• Journal of Korean Society of Industrial and Systems Engineering
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• v.46 no.4
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• pp.199-208
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• 2023

Taguchi method is one of the most popular approaches for design optimization such that performance characteristics become robust to uncontrollable noise variables. However, most previous Taguchi method applications have addressed a single-characteristic problem. Problems with multiple characteristics are more common in practice. The multi-criteria decision making(MCDM) problem is to select the optimal one among multiple alternatives by integrating a number of criteria that may conflict with each other. Representative MCDM methods include TOPSIS(Technique for Order of Preference by Similarity to Ideal Solution), GRA(Grey Relational Analysis), PCA(Principal Component Analysis), fuzzy logic system, and so on. Therefore, numerous approaches have been conducted to deal with the multi-characteristic design problem by combining original Taguchi method and MCDM methods. In the MCDM problem, multiple criteria generally have different measurement units, which means that there may be a large difference in the physical value of the criteria and ultimately makes it difficult to integrate the measurements for the criteria. Therefore, the normalization technique is usually utilized to convert different units of criteria into one identical unit. There are four normalization techniques commonly used in MCDM problems, including vector normalization, linear scale transformation(max-min, max, or sum). However, the normalization techniques have several shortcomings and do not adequately incorporate the practical matters. For example, if certain alternative has maximum value of data for certain criterion, this alternative is considered as the solution in original process. However, if the maximum value of data does not satisfy the required degree of fulfillment of designer or customer, the alternative may not be considered as the solution. To solve this problem, this paper employs the desirability function that has been proposed in our previous research. The desirability function uses upper limit and lower limit in normalization process. The threshold points for establishing upper or lower limits let us know what degree of fulfillment of designer or customer is. This paper proposes a new design optimization technique for multi-characteristic design problem by integrating the Taguchi method and our desirability functions. Finally, the proposed technique is able to obtain the optimal solution that is robust to multi-characteristic performances.

• Korean Chemical Engineering Research
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• v.61 no.4
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• pp.542-549
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• 2023

Since the growing interest in surrogate modeling, there has been continuous research aimed at simulating nonlinear chemical processes using data-driven machine learning. However, the opaque nature of machine learning models, which limits their interpretability, poses a challenge for their practical application in industry. Therefore, this study aims to analyze chemical processes using Explainable Artificial Intelligence (XAI), a concept that improves interpretability while ensuring model accuracy. While conventional sensitivity analysis of chemical processes has been limited to calculating and ranking the sensitivity indices of variables, we propose a methodology that utilizes XAI to not only perform global and local sensitivity analysis, but also examine the interactions among variables to gain physical insights from the data. For the ammonia synthesis process, which is the target process of the case study, we set the temperature of the preheater leading to the first reactor and the split ratio of the cold shot to the three reactors as process variables. By integrating Matlab and Aspen Plus, we obtained data on ammonia production and the maximum temperatures of the three reactors while systematically varying the process variables. We then trained tree-based models and performed sensitivity analysis using the SHAP technique, one of the XAI methods, on the most accurate model. The global sensitivity analysis showed that the preheater temperature had the greatest effect, and the local sensitivity analysis provided insights for defining the ranges of process variables to improve productivity and prevent overheating. By constructing alternative models for chemical processes and using XAI for sensitivity analysis, this work contributes to providing both quantitative and qualitative feedback for process optimization.

• Clean Technology
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• v.29 no.4
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• pp.305-312
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• 2023

Due to the strengthening of environmental requirements, aging denitrification facilities need to improve their performance. The present study aims to suggest the possibility of improving performance using computational analysis techniques. This involved modifying both the geometric design and the operating conditions, including the flow path shape of the equipment such as the inlet guide vane and the curved diffusing part, and the flow control of the ammonia injection nozzle. The conditions presented in this study were compared with existing operating conditions in terms of the flow uniformity, the NH₃/NO molar ratio of the mixed gas flowing into the catalyst layer, and the total pressure drop of the facility. The flow field applied in the computational analysis ranged from the outlet of the economizer in the combustion furnace to the inlet of the air preheater, the full domain of the denitrification facility. The performances were derived by solving the flow fields using ANSYS-Fluent and the injection amount of ammonia was adjusted for each nozzle using Design Xplorer. Compared to the denitrification performances of the equipment currently in operation, the conditions proposed in this study showed an improvement in the flow uniformity and NH₃/NO composition ratio by 45.1% and 8.7%, respectively, but the total pressure drop increased by 1.24%.

• Journal of the Korean Institute of Gas
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• v.27 no.4
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• pp.102-109
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• 2023

In realizing a hydrogen society, it is important to secure the safety of the hydrogen refueling station, which is the facility where consumers can easily meet hydrogen. The hydrogen refueling station consists of compressed gas facilities that store high-pressure hydrogen, and there is a risk that the high-pressure compressed gas facility will rupture due to a fire explosion due to hydrogen leakage in the facility or the influence of surrounding fires. Accordingly, the Korea Gas Safety Corporation is making every effort to find out risk factors from the installation stage, reflect them in the design, and secure safety through legal inspection. In this study, a TNT explosion demonstration test using a protection wall was conducted to confirm the safety effect of the protection wall installed at the hydrogen refueling station, and the empirical test results were compared and verified using FLACS-CFD, a CFD program. As a result of the empirical test and CFD analysis, it was confirmed that the effect of reducing the explosion over-pressure at the rear end of the protection wall decreased from 50% to up to 90% depending on the location, but the effect decreased when it exceeded a certain distance. The results of the empirical test and computer analysis for verifying the safety of the protection wall will be used in proposals for optimizing the protection wall standards in the future.

• Journal of the Computational Structural Engineering Institute of Korea
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• v.37 no.2
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• pp.85-93
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• 2024

In this paper, we propose a method for establishing a state-space equation model for the motion analysis of floating structures subjected to wave loads, by applying system-identification techniques. Traditionally, the motion of floating structures has been analyzed in the time domain by integrating the Cummins equation over time, which utilizes a convolution integral term to account for the effects of the retardation function. State-space equation models have been studied as a way to efficiently solve floating-motion equations in the time domain. The proposed approach outlines a procedure to derive the target transfer function for the load-displacement input/output relationship in the frequency domain and subsequently determine the state-space equation that closely approximates it. To obtain the state-space equation, the method employs the N4SID system-identification method and an optimization approach that treats the coefficients of the numerator and denominator polynomials as design variables. To illustrate the effectiveness of the proposed method, we applied it to the analysis of a single-degree-of-freedom model and the motion of a six-degree-of-freedom barge. Our findings demonstrate that the presented state-space equation model aligns well with the existing analysis results in both the frequency and time domains. Notably, the method ensures computational accuracy in the time-domain analysis while significantly reducing the calculation time.

• Journal of the Korea Organic Resources Recycling Association
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• v.32 no.2
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• pp.37-48
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• 2024

Wastewater treatment plants (WWTPs) are obligated to reduce carbon emissions as a part of public sector greenhouse gas (GHG) emission reduction targets. However, Sewage Statistics(2022) shows that CO₂ emissions per wastewater treatment volumes have decreased by only 3.03 % compared to 2020, which is far from enough to meet the Nationally Determined Contribution (NDC) targets. This study aimed to find operational conditions of biological reactors that minimize total carbon footprint (CFP). Total CFP considers both direct emissions from biological processes and indirect emissions from energy consumption. A study was conducted using a computer simulation program which is called as EQPS for a 4-stage BNR WWTP. The results showed that total CFP was reduced by 10.97% compared to the design condition when the mixed liquor recirculation (MLR) was set to 100 % of the influent flow. The N₂O emission factor (EF) of the target WWTP was calculated to be 0.138-0.199 %, which is significantly lower than the IPCC default value of 1.6 %. This study proposes a method to minimize total CFP in WWTPs by optimizing biological reactor operation and emphasizes the need for further research on N₂O emission reduction.

• Smart Media Journal
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• v.13 no.6
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• pp.9-15
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• 2024

In recent trends, there has been an increase in 'Qshing' attacks, a hybrid form of phishing that exploits fake QR (Quick Response) codes impersonating government agencies to steal personal and financial information. Particularly, this attack method is characterized by its stealthiness, as victims can be redirected to phishing pages or led to download malicious software simply by scanning a QR code, making it difficult for them to realize they have been targeted. In this paper, we have developed a classification technique utilizing machine learning algorithms to identify the maliciousness of URLs embedded in QR codes, and we have explored ways to integrate this with existing QR code readers. To this end, we constructed a dataset from 128,587 malicious URLs and 428,102 benign URLs, extracting 35 different features such as protocol and parameters, and used AutoML to identify the optimal algorithm and hyperparameters, achieving an accuracy of approximately 87.37%. Following this, we designed the integration of the trained classification model with existing QR code readers to implement a service capable of countering Qshing attacks. In conclusion, our findings confirm that deriving an optimized algorithm for classifying malicious URLs in QR codes and integrating it with existing QR code readers presents a viable solution to combat Qshing attacks.

• Journal of the Microelectronics and Packaging Society
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• v.31 no.2
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• pp.63-68
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• 2024

With the increasing use of transparent displays and flexible devices, polymer substrates offering excellent flexibility and strength are in demand. Since polymers are sensitive to heat, precise temperature control during the process is necessary. The study proposes a temperature measurement system for the laser processing area within the polymer base, aiming to address the drawbacks of using these polymer bases in laser-based selective processing technology. It presents the possibility of optimizing the process conditions of the polymer substrate through local temperature change measurements in the laser processing area. We developed and implemented the PDPT (Photodiode-based Planck Thermometry) to measure temperature in the laser-processing area. PDPT is a non-destructive, contact-free system capable of real-time measurement of local temperature increases. We monitored the temperature fluctuations during the laser processing of the polymer substrate. The study shows that the proposed laser-based temperature measurement technology can measure real-time temperature during laser processing, facilitating optimal production conditions. Furthermore, we anticipate the application of this technology in various laser-based processes, including essential micro-laser processing and 3D printing.

• Journal of the Korea Computer Graphics Society
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• v.30 no.3
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• pp.149-158
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• 2024

Photo booths have traditionally provided a fun and easy way to capture and print photos to cherish memories. These booths allow individuals to capture their desired poses and props, sharing memories with friends and family. To enable diverse expressions, generative AI-powered photo booths have emerged. However, existing AI photo booths face challenges such as difficulty in taking group photos, inability to accurately reflect user's poses, and the challenge of applying different concepts to individual subjects. To tackle these issues, we present CINEMAPIC, a photo booth system that allows users to freely choose poses, positions, and concepts for their photos. The system workflow includes three main steps: pre-processing, generation, and post-processing to apply individualized concepts. To produce high-quality group photos, the system generates a transparent image for each character and enhances the backdrop-composited image through a small number of denoising steps. The workflow is accelerated by applying an optimized diffusion model and GPU parallelization. The system was implemented as a prototype, and its effectiveness was validated through a user study and a large-scale pilot operation involving approximately 400 users. The results showed a significant preference for the proposed system over existing methods, confirming its potential for real-world photo booth applications. The proposed CINEMAPIC photo booth is expected to lead the way in a more creative and differentiated market, with potential for widespread application in various fields.

• Journal of the Institute of Electronics Engineers of Korea SD
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• v.46 no.1
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• pp.98-106
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• 2009

This work proposes a 1280-RGB $\times$ 800-Dot 70.78mW 0.l3um CMOS LCD driver IC (LDI) for high-performance 16M-color low temperature poly silicon (LTPS) thin film transistor liquid crystal display (TFT-LCD) systems such as ultra mobile PC (UMPC) and mobile applications simultaneously requiring high resolution, low power, and small size at high speed. The proposed LDI optimizes power consumption and chip area at high resolution based on a resistor-string based architecture. The single column driver employing a 1:12 MUX architecture drives 12 channels simultaneously to minimize chip area. The implemented class-AB amplifier achieves a rail-to-rail operation with high gain and low power while minimizing the effect of offset and output deviations for high definition. The supply- and temperature-insensitive current reference is implemented on chip with a small number of MOS transistors. A slew enhancement technique applicable to next-generation source drivers, not implemented on this prototype chip, is proposed to reduce power consumption further. The prototype LDI implemented in a 0.13um CMOS technology demonstrates a measured settling time of source driver amplifiers within 1.016us and 1.072us during high-to-low and low-to-high transitions, respectively. The output voltage of source drivers shows a maximum deviation of 11mV. The LDI with an active die area of $12,203um{\times}1500um$ consumes 70.78mW at 1.5V/5.5V.