• Journal of the Semiconductor & Display Technology
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• v.14 no.4
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• pp.8-12
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• 2015

As NMP (N-Methyl-2pyrrolidone) is becoming important in many fields, the demand for it is also rising rapidly. With its chemical property of high boiling point, low vapor pressure and high water solubility, it is easy to recover it after processing. Therefore, it is increasingly needed to develop a system that effectively recovers NMP solvent. The study produced a system modeling using AMESim software before developing high purity solvent recovery (HPSR) system to recover NMP solvent. Then, it verified reliability by comparing the simulation model with the test result.

• Proceedings of the Korean Institute of IIIuminating and Electrical Installation Engineers Conference
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• 2004.05a
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• pp.335-340
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• 2004

To analyze risk factors of temporary power installations, the investigation was carried out for power receiving system and pack and panel boards at construction sites. The subject was variable such as an airport, an apartment, a municipal playground. There are many risk factors caused by inadequate working environments and the deterioration of temporary power installations using equipment with minimum safety devices at construction sites. There, it is intended to present problems and preventive measures against electrical shock accidents, through analyzing risk factors of real field condition and investigating temporary power installations all over the country.

• Proceedings of the KIEE Conference
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• 2003.07b
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• pp.1392-1394
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• 2003

This paper presents the actual test data of 3 phase, 9 pole, 3.6 [kw] synchronized wind-power generator controlled by hinged vane system and the possibilities of the small mount wind-power generations at the south-east coast of Ul-san. It also shows the data of the wind-velocity acquired by wind-direction sensor, calculation and analysis of the estimated electrical generation power, energy storage systems, and the efficient usages of the wind-power system.

• The Transactions of the Korean Institute of Power Electronics
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• v.24 no.1
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• pp.16-24
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• 2019

The performance of the battery management system (BMS) algorithm is important for ensuring the stability and efficient operation of battery packs. Such a performance is determined by the internal parameters of the electrical equivalent circuit model (EECM). This study proposes a performance improvement and verification of battery parameters for the BMS algorithm using electrical experiments and tools. The parameters were extracted through electrical characteristic experiments, and an EECM based on Ah counting was designed. Simulation results using the EECM were compared with actual experimental data to determine the best parameter extraction method.

• The Transactions of the Korean Institute of Power Electronics
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• v.27 no.3
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• pp.265-274
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• 2022

This paper proposes a machine learning-based screening algorithm to build the retired battery pack of the energy storage system. The proposed algorithm creates the dataset of various performance parameters of the retired battery, and this dataset is preprocessed through a principal component analysis to reduce the overfitting problem. The retried batteries with a large deviation are excluded in the dataset through a density-based spatial clustering of applications with noise, and the K-means clustering method is formulated to select the group of the retired batteries to satisfy the deviation requirement conditions. The performance of the proposed algorithm is verified based on NASA and Oxford datasets.

• International Journal of Advanced Culture Technology
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• v.11 no.1
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• pp.165-170
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• 2023

This study focuses on the development of intelligent combat robot systems for future warfare. The research is structured as follows: First, the introduction presents the rationale for researching intelligent combat robots and their potential to become game changers in future warfare. Second, in the context of the intelligent robot paradigm, this study proposes the need for military organizations to innovate their combat concepts and weapon systems through the effective utilization of Artificial Intelligence, Cognitive, Biometric, and Mechanical technologies. This forms the theoretical background of the study. Third, the analysis of intelligent robot systems considers five examples: humanoid robots, jumping robots, wheeled and quadrupedal pack robots, and tank robots. Finally, the discussion and conclusion propose that intelligent combat robots should be selected as game changers in military organizations for future warfare, and suggest further research in this area.

• Proceedings of the Korean Institute of Building Construction Conference
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• 2021.05a
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• pp.10-11
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• 2021

As concrete is used in many construction works, the use of aggregates is increasing. However, supply and demand of high-quality aggregates has become difficult recently, and although circular aggregates that recycle construction waste are used, the performance of concrete, such as liquidity and strength, are being reduced due to defective aggregates. As a result, quality tests such as sieve analysis test are conducted, but a lot of waste occurs such as time and manpower. To solve this problem, this study was conducted to measure the assembly rate of fine aggregate, which accounts for about 35% of the concrete volume, using Deep Learning.

• Proceedings of the Korean Institute of Building Construction Conference
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• 2021.11a
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• pp.50-51
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• 2021

Recently, as concrete is used in many construction works in Korea, the use of aggregates is also increasing. However, the depletion of aggregate resources is making it difficult to supply and demand high-quality aggregates, and the use of defective aggregates is causing problems such as poor performance such as the liquidity and strength of concrete pouring out in the field. As a result, quality tests such as sieve analysis test is conducted on their own, but this study was conducted to improve time and manpower by using the CNN-based Deep Learning Model for the fineness modulus.

• Proceedings of the KIPE Conference
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• 2020.08a
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• pp.215-217
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• 2020

본 논문은 배터리 팩 내부 셀 파라미터의 불균일도에 대한 분석을 실시하고 이를 기반으로 과방전을 사전에 진단할 수 있는 방법을 제안한다. 이를 위해서 배터리 팩 내부 셀간 편차가 발생하는 셀을 선정하여 두 셀간 특성 분석을 실시하였으며, 이를 기준으로 예측 모델을 구성하였다. 예측 성능을 통해 배터리 전압 예측 성능에 영향을 미치는 인자를 분석하였으며, 배터리 전기적 등가회로 모델을 기반으로 예측 모델을 제안한다. 예측 모델은 실제 과방전이 발생한 셀을 기준으로 실험데이터와 비교하여 예측 성능을 검증하였다.

• Korean Journal of Head & Neck Oncology
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• v.17 no.2
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• pp.131-138
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• 2001

Objectives: Alcohol intake has been reported to be a risk factor of laryngeal cancer. Since the aldehyde dehydrogenase 2 (ALDH2) genotype is a major determinant of personal alcohol drinking habit, there is a possibility that ALDH2 genotype would be a risk factor for laryngeal cancer. N-Acetyltransferase 2 (NAT2) is a detoxifying enzyme and its polymorphism has been reported to be related to the risk of many environmental cancers. However, studies on the associations between these two genotypes and laryngeal cancer risk are scarce. We have assessed the effects of alcohol intake and the genotype of ALDH2 and NAT2 on the risk of laryngeal cancer in Koreans. Materials and Methods: Eighty-four pathologically proven laryngeal cancer patients and 168 age matched controls were included as the study subjects. Information about alcohol intake and smoking habit was collected using a self administered questionnaire. ALDH2 and NAT2 genotypes were analyzed using PCR-RFLP methods. Results: Alcohol intake was significant as a risk factor for laryngeal cancer (OR : 2.58, 95% CI : 1.24, 5.36), especially for supraglottic laryngeal cancer (OR : 3.24, 95% CI : 1.02, 10.31). Personal drinking habit was closely related with personal smoking habit, which was a potent risk factor of laryngeal cancer. In a stratified analysis according to the level of cumulative smoking amount, drinking was significant neither in light smokers (equal or less than 30 pack-years) nor in heavy smoker (over 30 pack-years). The ALDH2 genotype was significantly associated with the risk of laryngeal cancer in a univariate analysis. The statistical significance, however, disappeared after adjusting alcohol intake using a multiple conditional logistic model. The NAT2 genotype was not significant as a risk factor for laryngeal cancer. Conclusion: Alcohol drinking and ALDH2 genotype would have indirect effects on laryngeal cancer by their correlations with cigarette smoking or with alcohol drinking. It is less likely that the NAT2 genotype would be a potent risk factor of laryngeal cancer.