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정민중(Minjoong Jeong) 대한기계학회 2007 대한기계학회 춘추학술대회 Vol.2007 No.10
One of computational methods for protein structure design is a fragment assembly method. There are many barriers, however, in conventional fragment assembly method. Argues on protein energy functions and global optimization to design the structures are in progress for example. In this study, we propose new design algorithms for protein tertiary structures. A new fragment assembly which uses very shot fragments and a global optimization which folds the prototype will be introduced. The goodness of the proposed algorithms are shown through numerical experiments.
Discovery to Human Disease Research: Proteo-Metabolomics Analysis
Minjoong Joo,Jeong-Hun Mok,Van-An Duong,Jong-Moon Park,Hoo Keun Lee 사단법인 한국질량분석학회 2024 Mass spectrometry letters Vol.15 No.2
The advancement of high-throughput omics technologies and systems biology is essential for understanding complex biological mechanisms and diseases. The integration of proteomics and metabolomics provides comprehensive insights into cel- lular functions and disease pathology, driven by developments in mass spectrometry (MS) technologies, including electrospray ionization (ESI). These advancements are crucial for interpreting biological systems effectively. However, integrating these tech- nologies poses challenges. Compared to genomic, proteomics and metabolomics have limitations in throughput, and data inte- gration. This review examines developments in MS equipped electrospray ionization (ESI), and their importance in the effective interpretation of biological mechanisms. The review also discusses developments in sample preparation, such as Simultaneous Metabolite, Protein, Lipid Extraction (SIMPLEX), analytical techniques, and data analysis, highlighting the application of these technologies in the study of cancer or Huntington's disease, underscoring the potential for personalized medicine and diagnostic accuracy. Efforts by the Clinical Proteomic Tumor Analysis Consortium (CPTAC) and integrative data analysis methods such as O2PLS and OnPLS extract statistical similarities between metabolomic and proteomic data. System modeling techniques that mathematically explain and predict system responses are also covered. This practical application also shows significant improvements in cancer research, diagnostic accuracy and therapeutic targeting for diseases like pancreatic ductal adenocarci- noma, non-small cell lung cancer, and Huntington's disease. These approaches enable researchers to develop standardized proto- cols, and interoperable software and databases, expanding multi-omics research application in clinical practice.
Fluorine Plasma Corrosion Resistance of Anodic Oxide Film Depending on Electrolyte Temperature
신재수,Minjoong Kim,Je-beom Song,Nak-gwan Jeong,Jin-tae Kim,윤주영 한국진공학회 2018 Applied Science and Convergence Technology Vol.27 No.1
Samples of anodic oxide film used in semiconductor and display manufacturing processes were prepared at different electrolyte temperatures to investigate the corrosion resistance. The anodic oxide film was grown on aluminum alloy 6061 by using a sulfuric acid (H2SO4) electrolyte of 1.5M at 0oC, 5oC, 10oC, 15oC, and 20oC. The insulating properties of the samples were evaluated by measuring the breakdown voltage, which gradually increased from 0.43 kV (0oC) to 0.52 kV (5oC), 1.02 kV (10oC), and 1.46 kV (15oC) as the electrolyte temperature was increased from 0oC to 15oC, but then decreased to 1.24 kV (20oC). To evaluate the erosion of the film by fluorine plasma, the plasma erosion and the contamination particles were measured. The plasma erosion was evaluated by measuring the breakdown voltage after exposing the film to CF4/O2/Ar and NF3/O2/Ar plasmas. With exposure to CF4/O2/Ar plasma, the breakdown voltage of the film slightly decreased at 0oC, by 0.41 kV; however, the breakdown voltage significantly decreased at 20oC, by 0.83 kV. With exposure to NF3/O2/Ar plasma, the breakdown voltage of the film slightly decreased at 0oC, by 0.38 kV; however, the breakdown voltage significantly decreased at 20oC, by 0. 77 kV. In addition, for the entire temperature range, the breakdown voltage decreased more when sample was exposed to NF3/O2/Ar plasma than to CF4/O2/Ar plasma. The decrease of the breakdown voltage was lower in the anodic oxide film samples that were grown slowly at lower temperatures. The rate of breakdown voltage decrease after exposure to fluorine plasma was highest at 20oC, indicating that the anodic oxide film was most vulnerable to erosion by fluorine plasma at that temperature. Contamination particles generated by exposure to the CF4/O2/Ar and NF3/O2/Ar plasmas were measured on a real-time basis. The number of contamination particles generated after the exposure to the respective plasmas was lower at 5oC and higher at 0oC. In particular, for the entire temperature range, about five times more contamination particles were generated with exposure to NF3/O2/Ar plasma than for exposure to CF4/O2/Ar plasma. Observation of the surface of the anodic oxide film showed that the pore size and density of the non-treated film sample increased with the increase of the temperature. The change of the surface after exposure to fluorine plasma was greatest at 0oC. The generation of contamination particles by fluorine plasma exposure for the anodic oxide film prepared in the present study was different from that of previous aluminum anodic oxide films.
Park, Gyu-Byung,Jeong, Minjoong,Choi, Dong-Hoon Korean Society for Precision Engineering 2015 International Journal of Precision Engineering and Vol.16 No.10
It is well known that the performance of an evolutionary algorithm (EA) is highly dependent on the setting of EA parameters. There have been many studies on EA parameter setting, but no single method outperformed all other methods on all classes of problems as declared by the no free lunch theorem. In order to overcome the heavy computational burden usually required for parameter tuning, we propose an EA parameter tuning procedure applicable to any set of test problems. First, we employ an optimal Latin hypercube design (OLHD) in which parameters of an EA algorithm are set as factors. Next, using parameter settings sampled by OLHD, we run EAs to solve the test problems. Then, we statistically recommend parameter settings suitable for the test problems. Statistical evaluation of this application results suggests the best recombination method, and the recommended parameter ranges of population size, selection rate, and mutation rate are reduced by 93%, 80%, and 84%, respectively, compared to those usually used in parameter ranges. Finally, the recommended parameter setting is applied to the optimization problem of a high-speed spindle motor for a hard disk drive, and shows the effectiveness of the proposed procedure for a practical design optimization application.
Unsupervised Learning for Anomaly Detection of Electric Motors
손종환,Chayoung Kim,Minjoong Jeong 한국정밀공학회 2022 International Journal of Precision Engineering and Vol.23 No.4
This paper presents a novel approach for discriminating abnormal electric motors from normal motors using real sound data. The proportion of abnormal data among all training data is extremely low. Feature extraction techniques are applied to the sound signals. After the extraction, those features are used in unsupervised learning algorithms, including the convolutional autoencoder and one-class support vector machine. Results show that the proposed methods successfully distinguished normal data from abnormal data. The techniques can be applied to determine whether an electric motor is faulty during quality inspection.