• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 1998.06a
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• pp.740-749
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• 1998

This paper proposes compression of image data using neural networks based on conjugate gradient method and dynamic tunneling system. The conjugate gradient method is applied for high speed optimization .The dynamic tunneling algorithms, which is the deterministic method with tunneling phenomenon, is applied for global optimization. Converging to the local minima by using the conjugate gradient method, the new initial point for escaping the local minima is estimated by dynamic tunneling system. The proposed method has been applied the image data compression of 12 ${\times}$12 pixels. The simulation results shows the proposed networks has better learning performance , in comparison with that using the conventional BP as learning algorithm.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2018.10a
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• pp.512-513
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• 2018

Trap-assisted-tunneling (TAT) degrades subthreshold slope of real-world tunneling field-effect-transistors (TFET) and it should be considered in the simulation. However, its mechanism is not very well understood in line tunneling type L-shaped TFET (LTFET). This study investigates TAT mechanism in LTFETs using dynamic nonlcoal Schenk model. Both phonon assisted and direct band to trap tunneling events are considered in this study.

• Journal of the Korean Institute of Telematics and Electronics B
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• v.33B no.4
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• pp.201-208
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• 1996

This paper proposes an efficient method for improving the training performance of the neural network using a hybrid of backpropagation algorithm and dynamic tunneling system.The backpropagation algorithm, which is the fast gradient descent method, is applied for high-speed optimization. The dynamic tunneling system, which is the deterministic method iwth a tunneling phenomenone, is applied for blobal optimization. Converging to the local minima by using the backpropagation algorithm, the approximate initial point for escaping the local minima is estimated by the pattern classification, and the simulation results show that the performance of proposed method is superior th that of backpropagation algorithm with randomized initial point settings.

• Journal of the Korean Institute of Telematics and Electronics C
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• v.34C no.12
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• pp.61-69
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• 1997

This paper proposes a new method for improving the performances of the neural network for optimization using a hyubrid of gradient descent method and dynamic tunneling system. The update rule of gradient descent method, which has the fast convergence characteristic, is applied for high-speed optimization. The update rule of dynamic tunneling system, which is the deterministic method with a tunneling phenomenon, is applied for global optimization. Having converged to the for escaping the local minima by applying the dynamic tunneling system. The proposed method has been applied to the travelling salesman problems and the optimal task partition problems to evaluate to that of hopfield model using the update rule of gradient descent method.

• The Transactions of the Korea Information Processing Society
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• v.4 no.11
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• pp.2769-2779
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• 1997

This Paper Proposes an efficient method for improving the training performance of the neural networks using a hybrid of conjugate gradient backpropagation algorithm and dynamic tunneling backpropagation algorithm The conjugate gradient backpropagation algorithm, which is the fast gradient algorithm, is applied for high speed optimization. The dynamic tunneling backpropagation algorithm, which is the deterministic method with tunneling phenomenon, is applied for global optimization. Conversing to the local minima by using the conjugate gradient backpropagation algorithm, the new initial point for escaping the local minima is estimated by dynamic tunneling backpropagation algorithm. The proposed method has been applied to the parity check and the pattern classification. The simulation results show that the performance of proposed method is superior to those of gradient descent backpropagtion algorithm and a hybrid of gradient descent and dynamic tunneling backpropagation algorithm, and the new algorithm converges more often to the global minima than gradient descent backpropagation algorithm.

• The Transactions of the Korea Information Processing Society
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• v.6 no.5
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• pp.1393-1402
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• 1999

This paper proposes an efficient principal feature extraction of the image data using neural networks of a new learning algorithm. The proposed learning algorithm is a backpropagation(BP) algorithm based on the steepest descent and dynamic tunneling. The BP algorithm based on the steepest descent is applied for high-speed optimization, and the BP algorithm based on the dynamic tunneling is also applied for global optimization. Converging to the local minimum by the BP algorithm of steepest descent, the new initial weights for escaping the local minimum is estimated by the BP algorithm of dynamic tunneling. The proposed algorithm has been applied to the 3 image data of 12${\times}$12pixels and the Lenna image of 128${\times}$128 pixels respectively. The simulation results shows that the proposed algorithm has better performances of the convergence and the feature extraction, in comparison with those using the Sanger method and the Foldiak method for single-layer neural networks and the BP algorithm for multilayer neural network.

• Geomechanics and Engineering
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• v.20 no.2
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• pp.103-112
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• 2020

The dynamic response of crossing tunnels under heavy-haul train loads is still not fully understood. In this study, based on the case of a high-speed tunnel underneath an existing heavy-haul railway tunnel, a model experiment was performed to research the dynamic response characteristics of crossing tunnels. It is found that the under-crossing changes the dynamic response of the existing tunnel and surrounding rock. The acceleration response of the existing tunnel enhances, and the dynamic stress of rock mass between crossing tunnels decreases after the excavation. Both tunneling and the excitation of heavy-haul train loads stretch the tunnel base, and the maximum tensile strain is 18.35 µε in this model test. Then, the measured results were validated by numerical simulation. Also, a parametric study was performed to discuss the influence of the relative position between crossing tunnels and the advanced support on the dynamic behavior of the existing tunnel, where an amplifying coefficient of tunnel vibration was introduced to describe the change in acceleration due to tunneling. These results reveal the dynamic amplifying phenomenon of the existing tunnel during the new tunnel construction, which can be referred in the dynamic design of crossing tunnels.

• Proceedings of the IEEK Conference
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• 1998.10a
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• pp.47-50
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• 1998

In recent years, it is required that computing support mobile user with computer. The advantage of mobile computing is that users may access all their applications from any location, whether they are in another building or a different state. So, Internet combines with mobile computing technology to make new communication environment for supporting mobility. The research for solving the problem of mobility is actively in progress. This paper describes the implementation of tunneling method for flexible bypass between specific region. Tunneling method provide mobile service to mobile hosts. IP datagram's address tranform method is IP-within-IP encapsulation by which an IP datagram may be encapsulated within an IP datagram. The developed IP-within-IP protocol can provide not only enhanced performance because it is implemented in kernel mode, but also convenience of usage to the application developers because it gives user interface as a dynamic link library. Verification of IP packet tunneling was text file transfer program.

• Geomechanics and Engineering
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• v.37 no.2
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• pp.179-187
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• 2024

In this paper, a unified time-dependent constitutive model of Darcy flow and non-Darcy flow is proposed. The influencing factors of flow velocity are discussed, which demonstrates that permeability coefficient is the most significant factor. Based on this, the dynamic evolution characteristics of water inrush during tunneling through fault fracture zone is analyzed under the constant permeability coefficient condition (CPCC). It indicates that the curves of flow velocity and hydrostatic pressure can be divided into typical three stages: approximate high-velocity zone inside the fault fracture zone, velocity-rising zone near the tunnel excavation face and attenuation-low velocity zone in the tunnel. Furthermore, given the variation of permeability coefficient of the fault fracture zone with depth and time, the dynamic evolution of water flow in the fault fracture zone under the variable permeability coefficient condition (VPCC) is also studied. The results show that the time-related factor (α) affects the dynamic evolution distribution of flow velocity with time, the depth-related factor (A) is the key factor to the dynamic evolution of hydrostatic pressure.

• Proceedings of the Korean Vacuum Society Conference
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• 2015.08a
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• pp.63.2-63.2
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• 2015

Controlling and sensing spin states of magnetic molecules such as metallo-porphyrins at the single molecule level is essential for spintronic molecular device applications. Axial coordinations of diatomic molecules to metallo-porphyrins also play key roles in dynamic processes of biological functions such as blood pressure control and immune response. However, probing such reactions at the single molecule level to understand their physical mechanisms has been rarely performed. Here we present on our single molecule association and dissociation experiments between diatomic and metallo-porphyrin molecules on Au(111) describing its adsorption structures, spin states, and dissociation mechanisms. We observed bright ring shapes in NO adsorbed metallo-porphyrin compelxes and explained them by considering tilted binding and precession motion of NO. Before NO exposure, Co-porphryin showed a clear zero-bias peak in scanning tunneling spectroscopy, a signature of Kondo effect in STS, whereas after NO exposures it formed a molecular complex, NO-Co-porphyrin, that did not show any zero-bias feature implying that the Kondo effect was switched off by binding of NO. Under tunneling junctions of scanning tunneling microscope, both positive and negative energy pulses. From the observed power law relations between dissociation rate and tunneling current, we argue that the dissociations were inelastically induced with molecular orbital resonances. Our study shows that single molecule association and dissociation can be used to probe spin states and reaction mechanisms in a variety of axial coordination between small molecules and metallo-porphyrins.