• Bulletin of the Korean Chemical Society
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• v.35 no.2
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• pp.365-370
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• 2014

For real-time monitoring of colloidal nanoparticles (NPs) in aqueous media, a light sheet type dark-field microscopy system combined with a microfluidic concentration gradient generator (${\mu}FCGG$-LSDFM) was developed. Various concentrations of colloidal Au NPs were simultaneously generated with the iFCGG and characterized with the LSDFM setup. The number concentrations and hydrodynamic size distributions were measured via particle counting and tracking analysis (PCA and PTA, respectively) approaches. For the 30 nm Au NPs used in this study, the lower detection limit of the LSDFM setup was 3.6 ng/mL, which is about 400 times better than that of optical density measurements under the same ${\mu}FCGG$ system. Additionally, the hydrodynamic diameter distribution of Au NPs was estimated as $39.7{\pm}12.2nm$ with the PTA approach, which agrees well with DLS measurement as well as the manufacturer's specification. We propose this ${\mu}FCGG$-LSDFM setup with features of automatic generation of NP concentration gradient and real-time monitoring of their physicochemical characteristics (e.g., number concentration, and hydrodynamic size distribution) as an important component of future high-throughput screening or high-content analysis platforms of nanotoxicity.

• Advanced Industrial SCIence
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• v.2 no.3
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• pp.29-36
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• 2023

The purpose of this study is to present basic data for hair color work plans that can consistently produce hair color design products for designers through analysis of gradient techniques among hair color design techniques. The research method was to select 10 photos of women that appeared in mass media from 2022 to September 15, 2023, extract color chips and RGB values using the Eyedropper Tool in Adobe Photoshop CS6, and convert the RGB values of the color chips into Munsell Conversion ( The data was converted into HV/C values of version 12.1.13a). Based on the extracted data, the gradient hair colors of female pop stars were analyzed by displaying the data on a color scale. As a result, in the I.R.I color scheme image scale, the image of female pop stars was more hard than soft. In addition, it was confirmed that the focus was on static rather than dynamic. Color matching images according to hair color were extracted with adjectives such as noble, decent, elegant, and subtle. Three hairstyles were created using this theme.

• Proceedings of the KIEE Conference
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• 2001.07b
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• pp.626-628
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• 2001

고 기록 밀도의 HDD를 위해서는 HDD Media의 선 기록 밀도와 트랙 밀도를 높여야 한다. 선기록 밀도를 높이기 위해서는 HDD Write Head의 Field Gradient가 커야하고, 트랙 밀도를 높이기 위해서는 Write Head의 Aspect Ratio가 작아져야 한다. 본 연구에서는 3차원 유한 요소법을 이용하여 Write Head의 재료의 자기적 성질과 형상에 따른 고 기록 밀도용 Pole Tip Write Head를 설계하였다.

• Journal of Korea Multimedia Society
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• v.18 no.10
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• pp.1164-1171
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• 2015

The edge preserving method is important for image storage and geometric transformation. In this paper, we propose a new edge preserving method using HOG-Guide filter for image segmentation. In our approach, we extract edge information using gradient histogram to set HOG guide line. Then, we use HOG guide line to smooth image. With two to four iterations of smoothing operations, we finally obtain desirable edge preserved image. Our experimental results showed good performances showing that our proposed method is better than other methods.

• Proceedings of the Korea Society for Simulation Conference
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• 2001.10a
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• pp.223-230
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• 2001

This paper proposes a new contour detection method and adaptive reconstruction scheme for the cylindrical organs, such as blood vessels or arteries. Furthermore, we present java-based navigation controller which has been built to examine the inside of cylindrical objects. Tn the preprocessing procedure, a few preprocessing image filters are applied in order to remove unwanted artifacts from the medical images and to estimate threshold values for the object of interest. We define a context-free grammar, which is proper fur properties of contours of cylindrical objects. In the next procedure, we extract contours using advanced radial gradient method and represent contours as context-free grammar derivation trees. We build polygons between two contours efficiently by traversing the derivations trees of the contours. We fly through the reconstructed virtual models using java-based navigation controller and VRML viewer.

• Journal of the Korea Computer Graphics Society
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• v.11 no.1
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• pp.40-49
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• 2005

Several optimization techniques have been proposed for volume ray casting, but these cannot achieve real-time frame rates. In addition, it is difficult to apply them to some applications that require perspective projection. Recently, hardware-based methods using 3D texture mapping are being used for real-time volume rendering. Although rendering speed approaches real time, the larger volumes require more swapping of volume bricks for the limited texture memory. Also, image quality deteriorates compared with that of conventional volume ray casting. In this paper, we propose a data structure for real-time volume ray casting named PERM (Precomputed dEnsity and gRadient Map). The PERM stores interpolated density and gradient vector for quantized cells. Since the information requiring time-consuming computations is stored in the PERM, our method can ensure interactive frame rates on a consumer PC platform. Our method normally produces high-quality images because it is based on conventional volume ray casting.

• Smart Media Journal
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• v.12 no.10
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• pp.9-18
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• 2023

Harvest forecasting is the great demand of multiple aspects like temperature, rain, environment, and their relations. The existing study investigates the climate conditions and aids the cultivators to know the harvest yields before planting in farms. The proposed study uses federated learning. In addition, the additional widespread techniques such as bagging classifier, extra tees classifier, linear discriminant analysis classifier, quadratic discriminant analysis classifier, stochastic gradient boosting classifier, blending models, random forest regressor, and AdaBoost are utilized together. These presented nine algorithms achieved exemplary satisfactory accuracies. The powerful contributions of proposed algorithms can create exact harvest forecasting. Ultimately, we intend to compare our study with the earlier research's results.

• Smart Media Journal
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• v.13 no.4
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• pp.9-15
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• 2024

Tree-based algorithms have been the dominant methods used build a prediction model for tabular data. This also includes personal credit data. However, they are limited to compatibility with categorical and numerical data only, and also do not capture information of the relationship between other features. In this work, we proposed an ensemble model using the Transformer architecture that includes text features and harness the self-attention mechanism to tackle the feature relationships limitation. We describe a text formatter module, that converts the original tabular data into sentence data that is fed into FinBERT along with other text features. Furthermore, we employed FT-Transformer that train with the original tabular data. We evaluate this multi-modal approach with two popular tree-based algorithms known as, Random Forest and Extreme Gradient Boosting, XGBoost and TabTransformer. Our proposed method shows superior Default Recall, F1 score and AUC results across two public data sets. Our results are significant for financial institutions to reduce the risk of financial loss regarding defaulters.

• Environmental Engineering Research
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• v.10 no.1
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• pp.1-6
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• 2005

Hexavalent chromium in aqueous solutions was successfully removed via sorption and reduction in the presence of waste leaves. Cr(VI) removal followed a first-order reaction, and removal rates were proportional to the amount of waste leaves used in the tests. Most of Cr(VI) were removed via sorption in early stages of the tests, but the reduction reaction played a significant role in Cr(VI) removal later. Solution pHs were continuously decreased due to the microbial activity, which was induced from the microorganisms attached on waste leaves. The decreased solution pHs further enhanced the sorption and reduction of Cr(VI). To characterize the microorganisms found in the tests, a denaturing gradient gel electrophoresis (DGGE) method was used. The majority of microorganisms were composed of Bacillus sp. which can reduce Cr(VI). Thus, waste leaves can be effective reactive media for the treatment of Cr(VI) in the subsurface.

• The Journal of Asian Finance, Economics and Business
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• v.9 no.10
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• pp.189-200
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• 2022

The gig economy offers many advantages, such as flexibility, variety, independence, and lower cost. However, there are also safety concerns, lack of regulations, uncertainty, and unsatisfactory services, causing people to voice their opinion on social media. This paper aims to explore the sentiments of consumers concerning gig economy services (Grab, Foodpanda and Airbnb) through the analysis of social media. First, Vader Lexicon was used to classify the comments into positive, negative, and neutral sentiments. Then, the comments were further classified into three machine learning algorithms: Support Vector Machine, Light Gradient Boosted Machine, and Logistic Regression. Results suggested that gig economy services in Malaysia received more positive sentiments (52%) than negative sentiments (19%) and neutral sentiments (29%). Based on the three algorithms used in this research, LGBM has been the best model with the highest accuracy of 85%, while SVM has 84% and LR 82%. The results of this study proved the power of text mining and sentiment analysis in extracting business value and providing insight to businesses. Additionally, it aids gig managers and service providers in understanding clients' sentiments about their goods and services and making necessary adjustments to optimize satisfaction.