• The Journal of the Korea institute of electronic communication sciences
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• v.8 no.3
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• pp.409-414
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• 2013

With the increase of multimedia information such as images, researches have been realized on how to extract the high-level semantic information from low-level visual information, and a variety of techniques have been proposed to generate this information automatically. However, most of these technologies extract the semantic information between single images, it's difficult to extract semantic information when a combination of multiple objects within the image. In this paper, we extract the visual features of objects within the image and training images stored in the DB and the features of each object are defined by measuring the similarity. Using ontology reasoner, each object feature within images infers the semantic information by positional relation and associative relation. With this, it's possible to infer semantic information between objects within images, we proposed a method for inferring more complicated and a variety of high-level semantic information.

• Journal of Digital Convergence
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• v.13 no.11
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• pp.441-448
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• 2015

The purpose of the study was to perform a comparative analysis of the success and failure cases to increase the completeness of vault "Shirai-Kim Hee Hoon" technique. The subject of the study was "K" a male gymnast from Korean Artistic Gymnastic National team. The results obtained through the three-dimensional analysis during international as well as practice session are as follows: Firstly, excluding BC, the lead time in each PrF, HC and PoF phases were shorter during successful trials than in failure trials. Secondly, during successful trials, the horizontal and vertical velocity appeared to be higher during taking off, which contributed positively to the leaping motion in the horizontal direction. Thirdly, when compared with successful and failure trials, the body's angular rotation was highly maintained during the takeoff from the spring board followed by larger thigh angular displacement at the vault before actually attempting the backward rotation.

• The Journal of Korea CHUNA Manual Medicine
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• v.4 no.1
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• pp.119-127
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• 2003

Objective : We found out improvement at low back pain and lumber strength by isotonic lumbar extension training on lumbar strength and self low back exercise stretching program. Methods : We evaluated the symptom's changes VAS(Visual Analogue Scale) and lumbar strength by Medx which could estimate and exercise lumbar muscle. Conclusions: We can decrease low back pain by strengthening lumbar muscle, in additionally when patients are In admission state we may improve lumbar muscle more than Opd. state.

• Journal of the Korean Institute of Intelligent Systems
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• v.25 no.3
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• pp.287-292
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• 2015

The aim of this study was to provide a method to assume the value of the continuous and possible management part to investigate the relationship between component of evaluation of Disaster Management and Sustainability Management in enterprise by obtaining Fuzzy Relation Matrix in view of necessity and possibility when there are new data. The index of Disaster Management was yielded from 100 small and medium-sized enterprises for 4 component of evaluations of based on ISO standard, and that of Sustainability Management was obtained from same enterprises for 6 component of evaluations in GRI G4 version of Sustainability Management guideline. The above results suggest that this model is significant by using 80 data as a training data and 20 data as a checking data from the 100 data obtained in this study.

• Journal of Advanced Navigation Technology
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• v.18 no.2
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• pp.151-157
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• 2014

Recently UAV(unmanned aerial vehicle) is frequently used not only for military purpose but also for civil purpose. UAV automatically navigates following the coordinates input in advance using GPS information. However it is impossible when GPS cannot be received because of jamming or external interference. In order to solve this problem, we propose a real-time segmentation and classification algorithm for the specific regions from UAV image in this paper. We use the super-pixels algorithm using graph-based image segmentation as a pre-processing stage for the feature extraction. We choose the most ideal model by analyzing various color models and mixture color models. Also, we use support vector machine for classification, which is one of the machine learning algorithms and can use small quantity of training data. 18 color and texture feature vectors are extracted from the UAV image, then 3 classes of regions; river, vinyl house, rice filed are classified in real-time through training and prediction processes.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.10 no.10
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• pp.2837-2845
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• 2009

This study certified that the mentality training that utilized ICT learning has been working as an important base having much effect on learner's basic attitude on physical education class, improvement of bodily exercise function, and class satisfaction, and that the exercise ability was improved in the scope of speed, form(posture), accuracy(shooting success rate), and adaptability(performance ability). It means it is a much more step-forwarded educational method that the advantages of ICT learning and mentality training at the existing learning method were applied to the reality. Regarding the object of this study, it is a little bit unreasonable to generalize its study results in that it wasn't intended for national unit sampling. Therefore, in the future study, it is necessary to continue to advance the study that its representative-ness was supplemented through the balanced sampling between area and area, and between grade and grade.

• Korean Journal of Applied Biomechanics
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• v.18 no.4
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• pp.191-199
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• 2008

The purpose of this study was to analyze movement of inline skate players at inline roller skate T300m start so that we can find effective starting movement, and provide basic and scientific materials in improving performance of inline roller skaters for T300m inline roller skating. In doing so, five Korean national representative inline skaters who elected in 2008 Korean National Inline Roller Skating Cup were taped during the cup and analyzed through 3D viewing in terms of their starting movement Conclusions of the analysis were as follows: First, the better the record of starting phase is the shorter average of contact time on track. Second, to improve starting speed, players raised their body just like running instead of lowering them when gliding. players could shorten their strike and moved faster in order to accelerate, and it was more effective to speed up when they quickly switched from running to gliding. Third, the five country-representative players speeded up by bending their knees to a greater degree in order to improve stability. And then the most effective way was believed to minimize track connection of skating at starting in each phase.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.40 no.1
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• pp.72-78
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• 2003

A new self-organizing neuro-fuzzy network based rate control algorithm for MPEG-4 video encoder is proposed in this paper. Contrary to the traditional methods that construct the rate-distorion (RD) model based on experimental equations, the proposed method effectively exploits the non-stationary property of the video date with neuro-fuzzy network that self-organizes the RD model online and adaptively updates the structure. The method needs not require off-line pre-training; hence it is geared toward real-time coding. The comparative results through the experiments suggest that our proposed rate control scheme encodes the video sequences with less frame skip, providing good temporal quality and higher PSNR, compared to VM18.0.

• Journal of the Korea Society of Computer and Information
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• v.19 no.1
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• pp.111-118
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• 2014

Current friend recommendation system on Twitter primarily recommends the most influential twitter. However, this way of recommendation has drawbacks where it does not recommend the users of which attributes of interests are similar to theirs. Since users want other users of which attributes are similar, this study implements follower recommendation system based on the similarity of twitter node informations. The data in this study is from SNAP(Stanford Network Analysis Platform), and it consists of twitter node information of which number of followers is over 10,000 and twitter link information. We used the SNAP data as a training data, and generated a classifier which recommends and predicts the relation between followers. We evaluated the classifier by 10-Fold Cross validation. Once two twitter node informations are given, our model can recommend the relationship of the two twitters as one of following such as: FoFo(Follower Follower), FoFr(Follower Friend), NC(Not Connected).

• Journal of the Korea Society of Computer and Information
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• v.25 no.11
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• pp.89-95
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• 2020

In this paper, we present Beamforming (BF) Training (BFT) for asymmetric links in IEEE 802.11ay. IEEE 802.11ay introduced BFT for asymmetric links that aims to increase the BFT success probability for Station (STA) with insufficient link budget to communicate with an Access Point (AP). BFT for asymmetric links utilizes directional BFT allocation to avoid the usage of quasi-omni pattern at the AP side, and thus to increase STA's BFT success rate. However, there are no publicly available simulation tools supporting IEEE 802.11ay. For these reasons, we present in this paper an implementation of BFT for asymmetric links in ns-3 with its novel techniques such as Training RX (TRN-R) subfield and BFT allocation. We then evaluate by simulation the performance of BFT for asymmetric links.