• Textile Coloration and Finishing
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• v.9 no.3
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• pp.18-26
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• 1997

Polyester microfiber fabrics were decomposed at 100, 110, and 12$0^{\circ}C$ in saturated CaO/ethylene glycol solutions(CaO/EG), and the characteristics of decomposition kinetics were discussed in comparison to those by hot aqueous hydroxide solution(NaOH). The Arrhenius pre-exponential factor(A) was 9.17x $10^{14}$/M $sec^{-1}$and the activation energy($E_{a}$) was 8.19kcal/mol. While the A value was 1.947x $10^{14}$/M $sec^{-1}$ and the ($E_{a}$ value was about 15~19kcal/mol in NaOH-PET decomposition reaction. The much higher A value of the CaO/EG-PET decomposition reaction means that CaO/EG-PET decomposition reaction will occur in a less selective fashion in comparison to the NaOH-PET decomposition reaction. On the other hand, the lower ($E_{a}$) value of the CaO/EG-PET decomposition reaction than that of the NaOH-PET decomposition reaction means that CaO/EG-PET decomposition reaction is less sensitive on the variation of temperature than NaOH-PET decomposition reaction.

• Korean Journal of Soil Science and Fertilizer
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• v.46 no.3
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• pp.203-208
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• 2013

This study was conducted to investigate decomposition of livestock manure in soils cultivated with Chinese cabbage along an alitude gradient. The experiments were conducted in Kangreung (17 m above sea level), Bongpyeong (430 m above sea level), and Daekwanryeong (800 m above the sea level) in order to assess the decomposition rate and accumulations of livestock manures depending on different altitudes. During chinese cabbage cultivation, the decomposition ratios of organic matter derived form livestock manure expressed as % of the initial organic matter content were 42~48% for Kangreung, 26~29% for Bongpyeong and 10~14% for Daekwanryeong. Changes in air temperature with altitude might be a main factor affecting manure decomposition rates.

• Bulletin of the Korean Mathematical Society
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• v.59 no.3
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• pp.781-787
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• 2022

In this paper, we show that under certain conditions the Wedderburn decomposition of a finite semisimple group algebra 𝔽_qG can be deduced from a subalgebra 𝔽_q(G/H) of factor group G/H of G, where H is a normal subgroup of G of prime order P. Here, we assume that q = p^r for some prime p and the center of each Wedderburn component of 𝔽_qG is the coefficient field 𝔽_q.

• KIEE International Transactions on Electrophysics and Applications
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• v.3C no.2
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• pp.48-54
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• 2003

To evaluate the radiation degradation of ethylene propylene rubber (EPR), radiation effects on EPR were investigated by using dielectric analysis and thermal-gravimetric analysis. Permittivity, loss factor, tan$\delta$, and thermal decomposition temperature were observed for ${\gamma}$-ray irradiated EPR. As the radiation dose was increased, the peak temperature of the loss factor and tans of EPR were increased and loss factor and tan$\delta$ at peak temperature were decreased. Activation energies were calculated using loss factor and thermal decomposition for ${\gamma}$-ray irradiated EPR as well. The trends of both calculated activation energies showed the same tendencies as radiation dose was increased.

• 제어로봇시스템학회:학술대회논문집
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• 1992.10b
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• pp.245-250
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• 1992

In this paper, we present a nev algorithm for the fast computation of the discrete cosine transform(DCT). This algorithm consists of the three dimensional prime factor-decomposed algorithm(PFA) and three dimensional common factor-decomposed algorithm(CFA). We can compute N-point DCT for the number N decomposable Into three relative prime numbers using PFA and into three common numbers using CFA. We also show input and output index mapping for the three decomposition. it results in requiring fever multiplicaions than the previous algorithms. Particularly, for the large number N, it is more powerful in reducing the number of multiplication.

• Journal of Climate Change Research
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• v.9 no.4
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• pp.407-421
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• 2018

In this paper, I analyze the GHG (greenhouse gas) emission factor of the domestic railway transportation sector using the LMDI (Log Mean Divisia Index) methodology. These GHG factors are the emission factor effect, energy intensity effect, transportation intensity effect, and economic activity effect. The analysis period was from 2011 to 2016, and the analysis objects were an intercity railway, wide area railway, and urban railway. The results show that the GHG emission of railway transportation sector decreased during these 6 years. The factors decreasing the GHG emission are the emission factor effect, energy intensity effect, and transportation intensity effect, while the factor increasing the GHG emission is the economic activity effect.

• Smart Structures and Systems
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• v.17 no.3
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• pp.413-429
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• 2016

The recent research on proper orthogonal decomposition (POD) has revealed the linkage between proper orthogonal modes and linear normal modes. This paper presents an investigation into the modal identifiability of an instrumented cable-stayed bridge using an adapted POD technique with a band-pass filtering scheme. The band-pass POD method is applied to the datasets available for this benchmark study, aiming to identify the vibration modes of the bridge and find out the so-called deficient modes which are unidentifiable under normal excitation conditions. It turns out that the second mode of the bridge cannot be stably identified under weak wind conditions and is therefore regarded as a deficient mode. To judge if the deficient mode is due to its low contribution to the structural response under weak wind conditions, modal coordinates are derived for different modes by the band-pass POD technique and an energy participation factor is defined to evaluate the energy participation of each vibration mode under different wind excitation conditions. From the non-blind datasets, it is found that the vibration modes can be reliably identified only when the energy participation factor exceeds a certain threshold value. With the identified threshold value, modal identifiability in use of the blind datasets from the same structure is examined.

• Journal of Korea Multimedia Society
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• v.22 no.4
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• pp.443-454
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• 2019

In recent years, there has been active research on a recommender system that considers three or more inputs in addition to users and goods, making it a multi-dimensional array, also known as a tensor. The main issue with using tensor is that there are a lot of missing values, making it sparse. In order to solve this, the tensor can be shrunk using the tensor decomposition algorithm into a lower dimensional array called a factor matrix. Then, the tensor is reconstructed by calculating factor matrices to fill original empty cells with predicted values. This is called tensor reconstruction. In this paper, we propose a user-based Top-K recommender system by normalized PARAFAC tensor reconstruction. This method involves factorization of a tensor into factor matrices and reconstructs the tensor again. Before decomposition, the original tensor is normalized based on each dimension to reduce overfitting. Using the real world dataset, this paper shows the processing of a large amount of data and implements a recommender system based on Apache Spark. In addition, this study has confirmed that the recommender performance is improved through normalization of the tensor.

• Applied Chemistry for Engineering
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• v.24 no.2
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• pp.161-164
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• 2013

In this study, the application of recovered metals from spent batteries by extraction was investigated for ozone decomposition as a catalyst. Among the recovered metals, Mn contents was the most important factor for ozone decomposition. It was also found that the deactivation rate of the catalyst was dependent on the Zn contents, while K contents and activities were not perfectly correlated for ozone decomposition. In addition, the catalytic activity the $TiO_2$ added catalyst was decreased, due to the reduction of Mn contents. The structural characteristics of maganase oxide was not associated with the catalytic activity for ozone decomposition.

• Journal of Multimedia Information System
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• v.2 no.2
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• pp.215-222
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• 2015

Epileptic Seizure is a popular brain disease in the world. It affects the nervous system and the activities of brain function that make a person who has seizure signs cannot control and predict his actions. Based on the Electroencephalography (EEG) signals which are recorded from human or animal brains, the scientists use many methods to detect and recognize the abnormal activities of brain. Tucker model is investigated to solve this problem. Tucker decomposition is known as a higher-order form of Singular Value Decomposition (SVD), a well-known algorithm for decomposing a matric. It is widely used to extract good features of a tensor. After decomposing, the result of Tucker decomposition is a core tensor and some factor matrices along each mode. This core tensor contains a number of the best information of original data. In this paper, we used Tucker decomposition as a way to obtain good features. Training data is primarily applied into the core tensor and the remained matrices will be combined with the test data to build the Tucker base that is used for testing. Using core tensor makes the process simpler and obtains higher accuracies.