• Textile Coloration and Finishing
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• v.35 no.4
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• pp.196-205
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• 2023

Water-dispersed pigment is on-going study for without air pollution in the textile and print industry. Primer treatment is essential for the substrate to improve the printing quality of eco-friendly water-dispersed pigment ink. Otherwise in the case of untreated primer, the water-dispersed pigment ink will dry onto the surface and cause defective images. This study was conducted on film substrate coating (primer) to fix eco-friendly water-dispersed pigment ink on film substrate. The drying, bleeding, and color strength of the pigment ink were examined depending on the composition and mixing ratio of the coating solution. The mixing ratio of silica gel in the coating film is increased to 0, 0.5, 1, 2 and 3 and results that DK-1-3 of silica gel ratio of 1 showed the lowest bleeding such as 52%, the letter thickness of 0.76mm and DK-1-5 of SG ratio of 3 showed the highest bleeding such as 304%, the letter thickness of 2.02mm. The mixing ratio of SPA in the coating film is increased to 2.5, 5, 7.5, SPA ratio of 7.5 has a bleeding ratio of 9% and letter thickness of 0.544mm. It showed the closest value to 0.5mm. According to the result, the optimal mixing ratio of binder, polymer coagulant, silica gel is 100:7.5:1.

• Journal of the Microelectronics and Packaging Society
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• v.30 no.4
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• pp.44-49
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• 2023

In the global pursuit of carbon neutrality, the rapid increase in the adoption of electric vehicles (EVs) has led to a corresponding surge in the demand for batteries. To achieve high efficiency in electric vehicles, considerations of weight reduction and battery safety have become crucial factors. Copper and aluminum, both recognized as lightweight materials, can be effectively joined through laser welding. However, due to the distinct physical characteristics of these two materials, the process of joining them poses technical challenges. This study focuses on conducting simulations to identify the optimal laser parameters for welding copper and aluminum, with the aim of streamlining the welding process. Additionally, a Graphic User Interface (GUI) program has been developed using the Python language to visually present the results. Using machine learning image data, this program is anticipated to predict joint success and serve as a guide for safe and efficient laser welding. It is expected to contribute to the safety and efficiency of the electric vehicle battery assembly process.

• 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 Korea Water Resources Association
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• v.57 no.2
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• pp.73-85
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• 2024

Predicting water quality of rivers and reservoirs is necessary for the management of water resources. Artificial Neural Networks (ANNs) have been used in many studies to predict water quality with high accuracy. Previous studies have used Gradient Descent (GD)-based optimizers as an optimizer, an operator of ANN that searches parameters. However, GD-based optimizers have the disadvantages of the possibility of local optimal convergence and absence of a solution storage and comparison structure. This study developed improved optimizers to overcome the disadvantages of GD-based optimizers. Proposed optimizers are optimizers that combine adaptive moments (Adam) and Nesterov-accelerated adaptive moments (Nadam), which have low learning errors among GD-based optimizers, with Harmony Search (HS) or Novel Self-adaptive Harmony Search (NSHS). To evaluate the performance of Long Short-Term Memory (LSTM) using improved optimizers, the water quality data from the Dasan water quality monitoring station were used for training and prediction. Comparing the learning results, Mean Squared Error (MSE) of LSTM using Nadam combined with NSHS (NadamNSHS) was the lowest at 0.002921. In addition, the prediction rankings according to MSE and R² for the four water quality indices for each optimizer were compared. Comparing the average of ranking for each optimizer, it was confirmed that LSTM using NadamNSHS was the highest at 2.25.

• Korean Journal of Environmental Biology
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• v.41 no.4
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• pp.463-472
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• 2023

The insecticidal activities of 27 different commercial products with environmentally friendly organic material(EFOM) against Scotinophara lurida, a major rice pest, were evaluated in the laboratory using spraying methods on plants and insects. Seven plant-derived organic farming materials (EFOM-8, -10, -12, -13, -19, -20, and -26) with high insecticidal effects when sprayed directly on the insect's body rather than on the plant were selected. In the indoor rice pot test, all 7 EFOMs showed an insecticidal rate of over 73.3% under flooding conditions. Notably, EFOM-13 and EFOM-20 demonstrated much higher insecticidal rates, ranging from 1.5 to 1.8 times, in flooding conditions compared to drained conditions. In the semi-paddy field test, EFOM-10 (80% garlic extract), EFOM-13 (62% neem extract), and EFOM-26 (70% sophora extract+28% ethyl alcohol+2% pyrethrum extract) exhibited a higher control value of 88.9% in the irrigated paddy on the 7th day, surpassing the control values in the drained paddy by 1.4 to 1.9 times. The control value in the irrigated rice paddy field sprayed with EFOM-10 reached 86.2% on the 7th day, which was 1.4 times higher than 61.9% in the drained paddy. Taken together, the findings suggest that direct contact of the insect's body with sufficient amounts of spray solution and the maintenance of paddy irrigation can enhance the controlling effect of EFOMs. These findings will be valuable in developing an optimal S. lurida control strategy for application in rice paddy fields in the near future.

• Journal of the Institute of Convergence Signal Processing
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• v.25 no.2
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• pp.94-99
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• 2024

Recently, wind power has been gaining attention as a highly efficient renewable energy source, leading to various technological developments worldwide. Typically, wind power is operated in the form of large wind farms with many wind turbines installed in areas rich in wind resources. However, in developing countries or regions isolated from the power grid, off-grid small wind power systems are emerging as an efficient solution. To efficiently operate and expand off-grid small-scale power systems, the development of real-time monitoring systems is required. For the efficient operation of small wind power systems, it is essential to develop real-time monitoring systems that can actively respond to excessive wind speeds and various environmental factors, as well as ensure the stable supply of produced power to small areas or facilities through an Energy Storage System (ESS). The implemented system monitors turbine RPM, power generation, brake operation, and more to create an optimal operating environment. The developed small wind power system can be utilized in remote road lighting, marine leisure facilities, mobile communication base stations, and other applications, contributing to the development of the RE100 industry ecosystem.

• Journal of Korean Society of Transportation
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• v.18 no.1
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• pp.75-85
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• 2000

In existing models in optimization, the crisp data improve has been used in the objective or constraints to derive the optimal solution, Besides, the subjective environments are eliminated because the complex and uncertain circumstances were regarded as Probable ambiguity, In other words those optimal solutions in the existing models could be the complete satisfactory solutions to the objective functions in the Process of application for industrial engineering methods to minimize risks of decision-making. As a result of those, decision-makers in location Problems couldn't face appropriately with the variation of demand as well as other variables and couldn't Provide the chance of wide selection because of the insufficient information. So under the circumstance. it has been to develop the model for the location and size decision problems of logistics facility in the use of the fuzzy theory in the intention of making the most reasonable decision in the Point of subjective view under ambiguous circumstances, in the foundation of the existing decision-making problems which must satisfy the constraints to optimize the objective function in strictly given conditions in this study. Introducing the Process used in this study after the establishment of a general mixed integer Programming(MIP) model based upon the result of existing studies to decide the location and size simultaneously, a fuzzy mixed integer Programming(FMIP) model has been developed in the use of fuzzy theory. And the general linear Programming software, LINDO 6.01 has been used to simulate, to evaluate the developed model with the examples and to judge of the appropriateness and adaptability of the model(FMIP) in the real world.

• Applied Chemistry for Engineering
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• v.10 no.1
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• pp.24-29
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• 1999

Naturally-occurring iron minerals, goethite, magnetite, and hydrogen peroxide were used to catalyze and initiate Fenton-like oxidation of silica sand contaminated with mixture of diesel and kerosene in batch system. Optimal reaction conditions were investigated by varying pH(3, 7), $H_2O_2$ concentration(0%, 1%, 7%, 15%, 35%), initial contaminant concentration(0.2, 0.5, 1.0 g-mixture of diesel and kerosene/ kg-soil), and iron mineral contents(1, 5, and 10 wt % magnetite or goethite). Contaminant degradations in silica sand-iron mineral-$H_2O_2$ systems were identified by determining total petroleum hydrocarbon(TPH) concentration. The optimal pH of the system was 3. The system which iron minerals were the only iron source was more efficient than the system with $FeSO_4$ solution due to lower $H_2O_2$ consumption. In case of initial contaminant concentration of 1g-contaminant/kg-soil with 5 wt % magnetite, addition of 0%, 1%, 7%, 15%, and 35% of $H_2O_2$ showed 0%, 24.5%, 44%, 52%, and 70% of TPH reduction in 8 days, respectively. When the mineral contents were varied 0, 1, 5, and 10wt%, removal of contaminants were 0%, 33.5%, 50%, and 60% for magnetite and 0%, 29%, 41%, and 53% for goethite, respectively. Reaction of magnetite system showed higher degradation than that of goethite system due to dissolution of iron and mixed presence of iron(II) and iron(III); however, dissolved iron precipitated on the surface of iron mineral and seemed to cause reducing electron transfer activity on the surface and quenching $H_2O_2$. The system using goethite has better treatment efficiency due to less $H_2O_2$ consumption. When cach system was mixed by shaker, removal of contaminants increased by 41% for magnetite and 30% for goethite. Results of this study showed catalyzed $H_2O_2$ system made in-situ treatment of soil contaminated with petroleum possible without addition of iron source since natural soils generally contain iron minerals such as magnetite and goethite.

• Korean Journal of Food Science and Technology
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• v.38 no.6
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• pp.823-828
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• 2006

We established the optimal conditions for the hot water extraction of Camellia japonica compounds based on the yield, the stability (observed by peak changes on an HPLC chromatogram), and the 1,1-diphenyl-1-picrylhydrazyl radical-scavenging activity of the extracts. The extracts were prepared at $90^{\circ}C$ using six solution volumes (ranging from 100 mL to 600 mL), and four different extraction times (10, 30, 60, and 120 min). The results showed that increasing of the extraction volume elevated the radical-scavenging activity of the extracts; however, changes in volume had minimal affects on their yields and their stabilities. An increase in extraction time improved the compound yield; however, it reduced their stability and increased the deterioration of their radical-scavenging activity. Based on our results, we propose the following conditions to be optimal for the hot water extraction of dried C. japonica leaves: a water volume (mL) that is 60 times the weight (g) of the sample at a temperature of $90^{\circ}C$ for 30 min.

• Journal of Applied Biological Chemistry
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• v.61 no.2
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• pp.157-164
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• 2018

The purpose of this study was to develop a kelp (Laminaria japonica) product with optimal sensory and nutritional properties for eating as a snack by investigating its physicochemical properties and conducting sensory evaluation. A preliminary study using tripolypolyphosphate solution found that it was good for removing the fishy smell and for making it soft. We soaked the kelp in 0.3-0.4% sodium tripolyphosphate buffer and tested with or without baking. In searching for the optimal polyphosphate dilution concentration, soaking in 0.3-0.4% sodium tripolyphosphate resulted in the best texture and flavor. As kelp separates into thick or thin samples, thick kelp was best when soaked in 0.4% sodium tripolyphosphate buffer and thin soaked in 0.3%. The kelp snack made from the thick one (over 221 mm thickness) was better than the thin one. Baking improved the moisture, texture and feel of the kelp snack. Tripolyphosphate treatment affected protein contents and texture softening. The differences by baking and tripolyphosphate treatment were shown with electromicroscopic image. Kelp snacks with added sweet and hot taste were preferred to sour taste. In conclusion, in making kelp snacks, it is advisable to use a thick kelp, 0.3-0.4% sodium tripolyphosphate, and baking treatment for better texture and feel. This kelp snack has low fishy smell, better taste and soft feel. Further research is needed to support sea food's importance, and usefulness of the kelp snack to help prevent goiter in inland province citizens.