• The Journal of the Institute of Internet, Broadcasting and Communication
• /
• v.17 no.4
• /
• pp.49-59
• /
• 2017

Smart sensing plays a key role in a variety of IoT applications, and its importance is growing more and more together with the development of artificial intelligence. Therefore the importance of smart sensors cannot be overemphasized. However, most studies related to smart sensors have been focusing on specific application purposes, for example, security, energy saving, monitoring, and there are not much effort on researches on how to efficiently configure various types of smart sensors to be needed in the future. In this paper, a component-based framework with hierarchical structure for efficient construction of smart sensor is proposed and its application to smart home is designed and implemented. The proposed method shows that various types of smart sensors to be appeared in the near future can be configured through the design and development of necessary components within the proposed software framework. In addition, since it has a layered architecture, the configuration of the smart sensor can be expanded by inserting the internal or external layers. In particular, it is possible to independently design the internal and external modules when designing an IoT application service through connection with the external device layer. A small-scale smart home system is designed and implemented using the proposed method, and a home cloud operating as an external layer, is further designed to accommodate and manage multiple smart homes. By developing and thus adding the components of each layer, it will be possible to efficiently extend the range of applications such as smart cars, smart buildings, smart factories an so on.

• Journal of Plant Biotechnology
• /
• v.39 no.3
• /
• pp.121-126
• /
• 2012

To determine whether FT-IR spectroscopy combined with multivariate analysis for whole cell extracts can be used to discriminate major leguminous plant at metabolic level, seed extracts of six leguminous plants were subjected to Fourier transform infrared spectroscopy (FT-IR). FT-IR spectral data from seed extracts were analyzed by principal component analysis (PCA), partial least square discriminant analysis (PLS-DA) and hierarchical clustering analysis (HCA). The PCA could not fully discriminate six leguminous plants, however PLS-DA could successfully discriminate six leguminous plants. The hierarchical dendrogram based on PLS-DA separated the six leguminous plants into four branches. The first branch was consisted of all three Vigna species including Vigna radiata var. radiate, Vigna angularis var. angularis and Vigna unguiculata subsp. Unguiculata. Whereas Pisum sativum var. sativum, Glycine max L and Phaseolus vulgaris var. vulgaris were clustered into a separate branch respectively. The overall results showed that metabolic discrimination system were in accordance with known phylogenic taxonomy. Thus we suggested that the hierarchical dendrogram based on PLS-DA of FT-IR spectral data from seed extracts represented the most probable chemotaxonomical relationship between six leguminous plants.

• Journal of Advanced Navigation Technology
• /
• v.23 no.1
• /
• pp.84-89
• /
• 2019

This is a pilot study of machine learning based structural health monitoring system using flight data of composite aircraft. In this study, the most suitable machine learning algorithm for structural health monitoring was selected and dimensionality reduction method for application on the actual flight data was conducted. For these tasks, impact test on the cantilever beam with added mass, which is the simulation of damage in the aircraft wing structure was conducted and classification model for damage states (damage location and level) was trained. Through vibration test of cantilever beam with fiber bragg grating (FBG) sensor, data of normal and 12 damaged states were acquired, and the most suitable algorithm was selected through comparison between algorithms like tree, discriminant, support vector machine (SVM), kNN, ensemble. Besides, through neighborhood component analysis (NCA) feature selection, dimensionality reduction which is necessary to deal with high dimensional flight data was conducted. As a result, quadratic SVMs performed best with 98.7% for without NCA and 95.9% for with NCA. It is also shown that the application of NCA improved prediction speed, training time, and model memory.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
• /
• v.40 no.4
• /
• pp.275-292
• /
• 2022

In order to detect climate changes using satellite imagery, the GCOS (Global Climate Observing System) defines requirements such as spatio-temporal resolution, stability by the time change, and uncertainty. Due to limitation of GK-2A sensor performance, the level-2 products can not satisfy the requirement, especially for spatial resolution. In this paper, we found the optimal pan-sharpening algorithm for GK-2A products. The six pan-sharpening methods included in CS (Component Substitution), MRA (Multi-Resolution Analysis), VO (Variational Optimization), and DL (Deep Learning) were used. In the case of DL, the synthesis property based method was used to generate training dataset. The process of synthesis property is that pan-sharpening model is applied with Pan (Panchromatic) and MS (Multispectral) images with reduced spatial resolution, and fused image is compared with the original MS image. In the synthesis property based method, fused image with desire level for user can be produced only when the geometric characteristics between the PAN with reduced spatial resolution and MS image are similar. However, since the dissimilarity exists, RD (Random Down-sampling) was additionally used as a way to minimize it. Among the pan-sharpening methods, PSGAN was applied with RD (PSGAN_RD). The fused images are qualitatively and quantitatively validated with consistency property and the synthesis property. As validation result, the GSA algorithm performs well in the evaluation index representing spatial characteristics. In the case of spectral characteristics, the PSGAN_RD has the best accuracy with the original MS image. Therefore, in consideration of spatial and spectral characteristics of fused image, we found that PSGAN_RD is suitable for GK-2A products.

• Journal of the Society of Naval Architects of Korea
• /
• v.49 no.3
• /
• pp.254-263
• /
• 2012

The survivability of warship is assessed by susceptibility, vulnerability and recoverability. Essentially, a vulnerability assessment is a measure of the effectiveness of a warship to resist hostile weapon effects. Considering the shot line and its penetration effect on the warship, present study introduces the procedural aspects of vulnerability assessments of warship. Present study also considers the prediction of penetration damage to a target caused by the impact of projectiles. It reflects the interaction between the weapon and the target from a perspective of vulnerable area method and COVART model. The shotline and tracing calculation have been directly integrated into the vulnerability assessment method based on the penetration equation empirically obtained. A simplified geometric description of the desired target and specification of a threat type is incorporated with the penetration effect. This study describes how to expand the vulnerable area assessment method to the penetration effect. Finally, an example shows that the proposed method can provide the vulnerability parameters of the warship or its component under threat being hit through tracing the shotline path thereby enabling the vulnerability calculation. In addition, the proposed procedure enabling the calculation of the component's multi-hit vulnerability introduces a propulsion system in dealing with redundant Non-overlapping components.

• The Journal of Korean Institute of Communications and Information Sciences
• /
• v.38C no.12
• /
• pp.1114-1125
• /
• 2013

License Plate Detection (LPD) is a key component in automatic license plate recognition system. Despite the success of License Plate Recognition (LPR) methods in the past decades, the problem is quite a challenge due to the diversity of plate formats and multiform outdoor illumination conditions during image acquisition. This paper aims at automatical detection of car license plates via image processing techniques. In this paper, we proposed a real-time and robust method for license plate detection using Heuristic Energy Map(HEM). In the vehicle image, the region of license plate contains many components or edges. We obtain the edge energy values of an image by using the box filter and search for the license plate region with high energy values. Using this energy value information or Heuristic Energy Map(HEM), we can easily detect the license plate region from vehicle image with a very high possibilities. The proposed method consists two main steps: Region of Interest (ROI) Detection and License Plate Detection. This method has better performance in speed and accuracy than the most of existing methods used for license plate detection. The proposed method can detect a license plate within 130 milliseconds and its detection rate is 99.2% on a 3.10-GHz Intel Core i3-2100(with 4.00 GB of RAM) personal computer.

• The Transactions of the Korean Institute of Power Electronics
• /
• v.4 no.5
• /
• pp.462-473
• /
• 1999

This paper addresses the current measurement issue of all digital field oriented control of ac motors. The p paper focuses on the effect of low-pass filter and also on the sampling of the fundamental component of the m motor current. The low-pass filter, which suppresses the switching noise of the motor current, introduces v variable phase delay according to the current ripple frequency. It is shown that the current sampling error c consists of the fundamental component and high frL'quency ripple components. In this paper, the dependency of t this current sampling e$\pi$or on the reference voltage vector is investigated analytically and a sampling technique i is proposed to minimize the error. The work is based on the three phase symmetry pulse width modulation l inverter driving an induction machine. With this technique, the bandwidth of current regulator can be extended t to the limit given by the switching frequency of the inverter and more precise torque regulation is possible.

• Korean Journal of Plant Tissue Culture
• /
• v.24 no.2
• /
• pp.103-106
• /
• 1997

In order to establish a micropropagation system of Naricissus, the ability of bulblet regeneration among propagation materials was compared, and the adequate growth regulators and concentrations for each cultivar were investigated. The inorganic components were also assayed in the parts of propagation materials. In propagation materials, scape with based plates showed hightest rate of bulblet formation and rapid growth of formed bulblets in vitro, comparing to other parts of it. In comparing of varieties, 'Dutch Master' and 'Golden Harvest' showed a high ability for bulblet regeneration. The ability of bulblet regeneration was most favorable in the medium, supplemented with 5.0 mg/L BA and 2.5 mg/L NAA in 'Dutch Master', and 5.0 mg/L BA and 1.0mg/L NAA in 'Golden Harvest', respectively. In inorganic component analysis of propagation materials, the White part of scape contained 1.18 mg/L$P_2O_5$, 2.57 me Ca, 0.94 me Mg and 3.20 mg/L total N. It showed higher levels in concentration of inorganic components as compared to those of the other part of scape. In addition, leaves and yellow part of scape contained significantly high levels of Ca and Mg while scales bulb showed considerably low levels in all inorganic compounds.

• Journal of Agricultural Extension & Community Development
• /
• v.19 no.4
• /
• pp.1041-1066
• /
• 2012

This article aims to analyse the change factor of the industry in rural area. As the regional economy is consist of variety industry in local Revitalization of Rural Economy should consider the growth factor of industry. Analytical method is Shift-Share analysis, analysis data is used GRDP of the 5 target area. Analysis is showed that Agriculture, forestry and fishing is leading position. but Farm population decreased rapidly underway. Side work farmer and industry population is increasing rapidly. the Regional Economic growth inhibitory of 5 Gun is the weakness of the internal factor. especially Competition component is than industry-Mixed component. and the Growth of Agriculture, forestry and fishing is external factor. To improve the regional economy, 5 Gun must improve the fault. and the growth of Agriculture, forestry and fishing should promote the consumption of local products to as the local food system.

• Journal of the Institute of Electronics Engineers of Korea SP
• /
• v.40 no.6
• /
• pp.149-156
• /
• 2003

This paper proposes a face recognition method based on modified Otsu binarization, Hu moment and linear discriminant analysis (LDA). Proposed method is robust to brightness, contrast, scale, rotation, and translation changes. Modified Otsu binarization can make binary images that have the invariant characteristic in brightness and contrast changes. From edge and multi-level binary images obtained by the threshold method, we compute the 17 dimensional Hu moment and then extract feature vector using LDA algorithm. Especially, our face recognition system is robust to scale, rotation, and translation changes because of using Hu moment. Experimental results showed that our method had almost a superior performance compared with the conventional well-known principal component analysis (PCA) and the method combined PCA and LDA in the perspective of brightness, contrast, scale, rotation, and translation changes with Olivetti Research Laboratory (ORL) database and the AR database.