• KSII Transactions on Internet and Information Systems (TIIS)
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• v.13 no.9
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• pp.4408-4428
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• 2019

Due to the rapid advancement in smart phones, numerous new specifications are developed for variety of applications ranging from health monitoring to navigations and tracking. The word indoor navigation means location identification, however, where GPS signals are not available, accurate indoor localization is a challenging task due to variation in the received signals which directly affect distance estimation process. This paper proposes a hybrid approach which integrates fingerprinting based K-Nearest Neighbors (K-NN) and lateration based MinMax position estimation technique. The novel idea behind this hybrid approach is to use Euclidian distance formulation for distance estimates instead of indoor radio channel modeling which is used to convert the received signal to distance estimates. Due to unpredictable behavior of the received signal, modeling indoor environment for distance estimates is a challenging task which ultimately results in distance estimation error and hence affects position estimation process. Our proposed idea is indoor position estimation technique using Bluetooth enabled smart phones which is independent of the radio channels. Experimental results conclude that, our proposed hybrid approach performs better in terms of mean error compared to Trilateration, MinMax, K-NN, and existing Hybrid approach.

• Communications of the Korean Mathematical Society
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• v.18 no.2
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• pp.263-280
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• 2003

We prove weighted L$^{p}$ estimates with respect to the non-isotropic norm for the (equation omitted)-equation on real ellipsoids, where weights are powers of the distance to the boundary. The non-isotropic norm is smaller than the usual norm, by a factor which is equal to the distance to the boundary in the complex tangential component and which is equal to the m-th root of the distance to the boundary in the complex normal component. Here n is the maximal order of contact of the boundary of the real ellipsoid with complex analytic curves.

• Asian-Australasian Journal of Animal Sciences
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• v.15 no.5
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• pp.745-750
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• 2002

The effects of recording interval (1, 2, 3, 4, 5, 10, 15, 20 and 30 min) on the estimation of some grazing behavior variables in beef cows and calves (<4 months old) were investigated in a daytime grazing (7 h) system utilizing a bahiagrass (Paspalum notatum Flugge) pasture (a 1.1 ha paddock and a 0.4 ha resting area). Recording intervals of 10-30 min tended to underestimate the time spent grazing and ruminating and overestimate the time spent resting by animals, whereas intervals of 1-5 min resulted in almost constant estimates. In all grazing activities, the errors of estimation became larger when the recording interval exceeded 5 min. The accuracy of estimation was higher for grazing time>rumination time>resting time. An increase in recording interval always decreased estimates of the distance walked by animals. It was concluded that recording intervals of 1-5 min provide reliable estimates of the time spent grazing, ruminating and resting. It was also concluded that positioning of animals at 1 min intervals may provide estimates of walking distance with acceptable bias toward underestimation.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.9 no.6
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• pp.2132-2143
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• 2015

This paper presents two distance geometry-based algorithms for wireless location in cellular network systems-distance geometry filtering (DGF) and distance geometry constraint (DGC). With time-of-arrival range measurements, the DGF algorithm estimates the mobile station position by selecting a set of measurements with relatively small NLOS (non-line-of-sight) errors, and the DGC algorithm optimizes the measurements first and then estimates the position using those optimized measurements. Simulation results show that the proposed algorithms can mitigate the impact of NLOS errors and effectively improve the accuracy of wireless location.

• Journal of the Korean Regional Science Association
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• v.12 no.2
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• pp.59-68
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• 1996

Common belief in border regions holds that Mexican cross-border shoppers play a larger role in the regional economic base than they do and that NAFTA will provide a bigger stimulus to the regional economy than it is likely. In the regional economy than it is likely. In the first case, price elasticities are implicitly underestimated as highly inelastic and in the latter case, overestimated as highly elastic. This paper provides empirical evidence on the effects of distance and real exchange rates as price proxies on both field survey and population-imputed estimates of cross-border shopping. After estimating both distance-based and real exchange rate-based estimates of price elasticities of Mexican shopper demand for U.S. border-region goods, implications are obtained concerning the relative importance for U.S. border-regon economies of more distant Mexican markets, and the likely impacts of NAFTA.

• Communications of the Korean Mathematical Society
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• v.30 no.1
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• pp.23-34
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• 2015

We use mixed norm estimates for the spherical averaging operator to obtain some results concerning pinned distance sets.

• KDI Journal of Economic Policy
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• v.40 no.1
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• pp.67-83
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• 2018

We have hypothesized that nuclear risk is significantly inversely related to the distance from residences to nuclear power plants and that the level of life satisfaction of residents therefore increases with the distance. We empirically explore the relationship between Ulsan citizens' life satisfaction levels and the distance between their residences and the Kori and Wolsong nuclear power plants (NPP) based on the life satisfaction approach (LSA). The dataset we used covers only Ulsan citizens from the biennial Ulsan Statistics on Citizen's Living Condition and Consciousness of 2014 and 2016. Controlling for micro-variables such as education, work satisfaction, gender, marital status, and expenditures, we found a statistically significant relationship between life satisfaction and the distance between the residences and the nuclear power plants. Nuclear negative externalities including (i) health and environmental impact, (ii) radioactive waste disposal, and (iii) the effect of severe accidents can be quantified in terms of LS units and monetary units. We were able to calculate the monetary value of NPP externalities at $277 per kilometer of distance for Kori and $280 per kilometer of distance for Wolsong at constant 2015 prices. These estimates are quite different from the traditional estimates made with the contingent valuation method, whereas they are similar to the findings of LSA studies abroad. Hence, the need to adopt the LSA in South Korea and policy implications are demonstrated.

• Communications of the Korean Mathematical Society
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• v.22 no.1
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• pp.111-119
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• 2007

We consider the growth norm of a measurable function f defined by defined by $${\parallel}f{\parallel}-\sigma=ess\;sup\{\delta_D(z)^\sigma{\mid}f(z)\mid:z{\in}D\}$$, where $\delta_D(z)$ denote the distance from z to ${\partial}D$. We prove some kind of optimal growth norm estimates for a on convex domains.

• Journal of Ecology and Environment
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• v.30 no.2
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• pp.201-207
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• 2007

Researchers have used a variety of methods to measure patterns of animal movement, including the use of spatial data (mapping the position of a moving animal at specified intervals) and direct estimation of travel path length by pacing under a moving animal or group. I collected movement data from five groups of siamangs (Symphalangus syndactylus) using two different methods concurrently to estimate the effects of the method of data collection on estimates of daily path length (DPL). Estimates of DPL produced from spatial data collected at 15-minute intervals were 12% lower than estimates of DPL produced by pacing under the traveling animal. The actual magnitude of the difference was correlated with the travel distance, but there was no correlation between the proportional difference and the travel distance. While the collection of spatial data is generally preferable, as spatial data permit additional analyses of patterns of movements in two or three dimensions, the relatively small difference between the DPL's produced using different methods suggests that pacing is an acceptable substitute where the collection of spatial data is impractical. I also subsampled the spatial data at increasing time intervals to assess the effect of sampling interval on the calculation of daily path lengths. Longer sampling intervals produced significantly shorter estimates of travel paths than shorter sampling intervals. These results suggest that spatial data should be collected at short time intervals wherever possible, and that sampling intervals should not exceed 30 minutes. Researchers should be cautious when comparing data generated using different methods.

• Communications for Statistical Applications and Methods
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• v.29 no.4
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• pp.471-486
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• 2022

Autoregressive moving average (ARMA) models involve nonlinearity in the model coefficients because of unobserved lagged errors, which complicates the likelihood function and makes the posterior density analytically intractable. In order to overcome this problem of posterior analysis, some approximation methods have been proposed in literature. In this paper we first review the main analytic approximations proposed to approximate the posterior density of ARMA models to be analytically tractable, which include Newbold, Zellner-Reynolds, and Broemeling-Shaarawy approximations. We then use the Kullback-Leibler divergence to study the relation between these three analytic approximations and to measure the distance between their derived approximate posteriors for ARMA models. In addition, we evaluate the impact of the approximate posteriors distance in Bayesian estimates of mean and precision of the model coefficients by generating a large number of Monte Carlo simulations from the approximate posteriors. Simulation study results show that the approximate posteriors of Newbold and Zellner-Reynolds are very close to each other, and their estimates have higher precision compared to those of Broemeling-Shaarawy approximation. Same results are obtained from the application to real-world time series datasets.