• PNF and Movement
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• v.18 no.2
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• pp.287-296
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• 2020

Purpose: The study aims were to develop a wearable inertial sensor-based gait analysis device that uses machine learning algorithms, and to validate this novel device using temporal gait parameters. Methods: Thirty-four healthy young participants (22 male, 12 female, aged 25.76 years) with no musculoskeletal disorders were asked to walk at three different speeds. As they walked, data were simultaneously collected by a motion capture system and inertial measurement units (Reseed®). The data were sent to a machine learning algorithm adapted to the wearable inertial sensor-based gait analysis device. The validity of the newly developed instrument was assessed by comparing it to data from the motion capture system. Results: At normal speeds, intra-class correlation coefficients (ICC) for the temporal gait parameters were excellent (ICC [2, 1], 0.99~0.99), and coefficient of variation (CV) error values were insignificant for all gait parameters (0.31~1.08%). At slow speeds, ICCs for the temporal gait parameters were excellent (ICC [2, 1], 0.98~0.99), and CV error values were very small for all gait parameters (0.33~1.24%). At the fastest speeds, ICCs for temporal gait parameters were excellent (ICC [2, 1], 0.86~0.99) but less impressive than for the other speeds. CV error values were small for all gait parameters (0.17~5.58%). Conclusion: These results confirm that both the wearable inertial sensor-based gait analysis device and the machine learning algorithms have strong concurrent validity for temporal variables. On that basis, this novel wearable device is likely to prove useful for establishing temporal gait parameters while assessing gait.

• Korean Journal of Remote Sensing
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• v.36 no.5_1
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• pp.807-821
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• 2020

The objective of this study is to evaluate the applicability of representative spatio-temporal fusion models developed for the fusion of mid- and low-resolution satellite images in order to construct a set of time-series high-resolution images for crop monitoring. Particularly, the effects of the characteristics of input image pairs on the prediction performance are investigated by considering the principle of spatio-temporal fusion. An experiment on the fusion of multi-temporal Sentinel-2 and RapidEye images in agricultural fields was conducted to evaluate the prediction performance. Three representative fusion models, including Spatial and Temporal Adaptive Reflectance Fusion Model (STARFM), SParse-representation-based SpatioTemporal reflectance Fusion Model (SPSTFM), and Flexible Spatiotemporal DAta Fusion (FSDAF), were applied to this comparative experiment. The three spatio-temporal fusion models exhibited different prediction performance in terms of prediction errors and spatial similarity. However, regardless of the model types, the correlation between coarse resolution images acquired on the pair dates and the prediction date was more significant than the difference between the pair dates and the prediction date to improve the prediction performance. In addition, using vegetation index as input for spatio-temporal fusion showed better prediction performance by alleviating error propagation problems, compared with using fused reflectance values in the calculation of vegetation index. These experimental results can be used as basic information for both the selection of optimal image pairs and input types, and the development of an advanced model in spatio-temporal fusion for crop monitoring.

• Atmosphere
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• v.20 no.4
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• pp.495-503
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• 2010

Satellite data have an intrinsic problem due to a number of various physical parameters, which can have a similar effect on measured radiance. Most evaluations of satellite performance have relied on comparisons with limited spatial and temporal resolution of ground-based measurements such as soundings and in-situ measurements. In order to overcome this problem, a new way of satellite data evaluation is suggested with statistical tools such as empirical orthogonal function(EOF), and singular value decomposition(SVD). The EOF analyses with OMI and OMI HCHO over northeast Asia show that the spatial pattern show high correlation with population density. This suggests that human activity is a major source of as well as HCHO over this region. However, this analysis is contradictory to the previous finding with GOME HCHO that biogenic activity is the main driving mechanism(Fu et al., 2007). To verify the source of HCHO over this region, we performed the EOF analyses with vegetation and HCHO distribution. The results showed no coherence in the spatial and temporal pattern between two factors. Rather, the additional SVD analysis between $NO_2$ and HCHO shows consistency in spatial and temporal coherence. This outcome suggests that the anthropogenic emission is the main source of HCHO over the region. We speculate that the previous study appears to be due to low temporal and spatial resolution of GOME measurements or uncertainty in model input data.

• Journal of the Institute of Electronics and Information Engineers
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• v.50 no.3
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• pp.122-128
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• 2013

This paper presents a detection algorithm that accurately finds the active area of a video player on monitors or smart TVs. Unlike the previous approaches, temporal difference-based detection algorithms or hooking programs, the proposed detection algorithm can locate the active video player by using the spatial and temporal correlation and a corner detection filter. First, an initial location of the video player is found using conventional temporal difference-based detection. Then, starting from the initial location, the four corners of the active video player are detected by the spatial edge information and the corner detection filter. The experimental results show that proposed algorithm provides fast detection speed and high accuracy.

• Proceedings of the Korea Electromagnetic Engineering Society Conference
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• 2000.11a
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• pp.16-19
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• 2000

We propose a deterministic vector channel simulation model satisfying not only rigorous temporal correlation but also arbitrary spatial correlation using the method of Doppler phase difference sampling. The model is more efficient than the conventional PN filtered Gaussian model with coloring process in evaluating the laboratory performance of mobile communication systems employing adaptive way antennas or space diversity.

• Korean Journal of Remote Sensing
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• v.36 no.5_1
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• pp.725-733
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• 2020

The objectives of this study were (1) to develop a temporal mask map using MCD12Q1 data, and (2) to extract the annual variations in paddy, (3) to investigate the correlation analysis between MYD13Q1 NDVI and rice yield, and (4) to review its applicability. For these purposes, the temporal mask map was created using annual MCD12Q1 PFT data from 2002 to 2019, and compared with the fixed mask map. As a result, it found that the temporal mask map well reflected the variations of the paddy area. In addition, the correlation coefficient between NDVI and rice yield was also high significant as compared to the fixed mask map. Therefore, the temporal mask map will be useful for NDVI extraction, crop monitoring, and estimation of rice yield.

• Journal of the Korean Association of Geographic Information Studies
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• v.20 no.4
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• pp.102-114
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• 2017

The purpose of this study was the assessment of the accuracy of Global Precipitation Measurement (GPM) Integrated Multi-Satellite Retrievals for GPM (IMERG), a rainfall data source derived from satellite images, for evaluation of its applicability to use in ungauged or inaccessible areas. The study area was the overall area of the Korean peninsula divided into six regions. Automated Surface Observing System (ASOS) rainfall data from the Korean Meteorological Administration and IMERG satellite rainfall were used. Their average correlation coefficient was 0.46 for a 1-h temporal resolution, and it increased to 0.69 for a 24-h temporal resolution. The IMERG data quantitatively estimated less than the rainfall totals from ground gauges, and the bias decreased as the temporal resolution was decreased. The correlation coefficients of the two rainfall events, which had relatively greater rainfall amounts, were 0.68 and 0.69 for a 1-h temporal resolution. Additionally, the spatial distributions of the ASOS and IMERG data were similar to each other. The study results showed that the IMERG data were very useful in the assessment of the hydro-meteorological characteristics of ungauged or inaccessible areas. In a future study, verification of the accuracy of satellite-derived rainfall data will be performed by expanding the analysis periods and applying various statistical techniques.

• Anxiety and mood
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• v.18 no.2
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• pp.39-47
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• 2022

Objective : This study investigated brain functional connectivity in male firefighters who showed subclinical post-traumatic stress disorder (PTSD) symptoms. Methods : We compared the data of 17 firefighters who were not diagnosed with PTSD and 18 healthy controls who had no trauma exposure. The following instruments were applied to assess psychiatric symptoms: Korean version of the Post-traumatic stress disorder Checklist for DSM-5 (PCL-5-K), Beck Depression Inventory-II (BDI-II), Beck Anxiety Inventory (BAI). For all subjects, functional magnetic resonance imaging was performed, and functional connectivity was compared between the two groups (family-wise error-corrected p<0.05). Additionally, correlations between psychiatric symptoms and functional connectivity were explored. Results : The following connectivity was higher than that of healthy controls: 1) the central opercular cortex-superior temporal gyrus, 2) planum polare-parahippocampal gyrus, 3) angular gyrus-amygdala, and 4) temporal fusiform cortex-parahippocampal gyrus. The functional connectivity of 1) the lateral occipital cortex-inferior temporal gyrus, 2) superior parietal lobule-caudate, and 3) middle temporal gyrus-thalamus were lower in firefighters. In firefighters, the connectivity of the planum polare-parahippocampal gyrus showed a negative correlation with the severity of arousal symptoms (rho=-0.586, p=0.013). The connectivity of the middle temporal gyrus-thalamus showed a positive correlation with the severity of intrusion (rho=0.552, p=0.022) and arousal symptoms (rho=0.619, p=0.008). The connectivity of the temporal fusiform cortex-parahippocampal gyrus was negatively correlated with intrusion (rho=-0.491, p=0.045) and arousal (rho=-0.579, p=0.015). Conclusion : Our results indicate that the brain functional connectivity is associated with occupational trauma exposure in firefighters without PTSD. Therefore, this study provides evidence that close monitoring and early intervention are important for firefighters with traumatic experience even at a subthreshold level.

• The Korean Journal of Nuclear Medicine
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• v.39 no.6
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• pp.438-444
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• 2005

Purpose: Anhedonia has been proposed to be the result of a basic neurophysiologic dysfunction and a vulnerability marker that precede and contribute to the liability of developing schizophrenia. We hypothesized that anhedonia, as a construct reflecting the decreased capacity to experience pleasure, should be associated with decreased positive hedonic affect trait. This study examined the relationship between anhedonia and positive hedonic affect trait and searched for the brain legions which correlate with anhedonia in normal subjects. Materials and Methods: Using $^{18}F$-FDG PET scan, we investigated the brain activity of twenty one subjects during resting state. Questionnaires were administrated after the scan in order to assess the self-rated individual differences in physical/social anhedonia and positive/negative affect traits. Results: Negative correlation between physical anhedonia score and positive affect trait score was significant (Pearson coefficient =-0.440, p<0.05). The subjects physical and social anhedonia scores showed positive correlation with metabolic rates in the cerebellum and negative correlation with metabolic rates in the inferior temporal gyrus and middie frontal gyrus. In addition, the positive affect trait score positively correlated with various areas, most prominent with the inferior temporal gyrus. Conclusion: These results suggest that neural substrates, such as the inferior temporal gyrus and prefrontal-cerebellar circuit, which dysfunction has been proposed to be involved with the cognitive deficits of schizophrenia, may also play a significant role in the liability of affective deficits like anhedonia.

• Journal of Korea Multimedia Society
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• v.18 no.3
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• pp.323-329
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• 2015

In this paper we applied pattern recognition approach to detect audio forgery. Classification of the microphone types and models can help determining the authenticity of the recordings. Canonical correlation analysis was applied to extract feature for microphone classification. We utilized the linear dependence between two near-silence regions. To utilize the advantage of multi-feature based canonical correlation analysis, we selected three commonly used features to capture the temporal and spectral characteristics. Using three different microphones, we tested the usefulness of multi-feature based characteristics of canonical correlation analysis and compared the results with single feature based method. The performance of classification rate was carried out using the backpropagation neural network. Experimental results show the promise of canonical correlation features for microphone classification.