• Journal of Korean Society of Transportation
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• v.31 no.1
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• pp.15-24
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• 2013

To accommodate urban concentration of population, multi-purpose super-tall buildings have been introduced, but they induce many travel demands causing regional traffic problems. While several travel demand management policies such as transit promotion or parking limits are presented to alleviate such problems, transportation infrastructure are still insufficient to meet high demands. In this study, super-tall buildings are categorized by scale and purpose, then mode-specific derived demand is estimated using modal share of each category. Optimal transportation infrastructure level is determined by condition-based average changing amount yielded by street network delay (in case of road) or the number of transit routes (in case of transit).

• Asian Pacific Journal of Cancer Prevention
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• v.17 no.6
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• pp.2847-2852
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• 2016

Background: Although the breast cancer incidence rate in Japan is lower than in western countries, the age-specific rates have markedly increased in recent years, along with the problems of declining birth rate and an aging population. Materials and Methods: We examined past trends of age-specific breast cancer incidence using data from the Osaka Cancer Registry from 1976 to 2010, and estimated future trends until 2025 based on the changes observed and population dynamics using a log linear regression model. Results: The age-specific breast cancer incidence rate has increased consistently from the 1970s, and the rates have caught up with those of Japanese-Americans in the US. Assuming the increasing tendency of age-specific breast cancer incidence to be constant, the average annual incidence of breast cancer will increase 1.7-fold from 2006-2010 to 2021-2025. Furthermore, the number of patients aged 80 years should increase 3.4-fold. Conclusions: The medical demand for breast cancer care in Japan may increase explosively in the future, particularly among the elderly. We need to prepare for such a future increase in demand for care, although careful monitoring is needed to confirm these results.

• Earthquakes and Structures
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• v.5 no.1
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• pp.49-65
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• 2013

This article presents the statistical characteristics of elastic floor acceleration spectra that represent the peak response demand of non-structural components attached to a nonlinear supporting frame. For this purpose, a set of stiff and flexible general moment resisting frames with periods of 0.3-3.6 sec. are analyzed using forty-nine near-field strong ground motion records. Peak accelerations are derived for each single degree of freedom non-structural component, supported by the above mentioned frames, through a direct-integration time-history analysis. These accelerations are obtained by Floor Acceleration Response Spectrum (FARS) method. They are statistically analyzed in the next step to achieve a better understanding of their height-wise distributions. The factors that affect FARS values are found in the relevant state of the art. Here, they are summarized to evaluate the amplification and/or reduction of FARS values especially when the supporting structures undergo inelastic behavior. The properties of FARS values are studied in three regions: long-period, fundamental-period and short-period. Maximum elastic acceleration response of non-structural component, mounted on inelastic frames, depends on the following factors: inelasticity intensity and modal periods of supporting structure; natural period, damping ratio and location of non-structural component. The FARS values, corresponded to the modal periods of supporting structure, are strongly reduced beyond elastic domain. However, they could be amplified in the transferring period domain between the mentioned modal periods. In the next step, the amplification and/or reduction of FARS values, caused by inelastic behavior of supporting structure, are calculated. A parameter called the response acceleration reduction factor ($R_{acc}$), has been previously used for far-field earthquakes. The feasibility of extending this parameter for near-field motions is focused here, suggested repeatedly in the relevant sources. The nonlinearity of supporting structure is included in ($R_{acc}$) for better estimation of maximum non-structural component absolute acceleration demand, which is ordinarily neglected in the seismic design provisions.

• Korean Journal of Agricultural Science
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• v.49 no.1
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• pp.61-75
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• 2022

The first purpose of this study is to evaluate the usefulness of pork traceability data, which is monthly time-series data, and to draw implications with regard to its usefulness. The second purpose is to construct a dynamic ecological equation model (DEEM) that reflects the biological characteristics at each growth stage, such as pregnancy, birth and growth, and the slaughter of pigs, using traceability data. With the monthly pig model devised in this study, it is expected that the number of slaughtered animals (supply) that can be shipped in the future is predictable and that policy simulations are possible. However, this study was limited to traceability data and focused only on building a supply-side model. As a result of verifying the traceability data, it was found that approximately 6% of farms produce by mixing great grand parent (GGP), grand parent (GP), parent stock (PS), and artificial insemination (AI), meaning that it is necessary to separate them by business type. However, the analysis also showed that the coefficient values estimated by constructing an equation for each growth stage were consistent with the pig growth outcomes. Also, the model predictive power test was excellent. For this reason, it is judged that the model design and traceability data constructed with the cohort and the dynamic ecological equation model system considering biological growth and shipment times are excellent. Finally, the model constructed in this study is expected to be used as basic data to inform producers in their decision-making activities and to help with governmental policy directions with regard to supply and demand. Research on the demand side is left for future researchers.

• Economic Analysis
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• v.26 no.4
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• pp.98-136
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• 2020

We empirically investigate the determinants of a firm's exit from exporting, using Korean manufacturing firm-level data for the period from 2006 to 2014. Specifically, we estimate the effects of not only firm-level and industry-level characteristics, but also macroeconomic variables on the probability that a firm stops exporting by applying a Complementary Log-Log Model analysis. The results of our estimation suggest that firm-level heterogeneity, such as workforce size, capital intensity, intangible assets and foreign ownership, industry-level variation, such as the labor displacement rate, and macroeconomic variables, such as domestic demand and world demand, significantly affect the possibility of a firm ceasing exports. Also, we show that market interest rates increase the possibility of an export cessation and that the effects of market interest rates are more pronounced on firms with a higher debt ratio. In the primary exporting industries, the probability of a firm ceasing exports decreases as productivity at the firm rises.

• Korean Journal of Fisheries and Aquatic Sciences
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• v.34 no.4
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• pp.348-354
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• 2001

This study was conducted to estimation of change characteristics for water quality by the dyke gate operation in the Keum River estuary. The estimation data made use of surveyed data in Keum River estuary by NERDI (National Fisheries Research and Development Institute) during $1990\~1999$. Shown to compare water quality changes at st. A and st. D in Figure 1, the concentrations of TSS, COD and nutrients at st. A were as high as about $2\~4$ times than those at st. D due to affection of fresh water discharge in the Keum River. The percentages of water quality change at surface water by dyke gate operation in the Keum River estuary were shown that TSS (Total Suspended Solid) was decrease to $56\%,\;47\%$ at st. A and D, and COD (Chemical Oxygen Demand) was increase to $68\%,\;71\%$ at st. A and D, respectively. The changes percentage of DIN (Dissolved Inorganic Nitrogen) by dyke gate operation in the Keum River estuary were increase high to $95\%$ at surface water and $7\sim30\%$ at bottom water, but those of DIP (Dissolved Inorganic Phosphorus) were increase to $2.8\sim8.6\%$ at surface water and $28\%$ at bottom water. The range of fluctuation for water quality at each station by dyke gate operation has shown that salinity and TSS are little better than before dyke gate operation, but COD show highly fluctuation. Also we studied estimation of characteristics of water quality change by the season, COD was increased except the summer, TSS was decreased to all season. DIN was increased to about $61\sim172.1\%$ for all season, but DIP was increased to the spring and decreased to the autumn, DIN enrichment in the estuary by dyke gate operation are interpreted to improvement of organic matter decomposition and nitrification by increasing the residence time and to increase nutrient flux in sediments due to decreasing dissolved oxygen and increasing a deposit matter.

• Journal of the Institute of Electronics and Information Engineers
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• v.51 no.7
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• pp.60-68
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• 2014

In modern electronic warfare systems, a demand on the more accurate estimation method based on TDOA and FDOA has been increased. TDOA/FDOA localization consists of two-stage procedures; the extraction of information from signals, and the estimation of emitter location. CAF(complex ambiguity function) is known as a basic method in the extraction stage. However, when we extract TDOA and FDOA information from VHF(very high frequency) communication signals, conventional CAF algorithms may not work within a permitted time because of much computation. Therefore, in this paper, an improved sequential estimation algorithm based on CAF is proposed for effective calculation of extracting TDOA and FDOA estimates in terms of computational complexity. The proposed method is compared with the conventional CAF-based algorithms through simulation. In addition, we derive the optimal performance based on the CRLB(Cramer-Lao lower bound) to check the extraction performance of the proposed method.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.41 no.2
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• pp.254-262
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• 2016

With the increased demand for automotive radar systems, mutual interference between vehicles has become a crucial issue that must be resolved to ensure better automotive safety. Mutual interference between frequency modulated continuous waveform (FMCW) radar system appears in the form of increased noise levels in the frequency domain and results in a failure to separate the target object from interferers. The traditional fast fourier transform (FFT) algorithm, which is used to estimate the beat frequency, is vulnerable in interference-limited automotive radar environments. In order to overcome this drawback, we propose a high-resolution frequency estimation technique for use in interference environments. To verify the performance of the proposed algorithms, a 77GHz FMCW radar system is considered. The proposed method employs a high-resolution algorithm, specially the multiple signal classification and estimation of signal parameters via rotational invariance techniques, which are able to estimate beat frequency accurately.

• Journal of the Institute of Electronics and Information Engineers
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• v.52 no.4
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• pp.37-45
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• 2015

In modern electronic warfare systems, a demand on the more accurate estimation method based on TDOA and FDOA has been increased. TDOA/FDOA localization consists of two-stage procedures: the extraction of information from signals and the estimation of emitter location. Various algorithms based on CAF(complex ambiguity function), which is known as a basic method, has been presented in the area of extractions. When we extract TDOA and FDOA information using a conventional method based on the CAF algorithm from communication signals, considerably long integration time is required for the accurate position estimation of an unknown emitter far from sensors more than 300 km. Such long integration time yields huge amount of transmission data from sensors to a central processing unit, resulting in heavy computiational complexity. Therefore, we theoretically analyze the integration time for TDOA/FDOA information using CRLB and propose a two-stage global optimization algorithm which can minimize the transmission time and a computational complexity. The proposed method is compared with the conventional CAF-based algorithms in terms of a computational complexity and the CRLB to verify the estimation performance.

• Journal of Korean Society of Transportation
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• v.29 no.4
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• pp.85-93
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• 2011

Many policies, such as transit-oriented development, encouraged use of bicycle and pedestrian, reduction of green house gas (GHG) and etc., have been deployed to support transport sustainability. Although various studies regarding GHG were presented, no one has yet adequately explained the behavior of travelers. This paper proposes a GHG emission model by highlighting its sensitivity, elasticity with regard to such travel cost as travel time, travel fare, and GHG pricing, introduced to reduce the amount of GHG in transportation system. For better estimation of GHG, the proposed model adopts (1) a production-constrained gravity model and (2) the travel distance from the origin and the destination (OD). The gravity model has a merit that it considers travel pattern between OD pairs. The model was tested with an example, and the promising results confirmed its validation and applications.