• 제어로봇시스템학회:학술대회논문집
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• 2003.10a
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• pp.798-802
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• 2003

The robustness and reliability of vision algorithms is the key issue in robotic research and industrial applications. In this paper, the robust real time visual tracking in complex scene is considered. A common approach to increase robustness of a tracking system is to use different models (CAD model etc.) known a priori. Also fusion of multiple features facilitates robust detection and tracking of objects in scenes of realistic complexity. Because voting is a very simple or no model is needed for fusion, voting-based fusion of cues is applied. The approach for this algorithm is tested in a 3D Cartesian robot which tracks a toy vehicle moving along 3D rail, and the Kalman filter is used to estimate the motion parameters, namely the system state vector of moving object with unknown dynamics. Experimental results show that fusion of cues and motion estimation in a tracking system has a robust performance.

• Journal of Information Processing Systems
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• v.11 no.4
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• pp.630-642
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• 2015

In Jøsang's subjective logic, the fusion operator is not able to fuse three or more opinions at a time and it cannot consider the effect of time factors on fusion. Also, the base rate (a) and non-informative prior weight (C) could not change dynamically. In this paper, we propose an Improved Subjective Logic Model with Evidence Driven (ISLM-ED) that expands and enriches the subjective logic theory. It includes the multi-agent unified fusion operator and the dynamic function for the base rate (a) and the non-informative prior weight (C) through the changes in evidence. The multi-agent unified fusion operator not only meets the commutative and associative law but is also consistent with the researchers's cognitive rules. A strict mathematical proof was given by this paper. Finally, through the simulation experiments, the results show that the ISLM-ED is more reasonable and effective and that it can be better adapted to the changing environment.

• The KIPS Transactions:PartB
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• v.13B no.1 s.104
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• pp.35-46
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• 2006

The dynamic change of background and moving objects is an important factor which causes the problem of occlusion in tracking moving objects. The tracking accuracy is also remarkably decreased in the presence of occlusion. We therefore propose an active fusion model which is robust against partial occlusions that are occurred by background and other objects. The active fusion model is consisted of contour-based md region-based snake. The former is a conventional snake model using contour features of a moving object and the latter is a regional snake model which considers region features inside its boundary. First, this model classifies total occlusion into contour and region occlusion. And then it adjusts the confidence of each model based on calculating the location and amount of occlusion, so it can overcome the problem of occlusion. Experimental results show that the proposed method can successfully track a moving object but the previous methods fail to track it under partial occlusion.

• Journal of the Korean Society for Precision Engineering
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• v.24 no.8 s.197
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• pp.122-129
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• 2007

To evaluate the effect of artificial disc implantation and fusion on the biomechanics of adjacent motion segment, a nonlinear three-dimensional finite element model of whole lumbar spine (L1-S1) was developed. Biomechanical analysis was performed for two different types of artificial disc, ProDisc and SB $Charit{\acute{e}}$ III model, inserted at L4-L5 level and these results were also compared with fusion case. Angular motion of vertebral body, forces on the spinal ligaments and facet joint under sagittal plane loading with a compressive preload of 150 N at a nonlinear three-dimensional finite element model of Ll-S1 were compared. The implant did not significantly alter the kinematics of the motion segment adjacent to the instrumented level. However, $Charit{\acute{e}}$ III model tend to decrease its motion on the adjacent levels, especially in extension motion. Contrast to motion and ligament force changes, facet contact forces were increased in the adjacent levels as well as implanted level for constrained instantaneous center of rotation model, i.e. ProDisc model.

• Journal of Korean Neurosurgical Society
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• v.52 no.4
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• pp.281-287
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• 2012

Objective : To evaluate the effect of calcium supplementation on spinal bone fusion in ovariectomized (OVX) rats. Methods : Sixteen female Sprague Dawley rats underwent bilateral ovariectomy at 12 weeks of age to induce osteoporosis and were randomly assigned to two groups : control group (n=8) and calcium-supplemented group (OVX-Ca, n=8). Autologous spinal bone fusion surgery was performed on both groups 8 weeks later. After fusion surgery, the OVX-Ca group was supplemented with calcium in drinking water for 8 weeks. Blood was obtained 4 and 8 weeks after fusion surgery. Eight weeks after fusion surgery, the rats were euthanized and the L4-5 spine removed. Bone fusion status and fusion volume were evaluated by manual palpation and three-dimensional computed tomography. Results : The mean fusion volume in the L4-5 spine was significantly greater in the OVX-Ca group ($71.80{\pm}8.06mm^3$) than in controls ($35.34{\pm}8.24mm^3$) (p<0.01). The level of osteocalcin, a bone formation marker, was higher in OVX-Ca rats than in controls 4 weeks ($610.08{\pm}10.41$ vs. $551.61{\pm}12.34$ ng/mL) and 8 weeks ($552.05{\pm}19.67$ vs. $502.98{\pm}22.76$ ng/mL) after fusion surgery (p<0.05). The level of C-terminal telopeptide fragment of type I collagen, a bone resorption marker, was significantly lower in OVX-Ca rats than in controls 4 weeks ($77.07{\pm}12.57$ vs. $101.75{\pm}7.20$ ng/mL) and 8 weeks ($69.58{\pm}2.45$ vs. $77.15{\pm}4.10$ ng/mL) after fusion surgery (p<0.05). A mechanical strength test showed that the L4-5 vertebrae in the OVX-Ca group withstood a 50% higher maximal load compared with the controls (p<0.01). Conclusion : Dietary calcium given to OVX rats after lumbar fusion surgery improved fusion volume and mechanical strength in an ovariectomized rat model.

• Journal of Information Processing Systems
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• v.12 no.4
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• pp.724-740
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• 2016

The performance issues of screening large database compounds and multiple query compounds in virtual screening highlight a common concern in Chemoinformatics applications. This study investigates these problems by choosing group fusion as a pilot model and presents efficient parallel solutions in parallel platforms, specifically, the multi-core architecture of CPU and many-core architecture of graphical processing unit (GPU). A study of sequential group fusion and a proposed design of parallel CUDA group fusion are presented in this paper. The design involves solving two important stages of group fusion, namely, similarity search and fusion (MAX rule), while addressing embarrassingly parallel and parallel reduction models. The sequential, optimized sequential and parallel OpenMP of group fusion were implemented and evaluated. The outcome of the analysis from these three different design approaches influenced the design of parallel CUDA version in order to optimize and achieve high computation intensity. The proposed parallel CUDA performed better than sequential and parallel OpenMP in terms of both execution time and speedup. The parallel CUDA was 5-10x faster than sequential and parallel OpenMP as both similarity search and fusion MAX stages had been CUDA-optimized.

• KIPS Transactions on Computer and Communication Systems
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• v.2 no.1
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• pp.1-6
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• 2013

Variety of smart devices including smart phone have become and essential item in user's daily life. This means that smart devices are good mediators to get collecting user's behavior by sensors mounted on the devices. The information from smart devices is important clues to identify by analyzing the user's preferences and needs. Through this, the intelligent service which is fitted to the user is possible. This paper propose a smart service recommendation model based on user scenario using fusion context-awareness. The information for recommendation services is collected to make the scenario depending on time, location, action based on the Fusion process. The scenarios can help predict a user's situation and provide the services in advance. Also, content categories as well as the content types are determined depending on the scenario. The scenario is a method for providing the best service as well as a basis for the user's situation. Using this method, proposing a smart service model with the fusion context-awareness based on the hybrid sensing is the goal of this paper.

• Korean Institute of Interior Design Journal
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• v.13 no.2
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• pp.10-19
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• 2004

In order to attain unique aesthetic value, diversity of meanings of Fusion Design, 'openness', requires meaning interpreting process(communication) which harmonizes and combines new codes suggested by authors(senders) and codes interpreted by public(receivers). For this harmony, we should consider all the art aspects(integration of synchronic and diachronic, anti-rationalism ideology, negative concept) that are bases of creativity of Fusion Aesthetics. Moreover, we can approach open thought system of Fusion Design through theories of Entropy and Rhizome. This point of view which allowed a categorical means of natural science theory to be used in design context changed a methodic or interpretative perception. Not only in art interpreting process does Fusion Design take openness as one of its necessary factors but also in creating process, which enables a work of art to be opened at the maximum. In conclusion, the significance of fusion design is to suggest an ideal model of communication abstracted from open art works.

• Journal of Korean Institute of Industrial Engineers
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• v.28 no.2
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• pp.171-177
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• 2002

In this paper, we propose a new data fusion method to improve the performance of individual prediction models for time series data. Individual models used are ARIMA and neural network and their results are combined based on the weight reflecting the inverse of EWMA of squared prediction error of each individual model. Monte Carlo simulation is used to identify the situation where the proposed approach can take a vintage point over typical fusion methods which utilize MSE for weight. Study results indicate the following: EWMA performs better than MSE fusion when the data size is large with a relatively big amplitude, which is often observed in intra-cranial pressure data. Additionally, EWMA turns out to be a best choice among MSE fusion and the two individual prediction models when the data size is large with relatively small random noises, often appearing in tax revenue data.

• Proceedings of the Korean Statistical Society Conference
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• 2003.05a
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• pp.237-242
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• 2003

Various kinds of estimation methods have been developed for imputation of categorical missing data. They include modal category method, logistic regression, and association rule. In this study, we propose two imputation methods (neural network fusion and voting fusion) that combine the results of individual imputation methods. A Monte-Carlo simulation is used to compare the performance of these methods. Five factors used to simulate the missing data are (1) true model for the data, (2) data size, (3) noise size (4) percentage of missing data, and (5) missing pattern. Overall, neural network fusion performed the best while voting fusion is better than the individual imputation methods, although it was inferior to the neural network fusion. Result of an additional real data analysis confirms the simulation result.