• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
• /
• 2007.11a
• /
• pp.1307-1312
• /
• 2007

This paper proposes an optimal design scheme to reduce the noise of the engine cooling fan by adapting Kriging with two meta-heuristic techniques. An engineering model has been developed for the prediction of the noise spectrum of the engine cooling fan. The noise of the fan is expressed as the discrete frequency noise peaks at the BPF and its harmonics and line spectrum at the broad band by noise generation mechanisms. The object of this paper is to find the Optimal Design for Noise Reduction of the Engine Cooling Fan. We firstly show a comparison of the measured and calculated noise spectra of the fan for the validation of the noise prediction program. Orthogonal array is applied as design of experiments because it is suitable for Kriging. With these simulated data, we can estimate a correlation parameter of Kriging by solving the nonlinear problem with genetic algorithm and find an optimal level for the noise reduction of the cooling fan by optimizing Kriging estimates with simulated annealing. We notice that this optimal design scheme gives noticeable results. Therefore, an optimal design for the cooling fan is proposed by reducing the noise of its system.

• Korean Journal of Remote Sensing
• /
• v.25 no.6
• /
• pp.465-474
• /
• 2009

Convective/stratiform radar echo classification schemes by Steiner et al. (1995) and Biggerstaff and Listemaa (2000) are examined on a monsoonal front during the summer monsoon-Changma period, which is organized as a cloud cluster with mesoscale convective complex. Target radar is S-band with wavelength of 10cm, spatial resolution of 1km, elevation angle interval of 0.5-1.0 degree, and minimum elevation angle of 0.19 degree at Jindo over the Korean Peninsula. For verification of rainfall amount retrieved from the echo classification, ground-based rain gauge observations (Automatic Weather Stations) are examined, converting the radar echo grid data to the station values using the inverse distance weighted method. Improvement from the echo classification is evaluated based on the correlation coefficient and the scattered diagram. Additionally, an optimal use method was designed to produce combined rainfalls from the radar echo and Tropical Rainfall Measuring Mission Precipitation Radar (TRMM/PR) data. Optimal values for the radar rain and TRMM/PR rain are inversely weighted according to the error variance statistics for each single station. It is noted how the rainfall distribution during the summer monsoon frontal system is improved from the classification of convective/stratiform echo and the use of the optimal use technique.

• The KIPS Transactions:PartB
• /
• v.10B no.3
• /
• pp.311-320
• /
• 2003

The Optimal filter yielding optimal texture feature separation is a most effective technique for extracting the texture objects from multiple textures images. But, most optimal filter design approaches are restricted to the issue of supervised problems. No full-unsupervised method is based on the recognition of texture objects in image. We propose a novel approach that uses unsupervised learning schemes for efficient texture image analysis, and the band-pass feature of Gabor-filter is used for the optimal filter design. In our approach, the self-organizing neural network for multiple texture image identification is based on block-based clustering. The optimal frequency of Gabor-filter is turned to the optimal frequency of the distinct texture in frequency domain by analyzing the spatial frequency. In order to show the performance of the designed filters, after we have attempted to build a various texture images. The texture objects extraction is achieved by using the designed Gabor-filter. Our experimental results show that the performance of the system is very successful.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
• /
• v.36 no.3
• /
• pp.135-152
• /
• 2018

The purpose of this study is to propose an optimal fusion method of aerial multi - sensor data to improve the accuracy of land cover classification. Recently, in the fields of environmental impact assessment and land monitoring, high-resolution image data has been acquired for many regions for quantitative land management using aerial multi-sensor, but most of them are used only for the purpose of the project. Hyperspectral sensor data, which is mainly used for land cover classification, has the advantage of high classification accuracy, but it is difficult to classify the accurate land cover state because only the visible and near infrared wavelengths are acquired and of low spatial resolution. Therefore, there is a need for research that can improve the accuracy of land cover classification by fusing hyperspectral sensor data with multispectral sensor and aerial laser sensor data. As a fusion method of aerial multisensor, we proposed a pixel ratio adjustment method, a band accumulation method, and a spectral graph adjustment method. Fusion parameters such as fusion rate, band accumulation, spectral graph expansion ratio were selected according to the fusion method, and the fusion data generation and degree of land cover classification accuracy were calculated by applying incremental changes to the fusion variables. Optimal fusion variables for hyperspectral data, multispectral data and aerial laser data were derived by considering the correlation between land cover classification accuracy and fusion variables.

• The Journal of Korean Institute of Communications and Information Sciences
• /
• v.36 no.12B
• /
• pp.1736-1743
• /
• 2011

In Network Centric Warfare (NCW) environment, having a tactical communication network which provides high data exchange rate is very important. In the process, Korean Army developed Mobile Subscriber Access Point (MSAP) which is based on the commercial Wireless BroadBand (Wibro). MSAP is a vehicle attached base station which provide high data exchange communication environment in a given area. Thus MSAP can provide high data exchange rate and mobility to accomplish missions in the battlefield more effectively. In this paper, we propose an operational strategy of using MSAP to provide tactical communication network in the battlefield. The idea is to find the optimal location point of the MSAP in the operational area where all the troops in the operational area can be supported by the MSAP with a minimum number of MSAP. Since the current Korean Army's basic idea of using MSAP is just distribute this MSAP to each troop, so by applying our strategy we can save MSAP devices for more flexible operation. We will show our strategy's benefits through the mathematical model and the algorithm of the presented problem.

• Journal of Ginseng Research
• /
• v.27 no.3
• /
• pp.146-150
• /
• 2003

This study was carried out to obtain basic information on breeding using PCR-aided RFLP technology which can identify the variation inter- and intra-species of ginseng in the level of DNA. It was intended to investigate banding pattern on psbA and rbeL genes of chloroplast DNA in ginseng after treating with restriction enzymes. To isolate psbA and rbcL genes of chloroplast, both psbA-N, psbA-C primer and rbcL-N, PX-1 primer were used. As a result, 1,008 bp band of psbA gene and 1,336 bp band of rbcL gene were appeared, which was optimal and expected molecular weight. In addition, primers to isolate atpB, rpoB, trnL, and trnF genes were used, resulting in the expected 1366, 900, 1500 and 1008 bp bands. Genes of psbA and rbcL isolated by PCR were cut by restriction enzymes, Sau3A, TaqI, AluI, HaeIII, and RFLP pattern was investigated. KG line and other species of ginseng were cut by TaqI treatment, and bands were located in 800 bp. The treatment treated by AluI also showed the same 800 bp band in KG line and other species. In HaeIII treatment, 500 bp of faint bands were shown in case of KG line, whereas any bands were not observed in other species. All chloroplast genes formed bands by PCR amplification. However, it was not evident to distinguish intra-or inter-species of ginseng after restriction enzyme treatment. Therefore, more restriction enzyme treatment or sequence comparison method should be considered for further experiment.

• Journal of electromagnetic engineering and science
• /
• v.17 no.1
• /
• pp.20-28
• /
• 2017

A fully integrated dual-band CMOS power amplifier (PA) is developed for 802.11n WLAN applications using wafer-level package (WLP) technology. This paper presents a detailed design for the optimal impedance of dual-band PA (2 GHz/5 GHz PA) output transformers with low loss, which is provided by using 2:2 and 2:1 output transformers for the 2 GHz PA and the 5 GHz PA, respectively. In addition, several design issues in the dual-band PA design using WLP technology are addressed, and a design method is proposed. All considerations for the design of dual-band WLP PA are fully reflected in the design procedure. The 2 GHz WLP CMOS PA produces a saturated power of 26.3 dBm with a peak power-added efficiency (PAE) of 32.9%. The 5 GHz WLP CMOS PA produces a saturated power of 24.7 dBm with a PAE of 22.2%. The PA is tested using an 802.11n signal, which satisfies the stringent error vector magnitude (EVM) and mask requirements. It achieved an EVM of -28 dB at an output power of 19.5 dBm with a PAE of 13.1% at 2.45 GHz and an EVM of -28 dB at an output power of 18.1 dBm with a PAE of 8.9% at 5.8 GHz.

• Journal of the Computational Structural Engineering Institute of Korea
• /
• v.32 no.4
• /
• pp.241-247
• /
• 2019

A band gap refers to a certain frequency range where the propagation of mechanical waves is prohibited. This work focuses on engineering three-dimensional Kelvin lattices having external band gaps at low audible frequency ranges using a gradient-based design optimization method. Elastic wave propagation in an infinite periodic lattice is investigated by employing the Bloch theorem. We model the ligaments using a shear-deformable beam model obtained by consistent linearization in a geometrically exact beam theory. For a given lattice topology, we enlarge band gap sizes by controlling the configuration of the beam neutral axis and cross-section thickness that are smoothly parameterized by B-spline basis functions within the isogeometric analysis framework.

• Smart Media Journal
• /
• v.13 no.8
• /
• pp.39-48
• /
• 2024

Recently, various studies have emerged that utilize hyperspectral imaging for crop growth analysis and early disease diagnosis. However, the challenge of using numerous spectral bands or finding the optimal bands for crop area remains a difficult problem. In this paper, we propose a method of searching the optimized spectral band of crop area based on deep learning using the hyper-spectral image. The proposed method extracts RGB images within hyperspectral images to segment background and foreground area through a Vision Transformer-based Seformer. The segmented results project onto each band of gray-scale converted hyperspectral images. It determines the optimized spectral band of the crop area through the pixel comparison of the projected foreground and background area. The proposed method achieved foreground and background segmentation performance with an average accuracy of 98.47% and a mIoU of 96.48%. In addition, it was confirmed that the proposed method converges to the NIR regions closely related to the crop area compared to the mRMR method.

• Journal of the Korean Institute of Intelligent Systems
• /
• v.21 no.6
• /
• pp.786-791
• /
• 2011

An optimal feature selection and extraction procedure is an important task that significantly affects the success of brain activity analysis in brain-computer interface (BCI) research area. In this paper, a novel method for extracting the optimal feature from electroencephalogram (EEG) signal is proposed. At first, a student's-t-statistic method is used to normalize and to minimize statistical error between EEG measurements. And, 2D time-frequency data set from the raw EEG signal was extracted using discrete wavelet transform (DWT) as a raw feature, standard deviations and mean of 2D time-frequency matrix were extracted as a optimal EEG feature vector along with other basis feature of sub-band signals. In the experiment, data set 1 of BCI competition IV are used and classification using SVM to prove strength of our new method.