• Journal of the Korean Society of Safety
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• v.39 no.2
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• pp.38-43
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• 2024

Recently, with the expanding market for electronic devices and electric vehicles, secondary battery usage has been on the rise. Lithium-ion batteries are particularly popular due to their fast charging times and lightweight nature compared to other types of batteries. A secondary battery consists of four components: anode, cathode, electrolyte, and separator. Generally, the positive and negative electrode materials of secondary batteries are composed of an active material, a binder, and a conductive material. Acetylene Black (AB) is utilized to enhance conductivity between active material particles or metal dust collectors, preventing the binder from acting as an insulator. However, when recycling waste batteries that have been subject to high usage, there is a risk of fire and explosion accidents, as accurately identifying the characteristics of Acetylene Black dust proves to be challenging. In this study, the lower explosion limit for Acetylene Black dust with an average particle size of 0.042 ㎛ was determined to be 153.64 mg/L using a Hartmann-type dust explosion device. Notably, the dust did not explode at values below 168 mg, rendering the lower explosion limit calculation unfeasible. Analysis of explosion delay times with varying electrode gaps revealed the shortest delay time at 3 mm, with a noticeable increase in delay times for gaps of 4 mm or greater. The findings offer fundamental data for fire and explosion prevention measures in Acetylene Black waste recycling processes via a predictive model for lower explosion limits and ignition delay time.

• Journal of Wind Energy
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• v.14 no.4
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• pp.50-56
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• 2023

With the abnormal weather phenomena caused by global warming, the frequency and intensity of lightning strikes are increasing, and lightning accidents are becoming one of the biggest causes of failures and accidents in offshore wind turbines. In order to secure generator operation reliability, effective and practical measures are needed to reduce lightning damage. Because offshore wind turbines are tall structures installed at sea, the possibility of direct lightning strikes is very high compared to other structures, and the role of surge protection devices to minimize damage to the electrical and electronic circuits inside the wind turbine is very important. In this study, a varistor, which is a key element for a class 1 surge protection device for direct lightning protection, was developed. The current density was improved by changing the varistor composition, and the distance between the electrode located on the varistor surface and the edge of the varistor was optimized through a simulation program to improve the fabrication process. Considering the combined effects of heat distribution, electric field distribution, and current density on the optimized varistor surface, silver electrodes were formed with a gap of 0.5 mm. The varistor developed in this study was confirmed to have an energy tolerance of 10/350 ㎲, 50kA, which is a representative direct lightning current waveform, and good protection characteristics with a limiting voltage of 2 kV or less.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.24 no.2
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• pp.127-132
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• 2024

Recently, secondary batteries, commonly known as rechargeable batteries, find widespread applications across various industries. Particularly valued for their compact and lightweight characteristics, they play a crucial role in diverse portable electronic devices such as smartphones, laptops, and tablets, offering high energy density and efficient charge-discharge capabilities. Moreover, they serve as vital components in electric vehicles and contribute significantly to the field of renewable energy as part of Energy Storage Systems(ESS). However, despite advancements in this technology, issues such as reduced lifespan, cracking, damage, and even the risk of fire can arise due to excessive charging and discharging of secondary batteries. To address these challenges, Battery Management System(BMS) are employed to protect against overcharging and improve overall performance. Nevertheless, understanding the protective range settings of BMS using lithium-ion batteries, the most commonly used secondary batteries, and lead-acid batteries can be challenging. Therefore, this paper aims to utilize a battery charge-discharge tester and simulator to investigate the charging and discharging characteristics of lithium-ion batteries and lead-acid batteries, addressing the associated challenges of reduced lifespan, cracking, damage, and fire hazards in secondary batteries.

• International Journal of Heart Failure
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• v.6 no.1
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• pp.11-19
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• 2024

The prevalence of heart failure (HF) is increasing, necessitating accurate diagnosis and tailored treatment. The accumulation of clinical information from patients with HF generates big data, which poses challenges for traditional analytical methods. To address this, big data approaches and artificial intelligence (AI) have been developed that can effectively predict future observations and outcomes, enabling precise diagnoses and personalized treatments of patients with HF. Machine learning (ML) is a subfield of AI that allows computers to analyze data, find patterns, and make predictions without explicit instructions. ML can be supervised, unsupervised, or semi-supervised. Deep learning is a branch of ML that uses artificial neural networks with multiple layers to find complex patterns. These AI technologies have shown significant potential in various aspects of HF research, including diagnosis, outcome prediction, classification of HF phenotypes, and optimization of treatment strategies. In addition, integrating multiple data sources, such as electrocardiography, electronic health records, and imaging data, can enhance the diagnostic accuracy of AI algorithms. Currently, wearable devices and remote monitoring aided by AI enable the earlier detection of HF and improved patient care. This review focuses on the rationale behind utilizing AI in HF and explores its various applications.

• Journal of Cerebrovascular and Endovascular Neurosurgery
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• v.25 no.2
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• pp.175-181
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• 2023

Objective: Endovascular treatment of cerebrovascular diseases is often challenging due to small caliber, tortuous distal vessels. Several devices and techniques have evolved to overcome these challenges. Recently, a low profile dual lumen microballoon catheter, specifically designed for distal navigation is employed for neurovascular procedures. Due to its recent advent, scarce data is available on clinical utility and safety of Scepter Mini. The aim of this case series is to report our initial experience with Scepter Mini in the management of various cerebrovascular diseases. Methods: All interventional neurovascular cases performed using Scepter Mini between January 2020 till April 2021 were included. Data regarding patient demographics, procedural details and complications was retrospectively collected from patient's electronic medical record and procedure reports. Results: Total twelve embolization procedures were performed in eleven patients, including six brain arteriovenous malformation, two dural arteriovenous fistula, one vein of Galen malformation and three hyper-vascular glomus tumor embolizations. All procedures were successfully performed with adequate penetration of the embolic agent. Complete embolization was performed in six procedures, while intended partial embolization was performed in the rest of procedures. Scepter Mini was solely used in ten procedures, however in the other two embolization procedures it was used as an additional conjunct tool to complete the intended embolization. No balloon related complication was observed in any procedure. Conclusions: Scepter Mini dual lumen microballoon catheter is safe and feasible for delivery of liquid embolic agents for cerebrovascular embolization procedures.

• Korean Circulation Journal
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• v.54 no.3
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• pp.140-153
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• 2024

Background and Objectives: Although a single-lead electrocardiogram (ECG) patch may provide advantages for detecting arrhythmias in outpatient settings owing to user convenience, its comparative effectiveness for real-time telemonitoring in inpatient settings remains unclear. We aimed to compare a novel telemonitoring system using a single-lead ECG patch with a conventional telemonitoring system in an inpatient setting. Methods: This was a single-center, prospective cohort study. Patients admitted to the cardiology unit for arrhythmia treatment who required a wireless ECG telemonitoring system were enrolled. A single-lead ECG patch and conventional telemetry were applied simultaneously in hospitalized patients for over 24 hours for real-time telemonitoring. The basic ECG parameters, arrhythmia episodes, and signal loss or noise were compared between the 2 systems. Results: Eighty participants (mean age 62±10 years, 76.3% male) were enrolled. The three most common indications for ECG telemonitoring were atrial fibrillation (66.3%), sick sinus syndrome (12.5%), and atrioventricular block (10.0%). The intra-class correlation coefficients for detecting the number of total beats, atrial and ventricular premature complexes, maximal, average, and minimal heart rates, and pauses were all over 0.9 with p values for reliability <0.001. Compared to a conventional system, a novel system demonstrated significantly lower signal noise (median 0.3% [0.1-1.6%] vs. 2.4% [1.4-3.7%], p<0.001) and fewer episodes of signal loss (median 22 [2-53] vs. 64 [22-112] episodes, p=0.002). Conclusions: The novel telemonitoring system using a single-lead ECG patch offers performance comparable to that of a conventional system while significantly reducing signal loss and noise.

• The Journal of Korean Academic Society of Nursing Education
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• v.30 no.3
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• pp.222-231
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• 2024

Purpose: This study is to explore the antecedent factors of daycare teacher behaviors concerning the eye health of preschool children by applying an extended parallel process model. Methods: Focus group interviews were conducted with ten daycare center teachers on September 4 and 14, 2023. A data analysis was performed according to the content analysis method by clustering the data into the four categories: the two threat factors of severity and susceptibility and the two efficacy factors of self-efficacy and response-efficacy. Results: Daycare center teachers' perception of the severity of eye health problems in preschool children was high in relation to eye trauma, but it was recognized that viewing the electronic devices were of a less severe because symptoms were not noticed in a short period of time. They also showed low susceptibility because they were not sufficiently interested in the eye health hazard behaviors of preschool children. The self-efficacy of daycare center teachers was low because this was a lack of knowledge about symptoms of eye problems. However, they recognized that eye health activities performed in the preschool age could prevent negative eye health outcomes, thus showing a high response efficacy. Conclusion: In the future, it is necessary to increase the sensitivity and engagement of daycare center teachers concerning with the eye health of preschool children and to increase their self-efficacy. It will also be necessary to develop various interventions to improve eye health for preschool children that can be implemented by daycare center teachers.

• Journal of Korea Society of Industrial Information Systems
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• v.29 no.5
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• pp.51-68
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• 2024

To safely operate lithium-ion batteries that power mobile electronic devices, it is crucial to accurately predict the remaining useful life (RUL) of the battery. Recently, with the advancement of machine learning technologies, artificial intelligence (AI)-based RUL prediction models for batteries have been actively researched. However, existing models have limitations as the reasoning process within the models is not transparent, making it difficult to fully trust and utilize the predicted values derived from machine learning. To address this issue, various explainable AI techniques have been proposed, but these techniques typically visualize results in the form of graphs, requiring users to manually analyze the graphs. In this paper, we propose an explainable RUL prediction method for lithium-ion batteries that interprets the reasoning process of the prediction model in textual form using SHAP analysis based on large language models (LLMs). Experimental results using publicly available lithium-ion battery datasets demonstrated that the LLM-based SHAP analysis enabled us to concretely understand the model's prediction rationale in textual form.

• Journal of IKEEE
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• v.28 no.3
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• pp.337-341
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• 2024

As the production process for silicon-based integrated circuits approaches physical limits, a lot of attention is focused on the new semiconductor materials to overcome these problems. Carbon NanoTubes(CNTs) are attracting a lot of interest as one of the most competitive materials with excellent electrical transport and scaling properties, and CNTFETs using CNTs are gaining popularity as next-generation semiconductor devices. However, since the technology to place CNTs in a certain direction and interval on the wafer is not yet mature enough, it is difficult to construct all necessary circuits with CNTFET only. So, there is increasing interest in a hybrid configuration using MOSFET and CNTFET together. Because SRAM plays a role as a cache in microprocessors and is a critical circuit block influencing microprocessor performance, research to implement existing SRAM in a hybrid form is steadily progressing. Therefore, in this paper, we will explain the design method of hybrid 8T SRAM based on the existing hybrid 6T SRAM and discuss the performance difference between the two circuits.

• Journal of dental hygiene science
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• v.24 no.3
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• pp.125-133
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• 2024

Background: The management of dental plaque and the appropriate use of oral hygiene tools are crucial for oral health. With increasing interest in oral health care, various oral hygiene products are available on the market. As the most basic oral hygiene tool, the large-head toothbrush has gained significant consumer interest. This study evaluates the suitability of large-head toothbrushes as oral hygiene tools by comparing their efficacy with that of regular-sized toothbrushes. Methods: We evaluated the efficacy of large-head and regular-sized toothbrushes. The amount of dental plaque before and after brushing was measured using quantitative light-induced fluorescence digital (QLF-D) images and the plaque index (PI) in adult participants with more than 28 teeth (n=15/group). After brushing, the collected toothbrushes were rinsed 10 times in clean water, thoroughly dried, and weighed on an electronic scale. Data were analyzed using the Wilcoxon signed-rank test with SPSS Statistics Version 29.0. Results: QLF-D analysis showed a significant decrease in fluorescence intensity scores after use of a regular-sized toothbrush, whereas the scores after use of a large-head toothbrush were not significantly reduced. PI measurements indicated significant reductions in dental plaque for both head types. However, detailed analysis by tooth surface revealed that the regular-sized toothbrush significantly reduced plaque on the proximal, palatal/lingual, and labial/buccal surfaces. In contrast, the large-head toothbrush only showed significant reductions in place on the proximal and palatal/lingual surfaces, not on the labial/buccal surface. Additionally, compared to the regular-sized toothbrush, the large-head toothbrush retained more toothpaste residue despite similar cleaning efforts after brushing. Conclusion: Compared to the regular-sized toothbrush, the large-head toothbrush showed lower overall efficacy in dental plaque removal. The results of this study provide significant information regarding the use of large-head toothbrushes.