• Proceedings of the Korea Institute of Fire Science and Engineering Conference
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• 2010.04a
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• pp.75-78
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• 2010

고발포 소화약제의 발포력은 화재시 포소화약제의 성능을 검증하는데에 중요한 요소이다. 이러한 발포력 검증은 한국소방산업기술원의 "포소화약제의 형식승인 및 검정기술기준(KOFEIS 0103)"에서 제시하고 있는 표준발포기를 이용한 측정법을 통해 검증한다. 본 연구에서는 기존 방법의 제작 비용 및 측정의 번거로움을 보완하기 위한 약제 개발단계에서의 포소화약제 발포력 검증을 위한 실험실적인 측정법을 고안하여 적용성을 분석한다. 측정은 1000ml 시험관내에 3%의 수용액 $100m{\ell}$를 첨가하여 수용액 내부에 정량펌프를 통해 일정한 기포량 및 기포크기로 분사하여 발포시켰으며, 기포의 노즐은 거품의 정확도를 향상시키기 위해 마이크로 피펫팁 $0.2m{\ell}$ 용량을 사용하여 적용성을 분석하였다.

• Elastomers and Composites
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• v.30 no.2
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• pp.105-111
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• 1995

The thermal decomposition of the paper sludge with poly (acrylonitrile-butadiene-styrene) was using a thermal analysis techniques in the stream of nitrogen gas of 30ml/min at various heating rates from 4 to $20^{\circ}C/min$. The mathmatical, derivative and integral method were used to obtain values of activation energy of decomposition reaction. 1. The values of activation energy evaluated by derivative and Intergral method were consistent with each other very well. 2. The maximum value of heat of decomposition evaluated by DSC method was 10.120cal/g at weight ratio of paper sludge/ABS=20/80. 3. The thermogravimetric trace curve agreed with the theoretical equation.

• Proceedings of the Computational Structural Engineering Institute Conference
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• 1999.10a
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• pp.333-342
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• 1999

An improved optimization algorithm for multi-objective and multi-level (MO/ML) optimum design of steel frames is proposed in this paper. In order to optimize the steel frames under seismic load, two main objective functions need to be considered for minimizing the structural weight and maximizing the strain energy. For the efficiency of the proposed method, well known multi-level optimization techniques using decomposition method that separately utilizes both system-level and element-level optimizations and an artificial constraint deletion technique are incorporated in the algorithm. And also dynamic analysis is executed to evaluate the implicit function of structural strain energy at each iteration step. To save the numerical efforts, an efficient reanalysis technique through sensitivity analysis of dynamic properties is unposed in the paper. The efficiency and robustness of the improved MOML algorithm, compared with a plain MOML algorithm, is successfully demonstrated in the numerical examples.

• Journal of Microbiology and Biotechnology
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• v.18 no.5
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• pp.885-888
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• 2008

In this work, we demonstrate that glycolytic intermediates can serve as efficient energy sources to regenerate ATP during continuous-exchange cell-free (CECF) protein synthesis reactions. Through the use of an optimal energy source, approximately 10 mg/ml of protein was generated from a CECF protein synthesis reaction at greatly reduced reagent costs. Compared with the conventional reactions utilizing phosphoenol pyruvate as an energy source, the described method yields 10-fold higher productivity per unit reagent cost, making the techniques of CECF protein synthesis a more realistic alternative for rapid protein production.

• International journal of advanced smart convergence
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• v.8 no.3
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• pp.61-68
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• 2019

Spatial modulation (SM) is the first proposed space modulation technique. By further utilizing the quadrature spatial dimension, quadrature spatial modulation (QSM) has been developed as an amendment to SM system to enhance the overall spectral efficiency. Both techniques are capable of entirely eliminating interchannel interference (ICI) at the receiver. In this paper, we propose a simple adaptive hybrid switching transmission scheme to obtain better system performance than SM and QSM systems under a fixed transmission date rate. The presented modulator selection criterion for switching between spatial modulator and quadrature spatial modulator is based on the larger received minimum distance of spatial modulator and quadrature spatial modulator to exploit the spatial channel freedom. It is shown through Monte Carlo simulations that the proposed hybrid SM and QSM switching system yields lower error performance than the conventional SM and QSM systems under the same fixed data rate and thus can provide signal to noise ratio (SNR) gain.

• Electronics and Telecommunications Trends
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• v.34 no.4
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• pp.32-42
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• 2019

The performance of machine learning algorithms significantly depends on how a configuration of hyperparameters is identified and how a neural network architecture is designed. However, this requires expert knowledge of relevant task domains and a prohibitive computation time. To optimize these two processes using minimal effort, many studies have investigated automated machine learning in recent years. This paper reviews the conventional random, grid, and Bayesian methods for hyperparameter optimization (HPO) and addresses its recent approaches, which speeds up the identification of the best set of hyperparameters. We further investigate existing neural architecture search (NAS) techniques based on evolutionary algorithms, reinforcement learning, and gradient derivatives and analyze their theoretical characteristics and performance results. Moreover, future research directions and challenges in HPO and NAS are described.

• Medical Lasers
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• v.10 no.4
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• pp.201-206
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• 2021

The recent development of new surgical techniques using lasers has increased the opportunities for open surgery involving minimal manipulation and faster and more accurate removal of lesions. The increasing use of laser technology requires nurses to play an extensive role. As assistants, nurses play an important role in maintaining the efficacy and safety of the laser device. In addition, they are also responsible for providing pre-and post-operative care to patients. Therefore, nurses should be aware of how to proceed with operative laser treatment for all surgical procedures and the steps for maintaining safety prior to, during, and after laser treatment. This review provides in-depth knowledge for nurses undertaking continuing education on lasers and patient care in the field of gynecology.

• Proceedings of the Korean Society of Developmental Biology Conference
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• 2003.10a
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• pp.136-136
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• 2003

Mainly due to deficiencies in nuclear reprogramming, gene expression and DNA fragmentation, which result in early and late embryonic losses, the overall success rate achieved by cloning techniques to date is low. This present study compared the incidences of DNA fragmentation during development of IVF, parthenotes (PT), nuclear transfer (NT) and transgenic (TG) embryos. Terminal deoxynucleotidyl transferase (TdT) nick-end labelling (TUNEL) with propidium iodide counter staining was used for determination of DNA fragmentation and total number, respectively. TG and NT donor cells were fetal fibroblasts with or without transfection with EGFP, and cultured in DMEM+15% FCS until confluent, for 5 days. At 19 h post-maturation (hpm), enucleated oocytes were reconstructed with donor cells and activated at 24 hpm with the combinations of ionomycin (5 M, 5 min) and cyclo-heximide (10 g/ml, 5 h) after electric fusion by a single DC pulse (1.6 KV/cm, 60 sec). Parthenotes were produced by the same activation protocol at 24 hpm. (중략)

• International Journal of Computer Science & Network Security
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• v.23 no.6
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• pp.140-146
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• 2023

A detailed survey, applications and challenges of video encoding-decoding systems is discussed in this paper. A novel architecture has also been set aside for future work in the same direction. The literature reviews span the years 1960 to the present, highlighting the benchmark methods proposed by notable academics in the field of video compression. The timeline used to illustrate the review is divided into three sections. Classical methods, conventional heuristic methods, and current deep learning algorithms are all used for video compression in these categories. The milestone contributions are discussed for each category. The methods are summarized in various tables, along with their benefits and drawbacks. The summary also includes some comments regarding specific approaches. Existing studies' shortcomings are thoroughly described, allowing potential researchers to plot a course for future research. Finally, a closing note is made, as well as future work in the same direction.

• Annual Conference of KIPS
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• 2021.11a
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• pp.297-299
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• 2021

Text classification is one of the popular tasks in Natural Language Processing (NLP) used to classify text or document applications such as sentiment analysis and email filtering. Nowadays, state-of-the-art (SOTA) Machine Learning (ML) and Deep Learning (DL) algorithms are the core engine used to perform these classification tasks with high accuracy, and they show satisfying results. This paper conducts a benchmarking performance's analysis of multiple SOTA algorithms on the first known labeled Korean voice phishing dataset called KorCCVi. Experimental results reveal performed on a test set of 366 samples reveal which algorithm performs the best considering the training time and metrics such as accuracy and F1 score.