• Journal of Soil and Groundwater Environment
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• v.28 no.6
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• pp.9-15
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• 2023

In order to properly evaluate the spatio-temporal variations of groundwater flow, the data obtained in field experiments should be corroborated into numerical simulations. Particle tracking method is a simple simulation tool often employed in groundwater simulation to predict groundwater flow paths or solute transport paths. Particle tracking simulations visually show overall the particle flow path along the entire aquifer, but no previous simulation studies has yet described the parameter values at grid nodes around the particle path. Therefore, in this study, a new technical approach was proposed that enables acquisition of parameters associated with particle transport in grid nodes distributed in the center of the particle path in groundwater. Since the particle tracking path is commonly referred to as streamline, the algorithm and codes developed in this works designated streamline analysis method. The streamline analysis method can be applied in two-dimensional and three-dimensional finite element or finite difference grid networks, and can be utilized not only in the groundwater field but also in all fields that perform numerical modeling.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 1990.10a
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• pp.181-185
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• 1990

In the present study, the following factors are analyzed systematically using the theoretical and experimental methods, which have the significant influence on the quality of VTR tape path system in order to develope the high performance and quality in VTR mechanism: 1) Vibration characteristics of the deck including the tape path sytem, 2) Modeling the global tape path, 3) Torsional vibration of the VTR drum. 4) Capstan system, 5) Tension bar, 6) Stick-slip phenomenon of the running tape.

• Economic and Environmental Geology
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• v.35 no.1
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• pp.13-23
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• 2002

The chemical compositions of groundwaters from the granite areas mainly belong to Ca-HC0$_{3}$ and Na-HC0$_{3}$type, and some of these belong to Ca-(CI+S0$_{4}$) and Na-(CI+S0$_{4}$) type. Spring waters and groundwaters from anorthosite areas belong to Ca-HC03 and Na-HC03 type, respectively. The result of reaction path modeling shows that the chemical compositions of aqueous solution reacted with granite evolve from initial Ca-CI type, via CaHC0$_{3}$ type, to Na-HC0$_{3}$ type. The result of rain water-anorthosite interaction is similar to evolution path of granite reaction and both of these results agree well with the field data. In the reaction path modeling of rain watergranite/anorthosite reaction, as a reaction is progressing, the activity of hydrogen ion decreases (pH increases). The concentrations of cations are controlled by the dissolution of rock-forming minerals and precipitation and re-dissolution of secondary minerals according to the pH. The continuous addition of granite causes the formation of secondary minerals in the following sequence; gibbsite plus hematite, Mn-oxide, kaolinite, silica, chlorite, muscovite (a proxy for illite here), calcite, laumontite, prehnite, and finally analcime. In the anorthosite reaction, the order of precipitation of secondary minerals is the same as with granite reaction except that there is no silica precipitation and paragonite precipitates instead of analcime. The silica and kaolinite are predominant minerals in the granite and anorthosite reactions, respectively. Total quantities of secondary minerals in the anorthosite reaction are more abundant than those in the granite reaction.

• Journal of Korea Multimedia Society
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• v.25 no.8
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• pp.1007-1021
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• 2022

Autonomous driving of unmanned aerial vehicles may have to pay expensive cost to create and switch new routes if unexpected obstacles exist or local map updates occured by the control system due to incorrect route information. Integrating digital twins into the path-following process requires more computing resources to quickly switch the wrong path to an alternative path, but it can quickly update the path during flight. In this study, we design a DEVS-based simulation environment which can modify optimized paths through short-term simulation of multi-virtual UAVs for applying digital twin concepts to path follow. Through simulation, we confirmed the possibility of increasing the mission stability of UAV.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.16 no.8
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• pp.2473-2489
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• 2022

Urban development has brought about the increasing saturation of urban traffic demand, and traffic congestion has become the primary problem in transportation. Roads are in a state of waiting in line or even congestion, which seriously affects people's enthusiasm and efficiency of travel. This paper mainly studies the discrete domain path planning method based on the flow data. Taking the traffic flow data based on the highway network structure as the research object, this paper uses the deep learning theory technology to complete the path weight determination process, optimizes the path planning algorithm, realizes the vehicle path planning application for the expressway, and carries on the deployment operation in the highway company. The path topology is constructed to transform the actual road information into abstract space that the machine can understand. An appropriate data structure is used for storage, and a path topology based on the modeling background of expressway is constructed to realize the mutual mapping between the two. Experiments show that the proposed method can further reduce the interpolation error, and the interpolation error in the case of random missing is smaller than that in the other two missing modes. In order to improve the real-time performance of vehicle path planning, the association features are selected, the path weights are calculated comprehensively, and the traditional path planning algorithm structure is optimized. It is of great significance for the sustainable development of cities.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.43 no.6 s.312
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• pp.17-25
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• 2006

As information systems to be computerized get significantly scaled up, data modeling issues apparently considered to be crucial once again as the early 1980's under the terms of data governance, data architecture or data quality. Unfortuately, merely resorting to heuristics-based field approaches with more or less no firm theoretical foundation of knowledge with regard to criteria of data design lead quite often to major failures in efficacy of data modeling. In this paper, we have compared normalization-critical data modeling approach, well-known as the Non-Stop Data Modeling methodology in the literature, to the Information Engineering in which in many occasions the notion of do-normalization is supported and even recommended as a mandatory part in its modeling nature. Quantitative analyses have revealed that NS methodology ostensibly outperforms IE methodology in terms of efficiency indices like adequacy of entity judgement, degree of existence of data circulation path that confirms the balancedness of data design and ratio of unnecessary data attribute replication.

• The Journal of the Acoustical Society of Korea
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• v.27 no.8
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• pp.435-442
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• 2008

The n-gram model is appropriate for languages, such as English, in which the word-order is grammatically rigid. However, it is not suitable for Korean in which the word-order is relatively free. Previous work proposed a twoply HMM that reflected the characteristics of Korean but failed to reflect word-order structures among words. In this paper, we define a new segment unit which combines two words in order to reflect the characteristic of word-order among adjacent words that appear in verbal morphemes. Moreover, we propose a two-path language model that estimates probabilities depending on the context based on the proposed segment unit. Experimental results show that the proposed two-path language model yields 25.68% perplexity improvement compared to the previous Korean language models and reduces 94.03% perplexity for the prediction of verbal morphemes where words are combined.

• Journal of Ocean Engineering and Technology
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• v.20 no.1 s.68
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• pp.69-76
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• 2006

The design of efficient search path to maximize the Cumulative Detection Probability(CDP) is mainly dependent on experience and intuition when searcher detect the target using SONAR in the ocean. Recently with the advance of modeling and simulation method, it has been possible to access the optimization problems more systematically. In this paper, a method for the optimal search path calculation is developed based on the combination of the genetic algorithm and the calculation algorithm for detection range. We consider the discrete system for search path, space, and time, and use the movement direction of the SONAR for the gene of the genetic algorithm. The developed algorithm, OASPP(Optimal Acoustic Search Path Planning), is shown to be effective, via a simulation, finding the optimal search path for the case when the intuitive solution exists. Also, OASPP is compared with other algorithms for the measure of efficiency to maximize CDP.

• Journal of Communications and Networks
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• v.5 no.4
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• pp.303-308
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• 2003

We present a statistical model for the path loss of ultrawideband (UWB) channels in indoor environments. In contrast to our previously reported measurements, the data reported here are for a bandwidth of 6GHz rather than 1.25GHz; they encompass commercial buildings in addition to single-family homes (20 of each); and local spatial averaging is included. As before, the center frequency is 5.0GHz. Separate models are given for commercial and residential environments and, within each category, for lineof sight (LOS) and non-line-of-sight (NLS) paths. All four models have the same mathematical structure, differing only in their numerical parameters. The two new models (LOS and NLS) for residences closely match those derived from the previous measurements, thus affirming the stability of our path loss modeling. We find, also, that the path loss statistics for the two categories of buildings are quite similar.

• Proceedings of the KIEE Conference
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• 2006.10c
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• pp.527-529
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• 2006

In this paper, we find a robot's path using a Virtual Reality Modeling Language and overlay vision. For correct robot's path we describe a method for localizing a mobile robot in its working environment using a vision system and VRML. The robt identifies landmarks in the environment, using image processing and neural network pattern matching techniques, and then its performs self-positioning with a vision system based on a well-known localization algorithm. After the self-positioning procedure, the 2-D scene of the vision is overlaid with the VRML scene. This paper describes how to realize the self-positioning, and shows the overlap between the 2-D and VRML scenes. The method successfully defines a robot's path.