• The Korean Journal of Applied Statistics
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• v.30 no.5
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• pp.775-791
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• 2017

We frequently encounter binary data in real life. Logistic, Probit, Cauchit, Complementary log-log models are often used for binary data analysis. In order to analyze binary data, Liu (2004) proposed a Robit model, in which the inverse of cdf of the Student's t distribution is used as a link function. Kim et al. (2008) also proposed a generalized t-link model to make the binary regression model more flexible. The more flexible skewed distributions allow more flexible link functions in generalized linear models. In the sense, we propose a binary data regression model using skewed generalized t distributions introduced in Theodossiou (1998). We implement R code of the proposed models using the glm function included in R base and R sgt package. We also analyze Pima Indian data using the proposed model in R.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.5 no.4
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• pp.286-290
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• 2005

We consider the poisson equation where the functions involved are periodic including the solution function. Let $R=[0,1]{\times}[0,l]{\times}[0,1]$ be the region of interest and let $\phi$(x,y,z) be an arbitrary periodic function defined in the region R such that $\phi$(x,y,z) satisfies $\phi$(x+1, y, z)=$\phi$(x, y+1, z)=$\phi$(x, y, z+1)=$\phi$(x,y,z) for all x,y,z. We describe a very simple method for solving the equation ${\nabla}^2u(x, y, z)$ = $\phi$(x, y, z) based on the cubic spline interpolation of u(x, y, z); using the requirement that each interval [0,1] is a multiple of the period in the corresponding coordinates, the Laplacian operator applied to the cubic spline interpolation of u(x, y, z) can be replaced by a square matrix. The solution can then be computed simply by multiplying $\phi$(x, y, z) by the inverse of this matrix. A description on how the storage of nearly a Giga byte for $20{\times}20{\times}20$ nodes, equivalent to a $8000{\times}8000$ matrix is handled by using the fuzzy rule table method and a description on how the shape preserving property of the Laplacian operator will be affected by this approximation are included.

• Geophysics and Geophysical Exploration
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• v.5 no.4
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• pp.262-271
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• 2002

This study presents a practical procedure for the Bayesian inversion of geophysical data. We have applied geostatistical techniques for the acquisition of prior model information, then the Markov Chain Monte Carlo (MCMC) method was adopted to infer the characteristics of the marginal distributions of model parameters. For the Bayesian inversion of dipole-dipole array resistivity data, we have used the indicator kriging and simulation techniques to generate cumulative density functions from Schlumberger array resistivity data and well logging data, and obtained prior information by cokriging and simulations from covariogram models. The indicator approach makes it possible to incorporate non-parametric information into the probabilistic density function. We have also adopted the MCMC approach, based on Gibbs sampling, to examine the characteristics of a posteriori probability density function and the marginal distribution of each parameter.

• The Journal of the Korea institute of electronic communication sciences
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• v.9 no.11
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• pp.1233-1240
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• 2014

For the last three decades after the advent of the Toffoli gate in 1980, while many reversible circuit syntheses have been presented reversible embedding methods onto suitable reversible functions, only a few proposed direct irreversible-to-reversible mapping methods without reversible embedding. In this paper we present two effective policies to reduce the gate cost and complexity for the existing direct reversible mapping methods without reversible embedding. In order to develop new cost reduction policies we consider the cost influence of Toffoli module according to NOT gate arrangement in classical circuits. From this we deduced an inverse proportional property between inverting input numbers of classical AND/OR gates and reversible Toffoli module cost based on a fact - the inverting inputs of classical AND(OR) gates increase(decrease) the Toffoli module cost. We confirm the applications of the inverting input rearrangement and maximum fan-out policies preceding direct reversible mapping will be effective method to improve the reversible Toffoli module cost and complexity with the parallel using of the fan-out and supercell ones.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.37 no.1
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• pp.67-75
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• 2013

The flow stress of zircaloy-4 used in the spacer grid supporting a nuclear fuel rod was determined by the Johnson-Cook model, and model parameters were determined using reverse engineering. Parameters such as A, B, n and $\dot{\varepsilon}_0$ were determined by the tensile test result. To obtain the parameters C and m, a slot milling test and numerical simulation were performed. The objective functions were defined as the difference between the experimental and the simulation results, and then, the parameters were determined by minimizing the objective function. To verify the validity of the determined parameters, cross-verification for each case was conducted through a shearing test and simulation. The results tend to show agreement with the experimental results, such as the features of sheared edges and maximum punch force, with the correlation coefficients exceeding at least 0.97.

• Journal of Korea Society of Industrial Information Systems
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• v.25 no.5
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• pp.91-102
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• 2020

The Internet of Things (IoT) is characterized as the market where various companies compete for the same consumers. Thus, there are differences in functions and performance provided by the main business area and other characteristics of the service providers. This paper investigates whether satisfaction with the service provided depends on the characteristics of the operator by using sentiment analysis of comments. To achieve this goal, word importance analysis and sensitivity analysis are conducted on 34,310 reviews of 41 applications registered in the Google Play. The review analysis was conducted at various levels, including TD-IDF (Term frequency-inverse document frequency) value of keywords, service sectors, the origin of providers, and domestic/foreign providers. The results show that users' overall assessment of IoT services was found to be low, and smart homes received relatively high reviews compared to other services, and manufacturing-based and overseas providers received relatively higher evaluations than others.

• Journal of Gynecologic Oncology
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• v.29 no.6
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• pp.99.1-99.11
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• 2018

Objective: The present study is to evaluate the biological functions of long non-coding RNA (lncRNA), X-inactive specific transcript, X-inactive specific transcript (XIST) in human epithelial ovarian cancer (EOC). Methods: XIST was upregulated in EOC cell lines, CAOV3 and OVCAR3 cells by lentiviral transduction. The effects of XIST overexpression on cancer cell proliferation, invasion, chemosensitivity and in vivo tumor growth were investigated, respectively. Possible sponging interaction between XIST and human microRNA hsa-miR-214-3p was further evaluated. Furthermore, hsa-miR-214-3p was overexpressed in XIST-upregulated CAOV3 and OVCAR3 cells to evaluate its effect on XIST-mediated EOC regulation. Results: Lentivirus-mediated XIST upregulation had significant anticancer effects in CAOV3 and OVCAR3 cells by suppressing cancer cell proliferation, invasion, increasing cisplatin chemosensitivity and inhibiting in vivo tumor growth. Hsa-miR-214-3p was confirmed to directly bind XIST, and inversely downregulated in XIST-upregulated EOC cells. In EOC cells with XIST upregulation, secondary lentiviral transduction successfully upregulated hsa-miR-214-3p expression. Subsequently, hsa-miR-214-3p upregulation functionally reversed the anticancer effects of XIST-upregulation in EOC. Conclusion: Upregulation of lncRNA XIST may suppress EOC development, possibly through sponging effect to induce hsa-miR-214-3p downregulation

• The Plant Pathology Journal
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• v.37 no.6
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• pp.521-532
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• 2021

Knowledge and better understanding of functions of the microbial community are pivotal for crop management. This study was conducted to study bacterial structures including Acidovorax species community structures and diversity from the watermelon cultivated soils in different regions of South Korea. In this study, soil samples were collected from watermelon cultivation areas from various places of South Korea and microbiome analysis was performed to analyze bacterial communities including Acidovorax species community. Next generation sequencing (NGS) was performed by extracting genomic DNA from 92 soil samples from 8 different provinces using a fast genomic DNA extraction kit. NGS data analysis results revealed that, total, 39,367 operational taxonomic unit (OTU), were obtained. NGS data results revealed that, most dominant phylum in all the soil samples was Proteobacteria (37.3%). In addition, most abundant genus was Acidobacterium (1.8%) in all the samples. In order to analyze species diversity among the collected soil samples, OTUs, community diversity, and Shannon index were measured. Shannon (9.297) and inverse Simpson (0.996) were found to have the highest diversity scores in the greenhouse soil sample of Gyeonggi-do province (GG4). Results from NGS sequencing suggest that, most of the soil samples consists of similar trend of bacterial community and diversity. Environmental factors play a key role in shaping the bacterial community and diversity. In order to address this statement, further correlation analysis between soil physical and chemical parameters with dominant bacterial community will be carried out to observe their interactions.

• Journal of Bio-Environment Control
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• v.23 no.1
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• pp.39-42
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• 2014

The objective of this study was to estimate cardinal temperatures for germination of lettuce (Lactuca sativar L.) using bilinear, parabolic, and beta distribution functions. Seeds of lettuce were germinated in a growth chamber at 7 constant temperatures: 10, 14, 16, 20, 24, 28, and $32^{\circ}C$. Four replicates of 100 seeds were placed on two layers of filter paper in a 9 cm petri-dish. Radicle emergence of 1 mm was scored as germination. The time course of germination was modeled using a logistic function. These minimum, optimum, and maximum temperatures were estimated by regression of the inverse of time to 50% germination rate against the temperature gradient. In bilinear function, minimum, optimum, and maximum temperatures were $7.9^{\circ}C$, $23.3^{\circ}C$, and $28.0^{\circ}C$, respectively. In parabolic function, minimum, optimum, and maximum temperatures were $9.7^{\circ}C$, $19.5^{\circ}C$, and $29.4^{\circ}C$, respectively. In beta distribution function, minimum, optimum, and maximum temperatures were $3.7^{\circ}C$, $20.7^{\circ}C$ and $32.0^{\circ}C$, respectively. Minimum, optimum, and maximum ranges of temperatures were $3.7{\sim}9.7^{\circ}C$, $19.5{\sim}23.3^{\circ}C$, and $28.0{\sim}32.0^{\circ}C$, respectively.

• Journal of the Korean Institute of Landscape Architecture
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• v.49 no.5
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• pp.79-96
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• 2021

Green infrastructure planning represents landscape planning measures to reduce particulate matter. This study aimed to derive factors that may be used in planning green infrastructure for particulate matter reduction using text mining techniques. A range of analyses were carried out by focusing on keywords such as 'particulate matter reduction plan' and 'green infrastructure planning elements'. The analyses included Term Frequency-Inverse Document Frequency (TF-IDF) analysis, centrality analysis, related word analysis, and topic modeling analysis. These analyses were carried out via text mining by collecting information on previous related research, policy reports, and laws. Initially, TF-IDF analysis results were used to classify major keywords relating to particulate matter and green infrastructure into three groups: (1) environmental issues (e.g., particulate matter, environment, carbon, and atmosphere), target spaces (e.g., urban, park, and local green space), and application methods (e.g., analysis, planning, evaluation, development, ecological aspect, policy management, technology, and resilience). Second, the centrality analysis results were found to be similar to those of TF-IDF; it was confirmed that the central connectors to the major keywords were 'Green New Deal' and 'Vacant land'. The results from the analysis of related words verified that planning green infrastructure for particulate matter reduction required planning forests and ventilation corridors. Additionally, moisture must be considered for microclimate control. It was also confirmed that utilizing vacant space, establishing mixed forests, introducing particulate matter reduction technology, and understanding the system may be important for the effective planning of green infrastructure. Topic analysis was used to classify the planning elements of green infrastructure based on ecological, technological, and social functions. The planning elements of ecological function were classified into morphological (e.g., urban forest, green space, wall greening) and functional aspects (e.g., climate control, carbon storage and absorption, provision of habitats, and biodiversity for wildlife). The planning elements of technical function were classified into various themes, including the disaster prevention functions of green infrastructure, buffer effects, stormwater management, water purification, and energy reduction. The planning elements of the social function were classified into themes such as community function, improving the health of users, and scenery improvement. These results suggest that green infrastructure planning for particulate matter reduction requires approaches related to key concepts, such as resilience and sustainability. In particular, there is a need to apply green infrastructure planning elements in order to reduce exposure to particulate matter.