• The Journal of the Korea Contents Association
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• v.16 no.6
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• pp.9-18
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• 2016

This paper proposes a multi-view Wyner-Ziv Video coding scheme based on spatio-temporal adaptive estimation. The proposed algorithm is designed to search for a better estimated block with joint bi-directional motion estimation by introducing weights between temporal and spatial directions, and by classifying effectively the region of interest blocks, which is based on the edge detection and the synthesis, and by selecting the reference estimation block from the effective motion vector analysis. The proposed algorithm exploits the information of a single frame viewpoint and adjacent frame viewpoints, simultaneously and then generates adaptively side information in a variety of closure, and reflection regions to have a better performance. Through several simulations with multi-view video sequences, it is shown that the proposed algorithm performs visual quality improvement as well as bit-rate reduction, compared to the conventional methods.

• Journal of Broadcast Engineering
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• v.20 no.3
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• pp.449-463
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• 2015

Video object tracking is important for variety of applications, such as security, video indexing and retrieval, video surveillance, communication, and compression. This paper proposes an object tracking method in HEVC bitstreams. Without pixel reconstruction, motion vector (MV) and size of prediction unit in the bitstream are employed in an Spatio-Temporal Markov Random Fields (ST-MRF) model which represents the spatial and temporal aspects of the object's motion. Coefficient-based object shape adjustment is proposed to solve the over-segmentation and the error propagation problems caused in other methods. In the experimental results, the proposed method provides on average precision of 86.4%, recall of 79.8% and F-measure of 81.1%. The proposed method achieves an F-measure improvement of up to 9% for over-segmented results in the other method even though it provides only average F-measure improvement of 0.2% with respect to the other method. The total processing time is 5.4ms per frame, allowing the algorithm to be applied in real-time applications.

• The Journal of Korean Physical Therapy
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• v.18 no.1
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• pp.95-106
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• 2006

Purpose: The aim of this study was to investigate the kinematics of young adults during ramp climbing at different inclinations. Methods: Twenty-three subjects ascended and descended four steps at four different inclinations(level, $8^{\circ},\;16^{\circ},\;24^{\circ}$). Temporal-spatial parameters were measured by GaitRite system(standard mat). Groups difference was analysed with on-way ANOVA and Student-Newman-Keuls test. Results: The different kinematics of ramp ascent and descent were analysed and compared to level walking patterns. In ascending ramps, step length and stride length decreased with $24^{\circ}$ inclination (p<.000). Stance duration increased with $24^{\circ}$, but swing duration decreased with $24^{\circ}$ inclination (p<.000). Step time and velocity decreased with $16^{\circ}C,\;24^{\circ}$ inclination (p<.000). Cadence decreased with all inclination($8^{\circ},\;16^{\circ},\;24^{\circ}$)(p<.000). In descending ramps, step length and stride length, velocity decreased with all inclination($8^{\circ},\;16^{\circ},\;-24^{\circ}$)(p<.000). Stance duration increased with all inclination($8^{\circ},\;-16^{\circ},\;-24^{\circ}$) and swing duration decreased with all inclination($-8^{\circ},\;-16^{\circ},\;-24^{\circ}$)(p<.000). But Step time was not differentiated with different inclinations. Cadence decreased with only. $8^{\circ}$ inclination(p<.05). Conclusion: These results suggest that there is a certain inclination angle or angular range where subjects do switch between level walking and ramp walking gait pattern. This shows their motor control strategy between level and ramp walking. Further studies are necessary to confirm and detect the ascent and descent ramp gait patterns.

• Animal Bioscience
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• v.37 no.8
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• pp.1367-1376
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• 2024

Objective: Parathyroid hormone like hormone (PTHLH), as an essential factor for bone growth, is involved in a variety of physiological processes. The aim of this study was to explore the role of PTHLH gene in the growth of antlers. Methods: The coding sequence (CDS) of PTHLH gene cDNA was obtained by cloning in sika deer (Cervus nippon), and the bioinformatics was analyzed. The quantitative real-time polymerase chain reaction (qRT-PCR) was used to analyze the differences expression of PTHLH mRNA in different tissues of the antler tip at different growth periods (early period, EP; middle period, MP; late period, LP). Results: The CDS of PTHLH gene was 534 bp in length and encoded 177 amino acids. Predictive analysis results revealed that the PTHLH protein was a hydrophilic protein without transmembrane structure, with its secondary structure consisting mainly of random coil. The PTHLH protein of sika deer had the identity of 98.31%, 96.82%, 96.05%, and 94.92% with Cervus canadensis, Bos mutus, Oryx dammah and Budorcas taxicolor, which were highly conserved among the artiodactyls. The qRT-PCR results showed that PTHLH mRNA had a unique spatio-temporal expression pattern in antlers. In the dermis, precartilage, and cartilage tissues, the expression of PTHLH mRNA was extremely significantly higher in MP than in EP, LP (p<0.01). In the mesenchyme tissue, the expression of PTHLH mRNA in MP was significantly higher than that of EP (p<0.05), but extremely significantly lower than that of LP (p<0.01). The expression of PTHLH mRNA in antler tip tissues at all growth periods had approximately the same trend, that is, from distal to basal, it was first downregulated from the dermis to the mesenchyme and then continuously up-regulated to the cartilage tissue. Conclusion: PTHLH gene may promote the rapid growth of antler mainly through its extensive regulatory effect on the antler tip tissue.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.6 no.7
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• pp.1815-1830
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• 2012

Existing R-tree that is based on a variety of outdoor-based techniques to manage moving objects have been investigated. Due to the different characteristics of the indoor and outdoor, it is difficult to management of moving object using existed methods in indoor setting. We propose a new index structure called ACII(adaptive Cell-based index for Indoor moving objects) for Indoor moving objects. ACII is Cell-based access structure adopting an overlapping technique. The ACII refines cells adaptively to handle indoor regional data, which may change its locations over time. The ACII consumed at most 30% of the space required by R-tree based methods, and achieved higher query performance compared with r-tree based methods.

• Journal of the Korean Institute of Landscape Architecture
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• v.26 no.4
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• pp.105-112
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• 1999

Landcover change is an important factor that changes structure and function of regional ecosystem. As the rise of concern on environment quality, many studies are trying to quantify and evaluate the landsacpe in recent days. In this study, using landscape indices with RS(Remote Sensing) and GIS(Geographic Information System) technology, spatio-temporal variations of areas and distribution of forest patches were examined in the Chonan from 1985 to 1996. Fragstats 2.0 was employed to analyze and compute 31 landscape indices from 52 landcover maps. A result of this study showed that area of forest and paddy decreased as a result of urban sprawl. Especially from 1993 to 1996, the change of land use progressed rapidly because of merging a city and a country in Chonan. The size of patch in forest had been smaller and irregular form, heterogeneity of size of forest patches within sub-basin increased, and variety of patch types around forest patches increased from 1985 to 1996.

• Journal of Korea Multimedia Society
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• v.23 no.12
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• pp.1540-1551
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• 2020

Aiming at the problem that the existing human behavior recognition algorithm cannot fully utilize the multi-level spatio-temporal information of the network, a human behavior recognition algorithm based on a dense three-dimensional residual network is proposed. First, the proposed algorithm uses a dense block of three-dimensional residuals as the basic module of the network. The module extracts the hierarchical features of human behavior through densely connected convolutional layers; Secondly, the local feature aggregation adaptive method is used to learn the local dense features of human behavior; Then, the residual connection module is applied to promote the flow of feature information and reduced the difficulty of training; Finally, the multi-layer local feature extraction of the network is realized by cascading multiple three-dimensional residual dense blocks, and use the global feature aggregation adaptive method to learn the features of all network layers to realize human behavior recognition. A large number of experimental results on benchmark datasets KTH show that the recognition rate (top-l accuracy) of the proposed algorithm reaches 93.52%. Compared with the three-dimensional convolutional neural network (C3D) algorithm, it has improved by 3.93 percentage points. The proposed algorithm framework has good robustness and transfer learning ability, and can effectively handle a variety of video behavior recognition tasks.

• The Journal of the Korea Contents Association
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• v.20 no.12
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• pp.230-240
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• 2020

To develop a virtual world-based immersive tutoring system, we would like to develop a simulation in the spatial aspect to maximize the diversity and realism of the situation. This implementation requires the modeling of virtual space as well as the knowledge and intelligent thinking functions of virtual humans. First, information structures are needed to simulate the hierarchical and multifaceted composition of space and the corresponding knowledge of virtual humans. Specifically, four structures for 2.5D spatial distribution expression, complex spatial relationship expression, object expression, and temporal and spatial representation of events are developed respectively. It then uses these expressed knowledge to develop the spatial thinking function of virtual humans needed to make spatial movement. In general, events have a chain effect on adjacent or connected objects through force, resulting in a variety of situations and reflected in the planning of the next action by the virtual humans involved. For this purpose, the development of events according to historical trends is recorded on the representation structure of time and space. It embodies typical events to demonstrate the feasibility of independent behavior in complex spaces among virtual people.

• The KIPS Transactions:PartD
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• v.15D no.4
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• pp.451-462
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• 2008

Recently, with the advent of applications using locations of moving objects, it becomes crucial to develop efficient index schemes for spatio-temporal databases. The $TPR^*$-tree is most popularly accepted as an index structure for processing future-time queries. In the $TPR^*$-tree, the future locations of moving objects are predicted based on the CBR(Conservative Bounding Rectangle). Since the areas predicted from CBRs tend to grow rapidly over time, CBRs thus enlarged lead to serious performance degradation in query processing. Against the problem, we propose a new method to adjust CBRs to be tight, thereby improving the performance of query processing. Our method examines whether the adjustment of a CBR is necessary when accessing a leaf node for processing a user query. Thus, it does not incur extra disk I/Os in this examination. Also, in order to make a correct decision, we devise a cost model that considers both the I/O overhead for the CBR adjustment and the performance gain in the future-time owing to the CBR adjustment. With the cost model, we can prevent unusual expansions of BRs even when updates on nodes are infrequent and also avoid unnecessary execution of the CBR adjustment. For performance evaluation, we conducted a variety of experiments. The results show that our method improves the performance of the original $TPR^*$-tree significantly.

• Journal of Korea Water Resources Association
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• v.50 no.1
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• pp.17-28
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• 2017

A recent increase in extreme weather events and flash floods associated with the enhanced climate variability results in an increase in climate-related disasters. For these reasons, various studies based on a high resolution weather radar system have been carried out. The weather radar can provide estimates of precipitation in real-time over a wide area, while ground-based rain gauges only provides a point estimate in space. Weather radar is thus capable of identifying changes in rainfall structure as it moves through an ungauged basin. However, the advantage of the weather radar rainfall estimates has been limited by a variety of sources of uncertainty in the radar reflectivity process, including systematic and random errors. In this study, we developed an ensemble radar rainfall estimation scheme using the multivariate copula method. The results presented in this study confirmed that the proposed ensemble technique can effectively reproduce the rainfall statistics such as mean, variance and skewness (more importantly the extremes) as well as the spatio-temporal structure of rainfall fields.