• Journal of Broadcast Engineering
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• v.9 no.4 s.25
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• pp.384-390
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• 2004

In this paper we compare the performance of 4 different algorithms for converting the sampling frequency of an audio from 44.1KHz to 48KHz. The algorithms considered here include the basic polyphase method. sine function based method. multi-stage method. and B-spline based method. For a fair comparison, the sampling rate converters using the 4 algorithms are redesigned under a high fidelity condition. Then, their H/W complexities are compared in terms of the computational complexity and the memory size. As a result, it is shown that the basic polyphase method and sine function based method outperform the other two in terms of the computational complexity, while the B-spline based method requires less memory than the others.

• Structural Engineering and Mechanics
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• v.82 no.2
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• pp.245-258
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• 2022

Many Structural Health Monitoring (SHM) methods have been proposed for structural damage diagnosis and prognosis. However, SHM for pinched hysteretic structures can be problematic due to the high level of nonlinearity. The model-free hysteresis loop analysis (HLA) has displayed notable robustness and accuracy in identifying damage for full-scaled and scaled test buildings. In this paper, the performance of HLA is compared with seven other SHM methods in identifying lateral elastic stiffness for a six-story numerical building with highly nonlinear pinching behavior. Two successive earthquakes are employed to compare the accuracy and consistency of methods within and between events. Robustness is assessed across sampling rates 50-1000 Hz in noise-free condition and then assessed with 10% root mean square (RMS) noise added to responses at 250 Hz sampling rate. Results confirm HLA is the most robust method to sampling rate and noise. HLA preserves high accuracy even when the sampling rate drops to 50 Hz, where the performance of other methods deteriorates considerably. In noisy conditions, the maximum absolute estimation error is less than 4% for HLA. The overall results show HLA has high robustness and accuracy for an extremely nonlinear, but realistic case compared to a range of leading and recent model-based and model-free methods.

• Journal of Ocean Engineering and Technology
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• v.25 no.2
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• pp.120-126
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• 2011

The fatigue damages in structural details of offshore plants can be accumulated due to various environmental loadings such as swell, wave, wind and current. It is known that load histories acting on mooring and riser systems show stationary and ergodic bimodal wide-banded process. This paper provides refined approach to obtain time signals representing stress range histories from wide-banded bimodal spectrum which consists of ideally narrow-banded and fully separated two spectrums. Variations of the probabilistic characteristics for time signals according to frequency and sampling time increments are compared with the reference data to be the probabilistic characteristics such as zero-crossing period, peak period, and irregularity factor obtained from an assumed ideal spectrum. It is proved that the sampling time increment more affects on the probabilistic characteristics than frequency increment. The fatigue damages according to the frequency and sampling time increments are also compared with the ones with minimum increment condition which are thought to be exact fatigue damage. It is concluded that the maximum sampling time increment to obtain reliable time signals should be determined that ratio of applied maximum sampling time increment and minimum period is less than approximately 0.08.

• Journal of Korean Society of Occupational and Environmental Hygiene
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• v.23 no.2
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• pp.103-107
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• 2013

Objectives: The principal purpose of this study is to statistically compare dust levels among farmers with and without feeding in a nursery pig building. Methods: Total dust and respirable dust were measured by personal sampling method, and TSP and PM10 were monitored by the direct recording method in the pig building. Results: IIn the personal samples, mean exposure levels of total and respirable dust were higher among the farmers who conducted feeding compared to farmers who did not. A significant difference between farmers with feeding and farmers without feeding was found in total dust concentration(p<0.05), whereas there was no significant difference in respirable dust concentrations. In real-time monitoring of dust based on area sampling, the highest levels of total and respirable dust were detected in the feeding time periods; $4.33{\pm}2.57mg/m^3$ for TSP and $2.53{\pm}1.02mg/m^3$ for PM10, respectively. During time periods without feeding, the levels of total and respirable dust ranged from 1 to $2mg/m^3$ and from 0.5 to $1.5mg/m^3$, respectively. Conclusions: In terms of association of feeding work and air sampling location, the mean concentrations of total and respirable dust were highest in area sampling with feeding and lowest in personal sampling without feeding. However, a significant difference among groups investigated according to air sampling condition was found in total dust.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.13 no.10
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• pp.4940-4957
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• 2019

Compared with the localization methods in the static sensor networks, node localization in dynamic sensor networks is more complicated due to the mobility of the nodes. Dynamic Sampling Localization Algorithm Based on Virtual Anchor (DSLA) is proposed in this paper to localize the unknown nodes in dynamic sensor networks. Firstly, DSLA algorithm predicts the speed and movement direction of nodes to determine a sector sampling area. Secondly, a method of calculating the sampling quantity with the size of the sampling area dynamically changing is proposed in this paper. Lastly, the virtual anchor node, i.e., the unknown node that got the preliminary possible area (PLA), assists the other unknown nodes to reduce their PLAs. The last PLA is regarded as a filtering condition to filter out the conflicting sample points quickly. In this way, the filtered sample is close to its real coordinates. The simulation results show that the DSLA algorithm can greatly improve the positioning performance when ensuring the execution time is shorter and the localization coverage rate is higher. The localization error of the DSLA algorithm can be dropped to about 20%.

• Bulletin of the Korean Mathematical Society
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• v.45 no.2
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• pp.231-239
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• 2008

We obtain a necessary and sufficient condition for the existence of Mendelsohn triple systems excluding contiguous units with ${\lambda}$ = 1. Also, we obtain the spectrum for cyclic such systems.

• Journal of the Korean Statistical Society
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• v.34 no.1
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• pp.49-60
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• 2005

In this paper we introduce a nonparametric method for estimating the probability density function of detection distances in line transect sampling. The estimator is obtained using a frequency histogram density estimation method. The asymptotic properties of the proposed estimator are derived and compared with those of the kernel estimator under the assumption that the data collected satisfy the shoulder condition. We found that the asymptotic mean square error (AMSE) of the two estimators have about the same convergence rate. The formula for the optimal histogram bin width is derived which minimizes AMSE. Moreover, the performances of the corresponding k-nearest-neighbor estimators are studied through simulation techniques. In the absence of our knowledge whether the shoulder condition is valid or not a new semi-parametric model is suggested to fit the line transect data. The performances of the proposed two estimators are studied and compared with some existing nonparametric and semiparametric estimators using simulation techniques. The results demonstrate the superiority of the new estimators in most cases considered.

• Transactions of Materials Processing
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• v.29 no.4
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• pp.218-228
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• 2020

The prediction of final mass and optimized process conditions of injection molded products using Artificial Neural Network (ANN) were demonstrated. The ANN was modeled with 10 input parameters and one output parameter (mass). The input parameters, i.e.; melt temperature, mold temperature, injection speed, packing pressure, packing time, cooling time, back pressure, plastification speed, V/P switchover, and suck back were selected. To generate training data for the ANN model, 77 experiments based on the combination of orthogonal sampling and random sampling were performed. The collected training data were normalized to eliminate scale differences between factors to improve the prediction performance of the ANN model. Grid search and random search method were used to find the optimized hyper-parameter of the ANN model. After the training of ANN model, optimized process conditions that satisfied the target mass of 41.14 g were predicted. The predicted process conditions were verified through actual injection molding experiments. Through the verification, it was found that the average deviation in the optimized conditions was 0.15±0.07 g. This value confirms that our proposed procedure can successfully predict the optimized process conditions for the target mass of injection molded products.

• Journal of Institute of Control, Robotics and Systems
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• v.17 no.4
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• pp.289-294
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• 2011

Digital redesign is yet another efficient tool to convert a pre-designed analog controller into a sampled-data one to maintain the analog closed-loop performance in the sense of state matching. A rising difficulty in developing a digital redesign technique for trackers with time-varying references is the unavailability of a closed-form discrete-time model of a system, even if it is linear time-invariant. A way to resolve this is to approximate the time-varying reference as a piecewise constant one, which deteriorates the state matching performance. Another remedy may be to decrease a sampling period, which however could numerically destabilize the optimization-based digital redesign condition. In this paper, we develop a digital redesign condition for time-varying trackers by approximating the time-varying reference through a triangular hold and by introducing delta-operated discrete-time models. It is shown that the digitally redesigned sampled-data tracker recovers the performance of the pre-designed analog tracker under a fast sampling limit. Simulation results on the formation flying of satellites convincingly show the effectiveness of the development.

• The Journal of Asian Finance, Economics and Business
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• v.8 no.5
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• pp.143-150
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• 2021

This study aims to determine (1) the inhibiting factors and solutions in the development of eco-tourism, and (2) how green entrepreneurship can be used for eco-tourism development. The increasing issue of global warming is pushing awareness of environmental preservation. This condition changes the people's paradigm in traveling from the concept of mass-tourism to the concept of eco-tourism. The development of eco-tourism has consequences for entrepreneurial activities which is known as green entrepreneurship. This study is applied research conducted in East Lombok, one of the regions in Indonesia. The sampling technique used is purposive sampling covering a total of 34 informants. Data collection methods are carried out through interviews, observation, and documentation studies. Based on the data analysis, the findings of this study show that (a) inhibiting factors of eco-tourism development are limitation of eco-tourism knowledge, lack of awareness in environmental preservation, and absence of supporting government policy; and (b) solution for eco-tourism development discovered in this research is divided into five factors i.e., condition, demand, related industry and support, strategy, government. Besides, for applying the green entrepreneurship model i.e., developing the spirit of green entrepreneurship, training in making products and services that are environmentally friendly is needed.