• Journal of KIISE:Software and Applications
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• v.26 no.1
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• pp.157-157
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• 1999

Researches on the gesture recognition have become a very interesting topic in the computer vision area, Gesture recognition from visual images has a number of potential applicationssuch as HCI (Human Computer Interaction), VR(Virtual Reality), machine vision. To overcome thetechnical barriers in visual processing, conventional approaches have employed cumbersome devicessuch as datagloves or color marked gloves. In this research, we capture gesture images without usingexternal devices and generate a gesture trajectery composed of point-tokens. The trajectory Is spottedusing phase-based velocity constraints and recognized using the discrete left-right HMM. Inputvectors to the HMM are obtained by using the LBG clustering algorithm on a polar-coordinate spacewhere point-tokens on the Cartesian space .are converted. A gesture vocabulary is composed oftwenty-two dynamic hand gestures for editing drawing elements. In our experiment, one hundred dataper gesture are collected from twenty persons, Fifty data are used for training and another fifty datafor recognition experiment. The recognition result shows about 95% recognition rate and also thepossibility that these results can be applied to several potential systems operated by gestures. Thedeveloped system is running in real time for editing basic graphic primitives in the hardwareenvironments of a Pentium-pro (200 MHz), a Matrox Meteor graphic board and a CCD camera, anda Window95 and Visual C++ software environment.

• Journal of Advanced Navigation Technology
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• v.13 no.4
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• pp.523-531
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• 2009

In this study, we propose a joint source/channel rate control algorithm for video encoder targeting packet erasure channel. Based on the buffer constraints of video communication systems, encoding rate constraint is presented. After defining source distortion models for coded and skipped video frames and a channel distortion model for packet errors and their propagation, an average distortion model of received video is proposed for a given encoding window. Finally, we define an optimization problem to minimize the average distortion for given channel rates and packet loss rates by controlling spatio-temporal parameters of source video and FEC block sizes. Then, we propose a window-based algorithm to solve the problem in real-time.

• Journal of radiological science and technology
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• v.42 no.2
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• pp.119-130
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• 2019

Positron emission tomography (PET) is widely used imaging modality for effective and accurate functional testing and medical diagnosis using radioactive isotopes. However, PET has difficulties in acquiring images with high image quality due to constraints such as the amount of radioactive isotopes injected into the patient, the detection time, the characteristics of the detector, and the patient's motion. In order to overcome this problem, we have succeeded to improve the image quality by using the dynamic image reconstruction method based on singular value decomposition. However, there is still some question about the characteristics of the proposed technique. In this study, the characteristics of reconstruction method based on singular value decomposition was estimated over computational simulation. As a result, we confirmed that the singular value decomposition based reconstruction technique distinguishes the images well when the signal - to - noise ratio of the input image is more than 20 decibels and the feature vector angle is more than 60 degrees. In addition, the proposed methode to estimate the characteristics of reconstruction technique can be applied to other spatio-temporal feature based dynamic image reconstruction techniques. The deduced conclusion of this study can be useful guideline to apply medical image into SVD based dynamic image reconstruction technique to improve the accuracy of medical diagnosis.

• Journal of Plant Biotechnology
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• v.46 no.4
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• pp.255-273
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• 2019

Orchids are indispensable to the floriculture industry due to their unique floral organization. The flowers have two outer whorls of tepals including a lip (labellum), and two inner whorls, pollinia and gynostemiun (column). The floral organization and development is controlled at the molecular level, mainly by the MADS-box gene family, comprising homeotic genes divided into type I and type II groups. The type I group has four sub-groups, Mα, Mβ, Mγ, and Mδ, playing roles in seed, embryo, and female reproductive organ development; the type II group genes form classes A, B, C, D, and E, which are a part of the MIKC^C subgroup with specific roles in florigenesis and organization. The coordinated functioning of these classes regulates the development of various floral whorls. The availability of genome and transcriptome sequence data for Phalaenopsis equestris offers an opportunity to validate the ABCDE model of flower development. Hence, this study sought to characterize the MADS-box gene family and elucidate of the ABCDE model. A total of 48 identified MADS-box proteins, including 20 type I [Mα (12), Mγ (8)] and 28 type II [MIKC^C (27), MIKC*(1)] members, were characterized for physico-chemical features and domains and motifs organization. The exon-intron distribution and the upstream cis-regulatory elements in the promoter regions of MADS-box genes were also analysed. The discrete pace of duplication events in type I and type II genes suggested differential evolutionary constraints between groups. The correlation of spatio-temporal expression pattern with the presence of specific cis-regulatory elements and putative protein-protein interaction within the different classes of MADS-box gene family endorse the ABCDE model of floral development.

• Cartoon and Animation Studies
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• s.49
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• pp.203-220
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• 2017

In the field of visual arts, the introduction of synthesis allowed us to express various expressions that were outside the constraints of time and space. Digital synthesis is constrained by realistic representation due to technical limitations. However, it is no exaggeration to say that after digital synthesis has been fully established, at least the limits of image representation through synthesis have almost disappeared. The existing research papers on composing are either technical studies on the production techniques, or the synthesis was mainly focused on the change of the space-time concept and meaning of the visual arts. I felt the need for research on. In addition, I felt the need to look back on the changes in my view of art. Therefore, in this paper, rather than dealing with the conceptual theory of the technical part or spatio-temporal extension, it is necessary to classify it as natural, heterogeneous, heterogeneous and natural according to the traits revealed in the artistic expression of art, And diversity.

• Journal of Internet Computing and Services
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• v.10 no.4
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• pp.35-44
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• 2009

The emerging notion of data stream has brought many new challenges to the research communities as a consequence of its conceptual difference with conventional concepts of just data. One typical example is data stream processing in sensor networks. The range of data processing considerations in a sensor network is very wide, from physical resource restrictions such as bandwidth, energy, and memory to the peculiarities of query processing including continuous and specific types of queries. In this paper, as one of the physical constraints in data stream processing, we consider the problem of limited memory and propose a new scheme for data stream reduction based on the Principal Component Analysis (PCA) technique. PCA can transform a number of (possibly) correlated variables into a (smaller) number of uncorrelated variables. We adapt PCA for the data stream of a sensor network assuming the cooperation of a query engine (or application) with a network base station. Our method exploits the spatio-temporal correlation among multiple measurements from different sensors. Finally, we present a new framework for data processing and describe a number of experiments under this framework. We compare our scheme with the wavelet transform and observe the effect of time stamps on the compression ratio. We report on some of the results.

• Phonetics and Speech Sciences
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• v.11 no.3
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• pp.31-38
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• 2019

The current electromagnetic articulography study analyzes several articulatory measures and examines whether, and if so, how they are interconnected, with a focus on cluster types and an additional consideration of speech rates and morphosyntactic contexts. Using articulatory data on non-assimilating contexts from three Seoul-Korean speakers, we examine how speaker-dependent gestural overlap between C1 and C2 in a low vowel context (/a/-to-/a/) and their resulting intergestural coordination are realized. Examining three C1C2 sequences (/k(#)t/, /k(#)p/, and /p(#)t/), we found that three normalized gestural overlap measures (movement onset lag, constriction onset lag, and constriction plateau lag) were correlated with one another for all speakers. Limiting the scope of analysis to C1 velar stop (/k(#)t/ and /k(#)p/), the results are recapitulated as follows. First, for two speakers (K1 and K3), i) longer normalized constriction plateau lags (i.e., less gestural overlap) were observed in the pre-/t/ context, compared to the pre-/p/ (/k(#)t/>/k(#)p/), ii) the tongue dorsum at the constriction offset of C1 in the pre-/t/ contexts was more anterior, and iii) these two variables are correlated. Second, the three speakers consistently showed greater horizontal distance between the vertical tongue dorsum and the vertical tongue tip position in /k(#)t/ sequences when it was measured at the time of constriction onset of C2 (/k(#)t/>/k(#)p/): the tongue tip completed its constriction onset by extending further forward in the pre-/t/ contexts than the uncontrolled tongue tip articulator in the pre-/p/ contexts (/k(#)t/>/k(#)p/). Finally, most speakers demonstrated less variability in the horizontal distance of the lingual-lingual sequences, which were taken as the active articulators (/k(#)t/=/k(#)p/ for K1; /k(#)t/

• The KIPS Transactions:PartD
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• v.16D no.1
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• pp.113-122
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• 2009

Since the traditional pattern mining methods only probe unspecified moving patterns that seem to satisfy users' requests among diverse patterns within the limited scopes of time and space, they are not applicable to problems involving the mining of optimal moving patterns, which contain complex time and space constraints, such as 1) searching the optimal path between two specific points, and 2) scheduling a path within the specified time. Therefore, in this paper, we illustrate some problems on mining the optimal moving patterns with complex time and space constraints from a vast set of historical data of numerous moving objects, and suggest a new moving pattern mining method that can be used to search patterns of an optimal moving path as a location-based service. The proposed method, which determines the optimal path(most frequently used path) using pattern frequency retrieved from historical data of moving objects between two specific points, can efficiently carry out pattern mining tasks using by space generalization at the minimum level on the moving object's location attribute in consideration of topological relationship between the object's location and spatial scope. Testing the efficiency of this algorithm was done by comparing the operation processing time with Dijkstra algorithm and $A^*$ algorithm which are generally used for searching the optimal path. As a result, although there were some differences according to heuristic weight on $A^*$ algorithm, it showed that the proposed method is more efficient than the other methods mentioned.

• Journal of the Korean Geographical Society
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• v.42 no.5
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• pp.808-834
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• 2007

This study attempts to elucidate manifold dimensions of gendered accessibility experiences. How gender roles(household responsibilities) differentiate accessibility experiences between women and men is explored through the comparison of married dual-earner couples' parental status, using the US Portland activity-travel diary dataset with GIS-based geocomputation results of(time-geography based) space-time accessibility. First, this study shows how gender division of labor within the household still permeates current society, despite the widespread belief of the social change toward a gender-egalitarian society. Then, the study pays special attention to the way gender roles structure individual accessibility experiences of women and men differently, and, in turn, the way such accessibility experiences take a form of gendered spatiality. Gendered spatiality is examined through the analysis of accessibility space as well as activity space in order to ascertain women's home-attached and spatially entrapped characteristics. More household responsibilities throughout a day and, even more, the time constraint of picking up children at the daycare centers after work lead women's possible activity space to be more home-centered. The analysis of the spatio-temporal context of accessibility space makes gendered spatiality visible. However, the findings suggest that behavioral outcomes should be understood with an explicit awareness of constraints individuals face. It is because the revealed activity spaces can be not only an outcome of constraint but also an outcome of choice. Behavioral outcomes should not be treated as a straightforward expression of the level of constraints. It is problematic to expect that behavioral outcomes directly mirror the level of constraints. It is also problematic to suppose that the level of constraints can be straightforwardly elicited from revealed behavioral outcomes.

• Spatial Information Research
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• v.22 no.1
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• pp.55-63
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• 2014

Near surface air temperature data which are one of the essential factors in hydrology, meteorology and climatology, have drawn a substantial amount of attention from various academic domains and societies. Meteorological observations, however, have high spatio-temporal constraints with the limits in the number and distribution over the earth surface. To overcome such limits, many studies have sought to estimate the near surface air temperature from satellite image data at a regional or continental scale with simple regression methods. Alternatively, we applied various Kriging methods such as ordinary Kriging, universal Kriging, Cokriging, Regression Kriging in search of an optimal estimation method based on near surface air temperature data observed from automatic weather stations (AWS) in South Korea throughout 2010 (365 days) and MODIS land surface temperature (LST) data (MOD11A1, 365 images). Due to high spatial heterogeneity, auxiliary data have been also analyzed such as land cover, DEM (digital elevation model) to consider factors that can affect near surface air temperature. Prior to the main estimation, we calculated root mean square error (RMSE) of temperature differences from the 365-days LST and AWS data by season and landcover. The results show that the coefficient of variation (CV) of RMSE by season is 0.86, but the equivalent value of CV by landcover is 0.00746. Seasonal differences between LST and AWS data were greater than that those by landcover. Seasonal RMSE was the lowest in winter (3.72). The results from a linear regression analysis for examining the relationship among AWS, LST, and auxiliary data show that the coefficient of determination was the highest in winter (0.818) but the lowest in summer (0.078), thereby indicating a significant level of seasonal variation. Based on these results, we utilized a variety of Kriging techniques to estimate the surface temperature. The results of cross-validation in each Kriging model show that the measure of model accuracy was 1.71, 1.71, 1.848, and 1.630 for universal Kriging, ordinary Kriging, cokriging, and regression Kriging, respectively. The estimates from regression Kriging thus proved to be the most accurate among the Kriging methods compared.