• Carbon letters
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• v.12 no.4
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• pp.207-217
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• 2011

We discuss the influence of few-walled carbon nanotubes (FWCNTs) treated with nitric acid and/or sulfuric acid on field emission characteristics. FWCNTs/tetraethyl orthosilicate (TEOS) thin film field emitters were fabricated by a spray method using FWCNTs/TEOS sol one-component solution onto indium tin oxide (ITO) glass. After thermal curing, they were found tightly adhered to the ITO glass, and after an activation process by a taping method, numerous FWCNTs were aligned preferentially in the vertical direction. Pristine FWCNT/TEOS-based field emitters revealed higher current density, lower turn-on field, and a higher field enhancement factor than the oxidized FWCNTs-based field emitters. However, the unstable dispersion of pristine FWCNT in TEOS/N,N-dimethylformamide solution was not applicable to the field emitter fabrication using a spray method. Although the field emitter of nitric acid-treated FWCNT showed slightly lower field emission characteristics, this could be improved by the introduction of metal nanoparticles or resistive layer coating. Thus, we can conclude that our spray method using nitric acid-treated FWCNT could be useful for fabricating a field emitter and offers several advantages compared to previously reported techniques such as chemical vapor deposition and screen printing.

• Journal of Power Electronics
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• v.17 no.4
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• pp.1048-1057
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• 2017

An indirect matrix converter (IMC) is a modern power generation system that enables a direct ac/ac conversion without the need for any bulky and limited lifetime electrolytic capacitor. This system also allows four-quadrant operation, generation of sinusoidal output voltage waveforms with variable frequency and amplitude, and control of input power factor. This study proposes a pulse-width modulation-based sliding-mode controller to achieve unity input-power factor operation of the IMC independently of the active power exchanged with the grid, as well as a fast dynamic response. The designed equivalent control law determines, at each sampling period, the appropriate q-axis component of the modulated input current to be injected into the grid through the LC input filter. An integral term of the error is included in the expression of the sliding surface to increase the accuracy of the control method. A double space vector modulation method is used to synthesize the direction of the space vector of the input currents as required by the sliding-mode controller and the space vectors of the target output voltages. Simulation and experimental results are provided to show the effectiveness and evaluate the performance of the proposed control method.

• International Journal of Advanced Culture Technology
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• v.8 no.4
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• pp.167-176
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• 2020

Recommendation Systems is the top requirements for many people and researchers for the need required by them with the proper suggestion with their personal indeed, sorting and suggesting doctor to the patient. Most of the rating prediction in recommendation systems are based on patient's feedback with their information regarding their treatment. Patient's preferences will be based on the historical behaviour of similar patients. The similarity between the patients is generally measured by the patient's feedback with the information about the doctor with the treatment methods with their success rate. This paper presents a new method of predicting Top Ranked Doctor's in recommendation systems. The proposed Recommendation system starts by identifying the similar doctor based on the patients' health requirements and cluster them using K-Means Efficient Clustering. Our proposed K-Means Clustering with Content Based Doctor Recommendation for Cancer (KMC-CBD) helps users to find an optimal solution. The core component of KMC-CBD Recommended system suggests patients with top recommended doctors similar to the other patients who already treated with that doctor and supports the choice of the doctor and the hospital for the patient requirements and their health condition. The recommendation System first computes K-Means Clustering is an unsupervised learning among Doctors according to their profile and list the Doctors according to their Medical profile. Then the Content based doctor recommendation System generates a Top rated list of doctors for the given patient profile by exploiting health data shared by the crowd internet community. Patients can find the most similar patients, so that they can analyze how they are treated for the similar diseases, and they can send and receive suggestions to solve their health issues. In order to the improve Recommendation system efficiency, the patient can express their health information by a natural-language sentence. The Recommendation system analyze and identifies the most relevant medical area for that specific case and uses this information for the recommendation task. Provided by users as well as the recommended system to suggest the right doctors for a specific health problem. Our proposed system is implemented in Python with necessary functions and dataset.

• Atmosphere
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• v.24 no.4
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• pp.491-502
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• 2014

As a part of the KIAPS (Korea Institute of Atmospheric Prediction Systems) Package for Observation Processing (KPOP), we have developed the modules for Advanced Microwave Sounding Unit-A (AMSU-A) pre-processing and its bias correction. The KPOP system calculates the airmass bias correction coefficients via the method of multiple linear regression in which the scan-corrected innovation and the thicknesses of 850~300, 200~50, 50~5, and 10~1 hPa are respectively used for dependent and independent variables. Among the four airmass predictors, the multicollinearity has been shown by the Variance Inflation Factor (VIF) that quantifies the severity of multicollinearity in a least square regression. To resolve the multicollinearity, we adopted simple linear regression and Principal Component Regression (PCR) to calculate the airmass bias correction coefficients and compared the results with those from the multiple linear regression. The analysis shows that the order of performances is multiple linear, principal component, and simple linear regressions. For bias correction for the AMSU-A channel 4 which is the most sensitive to the lower troposphere, the multiple linear regression with all four airmass predictors is superior to the simple linear regression with one airmass predictor of 850~300 hPa. The results of PCR with 95% accumulated variances accounted for eigenvalues showed the similar results of the multiple linear regression.

• Journal of Advanced Navigation Technology
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• v.15 no.4
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• pp.672-679
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• 2011

In this paper, detection algorithm of face region based on skin color of in the TV images is proposed. In the first, reference image is set to the sampled skin color, and then the extracted of face region is candidated using the Euclidean distance between the pixels of TV image. The eye image is detected by using the mean value and standard deviation of the component forming color difference between Y and C through the conversion of RGB color into CMY color model. Detecting the lips image is calculated by utilizing Q component through the conversion of RGB color model into YIQ color space. The detection of the face region is extracted using basis of knowledge by doing logical calculation of the eye image and lips image. To testify the proposed method, some experiments are performed using front color image down loaded from TV color image. Experimental results showed that face region can be detected in both case of the irrespective location & size of the human face.

• Journal of Korea Multimedia Society
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• v.16 no.10
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• pp.1156-1162
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• 2013

Face verification has been widely studied during the past two decades. One of the challenges is the rising concern about the security and privacy of the template database. In this paper, we propose a secure face verification system which generates a unique secure cryptographic key from a face template. The face images are processed to produce face templates or codes to be utilized for the encryption and decryption tasks. The result identity data is encrypted using Advanced Encryption Standard (AES). Distance metric naming hamming distance and Euclidean distance are used for template matching identification process, where template matching is a process used in pattern recognition. The proposed system is tested on the ORL, YALEs, and PKNU face databases, which contain 360, 135, and 54 training images respectively. We employ Principle Component Analysis (PCA) to determine the most discriminating features among face images. The experimental results showed that the proposed distance measure was one the promising best measures with respect to different characteristics of the biometric systems. Using the proposed method we needed to extract fewer images in order to achieve 100% cumulative recognition than using any other tested distance measure.

• Proceedings of the KSME Conference
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• 2000.11b
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• pp.247-254
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• 2000

The base pressure of vacuum vessel of the KSTAR (Korea Superconducting Tokamak Advanced Research) Tokamak is to be a ultra high vacuum, $10^{-6}{\sim}10^{-7}Pa$, to produce clean plasma with low impurity containments. For this purpose, the KSTAR vacuum vessel and plasma facing components need to be baked up to at least $250^{\circ}C,\;350^{\circ}C$ respectively, within 24 hours by hot nitrogen gas from a separate baking/cooling line system to remove impurities from the plasma-material interaction surfaces before plasma operation. Here by applying the implicit numerical method to the heat balance equations of the system, overall temperature distributions of the KSTAR vacuum vessel and plasma facing components are obtained during the whole baking process. The model for 2-dimensional baking analysis are segmented into 9 imaginary sectors corresponding to each plasma facing component and has up-down symmetry. Under the resulting combined loads including dead weight, baking gas pressure, vacuum pressure and thermal loads, thermal stresses in the vacuum vessel during bakeout are calculated by using the ANSYS code. It is found that the vacuum vessel and its supports are structurally rigid based on the thermal stress analyses.

• 한국균학회소식:학술대회논문집
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• 2016.05a
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• pp.35-35
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• 2016

A mycotoxin is a toxic secondary metabolite produced by organisms of the fungus kingdom, commonly known as molds and has been widely contaminated in agricultural products such as grains and cereals. Many methods including high performance liquid chromatography (HPLC) and gas chromatography (GC) have already been proposed and reviewed for mycotoxins. These methods are either expensive or time-consuming due to the complication of sample preparation and pre-concentration before determination. In addition, both methods are unsuitable for the routine screening of large sample numbers. A biosensor is a fictive analytical device that combines a biological component with a physicochemical detector for the detection of an analyte. Biosensors represent a rapidly expanding field, at the present time, with an estimated 60% annual growth rate; the major impetus coming from the health-care industry but with some pressure from other areas, such as food safety and environmental monitoring. Antibodies and aptamers are bioreceptors which have been used in the development of biosensors. There are many kinds of antibodies and aptamers specific to mycotoxin, and antibody (or aptamer)-based biosensors have been successfully developed for the detection of mycotoxin. The biosensors permit the rapid, sensitive, simple, and on-site detection of a range of mycotoxins and can be an alternative method to traditional methods such as HPLC and GC. This presentation provides the development trends of biosensors to mycotoxins and their application to food and agricultural products.

• Journal of the Korean Society of Manufacturing Process Engineers
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• v.21 no.3
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• pp.92-99
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• 2022

Owing to the excellent corrosion resistance of titanium alloys, they are widely used as materials for aircraft components. However, in terms of machining, dimensional deformation methods vary significantly, such as forging, owing to their difficult-to-cut property and the uncontrollable vibration generated during machining. A method to minimize the vibration generated during machining by applying advanced tools and controlling the sequence of machining processes, which can improve the machinability and precision of titanium alloy-forged low-angle components, is proposed herein. Using the proposed tool and based on a process order experiment, the efficiency of the machining process is verified by measuring the dimensional deformation of the low-angle component.

• Geomechanics and Engineering
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• v.37 no.1
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• pp.21-29
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• 2024

The effective management of damage in tunnels is crucial for ensuring their safety, longevity, and operational efficiency. In this paper, we propose an educational management model tailored specifically for addressing damage in tunnels, utilizing numerical solution techniques. By leveraging advanced computational methods, we aim to develop a comprehensive understanding of the factors contributing to tunnel damage and to establish proactive measures for mitigation and repair. The proposed model integrates principles of tunnel engineering, structural mechanics, and numerical analysis to facilitate a systematic approach to damage assessment, diagnosis, and management. Through the application of numerical solution techniques, such as finite element analysis, we demonstrate the efficacy of the proposed model in simulating various damage scenarios and predicting their impact on tunnel performance. Additionally, the educational component of the model provides valuable insights and training opportunities for tunnel management personnel, empowering them to make informed decisions and implement effective strategies for ensuring the structural integrity and safety of tunnel infrastructure. Overall, the proposed educational management model represents a significant advancement in tunnel management practices, offering a proactive and knowledge-driven approach to addressing damage and enhancing the resilience of tunnel systems.