• Journal of the Korean Society for Railway
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• v.17 no.5
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• pp.342-348
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• 2014

Contact between wheel and rail leads to the creep phenomenon. Linear creep theory, assuming linear increase in the creep force vs creep, results in a critical speed at which the vibration of a railway vehicle goes to infinity. However, the actual creep force converges to a limited value, so that the vibration of a railway vehicle cannot increase indefinitely. In this study, the dynamics of a railway vehicle is investigated with a 6 DOF bogie model includingthe nonlinear creep curves of Vermeulen, Polach, and a newly calculated creep curve with strip theory. Strip theory considers the profiles of the wheel and rail. The results show that the vibration of a railway vehicle results in a limit-cycle over a specific running speed, and this limit-cycle becomes smaller as the slope of the creep-curve steepens. Moreover, a hunting phenomenon is caused due to flange contact, which restricts the magnitude of the limit-cycle.

• Proceedings of the KSME Conference
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• 2008.11a
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• pp.973-978
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• 2008

This study concerned on the critical speed due to hunting and snake motion train to ensure the stability. First, the critical speed was calculated by using a numerical model, and calculated the critical speed of the vehicle through the simulation with the use of ADAMS/RAII. Also, the snake motion was confirmed through a modal analysis and running simulation. The calculated results, show that the rail irregularity becomes the influential factors of the stability since it is the direct source of excitation of the vehicle.

• Proceedings of the KSR Conference
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• 2003.05a
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• pp.755-761
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• 2003

The dynamic analysis of the KTX can predict the dynamic motions which occurred in test drive. In this study an analytical model of the KTX is developed to find the critical speed. The numerical analysis for the nonlinear equation motions of 17 degrees of freedom show the running stability and the critical speed due to the hunting motion of the KTX. Also, the vibration modes of the KTX are calculated using the ADAMS/RAIL software, which show that the critical speed occurs for the yawing modes of the car body and the bogie. Finally, this paper shows that the critical speed of the KTX could be changed with the modifications of the design parameters of wheel conicity and wheel contact point.

• International Journal of Computer Science & Network Security
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• v.23 no.8
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• pp.177-189
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• 2023

Malware detection is an increasingly important operational focus in cyber security, particularly given the fast pace of such threats (e.g., new malware variants introduced every day). There has been great interest in exploring the use of machine learning techniques in automating and enhancing the effectiveness of malware detection and analysis. In this paper, we present a deep recurrent neural network solution as a stacked Long Short-Term Memory (LSTM) with a pre-training as a regularization method to avoid random network initialization. In our proposal, we use global and short dependencies of the inputs. With pre-training, we avoid random initialization and are able to improve the accuracy and robustness of malware threat hunting. The proposed method speeds up the convergence (in comparison to stacked LSTM) by reducing the length of malware OpCode or bytecode sequences. Hence, the complexity of our final method is reduced. This leads to better accuracy, higher Mattews Correlation Coefficients (MCC), and Area Under the Curve (AUC) in comparison to a standard LSTM with similar detection time. Our proposed method can be applied in real-time malware threat hunting, particularly for safety critical systems such as eHealth or Internet of Military of Things where poor convergence of the model could lead to catastrophic consequences. We evaluate the effectiveness of our proposed method on Windows, Ransomware, Internet of Things (IoT), and Android malware datasets using both static and dynamic analysis. For the IoT malware detection, we also present a comparative summary of the performance on an IoT-specific dataset of our proposed method and the standard stacked LSTM method. More specifically, of our proposed method achieves an accuracy of 99.1% in detecting IoT malware samples, with AUC of 0.985, and MCC of 0.95; thus, outperforming standard LSTM based methods in these key metrics.

• Transactions of the Korean Society of Mechanical Engineers
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• v.10 no.5
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• pp.742-750
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• 1986

The lateral vibrating motion of a railway vehicle over a certain critical speed is a well known problem in the field of train dynamics. It is known that the train equations of motion are strongly coupled and highly nonlinear with the motion and causing that it is very difficult to solve the equations simultaneously. In this paper, a 8 degree of feedom model of a railway vehicle was suggested to solve the rail vehicle lateral motion. In stead of solving the nonlinear equation simultaneously, statistical linearization technique was adopted to solve those equations. The analysis results from the statistical linearization method were directly compared with those from direct nonlinear equations and found that the linearization technique can be very effective and economical for railroad vehicle analysis. By the way, it was found that the analysis results can analytically explain the intermittent hunting phenomena which has been frequently observed in experiments.

• Proceedings of the KSR Conference
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• 2008.11b
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• pp.1435-1440
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• 2008

High-speed train under development is a type of EMU(electric multiple units). Since power sources like motors and gears are distributed in the high-speed EMU, the high-speed EMU generates vibration and sound more than the articulated high-speed train. Vibration of vehicle, vibration between rails and wheels, hunting of bogie and snake motion reduce ride comfort. In this paper, to decrease the vibration of the articulated high-speed train, improvements were presented using an analytical model and a simulation model. The simulation model of the high-speed EMU was designed on the basis of the korean high-speed train and the design parameters for ride comfort were showed and the dynamic characteristics of the vehicle was understood. To consider the characteristics of the vehicle suspension, the analytical model was designed and the simulation model was verified with it.

• Journal of the Korean Society for Railway
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• v.4 no.3
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• pp.116-122
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• 2001

As freight traffic becomes heavier, the high speed of existing freight cars is essential, instead of the construction of a new railway. The high speed can be achieved by the modifications of freight bogie design. In this paper, an analytical model of freight bogie is developed to decide the critical speed. The dynamic responses of the analytical model are compared with the experimental data from a running test of freight bogie and showed good agreements between them. The analytical model is used to find the design of freight bogie. The parameter studies show that the reduction of wheelset mass ratio and the increase of the axle distance of freight bogie can increase the critical speed, but the primary lateral stiffness has little effects on the critical speed. And this study also shows that smaller wheel conicity deteriorates the running safety of freight car, which means that the overhauling of the wheel of freight bogie should be done regularly.

• Proceedings of the KSR Conference
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• 2001.10a
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• pp.179-186
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• 2001

As the freight traffic becomes heavier, the high speed of existing freight cars is essential instead of the construction of a new railway. The high speed can be achieved by the design modifications of the freight bogie. In this paper, an analytical model of freight bogie including the lateral force between rail and the flange of wheel is developed to decide the critical speed, which activates a hunting motion and tells the running safety of freight bogie. The dynamic responses of the analytical model were compared with an experimental data from a running test of a freight bogie and showed good agreements between them. The analytical model is used to find the design modifications of the freight bogie by parameter studies. The results show that the reduction of wheelset mass ratio and the increase of the axle distance of the freight bogie can increase the critical speed, but the primary lateral stiffness has little effects on the critical speed. And this also study shows that smaller wheel conicity deteriorates the running safety of the freight car, which means the overhauling of the wheel of freight bogie should be done regularly.

• Geomechanics and Engineering
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• v.13 no.6
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• pp.997-1010
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• 2017

The black box model is a relatively new option for nonlinear dynamic system identification. It can be used for prediction problems just based on analyzing the input and output data without considering the changes of the internal structure. In this paper, a black box model was presented to solve unconstrained overlying strata movement problems in coal mine production. Based on the black box theory, the overlying strata regional system was viewed as a "black box", and the black box model on overburden strata movement was established. Then, the rock mechanical properties and the mining thickness and mined-out section area were selected as the subject and object respectively, and the influences of coal mining on the overburden regional system were discussed. Finally, a corrected method for height prediction of the fractured zone was obtained. According to actual mine geological conditions, the measured geological data were introduced into the black box model of overlying strata movement for height calculation, and the fractured zone height was determined as 40.36 m, which was comparable to the actual height value (43.91 m) of the fractured zone detected by Double-block Leak Hunting in Drill. By comparing the calculation result and actual surface subsidence value, it can be concluded that the proposed model is adaptable for height prediction of the fractured zone.

• Journal of Korea Game Society
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• v.21 no.6
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• pp.87-96
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• 2021

As the industry develops, the technology used for games is also being advanced. In particular, AI technology is used to game automation and intelligence. These game player patterns are widely used in online games such as player matchmaking, generation of friendly or hostile NPCs, and balancing of game worlds. This study proposes a model generation method for game players. For model generation, attributes such as hunting, collection, movement, combat, crisis management, production, and interaction were defined, and patterns were extracted and modeled using decision tree method. To evaluate the proposed method, we used the game log of a commercial game and confirmed the meaningful results.