• Journal of the Korean Mathematical Society
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• v.56 no.1
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• pp.239-263
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• 2019

The $Calder{\acute{o}}n$-Zygmund type estimate is proved for elliptic obstacle problems in bounded non-smooth domains. The problems are related to divergence form nonlinear elliptic equation with measurable nonlinearities. Precisely, nonlinearity $a({\xi},x_1,x^{\prime})$ is assumed to be only measurable in one spatial variable $x_1$ and has locally small BMO semi-norm in the other spatial variables x', uniformly in ${\xi}$ variable. Regarding non-smooth domains, we assume that the boundaries are locally flat in the sense of Reifenberg. We also investigate global regularity in the settings of weighted Orlicz spaces for the weak solutions to the problems considered here.

• Journal of the Semiconductor & Display Technology
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• v.18 no.2
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• pp.63-66
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• 2019

Due to the development of medical imaging technology, different imaging technologies provide a large amount of effective information. However, different imaging method caused the limitations of information integrity by using single type of image. Combining different image together so that doctor can obtain the information from medical image comprehensively. Image registration algorithm based on mutual information has become one of the hotspots in the field of image registration with its high registration accuracy and wide applicability. Because the information theory-based registration technology is not dependent on the gray value difference of the image, and it is very suitable for multimodal medical image registration. However, the method based on mutual information has a robustness problem. The essential reason is that the mutual information itself is not have enough information between the pixel pairs, so that the mutual information is unstable during the registration process. A large number of local extreme values are generated, which finally cause mismatch. In order to overcome the shortages of mutual information registration method, this paper proposes a registration method combined with image spatial structure information and mutual information.

• Journal of The Korean Society of Agricultural Engineers
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• v.61 no.2
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• pp.105-115
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• 2019

For 159 administrative areas, SPI(Standardized Precipitation Index), ARDI(Agricultural Reservoir Drought Index) and ARDIs(Agricultural Reservoir Drought Index Simulated) were developed and applied to analyze the characteristics of agricultural drought index and agricultural droughts. In order to identify hydrometeorological characteristics of agricultural droughts, SPI, ARDI and ARDIs were calculated nationwide, and the applicability was compared and examined. SPI and ARDI showed significant differences in time and depth of drought in both spatial and temporal. ARDI and ARDIs showed similar tendency of change, and ARDIs were considered to be more representative of agricultural drought characteristics. The results of this study suggest that agricultural drought is a problem to be solved in the medium and long term rather than short term due to various forms of development, complexity of development, and difficulty in forecasting. Therefore, it is concluded that a preliminary and systematic approach is needed in consideration of meteorological, hydrological and hydrometeorological characteristics rather than a fragmentary approach, and that an agricultural drought index is needed to quantitatively evaluate agricultural drought.

• Journal of applied mathematics & informatics
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• v.39 no.5_6
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• pp.655-676
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• 2021

A parameter uniform numerical scheme is proposed for solving singularly perturbed parabolic partial differential-difference convection-diffusion equations with a small delay and advance parameters in reaction terms and spatial variable. Taylor's series expansion is applied to approximate problems with the delay and advance terms. The resulting singularly perturbed parabolic convection-diffusion equation is solved by utilizing the implicit Euler method for the temporal discretization and finite difference method for the spatial discretization on a uniform mesh. The proposed numerical scheme is shown to be an ε-uniformly convergent accurate of the first order in time and second-order in space directions. The efficiency of the scheme is proved by some numerical experiments and by comparing the results with other results. It has been found that the proposed numerical scheme gives a more accurate approximate solution than some available numerical methods in the literature.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.14 no.4
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• pp.314-322
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• 2021

Skeleton-based action recognition has attracted considerable attention in human action recognition. Recent methods for skeleton-based action recognition employ spatiotemporal graph convolutional networks (GCNs) and have remarkable performance. However, most of them have heavy computational complexity for robust action recognition. To solve this problem, we propose a shuffle graph convolutional network (SGCN) which is a lightweight graph convolutional network using pointwise group convolution rather than pointwise convolution to reduce computational cost. Our SGCN is composed of spatial and temporal GCN. The spatial shuffle GCN contains pointwise group convolution and part shuffle module which enhances local and global information between correlated joints. In addition, the temporal shuffle GCN contains depthwise convolution to maintain a large receptive field. Our model achieves comparable performance with lowest computational cost and exceeds the performance of baseline at 0.3% and 1.2% on NTU RGB+D and NTU RGB+D 120 datasets, respectively.

• International Journal of Internet, Broadcasting and Communication
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• v.13 no.3
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• pp.104-108
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• 2021

In order to improve performance in IoT, edge computing system, a memory is usually configured in a hierarchical structure. Based on the distance from CPU, the access speed slows down in the order of registers, cache memory, main memory, and storage. Similar to the change in performance, energy consumption also increases as the distance from the CPU increases. Therefore, it is important to develop a technique that places frequently used data to the upper memory as much as possible to improve performance and energy consumption. However, the technique should solve the problem of cache performance degradation caused by lack of spatial locality that occurs when the data access stride is large. This study proposes a technique to selectively place data with large data access stride to a software-controlled cache. By using the proposed technique, data spatial locality can be improved by reducing the data access interval, and consequently, the cache performance can be improved.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.16 no.9
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• pp.2961-2975
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• 2022

The Location-Based Service (LBS) is one of the most well-known services on the Internet. Positioning is the primary association with LBS services. This study proposes an intelligent LoRa-based positioning system, called AI@LBS, to provide accurate location data. The fingerprint mechanism with the clustering algorithm in unsupervised learning filters out signal noise and improves computing stability and accuracy. In this study, data noise is filtered using the DBSCAN (Density-Based Spatial Clustering of Applications with Noise) algorithm, increasing the positioning accuracy from 95.37% to 97.38%. The problem of data imbalance is addressed using the SMOTE (Synthetic Minority Over-sampling Technique) technique, increasing the positioning accuracy from 97.38% to 99.17%. A field test in the NTUST campus (www.ntust.edu.tw) revealed that AI@LBS system can reduce average distance error to 0.48m.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.15 no.12
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• pp.4600-4616
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• 2021

In cognitive radio networks where unlicensed secondary users opportunistically access to licensed spectrum unused by licensed primary users, spectrum sensing is one of the key issues in order to effectively use the frequency resource. For enhancing the sensing performance in energy detection-based spectrum sensing, spatial diversity based on multiple antennas is utilized. However, the sensing performance can be degraded when antennas are spatially correlated, resulting in inducing the harmful interference to primary users. To overcome this problem, in this paper, an advanced energy detector is proposed. In the proposed sensing method, a weight matrix based on the eigenvalues of the spatial channels without any prior information on the primary signals is defined and utilized. In numerical simulations, it is shown that the proposed detector outperforms the conventional detector with regard to false-alarm and detection probabilities when antenna are spatially correlated.

• Proceedings of The Korean Society of Agricultural and Forest Meteorology Conference
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• 2001.06a
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• pp.151-152
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• 2001

A common problem of the model simulations of the land surface - atmosphere interaction is to choose the appropriate spatial scale and resolution at which the simulations are to be performed. The accuracy of energy and water exchange predictions between the land surface and the atmosphere in regional and global scale atmospheric models is mainly influenced by: model simplifications applied to describe the spatial heterogeneity of land surface properties within individual grid cells; ignoring the variability of sub-grid properties (e.g. relief, vegetation, soils), and; lacks of necessary input meteorological and biophysical data.(omitted)

• Journal of applied mathematics & informatics
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• v.41 no.6
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• pp.1327-1339
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• 2023

World Wide Web (WWW) use has been increasing recently due to users needing more information. Lately, there has been a growing trend in the document information available to end users through the internet. The web's document search process is essential to find relevant documents for user queries.As the number of general web pages increases, it becomes increasingly challenging for users to find records that are appropriate to their interests. However, using existing Document Information Retrieval (DIR) approaches is time-consuming for large document collections. To alleviate the problem, this novel presents Spatial Clustering Ranking Pattern (SCRP) based Density Ant Colony Information Retrieval (DACIR) for user queries based DIR. The proposed first stage is the Term Frequency Weight (TFW) technique to identify the query weightage-based frequency. Based on the weight score, they are grouped and ranked using the proposed Spatial Clustering Ranking Pattern (SCRP) technique. Finally, based on ranking, select the most relevant information retrieves the document using DACIR algorithm.The proposed method outperforms traditional information retrieval methods regarding the quality of returned objects while performing significantly better in run time.