• Journal of the Korean Data and Information Science Society
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• v.22 no.3
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• pp.605-612
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• 2011

In multi-center randomized clinical trial the treatment eect may be changed over centers. It is thus important to investigate the heterogeneity in treatment eect between centers. For this, uncorrelated random-eect models assuming independence between random-eect terms have been often used, which may be a strong assumption. In this paper we propose a correlated frailty modelling approach of investigating such heterogeneity using the hierarchical-likelihood method when the outcome is time-to-event. In particular, we show how to construct a proper prediction interval for frailty, which explores graphically the potential heterogeneity for a treatment-by-center interaction term. The proposed method is illustrated via numerical studies based on data from the design of a multi-center clinical trial.

• 한국공간정보시스템학회:학술대회논문집
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• 2004.05a
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• pp.190-196
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• 2004

Thick composite laminated plates is considered in 3D finite-element. To consider continuity of transverse stresses and displacement field, mixed finite-element has been developed by using layerwise theory and the minimum potential energy principle. Mixed finite-element has been enforced through the thick direction, Z, of a laminated plate by considering six degree-of-freedoms per node. Six degree-of-freedoms are three displacement components in the coordinate axes directions and three transverse stress components ${\sigma}_z,\;{\tau}_{xz},\;{\tau}_{yz}$. The model maintain the fundamental elasticity relations that are stress-strain relation and displacement-strain relation, because the transverse stress components invoked as nodal degrees of freedom by using the fundamental elasticity relationship between th components of stress and displacement. Random vibration analysis of the model is performed by computing consistent mass matrix and computing covariance in frequency domain technique.

• Korean Journal of Fisheries and Aquatic Sciences
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• v.29 no.6
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• pp.761-769
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• 1996

The random amplified polymorphic DNA (RAPD) technique was used to characterize 18 reference strains of microalgae, mostly Chlorella species, collected from various localities around Korea peninsular. Eighteen strains consist of four genera of the family marine Chlorella from 12 samples, two genera of fresh water Chlorella from three samples, and three genera on Nannochloris. Twenty 10-mer anonymous primers were screened for amplification of genomic DNA extracted from samples using the CTAB extraction method. Nineteen of these oligonucleotide primers were positive or band producing. Three of 20 random primers (OPA 10, OPA 12, and OPA 18) resulted in both clear band and a high degree of reproducibility and showed some potential to be used to discriminate individual samples of both genetically hetero-and homogeneous populations, in determining phylogenetic relationships between species within a genus and developing individual fingerprints for each samples.

• Communications for Statistical Applications and Methods
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• v.16 no.6
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• pp.1031-1036
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• 2009

Under recent dramatic declines in response rates, various procedures have been considered among survey practitioners to reduce nonresponse in order to avoid its potential impairment to the inference. In the random digit dialing telephone surveys, substantial efforts are often required to obtain the initial contact for the screener interview. To reduce a burden with higher data collection costs, refusal conversion can be administered only to a random portion of the sample, reducing nonresponse (bias) with an expense of sample variability increment due to the associated weight adjustment. In this paper, we provide ways to determine the optimal subsampling rate using a linear cost model. Our approach for refusal subsampling is to predetermine a random portion from the full sample and to apply refusal conversion efforts if needed only to the subsample.

• IEIE Transactions on Smart Processing and Computing
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• v.4 no.6
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• pp.443-449
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• 2015

This paper considers the physical layer security problem for a two-way vehicle-to-vehicle network, where the two source vehicles can only exchange information through an untrusted relay vehicle. The relay vehicle helps the two-way transmission but also acts as a potential eavesdropper. Each vehicle has a random velocity. By exploiting the random carrier frequency offsets (CFOs) caused by random motions, a secure double-differential two-way relay scheme is proposed. While achieving successful two-way transmission for the source vehicles, the proposed scheme guarantees a high decoding error floor at the untrusted relay vehicle. Average symbol error rate (SER) performance for the source vehicles and the untrusted relay vehicle is analyzed. Simulation results are provided to verify the proposed scheme.

• The Journal of Asian Finance, Economics and Business
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• v.7 no.10
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• pp.201-210
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• 2020

This study aimed to analyze the influence of the industrial growth and the effect on government tax potential of the South Sulawesi Province. The growth of the tax object affects government tax potential of South Sulawesi Province. Environmental resources affect government tax potential of the province. The study used multiple linear regressions on primary data. The population consisted of all officers and staff involved in regional work units. Revenue Service area in South Sulawesi Province counts 630 employees. The sampling method is purposive sampling random carried out based on specific objectives. The respondent qualifications are taken from the Technical Implementation Unit Office and the Department of Revenue. The number of respondents is 96 from the Head of UPTD and three of them are related with tax Section Chief Officer. The results showed that industrial growth has a significant and positive effect on the potential increase in tax of South Sulawesi. Growth in tax object significantly affects the potential increasing tax of South Sulawesi. Environmental resources significantly affect the potential Increase in tax. Practical recommendations for local government is to enhance tax potential, reduce bureaucracy in industrial licensing, and facilitate local farmers to get involved in economic contributions.

• Journal of the Korean Society of Environmental Restoration Technology
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• v.26 no.5
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• pp.19-32
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• 2023

The fragmentation of habitats resulting from human activities leads to the isolation of wildlife and it also causes wildlife-vehicle collisions (i.e. Road-kill). In that sense, it is important to predict potential habitats of specific wildlife that causes wildlife-vehicle collisions by considering geographic, environmental and transportation variables. Road-kill, especially by large mammals, threatens human safety as well as financial losses. Therefore, we conducted this study on roe deer (Capreolus pygargus tianschanicus), a large mammal that causes frequently Road-kill in Jeju Island. So, to predict potential wildlife habitats by considering geographic, environmental, and transportation variables for a specific species this study was conducted to identify high-priority restoration sites with both characteristics of potential habitats and road-kill hotspot. we identified high-priority restoration sites that is likely to be potential habitats, and also identified the known location of a Road-kill records. For this purpose, first, we defined the environmental variables and collect the occurrence records of roe deer. After that, the potential habitat map was generated by using Random Forest model. Second, to analyze roadkill hotspots, a kernel density estimation was used to generate a hotspot map. Third, to define high-priority restoration sites, each map was normalized and overlaid. As a result, three northern regions roads and two southern regions roads of Jeju Island were defined as high-priority restoration sites. Regarding Random Forest modeling, in the case of environmental variables, The importace was found to be a lot in the order of distance from the Oreum, elevation, distance from forest edge(outside) and distance from waterbody. The AUC(Area under the curve) value, which means discrimination capacity, was found to be 0.973 and support the statistical accuracy of prediction result. As a result of predicting the habitat of C. pygargus, it was found to be mainly distributed in forests, agricultural lands, and grasslands, indicating that it supported the results of previous studies.

• The Journal of the Korea Contents Association
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• v.20 no.11
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• pp.636-643
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• 2020

The differential evolution algorithm is one of the meta-heuristic techniques developed to solve the real optimization problem, which is a continuous problem space. In this study, in order to use the differential evolution algorithm to solve the traveling salesman problem, which is a discontinuous problem space, a random key representation method is applied to the differential evolution algorithm. The differential evolution algorithm searches for a real space and uses the order of the indexes of the solutions sorted in ascending order as the order of city visits to find the fitness. As a result of experimentation by applying it to the benchmark traveling salesman problems which are provided in TSPLIB, it was confirmed that the proposed differential evolution algorithm based on the random key representation method has the potential to solve the traveling salesman problems.

• Geomechanics and Engineering
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• v.22 no.3
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• pp.207-217
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• 2020

Slope reliability analysis and risk assessment for spatially variable soils under rainfall infiltration are important subjects but they have not been well addressed. This lack of study may in part be due to the multiple and diverse evaluation indexes and the low computational efficiency of Monte-Carlo simulations. To remedy this, this paper proposes a highly efficient computational method for investigating random field problems for slopes. First, the probability density evolution method (PDEM) is introduced. This method has high computational efficiency and does not need the tens of thousands of numerical simulation samples required by other methods. Second, the influence of rainfall on slope reliability is investigated, where the reliability is calculated from based on the safety factor curves during the rainfall. Finally, the uncertainty of the sliding mass for the slope random field problem is analyzed. Slope failure consequences are considered to be directly correlated with the sliding mass. Calculations showed that the mass that slides is smaller than the potential sliding mass (shallow surface sliding in rainfall). Sliding mass-based risk assessment is both needed and feasible for engineered slope design. The efficient PDEM is recommended for problems requiring lengthy calculations such as random field problems coupled with rainfall infiltration.

• Industrial Engineering and Management Systems
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• v.16 no.1
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• pp.64-79
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• 2017

Identifying disease genes from human genome is a critical task in biomedical research. Important biological features to distinguish the disease genes from the non-disease genes have been mainly selected based on traditional feature selection approaches. However, the traditional feature selection approaches unnecessarily consider many unimportant biological features. As a result, although some of the existing classification techniques have been applied to disease gene identification, the prediction performance was not satisfactory. A small set of the most important biological features can enhance the accuracy of disease gene identification, as well as provide potentially useful knowledge for biologists or clinicians, who can further investigate the selected biological features as well as the potential disease genes. In this paper, we propose a new stepwise random forests (SRF) approach for biological feature selection and disease gene identification. The SRF approach consists of two stages. In the first stage, only important biological features are iteratively selected in a forward selection manner based on one-dimensional random forest regression, where the updated residual vector is considered as the current response vector. We can then determine a small set of important biological features. In the second stage, random forests classification with regard to the selected biological features is applied to identify disease genes. Our extensive experiments show that the proposed SRF approach outperforms the existing feature selection and classification techniques in terms of biological feature selection and disease gene identification.