• Journal of the Korea Society for Simulation
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• v.19 no.1
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• pp.113-123
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• 2010

The interest in combat network systems rises among specialists as the military technology advances. This study considers some new elements such as characteristics of weapon systems, force moving rules at the end of each small battle, etc. to improve the accuracy of the analysis of series of mini battle problems. There is a significant difference in MOEs among the scenarios and the models. This study suggests some further works in weapon allocation, moving speed, tactics, weather, and topography which need to be investigated.

• The Korean Journal of Physiology and Pharmacology
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• v.28 no.2
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• pp.165-181
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• 2024

The slow and regular pacemaking activity of midbrain dopamine (DA) neurons requires proper spatial organization of the excitable elements between the soma and dendritic compartments, but the somatodendritic organization is not clear. Here, we show that the dynamic interaction between the soma and multiple proximal dendritic compartments (PDCs) generates the slow pacemaking activity in DA neurons. In multipolar DA neurons, spontaneous action potentials (sAPs) consistently originate from the axon-bearing dendrite. However, when the axon initial segment was disabled, sAPs emerge randomly from various primary PDCs, indicating that multiple PDCs drive pacemaking. Ca²⁺ measurements and local stimulation/perturbation experiments suggest that the soma serves as a stably-oscillating inertial compartment, while multiple PDCs exhibit stochastic fluctuations and high excitability. Despite the stochastic and excitable nature of PDCs, their activities are balanced by the large centrally-connected inertial soma, resulting in the slow synchronized pacemaking rhythm. Furthermore, our electrophysiological experiments indicate that the soma and PDCs, with distinct characteristics, play different roles in glutamate-induced burst-pause firing patterns. Excitable PDCs mediate excitatory burst responses to glutamate, while the large inertial soma determines inhibitory pause responses to glutamate. Therefore, we could conclude that this somatodendritic organization serves as a common foundation for both pacemaker activity and evoked firing patterns in midbrain DA neurons.

• Journal of KSNVE
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• v.10 no.6
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• pp.941-948
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• 2000

Active noise control is an approach to reduce the noise by utilizing a secondary noise source that destructively interferes with the unwanted noise. In general, active noise control systems rely on multiple sensors to measure the unwanted noise field and the effect of the cancellation. This paper develops an approach that utilizes a single sensor. The noise field is modeled as a stochastic process, and an adaptive algorithm is used to adaptively estimate the parameters of the process. Based on these parameter estimates, a canceling signal is generated. Oppenheim assumed that transfer function characteristics from the canceling source to the error sensor is only a propagation delay. This paper proposes a modified Oppenheim algorithm by considering transfer characteristics of speaker-path-sensor This transfer characteristics is adaptively cancelled by the proposed adaptive modeling technique. Feasibility of the proposed method is proved by computer simulations with artificially generated random noises and sine wave noise. The details of the proposed architecture. and theoretical simulation of the noise cancellation system for three dimension enclosure are presented in the Paper.

• Structural Engineering and Mechanics
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• v.3 no.5
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• pp.497-509
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• 1995

Effectiveness of multiple tuned mass dampers (MTMD) in suppressing the dynamic response of base excited structure for first mode vibration is investigated. The effectiveness of the MTMD is expressed by the ratio of the root mean square (RMS) displacement of the structure with MTMD to corresponding displacement without MTMD. The frequency content of base excitation is modelled as a broad-band stationary random process. The MTMD's with uniformly distributed natural frequencies are considered for this purpose. A parametric study is conducted to investigate the fundamental characteristics of the MTMD's and the effect of important parameters on the effectiveness of the MTMD's. The parameters include: the fundamental characteristics of the MTMD system such as damping, mass ratio, total number of MTMD, tuning frequency ratio, frequency spacing of the dampers and frequency content of the base excitation. It has been shown that MTMD can be more effective and more robust than a single TMD with equal mass and damping ratio.

• Proceedings of the Earthquake Engineering Society of Korea Conference
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• 2003.03a
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• pp.61-68
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• 2003

The H/V ratio (Horizontal to Vertical spectral ratio) has been used to infer site amplification without previous knowledge of near-surface geology and in fact may provide useful general site condition information. This method is used to classify the site characteristics of seismic stations in Korea by comparison with known H/V ratios representative of various sites all over the world. In addition, differences between horizontal and vertical kappa values were evaluated for each seismic stations by comparing WV ratio and Weak Motion amplification derived from inversion of stochastic ground motion parameters and were used as index to quantitatively classify the site characteristics.

• The KIPS Transactions:PartB
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• v.17B no.1
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• pp.69-78
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• 2010

Spectral modeling synthesis (SMS) has been used as a powerful tool for musical sound modeling. This technique considers a sound as a combination of a deterministic plus a stochastic component. The deterministic component is represented by the series of sinusoids that are described by amplitude, frequency, and phase functions and the stochastic component is represented by a series of magnitude spectrum envelopes that functions as a time varying filter excited by white noise. These representations make it possible for a synthesized sound to attain all the perceptual characteristics of the original sound. However, sometimes considerable phase variations occur in the deterministic component by using the conventional SMS for the complex sound such as whale sounds when the partial frequencies in successive frames differ. This is because it utilizes the calculated phase to synthesize deterministic component of the sound. As a result, it does not provide a good spectrum matching between original and synthesized spectrum in higher frequency region. To overcome this problem, we propose a modified SMS that provides good spectrum matching of original and synthesized sound by calculating complex residual spectrum in frequency domain and utilizing original phase information to synthesize the deterministic component of the sound. Analysis and simulation results for synthesizing whale sounds suggest that the proposed method is comparable to the conventional SMS in both time and frequency domain. However, the proposed method outperforms the SMS in better spectrum matching.

• Journal of Korean Society of Transportation
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• v.22 no.4 s.75
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• pp.147-158
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• 2004

A class of SWP(Stochastic Wane Propagation) models microscopically mimics individual vehicles' stochastic behavior and traffic jam propagation with simplified car-following models based on CA(Cellular Automata) theory and macroscopically captures dynamic traffic flow relationships based on statistical physics. SWP model, a program-oriented model using both discrete time-space and integer data structure, can simulate a huge road network with high-speed computing time. However, the model has shortcomings to both the capturing of low speed within a jam microscopically and that of the density and back propagation speed of traffic congestion macroscopically because of the generation of spontaneous jam through unrealistic collision avoidance. In this paper, two additional rules are integrated into the NaSch model. The one is SMR(Stopping Maneuver Rule) to mimic vehicles' stopping process more realistically in the tail of traffic jams. the other is LAR(Low Acceleration Rule) for the explanation of low speed characteristics within traffic jams. Therefore, the CA car-following model with the two rules prevents the lockup condition within a heavily traffic density capturing both the stopping maneuver behavior in the tail of traffic jam and the low acceleration behavior within jam microscopically, and generates more various macroscopic traffic flow mechanism than NaSch model's with the explanation of propagation speed and density of traffic jam.

• The Transactions of the Korea Information Processing Society
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• v.7 no.8
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• pp.2484-2496
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• 2000

High speed switches have been developing to interconnect a large number of nodes. It is important to analyze the switch performance under various conditions to satisfy the requirements. Queueing analysis, in general, has the intrinsic problem of large state space dimension and complex computation. In fact, The petri net is a graphical and mathematical model. It is suitable for various applications, in particular, manufacturing systems. It can deal with parallelism, concurrence, deadlock avoidance, and asynchronism. Currently it has been applied to the performance of computer networks and protocol verifications. This paper presents a framework for modeling and analyzing ATM switch using stochastic activity networks (SANs). In this paper, we provide the ATM switch model using SANs to extend easily and an approximate analysis method to apply A TM switch models, which significantly reduce the complexity of the model solution. Cell arrival process in output-buffered Queueing A TM switch with finite buffer is modeled as Markov Modulated Poisson Process (MMPP), which is able to accurately represent real traffic and capture the characteristics of bursty traffic. We analyze the performance of the switch in terms of cell-loss ratio (CLR), mean Queue length and mean delay time. We show that the SAN model is very useful in A TM switch model in that the gates have the capability of implementing of scheduling algorithm.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.3 no.1 s.4
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• pp.31-44
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• 2004

The study of Estimation model for the short-term travel time prediction. There is a different solution which has predicted the link travel time to solve this problem. By using this solution, the link travel time is predicted based on link conditions from time to time. The predicated link travel time is used to search the shortest path. Before providing a dynamic shortest path finding, the prediction model should be verified. To verify the prediction model, three models such as Kalman filtering, Stochastic Process, ARIMA. The ARIMA model should adjust optimal parameters according to the traffic conditions. It requires a frequent adjustment process of finding optimal parameters. As a result of these characteristics, It is difficult to use the ARIMA model as a prediction. Kalman Filtering model has a distinguished prediction capability. It is due to the modification of travel time predictive errors in the gaining matrix. As a result of these characteristics, the Kalman Filtering model is likely to have a non-accumulative errors in prediction. Stochastic Process model uses the historical patterns of travel time conditions on links. It if favorably comparable with the other models in the sense of the recurrent travel time condition prediction. As a result, for the travel time estimation, Kalman filtering model is the better estimation model for the short-term estimation, stochastic process is the better for the long-term estimation.

• Water for future
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• v.9 no.2
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• pp.87-100
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• 1976

These studies are aimed at the analysis of systematic variation pattern of water resources in Korean river catchments and the development of their simulation models from the stochastic analysis of monthly and annual hydrologic data as main elements of water resources, i.e. rainfall and streamflow. In the analysis, monthly & annual rainfall records in Soul, Taegu, Pusan and Kwangju and streamflow records at the main gauging stations in Han, Nakdong and Geum river were used. Firstly, the systematic variation pattern of annual streamflow was found by the exponential function relationship between their standard deviations and mean values of log-annual runoff. Secondly, stochastic characteristics of annual rainfall & streamflow series were studied by the correlogram Monte Carlo method and a single season model of 1st-order Markov type were applied and compared in the simulation of annual hydrologic series. In the simulation, single season model of Markov type showed better results than LN-model and the simulated data were fit well with historical data. But it was noticed that LN-model gave quite better results in the simulation of annual rainfall. Thirdly, stochastic characteristics of monthly rainfall & streamflow series were also studied by the correlogram and spectrum analysis, and then the Model-C, which was developed and applied for the synthesis of monthly perennial streamflow by lst author and is a Markov type model with transformed skewed random number, was used in the simulation of monthly hydrologic series. In the simulation, it was proved that Model-C was fit well for extended area in Korea and also applicable for menthly rainfall as well as monthly streamflow.