• 한국생산제조학회지
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• 제20권3호
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• pp.335-341
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• 2011

In this paper, we proposed an automatic packing mechanism of one station concept for fastener objects where the continuous work is performed in a finite space. The proposed packing mechanism is composed of supporting frame, feeding supply, air shower device, clamping/opening device, batch charging device, sealing/cutting device and supply adjusting device. And, these mechanisms have been modularized through mechanical, dynamical, structural and fluid optimized design using the SMO(SimDesigner Motion) analysis module. Also, the virtual prototype was carried out using the 3-D CAD program. The packing process is consisted performed in the order of feeding, clamping, bottom sealing, cutting, opening, object charging, closing and the upper sealing. And the time of these cycles were designed to be completed in 15-20 seconds. This packing mechanism will be created as a prototype in the near future. In addition, it will be applied to the production scenes after going through a field test for the validation of performance.

• 한국분말야금학회:학술대회논문집
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• 한국분말야금학회 1997년도 춘계학술강연 및 발표대회 강연 및 발표논문 초록집
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• pp.35-35
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• 1997

High$\cdot$speed steels (HSS) with a combination of good wear resistance and toughness are finding new, non-cutting applications such as rolls and rollers. In this paper, the research interests are focused on the microstructural evolution of a SMo-6W series high speed steel during HIPping and the effect of HIPping process parameters on its microstructure and properties. HIPping process variables includes; temperature, pressure and hold time. The microstructures of the HIPped HSS were examined by SEM, OM and X-ray diffraction whereas the properties measured were the relative density, hardness, and bend strength at room temperature. In HIPped materials, MC and M6C were the major carbides formed in a matrix of martensite. The effect of powder size on the microstructure and mechanical properties of HIPped materials was insignificant. However, HIPping temperature and hold time strongly affected the carbide size and distribution. The results show that at proper HIPping temperature and pressure conditions, the final products approach the full density ( > 99% RD). The particle boundaries were completely eliminated without an eminent microstructural coarsening. The bend strength was about 2.3 Gpa, which is superior to cast HSS. At excessive HIPping temperatures, rapid carbide coarsening occurred, thus deteriorating the mechanical properties of the P/M steels.

• Journal of Electrical Engineering and Technology
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• 제13권3호
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• pp.1185-1201
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• 2018

This paper presents a sensorless direct torque control (DTC) combined with sliding mode approach (SM) and space vector modulation (SVM) to achieve mainly a high performance and reduce torque and flux ripples of a parallel-connected two five-phase permanent magnet synchronous machine (PMSM) drive system. In order to increase the proposed drive robustness and decrease its complexity and cost, the rotor speeds, rotor positions, fluxes as well as torques are estimated by using a sliding mode observer (SMO) scheme. The effectiveness of the proposed sliding mode observer in conjunction with the sliding mode control based DTC is confirmed through the application of different load torques for wide speed range operation. Comparison between sliding mode control and proportional integral (PI) control based DTC of the proposed two-motor drive is provided. The obtained speeds, torques and fluxes responses follow their references; even in low and reverse speed operations, load torques changes, and machines parameters variations. Simulation results confirm also that, the ripples of the torques and fluxes are reduced more than 3.33% and 16.66 %, respectively, and the speed overshoots and speed drops are reduced about 99.85% and 92.24%, respectively.

• 대한원격탐사학회지
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• 제26권1호
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• pp.59-64
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• 2010

유럽 우주국 (ESA)에서 지구 탐사 계획의 일환으로 개발한 두 번째 위성인 SMOS (Soil Moisture and Ocean Salinity) 위성이 지난 2009년 11월 발사되어 궤도에 안착, 운행 중에 있다. SMOS는 탑재된 L 대역 합성 개구형 라디오미터를 이용하여 상시 전지구적으로 토양 수분량과 해양 염도를 측정하는 것을 목표로 한다. 이를 통하여 지구의 물순환 및 기상, 기후 연구에 주요한 데이터를 얻을 수 있다. 본 글은 SMOS 발사와 관련된 개괄적인 연구 개발과 현재 운용 현황에 대해 설명한다.

• 한국컴퓨터정보학회:학술대회논문집
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• 한국컴퓨터정보학회 2019년도 제60차 하계학술대회논문집 27권2호
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• pp.115-116
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• 2019

SVM (Support Vector Machine)은 견고성으로 인해 다양한 분류 문제에 적용 할 수 있는 효율적인 기계 학습 기술이다. 그러나 훈련 데이터의 수가 증가함에 따라 시간 복잡도가 급격히 증가하므로 대규모 데이터 세트의 경우 SVM이 비실용적이다. 본 논문에서는 SVM을 사용하여 중복 된 학습 데이터를 효율적으로 제거하는 새로운 병렬 평면(Parallel Hyperplane) 기법을 소개한다. 제안 기법에서 PH는 재귀 적으로 형성되는 반면 PH의 외부에 있는 데이터 포인트의 클러스터는 매 반복마다 제거된다. 시뮬레이션 결과 제안 기법은 기존의 클러스터링 기반 감축 기법과 SMO 기법에 비해 학습 시간을 크게 단축시키면서 데이터 축소 없이 분류의 정확성을 높일 수 있음을 확인 하였다.

• 센서학회지
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• 제30권6호
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• pp.376-380
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• 2021

The accurate detection of hydrogen gas molecules is considered to be important for industrial safety. However, the selective detection of the gas using semiconductive metal oxides (SMOs)-based sensors is challenging. Here, we describe the fabrication of H₂ sensors in which a nanocellulose/graphene oxide (GO) hybrid membrane is attached to SnO₂ nanosheets (NSs). One-dimensional (1D) nanocellulose fibrils are attached to the surface of GO NSs (GONC membrane) by mixing GO and nanocellulose in a solution. The as-prepared GONC membrane is employed as a sacrificial template for SnO₂ NSs as well as a molecular sieving membrane for selective H₂ filtration. The combination of GONC membrane and SnO₂ NSs showed substantial selectivity to hydrogen gas (R_air / R_gas > 10 @ 0.8 % H₂, 100 ℃) with noise level responses to interfering gases (H₂S, CO, CH₃COCH₃, C₂H₅OH, and NO₂). These remarkable sensing results are attributed mainly to the molecular sieving effect of the GONC membrane. These results can facilitate the development of a highly selective H₂ detector using SMO sensors.

• Journal of Power Electronics
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• 제15권3호
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• pp.753-762
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• 2015

This paper presents a nonlinear sliding mode control (SMC) scheme with a variable damping ratio for interior permanent magnet synchronous motors (IPMSMs). First, a nonlinear sliding surface whose parameters change continuously with time is designed. Actually, the proposed SMC has the ability to reduce the settling time without an overshoot by giving a low damping ratio at the initial time and a high damping ratio as the output reaches the desired setpoint. At the same time, it enables a fast convergence in finite time and eliminates the singularity problem with the upper bound of an uncertain term, which cannot be measured in practice, by using a simple adaptation law. To improve the efficiency of a system in the constant torque region, the control system incorporates the maximum torque per ampere (MTPA) algorithm. The stability of the nonlinear sliding surface is guaranteed by Lyapunov stability theory. Moreover, a simple sliding mode observer is used to estimate the load torque and system uncertainties. The effectiveness of the proposed nonlinear SMC scheme is verified using comparative experimental results of the linear SMC scheme when the speed reference and load torque change under system uncertainties. From these experimental results, the proposed nonlinear SMC method reveals a faster transient response, smaller steady-state speed error, and less sensitivity to system uncertainties than the linear SMC method.

• 산업경영시스템학회지
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• 제40권1호
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• pp.57-64
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• 2017

In order to reduce damages to major railroad components, which have the potential to cause interruptions to railroad services and safety accidents and to generate unnecessary maintenance costs, the development of rolling stock maintenance technology is switching from preventive maintenance based on the inspection period to predictive maintenance technology, led by advanced countries. Furthermore, to enhance trust in accordance with the speedup of system and reduce maintenances cost simultaneously, the demand for fault diagnosis and prognostic health management technology is increasing. The objective of this paper is to propose a highly reliable learning model using various machine learning algorithms that can be applied to critical rolling stock components. This paper presents a model for railway rolling stock component fault diagnosis and conducts a mechanical failure diagnosis of motor components by applying the machine learning technique in order to ensure efficient maintenance support along with a data preprocessing plan for component fault diagnosis. This paper first defines a failure diagnosis model for rolling stock components. Function-based algorithms ANFIS and SMO were used as machine learning techniques for generating the failure diagnosis model. Two tree-based algorithms, RadomForest and CART, were also employed. In order to evaluate the performance of the algorithms to be used for diagnosing failures in motors as a critical railroad component, an experiment was carried out on 2 data sets with different classes (includes 6 classes and 3 class levels). According to the results of the experiment, the random forest algorithm, a tree-based machine learning technique, showed the best performance.

• Journal of Gastric Cancer
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• 제20권1호
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• pp.29-40
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• 2020

Purpose: Gastrointestinal stromal tumors (GISTs) frequently harbor activating gene mutations in either KIT or platelet-derived growth factor receptor A (PDGFRA) and are highly responsive to several selective tyrosine kinase inhibitors. In this study, a targeted next-generation sequencing (NGS) assay with an Oncomine Focus Assay (OFA) panel was used for the genetic characterization of molecular targets in 30 Korean patients with GIST. Materials and Methods: Using the OFA that enables rapid and simultaneous detection of hotspots, single nucleotide variants (SNVs), insertion and deletions (Indels), copy number variants (CNVs), and gene fusions across 52 genes relevant to solid tumors, targeted NGS was performed using genomic DNA extracted from formalin-fixed and paraffin-embedded samples of 30 GISTs. Results: Forty-three hotspot/other likely pathogenic variants (33 SNVs, 8 Indels, and 2 amplifications) in 16 genes were identified in 26 of the 30 GISTs. KIT variants were most frequent (44%, 19/43), followed by 6 variants in PIK3CA, 3 in PDGFRA, 2 each in JAK1 and EGFR, and 1 each in AKT1, ALK, CCND1, CTNNB1, FGFR3, FGFR4, GNA11, GNAQ, JAK3, MET, and SMO. Based on the mutation types, majority of the variants carried missense mutations (60%, 26/43), followed by 8 frameshifts, 6 nonsense, 1 stop-loss, and 2 amplifications. Conclusions: Our study confirmed the advantage of using targeted NGS with a cancer gene panel to efficiently identify mutations associated with GISTs. These findings may provide a molecular genetic basis for developing new drugs targeting these gene mutations for GIST therapy.

• BMB Reports
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• 제49권9호
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• pp.497-501
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• 2016

Wide-line ¹H NMR intensity and differential scanning calorimetry measurements were carried out on the intrinsically disordered 73-residue full transactivation domain (TAD) of the p53 tumor suppressor protein and two peptides: one a wild type p53 TAD peptide with a helix pre-structuring property, and a mutant peptide with a disabled helix-forming propensity. Measurements were carried out in order to characterize their water and ion binding characteristics. By quantifying the number of hydrate water molecules, we provide a microscopic description for the interactions of water with a wild-type p53 TAD and two p53 TAD peptides. The results provide direct evidence that intrinsically disordered proteins (IDPs) and a less structured peptide not only have a higher hydration capacity than globular proteins, but are also able to bind a larger amount of charged solute ions.