• Proceedings of the Korean Institute of Electrical and Electronic Material Engineers Conference
• /
• 2002.08a
• /
• pp.128-132
• /
• 2002

Many compound semiconductors which have high carrier mobility and small band gap have attentive in application of various practical a field. Especially, InSb served for Hall device and magnetic resistor such as magnetic sensor because InSb thin film has high mobility. Many studies on InSb thin film deposistion because In and Sb has been very different feature of vapor pressure($10^{-4}$ times) When In and. Sb deposited. In this paper studied it In and Sb deposited simultaneously using by method of co-sputtering deposotion. This process, get to effects of manufacture process simplification. After that this paper observed micro structure and electronic behavior of InSb thin film using by co-sputtering and we study properties of magneto-resistance by annealing

• Proceedings of the Korean Society for Technology of Plasticity Conference
• /
• 2005.05a
• /
• pp.237-240
• /
• 2005

The demand of micro electrical mechanical system (MEMS) bio/chemical sensor is rapidly increasing. To prevent the contamination of sensing area, a filtration system is required in on-chip total analyzing MEMS bio/chemical sensor. A nano-filter was mainly applied in some application detecting submicron feature size bio/chemical products such as bacteria, fungi and so on. We suggested a simple nano-filter fabrication process based on replication process. The mother pattern was fabricated by holographic lithography and reactive ion etching process, and the replication process was carried out using polymer mold and UV-imprinting process. Finally the nano-filter is obtained after removing the replicated part of metal deposited replica. In this study, as a practical example of the suggested process, a nano-dot array was replicated to fabricate nano-filter fur bacteria sensor application.

• Structural Monitoring and Maintenance
• /
• v.6 no.3
• /
• pp.173-190
• /
• 2019

Steel-confined reinforced concrete (SCRC) columns feature highly complex and invisible mechanisms that make damage evaluation and pattern recognition difficult. In the present article, the prevailing acoustic emission (AE) technique was applied to monitor and evaluate the damage process of steel-confined RC columns in a quasi-static test. AE energy-based indicators, such as index of damage and relax ratio, were proposed to trace the damage progress and quantitatively evaluate the damage state. The fuzzy C-means algorithm successfully discriminated the AE data of different patterns, validity analysis guaranteed cluster accuracy, and principal component analysis simplified the datasets. A detailed statistical investigation on typical AE features was conducted to relate the clustered AE signals to micro mechanisms and the observed damage patterns, and differences between steel-confined and unconfined RC columns were compared and illustrated.

• Smart Structures and Systems
• /
• v.29 no.6
• /
• pp.799-805
• /
• 2022

Permanent magnet synchronous motors (PMSMs) are widely used in systems requiring high control precision, efficiency, and reliability. Predicting the remaining useful life (RUL) with health monitoring of PMSMs prevents catastrophic failure and ensures reliable operation of system. In this study, a model-based method for predicting the RUL of PMSMs using phase current and vibration signals is proposed. The proposed method includes feature selection and RUL prediction based on a particle filter with a degradation model. The Paris-Erdogan model describing micro fatigue crack propagation is used as the degradation model. An experimental set-up to conduct accelerated life test, capable of monitoring various signals was designed in this study. Phase current and vibration data obtained from an accelerated life test of the PMSMs were used to verify the proposed approach. Features extracted from the data were clustered based on monotonicity and correlation clustering, respectively. The results identify the effectiveness of using the current data in predicting the RUL of PMSMs.

• The Journal of the Acoustical Society of Korea
• /
• v.39 no.6
• /
• pp.592-599
• /
• 2020

This paper proposes a Convolutional Recurrent Neural Net (CRNN) structure that can simultaneously reflect both static and dynamic characteristics of seismic waveforms for various earthquake events classification. Addressing various earthquake events, including not only micro-earthquakes and artificial-earthquakes but also macro-earthquakes, requires both effective feature extraction and a classifier that can discriminate seismic waveform under noisy environment. First, we extract the static characteristics of seismic waveform through an attention-based convolution layer. Then, the extracted feature-map is sequentially injected as input to a multi-input single-output Long Short-Term Memory (LSTM) network structure to extract the dynamic characteristic for various seismic event classifications. Subsequently, we perform earthquake events classification through two fully connected layers and softmax function. Representative experimental results using domestic and foreign earthquake database show that the proposed model provides an effective structure for various earthquake events classification.

• The Journal of the Korea Contents Association
• /
• v.9 no.2
• /
• pp.432-438
• /
• 2009

In this paper, we evaluated the performance of the automatic classifier applied for the discrimination of acute alcoholic liver injury and chronic liver fibrosis. The classifier uses the discriminant peaks of the preprocessed Raman spectrum as a feature set. In preprocessing step, we subtract baseline and apply Savitzky-Golay smoothing filter which is known to be useful at preserving peaks. After identifying discriminant peaks from the spectra, we carried out the classification experiments using MAP and neural networks. According to the experimental results, the classifier shows the promising results to diagnosis alcoholic liver injury and chronic liver fibrosis. Classification results over 80% means that the peaks used as a feature set is useful for diagnosing liver disease.

• Journal of the Korea Academia-Industrial cooperation Society
• /
• v.12 no.11
• /
• pp.5150-5155
• /
• 2011

Alzheimer's disease (AD) and vascular dementia (VD) are the most common dementia. In this paper, we proposed a region selection for classification of AD, VD and normal (NOR) based on micro-Raman spectra from platelet. The preprocessing step is a smoothing followed by background elimination to the original spectra. Then we applied the minmax method for normalization. After the inspection of the preprocessed spectra, we found that 725-777, 1504-1592 and 1632-1700 $cm^{-1}$ regions are the most discriminative features in AD, VD and NOR spectra. We applied the feature transformation using PCA (principal component analysis) and NMF (nonnegative matrix factorization). The classification result of MAP(maximum a posteriori probability) involving 327 spectra transformed features using proposed local region showed about 92.8 % true classification average rate.

• Journal of The Korean Astronomical Society
• /
• v.53 no.6
• /
• pp.161-168
• /
• 2020

We report the discovery of a giant exoplanet in the microlensing event OGLE-2017-BLG-1049, with a planet-host star mass ratio of q = 9.53 ± 0.39 × 10-3 and a caustic crossing feature in Korea Microlensing Telescope Network (KMTNet) observations. The caustic crossing feature yields an angular Einstein radius of θE = 0.52 ± 0.11 mas. However, the microlens parallax is not measured because the time scale of the event, tE ≃ 29 days, is too short. Thus, we perform a Bayesian analysis to estimate physical quantities of the lens system. We find that the lens system has a star with mass Mh = 0.55+0.36-0.29 M⊙ hosting a giant planet with Mp = 5.53+3.62-2.87 MJup, at a distance of DL = 5.67+1.11-1.52 kpc. The projected star-planet separation is a⊥ = 3.92+1.10-1.32 au. This means that the planet is located beyond the snow line of the host. The relative lens-source proper motion is μrel ~ 7 mas yr-1, thus the lens and source will be separated from each other within 10 years. After this, it will be possible to measure the flux of the host star with 30 meter class telescopes and to determine its mass.

• The KIPS Transactions:PartC
• /
• v.11C no.2
• /
• pp.193-202
• /
• 2004

Handoff if the most Important feature for the user's mobility in a cellular communication system, which is related to resource reservation at nearby cells. For efficient resource reservation, mobility prediction has been reported as an effective means to decrease call dropping probability and to shorten handoff latency in wireless cellular environments. Several early proposed handoff schemes making use of tile user's movement history on a cell-by-cell basis work on the assumption that the user's movements are restricted to the indoor locations such as an office or a building. However, those algorithms cannot be applied to a micro-cell structure or a metropolis with complicated structure of roads. In this paper, to overcome those drawbacks we propose a new mobility prediction algorithm, which stores and uses the history of the user's positions within the current cell to predict the next cell.

• Asian Journal of Atmospheric Environment
• /
• v.11 no.2
• /
• pp.122-130
• /
• 2017

The main purpose of the study was to clarify the properties of individual particles collected at each behavior space of a factory worker. The samplings of size-segregated ($PM_{2.1-1.1}$ and $PM_{4.7-3.3}$) indoor particles were conducted at three different behavior spaces of a factory worker who is engaged in an auto parts manufacturing plant (i.e., his home, his work place in factory, and his favorite restaurant). Elemental specification (i.e., relative elemental content and distribution in and/or on individual particles) was performed by a micro-PIXE system. Every element detected from the coarse particulate matters of home was classified into three groups, i.e., a group of high net-counts (Na, Al, and Si), a group of intermediate net-counts (Mg, S, Cl, K, and Ca), and a group of minor trace elements (P, Ti, V, Cr, Mn, Fe, Co, Ni, Cu, Zn, and Pb). The results of EF for $PM_{4.7-3.3}$ in home indicated that several heavy metals were generated from the sources within the house itself. An exceptional feature shown in the individual particles in workplace is that Cr, Mn, and Co were clearly detected in both fine and coarse particles. Cluster analysis suggested that the individual coarse particles ($PM_{4.7-3.3}$) collected at the indoor of factory were chemically heterogeneous and they modified with sea-salt, mineral, and artificially derived elements. The principal components in individual coarse particles collected at restaurant were sea-salt and mineral without mixing with harmful trace elements like chromium and manganese. Compared to the indoor fine particles of home and restaurant, many elements, especially, Cl, Na, Cr, Mn, Pb, and Zn showed overwhelmingly high net-counts in those of factory.