• Journal of the Korea Computer Graphics Society
• /
• v.13 no.3
• /
• pp.11-18
• /
• 2007

Creating stylistic facial animation is one of the most important problems in character animation. Traditionally facial animation is created manually by animators of captured using motion capture systems. But this process is very difficult and labor-intensive. In this work, we present an intuitive, easy-to-use, sketch-based user interface system that facilitates the process of creating facial animation and key-frame interpolation method using facial capture data. The user of our system is allowed to create expressive speech facial animation easily and rapidly.

• Journal of the Korean Institute of Telematics and Electronics
• /
• v.23 no.2
• /
• pp.225-235
• /
• 1986

Dataflow computers exhibit a high degree of parallelism which can not be obtained easily with the conventional von-Neumann architecture. Since many instructions are ready for execution simultaneously, concurrency can easily by achieved by the multiple processors modified the data-flow machine. In paper, we describe an improved dataflow architecture which is designed by adding the demand propagation network to the MIT dataflow machine. and show the improved performance by the execution time and the efficiency of processing elements through simulation with the time acceleration method.

• Structural Monitoring and Maintenance
• /
• v.9 no.2
• /
• pp.179-200
• /
• 2022

This paper proposes a data-driven methodology for online early damage identification under changing environmental conditions. The proposed method relies on two data analysis methods: feature-based method and hybrid principal component analysis (PCA) and kernel PCA to separate damage from environmental influences. First, spectral sub-band features, namely, spectral sub-band centroids (SSCs) and log spectral sub-band energies (LSSEs), are proposed as damage-sensitive features to extract damage information from measured structural responses. Second, hybrid modeling by integrating PCA and kernel PCA is performed on the spectral sub-band feature matrix for data normalization to extract both linear and nonlinear features for nonlinear procedure monitoring. After feature normalization, suppressing environmental effects, the control charts (Hotelling T² and SPE statistics) is implemented to novelty detection and distinguish damage in structures. The hybrid PCA-KPCA technique is compared to KPCA by applying support vector machine (SVM) to evaluate the effectiveness of its performance in detecting damage. The proposed method is verified through numerical and full-scale studies (a Bridge Health Monitoring (BHM) Benchmark Problem and a cable-stayed bridge in China). The results demonstrate that the proposed method can detect the structural damage accurately and reduce false alarms by suppressing the effects and interference of environmental variations.

• Journal of the Korea Society of Computer and Information
• /
• v.29 no.1
• /
• pp.195-209
• /
• 2024

The current road traffic signal controller developed in the 1990s has limitations in flexibility and scalability due to power supply problems, various communication methods, and hierarchical black box structures for various equipment and devices installed to improve traffic safety for road users and autonomous cooperative driving. In this paper, we designed a road traffic safety facilities equipment and devices integrated management system that can cope with the rapidly changing future traffic environment by solving the using direct current(DC) and power supply problem through the power over ethernet(PoE) technology and centralized data-driven control through message broker technology. In addition, a data-driven real-time control method for road traffic safety facilities equipment and devices operating based on time series data was implemented and verified.

• Journal of Korea Water Resources Association
• /
• v.51 no.6
• /
• pp.503-514
• /
• 2018

In recent, the hydrological regime of the Mekong river is changing drastically due to climate change and haphazard watershed development including dam construction. Information of hydrologic feature like streamflow of the Mekong river are required for water disaster prevention and sustainable water resources development in the river sharing countries. In this study, runoff simulations at the Kratie station of the lower Mekong river are performed using SWAT (Soil and Water Assessment Tool), a physics-based hydrologic model, and LSTM (Long Short-Term Memory), a data-driven deep learning algorithm. The SWAT model was set up based on globally-available database (topography: HydroSHED, landuse: GLCF-MODIS, soil: FAO-Soil map, rainfall: APHRODITE, etc) and then simulated daily discharge from 2003 to 2007. The LSTM was built using deep learning open-source library TensorFlow and the deep-layer neural networks of the LSTM were trained based merely on daily water level data of 10 upper stations of the Kratie during two periods: 2000~2002 and 2008~2014. Then, LSTM simulated daily discharge for 2003~2007 as in SWAT model. The simulation results show that Nash-Sutcliffe Efficiency (NSE) of each model were calculated at 0.9(SWAT) and 0.99(LSTM), respectively. In order to simply simulate hydrological time series of ungauged large watersheds, data-driven model like the LSTM method is more applicable than the physics-based hydrological model having complexity due to various database pressure because it is able to memorize the preceding time series sequences and reflect them to prediction.

• Journal of ILASS-Korea
• /
• v.21 no.1
• /
• pp.1-6
• /
• 2016

A gasoline injector rig which can measure cumulative injected fuel mass under a vehicle driving condition was developed. The measurement system consists of an engine control unit (ECU), data acquisition (DAQ) and injected fuel collection system using loadcells. By supplying reconstructed sensor signals which simulate the real vehicle's sensor signals to the ECU, the ECU drives injectors as if they were driven in the vehicle. The vehicle's performance was computer simulated by using $GT-Suite^{(R)}$ software based on both engine part load performance and automatic transmission shift map. Throttle valve position, engine and vehicle speed, air mass flow rate et al. were computer simulated. The used vehicle driving pattern for the simulation was FTP-75 mode. For reconstructing the real vehicle sensor signals which are correspondent to the $GT-Suite^{(R)}$ simulated vehicle's performance, the DAQ systems were used. The injected fuel was collected with mess cylinders. The collected fuel mass in the mess cylinder with elapsed time after starting FTP-75 driving mode was measured using loadcells. The developed method shows highly improved performance in fast timing and accuracy of the cumulative injected fuel mass measurement under the vehicle driven condition.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.13 no.4
• /
• pp.2042-2059
• /
• 2019

Digital shadow puppet has traditionally relied on expensive motion capture equipments and complex design. In this paper, a low-cost driven technique is presented, that captures human pose estimation data with simple camera from real scenarios, and use them to drive virtual Chinese shadow play in a 2.5D scene. We propose a special method for extracting human pose data for driving virtual Chinese shadow play, which is called 2.5D human pose estimation. Firstly, we use the 3D human pose estimation method to obtain the initial data. In the process of the following transformation, we treat the depth feature as an implicit feature, and map body joints to the range of constraints. We call the obtain pose data as 2.5D pose data. However, the 2.5D pose data can not better control the shadow puppet directly, due to the difference in motion pattern and composition structure between real pose and shadow puppet. To this end, the 2.5D pose data transformation is carried out in the implicit pose mapping space based on self-network and the final 2.5D pose expression data is produced for animating shadow puppets. Experimental results have demonstrated the effectiveness of our new method.

• Proceedings of the Korean Geotechical Society Conference
• /
• 2010.03a
• /
• pp.324-337
• /
• 2010

For the development of load and resistance factor design, reliability analysis is required to calibrate resistance factors in the framework of reliability theory. The distribution of measured-to-predicted pile resistance ratio was constructed based on only the results of load tests conducted to failure for the assessment of uncertainty regarding pile resistance and used in the conventional reliability analysis. In other words, successful pile load test (piles resisted twice their design loads without failure) results were discarded, and therefore, were not reflected in the reliability analysis. In this paper, a new systematic method based on Bayesian theory is used to update reliability index of driven steel pile piles by adding more pile load test results, even not conducted to failure, into the prior distribution of pile resistance ratio. Fifty seven static pile load tests performed to failure in Korea were compiled for the construction of prior distribution of pile resistance ratio. Reliability analyses were performed using the updated distribution of pile resistance ratio and the total load distribution using First-order Reliability Method (FORM). The challenge of this study is that the distribution updates of pile resistance ratio are possible using the load test results even not conducted to failure, and that Bayesian update are most effective when limited data are available for reliability analysis or resistance factors calibration.

• Journal of the military operations research society of Korea
• /
• v.31 no.2
• /
• pp.105-115
• /
• 2005

To ensure interoperability among TADILs, we need inter-operational system of tactical data link that allows sharing of specific, planned information among different TADILs. In this paper, we have proposed the design of a conceptual software architecture of inter-operational system. For developing of a conceptual software architecture, we analyze the actual condition of ADSI used in the US military and identify functions and quality-attributes. Based on these factors, we design the conceptual software architecture for inter-operational system of tactical data link using Attribute-Driven Design(ADD) method. ADD is consist of three phases - choose the module to decompose, refine the module, repeat the steps for every module that needs further decomposition. To evaluate of ADD results, we apply the Software Architecture Analysis Method(SAAM) which is consist of making evaluation scenarios, choosing indirect scenarios, evaluation scenarios' interaction, and creating an overall evaluation. Through the evaluation, we verify the conceptual software architecture of inter-operational system.

• Communications for Statistical Applications and Methods
• /
• v.4 no.3
• /
• pp.891-901
• /
• 1997

The objective of this research is to investigate the problem of goodness of fit testing based on nonparametric density estimation with a data-driven smoothing parameter. The small and large smaple properties of the proposed test statistic $Z_{mn}$ are investigated with the minimizer $\widehat{m}$ of the estimated mean integrated squared error by the Diggle and Hall (1986) method.