• Transactions of the Korean Society for Noise and Vibration Engineering
• /
• v.12 no.1
• /
• pp.21-28
• /
• 2002

This paper intends to investigate the effects of speed fluctuation caused by the cogging torque in permanent magnetic motors on the stability of the transverse vibration for a spinning disk. Based on the Kirchhoff\`s plate theory and the assumed mode methods, a set of discretized equations of motion were derived for an annular disk rotating with a harmonically varying speed. Then, a perturbation method using the multiple time scales was employed and stability boundaries were determined explicitly in terms of the magnitude and frequency of speed fluctuation, a nominal sped and the modal characteristics of the disk. It is found that parametric resonance occurs at several speed ranges and a single mode or a combination of two modes are involved to cause instability. It is also observed that unstable regions become broadened as the spinning speed increases or two modes are combined in parametric instability. As numerical simulations, stability analysis of a conventional CD-ROM drive was performed. Results of this work can e used as guidelines for motor design and operations with low vibration.

• Journal of The Korean Astronomical Society
• /
• v.47 no.6
• /
• pp.209-214
• /
• 2014

In this study we develop a set of solar proton event (SPE) forecast models with NOAA scales by Multi Layer Perceptron (MLP), one of neural network methods, using GOES solar X-ray flare data from 1976 to 2011. Our MLP models are the first attempt to forecast the SPE scales by the neural network method. The combinations of X-ray flare class, impulsive time, and location are used for input data. For this study we make a number of trials by changing the number of layers and nodes as well as combinations of the input data. To find the best model, we use the summation of F-scores weighted by SPE scales, where F-score is the harmonic mean of PODy (recall) and precision (positive predictive value), in order to minimize both misses and false alarms. We find that the MLP models are much better than the multiple linear regression model and one layer MLP model gives the best result.

• The Journal of Korean Institute of Communications and Information Sciences
• /
• v.34 no.8A
• /
• pp.600-609
• /
• 2009

The traditional carrier sense multiple access (CSMA) protocol like IEEE 802.11 Distributed Coordination Function (DCF) does not handle the constraints adequately, leading to degraded delay latency and throughput as the network scales are enlarged. We present more efficient method of a medium access for real-time wireless sensor networks. Proposed MAC protocol is like the randomized CSMA protocol, but unlike previous legacy protocols, it does not use a time-varying contention window from which a node randomly picks a transmission slot. To reduce the latency for the delivery of event reports, we carefully decide to select a fixed-size contention window with non-uniform probability distribution of transmitting in each slot. We show that the proposed method can offer up to severaansimes latency reduction compared to legacy of IEEE 802.11 as the size of the sensor network scales up to 256 nodes using widely using network simulation package,caS-2. We finally show that proposed MAC scheme comes close to meet bounds on the best latency being achieved by a decentralized CSMA-based MAC protocol for real-time wireless sensor networks which is sensitive to delay latency.

• Proceedings of the KSRS Conference
• /
• 1998.09a
• /
• pp.236-241
• /
• 1998

The NOAA AVHRR remote sense SST data, collected by the National Fisheries Research and Development Institute (NFRDI), are analyzed in order to understand the spatial and temporal distributions of SST in the seas adjacent to Korea. Our study is based on 10-day SST images during last 7 years (1991-1997). For a time series analysis of multiple 557 images, all of images must be aligned exactly at the same position by adjusting the scales and positions of each SST image. We devised an algorithm which yields automatic detections of cloud pixels from multiple SST images. The cloud detection algorithm is based on a physical constraint that SST anomalies in the ocean do not exceed certain limits (we used $\pm$ 3$^{\circ}C$ as a criterion of SST anomalies). The remote sense SST data are tuned by comparing remote sense data with observed SST at coastal stations. Seasonal variations of SST are studied by harmonic fit of SST normals at each pixel. The SST anomalies are studied by statistical method. We found that the SST anomalies are rather persistent with time scales between 1 and 2 months. Utilizing the persistency of SST anomalies, we devised an algorithm for a prediction of future SST Model fit of SST anomalies to the Markov process model yields that autoregression coefficients of SST anomalies during a time elapse of 10 days are between 0.5 and 0.7. We plan to improve our algorithms of automatic cloud pixel detection and prediction of future SST. Our algorithm is expected to be incorporated to the operational real time service of SST around Korea.

• Korean Journal of Remote Sensing
• /
• v.35 no.6_3
• /
• pp.1209-1219
• /
• 2019

For consistent vegetation monitoring, it is necessary to generate time-series vegetation index datasets at fine temporal and spatial scales by fusing the complementary characteristics between temporal and spatial scales of multiple satellite data. In this study, we quantitatively and qualitatively analyzed the prediction accuracy of time-series change information extracted from spatio-temporal fusion models of multiple satellite data for vegetation monitoring. As for the spatio-temporal fusion models, we applied two models that have been widely employed to vegetation monitoring, including a Spatial and Temporal Adaptive Reflectance Fusion Model (STARFM) and an Enhanced Spatial and Temporal Adaptive Reflectance Fusion Model (ESTARFM). To quantitatively evaluate the prediction accuracy, we first generated simulated data sets from MODIS data with fine temporal scales and then used them as inputs for the spatio-temporal fusion models. We observed from the comparative experiment that ESTARFM showed better prediction performance than STARFM, but the prediction performance for the two models became degraded as the difference between the prediction date and the simultaneous acquisition date of the input data increased. This result indicates that multiple data acquired close to the prediction date should be used to improve the prediction accuracy. When considering the limited availability of optical images, it is necessary to develop an advanced spatio-temporal model that can reflect the suggestions of this study for vegetation monitoring.

• 한국정보컨버전스학회:학술대회논문집
• /
• 2008.06a
• /
• pp.199-204
• /
• 2008

Sensor nodes have various energy and computational constraints because of their inexpensive nature and ad-hoc method of deployment. Considerable research has been focused at overcoming these deficiencies through faster media accessing, more energy efficient routing, localization algorithms and system design. Our research attempts to provide a method of improvement MAC performance in these issues. We show that traditional carrier-sense multiple access(CSMA) protocols like IEEE 802.11 do not handle the first constraint adequately, and do not take advantage of the second property, leading to degraded latency and throughput as the network scales in size, We present more efficient method of a medium access for real-time wireless sensor networks. Proposed MAC protocol is a randomized CSMA protocol, but unlike previous legacy protocols, does not use a time-varying contention window from which a node randomly picks a transmission slot. To reduce the latency for the delivery of event reports, it carefully decides a fixed-size contention window, non-uniform probability distribution of transmitting in each slot within the window. We show that it can offer up to several times latency reduction compared to legacy of IEEE 802.11 as the size of the sensor network scales up to 256 nodes using widely used simulator ns-2. We, finally show that proposed MAC scheme comes close to meeting bounds on the best latency achievable by a decentralized CSMA-based MAC protocol for real-time wireless sensor networks which is sensitive to latency.

• The Bulletin of The Korean Astronomical Society
• /
• v.37 no.1
• /
• pp.75.2-75.2
• /
• 2012

Turbulence is ubiquitous in astrophysical fluids such as the interstellar medium and intracluster medium. To maintain turbulent motion, energy must be injected into the fluids. In turbulence studies, it is customary to assume that the fluid is driven on a scale, but there can be many different driving mechanisms that act on different scales in astrophysical fluids. We expect different statistical properties of turbulence between turbulence with single driving scale and turbulence with double driving scales. In this work, we perform 3-dimensional incompressible MHD turbulence simulations with energy injection in two ranges, 2${\surd}$12 (large scale) and 15

• Wind and Structures
• /
• v.36 no.6
• /
• pp.367-377
• /
• 2023

This study proposes a few-shot learning model for extrapolating the wind pressure of scaled experiments to full-scale measurements. The proposed ML model can use scaled experimental data and a few full-scale tests to accurately predict the remaining full-scale data points (for new specimens). This model focuses on extrapolating the prediction to different scales while existing approaches are not capable of accurately extrapolating from scaled data to full-scale data in the wind engineering domain. Also, the scaling issue observed in wind tunnel tests can be partially resolved via the proposed approach. The proposed model obtained a low mean-squared error and a high coefficient of determination for the mean and standard deviation wind pressure coefficients of the full-scale dataset. A parametric study is carried out to investigate the influence of the number of selected shots. This technique is the first of its kind as it is the first time an ML model has been used in the wind engineering field to deal with extrapolation in wind performance prediction. With the advantages of the few-shot learning model, physical wind tunnel experiments can be reduced to a great extent. The few-shot learning model yields a robust, efficient, and accurate alternative to extrapolating the prediction performance of structures from various model scales to full-scale.

• Korean Journal of Health Education and Promotion
• /
• v.21 no.3
• /
• pp.1-17
• /
• 2004

The purpose of this study is to evaluate the roles of expected self-control and expected self-control results in explaining adolescents' Internet addiction. In the study model, expectations of self-control and self-control results directly determine Internet addiction and Internet use time meditates the impacts of expectations of self-control and self-control results on Internet addiction. The study subjects are 1,080 middle and high school students in Busan. Stratified cluster sampling is applied by school type and school year. The response rate is 96%(l,037cases). This study develops the scales of expected self-control and expected self-control results. The scales of Internet addiction are devised by using the concept of functional dependency such as salience, withdrawal symptoms, mood modification, tolerance, relapse, and conflict. For verifying the study model, path analysis and multiple regression models are applied for identifying path significants and evaluating confounding effects of control variables, respectively. Moreover, multi partial F-test is performed for selecting the best regression model. Expected self-control is a significant determinant of Internet addiction and Internet use time that also significantly explains Internet addiction. The total effect of expected self-control towards Internet addiction is -.95. The total effect is comprised with the direct effect (-.71) and the indirect effect(-.24). In this result, the direct effect refers a curative effect since expected self-control directly reduces the level of Internet addiction, and the indirect effect refers a preventive effect because self-control can reduce time of Internet use that is a direct determinant of Internet addiction. In the test of the confounding effects of control variables, there are no confounding effects in the models of multiple regression. It implies a robustness of the study model as regards control variables. In conclusion, improving adolescents' expected self-control can control Internet addiction level. This finding implies that a health promotion program for improving expected self-control can be a cost effective method compared to other approaches.

• Sleep Medicine and Psychophysiology
• /
• v.1 no.2
• /
• pp.125-144
• /
• 1994

Recently excessive daytime sleepiness was found to have relations with various social, occupational, and health problems. This condition is common symptom of several sleep disorders, among which sleep apnea syndrome is most contributive. It is essential to assess daytime sleepiness exactly for the diagnosis of such sleep disorders. Multiple sleep latency test which is a valid and objective measurement technique of sleepiness is time and cost consuming, and so there is increasing need of scales measuring general level of daytime sleepiness which are quick and simple to perform for clinical and research purpose. And also, there have been a lot of sleep researches viewing sleep as a chronobiological process, especially in the study of circadian type of shift workers. In these studies they used various techniques of multiple demensions to assess sleepiness or circadian rhythm which concerns various psychological variables. Of these measurement techniques circadian type questionnaires might have some problems in their psychometric properties. So some of these morningness-eveningness questionnaires have been revised and more valid scales are being suggested by different authors. The author briefly reviewed various measurement techniques of sleepiness and circadian rhythm and introduced recently developed scales which are more valid allegedly, and finally discussed psychometric properties of these morningness-eveningness questionnaires.