• Journal of the Economic Geographical Society of Korea
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• v.24 no.4
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• pp.411-424
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• 2021

The purpose of this study is to analyze the location characteristics of convenience stores, a consumption industry that forms a new retail environment and implements unattended, and reveals the geographic factors that affect its location. For this purpose, we first examine the growth and regional distribution of manned convenience stores and then construct a gamma generalized linear regression model that explains the distribution of the unmanned convenience stores as well as the manned and unmanned combined convenience stores. As the result, it was observed that the unmanned convenience stores and the unmanned discount stores are located close to public transportation facilities and they have relatively little movement of the population but they are distributed in areas with a higher density of young residential population and densely distributed retail stores and restaurants. The effects of demographic factors on the location of the unmanned convenience stores and the unmanned discount stores differed according to the scope and characteristics of their sales items. Our findings provide an empirical basis for subsequent academic research as an initial study that identified geographic factors influencing the selection of opening locations for unmanned stores.

• Journal of Animal Science and Technology
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• v.64 no.3
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• pp.471-480
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• 2022

This experiment was conducted to determine the maximum dietary energy levels on growth performance and carcass characteristics of White Pekin duck. the Six dietary treatments were formulated based on their apparent metabolizable energy (AME) concentrations from 2,700 to 3,200 kcal/kg with a 100 kcal/kg gap to evaluate the accurate dietary AME requirement to address current knowledge and further issues for fulfilling the genetic potential of meat-type white Pekin ducklings. A total of 432 one-day-old male White Pekin ducklings were randomly allocated into one of six dietary treatments with six replicates (12 birds per pen). The diets were formulated as corn-soybean meal-based diets to meet or exceed the Nutrient Requirement of Poultry specification for meat-type ducks. Growth performance indices (i.e. average daily gain [ADG], average daily feed intake, feed conversion ratio) were measured weekly. Medium body weight (BW) ducklings from each pen were sacrificed to analyze the carcass traits and abdominal fat content on day 21. Obtained data were analyzed to estimate significant effect using the one-way ANOVA of IBM SPSS Statistics (Version, 25). If the p-value of the results were significant, differences in means among treatments were separated by Tukey's post hoc test. Significant differences were then analyzed with a linear and quadratic broken model to estimate the accurate concentration of AME. Ducklings fed higher dietary AME diets increased (p < 0.05) BW, ADG. Ducklings fed higher AME than 2,900 kcal/kg diets increased abdominal fat accumulation and leg meat portion. The estimated requirement by linear plateau method showed from 3,000.00 kcal/kg to 3,173.03 kcal/kg whereas the requirement by quadratic plateau method indicated from 3,100.00 kcal/kg to 3,306.26 kcal/kg. Collectively, estimated dietary requirements exhibit diverse results based on the measured traits and analysis methods. All the estimated requirements in this experiment present higher than previous research, the maximum requirement for the next diet formulation should be selected by the purpose of the diet.

• Journal of Information Technology Services
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• v.18 no.1
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• pp.113-130
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• 2019

Data can be considered a core driver of the Fourth Industrial Revolution, and databases are needed to create value by efficiently obtaining, storing and analyzing the data. However, there are currently no adequate valuation methods to handle databases. This study aims first, to understand databases as the subject of valuation and analyze value drivers of databases, and second, to propose a database valuation model based on this finding. To this end, we derive value drivers of databases from the characteristics and value criteria of databases observed in previous studies. Based on survey data from 396 database service firms we verify the value drivers through linear regression analysis. We find that the annual growth rate in database capacity and the data types positively affect sales of databases and offer ways to utilize them when estimating the cash flow, which is the variable to apply the discounted cash flow method-based income approach. This study contributes empirical insights into how to valuate databases considering their value drivers.

• Journal of the Institute of Electronics Engineers of Korea TC
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• v.47 no.2
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• pp.9-17
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• 2010

Recently, there has been much interest in orthogonal frequency division multiplexing (OFDM) for next generation wireless wideband communication systems. OFDM is a special case of multicarrier transmission, where a single data stream is transmitted over a number of lower-rate subcarriers. One of the main reasons to use OFDM is to increase robustness against frequency-selective fading or narrowband interference. However, in the radio systems it is also important to distortion introduced by high power amplifiers (HPA's) such as solid state power amplifier (SSPA) considered in this paper. Since the signal amplitude of the OFDM system is Rayleigh-distributed, the performance of the OFDM system is significantly degraded by the nonlinearity of the HPA in the OFDM transmitter. In this paper, we propose a canonical piecewise-linear (PWL) model based digital predistorter to prevent signal distortion and spectral re-growth due to the high peak-to-average power ratio (PAPR) of OFDM signal and the nonlinearity of HPA's. Computer simulation on an OFDM system under additive white Gaussian noise (AWGN) channels with QPSK, 16-QAM and 64-QAM modulation schemes and modulator/demodulator implemented with 1024-point FFT/IFFT, demonstrate that the proposed predistorter achieves significant performance improvement by effectively compensating for the nonlinearity introduced by the SSPA.

• Korean Journal of Agricultural and Forest Meteorology
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• v.23 no.4
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• pp.329-339
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• 2021

Soybeans (Glycine max), one of major upland crops, require precise management of environmental conditions, such as temperature, water, and soil, during cultivation since they are sensitive to environmental changes. Application of spectral technologies that measure the physiological state of crops remotely has great potential for improving quality and productivity of the soybean by estimating yields, physiological stresses, and diseases. In this study, we developed and validated a soybean growth prediction model using multispectral imagery. We conducted a linear regression analysis between vegetation indices and soybean growth data (fresh weight and LAI) obtained at Miryang fields. The linear regression model was validated at Goesan fields. It was found that the model based on green ratio vegetation index (GRVI) had the greatest performance in prediction of fresh weight at the calibration stage (R²=0.74, RMSE=246 g/m², RE=34.2%). In the validation stage, RMSE and RE of the model were 392 g/m² and 32%, respectively. The errors of the model differed by cropping system, For example, RMSE and RE of model in single crop fields were 315 g/m² and 26%, respectively. On the other hand, the model had greater values of RMSE (381 g/m²) and RE (31%) in double crop fields. As a result of developing models for predicting a fresh weight into two years (2018+2020) with similar accumulated temperature (AT) in three years and a single year (2019) that was different from that AT, the prediction performance of a single year model was better than a two years model. Consequently, compared with those models divided by AT and a three years model, RMSE of a single crop fields were improved by about 29.1%. However, those of double crop fields decreased by about 19.6%. When environmental factors are used along with, spectral data, the reliability of soybean growth prediction can be achieved various environmental conditions.

• Horticultural Science & Technology
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• v.32 no.4
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• pp.493-498
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• 2014

The objective of this study was to make growth and yield models for common ice plant (Mesembryanthemum crystallinum L.) using expolinear functional equations in a closed-type plant production system. Three-band radiation type fluorescent lamps with a 12-hours photoperiod were used, and the light intensity was $200{\mu}mol{\cdot}m^{-2}{\cdot}s^{-1}$. Nutrient film systems with three layers were used for plant growth. Environmental conditions, such as air temperature, relative humidity and $CO_2$ concentration were controlled by an ON/OFF operation. Leaf area, shoot fresh and dry weights, light use efficiency of common ice plant as function of days after transplanting, accumulative temperature and accumulative radiation were analyzed. Leaf area, shoot fresh and dry weights per area were described using an expolinear equation. A linear relationship between shoot dry and fresh weights was observed. Light use efficiency of common ice plant was $3.3g{\cdot}MJ^{-1}$ at 30 days after transplanting. It is concluded that the expolinear growth model can be a useful tool for quantifying the growth and yield of common ice plant in a closed plant production system.

• Korean Journal of Weed Science
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• v.30 no.2
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• pp.94-102
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• 2010

Field and pot experiments were conducted to investigate seedling emergence and early growth of Eleocharis kuroguwai panted on different dates. Non-linear regression analyses of observed data against effective accumulated temperature (EAT) with the Gompertz model showed that the Gompertz model works well in describing seedling emergence and early growth of E. kuroguwai regardless of planting date and soil burial depth. EATs required for 50% of the maximum seedling emergence of E. kuroguwai planted at 1, 3 and 5 cm soil burial depth in the pot experiment were estimated to be 54.5, 84.0 and $118.0^{\circ}C$, respectively, and $56.7^{\circ}C$ when planted at 1 cm in the field experiment. EATs required for 50% of the maximum leaf number of E. kuroguwai planted at 1, 3 and 5 cm soil burial depth in the pot experiment were estimated to be 213.3, 249.0 and $291.6^{\circ}C$, respectively, and $239.5^{\circ}C$ when planted at 1 cm in the field experiment. Therefore, models developed in this study thus predicted that if rotary tillage with water is made on 27 May under $+2^{\circ}C$ elevated temperature condition, dates for 50% of the maximum seedling emergence, 5 leaf stage and 5 cm plant height of E. kuroguwai buried at 3 cm soil depth were predicted to be 2 June, 10 June and 12 June. These dates are 1 day earlier for the seedling emergence and 3 days earlier for the early growth as compared with current temperature condition, suggesting that earlier application of herbicides is required for effective control of E. kuroguwai.

• International Journal of Contents
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• v.16 no.3
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• pp.66-86
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• 2020

With the rapid growth of high-tech, the development of cultural and creative industries has gradually become the focus of national industrial development. With the proposal of China's "Belt and Road" strategy, the role of cultural and creative industries in the provinces and cities along the "Belt and Road" in the entire international trade is becoming increasingly critical. It is necessary to explore solutions to improve the competitiveness of China's cultural and creative industries, factoring the surrounding cities of the "Belt and Road" as an example. Thus, this paper proposes the six-element diamond model based on innovation capability and government support to render a comprehensive evaluation of the competitiveness of the cultural and creative industries in the 31 provinces and cities across the country. The results show that the overall competitiveness of the 18 provinces and cities along the "Belt and Road" cultural and creative industries is weak. Focusing on the 18 provinces and cities along the "Belt and Road", using the linear regression measurement model quantitative analysis, the four types of influencing factors affecting the development of the competitiveness of cultural and creative industries along the "Belt and Road" were obtained. Finally, according to the four types of influence, the competitiveness improvement plan is proposed from the four aspects: government role, consumption preference, industrial innovation ability, and the introduction of high-quality talent.

• Journal of Korean Society of Coastal and Ocean Engineers
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• v.5 no.3
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• pp.212-220
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• 1993

A numerical model for the transformation of irregular waves in a coastal area is developed, which takes account of shoaling, refraction, diffraction, bottom friction and wave breaking. The governing equations are the usual energy conservation equation and kinematic conservation equations, but to consider the diffraction effects additional terms are included in the usual kinematic conservation or wave number equations. A linear superposition technique is used to represent the spectral formation. and an explicit formula is developed for the estimation of friction factor of irregular waves. A breaking criterion of component waves, which is the modified form of the Kitaigorodskii saturation relation, is employed to restrict the growth of shoaling waves in very shallow waters. The model was applied to a laboratory test and satisfactory agreement was obtained between the computation and measurement.

• Proceedings of the KIEE Conference
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• 2003.07d
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• pp.2627-2629
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• 2003

In this paper, we propose a new architecture of Genetic Algorithms(GAs)-based Self-Organizing Polynomial Neural Networks(SOPNN). The conventional SOPNN is based on the extended Group Method of Data Handling(GMDH) method and utilized the polynomial order (viz. linear, quadratic, and modified quadratic) as well as the number of node inputs fixed (selected in advance by designer) at Polynomial Neurons (or nodes) located in each layer through a growth process of the network. Moreover it does not guarantee that the SOPNN generated through learning has the optimal network architecture. But the proposed GA-based SOPNN enable the architecture to be a structurally more optimized networks, and to be much more flexible and preferable neural network than the conventional SOPNN. An aggregate performance index with a weighting factor is proposed in order to achieve a sound balance between approximation and generalization (predictive) abilities of the model. To evaluate the performance of the GA-based SOPNN, the model is experimented with using nonlinear system data.