• Applied Chemistry for Engineering
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• v.30 no.5
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• pp.562-568
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• 2019

Cylindrical shape extrudates of calcium silicate hydrate (CSH) were prepared using different percentages of polyvinyl alcohol (PVA) / sodium alginate (SA) mixtures as binders and an aqueous solution containing 6% $H_3BO_3$ and 3% $CaCl_2$ was used as a cross linking agent. As the quantity of alginate increases, the phosphate removal efficiency and capacity were decreased. Among four different extrudate samples, the sample prepared by 8% PVA + 2% SA showed the highest phosphate removal efficiency (59.59%) and capacity (29.97 mg/g) at an initial phosphate concentration of 100 ppm and 2.0 g/L adsorbent dosage. Effects of the adsorbent dosage, contact time and initial phosphate concentration on the sample were further studied. The removal efficiency and capacity obtained by a 4.0 g/L adsorbent dose at an initial phosphate concentration of 100 ppm in 3 h were 79.38% and 19.96 mg/g, respectively. The experimental data of kinetic and isotherm measurements followed the pseudo-second-order kinetic equation and Langmuir isotherm model, respectively. These results suggested that the phosphate removal was processed via a chemisorption and a monolayer coverage of phosphate anions was on the CSH surface. The maximum adsorption capacity ($q_{max}$) was calculated as 23.87 mg/g from Langmuir isotherm model.

• Journal of Magnetics
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• v.21 no.4
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• pp.660-665
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• 2016

The electromagnetic apparatus plays an important role in high power electrical systems. It is of great importance to provide an effective approach for the optimization of the high power electromagnetic apparatus. However, premature convergence and few Pareto solution set of the optimization for electromagnetic apparatus always happen. This paper proposed a modified multi-objective particle swarm optimization algorithm based on the niche sorting strategy. Applying to the modified algorithm, this paper guarantee the better Pareto optimal front with an enhanced distribution. Aiming at shortcomings in the closing bounce and slow breaking velocity of electromagnetic apparatus, the multi-objective optimization model was established on the basis of the traditional optimization. Besides, by means of the improved multi-objective particle swarm optimization algorithm, this paper processed the model and obtained a series of optimized parameters (decision variables). Compared with other different classical algorithms, the modified algorithm has a satisfactory performance in the multi-objective optimization problems in the electromagnetic apparatus.

• The Journal of Asian Finance, Economics and Business
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• v.8 no.5
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• pp.1011-1017
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• 2021

An effective measure to prevent the spread of COVID-19 is wearing masks in public places. This solution is highly recommended in many countries all over the world. The objective of this study is to identify the antecedents of citizens' intention to purchase masks during the COVID-19 pandemic. Based on the theory of planned behavior (TPB), the current study analyzes attitudes toward mask-purchasing, subjective norms, and perceived behavioral control, to assess their impact on intention to purchase masks. In total, six variables are examined: attitude toward mask-wearing, subjective norms, perceived behavioral control, perceived severity, perceived susceptibility, and the intention to wear masks. Data are collected from 243 respondents in Ho Chi Minh City, Vietnam. They were processed through by factor analysis and multiple regressions. The results report that all three factors positively affect citizens' intention to buy masks in the following ascending order: Attitude toward mask-purchasing, subjective norms, and perceived behavioral control. Our study is the first research that applies TPB to investigate citizens' intention to purchase masks to during the COVID-19 pandemic. Moreover, this study provides guidelines to the Vietnamese public managers to combat COVID-19 through the purchase of masks. Shopkeepers would be well advised to observe the intentions of consumers toward masks.

• Journal of the Semiconductor & Display Technology
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• v.17 no.1
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• pp.54-61
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• 2018

In this study, two aspects were analyzed about the robot for removal of explosive devices. First, the cost analyses were performed to provide a reasonable solution for the acquirement of the system. It is processed by an engineering estimate method and the process was consisted of two ways : a system development expense and a mass production unit price. In additions, the resultant cost analyses were compared between the cases excluding and including a mines detection system. As results, in the case of the acquirement of the robot system for removal of explosive devices, it is recommended that the performance by improving the mines detection ability should be considered preferentially rather than the cost because the material cost for the mines detection system is negligible compared to the whole system cost. Second, as a way for improving the system performance by the mine detection function, the carbon nanotube (CNT) based sensor technology was studied in terms of sensitivity and simple productivity with presenting its preliminary experimental results. The detection electrodes were formed by a photolithography method using a photosensitive CNT paste. As results, this method was shown as a scalable and expandable technology for the excellent mines detection sensors.

• Journal of Sensor Science and Technology
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• v.28 no.5
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• pp.329-333
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• 2019

Solution-processed oxide thin-film transistors (TFTs) have garnered great attention, owing to their many advantages, such as low-cost, large area available for fabrication, mechanical flexibility, and optical transparency. Negative bias stress (NBS)-induced instability of sol-gel IGZO TFTs is one of the biggest concerns arising in practical applications. Thus, understanding the bias stress effect on the electrical properties of sol-gel IGZO TFTs and proposing an effective recovery method for negative bias stressed TFTs is required. In this study, we investigated the variation of transfer characteristics and the corresponding electrical parameters of sol-gel IGZO TFTs caused by NBS and positive bias recovery (PBR). Furthermore, we proposed an effective PBR method for the recovery of negative bias stressed sol-gel IGZO TFTs. The threshold voltage and field-effect mobility were affected by NBS and PBR, while current on/off ratio and sub-threshold swing were not significantly affected. The transfer characteristic of negative bias stressed IGZO TFTs increased in the positive direction after applying PBR with a negative drain voltage, compared to PBR with a positive drain voltage or a drain voltage of 0 V. These results are expected to contribute to the reduction of recovery time of negative bias stressed sol-gel IGZO TFTs.

• Journal of the Korean Society of Manufacturing Process Engineers
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• v.18 no.6
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• pp.33-38
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• 2019

Researchers have recently begun to study hot stamping processes to shorten the mold cooling time and improve productivity. These publications explain that the mold cooling time can be reduced by using a curved cooling channel, where the mold surface is processed to a uniform depth, instead of a straight cooling channel that uses the conventional gun drilling machine. This study investigates the characteristics of the front pillar of an automobile after using a mold with a curved cooling channel. To analyze the change in properties, we used a 1.6 mm boron steel blank and heated the prototype at $930^{\circ}C$ for 5 minutes. Next, we formed the prototype with a load of about 500 tons while varying the mold cooling time between 1 and 10 seconds. We subjected each prototype specimen to a tensile strength test, a hardness test, and a tissue surface observation.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.39 no.5
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• pp.313-319
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• 2021

The national geodetic reference frame of Korea was adopted in 2003, which is referenced to ITRF (International Terrestrial Reference Frame) 2000 at the epoch of January 1, 2002. For precise positioning based on the satellites, it should be thoroughly maintained to the newest global reference frame. Other than plate tectonic motion, there are significant events or changes such as earthquakes, antenna replacement, PSD (Post-Seismic Deformation), seasonal variation etc. We processed three years of GNSS (Global Navigation Satellite System) data(60 NGII CORS stations, 51 IGS core stations) to produce daily solutions minimally constrained to ITRF. From the time series of daily solutions, the sites with unexpected discontinuity were identified to set up an event(mostly antenna replacement). The combined solution with minimum constraints was estimated along with the velocity, the offsets, and the periodic signals. The residuals show that the surrounding environment also affects the time series to a certain degree, thus it should be improved eventually. The transformation parameters to ITRF2014 were calculated with stability and consistency, which means the national geodetic reference frame is properly aligned to the global reference frame.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.14 no.12
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• pp.4866-4888
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• 2020

One major and time-consuming task in fish production is obtaining an accurate estimate of the number of fish produced. In most Nigerian farms, fish counting is performed manually. Digital image processing (DIP) is an inexpensive solution, but its accuracy is affected by noise, overlapping fish, and interfering objects. This study developed a catfish recognition and counting algorithm that introduces detection before counting and consists of six steps: image acquisition, pre-processing, segmentation, feature extraction, recognition, and counting. Images were acquired and pre-processed. The segmentation was performed by applying three methods: image binarization using Otsu thresholding, morphological operations using fill hole, dilation, and opening operations, and boundary segmentation using edge detection. The boundary features were extracted using a chain code algorithm and Fourier descriptors (CH-FD), which were used to train an artificial neural network (ANN) to perform the recognition. The new counting approach, based on the geometry of the fish, was applied to determine the number of fish and was found to be suitable for counting fish of any size and handling overlap. The accuracies of the segmentation algorithm, boundary pixel and Fourier descriptors (BD-FD), and the proposed CH-FD method were 90.34%, 96.6%, and 100% respectively. The proposed counting algorithm demonstrated 100% accuracy.

• Journal of the Semiconductor & Display Technology
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• v.20 no.2
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• pp.126-130
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• 2021

The ball grid array is one of the packaging methods that used in high density printed circuit board. Solder void defects caused by voids in the solder ball during the BGA process do not directly affect the reliability of the product, but it may accelerate the aging of the device on the PCB layer or interface surface depending on its size or location. Void inspection is important because it is related in yields with products. The most important process in the optical inspection of solder void is the segmentation process of solder and void. However, there are several segmentation algorithms for the vision inspection, it is impossible to inspect all of images ideally. When X-Ray images with poor contrast and high level of noise become difficult to perform image processing for vision inspection in terms of software programming. This paper suggests the solution to deal with the suggested problem by means of using Mask R-CNN instead of digital image processing algorithm. Mask R-CNN model can be trained with images pre-processed to increase contrast or alleviate noises. With this process, it provides more efficient system about complex object segmentation than conventional system.

• International Journal of Computer Science & Network Security
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• v.21 no.3
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• pp.177-184
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• 2021

All over the world, people are affected by many chronic diseases and medical practitioners are working hard to find out the symptoms and remedies for the diseases. Many researchers focus on the feature detection of the disease and trying to get a better health recommendation system. It is necessary to detect the features automatically to provide the most relevant solution for the disease. This research gives the framework of Health Recommendation System (HRS) for identification of relevant and non-redundant features in the dataset for prediction and recommendation of diseases. This system consists of three phases such as Pre-processing, Feature Selection and Performance evaluation. It supports for handling of missing and noisy data using the proposed Imputation of missing data and noise detection based Pre-processing algorithm (IMDNDP). The selection of features from the pre-processed dataset is performed by proposed ensemble-based feature selection using an expert's knowledge (EFS-EK). It is very difficult to detect and monitor the diseases manually and also needs the expertise in the field so that process becomes time consuming. Finally, the prediction and recommendation can be done using Support Vector Machine (SVM) and rule-based approaches.