• The Journal of the Acoustical Society of Korea
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• v.43 no.4
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• pp.400-405
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• 2024

When cavitation noise occurs in ship propellers, the level of underwater radiated noise abruptly increases, which can be a critical threat factor as it increases the probability of detection, particularly in the case of naval vessels. Therefore, accurately and promptly assessing cavitation signals is crucial for improving the survivability of submarines. Traditionally, techniques for determining cavitation occurrence have mainly relied on assessing acoustic/vibration levels measured by sensors above a certain threshold, or using the Detection of Envelop Modulation On Noise (DEMON) method. However, technologies related to this rely on a physical understanding of cavitation phenomena and subjective criteria based on user experience, involving multiple procedures, thus necessitating the development of techniques for early automatic recognition of cavitation signals. In this paper, we propose an algorithm that automatically detects cavitation occurrence based on simple statistical features reflecting cavitation characteristics extracted from acoustic signals measured by sensors attached to the hull. The performance of the proposed technique is evaluated depending on the number of sensors and model test conditions. It was confirmed that by sufficiently training the characteristics of cavitation reflected in signals measured by a single sensor, the occurrence of cavitation signals can be determined.

• Journal of The Korean Institute of Defense Technology
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• v.5 no.3
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• pp.8-17
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• 2023

The current weapon system is operated as a complex weapon system with various standards and protocols applied, so there is a risk of failure in smooth information exchange during combined and joint operations on the battlefield. The interoperability of weapon systems to carry out precise strikes on key targets through rapid situational judgment between weapon systems is a key element in the conduct of war. Since the Korean military went into service, there has been a need to change the configuration and improve performance of a large number of software and hardware, but there is no verification system for the impact on interoperability, and there are no related test tools and facilities. In addition, during combined and joint training, errors frequently occur during use after arbitrarily changing the detailed operation method and software of the weapon/power support system. Therefore, periodic verification of interoperability between weapon systems is necessary. To solve this problem, rather than having people schedule an evaluation period and conduct the evaluation once, AI should continuously evaluate the interoperability between weapons and power support systems 24 hours a day to advance warfighting capabilities. To solve these problems, To this end, preliminary research was conducted to improve defense interoperability capabilities by applying natural language processing techniques (①Word2Vec model, ②FastText model, ③Swivel model) (using published algorithms and source code). Based on the results of this experiment, we would like to present a methodology (automated evaluation of interoperability requirements evaluation / level measurement through natural language processing model) to implement an automated defense interoperability evaluation tool without relying on humans.

• Journal of Korean Elementary Science Education
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• v.43 no.3
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• pp.402-414
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• 2024

The purpose of this study is to explore the experiences of Science Chief Teachers in schools, focusing on the specific activities in which they engage during the school year as a part of the science curriculum in the school. To do so, five research participants were selected who were in charge of the activities of the Science Chief Teacher in elementary schools. After the interviews, their activities and roles were categorized into "planning and implementation" and "management and supplementation." In addition, the research participants were asked to bring documents they had drafted and provide information about accomplishments related to science contests, lists of materials and equipment used in science labs, and other materials to be used as reference data for the research. As prompted by the research, the category of "planning and implementation," which represented the activities conducted by the Science Chief Teachers, was further classified into "operation of the intramural events for the Month of Science at the beginning of the school year," "participation in contests sponsored by the Office of Education in accordance with the results of the intramural events," " the operation of the science club in school," and "preparation for the end of the year evaluation of the science education performance." As for the category of "management and supplementation," it was further classified into "constant management and improvement of the science lab," "maintenance of the relationship with the public service officials present at science lab," and "management of other matters related to the science education." Through this study, it was possible to look into the activities of the Science Chief Teachers who supported the smooth progress of science education in schools. This study will provide implications for improving the work efficiency of the Chief Science Teachers and indicate the difficulties expected in the future.

• Journal of Internet Computing and Services
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• v.25 no.3
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• pp.43-54
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• 2024

This study employs text mining techniques to compare user responses across various Over-The-Top (OTT) service platforms. The primary objective of the research is to understand user satisfaction with OTT service platforms and contribute to the formulation of more effective review strategies. The key questions addressed in this study involve identifying prominent topics and keywords in user reviews of different OTT services and comprehending platform-specific user reactions. TF-IDF is utilized to extract significant words from positive and negative reviews, while BERTopic, an advanced topic modeling technique, is employed for a more nuanced and comprehensive analysis of intricate user reviews. The results from TF-IDF analysis reveal that positive app reviews exhibit a high frequency of content-related words, whereas negative reviews display a high frequency of words associated with potential issues during app usage. Through the utilization of BERTopic, we were able to extract keywords related to content diversity, app performance components, payment, and compatibility, by associating them with content attributes. This enabled us to verify that the distinguishing attributes of the platforms vary among themselves. The findings of this study offer significant insights into user behavior and preferences, which OTT service providers can leverage to improve user experience and satisfaction. We also anticipate that researchers exploring deep learning models will find our study results valuable for conducting analyses on user review text data.

• Journal of Platform Technology
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• v.12 no.3
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• pp.41-54
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• 2024

Recently, support for various types of entrepreneurship has been increasing. At the same time, interest in entrepreneurship education is increasing to expand support for entrepreneurship and improve entrepreneurship performance. Therefore, the scope and interest of entrepreneurship education and support is expanding beyond college students and the general public to include high school students. Accordingly, this study seeks to investigate in more depth the relationship between entrepreneurship competency, entrepreneurship attitude, and intention to start a business in order to increase the intention to start a business. As a result of the analysis, entrepreneurship capabilities (creativity, risk-taking, and innovation) had a positive effect on attitude toward entrepreneurship, and attitude toward entrepreneurship had a positive effect on the will to start a business. In addition, the results of the analysis of the mediating effect of entrepreneurship attitude in the relationship between entrepreneurship capabilities (creativity, risk-taking, and innovation) and entrepreneurship will are as follows. First, in the relationship between creativity and entrepreneurial will, entrepreneurial attitude played a partial mediating role. Additionally, in the relationship between risk tolerance and entrepreneurial intention, entrepreneurial attitude played a partial mediating role. Lastly, in the relationship between innovation and entrepreneurial will, entrepreneurial attitude played a complete mediating role. The research conclusion summarizes the results of this study, suggests implications for entrepreneurs and start-ups, as well as limitations of this study and directions for future research..

• The Journal of Bigdata
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• v.8 no.2
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• pp.165-175
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• 2023

LNG is a representative imported cargo at Incheon Port and has a relatively high contribution to the increase/decrease in overall cargo volume at Incheon Port. In addition, in the view point of nationwide, LNG is the one of the most important key resource to supply the gas and generate electricity. Thus, it is very essential to identify the factors that have impact on the demand fluctuation and build the appropriate forecasting model, which present the basic information to make balance between supply and demand of LNG and establish the plan for power generation. In this study, different to previous research based on macroscopic annual data, the weekly demand of LNG is converted from the cargo volume unloaded by LNG carriers. We have identified the periodicity and correlations among internal and external factors of demand variability. We have identified the input factors for predicting the LNG demand such as seasonality of weekly cargo volume, the peak power demand, and the reserved capacity of power supply. In addition, in order to predict LNG demand, considering the characteristics of the data, time series prediction with weekly LNG cargo volume as a dependent variable and prediction through an artificial neural network model were made, the suitability of the predictions was verified, and the optimal model was established through error comparison between performance and estimates.

• Applied Chemistry for Engineering
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• v.35 no.4
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• pp.309-315
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• 2024

Silicon and carbon composite (SiC) is considered one of the most promising anode materials for the commercialization of Si-based anodes, as it could simultaneously satisfy the high theoretical capacity of Si and the high electronic conductivity of carbon. However, SiC active material undergoes repeated volumetric changes during charge/discharge processes, leading to continuous electrolyte decomposition and capacity fading, which is still considered an issue that needs to be addressed. To solve this issue, we suggest a 4,4'-Methylenebis(cyclohexyl isocyanate) (H₁₂MDI)-based waterborne polyurethane binder (HPUD), which forms a 3D network structure through thermal cross-linking reaction. The cross-linked HPUD (denoted as CHPU) was prepared using an epoxy ring-opening reaction of the cross-linker, triglycidyl isocyanurate (TGIC), via simple thermal treatment during the SiC anode drying process. The SiC anode with the CHPU binder, which exhibited superior mechanical and adhesion properties, not only demonstrated excellent rate and cycling performance but also alleviated the volume expansion of the SiC anode. This work implies that eco-friendly binders with cross-linked structures could be utilized for various Si-based anodes.

• Korean Chemical Engineering Research
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• v.62 no.3
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• pp.233-237
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• 2024

This study is about the fabrication of a flexible electrode based on PAN-based carbon fibers tow using organic/inorganic nanocomposite and its application of non-enzymatic sensor. The organic/inorganic nanocomposite was composed of the conductive polymer polyaniline (PANI) and the metal oxide CuO. And glucose was used as the target of the electrochemical sensor. Commercialized CFTs were pretreated through heat treatment for desizing and electrochemical oxidation for activation. This nanocomposite was sequentially synthesized on the pretreated CFT surface using electrochemical polymerization and electrochemical deposition. Finally, the CFT/PANI/CuO NPs electrode was obtained. The electrochemical properties and sensing performance of the CFT/PANI/CuO NPs electrode were analyzed using chronoamperometry (CA), cyclic voltammetry (CV), and electrochemical impedance spectroscopy (EIS). The sensitivity of the CFT/PANI/CuO NPs electrode was about 8.352 mA/mM (in a linear range of 0.445~6.674 mM) and 3.369 mA/mM (in a linear range of 6.674~50 mM), respectively. So, the CFT/PANI/CuO NPs electrode exhibited the enhanced sensing performances due to unique properties such as small peak potential separation, low electron transfer resistance, and large specific surface area.

• Journal of Korea Water Resources Association
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• v.57 no.7
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• pp.461-470
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• 2024

This study aimed to predict total phosphorus (T-P) to address early eutrophication caused by nutrient influx from various human activities. Traditional T-P monitoring systems are labor-intensive and time-consuming, leading to a global trend of using direct reading sensors. Therefore, this study utilized water quality parameters obtained from direct reading sensors in a two-stage T-P prediction process. The importance of turbidity (Tur) in T-P prediction was examined, and an analysis was conducted to determine if T-P prediction is possible using only direct reading sensor parameters by adding automatic water quality analyzer parameters. The study found that T-P concentrations were higher in the mid-lower reaches of the Nakdong River basin compared to the upper reaches. Pearson correlation analysis identified water quality parameters highly correlated with T-P at each site, which were then used in multiple linear regression analysis to predict T-P. The analysis was conducted with and without the inclusion of Tur, and the performance of models incorporating automatic water quality analyzer parameters was compared with those using only direct reading sensor parameters. The results confirmed the significance of Tur in T-P prediction, suggesting that it can be used as a foundational element in the development of measures to prevent eutrophication.

• Dementia and Neurocognitive Disorders
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• v.21 no.4
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• pp.147-161
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• 2022

Background and Purpose: Subjective cognitive decline (SCD) refers to the self-perception of cognitive decline with normal performance on objective neuropsychological tests. SCD, which is the first help-seeking stage and the last stage before the clinical disease stage, can be considered to be the most appropriate time for prevention and treatment. This study aimed to compare characteristics between the amyloid positive and amyloid negative groups of SCD patients. Methods: A cohort study to identify predictors for the clinical progression to mild cognitive impairment (MCI) or dementia from subjective cognitive decline (CoSCo) study is a multicenter, prospective observational study conducted in the Republic of Korea. In total, 120 people aged 60 years or above who presented with a complaint of persistent cognitive decline were selected, and various risk factors were measured among these participants. Continuous variables were analyzed using the Wilcoxon rank-sum test, and categorical variables were analyzed using the χ² test or Fisher's exact test. Logistic regression models were used to assess the predictors of amyloid positivity. Results: The multivariate logistic regression model indicated that amyloid positivity on PET was related to a lack of hypertension, atrophy of the left temporal lateral and entorhinal cortex, low body mass index, low waist circumference, less body and visceral fat, fast gait speed, and the presence of the apolipoprotein E ε4 allele in amnestic SCD patients. Conclusions: The CoSCo study is still in progress, and the authors aim to identify the risk factors that are related to the progression of MCI or dementia in amnestic SCD patients through a two-year follow-up longitudinal study.