• Journal of the Institute of Electronics Engineers of Korea CI
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• v.38 no.6
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• pp.1-17
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• 2001

Nowadays, spatiotemporal data models deal with objects which can be potentially useful for wide range applications in order to describe complex objects with spatial and/or temporal facilities. However, the information needed by each application usually varies, specially in the geographic information which depends on the kind of time oriented views, as defined in the modeling phase of the spatiotemporal geographic data design. To be able to deal with such diverse needs, geographic information systems must offer features that manipulate geometric, space-dependent(i.e, thematic), and spatial relationship positions with multiple time oriented views. This paper addresses problems of the formal definition of relationships among spatiotemporal objects and their properties on geographic information systems. The geographical data are divided in two main classes : geo-objects and geo-fields, which describe discrete and continuous representations of the spatial reality. I study semantics and syntax about the temporal changes of attributes and the relationship roles on geo-objects and non-geo-objects, This result will contribute on the design of object oriented spatiotemporal data model which is distinguishied from the recent geographic information system of the homogeneously anchored spatial objects

• Physical Therapy Korea
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• v.26 no.1
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• pp.1-7
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• 2019

Background: The Microsoft Kinect which is a low-cost gaming device has been studied as a promise clinical gait analysis tool having satisfactory reliability and validity. However, its accuracy is only guaranteed when it is properly positioned in front of a subject. Objects: The purpose of this study was to identify the error when the Kinect was positioned at a $45^{\circ}$ angle to the longitudinal walking plane compare with those when the Kinect was positioned in front of a subject. Methods: Sixteen healthy adults performed two testing sessions consisting of walking toward and $45^{\circ}$ obliquely the Kinect. Spatiotemporal outcome measures related to stride length, stride time, step length, step time and walking speed were examined. To assess the error between Kinect and 3D motion analysis systems, mean absolute errors (MAE) were determined and compared. Results: MAE of stride length, stride time, step time and walking speed when the Kinect set in front of subjects were investigated as .36, .04, .20 and .32 respectively. MAE of those when the Kinect placed obliquely were investigated as .67, .09, .37, and .58 respectively. There were significant differences in spatiotemporal outcomes between the two conditions. Conclusion: Based on our study experience, positioning the Kinect directly in front of the person walking towards it provides the optimal spatiotemporal data. Therefore, we concluded that the Kinect should be placed carefully and adequately in clinical settings.

• Journal of the Korea Fashion and Costume Design Association
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• v.8 no.2
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• pp.47-59
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• 2006

The purpose of this study is to grasp the meaning of retro-fashion, to research the formative feature characteristic and aesthetic values. Retro-fashion is one of the expression of spatiotemporal-eclecticism, The formative of modern Retro-fashion are as follows: First, Retro-fashion based on spatiotemporal-eclecticism have been come from 40s, 50s, 60s, 70s, 80s style of time, and the asia, africa, middle east, latin America in region. Second, the design inspiration and technique is used more primitive crafts and decoration like handcrafted material, handmade ornaments as dyeing and embroidery of bohemian, jacqwuard pattern, oriental beads, applique, new hippie touch, patchwork, smocking, primitive button, woods, ethnic motives. Third, modern Retro-fashion is reflection of human feelings as nostalgia from the past, it supplies the sense of fashion creativity and new ideas.

• 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.

• Journal of the Korea Society of Computer and Information
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• v.10 no.5 s.37
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• pp.95-102
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• 2005

A Parallel Processing model by considering a spatiotemporal parallelism is presented for the training procedure of the MLP neural network. We tried to design the flexible Parallel Processing model by simultaneously applying both of the training-set decomposition for a temporal parallelism and the network decomposition for a spatial parallelism. The analytical Performance evaluation model shows that when the problem size is extremely large, the speedup of each implementation depends, in the extreme, on whether the problem size is pattern-size intensive or pattern-quantify intensive.

• Journal of Institute of Control, Robotics and Systems
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• v.15 no.1
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• pp.111-119
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• 2009

For daily life interaction with human, robots need the capability of encoding and storing cognitive information and retrieving it contextually. In this paper, spatiotemporal grounding of cognitive information for a language based cognitive system is presented. The cognitive information of the event occurred at a robot is described with a sentence, stored in a memory, and retrieved contextually. Each sentence is parsed, discriminated with the functional type of it, and analyzed with argument structure for connecting to cognitive information. With the proposed grounding, the cognitive information is encoded to sentence form and stored in sentence memory with object descriptor. Sentences are retrieved for answering questions of human by searching temporal information from the sentence memory and doing spatial reasoning in schematic imagery. An experiment shows the feasibility and efficiency of the spatiotemporal grounding for advanced service robot.

• Communications for Statistical Applications and Methods
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• v.10 no.1
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• pp.19-30
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• 2003

Spatiotemporal statistical models are used for analyzing space-time data in many fields, such as environmental sciences, meteorology, geology, epidemiology, forestry, hydrology, fishery, and so on. It is well known that classical spatiotemporal process modeling requires the estimation of space-time variogram or covariance functions. In practice, the estimation of such variogram or covariance functions are computationally difficult and highly sensitive to data structures. We investigate a Bayesian hierarchical model which allows the specification of a more realistic series of conditional distributions instead of computationally difficult and less realistic joint covariance functions. The spatiotemporal model investigated in this study allows both spatial component and autoregressive temporal component. These two features overcome the inability of pure time series models to adequately predict changes in trends in individual sites.

• Korean Journal of Remote Sensing
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• v.36 no.4
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• pp.637-643
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• 2020

In this study, the information from environmental impact statements was converted into spatial data because environmental data from development sites are collected during the environmental impact assessment (EIA) process. Spatiotemporal big data were built from environmental spatial data for each environmental medium for 2,235 development sites during 2007-2018, available from public data portals. Comparing air-quality monitoring stations, 33,863 measurement points were constructed, which is approximately 75 times more measurement points than that 452 in Air Korea's real-time measurement network. Here, spatiotemporal big data from 2,677,260 EIAs were constructed. In the future, such data might be used not only for EIAs but also for various spatial plans.

• Journal of the Optical Society of Korea
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• v.16 no.4
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• pp.425-431
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• 2012

Utilizing the three-dimensional Snyder-Mitchell model with a PT-symmetric potential, we study the influence of PT symmetry on beam propagation in strongly nonlocal nonlinear media. The complex Coulomb potential is used as the PT-symmetric potential. A localized spatiotemporal accessible soliton solution of the model is obtained. Specific values of the modulation depth for different soliton parameters are discussed. Our results reveal that in these media the localized solitons can exist in various shapes, such as single-layer and multi-layer disk-shaped structures, as well as vortex-ring and necklace patterns.

• 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.