• Applied Microscopy
• /
• v.49
• /
• pp.1.1-1.10
• /
• 2019

Joints of three-dimensional (3D) rutile-type (r) tin dioxide ($SnO_2$) nanowire networks, produced by the flame transport synthesis (FTS), are formed by coherent twin boundaries at $(101)^r$ serving for the interpenetration of the nanowires. Transmission electron microscopy (TEM) methods, i.e. high resolution and (precession) electron diffraction (PED), were utilized to collect information of the atomic interface structure along the edge-on zone axes $[010]^r$, $[111]^r$ and superposition directions $[001]^r$, $[101]^r$. A model of the twin boundary is generated by a supercell approach, serving as base for simulations of all given real and reciprocal space data as for the elaboration of three-dimensional, i.e. relrod and higher order Laue zones (HOLZ), contributions to the intensity distribution of PED patterns. Confirmed by the comparison of simulated and experimental findings, details of the structural distortion at the twin boundary can be demonstrated.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.13 no.2
• /
• pp.945-961
• /
• 2019

Tongue diagnosis is one of the most important diagnostic methods in Traditional Chinese Medicine (TCM). Tongue image segmentation aims to extract the image object (i.e., tongue body), which plays a key role in the process of manufacturing an automated tongue diagnosis system. It is still challenging, because there exists the personal diversity in tongue appearances such as size, shape, and color. This paper proposes an innovative segmentation method that uses image thresholding, gray projection and active contour model (ACM). Specifically, an initial object region is first extracted by performing image thresholding in HSI (i.e., Hue Saturation Intensity) color space, and subsequent morphological operations. Then, a gray projection technique is used to determine the upper bound of the tongue body root for refining the initial object region. Finally, the contour of the refined object region is smoothed by ACM. Experimental results on a dataset composed of 100 color tongue images showed that the proposed method obtained more accurate segmentation results than other available state-of-the-art methods.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.18 no.1
• /
• pp.64-88
• /
• 2024

Security and reliability are the utmost importance facts in intelligent networked vehicles. Stochastic Petri Net and Z (SPZN) as an excellent formal verification tool for modeling concurrent systems, can effectively handles concurrent operations within a system, establishes relationships among components, and conducts verification and reasoning to ensure the system's safety and reliability in practical applications. However, the application of a system with numerous nodes to Petri Net often leads to the issue of state explosion. To tackle these challenges, a refinement and abstraction method based on SPZN is proposed in this paper. This approach can not only refine and abstract the Stochastic Petri Net but also establish a corresponding relationship with the Z language. In determining the implementation rate of transitions in Stochastic Petri Net, we employ the interval average and weighted average method, which significantly reduces the time and space complexity compared to alternative techniques and is suitable for expert systems at various levels. This reduction facilitates subsequent comprehensive system analysis and module analysis. Furthermore, by analyzing the properties of Markov Chain isomorphism in the case study, recommendations for minimizing system risks in the application of intelligent parking within the intelligent networked vehicle system can be put forward.

• Journal of the Korean Mathematical Society
• /
• v.61 no.5
• /
• pp.875-898
• /
• 2024

This study estimates the true price of an asset and finds the optimal bid/ask prices for market makers. We provide a novel state-space model based on the exponential Ornstein-Uhlenbeck volatility and the Heston models with Gaussian noise, where the traded price and volume are available, but the true price is not observable. An objective of this study is to use Bayesian filtering to estimate the posterior distribution of the true price, given the traded price and volume. Because the posterior density is intractable, we employ the guided particle filtering algorithm, with which adaptive rejection metropolis sampling is used to generate samples from the density function of an unknown distribution. Given a simulated sample path, the posterior expectation of the true price outperforms the traded price in estimating the true price in terms of both the mean absolute error and root-mean-square error metrics. Another objective is to determine the optimal bid/ask prices for a market maker. The profit-and-loss of the market maker is the difference between the true price and its bid/ask prices multiplied by the traded volume or bid/ask size of the market maker. The market maker maximizes the expected utility of the PnL under the posterior distribution. We numerically calculate the optimal bid/ask prices using the Monte Carlo method, finding that its spread widens as the market maker becomes more risk-averse, and the bid/ask size and the level of uncertainty increase.

• Journal of the Korea Society for Simulation
• /
• v.20 no.1
• /
• pp.79-85
• /
• 2011

The problem of evacuating pedestrians from a room or channel under panic conditions is of obvious importance in daily life. In recent years, several computer models have been developed to simulate pedestrian dynamics. Understanding evacuation dynamics can allow for the design of more comfortable and safe pedestrian facilities. However, these models do not take into account the type and state of mind of pedestrians. They deal with pedestrians as particles and the state of mind as a social force, which is represented by conservative and long-range interactions between individuals. In this study, I used the lattice model proposed in my previous study to explore the evacuation behavior of pedestrians with morality. In this model, three types of pedestrians are considered: adults, children, and injured people. Collisions between adults and children result in injured people. When the number of injured people continuously in contact with each other reaches a given value k, the injured people are removed from the lattice space. This situation is the same as that in which pedestrians start stepping over injured people. This behavior was interpreted as the morality of pedestrians. Simulations showed that the evacuation showed down and eventually became jammed owing to the injured people acting as "obstacles" in relation to the morality k.

• Journal of the Korea Society for Simulation
• /
• v.22 no.3
• /
• pp.1-6
• /
• 2013

The ecosystem is the complex system consisting of various biotic and abiotic factors and the factors interact with each other in the hierarchical predator-prey relationship. Since the competitive relation spatiotemporally occurs, the initial state of population density and species distribution are likely to play an important role in the stability of the ecosystem. In the present study, we constructed a lattice model to simulate the three-trophic ecosystem (predatorprey- plant) and using the model, explored how the ecosystem stability is affected by the initial density. The size of lattice space was $L{\times}L$, (L=100) with periodic boundary condition. The initial density of the plant was arbitrarily set as the value of 0.2. The simulation result showed that predator and prey coexist when the density of predator is less than or equal to 0.4 and the density of prey is less than or equal to 0.5. On the other hand, when the predator density is more than or equal to 0.5 and the density of prey is more than or equal to 0.6, both of predator and prey were extinct. In addition, we found that the strong nonlinearity in the interaction between species was observed in the border area between the coexistence and extinction in the species density space.

• Journal of KIISE:Software and Applications
• /
• v.35 no.9
• /
• pp.554-561
• /
• 2008

Prediction technique of user's intention can be used as a post-processing method for reducing the search space of an automatic speech recognizer. Prediction technique of system's intention can be used as a pre-processing method for generating a flexible sentence. To satisfy these practical needs, we propose a statistical model to predict speakers' intentions that are generalized into pairs of a speech act and a concept sequence. Contrary to the previous model using simple n-gram statistic of speech acts, the proposed model represents a dialogue history of a current utterance to a feature set with various linguistic levels (i.e. n-grams of speech act and a concept sequence pairs, clue words, and state information of a domain frame). Then, the proposed model predicts the intention of the next utterance by using the feature set as inputs of CRFs (Conditional Random Fields). In the experiment in a schedule management domain, The proposed model showed the precision of 76.25% on prediction of user's speech act and the precision of 64.21% on prediction of user's concept sequence. The proposed model also showed the precision of 88.11% on prediction of system's speech act and the Precision of 87.19% on prediction of system's concept sequence. In addition, the proposed model showed 29.32% higher average precision than the previous model.

• The Journal of Engineering Geology
• /
• v.32 no.4
• /
• pp.449-466
• /
• 2022

The establishment of a complete geological model that includes information about all the various components at a site (such as underground structures and the compositions of rock and soil underground space) is difficult, and geological modeling is a developing field. This study uses commercial software for the relatively easy composition of geological models. Our digital modeling process integrates a model of Jeju Island's 3D geological information, models of cave shapes, and information on the state of a road at the site's upper surface. Among the numerous natural caves that exist in Jeju Island, we studied the Jaeamcheon lava tube near Hallim town, and the selected site lies below a road. We developed a digital model by applying the principles of building information modeling (BIM) to the cave (CaveBIM). The digital model was compiled through gathering and integrating specific data: relevant processes include modeling the cave's shape using a laser scanner, 3D geological modeling using geological information and geophysical exploration data, and modeling the surrounding area using drones. This study developed a global-scale model of the Hallim region and a local-scale model of the Jaeamcheon cave. Cross-validation was performed when constructing the LSM, and the results were compared and analyzed.

• Transactions of the Korean Society of Mechanical Engineers
• /
• v.17 no.5
• /
• pp.1054-1065
• /
• 1993

A computer simulation is performed on the effectiveness of the active minimization of harmonically excited enclosed sound fields for producing global reduction in the amplitude of the pressure fluctuations. In this study for the appreciable reductions in total time averaged acoustic potential energy, $E_{pp}$, the transducer location strategies for three dimensional active noise control is presented based on a state space modal which approximates the closed acoustic field.In this study, the above theoretical basis is used to investigate the application of active control to sound fields of low modal density. By the used of room-like 3-dimensional rectangular enclosure it is demonstrated that the reductions in $E_{pp}$ can be achieved by using a single secondary source, provided that the source is placed within the half a wavelength from the primary source and placed away from nodal line of the sound field. Concerning the reductions in $E_{pp}$ by minimzing the pressure in sound fields by the use of 3-dimensional rectangular enclosure, the effects of the number of sensors and the locations of these sensors are investigated. When a few modes dominate the response it is found that if only a limited number of sensors are located away from nodal line and located at the pressure maxima of the sound field such as at each corner of a rectangular enclosure.

• The KIPS Transactions:PartB
• /
• v.9B no.2
• /
• pp.139-146
• /
• 2002

The robot soccer simulation game is a dynamic multi-agent environment. In this paper we suggest a new reinforcement learning approach to each agent's dynamic positioning in such dynamic environment. Reinforcement learning is the machine learning in which an agent learns from indirect, delayed reward an optimal policy to choose sequences of actions that produce the greatest cumulative reward. Therefore the reinforcement learning is different from supervised learning in the sense that there is no presentation of input-output pairs as training examples. Furthermore, model-free reinforcement learning algorithms like Q-learning do not require defining or learning any models of the surrounding environment. Nevertheless these algorithms can learn the optimal policy if the agent can visit every state-action pair infinitely. However, the biggest problem of monolithic reinforcement learning is that its straightforward applications do not successfully scale up to more complex environments due to the intractable large space of states. In order to address this problem, we suggest Adaptive Mediation-based Modular Q-Learning (AMMQL) as an improvement of the existing Modular Q-Learning (MQL). While simple modular Q-learning combines the results from each learning module in a fixed way, AMMQL combines them in a more flexible way by assigning different weight to each module according to its contribution to rewards. Therefore in addition to resolving the problem of large state space effectively, AMMQL can show higher adaptability to environmental changes than pure MQL. In this paper we use the AMMQL algorithn as a learning method for dynamic positioning of the robot soccer agent, and implement a robot soccer agent system called Cogitoniks.