• Proceedings of the IEEK Conference
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• 2000.06b
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• pp.137-140
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• 2000

In this paper, we have proposed an efficient test generation method for asynchronous circuits. The test generation is based on specification level, especially on Signal Transition Graph(STG)〔1〕 which is a kind of specification method for asynchronous circuits. To conduct a high-level test generation, we have defined a high-level fault model, called single State Transition Fault(STF) model on STG and proposed a test generation algorithm for STF model. The effectiveness of the proposed fault model and its test generation algorithm is shown by experimental results on a set of benchmarks given in the form of STG. Experimental results show that the generated test for the proposed fault model achieves high fault coverage over single input stuck-at fault model with low cost. We have also proposed extended STF model with additional gate-level information to achieve higher fault coverage in cost of longer execution time.

• Korean Journal of Computational Design and Engineering
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• v.12 no.2
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• pp.87-94
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• 2007

The functional behavior of a consumer electronic product is nearly all expressed with human-machine interaction (HMI) tasks. Although physical prototyping and computer aided design (CAD) software can show the appearance of the product, they cannot properly reflect its functional behavior. In this paper, we propose an approach to virtual prototyping (VP) that incorporates HMI functional simulation into virtual reality techniques in order to enables users to capture not only the realistic look of a consumer electronic product but also its functional behavior. We adopt state transition methodology to capture the HMI functional behavior of the product into a state transition chart, which is later used to construct a finite state machine (FSM) for the functional simulation of the product. The FSM plays an important role to control the transition between states of the product. We have developed a VP system based on the proposed approach. The system receives input events such as mouse clicks on buttons and switches of the virtual prototype model, and it reacts to the events based on the FSM by activating associated activities. The system provides the realistic visualization of the product and the vivid simulation of its functional behavior using head-mounted displays (HMD) and stereo speakers. It can easily allow users to perform functional evaluation and usability testing. A case study about the virtual prototyping of an MP3 player is given to show the usefulness of the proposed approach.

• ETRI Journal
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• v.38 no.4
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• pp.714-723
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• 2016

Considerable attention has been given to processing graph data in recent years. An efficient method for computing the node proximity is one of the most challenging problems for many applications such as recommendation systems and social networks. Regarding large-scale, mutable datasets and user queries, top-k query processing has gained significant interest. This paper presents a novel method to find top-k answers in a node proximity search based on the well-known measure, Personalized PageRank (PPR). First, we introduce a distribution state transition graph (DSTG) to depict iterative steps for solving the PPR equation. Second, we propose a weight distribution model of a DSTG to capture the states of intermediate PPR scores and their distribution. Using a DSTG, we can selectively follow and compare multiple random paths with different lengths to find the most promising nodes. Moreover, we prove that the results of our method are equivalent to the PPR results. Comparative performance studies using two real datasets clearly show that our method is practical and accurate.

• Bulletin of the Korean Chemical Society
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• v.26 no.12
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• pp.1953-1961
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• 2005

We have performed high-level quantum mechanical calculation for multiple proton transfer in HOCl + HCl and $H_2O$ + $ClONO_2$ on water clusters, which can be used as a model of the reactions on ice surface in stratospheric clouds. Multiple proton transfer on ice surface plays crucial role in these reactions. The structures of the clusters with 0-3 water molecules and the transition state structures for the multiple proton transfer have been calculated. The energies and barrier heights of the proton transfer were calculated at various levels of theory including multi-coefficient correlated quantum mechanical methods (MCCM) that have recently been developed. The transition state structures and the predicted reaction mechanism depend very much on the level of theory. In particular, the HF level can not correctly predict the TS structure and barrier heights, so the electron correlation should be considered appropriately.

• Food Science and Biotechnology
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• v.14 no.2
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• pp.301-303
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• 2005

State diagram of highly concentrated branched oligosaccharides (HBOS) was constructed to better understand phase behavior of mixtures with different size of oligosaccharides. It showed dramatic plasticizing effect on glass transition, which was successfully described based on Couchman-Karasz equation model. $T_g$' estimated from state diagram corresponded well with previous empirical data measured by maximum ice formation through isothermal holding (annealing) process. Estimated $T_g$' and $C_g$' values were $-36.3^{\circ}C$ and 79.99%, respectively. $T_g$' value of HBOS was approximately $10^{\circ}C$ higher than that of sucrose, while $C_g$' value was similar to those of general carbohydrate materials, which could be useful for applications in frozen system.

• Journal of Korea Multimedia Society
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• v.13 no.12
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• pp.1820-1831
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• 2010

When interacting with unknown environments, an autonomous agent needs to decide which action or action order can result in a good state and determine the transition probability based on the current state and the action taken. The traditional multiple sequential learning model requires predefined probability of the states' transition. This paper proposes a multiple sequential learning and prediction system with definition of autonomous states to enhance the automatic performance of existing AI algorithms. In sequence learning process, the sensed states are classified into several group by a set of proposed motivation filters to reduce the learning computation. In prediction process, the learning agent makes a decision based on the estimation of each state's cost to get a high payoff from the given environment. The proposed learning and prediction algorithms heightens the automatic planning of the autonomous agent for interacting with the dynamic unknown environment. This model was tested in a virtual library.

• The Korean Journal of Applied Statistics
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• v.29 no.7
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• pp.1311-1327
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• 2016

We propose a multi-state model for analyzing semi-competing risks data with interval-censored or missing intermediate events. This model is an extension of the 'illness-death model', which composes three states, such as 'healthy', 'diseased', and 'dead'. The state of 'diseased' can be considered as an intermediate event. Two more states are added into the illness-death model to describe missing events caused by a loss of follow-up before the end of the study. One of them is a state of 'LTF', representing a lost-to-follow-up, and the other is an unobservable state that represents the intermediate event experienced after LTF occurred. Given covariates, we employ the Cox proportional hazards model with a normal frailty and construct a full likelihood to estimate transition intensities between states in the multi-state model. Marginalization of the full likelihood is completed using the adaptive Gaussian quadrature, and the optimal solution of the regression parameters is achieved through the iterative Newton-Raphson algorithm. Simulation studies are carried out to investigate the finite-sample performance of the proposed estimation procedure in terms of the empirical coverage probability of the true regression parameter. Our proposed method is also illustrated with the dataset adapted from Helmer et al. (2001).

• Korean Journal of Computational Design and Engineering
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• v.13 no.3
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• pp.209-216
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• 2008

This paper presents a novel approach to design evaluation of portable consumer electronic (PCE) products using augmented reality (AR) based tangible interaction and functional behavior simulation. In the approach, the realistic visualization is acquired by overlaying the rendered image of a PCE product on the real world environment in real-time using computer vision based augmented reality. For tangible user interaction in an AR environment, the user creates input events by touching specified regions of the product-type tangible object with the pointer-type tangible object. For functional behavior simulation, we adopt state transition methodology to capture the functional behavior of the product into a markup language-based information model, and build a finite state machine (FSM) to controls the transition between states of the product based on the information model. The FSM is combined with AR-based tangible objects whose operation in the AR environment facilitates the realistic visualization and functional simulation of the product, and thus realizes faster product design and development. Based on the proposed approach, a product design evaluation system has been developed and applied for the design evaluation of various PCE products with highly encouraging feedbacks from users.

• Computers and Concrete
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• v.34 no.2
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• pp.231-245
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• 2024

A 3D discrete element model integrating the rough surface contact concept with the flat-joint model is suggested to examine the mechanical characteristics of the interfacial transition zone (ITZ) in concrete. The essential components of our DEM procedure include the calculation of the actual contact area in an element contact-pair related to the bonded factor using a Gaussian probability distribution of asperity height, as well as the determination of the contact probability-relative displacement form using the least square method for further computing the force-displacement of ITZs. The present formulations are implemented in MUSEN, an open source development environment for discrete element analysis that is optimized for high performance computation. The model's meso-parameters are calibrated by using uniaxial compression and splitting tensile simulations, as well as laboratory tests of concrete from the literature. The present model's DEM predictions accord well with laboratory experimental tests of pull-out concrete specimens published in the literature.

• Journal of IKEEE
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• v.13 no.2
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• pp.159-166
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• 2009

So far, many researches have been done to retrieve music information using static classification descriptors such as genre and mood. Since static classification descriptors are based on diverse content-based musical features, they are effective in retrieving similar music in terms of such features. However, human emotion or mood transition triggered by music enables more effective and sophisticated query in music retrieval. So far, few works have been done to evaluate the effect of human mood transition by music. Using formal representation of such mood transitions, we can provide personalized service more effectively in the new applications such as music recommendation. In this paper, we first propose our Emotion State Transition Model (ESTM) for describing human mood transition by music and then describe a music classification and recommendation scheme based on the ESTM. In the experiment, diverse content-based features were extracted from music clips, dimensionally reduced by NMF (Non-negative Matrix Factorization, and classified by SVM (Support Vector Machine). In the performance analysis, we achieved average accuracy 67.54% and maximum accuracy 87.78%.