• The Korean Journal of Applied Statistics
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• v.32 no.6
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• pp.909-922
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• 2019

In this paper, we study the adaptive least absolute shrinkage and selection operator (LASSO) for the unstable autoregressive (AR) model. To identify the existence of the unit root, we apply the adaptive LASSO to the augmented Dickey-Fuller regression model, not the original AR model. We illustrate our method with simulations and a real data analysis. Simulation results show that the adaptive LASSO obtained by minimizing the Bayesian information criterion selects the order of the autoregressive model as well as the degree of differencing with high accuracy.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.37 no.5
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• pp.855-862
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• 2017

The Republic of Korea has achieved rapid growth in economic, cultural and social through the development policy over the past half-century. However, principle of the nodal system has made an overgrown city and underdeveloped regions. A range of policies have been introduced aimed at underdeveloped regions. But many problems were found in policies. Because government ministry and public services were many and various. In addition, development priority are not based on objective index, Distribution business for the local government have been carried out. A study of the Index selection of the existing regions, has been large-scale center analysis. Thus, the difficulty is often in selecting the priorities of small unit operations. It is difficult to reach a selection of business to region priorities. Accordingly I want to be used as material for the efficient development of rural areas through the selection of indicators for a small areas. Intend to use the decision support system for the efficient development of small underdeveloped areas through index selection for a small and underdeveloped regions.

• Journal of Communications and Networks
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• v.18 no.1
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• pp.50-64
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• 2016

Nowadays, smart meter (SM) technology is widely effectively used. In addition, power allocation (PA) and channel selection (CS) are considered problems with many proposed approaches. In this paper, we will suggest a specific scenario for an SM configuration system and show how to solve the optimization problem for transmission between SMs and the data concentrator unit (DCU), the center that collects the data from several SMs, via simulation. An efficient CS with PA scheme is proposed in the TV white space system, which uses the TV band spectrum. On the basic of the optimal configuration requirements, SMs can have a transmission schedule and channel selection to obtain the optimal efficiency of using spectrum resources when transmitting data to the DCU. The optimal goals discussed in this paper are the maximum capacity or maximum channel efficiency and the maximum allowable power of the SMs used to satisfy the quality of service without harm to another wireless system. In addition, minimization of the interference to the digital television system and other SMs is also important and needs to be considered when the solving coexistence scenario. Further, we propose a process that performs an interference analysis scheme by using the spectrum engineering advanced Monte Carlo analysis tool (SEAMCAT), which is an integrated software tool based on a Monte-Carlo simulation method. Briefly, the process is as follows: The optimization process implemented by genetic evolution optimization engines, i.e., a genetic algorithm, will calculate the best configuration for the SM system on the basis of the interference limitation for each SM by SEAMCAT in a specific configuration, which reaches the solution with the best defined optimal goal satisfaction.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.18 no.7
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• pp.970-979
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• 1993

In this paper, a multi-function processor unit is implemented for binary image processing. This unit consists of a set of address generatior, window pipeline register, look up table, control unit, and two local memories .The merits of multi-function processor unit are more simpler than basic SAP and improved disposal speed. A simple software selection give the various choices of image sizes and it can process the function of smoothing, thinning, feature extraction, and edge detection, selectively or sequentially.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.21 no.1
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• pp.67-79
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• 1996

This paper presents a composite luminance signal processing system for NTSC, PAL and SECAM standards. Eaxh of the three standards employs its own specifications of subcarmier bandwidth and luminance signal waveform. The proposed system, compatible to the specifications of the three standard and B/W TV, implements variable freqneucy characteristics by controlling filter coefficients. The major features of the system are a luminance/chroma separation unit and an aperture compensation unit. The luminance/chroma separation unit employes a notch filter selection a trap freqneyc to atenuate unwanted color signals in luminance signal bands. The aperture compensation unit comprises two subunits, to provide clear color definition for each of the three standards: a primary compensation circuit and a variable compensation circuits. The proposed system yields a 40 dB gain from the chroma/luminance separation and a 10 dB gain from the aperture compensation unit.

• Journal of Biosystems Engineering
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• v.40 no.4
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• pp.417-427
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• 2015

Purpose: This study investigated different band selection methods to classify spectrally similar data - obtained from aerial images of healthy citrus canopies and citrus greening disease (Huanglongbing or HLB) infected canopies - using small differences without unmixing endmember components and therefore without the need for an endmember library. However, large number of hyperspectral bands has high redundancy which had to be reduced through band selection. The objective, therefore, was to first select the best set of bands and then detect citrus Huanglongbing infected canopies using these bands in aerial hyperspectral images. Methods: The forward feature selection algorithm (FFSA) was chosen for band selection. The selected bands were used for identifying HLB infected pixels using various classifiers such as K nearest neighbor (KNN), support vector machine (SVM), naïve Bayesian classifier (NBC), and generalized local discriminant bases (LDB). All bands were also utilized to compare results. Results: It was determined that a few well-chosen bands yielded much better results than when all bands were chosen, and brought the classification results on par with standard hyperspectral classification techniques such as spectral angle mapper (SAM) and mixture tuned matched filtering (MTMF). Median detection accuracies ranged from 66-80%, which showed great potential toward rapid detection of the disease. Conclusions: Among the methods investigated, a support vector machine classifier combined with the forward feature selection algorithm yielded the best results.

• Journal of the Korean GEO-environmental Society
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• v.14 no.10
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• pp.11-16
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• 2013

Success or failure of the bi-directional pile load test for drilled shaft depends on point selection for loading cells, that is balanced location both uplift force and downward force. Methods to evaluate the ultimate unit side resistance in rockmass layer in both domestic and foreign are based on the uniaxial compression strength of rock core, which can hardly be obtained in domestic rockmass layers which are weathered rockmass layer and soft rockmass layer with very low RQD. Therefore, this study suggested the relation charts between the revised SPT N values and developed unit side resistance of each different layers, which were obtained from bi-directional pile load tests in various domestic sites. To evaluate the appropriateness of the relation charts, the developed unit side resistances from the relation charts were used to select the loading cell position and compared with the measured unit side resistances from field pile load test. Results showed that the developed side resistance from relation charts and the measured side resistance of weathered soil layer and weathered rock layer were very close. Average developed side resistance($1,325kN/m^2$), which are average of upper soft rock layer of loading device($1,151kN/m^2$) and lower($1,500kN/m^2$), was similar with the estimated value ($1,250kN/m^2$).

• Journal of the Korean Institute of Landscape Architecture
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• v.36 no.5
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• pp.64-72
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• 2008

The purpose of this study is to compare a habitat suitability grid unit included within a radius of 100m and $1km^2,\;2km^2,\;4km^2$ watershed units in order to predict suitable habitats for Chungcheong province's endangered leopard species(Prionailurus bengalensis). Other developed countries have carried out habitat assessment and established management policies for species conservation using such methods as HEP(Habitat Evaluation Procedures), HSI(Habitat Suitability Index) and GAP(Gap Analysis Program), etc. In accordance with these studies, many evaluation methods for habitat conservation have been proposed in Korea, but these studies are lacking in consideration of analytic units and general application of analysis results. This study predicted leopard habitat using a logistic regression analysis according to analytic units by data from 56 location and 8 sources of environmental data, including elevation, slope, forest area, land cover, roads, water, broadleaf trees, and human habitation. Moreover, the habitat suitability assessment unit was confirmed by a model comparison process encompassing model explanation. verification, and application on a regional scale. Results showed that assessment methods that took into consideration areas in and around the location points were beneficial in predicting habitat and that the assessment unit was appropriate for a 30m grid unit including areas within a radius of 100m and a $1km^2$ watershed unit in Chungcheong Province. This study suggests a method for regional habitat conservation to complement existing conservation area selection methods, and the results are expected to be used in conservation area selection and ecosystem management policies for endangered species.

• Animal Bioscience
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• v.37 no.4
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• pp.576-590
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• 2024

Objective: The objective of this study was to identify genes associated with 305-day milk yield (MY) and fat yield (FY) that also influence the adaptability of the Thai multibreed dairy cattle population to tropical conditions. Methods: A total of 75,776 imputed and actual single nucleotide polymorphisms (SNPs) from 2,661 animals were used to identify genomic regions associated with MY and FY using the single-step genomic best linear unbiased predictions. Fixed effects included herd-year-season, breed regression, heterosis regression and calving age regression effects. Random effects were animal additive genetic and residual. Individual SNPs with a p-value smaller than 0.05 were selected for gene mapping, function analysis, and quantitative trait loci (QTL) annotation analysis. Results: A substantial number of QTLs associated with MY (9,334) and FY (8,977) were identified by integrating SNP genotypes and QTL annotations. Notably, we discovered 17 annotated QTLs within the health and exterior QTL classes, corresponding to nine unique genes. Among these genes, Rho GTPase activating protein 15 (ARHGAP15) and catenin alpha 2 (CTNNA2) have previously been linked to physiological traits associated with tropical adaptation in various cattle breeds. Interestingly, these two genes also showed signs of positive selection, indicating their potential role in conferring tolerance to trypanosomiasis, a prevalent tropical disease. Conclusion: Our findings provide valuable insights into the genetic basis of MY and FY in the Thai multibreed dairy cattle population, shedding light on the underlying mechanisms of tropical adaptation. The identified genes represent promising targets for future breeding strategies aimed at improving milk and fat production while ensuring resilience to tropical challenges. This study significantly contributes to our understanding of the genetic factors influencing milk production and adaptability in dairy cattle, facilitating the development of sustainable genetic selection strategies and breeding programs in tropical environments.

• International journal of advanced smart convergence
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• v.9 no.2
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• pp.58-67
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• 2020

In this paper, we propose a data-driven-based beam selection scheme for massive multiple-input and multiple-output (MIMO) systems in ultra-dense networks (UDN), which is capable of addressing the problem of high computational cost of conventional coordinated beamforming approaches. We consider highly dense small-cell scenarios with more small cells than mobile stations, in the millimetre-wave band. The analog beam selection for hybrid beamforming is a key issue in realizing millimetre-wave UDN MIMO systems. To reduce the computation complexity for the analog beam selection, in this paper, two deep neural network models are used. The channel samples, channel gains, and radio frequency beamforming vectors between the access points and mobile stations are collected at the central/cloud unit that is connected to all the small-cell access points, and are used to train the networks. The proposed machine-learning-based scheme provides an approach for the effective implementation of massive MIMO system in UDN environment.