• Journal of Powder Materials
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• v.19 no.1
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• pp.60-66
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• 2012

In this study, Platinum(Pt) nanoparticles were synthesized by using polyol process which is one of the liquid phase reduction methods. Dihydrogen hexachloroplatinate (IV) hexahydrate $(H_2PtCl_6{\cdot}6H_2O)$, as a precursor, was dissolved in ethylene glycol and silver nitrate ($AgNO_3$) was added as metal salt for shape control of Pt particle. Also, polyvinylpyrrolidone (PVP), as capping agent, was added to reduce the size of particle and to separate the particles. The size of Pt nanoparticles was evaluated particle size analyzer (PSA). The size and morphology of Pt nanoparticles were observed by transmission electron microscopy (TEM) and high resolution TEM (HRTEM). Synthesized Pt nanoparticles were studied with varying time and temperature of polyol process. Pt nanoparticles have been successfully synthesized with controlled sizes in the range 5-10 and 20-40 nm with cube and multiple-cube shapes.

• International Journal of Computer Science & Network Security
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• v.22 no.7
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• pp.65-74
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• 2022

In natural language processing, commonly used words such as prepositions are referred to as stop-words; they have no inherent meaning and are therefore ignored in indexing and retrieval tasks. The removal of stop-words from Arabic text has a significant impact in terms of reducing the size of a cor- pus text, which leads to an improvement in the effectiveness and performance of Arabic-language processing systems. This study investigated the effectiveness of applying a stop-word lists elimination with normalization as a preprocessing step. The idea was to merge statistical method with the linguistic method to attain the best efficacy, and comparing the effects of this two-pronged approach in reducing corpus size for Ara- bic natural language processing systems. Three stop-word lists were considered: an Arabic Text Lookup Stop-list, Frequency- based Stop-list using Zipf's law, and Combined Stop-list. An experiment was conducted using a selected file from the Arabic Newswire data set. In the experiment, the size of the cor- pus was compared after removing the words contained in each list. The results showed that the best reduction in size was achieved by using the Combined Stop-list with normalization, with a word count reduction of 452930 and a compression rate of 30%.

• Korean Journal of Artificial Intelligence
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• v.11 no.1
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• pp.17-24
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• 2023

With the continuous growth in the amount of data collected and analyzed, deep learning has become increasingly popular for extracting meaningful insights from various fields. However, hardware limitations pose a challenge for achieving meaningful results with limited data. To address this challenge, this paper proposes an algorithm that leverages the characteristics of convolutional neural networks (CNNs) to reduce the size of image datasets by 20% through smoothing and shrinking the size of images using color elements. The proposed algorithm reduces the learning time and, as a result, the computational load on hardware. The experiments conducted in this study show that the proposed method achieves effective learning with similar or slightly higher accuracy than the original dataset while reducing computational and time costs. This color-centric dataset construction method using image smoothing techniques can lead to more efficient learning on CNNs. This method can be applied in various applications, such as image classification and recognition, and can contribute to more efficient and cost-effective deep learning. This paper presents a promising approach to reducing the computational load and time costs associated with deep learning and provides meaningful results with limited data, enabling them to apply deep learning to a broader range of applications.

• 한국전기화학회:학술대회논문집
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• 2005.07a
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• pp.37-42
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• 2005

• Proceedings of the Korean Magnestics Society Conference
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• 2008.12a
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• pp.168.1-168.1
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• 2008

• Transactions of Materials Processing
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• v.22 no.7
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• pp.394-400
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• 2013

Microforming is a very efficient and economical technology to fabricate very small metallic parts in various applications. In order to extend the use of this forming technology for the production of microparts, the size effect, which occurs with the reduction of part size and affects the forming process significantly, must be thoroughly investigated. In this study, the tribological size effect in microforming was studied using modeling and scaled ring compression experiments. A micro-scale friction approach based on the slip-line field theory and lubricant pocket model was used to understand the friction mechanism and explain the tribological size effect. Ring compression tests were performed to analyze the interfacial friction condition from the deformation characteristics of the ring specimens. In addition, finite element analysis results were utilized to quantitatively determine the size-dependent frictional behavior of materials in various process conditions. By comparing theoretical results and experimental measurements for different size factors, the accuracy and reliability of the model were verified.

• Proceedings of the Korean Vacuum Society Conference
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• 2013.08a
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• pp.267.2-267.2
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• 2013

In the citrate reduction method of gold nanoparticle (AuNP) synthesis, pH of the reaction mixture can have a considerable impact on the size and size distribution of AuNPs. In this work, effects of pH variation upon the size and its distribution were examined systematically. As the initial pH was change from 5.5 to 10.5, it showed an optimal pH around 7.5. At this pH, both of the size and the size distribution showed their minimum values, which was verified by transmission electron microscopy and UV-vis spectroscopy. This occurrence of optimal pH was discussed with the results of in situ monitoring pH during the reaction of AuNP synthesis.

• Journal of the Korean Ceramic Society
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• v.42 no.6 s.277
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• pp.432-436
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• 2005

Nickel powders synthesized by the reduction of hydrazine of nickel salts fiom diethanolamine(DEA) solution, and investigated the morphological characteristics of nickel powders with the addition of hydrazine, reaction temperature, the composition of mixed solvents. The addition of hydrazine in DEA solution largely affected on size control of nickel powders. Under $N_2H_4/Ni^{2+}$ molar ratio= 1.5 and 2.0 conditions, spherical nickel powders in the submicron range obtained, owing to higher the reduction rate. An increase of temperature increased the size of nickel particles. At $220^{\circ}C$ for 40 min, the nickel powders composed of polyhedral particles with high crystalline in the submicron range. The mixed volume ratio of TEA to DEA affected on the increase of particle size and the inhibition of agglomerate between particles.

• The Journal of the Acoustical Society of Korea
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• v.22 no.8
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• pp.703-710
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• 2003

Because of their human-like synthesized speech quality, recently Corpus-Based Text-To-Speech(CB-TTS) have been actively studied worldwide. However, due to their large size speech database (DB), their application is very restricted. In this paper we propose and evaluate three DB reduction algorithms to which are designed to solve the above drawback. The first method is based on a K-means clustering approach, which selects k-representatives among multiple instances. The second method is keeping only those unit instances that are selected during synthesis, using a domain-restricted text as input to the synthesizer. The third method is a kind of hybrid approach of the above two methods and is using a large text as input in the system. After synthesizing the given sentences, the used unit instances and their occurrence information is extracted. As next step a modified K-means clustering is applied, which takes into account also the occurrence information of the selected unit instances, Finally we compare three pruning methods by evaluating the synthesized speech quality for the similar DB reduction rate, Based on perceptual listening tests, we concluded that the last method shows the best performance among three algorithms. More than this, the results show that the last method is able to reduce DB size without speech quality looses.

• Journal of the Institute of Convergence Signal Processing
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• v.8 no.3
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• pp.192-198
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• 2007

In this paper, a new method to reduce the size of ROM in the direct digital frequency synthesizer(DDFS) is proposed. The new ROM compression method can reduce the ROM size by using the two ROM. The quantized value of sine is stored by the quantized-ROM(Q-ROM) and the differential ROM(D-ROM). To reduce the ROM size, we use the differential quantization technique with this two ROM. First, we quantize the quarter sine wave with the $2^L$ address and store the quantized value at the Q-ROM. Second, after the $2^L$ address are equally divided into $2^M$ sampling intervals, the sampling value is quantized. And the D-ROM store only the difference between this quantized value and the Q-ROM. So the total size of the ROM in the proposed DDFS is significantly reduced compared to the original ROM. The ROM compression ratio of 67.5% is achieved by this method. Also, the power consumption is affected mostly by this ROM reduction.