• 한국가시화정보학회:학술대회논문집
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• 2004.12a
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• pp.33-40
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• 2004

A 4D-PTV system was constructed. The measurement system consists of three high-speed high-definition cameras(1k x 1k, 2000fps), Nd-Yag laser(2000Hz) and a host computer. The GA-3D-PTV algorithm was used for completing the measurement system. The 4D-PTV is capable of probing the spatial distribution of velocity vectors of the flow field overcoming the temporal resolution of the characteristic turbulence length scales of the measured flow fields. A horizontal impinged jet flow (H/D=7) was measured. The Reynolds number is about 33,000. Spatial temporal evolution of the jet flow was examined and physical properties such as spatial distributions of vorticity and turbulent kinetic energy were obtained with the constructed.

• Journal of The Korean Astronomical Society
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• v.56 no.1
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• pp.41-57
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• 2023

We measured temporal and emission properties of quiescent magnetars using archival Chandra and XMM-Newton data, produced a list of the properties for 17 magnetars, and revisited previously suggested correlations between the properties. Our studies carried out with a larger sample, better spectral characterizations, and more thorough analyses not only confirmed previously-suggested correlations but also found new ones. The observed correlations differ from those seen in other neutron-star populations but generally accord with magnetar models. Specifically, the trends of the intriguing correlations of blackbody luminosity (L_BB) with the spin-inferred dipole magnetic field strength (B_S) and characteristic age (τ_c) were measured to be L_BB ∝ B^1.5_S and L_BB ∝ τ^-0.6_c, supporting the twisted magnetosphere and magnetothermal evolution models for magnetars. We report the analysis results and discuss our findings in the context of magnetar models.

• The Journal of the Acoustical Society of Korea
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• v.42 no.6
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• pp.603-616
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• 2023

In this study, machine learning-based clustering and classification of residential noise in apartment buildings was conducted using frequency and temporal characteristics. First, a residential noise source dataset was constructed . The residential noise source dataset was consisted of floor impact, airborne, plumbing and equipment noise, environmental, and construction noise. The clustering of residential noise was performed by K-Means clustering method. For frequency characteristics, L_eq and L_max values were derived for 1/1 and 1/3 octave band for each sound source. For temporal characteristics, Leq values were derived at every 6 ms through sound pressure level analysis for 5 s. The number of k in K-Means clustering method was determined through the silhouette coefficient and elbow method. The clustering of residential noise source by frequency characteristic resulted in three clusters for both L_eq and L_max analysis. Temporal characteristic clustered residential noise source into 9 clusters for L_eq and 11 clusters for L_max. Clustering by frequency characteristic clustered according to the proportion of low frequency band. Then, to utilize the clustering results, the residential noise source was classified using three kinds of machine learning. The results of the residential noise classification showed the highest accuracy and f1-score for data labeled with L_eq values in 1/3 octave bands, and the highest accuracy and f1-score for classifying residential noise sources with an Artificial Neural Network (ANN) model using both frequency and temporal features, with 93 % accuracy and 92 % f1-score.

• Journal of KIISE:Databases
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• v.32 no.1
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• pp.43-55
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• 2005

Spatiotemporal databases support methods of recording and querying for spatiotemporal data to user by offering both spatial management and historical information on various types of objects in the real world. We can answer to the following query in real world: 'What is the average of volume of pesticide sprayed for cach farm land from April to August on 2001, within some query window' Such aggregation queries have both temporal and spatial constraint. However, previous works for aggregation are attached only to temporal aggregation or spatial aggregation. So they have problems that are difficult to apply for spatiotemporal data directly which have both spatial and temporal constraint. Therefore, in this paper, we propose spatiotemporal aggregate functions for analysis of spatiotemporal data which have spatiotemporal characteristic, such as stCOUNT, stSUM, stAVG, stMAX, stMIN. We also show that our proposal resulted in the convenience and improvement of query in application systems, and facility of analysis on spatiotemporal data which the previous temporal or spatial aggregate functions are not able to analyze, by applying to the estate management system. Then, we show the validity of our algorithm performance through the evaluation of spatiotemporal aggregate functions.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.23 no.6
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• pp.119-124
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• 2023

This paper proposes a new reference model that can represent data access with temporal locality and popularity bias. Among existing reference models, the LRU-stack model can express temporal locality, which is a characteristic that the more recently referenced data has, the higher the probability of being referenced again. However, it cannot take into account differences in popularity of the data. Conversely, the independent reference model can reflect the different popularity of data, but has the limitation of not being able to model changes in data reference trends over time. The reference model presented in this paper overcomes the limitations of these two models and has the feature of reflecting both the popularity bias of data and their changes over time. This paper also examines the relationship between the cache replacement algorithm and the reference model, and shows the optimality of the proposed model.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.17 no.10
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• pp.2627-2642
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• 2023

Parkinson's disease (PD) is a typical, chronic neurodegenerative disease involving the concentration of dopamine, which can disrupt motor activity and cause different degrees of gait disturbance relevant to PD severity in patients. As current clinical PD diagnosis is a complex, time-consuming, and challenging task that relays on physicians' subjective evaluation of visual observations, gait disturbance has been extensively explored to make automatic detection of PD diagnosis and severity rating and provides auxiliary information for physicians' decisions using gait data from various acquisition devices. Among them, wearable sensors have the advantage of flexibility since they do not limit the wearers' activity sphere in this application scenario. In this paper, an attention-based temporal network (ATN) is designed for the time series structure of gait data (vertical ground reaction force signals) from foot sensor systems, to learn the discriminative differences related to PD severity levels hidden in sequential data. The structure of the proposed method is illuminated by Transformer Network for its success in excavating temporal information, containing three modules: a preprocessing module to map intra-moment features, a feature extractor computing complicated gait characteristic of the whole signal sequence in the temporal dimension, and a classifier for the final decision-making about PD severity assessment. The experiment is conducted on the public dataset PDgait of VGRF signals to verify the proposed model's validity and show promising classification performance compared with several existing methods.

• 한국공간정보시스템학회:학술대회논문집
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• 2005.11a
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• pp.61-66
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• 2005

Spatiotemporal data mining represents the confluence of several fields including spatiotemporal databases, machine loaming, statistics, geographic visualization, and information theory. Exploration of spatial data mining and temporal data mining has received much attention independently in knowledge discovery in databases and data mining research community. In this paper, we introduce an algorithm Max_MOP for discovering moving sequences in mobile environment. Max_MOP mines only maximal frequent moving patterns. We exploit the characteristic of the problem domain, which is the spatiotemporal proximity between activities, to partition the spatiotemporal space. The task of finding moving sequences is to consider all temporally ordered combination of associations, which requires an intensive computation. However, exploiting the spatiotemporal proximity characteristic makes this task more cornputationally feasible. Our proposed technique is applicable to location-based services such as traffic service, tourist service, and location-aware advertising service.

• Bulletin of the Korean Chemical Society
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• v.32 no.2
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• pp.583-589
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• 2011

Fluorescence correlation spectroscopy (FCS) is a sophisticated and an accurate analytical technique used to study the diffusion of molecules in a solution at the single-molecule level. FCS is strongly affected by many factors such as the stability of the excitation power, photochemical processes, mismatch between the refractive indices, and variations in the cover glass thickness. We have studied FCS near the surface of a cover glass by using rhodamine 123 as a fluorescent probe and have observed that the surface has a strong influence on the measurements. The temporal autocorrelation of FCS decays with two characteristic times when the confocal detection volume is positioned near the surface of the cover glass. As the position of the detection volume is moved away from the surface, the FCS autocorrelation becomes one-component decaying; the characteristic time of the decay is the same as the faster-decaying component in the FCS autocorrelation near the surface. This observation suggests that the faster component can be attributed to the free diffusion of the probe molecules in the solution, while the slow component has its origin from the interaction between the probe molecules and the surface. We have characterized the surface contribution to the FCS measurements near the surface by changing the position of the detection volume relative to the surface. The influence of the surface on the diffusion of the probe molecules was monitored by changing the chemical properties of the surface. The surface contribution to the temporal autocorrelation of the FCS strongly depends on the chemical nature of the surface. The hydrophobicity of the surface is a major factor determining the surface influence on the free diffusion of the probe molecules near the surface.

• Journal of Advanced Marine Engineering and Technology
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• v.31 no.3
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• pp.282-292
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• 2007

The present paper describes the results of high speed photography, acoustic emission (AE) detection and plasma light emission (LE) measurement during $CO_2$ laser welding of 304 stainless steel in different processing conditions. Video images with high spatial and temporal resolution allowed to observe the melt dynamics and keyhole evolution. The existence of keyhole was confirmed by the slag motion on the weld pool. The characteristic frequencies of flow instability and keyhole fluctuations at different welding speed were measured and compared with the results of Fourier analyses of temporal AE and LE spectra. The experimental results were compared with the newly developed numerical model of keyhole dynamics. The model is based on the assumption that the propagation of front part of keyhole into material is due to the melt ejection driven by laser induced surface evaporation. The calculations predict that a high speed melt flow is induced at the front part of keyhole when the sample travel speed exceeds several 10 mm/s. The numerical analysis also shows the hump formation on the front keyhole wall surface. Experimentally observed melt behavior and transformation of the AE and LE spectra with variation of welding speed are qualitatively in good agreement with the model predictions.

• Proceedings of the KSME Conference
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• 2002.08a
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• pp.717-720
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• 2002

The present study is to evaluate the performances of flow velocity and wall shear stress in the stenosed coronary artery using human in vivo hemodynamic Parameters and computer simulation. Initial and follow-up coronary angiographics in the patients with angulated coronary stenosis are performed. Follow-up coronary angiogram demonstrated significant difference in the percent of diameter in the stenosed coronary between two groups ($Group\;1:\;40.3{\%},\;Group\;2:\;25.5{\%}$). Flow-velocity wave obtained from in vivo intracoronary Doppler ultrasound data is used for the boundary condition for the computer simulation. Spatial and temporal variations of flow velocity vector and recirculation area are drawn throughout the selected segment of coronary models. The WSS of pre- and post-intracoronary stenting are calculated from three-dimensional computer simulation. Then negative shear stresses area on 3D simulation we noted on the inner wall of the post-stenotic area before stenting. The negative WSS is disappeared after stenting. High spatial and temporal WSS before stenting fell into within physiologic WSS after stenting. This finding was prominent in Model 2. The present study suggest that hemodynamic forces exerted by pulsatile coronary circulation termed WSS might affect on the evolution of atherosclerosis within the angulated vascular curvature. The local recirculation area which has low or negative WSS, might lead to progression of atherosclerosis.