• Journal of the Korean Applied Science and Technology
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• v.37 no.6
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• pp.1635-1645
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• 2020

In this study would like to find extending or increasing the efficacy of the antibiotic substance for the strains with resistance to antibiotics or persister cells by inhibition of the resistance. This study was used different species of 'legal high' plants leaves from Leonotis leonurus, Mitragyna speciosa, and seeds from Ipomoea murucoides with antibiotics which are Amoxicillin, Chloramphenicol, Ciprofloxacin, Kanamycin, Oxacillin, and Vancomycin. Legal highs were extracted with methanol. Minimum inhibitory concentration(MIC) testing for a range of antibiotics with extracts of plant was fulfilled by broth dilution methods. In this essay, it was determined in a microdilution assay utilizing suspended in ISB up to a final concentration of 512㎍/ml in 96 wells microtitre plates, threefold and serial dilutions. After that, the microplates were kept in incubator between 35℃ and 37℃ for overnight. Leonotis leonurus, Mitragyna speciosa, and Ipomoea murucoides of Legal highs (512㎍/ml) investigated small activity to inhibit against pathogens which are susceptible Staphylococcus aureus, resistant Staphylococcus aureus, susceptible Enterococcus faecalis, resistant Escherichia coli.

• Applied Chemistry for Engineering
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• v.33 no.4
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• pp.352-366
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• 2022

Nuclear power plant operations for electricity generation, rare-earth mining, nuclear medical research, and nuclear weapons reprocessing considerably increase radioactive waste, necessitating massive efforts to eradicate radioactive waste from aquatic environments. Cobalt (⁵⁸Co) and strontium (⁹⁰Sr) radioactive elements have been extensively employed in energy generation, nuclear weapon testing, and the manufacture of healthcare products. The erroneous discharge of these elements as pollutants into the aquatic system, radiation emissions, and long-term disposal is extremely detrimental to humans and aquatic biota. Numerous methods for treating radioactive waste-contaminated water have emerged, among which the adsorption process has been promoted for its efficacy in eliminating radioactive waste from aquatic habitats. The current review discusses the adsorptive removal of radioactive waste from aqueous solutions using low-cost adsorbents, such as graphene oxide, metal-organic frameworks, and inorganic metal oxides, as well as their composites. The chemical modification of adsorbents to increase their removal efficiency is also discussed. Finally, the current state of ⁵⁸Co and ⁹⁰Sr removal performances is summarized and the efficiencies of various adsorbents are compared.

• KOREAN JOURNAL OF PACKAGING SCIENCE & TECHNOLOGY
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• v.28 no.2
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• pp.127-132
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• 2022

The growth of e-commerce market requires more delivery packagings, which protect goods from the damage factors on the delivery. In this study, we have analyzed the distribution environment data (vibration and impact) measured in previous study and compared with global standards (ISTA, ASTM), so that we developed the testing method for Field-to-Lab simulation suitable to the domestic delivery. In order to verify the efficacy of this method, we took the Field-to-Lab tests for 3 packaged products (detergents set, glass tableware set, small furniture), which has been frequent breakages or damages on the actual delivery by e-commerce order, so that we could find out the test results were similar to those of the actual delivery occasions. In addition, we could perform redesign and improvement of the parcel delivery packagings for safe transportation by taking this Field-to-Lab test repeatedly. This test methods was finally proposed to be Korean industrial standard (KS), and is expected to be useful as a designing tool for the packaging optimization between protecting goods and reducing packaging waste.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.46 no.4
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• pp.229-237
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• 2023

In this research, a new Test and Evaluation (T&E) procedure for defense AI systems is proposed to fill the existing gap in established methodologies. This proposed concept incorporates a data-based performance evaluation, allowing for independent assessment of AI model efficacy. It then follows with an on-site T&E using the actual AI system. The performance evaluation approach adopts the project promotion framework from the defense acquisition system, outlining 10 steps for R&D projects and 9 steps for procurement projects. This procedure was crafted after examining AI system testing standards and guidelines from both domestic and international civilian sectors. The validity of each step in the procedure was confirmed using real-world data. This study's findings aim to offer insightful guidance in defense T&E, particularly in developing robust T&E procedures for defense AI systems.

• Geomechanics and Engineering
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• v.37 no.3
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• pp.253-262
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• 2024

Dynamic properties are pivotal in soil analysis, yet their experimental determination is hampered by complex methodologies and the need for costly equipment. This study aims to predict dynamic soil properties using static properties that are relatively easier to obtain, employing machine learning techniques. The static properties considered include soil cohesion, friction angle, water content, specific gravity, and compressional strength. In contrast, the dynamic properties of interest are the velocities of compressional and shear waves. Data for this study are sourced from 26 boreholes, as detailed in a geotechnical investigation report database, comprising a total of 130 data points. An importance analysis, grounded in the random forest algorithm, is conducted to evaluate the significance of each dynamic property. This analysis informs the prediction of dynamic properties, prioritizing those static properties identified as most influential. The efficacy of these predictions is quantified using the coefficient of determination, which indicated exceptionally high reliability, with values reaching 0.99 in both training and testing phases when all input properties are considered. The conventional method is used for predicting dynamic properties through Standard Penetration Test (SPT) and compared the outcomes with this technique. The error ratio has decreased by approximately 0.95, thereby validating its reliability. This research marks a significant advancement in the indirect estimation of the relationship between static and dynamic soil properties through the application of machine learning techniques.

• Structural Monitoring and Maintenance
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• v.11 no.1
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• pp.41-55
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• 2024

This study aims to determine the characteristics of concrete as identified by Rebound Hammer and Ultrasonic Pulse Velocity (UPV) tests, focusing particularly on their efficacy in estimating compressive strength of concrete material. The study involved three concrete samples designed to achieve a target strength of 29 MPa, comprising normal concrete, instant concrete, and concrete with additives. These were cast into cube specimens measuring 150×150×150 mm. Compressive strength values were determined through both destructive and non-destructive testing on the cubic specimens. As a result, the non-destructive methods yielded varying outcomes for each correlation approach, influenced by the differing constituent materials in the tested concretes. However, normal concrete consistently showed the most reliable correlation, followed by concrete with additives, and lastly, instant concrete. The study found that combining Rebound Hammer and UPV tests enhances the prediction accuracy of compressive strength of concrete. This synergy was quantified through multivariate regression, considering UPV, rebound number, and actual compressive strength. The findings also suggest a more significant influence of the Rebound Hammer measurements on predicting compressive strength for BN and BA, whereas UPV and RN had a similar impact on predicting BI compressive strength.

• Journal of Information Processing Systems
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• v.20 no.4
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• pp.491-500
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• 2024

In hopes of resolving the issue of poor quality of information input for teaching spoken English online, the study creates an English teaching assistance model based on a recognition algorithm named dynamic time warping (DTW) and relies on automated voice recognition technology. In hopes of improving the algorithm's efficiency, the study modifies the speech signal's time-domain properties during the pre-processing stage and enhances the algorithm's performance in terms of computational effort and storage space. Finally, a simulation experiment is employed to evaluate the model application's efficacy. The study's revised DTW model, which achieves recognition rates of above 95% for all phonetic symbols and tops the list for cloudy consonant recognition with rates of 98.5%, 98.8%, and 98.7% throughout the three tests, respectively, is demonstrated by the study's findings. The enhanced model for DTW voice recognition also presents higher efficiency and requires less time for training and testing. The DTW model's KS value, which is the highest among the models analyzed in the KS value analysis, is 0.63. Among the comparative models, the model also presents the lowest curve position for both test functions. This shows that the upgraded DTW model features superior voice recognition capabilities, which could significantly improve online English education and lead to better teaching outcomes.

• International Journal of Internet, Broadcasting and Communication
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• v.16 no.3
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• pp.146-157
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• 2024

Despite numerous air mattresses marketed to prevent Pressure Ulcers (PU), none have fully succeeded due to residual pressure surpassing critical levels. We introduces an innovative medical bed system aiming at complete PU prevention. This system employs a unique 4-bar link mechanism, moving keys up and down to manage body pressure. Each of the 17 keys integrates a sensor controller, reading pressure from 10 sensors. By regulating motor input, we maintain body pressure below critical levels. Keys are equipped with a servo drive and sensor controller, linked to the main controller via two CAN series. Using fuzzy or PI/IP controllers, we adjust keys to minimize total error, dispersing body pressure and ensuring comfort. In case of controller failure, keys alternate swiftly, preventing ulcer development. Through experimental tests under varied conditions, the fuzzy controller with tailored membership functions demonstrated swift performance. PI control showed rapid convergence, while IP control exhibited slower convergence and oscillations near zero error. Our specialized medical robot bed, incorporating 4-bar links and pressure sensors, underwent testing with three controllers-fuzzy, PI, and IP-showcasing their effectiveness in keeping body pressure below critical ulcer levels. Experimental results validate the proposed approach's efficacy, indicating potential for complete PU prevention.

• Mass Spectrometry Letters
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• v.15 no.3
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• pp.158-165
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• 2024

Pneumonia is an acute respiratory infection that primarily affects the lungs and is caused by various microorganisms, including viruses, fungi, and bacteria. Klebsiella pneumoniae, a multidrug-resistant (MDR) and extensively drug-resistant (XDR) bacterium, is a leading cause of widespread pneumonia. This study aimed to identify endophytic bacteria from the leaves of Acalypha indica L. and evaluate their antibacterial properties through both in vitro and in silico approaches. The objectives included isolating endophytic bacteria from Acalypha indica L., testing their antibacterial activity against Klebsiella pneumoniae, identifying the selected bacterial isolates using molecular techniques, analyzing their secondary metabolites via gas chromatography-mass spectrometry (GC-MS), and performing in silico molecular docking studies. The study identified BE 4, an endophytic bacterial isolate of Bacillus pumilus, as exhibiting the most potent antibacterial activity against Klebsiella pneumoniae. GC-MS analysis of the ethyl acetate extract of this isolate revealed 1,2-benzenedicarboxylic acid, bis(2-methylpropyl) ester as the primary metabolite component. Furthermore, molecular docking analysis identified two natural compound ligands, 1,2-benzenedicarboxylic acid, diethyl ester (-6.5 kcal/mol), and lilial (-6.2 kcal/mol), as having potential efficacy against drugresistant bacteria responsible for pneumonia. These findings suggest that endophytic bacteria and their bioactive compounds could serve as promising candidates for the development of new treatments against drug-resistant pneumonia.

• Child Health Nursing Research
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• v.19 no.2
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• pp.85-93
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• 2013

Purpose: The study purposes were to describe the process of developing the Korean versions of the Six Dimension Scale of Nursing Performance (Six-D) and Student Nurse Stress Index (SNSI) and psychometric evaluation of the two measurements. Methods: This was a methodology study using a descriptive cross-sectional design with 51 nursing students in 4th year of university. Internal consistency reliability was assessed using Cronbach alphas. Construct validity was determined by exploring correlations among Six-D, SNSI, objective structured clinical examination (OSCE), self-efficacy and grade point average (GPA). Results: Internal consistency reliability of Six-D and SNSI was acceptable with Cronbach's ${\alpha}$ of .95 and .82. Correlation analysis to determine construct validity revealed that Six-D presented positive correlations with OSCE (r=.109~.272) and self-efficacy (r=.005~.161) and negative correlation with GPA (r=-.246~-.394), although all were not statistically significant. SNSI presented all negative correlations with OSCE (r= -.007~-.238), self-efficacy (r=-.246~-.394), and GPA (r=-.092~-.426) and were mostly statistically significant except OSCE. Conclusion: Six-D needs more evidence to confirm validity to predict observed clinical competency and theoretical relationships with self-efficacy and GPA. However, SNSI presented trends of expected relationships with relevant variables. Therefore, further research is recommended in testing validity of Six-D with other student populations.