat alleviate these issues and anticipates contributing to the development of our military capabilities in becoming a future scientific and technological force.

• The Plant Pathology Journal
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• v.40 no.4
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• pp.346-357
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• 2024

This study was carried out to screen the antifungal activity against Colletotrichum acutatum, Colletotrichum dematium, and Colletotrichum coccodes. Bacterial isolate GP-P8 from pepper soil was found to be effective against the tested pathogens with an average inhibition rate of 70.7% in in vitro dual culture assays. 16S rRNA gene sequencing analysis result showed that the effective bacterial isolate as Bacillus siamensis. Biochemical characterization of GP-P8 was also performed. According to the results, protease and cellulose, siderophore production, phosphate solubilization, starch hydrolysis, and indole-3-acetic acid production were shown by the GP-P8. Using specific primers, genes involved in the production of antibiotics, such as iturin, fengycin, difficidin, bacilysin, bacillibactin, surfactin, macrolactin, and bacillaene were also detected in B. siamensis GP-P8. Identification and analysis of volatile organic compounds through solid phase microextraction/gas chromatography-mass spectrometry (SPME/GC-MS) revealed that acetoin and 2,3-butanediol were produced by isolate GP-P8. In vivo tests showed that GP-P8 significantly reduced the anthracnose disease caused by C. acutatum, and enhanced the growth of pepper plant. Reverse transcription polymerase chain reaction analysis of pepper fruits revealed that GP-P8 treated pepper plants showed increased expression of immune genes such as CaPR1, CaPR4, CaNPR1, CaMAPK4, CaJA2, and CaERF53. These results strongly suggest that GP-P8 could be a promising biocontrol agent against pepper anthracnose disease and possibly a pepper plant growth-promoting agent.

• Journal of the Korean Ceramic Society
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• v.59
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• pp.338-349
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• 2020

Large scale with high-purity hexagonal aluminum nitride nanoparticles (AlN NPs) was synthesized using DC thermal plasma arc discharge method (TPAD). Argon gas was used as the plasma forming gas, while ammonia (NH₃) gas was used as the reactive gas, which was fed into the reactor at a constant flow rate of 5 LPM. In order to optimize the process for high yield, the experiments were carried out at various plasma input powers, such as 1.5, 3.0, and 4.5 kW. Following the optimization, to examine the influence of using pure nitrogen gas, an experiment was also carried out in the nitrogen ambience. The phase identification and structural determination of the synthesized NPs were carried out using XRD and Raman spectroscopic analyses. While the morphology, particle size, and elemental compositions of the synthesized NPs were observed from SEM, HRTEM, XPS, and EDX analyses. The photoluminescence response was confirmed from the PL spectrum. The PL emission peaks observed around 440 nm (2.8 eV) and 601 nm (2.07 eV), respectively, which correspond to the UV blue and red band emissions of both AlN and Al/AlN NPs. The results show that the synthesized nano-AlN NPs exhibit excellent crystallinity with a high yield of approximately 210 g/h. The current plasma technology can be regarded as a perfect potential process for developing nano-AlN powders with improved efficiency.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.47 no.2
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• pp.30-39
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• 2024

This study introduces a novel approach for identifying potential failure risks in missile manufacturing by leveraging Quality Inspection Management (QIM) data to address the challenges presented by a dataset comprising 666 variables and data imbalances. The utilization of the SMOTE for data augmentation and Lasso Regression for dimensionality reduction, followed by the application of a Random Forest model, results in a 99.40% accuracy rate in classifying missiles with a high likelihood of failure. Such measures enable the preemptive identification of missiles at a heightened risk of failure, thereby mitigating the risk of field failures and enhancing missile life. The integration of Lasso Regression and Random Forest is employed to pinpoint critical variables and test items that significantly impact failure, with a particular emphasis on variables related to performance and connection resistance. Moreover, the research highlights the potential for broadening the scope of data-driven decision-making within quality control systems, including the refinement of maintenance strategies and the adjustment of control limits for essential test items.

• Journal of Cerebrovascular and Endovascular Neurosurgery
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• v.26 no.1
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• pp.23-29
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• 2024

Objective: Flow diverting stents (FDS) are increasingly used for the treatment of intracranial aneurysms. While FDS can provide flow diversion of parent vessels, their high metal surface coverage can cause thromboembolism. Transcranial Doppler (TCD) emboli monitoring can be used to identify subclinical embolic phenomena after neurovascular procedures. Limited data exists regarding the use of TCDs for emboli monitoring in the periprocedural period after FDS placement. We evaluated the rate of positive TCDs microembolic signals and stroke after FDS deployment at our institution. Methods: We retrospectively evaluated 105 patients who underwent FDS treatment between 2012 and 2016 using the Pipeline stent (Medtronic, Minneapolis, MN, USA). Patients were pretreated with aspirin and clopidogrel. All patients were therapeutic on clopidogrel pre-operatively. TCD emboli monitoring was performed immediately after the procedure. Microembolic signals (mES) were classified as "positive" (<15 mES/hour) and "strongly positive" (>15 mES/hour). Clinical stroke rates were determined at 2-week and 6-month post-operatively. Results: A total of 132 intracranial aneurysms were treated in 105 patients. TCD emboli monitoring was "positive" in 11.4% (n=12) post-operatively and "strongly positive" in 4.8% (n=5). These positive cases were treated with heparin drips or modification of the antiplatelet regimen, and TCDs were repeated. Following medical management modifications, normalization of mES was achieved in 92% of cases. The overall stroke rates at 2-week and 6-months were 3.8% and 4.8%, respectively. Conclusions: TCD emboli monitoring may help early in the identification of thromboembolic events after flow diversion stenting. This allows for modification of medical therapy and, potentially, preventionf of escalation into post-operative strokes.

• Herbal Formula Science
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• v.32 no.3
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• pp.223-233
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• 2024

Objectives : Natural products containing bioactive compounds with high antioxidant activity are potentially important sources that can contribute to the improvement of various diseases. Therefore, the aim of this study was to investigate phenolic compounds of Cinnamomum cassia (C. cassia) ethanolic extract (CCEE). And then we evaluated the antioxidant effect. Methods : We used liquid chromatography with tandem mass spectrometry (LC-MS/MS) to identify the compounds in CCEE. LC-MS/MS was performed in positive ion mode using Shimadzu, Nexera HPLC system and IDA TOF mass system. Solvent A was distilled water and solvent B was acetonitrile as mobile phase. The analysis was performed at a flow rate of 0.5 ml/min, column temperature of 35 ℃ and wavelength of 284 nm. The antioxidant effect of CCEE was analyzed using DPPH (2,2-diphenyl-2-picrylhydrazyl free radical) and ABTS (2,2'-azino-bis (3-ethylbenzothiazoline-6-sulfonic acid)). In addition, total phenolics and total flavonoids contents were measured to determine antioxidant effects. Results : Analysis using LC-MS/MS identified four compounds: Coumarin, Trans-cinnamaldehyde, Trans-cinnamic acid, and 2-Methoxycinnamaldehyde. Free radicals decreased in a concentration-dependent manner starting from 10 ㎍/ml of CCEE, and decreased to a level similar to Ascorbic acid (AA) from a concentration of 60 ㎍/ml onwards. Conclusions : Based on the findings, CCEE exhibits strong antioxidant activity as evidenced by the presence of Coumarin, Trans-cinnamaldehyde, Trans-cinnamic acid, and 2-Methoxycinnamaldehyde. Consequently, this study suggests that CCEE can serve as an important source of natural antioxidants and can be efficiently used in the management of oxidative stress diseases.

• Journal of The Korea Institute of Healthcare Architecture
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• v.30 no.3
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• pp.67-74
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• 2024

Purpose: The identification and quantification of indoor airborne contaminants, including bio-aerosols, particulates, and gaseous contaminants, are crucial for maintaining acceptable indoor air quality for hospital operating rooms (ORs). Laparoscopic surgery has become widely accepted for various surgical procedures due to its rapid recovery rate and the low risk associated with small incisions compared to conventional open surgery. The objective of this study is to investigate the indoor air quality in hospital ORs and to identify indoor airborne contaminants generated during laparoscopic surgery. Methods: Measurements of an indoor environment, including temperature, humidity and air quality, were performed in an OR before and during a laparoscopic surgery. Indoor airborne contaminants, including volatile organic compounds (VOCs), formaldehyde, carbon monoxide (CO), carbon dioxide (CO₂), sulfur dioxide (SO₂), nitrogen dioxide (NO₂), suspended indoor particles, and airborne bacteria, were measured simultaneously. Results: The study determined that the concentrations of indoor air particles and airborne bacteria increased during the surgery but were within acceptable levels. However, the concentration of CO₂, reached a high level of 1,791 ppm due to the CO₂ gas required for maintaining the pneumoperitoneum during the surgery. Implications: The results emphasized the use of ventilation and filtration in a laparoscopic surgery room to lower the concentration of filterable and non-filterable contaminants.

• Journal of the Korean Applied Science and Technology
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• v.41 no.3
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• pp.733-744
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• 2024

This study extracted essential oil from the native Korean plant Valeriana fauriei and performed fragrance component analysis, antioxidant (DPPH, ABTS), cell viability (MTS), and anti-inflammatory (Nitric oxide) experiments based on the analysis results. The fragrance component analysis revealed that the major effective component of Valeriana fauriei, bornyl acetate, was present at a high content of 47.88%, compared to other regions. Additionally, patchouli alcohol (18.9%), camphene (11.37%), α-Pinene (5.44%), and D-limonene (1.11%) were identified. The antioxidant activity showed that the DPPH radical scavenging activity was 73.62% at 250 µl/ml, and the ABTS radical scavenging activity was 82.17% at 250 µl/ml. At a concentration of 5 µl/ml, which did not exhibit cytotoxicity, the NO production inhibition rate decreased by 62.02% compared to the control group. Through these findings, the potential for the application of Valeriana fauriei essential oil in functional products has been scientifically validated, contributing to research utilizing Valeriana fauriei essential oil.

• Nuclear Engineering and Technology
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• v.56 no.9
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• pp.3717-3729
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• 2024

Accurately predicting evacuation time in a ventilated main control room (MCR) during fire emergencies is crucial for ensuring the safety of personnel at nuclear power plants. This study proposes to use neural networks alongside consolidated fire and smoke transport (CFAST) simulations to serve as a surrogate model for physics-based simulation tools. Our neural networks can promptly predict the evacuation time in MCRs, proving to be a valuable asset in fire emergencies and eliminating the need for time-consuming rollouts of the CFAST simulations. The CFAST model simulates fire and evacuation scenarios in a ventilated MCR with variations in input parameters such as door conditions, ventilation flow rate, leakage area, and fire propagation time. Target output parameters, such as hot gas layer temperature (HGLT), heat flux (HF), and optical density (OD), are used alongside standardized evacuation variables to train a machine learning model for predicting evacuation time. The findings suggest that high ventilation flow rates help to dilute smoke and discharge hot gas, leading to lower target output parameters and quicker evacuation. Standardized evacuation variables exceed the required abandonment criteria for all door conditions, indicating the importance of proper evacuation procedures. The results show that neural networks can generate evacuation times close to those obtained from CFAST simulations.

• Journal of Distribution Research
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• v.15 no.1
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• pp.1-24
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• 2010

I. Introduction The industry of domestic discount store was reorganized with 2 bigs and 1 middle, and then Home Plus took over Home Ever in 2008. In present, Oct, 2008, E-Mart has 118 outlets, Home Plus 112 outlets, and Lotte Mart 60 stores. With total number of 403 outlets, they are getting closer to a saturation point. We know that the industry of discount store has been getting through the mature stage in retail life cycle. There are many efforts to maintain existing customers rather than to get new customers. These competitions in this industry lead firms to acknowledge 'store loyalty' to be the first strategic tool for their sustainable competitiveness. In other words, the strategic goal of discount store is to boost up the repurchase rate of customers throughout increasing store loyalty. If owners of retail shops can figure out main factors for store loyalty, they can easily make more efficient and effective retail strategies which bring about more sales and profits. In this practical sense, there are many papers which are focusing on the antecedents of store loyalty. Many researchers have been inspecting causal relationships between antecedents and store loyalty; store characteristics, store image, atmosphere in store, sales promotion in store, service quality, customer characteristics, crowding, switching cost, trust, satisfaction, commitment, etc., In recent times, many academic researchers and practitioners have been interested in 'dual path model for service loyalty'. There are two paths in store loyalty. First path has an emphasis on symbolic and emotional dimension of service brand, and second path focuses on quality of product and service. We will call the former an extrinsic path and call the latter an intrinsic path. This means that consumers' cognitive path for store loyalty is not single but dual. Existing studies for dual path model are as follows; First, in extrinsic path, some papers in domestic settings show that there is 'store personality-identification-loyalty' path. Second, service quality has an effect on loyalty, which is a behavioral variable, in the mediation of customer satisfaction. But, it's very difficult to find out an empirical paper applied to domestic discount store based on this mediating model. The domestic research for store loyalty concentrates on not only intrinsic path but also extrinsic path. Relatively, an attention for intrinsic path is scarce. And then, we acknowledge that there should be a need for integrating extrinsic and intrinsic path. Also, in terms of retail industry, this study is meaningful because retailers want to achieve their competitiveness by using store loyalty. And so, the purpose of this paper is to integrate and complement two existing paths into one specific model, dual path model. This model includes both intrinsic and extrinsic path for store loyalty. With this research, we would expect to understand the full process of forming customers' store loyalty which had not been clearly explained. In other words, we propose the dual path model for discount store loyalty which has been originated from store personality and service quality. This model is composed of extrinsic path, discount store personality$\rightarrow$store identification$\rightarrow$store loyalty, and intrinsic path, service quality of discount store$\rightarrow$customer satisfaction$\rightarrow$store loyalty. II. Research Model Dual path model integrates intrinsic path and extrinsic path into one specific model. Intrinsic path put an emphasis on quality characteristics and extrinsic path focuses on brand characteristics. Intrinsic path is based on information processing perspective, and extrinsic path emphasizes symbolic and emotional dimension of brand. This model is composed of extrinsic path, discount store personality$\rightarrow$store identification$\rightarrow$store loyalty, and intrinsic path, service quality of discount store$\rightarrow$customer satisfaction$\rightarrow$store loyalty. Hypotheses are as follows; Hypothesis 1: Service quality perceived by customers in discount store has an positive effect on customer satisfaction Hypothesis 2: Store personality perceived by customers in discount store has an positive effect on store identification Hypothesis 3: Customer satisfaction in discount store has an positive effect on store loyalty. Hypothesis 4: Store identification has an positive effect on store loyalty. III. Results and Implications We examined consumers who patronize discount stores for samples of this study. With the structural equation model(SEM) analysis, we empirically tested the validity and fitness of the dual path model for store loyalty in discount stores. As results, the fitness indices of this model were well fitted to data obtained. In an intrinsic path, service quality(SQ) is positively related to customer satisfaction(CS), customer satisfaction(CS) has very significantly positive effect on store loyalty(SL). Also, in an extrinsic path, the store personality(SP) is positively related to store identification(SI), it shows significant effect on store loyalty. Table 1 shows the results as follows; There are some theoretical and practical implications. First, Many studies on discount store loyalty have been executed from various perspectives. But there has been no integrative view on this issue. And so, this research was theoretically designed to integrate various and controversial arguments into one systematic model. We empirically tested dual path model forming store loyalty, and brought up a systematic and integrative framework for future studies. We want to expect creative and aggressive research activities. Second, a few established papers are focused on the relationship between antecedents and store loyalty; store characteristics, atmosphere, sales promotion in store, service quality, trust, commitment, etc., There has been some limits in understanding thoroughly the formation process of store loyalty with a singular path, intrinsic or extrinsic. Beyond these limits in single path, we could propose the new path for store loyalty. This is meaningful. Third, discount store firms make and execute marketing strategies for increasing store loyalty. This research provides real practitioners with reference framework needed for actual strategy formation. Because this paper shows integrated and systematic path for store loyalty. A special feature of this study is to represent 6 sub dimensions of service quality in intrinsic path and 4 sub dimensions of store personality in extrinsic path. Marketers can make more analytic marketing planning with concrete sub dimensions of service quality and store personality. When marketers of discount stores make strategic planning like MPR, Ads, campaign, sales promotion, they can use many items which are more competitive than competitors.