• Journal of the Korea Institute of Information and Communication Engineering
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• v.24 no.2
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• pp.276-284
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• 2020

This paper proposes a new convolutional neural network (CNN) based spectrum sensing technique for cognitive radio communications. The proposed technique determines the existence of the primary user (PU) by using energy detection without any prior knowledge of the PU's signal. In the proposed method, the received signal is high-rate sampled to sense the entire spectrum bands of interest. After that, fast Fourier transform (FFT) of the signal converts the time domain signal to frequency domain spectrum and by stacking those consecutive spectrums, a 2 dimensional signal is made. The 2 dimensional signal is cut by the sensing channel bandwidth and inputted to the CNN. The CNN determines the existence of the primary user. Since there are only two states (existence or non-existence), binary classification CNN is used. The performance of the proposed method is examined through computer simulation and indoor experiment. According to the results, the proposed method outperforms the conventional threshold-based method by over 2 dB.

• 한국신재생에너지학회:학술대회논문집
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• 2005.06a
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• pp.306-309
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• 2005

One of the most critical issues in sol id oxide fuel cell (SOFC)running on hydrocarbon fuels is the risk of carbon formation from the fuel gas. The simple method to reduce the risk of carbon formation from the reactions is to add steam to the fuel stream, leading to the carbon gasification react ion. However, the addition of steam to fuel is not appropriate for the auxiliary power unit (APU) and potable power generation (PPG) systems due to an increase of complexity and bulkiness. In this regard, many researchers have focused on so-called 'direct methane' operation of SOFC, which works with dry methane without coking. However, coking can be suppressed only by the operation with a high current density, which may be a drawback especially for the APU and PPG systems. The single chamber fuel cell (SC-SOFC) is a novel simplification of the conventional SOFC into which a premixed fuel/air mixture is introduced. It relies on the selectivity of the anode and cathode catalysts to generate a chemical potential gradient across the cell. Moreover it allows compact and seal-free stack design. In this study, we fabricated honeycomb type mixed-gas fuel cell (MGFC) which has advantages of stacking to the axial direction and increasing volume power density. Honeycomb-structured SOFC with four channels was prepared by dry pressing method. Two alternative channels were coated with electrolyte and cathode slurry in order to make cathodic reaction sites. We will discuss that the anode supported honeycomb type cell running on mixed gas condition.

• Composites Research
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• v.35 no.6
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• pp.371-377
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• 2022

Triboelectric nanogenerator (TENG) devices have generated a lot of interest in recent decades. TENG technology, which is one of the technologies for harvesting mechanical energy among the energy wasted in the environment, is obtained by the dual effect of electrostatic induction and triboelectric charging. Recently, a multilayer thin film stacking method (or layer-by-layer (LbL) self-assembly technique) is being considered as a method to improve the performance of TENG and apply it to new fields. This LbL assembly technology can not only improve the performance of TENG and successfully overcome the thickness problem in applications, but also present an inexpensive, environmentally friendly process and be used for large-scale and mass production. In this review, recent studies in the accomplishment of LbL-based materials for TENG devices are reviewed, and the potential for energy harvesting devices reviewed so far is checked. The advantages of the TENG device fabricated by applying the LbL technology are discussed, and finally, the direction and perspective of this fabrication technology for the implementation of various ultra-thin TENGs are briefly presented.