• Asian Journal of Atmospheric Environment
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• v.2 no.2
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• pp.75-80
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• 2008

A new-type apparatus decomposing volatile organic compounds (VOCs) using a combination system of an electrical exothermic SiC honeycomb and a catalytic filter was developed. This linear combination system is very useful to the catalytic decomposition of VOCs, because the gas involving VOCs is well heated in the SiC honeycomb and then flows into the catalytic filter. In the proposed apparatus, the outlet gas temperatures of SiC honeycomb maintained at ca. $300^{\circ}C$ after 5 min from the starting of applying electric current, and sufficient for the catalytic degradation of VOC components, i.e. toluene, isopropanol, methyl ethyl ketone and ethyl acetate. The average decomposition rate of total VOCs exhausted from a printing factory was 85% using pt catalyst at SV=19,000 in this system.

• Journal of Electrical Engineering and Technology
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• v.13 no.5
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• pp.1807-1813
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• 2018

In this paper, the fault line selection and location problems of single line-to-ground (SLG) fault in distribution network are addressed. Firstly, the adaptive filtering property for empirical mode decomposition is formulated. Then in view of the different characteristics showed by the intrinsic mode functions(IMF) under different fault inception angles obtained by empirical mode decomposition, the sign of peak value about the low-frequency IMF and the capacitance transient energy is chosen as the fault line selection criteria according to the different proportion occupied by the low-frequency components. Finally, the fault location is determined based upon the comparison result with adjacent fault passage indicators' (FPI) waveform on the strength of the interaction between the distribution terminal unit(DTU) and the FPI. Moreover, the logic nodes regarding to fault line selection and location are newly expanded according to IEC61850, which also provides reference to acquaint the DTU or FPI's function and monitoring. The simulation results validate the effectiveness of the proposed fault line selection and location methods.

• Applied Chemistry for Engineering
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• v.32 no.6
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• pp.706-710
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• 2021

In the current research, thermal and catalytic thermogravimetric (TG) analysis of polyethylene terephthalate (PET) over natural zeolite (NZ), olivine, bentonite, HZSM-5, and HAl-MCM-41 were investigated using a TG analyzer and model-free kinetic analysis. Catalytic TG analysis of PET was carried out at multi-heating rates, 10, 20, 30, and 40 ℃/min, under nitrogen atmosphere. Apparent activation energy (Ea) values for the thermal and catalytic pyrolysis of PET were calculated using Flynn-Wall-Ozawa method. Although natural catalysts, NZ, olivine, and bentonite, could not lead the higher PET decomposition efficiency than synthetic zeolites, HZSM-5 and HAl-MCM-41, maximum decomposition temperatures on the differential TG (DTG) curves for the catalytic pyrolysis of PET, 436 ℃ over olivine, 435 ℃ over bentonite, and 434 ℃ over NZ, at 10 ℃/min, were definitely lower than non-catalytic pyrolysis. Calculated Ea values for the catalytic pyrolysis of PET over natural catalysts, 177 kJ/mol over olivine, 168 kJ/mol over bentonite, and 171 kJ/mol over NZ, were also not lower than those over synthetic zeolites, however, those were also much lower than the thermal decomposition, suggesting their feasibility as the proper and cost-effective catalysts on the pyrolysis of PET.

• Nuclear Engineering and Technology
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• v.55 no.3
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• pp.827-838
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• 2023

Centrifugal pump is a key part of nuclear power plant systems, and its health status is critical to the safety and reliability of nuclear power plants. Therefore, fault diagnosis is required for centrifugal pump. Traditional fault diagnosis methods have difficulty extracting fault features from nonlinear and non-stationary signals, resulting in low diagnostic accuracy. In this paper, a new fault diagnosis method is proposed based on the improved particle swarm optimization (IPSO) algorithm-based variational modal decomposition (VMD) and relevance vector machine (RVM). Firstly, a simulation test bench for rotor faults is built, in which vibration displacement signals of the rotor are also collected by eddy current sensors. Then, the improved particle swarm algorithm is used to optimize the VMD to achieve adaptive decomposition of vibration displacement signals. Meanwhile, a screening criterion based on the minimum Kullback-Leibler (K-L) divergence value is established to extract the primary intrinsic modal function (IMF) component. Eventually, the factors are obtained from the primary IMF component to form a fault feature vector, and fault patterns are recognized using the RVM model. The results show that the extraction of the fault information and fault diagnosis classification have been improved, and the average accuracy could reach 97.87%.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.16 no.2
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• pp.125-130
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• 2016

The proposal of this study is a fast version of the conventional extreme learning machine (ELM), called pseudoinverse matrix decomposition based incremental ELM (PDI-ELM). One of the main problems in ELM is to determine the number of hidden nodes. In this study, the number of hidden nodes is automatically determined. The proposed model is an incremental version of ELM which adds neurons with the goal of minimization the error of the ELM network. To speed up the model the information of pseudoinverse from previous step is taken into account in the current iteration. To show the ability of the PDI-ELM, it is applied to few benchmark classification datasets in the University of California Irvine (UCI) repository. Compared to ELM learner and two other versions of incremental ELM, the proposed PDI-ELM is faster.

• The Korean Journal of Ecology
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• v.15 no.4
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• pp.387-394
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• 1992

Decomposition in the litteras of platanus orientalis was studied by month in the dam of seoul national university. total amounts of the litter had the tendency to decrease with the laps of the time. Those of crude protein and phosphate contents, however, increased much more than initial amounts. It was throught that the growth of aquatic microbes gave rise to increase them. Dry weight, organic matter and holocellulose tended to decreased gradually. But, the amount of calcium loss increased rapidly since march and then the amoung of potassium and sodium decreased slowly. It was thought that this changing pattern was ascribed to water temperature, the growth of aquaqtic microbes and the leaching of soluble parts by stream current.

• Proceedings of the IEEK Conference
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• 2001.06a
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• pp.317-320
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• 2001

Blind adaptive channel identification of communication channels is a problem of important current theoretical and practical concerns. Recently proposed solutions for this problem exploit the diversity induced by antenna array or time oversampling leading to the so-called, second order statistics techniques. And adaptive blind channel identification techniques based on a off-line least-squares approach have been proposed. In this paper, a new approach is proposed that is based on eigenvalue decomposition. And the eigenvector corresponding to the minimum eigenvalue of the covariance matrix of the received signals contains the channel impulse response. And we present a adaptive algorithm to solve this problem. The performance of the proposed technique is evaluated over real measured channel and is compared to existing algorithms.

• Journal of the Korean Magnetic Resonance Society
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• v.4 no.2
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• pp.116-124
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• 2000

Singular value decomposition (SVD) has been used during past few decades in the advanced NMR data processing and in many applicable areas. A new modified SVD, piecewise polynomial truncated SVD (PPTSVD) was developed far the large solvent peak suppression and noise elimination in U signal processing. PPTSVD consists of two algorithms of truncated SVD (TSVD) and L$_1$ problems. In TSVD, some unwanted large solvent peaks and noises are suppressed with a certain son threshold value while signal and noise in raw data are resolved and eliminated out in L$_1$ problem routine. The advantage of the current PPTSVD method compared to many SVD methods is to give the better S/N ratio in spectrum, and less time consuming job that can be applicable to multidimensional NMR data processing.

• Current Optics and Photonics
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• v.2 no.5
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• pp.413-421
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• 2018

We propose a novel methodology based on the multiplication function to improve the signal-to-noise ratio (SNR) for vibration detection in a phi optical time-domain reflectometer system (phi-OTDR). The extreme-mean complementary empirical mode decomposition (ECEMD) is designed to break down the original signal into a set of inherent mode functions (IMFs). The multiplication function in terms of selected IMFs is used to determine a vibration's position. By this method, the SNR of a phi-OTDR system is enhanced by several orders of magnitude. Simulations and experiments applying the method to real data prove the validity of the proposed approach.

• ETRI Journal
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• v.43 no.1
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• pp.152-162
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• 2021

In the last few years, detection has become a powerful methodology for network protection and security. This paper presents a new detection scheme for data recorded over a computer network. This approach is applicable to the broad scientific field of information security, including intrusion detection and prevention. The proposed method employs bidimensional (time-frequency) data representations of the forms of the short-time Fourier transform, as well as the Wigner distribution. Moreover, the method applies matrix factorization using singular value decomposition and principal component analysis of the two-dimensional data representation matrices to detect intrusions. The current scheme was evaluated using numerous tests on network activities, which were recorded and presented in the KDD-NSL and UNSW-NB15 datasets. The efficiency and robustness of the technique have been experimentally proved.