• Journal of Communications and Networks
• /
• v.18 no.5
• /
• pp.773-783
• /
• 2016

Both coordinated multi-point transmission and frequency reuse are effective approaches to mitigate inter-cell interference and improve network coverage. The motivation of this work is to explore the manner to effectively utilize the spectrum resource by reasonably combining cooperation and frequency reuse. The $Mat{\acute{e}}rn$ cluster process, which is appropriate to model networks with hot spots, is used to model the spatial distribution of base stations. Two cooperative mechanisms, coherent and non-coherent joint transmission (JT), are analyzed and compared. We also evaluate the effect of multiple antennas and imperfect channel state information. The simulation reveals that the proposed approach to combine cooperation and frequency reuse is effective to improve the network coverage for users located at both the center and the boundary of the cooperative region.

• Journal of Communications and Networks
• /
• v.17 no.1
• /
• pp.47-57
• /
• 2015

With the ever growing demand of data applications, the joint macro-relay networks are emerging as a promising heterogeneous deployment to provide coverage extension and throughput enhancement. However, the current cellular networks are usually designed to be performance-oriented without enough considerations on the traffic variation, causing substantial energy waste. In this paper, we consider a joint macro-relay network with densely deployed relay stations (RSs), where the traffic load varies in both time and spatial domains. An energy-efficient scheme is proposed to dynamically adjust the RS working modes (active or sleeping) according to the traffic variations, which is called traffic-aware relay sleep control (TRSC). To evaluate the performance of TRSC,we establish an analytical model using stochastic geometry theory and derive explicit expressions of coverage probability, mean achievable rate and network energy efficiency (NEE). Simulation results demonstrate that the derived analytic results are reasonable and the proposed TRSC can significantly improve the NEE when the network traffic varies dynamically.

• Spatial Information Research
• /
• v.20 no.1
• /
• pp.81-90
• /
• 2012

When analyzing geographical phenomena, two properties need to be considered. One is the spatial dependence structure and the other is a variation or an uncertainty inhibited in a geographic space. Two problems are encountered due to the properties. Firstly, spatial dependence structure, which is conceptualized as spatial autocorrelation, generates heterogeneous geographic landscape in a spatial process. Secondly, generic statistics, although suitable for dealing with stochastic uncertainty, tacitly ignores location information im plicit in spatial data. GIS is a versatile tool for manipulating locational information, while spatial statistics are suitable for investigating spatial uncertainty. Therefore, integrating spatial statistics to GIS is considered as a plausible strategy for appropriately understanding geographic phenomena of interest. Geographic hot-spot analysis is a key tool for identifying abnormal locations in many domains (e.g., criminology, epidemiology, etc.) and is one of the most prominent applications by utilizing the integration strategy. The article aims at reviewing spatial statistical perspective for analyzing spatial processes in the framework of GIS by carrying out empirical analysis. Illustrated is the analysis procedure of using spatial scan statistic for detecting clusters in the framework of GIS. The empirical analysis targets for identifying spatial clusters of breast cancer incidents in Erie and Niagara counties, New York.

• Journal of the Computational Structural Engineering Institute of Korea
• /
• v.22 no.6
• /
• pp.627-637
• /
• 2009

Composite materials have been employed in the various engineering applications due to high mechanical performances including high strength-weight ratio and high degree of free formability. Due to complex manufacturing process, however, it can have intrinsic randomness in the material constants which affect the deterministic behavior of the composite structures. In this study, we suggest a formulation for stochastic finite element analysis considering the spatial randomness of Poisson's ratio. Considering the reciprocal relation between elastic moduli and Poisson's ratios in the two mutually orthogonal axes, one of two values of Poisson's ratio can be expressed in terms of the other. Using this, the relation between stress resultants and strains is derived in the ascending order of power of the stochastic field function, which can be directly used in the formulation to obtain the coefficient of variation of responses. The adequacy of the proposed scheme is demonstrated by comparison with the results of Monte Carlo analysis.

• Korean Journal of Remote Sensing
• /
• v.25 no.3
• /
• pp.295-309
• /
• 2009

In this study, an iterative maximum a posteriori (MAP) approach using a Bayesian model of Markovrandom field (MRF) was proposed for despeckling images that contains speckle. Image process is assumed to combine the random fields associated with the observed intensity process and the image texture process respectively. The objective measure for determining the optimal restoration of this "double compound stochastic" image process is based on Bayes' theorem, and the MAP estimation employs the Point-Jacobian iteration to obtain the optimal solution. In the proposed algorithm, MRF is used to quantify the spatial interaction probabilistically, that is, to provide a type of prior information on the image texture and the neighbor window of any size is defined for contextual information on a local region. However, the window of a certain size would result in using wrong information for the estimation from adjacent regions with different characteristics at the pixels close to or on boundary. To overcome this problem, the new method is designed to use less information from more distant neighbors as the pixel is closer to boundary. It can reduce the possibility to involve the pixel values of adjacent region with different characteristics. The proximity to boundary is estimated using a non-uniformity measurement based on standard deviation of local region. The new scheme has been extensively evaluated using simulation data, and the experimental results show a considerable improvement in despeckling the images that contain speckle.

• Nuclear Engineering and Technology
• /
• v.51 no.6
• /
• pp.1616-1625
• /
• 2019

Measuring occurrence times of random events, aimed to determine the statistical properties of the governing stochastic process, is a basic topic in science and engineering, and has been the subject of numerous mathematical modeling approaches. Often, true statistical properties deviate from measured properties due to the so called dead time phenomenon, where for a certain time period following detection, the detection system is not operational. Understanding the dead time effect is especially important in radiation measurements, often characterized by high count rates and a non-reducible detector dead time (originating in the physics of particle detection). The effect of dead time can be interpreted as a suitable rarefied sequence of the original time sequence. This paper provides a limit theorem for a high rate (diffusion-scale) counter with extendable (Type II) dead time, where the underlying counting process is a renewal process with finite second moment for the inter-event distribution. The results are very general, in the sense that they refer to a general inter arrival time and a random dead time with general distribution. Following the theoretical results, we will demonstrate the applicability of the results in three applications: serially connected components, multiplicity counting and measurements of aerosol spatial distribution.

• Transactions of the Korean Society of Mechanical Engineers A
• /
• v.28 no.6
• /
• pp.685-692
• /
• 2004

A stochastic approach has been presented for superplastic deformation of Ti-6Al-4V alloy, and probability functions are used to model the heterogeneous phase distributions. The experimentally observed spatial correlation functions are developed, and microstructural evolutions together with superplastic deformation behavior have been investigated by means of the two-point and three-point probability functions. The results have shown that the probability varies approximately linearly with separation distance, and deformation enhanced probability changes during the process. The stress-strain behavior with the evolutions of probability function can be correctly predicted by the model. The finite element implementation using Monte Carlo simulation associated with reconstructed microstructures shows that better agreement with experimental data of failure strain on the test specimen.

• 한국신재생에너지학회:학술대회논문집
• /
• 2008.05a
• /
• pp.588-590
• /
• 2008

The thermal signature of nucleation process is characterized by the induction time, the degree of supercooling, and the equilibrium temperature depression. The initiation of nucleation presents stochastic characteristics. The factors that affect nucleation are mechanical impact, ionic concentration, mineral surface characters, and pore size. Hydrate-bearing sediments behave mechanically like other cemented sediments. The data set has important implications for the calibration and interpretation of geophysical measurements and downhole logs collected in gas hydrate provinces, providing particular insight for the interpretation of P- and S-wave data and resistivity logs. In addition, laboratory formation history and ensuing pore-scale spatial distribution likely have a more pronounced effect on the macroscale mechanical properties of hydrate-bearing sediments

• Journal of Ocean Engineering and Technology
• /
• v.13 no.2 s.32
• /
• pp.58-65
• /
• 1999

The effect of specimen thickness on fatigue crack growth rate was studied. The objective of the present study is to investigate the effect of specimen thickness on the fatigue crack growth behavior at various stress intensity factor ranges and also the variation of material restance to fatigue crack growth. The fatigue crack growth resistance was treated as a spatial stochastic process, which varies randomly on the crack path, Compact tension specimens with a LT orientation for structural steel were used. All testing was done at a constant stress intensity level. The experimental data were analyzed for the size effect to determine the Weibull distributions of the material resistance.

• Proceedings of the Korea Water Resources Association Conference
• /
• 2020.06a
• /
• pp.125-125
• /
• 2020

European Space Agency's Sentinel-1 has an improved spatial and temporal resolution, as compared to previous satellite data such as Envisat Advanced SAR (ASAR) or Advanced Scatterometer (ASCAT). Thus, the assumption used for low-resolution retrieval algorithms used by ENVISAT ASAR or ASCAT is not applicable to Sentinel-1, because a higher degree of land surface heterogeneity should be considered for retrieval. The assumption of homogeneity over land surface is not valid any more. In this study, considering that soil roughness is one of the key parameters sensitive to soil moisture retrievals, various approaches are discussed. First, soil roughness is spatially inverted from Sentinel-1 backscattering over Yanco sites in Australia. Based upon this, Artificial Neural Networks data (feedforward multiplayer perception, MLP, Levenberg-Marquadt algorithm) are compared with Fractal approach (brownian fractal, Hurst exponent of 0.5). When using ANNs, training data are achieved from theoretical forward scattering models, Integral Equation Model (IEM). and Sentinel-1 measurements. The network is trained by 20 neurons and one hidden layer, and one input layer. On the other hand, fractal surface roughness is generated by fitting 1D power spectrum model with roughness spectra. Fractal roughness profile is produced by a stochastic process describing probability between two points, and Hurst exponent, as well as rms heights (a standard deviation of surface height). Main interest of this study is to estimate a spatial variability of roughness without the need of local measurements. This non-local approach is significant, because we operationally have to be independent from local stations, due to its few spatial coverage at the global level. More fundamentally, SAR roughness is much different from local measurements, Remote sensing data are influenced by incidence angle, large scale topography, or a mixing regime of sensors, although probe deployed in the field indicate point data. Finally, demerit and merit of these approaches will be discussed.