By adapting black body leadflame and thin film type Green A filter, we successfully demonstrated night vision imaging system (NVIS) Green A compatible LED. Fabricated NVIS compatible LEDs show small form factor compared to that of commercialized NVIS compatible LED. Especially, NVIS radiance and chromaticity of MIL-STD-3009 specification can be satisfied simultaneously and easily by controlling the color temperature of the white LED as well as the concentration of the Green A dye and the thickness of the Green A filter. The optimal dye concentration of the NVIS Green A filter is expected to be about 1 wt%. The results of this study are expected to contribute to miniaturization, weight reduction and localization of avionic display and lighting devices.

The silver nanowires (AgNWs) were synthesized by the conventional polyol process, which revealed 25 ㎛ and 30 nm of average length and diameter, respectively. The synthesized AgNWs were applied to the CdSe/CdZnS quantum dot (QD) based transparent light-emitting device (LED). The device using a randomly networked AgNWs electrode had some problems such as the high threshold voltage (for operating the device) due to the random pores from the networked AgNWs. As a method of improvement, a composite electrode was formed by overlaying the ZnO:Ga on the AgNWs network. The device used the composite electrode revealed a low threshold voltage (4.4 Vth) and high current density compared to the AgNWs only electrode device. The brightness and current density of the device using composite electrode were 55.57 cd/㎡ and 41.54 mA/㎠ at the operating voltage of 12.8 V, respectively, while the brightness and current density of the device using (single) AgNWs only were 1.71 cd/㎡ and 2.05 mA/㎠ at the same operating voltage. The transmittance of the device revealed 65 % in a range of visible light. Besides the reliability of the devices was confirmed that the device using the composite electrode revealed 2 times longer lifetime than that of the AgNWs only electrode device.

In this study, a new method for fabricating flexible transparent electrodes based on silver nanowire-polymer (AgNW-PEDOT:PSS) composite materials having a mesh pattern formed by a solution-based process without lithography was proposed. By optimizing conditions such as the amount of ultraviolet (UV) photosensitizer injected into the suspension of AgNW and PEDOT:PSS, UV exposure time, and deionized (DI) washing time, a clear and uniform mesh pattern was obtained. For the fabricated AgNW-PEDOT:PSS-based mesh-type electrodes, characteristics such as electrical sheet resistance, light transmittance, haze, and bending flexibility were analyzed according to the mixing ratio of AgNW and PEDOT:PSS included in the suspension. The fabricated mesh electrodes typically exhibited a low electrical sheet resistance of less than 20 Ω/sq while maintaining a high transmittance of 80% or more. In addition, it was confirmed from the results of analyzing the effect of PEDOT:PSS on the characteristics of the mesh-type AgNW-PEDOT electrode that the optical visibility was greatly enhanced by reducing the surface roughness and haze, and the bending flexibility was remarkably improved.

Undetected wafer slip during the lift pin-down motion in semiconductor equipment may affect the center to edge variation, wafer warpage, and pattern misalignment in plasma equipment. Direct measuring of the amount of wafer slip inside the plasma process chamber is not feasible because of the hardware space limitation inside the plasma chamber. In this paper, we demonstrated a practice for the wafer lift pin-up and down motions with respect to the gear ratio, operating voltage, and pulse width modulation to maintain accurate wafer position using remote control linear servo motor with an experimentally designed chamber mockup. We noticed that the pin moving velocity and gear ratio are the most influencing parameters to be control, and the step-wised position control algorithm showed the most suitable for the reduction of wafer slip.

In this paper, a generalized efficiency equation was proposed to estimate the internal loss of the SMPS (switched-mode power supply) with 3 variables. The first variable was an internal loss not related to the load current such as auxiliary power, the second was a loss proportional to the current such as diode loss, and the third was a loss proportional to square of the current such as conduction loss. Especially, theoretical internal losses of the totem pole bridgeless PFC which is widely used for high efficiency SMPS were expressed as output function to compare generalized efficiency equation. In addition, in order to reduce the conduction loss of the switch, when a multiple switch were paralleled, the correlation with the efficiency was analyzed and shown as a graph. In order to confirm the degree of the parallel switch structure on the efficiency improvement, a 2kW class totem pole bridgeless PFC was constructed and the effectiveness of the analysis was confirmed by comparing the generalized efficiency equation and theoretical loss analysis results with experimental data.

Plasma etching process employs high density plasma to create surface chemistry and physical reactions, by which to remove material. Plasma chamber includes silicon-based materials such as a focus ring and gas distribution plate. Focus ring needs to be replaced after a short period. For this reason, there is a need to find materials resistant to erosion by plasma. The developed chemical vapor deposition processing to produce silicon carbide parts with high purity has also supported its widespread use in the plasma etch process. Silicon carbide maintains mechanical strength at high temperature, it have been use to chamber parts for plasma. Recently, besides the structural aspects of silicon carbide, its electrical conductivity and possibly its enhanced life time under high density plasma with less generation of contamination particles are drawing attention for use in applications such as upper electrode or focus rings, which have been made of silicon for a long time. However, especially for high purity silicon carbide focus ring, which has usually been made by the chemical vapor deposition method, there has been no study about quality improvement. The goal of this study is to reduce surface roughness and depth of damage by diamond tool grit size and tool dressing of diamond tools for precise dimensional assurance of focus rings.

In this paper, we implement a Dashcam system capable of shooting 360 degrees using a Raspberry Pi, shock sensors, distance sensors, and rotating camera with a servo motor. If there is an object approaching the vehicle by the distance sensor, the camera rotates to take a video. In the event of an external shock, videos and images are stored in the server to analyze the cause of the vehicle's accident and prevent the user from forging or tampering with videos or images. We also implement functions that transmit the message with the location and the intensity of the impact when the accident occurs and send the vehicle information to an insurance authority with by linking the system with a smart device. It is advantage that the authority analyzes the transmitted message and provides the accident handling information giving the user's safety and convenience.

In the production process, the buffer acts as a buffer to alleviate some of the problems such as delays in delivery and process control failures in unexpected situations. Determining the optimal buffer size can contribute to system performance, such as increased output and resource utilization. However, there are difficulties in allocating the optimal buffer due to the complexity of the process or the increase in the number of variables. Therefore, the purpose of this research is proposing an optimal buffer allocation that maximizes throughput. First step is to design the production process to carry out the research. The second step is to maximize the throughput through the harmony search algorithm and to find the buffer capacity that minimizes the lead time. To verify the efficiency, comparing the ratio of the total increase in throughput to the total increase in buffer capacity.

In this research, the attractive force of Coulomb type electrostatic chuck(ESC), which consisted of alumina dielectric, on glass substrate was studied by using the finite element analysis. The attractive force is caused by the high electrical resistance which occurs in contact region between glass substrate and dielectric layer. This research tries the simple geometrical modeling of ESC and glass substrate with air gap. The influences of the applied voltage, and air gap are investigated. When alumina dielectric with 1014 Ω·cm, 1.5 kV voltage, and 0.01 mm air gap were applied, electrostatic force in this work reached to 4 gf/㎠. This results show that the modeling of air gap is essential to derive the attractive force of the ESC.

Many types of optical plastic films are essential in optoelectronics display unit fabrication and it is important to develop high precision laser cutting methods of optical films with extremely low level of film surface contamination by fume particles. This study investigates the effects of suction and blowing air motions with air flow misalignment in removing fume particles from laser cut line by employing random particle trajectory simulation and probabilistic particle generation model. The computational results show fume particle dispersion behaviors on optical film under suction and blowing air flow conditions. It is found that suction air flow motion is more advantageous to blowing air motion in reducing film surface contamination outside designated target margin from laser cut line. While air flow misalignment adversely affects particle dispersion in blowing air flows, its effects become much more complicated in suction air flows by showing different particle dispersion patterns around laser cut line. It is required to have more careful air flow alignment in fume particle removal under suction air flow conditions.

In this paper, we found the solution using data based machine learning regression method to check the pore shape, to solve the problem of the experiment quantity occurring when producing scaffold with the 3d printer. Through experiments, we learned secured each print condition and pore shape. We have produced the scaffold from scaffold pore shape defect prediction model using multiple linear regression method. We predicted scaffold pore shapes of unsecured print condition using the manufactured scaffold pore shape defect prediction model. We randomly selected 20 print conditions from various predicted print conditions. We print scaffold five times under same print condition. We measured the pore shape of scaffold. We compared printed average pore shape with predicted pore shape. We have confirmed the prediction model precision is 99 %.

CNN's technologies that represent emotional detection include primitive CNN algorithms, deployment normalization, and drop-off. We present the methods and data of the three experiments in this paper. The training database and the test database are set up differently. The first experiment is to extract emotions using Batch Normalization, which complemented the shortcomings of distribution. The second experiment is to extract emotions using Dropout, which is used for rapid computation. The third experiment uses CNN using convolution and maxpooling. All three results show a low detection rate, To supplement these problems, We will develop a deep learning algorithm using feature extraction method specialized in image processing field.

In this paper, we propose a super-resolution method that reconstructs compressed low-resolution images into high-resolution images. We propose a CNN model with a small number of parameters, and even if quantization is applied to the proposed model, super-resolution can be implemented without deteriorating the image quality. To further improve the quality of the compressed low-resolution image, a new degradation model was proposed instead of the existing bicubic degradation model. The proposed degradation model is used only in the training process and can be applied by changing only the parameter values to the original CNN model. In the super-resolution image applying the proposed degradation model, visual artifacts caused by image compression were effectively removed. As a result, our proposed method generates higher PSNR values at compressed images and shows better visual quality, compared to conventional CNN-based SR methods.

The Linear system analysis for physical system is very powerful tool for system diagnostic utilizing relationship between the input signal and output signal. This method utilized generally to investigate physical properties of system and the nondestructive test by ultrasonic signals. This method can be explained by linear system theory. In this paper the Continuous Wavelets Transform is utilized to search the relation between the linear system and continuous wavelets transform.

The properties of ultra-thin two-dimensional (2D) organic ferroelectric Langmuir-Blodgett (LB) films of the poly(vinylidene fluoride-trifluoroethylene) [P(VDF-TrFE)] were investigated to find possible applicability in flexible and wearable electronics applications. In the C-V characteristics of the MFM capacitor of 2-monolayer of 5 nm films, a butterfly hysteresis curve due to the ferroelectricity of P(VDF-TrFE) was confirmed. Typical residual polarization value was measured at 2μC/㎠. When the MFM capacitor with ultra-thin ferroelectric film was measured by applying a 10 Hz bipolar pulse, it was shown that 65% of the initial polarization value in 105 cycles deteriorated the polarization. The leakage current density of the 2-monolayer film was maintained at about 5 × 10-8 A/㎠ for the case at a 5MV/cm electric field. The resistivity of the 2-monolayer film in the case at an electric field at 5 MV/cm was more than 2.35 × 1013 Ω·cm.

Based on the capture-emission energy (CEE) maps of CMOS devices, a physics-informed machine learning model for the bias temperature instability (BTI)-induced threshold voltage shifts and low frequency noise is presented. In order to incorporate physics theories into the machine learning model, the integration of artificial neural network (IANN) is employed for the computation of the threshold voltage shifts and low frequency noise. The model combines the computational efficiency of IANN with the optimal estimation of Gaussian mixture model (GMM) with soft clustering. It enables full lifetime prediction of BTI under various stress and recovery conditions and provides accurate prediction of the dynamic behavior of the original measured data.

The core/shell of nanowires (NWs) with Cu-doped CdSe quantum dots were fabricated as an electron transport layer (ETL) for perovskite solar cells, based on ZnO/TiO2 arrays. We presented CdSe with Cu2+ dopants that were synthesized by a colloidal process. An improvement of the recombination barrier, due to shell supplementation with Cu-doped CdSe quantum dots. The enhanced cell steady state was attributable to TiO2 with Cu-doped CdSe QD supplementation. The mechanism of the recombination and electron transport in the perovskite solar cells becoming the basis of ZnO/TiO2 arrays was investigated to represent the merit of core/shell as an electron transport layer in effective devices.

In this paper, efficiency and loss characteristics of GaN FET were reported by applying it into the QR flyback converter. In particular, for the comparison of efficiency characteristics, QR flyback converter experimental circuits with Si FET and with GaN FET were separately produced in 12W class. As a result of the experiment, the experimental circuit of the QR flyback converter using GaN FET reached a high efficiency of 90% or more when the load power was 2W or more, and the maximum efficiency was observed to be about 92%, and the maximum loss power was about 1.1W. Meanwhile, the efficiency of the experimental circuit with Si FET increased as the input voltage increased, and the maximum efficiency was observed to be about 82% when the load power was 9W or higher, and the maximum loss power was about 2.8W. From the results, it is estimated that that in the case of the experimental circuit applying the GaN FET switch, the power conversion efficiency was improved as the switching loss and conduction loss due to on-resistance were reduced, and the internal loss due to the synchronous rectifier was minimized. Consequently, it is concluded that the GaN FET is suitable for under 20W class power supply unit as a high efficiency power switch.

In most multiple input/output systems, one input affects two or more different outputs. Therefore, there are many inconveniences in using the actual system. In order to solve this problem, a controller that makes an input signal and an output correspond 1:1 is called a decoupling controller. In this paper, I try to implement a relatively simple decoupling controller using a cross-compensator, that is, a compensator that takes an uncorresponding output as an input value. And this cross-compensator has a gain scheduler structure in order to increase the performance. In addition, this system is designed with a distributed control structure using CAN communication, so that it can be manufactured and operated in an easier way when implementing an actual experimental system. The proposed structure is applied to the modified new Arago's disk system and tested, and through this, the effectiveness is confirmed and reported.

Trump cards are used in variable games in households such as poker and blackjack. In many cases, it is able to be helpful to algorithmically identify the playing cards from camera views. In this paper, we provide an approach that detects and identifies the playing card using template matching scheme, and evaluate the results of the provided implementation. For ideal cases, the implemented system provides a 100% success rate for card identification correct. However, non-ideal case of perspective distortion is estimated with 70% success ratio. This work aims to evaluate the effectiveness of augmented reality user interface for an entertainment application like playing card games.

In this paper, we developed an electrochemical glucose sensor strip using a paper substrate. The paper glucose sensor strip is eco-friendly because it uses paper as a substrate, and it has the advantage that it can be manufactured only with four printing, drying and cutting processes. The paper glucose sensor is significantly simplified by the production process than the conventional glucose sensors because the production of only four printing on the paper substrate. In this paper, eco-friendly tracing paper was used to develop a paper glucose sensor strip, and screen-printing technology was used to form a carbon/silver electrode, insulating layer and glucose oxidase(GOD) layer. The developed paper glucose sensor strip has a flat structure with a size of 30 × 4.6 ㎟, and blood injection is a type of direct contact with the exposed enzyme layer above the strip. In this paper, the performance of paper glucose sensor strips was evaluated by analyzing the cyclic voltammetry(CV) and chronoamperometry(CA) characteristics.

With miniaturization of semiconductor, the manufacturing process become more complex, and undetected small changes in the state of the equipment have unexpectedly changed the process results. Fault detection classification (FDC) system that conducts more active data analysis is feasible to achieve more precise manufacturing process control with advanced machine learning method. However, applying machine learning, especially in supervised learning criteria, requires an arduous data labeling process for the construction of machine learning data. In this paper, we propose a semi-supervised learning to minimize the data labeling work for the data preprocessing. We employed equipment status variable identification (SVID) data and optical emission spectroscopy data (OES) in silicon etch with SF6/O2/Ar gas mixture, and the result shows as high as 95.2% of labeling accuracy with the suggested semi-supervised learning algorithm.

We introduce a lifetime assessment technique using deep learning algorithm with complex electrical parameters such as resistivity, permittivity, impedance parameters as integrated indicators for predicting the degradation of the organic molecules. The evaluation system consists of fully automated in-situ measurement system and multiple layer perceptron learning system with five hidden layers and 1011 perceptra in each layer. Prediction accuracies are calculated and compared depending on the physical feature, learning hyperparameters. 62.5% of full time-series data are used for training and its prediction accuracy is estimated as r-square value of 0.99. Remaining 37.5% of the data are used for testing with prediction accuracy of 0.95. With k-fold cross-validation, the stability to the instantaneous changes in the measured data is also improved.

This paper proposes a new method for the digit recognition on a 7-segment display. The proposed method uses morphological processing that dilates segments of digits and connects them into strokes. The digits are extracted by connected component analysis and finally, template matching method recognizes the extracted digits. The proposed method is implemented using C language in Raspberry Pi 4 system with a camera module for a real-time image processing. Experiments were conducted by using various 7-segment LED displays and 7-segment mono LCD displays. The results show that the proposed method is successful for the digit recognition on the 7-segment displays.

This paper suggests a method of automatic clustering to search of relevant digital photos using geo-coded information. The provided scheme labels photo images with their corresponding global positioning system coordinates and date/time at the moment of capture, and the labels are used as clustering metadata of the images when they are in the use of retrieval. Experimental results show that geo-location information can improve the accuracy of image retrieval, and the information embedded within the images are effective and precise on the image clustering.

Recently, the electronic equipment industry has become active due to the continuous increase in portable storage media with high-speed information communication, and in particular, the production of SSD(Solid State Drives) for miniaturization of mobile devices and high-speed information communication has increased rapidly. When the SSD is ejecting in the SSD test gender, the necessary ejecting force must be kept constant to have a lifespan applicable to the test device. When the ejecting force increased, it leads to wear of the link for ejecting, which causes a problem in that repeated durability decreases and the ejecting of the SSD becomes impossible. In this paper, the repeated durability test analysis according to the material and the reducing ejecting force design were performed to increase the life of the test gender for SSD inspection. The wear level of the pusher head and ejector was analyzed through repeated durability tests according to the material of the pusher head. The validity of the design was verified through the ejecting force test and repeated durability test of the Test gender, which was designed by carrying out the design to reduce the size and ejecting force of the test gender.