• Journal of the Korean Society of Marine Environment & Safety
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• v.26 no.7
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• pp.759-766
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• 2020

In recent years, the maritime traffic environment has been changing in various ways, and the traffic volume has been increasing constantly. Accordingly, the requirements for maritime traffic analysis have become diversified. To this end, traffic characteristics must first be analyzed using vessel trajectory data. However, as the conventional method is mostly manual, it requires a considerable amount of time and effort, and errors may occur during data processing. In addition, ensuring the reliability of the analysis results is difficult, because this method considers the subjective opinion of analysts. Therefore, in this paper, we propose an automated method of traffic network generation for maritime traffic analysis. In the experiment, spatiotemporal features are analyzed using data collected at Mokpo Harbor over six months. The proposed method can automatically generate a traffic network reflecting the traffic characteristics of the experimental area. In addition, it can be applied to a large amount of trajectory data. Finally, as the spatiotemporal characteristics can be analyzed using the traffic network, the proposed method is expected to be used in various maritime traffic analyses.

• ETRI Journal
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• v.44 no.4
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• pp.624-640
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• 2022

Taxi-demand forecasting and hotspot prediction can be critical in reducing response times and designing a cost effective online taxi-booking model. Taxi demand in a region can be predicted by considering the past demand accumulated in that region over a span of time. However, other covariates-like neighborhood influence, sociodemographic parameters, and point-of-interest data-may also influence the spatiotemporal variation of demand. To study the effects of these covariates, in this paper, we propose three models that consider different covariates in order to select a set of independent variables. These models predict taxi demand in spatial units for a given temporal resolution using linear and ensemble regression. We eventually combine the characteristics (covariates) of each of these models to propose a robust forecasting framework which we call the combined covariates model (CCM). Experimental results show that the CCM performs better than the other models proposed in this paper.

• Journal of Biomedical Engineering Research
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• v.28 no.1
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• pp.17-23
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• 2007

Long-term potentiation (LTP) of synaptic transmission is the most widely studied model for learning and memory. However its mechanisms are not clearly elucidated and are a subject for intense investigation. Previous attempts to decipher cellular mechanisms and network properties involved a current-source density analysis (CSDA) of the LTP from small animal hippocampus measured with a limited number of microelectrodes (typically <3), only revealing limited nature of spatiotemporal dynamics. Recent advancement in multi-electrode array (MEA) technology allows continuous and simultaneous recordings of LTP with more than 60 electrodes. However CSDA via the standard Laplacian transform is still limited due to its relatively high sensitivity toward noise, inability of resolving overlapped current sources and sinks, and its requirement for tissue conductivity values. In this study, we propose a new methodology for improved CSDA. Independent component analysis and its joint use (i.e., Joint-ICA) are applied to extract spatiotemporal components of LTP. The results show that ICA and Joint-ICA are capable of extracting independent spatiotemporal components of LTP generators. The ICs of LTP indicate the reversing roles of current sources and sinks which are associated with LTP.

• The Journal of the Society of Stroke on Korean Medicine
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• v.14 no.1
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• pp.1-7
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• 2013

The following study reviewed the walking patterns of stroke patients with hemiplegia, which is called hemiplegic gait of stroke patients. Focusing is given to the changes in the distance and temporal factors of walking, which is called spatiotemporal characteristics, throughout the walking cycle. First, we introduced the definitions of essential terms related to gait and its measure. Second, we reviewed the spatiotemporal characteristics of hemiplegic gait. A main issue was that hemiplegic gait showed significant deviations from normal healthy gait. Although hemiplegia is primarily associated with unilateral motor disorder, changes in almost all spatiotemporal parameters used to assess walking were evident on both the involved and uninvolved sides of the body. Last, we reviewed the changes of spatiotemporal parameters of hemiplegic gait according to the prognosis or status of stroke patients, which may help to give a specific intervention for rehabilitation of stroke.

• Physical Therapy Rehabilitation Science
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• v.11 no.1
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• pp.105-112
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• 2022

Objective: Nonspecific low back pain (NS-LBP) causes pain and disability, affecting the neuromuscular system and altering gait patterns. The purpose of this study is to investigate the effect of improvement of low back pain symptoms through physical therapy on foot pressure and spatiotemporal gait parameters. Design: A pilot study. Methods: Participants received manual therapy and supervised therapeutic exercise, which consisted of 12 sessions for 6 weeks. Participants were assessed for pain intensity (a numeric pain rating scale), disability index (oswestry disability index), and spatiotemporal gait parameters before and after intervention. Wilcoxon signed rank test was used to analyze the before-and-after differences in a single group. Results: All seven NS-LBP patients completed the study without dropout. After six weeks of physical therapy, the numeric pain rating scale and oswestry disability index showed significant improvement (Z= -2.388, P=0.017). There was no significant improvement in both static and dynamic conditions in foot pressure (P>0.05). However, in the spatiotemporal gait parameters, there were significant differences in all variables except the right stance phase and left mid stance (P<0.05). Conclusions: In our pilot study, 12 sessions of physical therapy in NS-LBP patients improved gait quilty in spatiotemporal gait parameters. Similarly, it has resulted in clinically positive improvements in pain and disability.

• Korean Journal of Applied Biomechanics
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• v.31 no.2
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• pp.95-103
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• 2021

Objective: The aim of this study was to investigate the differences in spatiotemporal gait performance, function, and pain of lower-extremity according to foot morphological characteristics. Method: This case-control study recruited 42 adults and they were classified into 3 groups according to foot morphology using navicular-drop test: pronated (≥ 10 mm), normal (5~9 mm), and supinated (≤ 4 mm) feet. Spatiotemporal gait analysis and questionnaires including Foot and Ankle Ability Measure activities of daily living / Sports, Western Ontario and McMasters Universities Osteoarthritis Index, Lower Extremity Functional Scale, International Physical Activity Questionnaire, and Tegner activity score were conducted. One-way analysis of variance was used for statistical analysis. Results: The pronated feet group showed longer loading response and double limb support in both feet and increased pre-swing phase in non-dominant feet. The supinated feet group demonstrated a longer swing phase in non-dominant feet and single limb support in dominant feet. However, there was no significant group difference in function and pain of knee joint and lower-extremity between groups. Conclusion: Our results indicated that abnormal spatiotemporal gait performance according to foot morphology. Although there was no difference in lower extremity dysfunction and pain according to the difference in foot morphology, they have the possibility of symptom occurs as a result of continuous participation in activities of daily living and sports. Therefore, individuals with pronated or supinated foot should be supplemented by utilizing an orthosis or training to restore normal gait performance.

• Journal of information and communication convergence engineering
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• v.6 no.3
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• pp.315-319
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• 2008

This paper describes a method for recognizing and measuring the motion of each individual leukocyte in microvessel from a sequence of images. A spatiotemporal image is generated whose spatial axes are parallel and vertical to vessel region contours. In order to enhance and extract only leukocyte traces with a turned velocity range even under noisy background, we use a combination of a filtering process using Gabor filters with sharp orientation selectivity and a subsequent 3D spatiotemporal grouping process. The proposed method is shown to be effective by experiments using image sequences of two kinds of microcirculation, rat mesentery microvessels and human retinal capillaries.

• ETRI Journal
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• v.43 no.2
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• pp.272-287
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• 2021

This article presents a multi-dimensional spatial pattern analysis of crime events in San Francisco. Our analysis includes the impact of spatial resolution on hotspot identification, temporal effects in crime spatial patterns, and relationships between various crime categories. In this work, crime prediction is viewed as a classification problem. When predictions for a particular category are made, a binary classification-based model is framed, and when all categories are considered for analysis, a multiclass model is formulated. The proposed crime-prediction model (HotBlock) utilizes spatiotemporal analysis for predicting crime in a fixed spatial region over a period of time. It is robust under variation of model parameters. HotBlock's results are compared with baseline real-world crime datasets. It is found that the proposed model outperforms the standard DeepCrime model in most cases.

• Journal of the Korean Mathematical Society
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• v.57 no.1
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• pp.249-281
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• 2020

A reaction-diffusion model with spatiotemporal delay modeling the dynamical behavior of a single species is investigated. The parameter regions for the local stability, global stability and instability of the unique positive constant steady state solution are derived. The conditions of the occurrence of Turing (diffusion-driven) instability are obtained. The existence of time-periodic solutions, the existence and nonexistence of nonconstant positive steady state solutions are proved by bifurcation method and energy method. Numerical simulations are presented to verify and illustrate the theoretical results.

• The KIPS Transactions:PartD
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• v.8D no.2
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• pp.105-116
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• 2001

Moving objects are spatiotemporal data that location and shape of spatial objects are changed continuously over time. If spatiotemporal moving objects are managed by conventional database system, moving objects management systems have two problems as follows. First, update for location information changed over time is occurred frequently. Second, past and future information of moving objects are not provided by system because only current state of objects is stored in the system. Therefore, in this paper, we propose a spatiotemporal moving objects management system which is able to not only manage historical information of moving objects without frequent update, but also provide all location information about past, current, and near future. In the proposed system, information of moving objects are divided into location information for representing location and motion information for representing moving habits. Especially, we propose the method which can search location information all objects by use of changing process algorithms with minimum history information. Finally, we applied the proposed method to battlefield analysis system, as the result of experiment, we knew that past, current, and near future location information for moving objects are managed by relational database and GIS system.