• The Journal of Korean Medicine
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• v.35 no.4
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• pp.24-35
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• 2014

Objectives: Although the autonomic nervous system (ANS) is thought to play an important role in treatment of obesity, no study has been conducted to investigate acupuncture's effects on this aspect of the ANS. This study aimed to describe the effects of acupuncture in the ANS by means of heart rate variability (HRV) analysis. Methods: A total of 46 obese women aged from 21 to 54 with body mass index ranging from 25.1 to $39.3kg/m^2$ were recruited and randomized into both the real acupuncture group (n=23) and sham acupuncture group (n=23). A total of 3 instances of HRV analysis were conducted before, during, and after treatment. Statistically significant differences between time and groups were analyzed using repeated measure analysis of variance. Results: All parameters of time domain analysis and frequency domain analysis except for the square root of the mean squared differences of successive normal sinus intervals (RMSSD) and very low frequency (VLF) showed significant differences between times. The mean of all R-R intervals (mean RR) showed significant level of interaction between time and group. Between groups, time domain analysis of standard deviation of the normal-to-normal intervals (SDNN), RMSSD and frequency domain analysis of total power (TP) and high frequency (HF) showed significant differences. Conclusions: The real acupuncture group showed deactivation of parasympathetic function and relative increase of sympathetic activity in obese subjects. Further studies are necessary to uncover the mechanisms of acupuncture in obesity treatment.

• Journal of Internet Computing and Services
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• v.9 no.5
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• pp.153-163
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• 2008

Almost literature has so far proposed the modifications to IEEE 802.11 DCF MAC protocol to improve system throughput and average delay. Jitter(variance in packet delays) is, however, considered as an important QoS parameter for real-time streaming service which is popularized increasingly. Unfortunately, legacy access protocol for WLAN can't support the jitter. This paper proposes two schemes modifying the DCF MAC protocol to reduce the average value of jitter for multimedia frames arrived at received nodes. The one scheme, referred to as DCW-DCF(Decreasing Contention Window-DCF), reduces CW(Contention Window) size by half whenever a transmitted frame collided against other frames and back-off happens. Also, it increase initial CW size according as the link utilization and the collision probability increase. The other scheme, referred to as D-DIFS(Differential-DIFS), assigns different values to DIFS. That is, the DIFS interval is deceased as the number of back-off for a frame increases. In this paper, the two schemes are evaluated through simulation using ns2 and simulation results show that the proposed schemes are effective for improving the jitter property of standard WLAN.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.17 no.6
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• pp.105-111
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• 2017

In this paper, the analysis results are shown about several weights of Weighted K-Nearest Neighbor method, Recently, it is employed for the indoor positioning technologies using WiFi fingerprint which has been actively studied. In spite of the simplest feature, the W-KNN method shows comparable performance to another methods using WiFi fingerprint technology. So W-KNN method has employed in the existing indoor positioning system. It shows positioning error performance according to data preprocessing and weight factor, and the analysis on the weight is very important. In this paper, based on the real measured WiFi fingerprint data, the estimation error is analyzed and the performances are compared, for the case of data processing methods, of the weight of average, variance, and distance, and of the averaging several position of number K. These results could be practically useful to construct the real indoor positioning system.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.12 no.3
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• pp.1224-1242
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• 2018

Aiming at motion analysis and compensation, it is essential to conduct motion detection with images. However, motion detection and tracking from low-altitude images obtained from an unmanned aerial system may pose many challenges due to degraded image quality caused by platform motion, image instability and illumination fluctuation. This research tackles these challenges by proposing a modified joint transform correlation algorithm which includes two preprocessing strategies. In spatial domain, a modified fuzzy edge detection method is proposed for preprocessing the input images. In frequency domain, to eliminate the disturbance of self-correlation items, the cross-correlation items are extracted from joint power spectrum output plane. The effectiveness and accuracy of the algorithm has been tested and evaluated by both simulation and real datasets in this research. The simulation experiments show that the proposed approach can derive satisfactory peaks of cross-correlation and achieve detection accuracy of displacement vectors with no more than 0.03pixel for image pairs with displacement smaller than 20pixels, when addition of image motion blurring in the range of 0~10pixel and 0.002variance of additive Gaussian noise. Moreover,this paper proposes quantitative analysis approach using tri-image pairs from real datasets and the experimental results show that detection accuracy can be achieved with sub-pixel level even if the sampling frequency can only attain 50 frames per second.

• Journal of the Korean Data and Information Science Society
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• v.24 no.6
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• pp.1263-1274
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• 2013

VaR (value at risk), which represents the expectation of the worst loss that may occur over a period of time within a given level of confidence, is currently used by various financial institutions for the purpose of risk management. In the majority of previous studies, the probability of return has been modeled with normal distribution. Recently Chen et al. (2010) measured VaR with asymmetric Laplacian distribution. However, it is difficult to estimate the mode, the skewness, and the degree of variance that determine the shape of an asymmetric Laplacian distribution with limited data in the real-world market. In this paper, we show that the VaR estimated with (symmetric) Laplacian distribution model provides more accuracy than those with normal distribution model or asymmetric Laplacian distribution model with real world stock market data and with various statistical measures.

• Nuclear Engineering and Technology
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• v.52 no.10
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• pp.2250-2261
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• 2020

Accurate localization of radioactive materials is crucial in homeland security and radiological emergencies. Coded-aperture gamma camera is an interesting solution for such applications and can be developed into portable real-time imaging devices. However, traditional reconstruction methods cannot effectively deal with signal-independent noise, thereby hindering low-noise real-time imaging. In this study, a novel reconstruction method with excellent noise-suppression capability based on a multi-layer perceptron (MLP) is proposed. A coded-aperture gamma camera based on pixel detector and coded-aperture mask was constructed, and the process of radioactive source imaging was simulated. Results showed that the MLP method performs better in noise suppression than the traditional correlation analysis method. When the Co-57 source with an activity of 1 MBq was at 289 different positions within the field of view which correspond to 289 different pixels in the reconstructed image, the average contrast-to-noise ratio (CNR) obtained by the MLP method was 21.82, whereas that obtained by the correlation analysis method was 5.85. The variance in CNR of the MLP method is larger than that of correlation analysis, which means the MLP method has some instability in certain conditions.

• Asian-Australasian Journal of Animal Sciences
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• v.31 no.12
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• pp.1863-1870
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• 2018

Objective: The Bayesian first-order antedependence models, which specified single nucleotide polymorphisms (SNP) effects as being spatially correlated in the conventional BayesA/B, had more accurate genomic prediction than their corresponding classical counterparts. Given advantages of $BayesC{\pi}$ over BayesA/B, we have developed hyper-$BayesC{\pi}$, ante-$BayesC{\pi}$, and ante-hyper-$BayesC{\pi}$ to evaluate influences of the antedependence model and hyperparameters for $v_g$ and $s_g^2$ on $BayesC{\pi}$.Methods: Three public data (two simulated data and one mouse data) were used to validate our proposed methods. Genomic prediction performance of proposed methods was compared to traditional $BayesC{\pi}$, ante-BayesA and ante-BayesB. Results: Through both simulation and real data analyses, we found that hyper-$BayesC{\pi}$, ante-$BayesC{\pi}$ and ante-hyper-$BayesC{\pi}$ were comparable with $BayesC{\pi}$, ante-BayesB, and ante-BayesA regarding the prediction accuracy and bias, except the situation in which ante-BayesB performed significantly worse when using a few SNPs and ${\pi}=0.95$. Conclusion: Hyper-$BayesC{\pi}$ is recommended because it avoids pre-estimated total genetic variance of a trait compared with $BayesC{\pi}$ and shortens computing time compared with ante-BayesB. Although the antedependence model in $BayesC{\pi}$ did not show the advantages in our study, larger real data with high density chip may be used to validate it again in the future.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• 2004.11a
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• pp.97-101
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• 2004

In this paper, we study the fishery detection system for protection of an aquamlture farm. The FDS(fishery detection system) will be recognize a robbing vessel with real time and variance the position of aquaculture farm. We try to develop the F-AIS(Fishery Automatic Identification System) which am be detect approaching object to aquaculture farm and distinguish our fishing boot from thief vessel. The F-AIS with low price and wideband responsibility am be adopt to the FDS, i. e. the identification for a small-sized fishing boots.

• Imaging Science in Dentistry
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• v.30 no.2
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• pp.101-108
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• 2000

Purpose : The effects of step numbers of copper wedge and exposure on the coefficient of determination (r²) of the conversion equation to Cu-equivalent image and on the Cu-equivalent value (mmCu) and it's coefficient of variation measured at each copper step and the mandibular premolar area were evaluated. Method: Digital image analyzing system consisted of scanner, personal computer, and a stepwedge with 10 steps of 0.03 mm copper in thickness as reference material was prepared for quantitative assessment of the bone mineral density. NIH image program was used for analyzing images. Results : The film having moderately high film density showed the discrepancy between the real thickness and the measured Cu-equivalent value of each copper step. The Cu-equivalent image was dependent on the determinational coefficient of the conversion equation than the coefficient of variance of the measured value. Conclusion : Obtaining conversion equation with high coefficient of determination and proper film exposure are supposed to be neccessary for quantitative assessment of bone density. Multiple steps in the range of the corresponding copper thickness to the bone density of the area to be measured should be prepared.

• Membrane and Water Treatment
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• v.1 no.1
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• pp.49-60
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• 2010

In this study, response surface methodology (RSM) was performed in NF membrane process to evaluate the separation efficiency of membrane in the removal of salt and reactive dye by varying different variables such as pressure, temperature, pH, dye concentration and salt concentration. The significant level of both the main effects and the interaction were observed by analysis of variance (ANOVA) approach. Based on the statistical analysis, the results have provided valuable information on the relationship between these variables and the performances of membrane. The rejection of salt was found to be greatly influenced by pressure, pH and salt concentration whereas the dye rejection was relatively constant in between 96.22 and 99.43% regardless of the changes in the variables. The water flux on the other hand was found to be affected by the pressure and salt concentration. It is also found that the model predictions were in good agreement with the experimental data, indicating the validity of these models in predicting membrane performances prior to the real filtration process.