• Journal of Korea Multimedia Society
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• v.19 no.6
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• pp.1074-1088
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• 2016

Successful Visual Story Telling(VST) of desire is a crucial key for the success of animation because desire is the leading power of story development of animation. An analysis of the desire of VST using the top 5 successful American feature film animations is carried out. Totally, 147 desire shots are extracted by using the proposed Objective Selection of Desire Shots(OSDS) method based on the theory of Makee's conflict and desire pursuing modeling, Maslow's 20 desire types, Greimas's actant model, and the 17 narrative process classification. In addition to them, the 5 Beat(5B) model of a scene is proposed. Five image specialists have evaluated VST of the selected 147 desire shots. For each shot, the desire type among the 20 desires and the strength are obtained. Among them, the top 3 desires(affiliation, achievement, and nurturance) appearing 51.8% are analyzed. The composition elements of shots affecting the desire type and the strength have found. These can be used for better VST of preproduction and production of animation.

• Structural Monitoring and Maintenance
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• v.5 no.2
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• pp.231-242
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• 2018

Subway tunnel structure has been rapidly developed in many cities for its strong transport capacity. The model-based damage detection of subway tunnel structure is usually difficult due to the complex modeling of soil-structure interaction, the indetermination of boundary and so on. This paper proposes a new data-based method for the damage detection of subway tunnel structure. The root mean square acceleration and cross correlation function are used to derive a statistical pattern recognition algorithm for damage detection. A damage sensitive feature is proposed based on the root mean square deviations of the cross correlation functions. X-bar control charts are utilized to monitor the variation of the damage sensitive features before and after damage. The proposed algorithm is validated by the experiment of a full-scale two-rings subway tunnel lining, and damages are simulated by loosening the connection bolts of the rings. The results verify that root mean square deviation is sensitive to bolt loosening in the tunnel lining and X-bar control charts are feasible to be used in damage detection. The proposed data-based damage detection method is applicable to the online structural health monitoring system of subway tunnel lining.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.9 no.4
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• pp.892-898
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• 2008

3D rapid prototyping is the manufacturing technology to fabricate a prototype with the data stored in a computer, which differs from conventional casting technology in terms of an additive process. Various 3D rapid prototyping techniques such as stereolithograpy. fused deposition modeling. selective laser sintering, laminated object manufacturing have been developed but among them, 3D inkjet printing has a unique feature that materials could be jetted to directly form the body of a prototype, which could be a finished product functionally and structurally. However, this needs ink with a high solid content, which tends to increase the dynamic viscosity of ink. The increase of ink viscositytends to restrict the jettable range of ink and hence the jetting conditions should be optimized. The intrinsic speed of sound in a hot melt ink with ceramic nanoparticles dispersed is one of key components to determine the jettable range of ink. In this paper, the way to measure the intrinsic speed of sound in a hot melt ceramic ink is proposed and its influence on the jetting condition is discussed.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 1999.05a
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• pp.230-234
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• 1999

Inheritance and concurrency are the primary feature of object oriented languages, and are especially important for code re-use. They provide maximum computational power and modeling power through concurrency of objects. But, concurrent objects and inheritance have conflicting characteristics, thereby simultaneously use of them causes the problem, so failed inheritance anomaly, which requires code redefinition of inherited methods to maintain integrity of objects. In this paper, to solve the inheritance anomaly problems we introduce concept of state abstraction, in which infernal states of encapsulated objects are made available from a part of object's external interface. And we design inheritance interface mechanisms which methods are inherited efficiently. In our scheme, we can solve the typical inheritance anomaly problems.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.31 no.5A
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• pp.441-450
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• 2006

Recently, with the exponential growth of the number of Internet users, IP traffic which occupies more than 90 percent of the entire Internet traffic affects significantly to the performance of networks. Therefore, the design of the self-similar traffic generator reflected the feature of IP traffic is very important to design the networks efficiently and evaluate the performance of it correctly. In this paper, we design the self-similar traffic generator using OPNET. In order to implement the self-similar characteristics, ON-OFF sources with Pateto distribution are employed and aggregated. The designed self-similarity traffic generator is evaluated and verified with R/S plot, variance time(VT) plot under the various offered loads and the number of sources. It is expected that the designed self-similar traffic generator can be put to practical use when wire or wireless networks is designed and verified as well as it can be useful to decide the specific parameter value for Internet traffic modeling.

• Journal of Agricultural Extension & Community Development
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• v.24 no.4
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• pp.249-264
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• 2017

Modeling the consumer demand of fresh meat requires its distinct feature which other types of food product does not have. Most of the fresh meat products are likely to be unbranded, bought on a weight basis and affected by macro shocks such as seasonality, holiday effect and the disease incidence. Furthermore, consumers tend to purchase multiple categories of fresh meat in a week. Therefore, we apply a multiple discrete/continuous model on fresh meat consumption data to study the effect of macro shocks on fresh meat sales as well as of price change. As a result shows, Each fresh meat is relatively more likely to be bought in peak season of each fresh meat compared with imported pork which is set as a 'reference category' in this analysis. For clarity of the effect of disease incidence, we perform further analysis regarding the effect of livestock disease on fresh meat purchase probability. It shows that the avian flu in 2014 has strong negative impact on the purchase probability of chicken and the foot-and-mouth disease has negative impact on the purchase probability of pork and beef for part of outbreak periods.

• Journal of the Korea Concrete Institute
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• v.14 no.6
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• pp.1022-1031
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• 2002

This paper presents efficient models for bridge structures using CART-ANFIS (classification and regression tree-adaptive neuro fuzzy inference system). A fuzzy decision tree partitions the input space of a data set into mutually exclusive regions, each region is assigned a label, a value, or an action to characterize its data points. Fuzzy decision trees used for classification problems are often called fuzzy classification trees, and each terminal node contains a label that indicates the predicted class of a given feature vector. In the same vein, decision trees used for regression problems are often called fuzzy regression trees, and the terminal node labels may be constants or equations that specify the predicted output value of a given input vector. Note that CART can select relevant inputs and do tree partitioning of the input space, while ANFIS refines the regression and makes it continuous and smooth everywhere. Thus it can be seen that CART and ANFIS are complementary and their combination constitutes a solid approach to fuzzy modeling.

• Journal of the Korea Computer Graphics Society
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• v.8 no.1
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• pp.37-45
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• 2002

We present a cloth simulation technique that is very stable yet also responsive. The stability of the technique allows the use of a large fixed time step when simulating various types of fabrics and character motions. The animations generated using this technique are strikingly realistic. Wrinkles form and disappear in a quite natural way, which is the feature that most distinguishes textile fabrics from other sheet materials. Significant improvements in both the stability and realism were made possible by overcoming the post-buckling instability as well as the numerical instability. The instability caused by buckling arises from a structural instability and therefore cannot be avoided by simply employing an implicit method. Addition of a damping force may help to avoid instabilities; however, it can significantly degrade the realism of the cloth motion. In this paper, a new buckling model based on immediate buckling assumption is proposed. A cloth element is assumed to reach a stable configuration immediately once it begins to buckle. This assumption makes it possible to simulate the fabric buckling stably without introducing any fictitious damping force. Consequently, it produces highly responsive cloth motion as well as improves the stability by modeling the fabric-specific buckling property adequately.

• International Journal of Control, Automation, and Systems
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• v.1 no.2
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• pp.194-202
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• 2003

In this paper, we introduce a category of Multi-FNN (Fuzzy-Neural Networks) models, analyze the underlying architectures and propose a comprehensive identification framework. The proposed Multi-FNNs dwell on a concept of fuzzy rule-based FNNs based on HCM clustering and evolutionary fuzzy granulation, and exploit linear inference being treated as a generic inference mechanism. By this nature, this FNN model is geared toward capturing relationships between information granules known as fuzzy sets. The form of the information granules themselves (in particular their distribution and a type of membership function) becomes an important design feature of the FNN model contributing to its structural as well as parametric optimization. The identification environment uses clustering techniques (Hard C - Means, HCM) and exploits genetic optimization as a vehicle of global optimization. The global optimization is augmented by more refined gradient-based learning mechanisms such as standard back-propagation. The HCM algorithm, whose role is to carry out preprocessing of the process data for system modeling, is utilized to determine the structure of Multi-FNNs. The detailed parameters of the Multi-FNN (such as apexes of membership functions, learning rates and momentum coefficients) are adjusted using genetic algorithms. An aggregate performance index with a weighting factor is proposed in order to achieve a sound balance between approximation and generalization (predictive) abilities of the model. To evaluate the performance of the proposed model, two numeric data sets are experimented with. One is the numerical data coming from a description of a certain nonlinear function and the other is NOx emission process data from a gas turbine power plant.

• Journal of Institute of Control, Robotics and Systems
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• v.20 no.9
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• pp.900-907
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• 2014

This paper proposes a MPC (Model Predictive Control) method for the torque and flux controls of induction motor. The proposed MPC method selects the optimized voltage vector for the matrix converter control using the predictive modeling equation of the induction motor and cost function. Hence, the reference voltage vector that minimizes the cost function of the torque and flux error within the control period is selected and applied to the actual system. As a result, it is possible to perform the torque and flux control of induction motor using only the MPC controller without a PI (Proportional-Integral) or hysteresis controller. Even though the proposed control algorithm is more complicated and has lots of computations compared with the conventional MPC, it can perform torque ripple reduction by synthesizing voltage vectors of various magnitude. This feature provides the reduction of amount of calculations and the improvement of the control performance through the adjustment of the number of the unit vectors n. The proposed control method is validated through the PSIM simulation.