• Korean Journal of Optics and Photonics
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• v.29 no.6
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• pp.262-267
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• 2018

In this paper, we designed a new antireflective film to improve the optical efficiency of organic light-emitting diode displays (OLEDs). The reflection characteristics in the normal and side viewing directions of OLEDs with the antireflective film were calculated, depending on the degree of polarization and transmittance of the currently used polarizer when used in the antireflective film of an OLED. The results showed that when the polarization degree of the commercial polarizer (99.990~99.995%) is lowered to 99.900%, the average reflectance of the antireflective film is increased by about 0.1% (2.5% in terms of rate of increase) which is difficult to notice with the human eye, while the transmittance is increased by 1.63~3.34% (4.2~8.2% in terms of rate of increase). This study provides an optimal design for high-light-efficiency OLEDs with good antireflection properties.

• Journal of the Korean Society of Industry Convergence
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• v.25 no.4_2
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• pp.699-706
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• 2022

In this study, Directed energy deposition (DED) among additive manufacturing is applied to repair damaged spindle key parts of planner miller. The material of the spindle key is SCM415, and the P21 Powder is used. In order to find the optimal deposition conditions for DED equipment, a single-line deposition experiment is conducted to analysis five parameters. The laser power affects the width, and the height is a parameter affected by coaxial gas and powder gas. In addition, laser power, powder feed rate, coaxial gas, and powder gas are parameters that affect dilution. Otimal deposition is that 400 W of laser power, 4.0 g/min of powder feed rate, 6.5 L/min of coaxial gas, 3.0 L/min of powder gas and 4.5 L/min of shield gas. By setting the optimum conditions, a uniform deposition cross section in the form of an ellipse can be obtained. Damage recovery process of spindle key consists of 3D shape design of the base and deposition parts, deposition path creation and deposition process, and post-processing. The hardness of deposited area with P21 powder on the SCM415 spindle key is 336 HV for the surface of the deposition, 260 HV for the boundary area, and 165 HV for the base material.

• Journal of information and communication convergence engineering
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• v.4 no.4
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• pp.141-146
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• 2006

In these days, wireless data services are becoming ubiquitous in our daily life because they offers several fundamental benefits including user mobility, rapid installation, flexibility, and scalability. Moreover, the requests for various multimedia services and the Quality of Service (QoS) support have been one of key issues in wireless data communications. Therefore the research relative to Medium Access Control (MAC) has been progressing rapidly. Especially a number of QoS-aware MAC schemes have been introduced to extend the legacy IEEE 802.11 MAC protocol which has not guaranteed any service differentiation. However, none of those schemes fulfill both QoS features and channel efficiency although these support the service differentiation based on priority. Therefore this paper studies a novel MAC scheme, referred to as Enhanced Distributed Coordination Function with Network Adaptation (EDCF-NA), for enhancements of both QoS and medium efficiency. It uses a smart factor denoted by ACK rate and Network Load Threshold (TH). In this paper, we study how the value of TH has effect on MAC performance and how the use of optimal TH pair improves the overall MAC performance in terms of the QoS, channel utilization, collision rate, and fairness. In addition, we evaluate and compare both the performance of EDCF-NA depending on several pairs of TH and the achievement of various MAC protocols through simulations by using Network Simulator-2 (NS-2).

• The Journal of Korean Institute of Communications and Information Sciences
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• v.41 no.11
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• pp.1417-1419
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• 2016

In order to improve the transmission performance of a chirp signal-based chirp spread spectrum system, the cross-correlation coefficient (CCC) should be carefully considered. In this paper, we derive the CCC for analyzing the transmission performance and propose the optimal chirp rate based on the analysis. The simulation results verify the mathematical derivations and show that the considered scheme can improve the performance by considering the CCC.

• Proceedings of the Korean Institute of Electrical and Electronic Material Engineers Conference
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• 2002.11a
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• pp.573-577
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• 2002

A new estimated neural networks are proposed in order to measure nonlinear road environments in realtime. This new neural networks is Error Estimated Neural Networks. The structure of it is similar to recurrent neural networks; a delayed output as the input and a delayed error between the output of plant and neural networks as a bias input. In addition, we compute the desired value of hidden layer by an optimal method instead of transfering desired values by backpropagation and each weights are updated by RLS(Recursive Least Square). Consequently, this neural networks are not sensitive to initial weights and a learning rate, and have a faster convergence rate than conventional neural networks. We can estimate nonlinear models in realtime by the proposed networks and control nonlinear models. To show the performance of this one, we control 7 degree simulation, this controller and driver were proved to be effective to drive a car in the environments of nonlinear road systems.

• Journal of information and communication convergence engineering
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• v.11 no.4
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• pp.229-234
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• 2013

Diversity-multiplexing tradeoff (DMT) characterizes the fundamental relationship between the diversity gain in terms of outage probability and the multiplexing gain as the normalized rate parameter r, where the limiting transmission rate is give by rlog SNR (here, SNR denote the received signal-to-noise ratio). In this paper, we analyze the DMT and performance of an underwater network with a cooperative relay. Since over an acoustic channel, the propagation delay is commonly considerably higher than the processing delay, the existing transmission protocols need to be explained accordingly. For this underwater network, we briefly describe two well-known relay transmissions: decode-and-forward (DF) and amplify-and-forward (AF). As our main result, we then show that an instantaneous DF relay scheme achieves the same DMT curve as that of multiple-input single-output channels and thus guarantees the DMT optimality, while using an instantaneous AF relay leads at most only to the DMT for the direct transmission with no cooperation. To validate our analysis, computer simulations are performed in terms of outage probability.

• Proceedings of the KIEE Conference
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• 2000.07d
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• pp.2949-2952
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• 2000

A new neural networks and learning algorithm are proposed in order to measure nonlinear heights of complexed road environments in realtime without pre-information. This new neural networks is Error Self Recurrent Neural Networks(ESRN), The structure of it is similar to recurrent neural networks: a delayed output as the input and a delayed error between the output of plant and neural networks as a bias input. In addition, we compute the desired value of hidden layer by an optimal method instead of transfering desired values by back-propagation and each weights are updated by RLS(Recursive Least Square). Consequently. this neural networks are not sensitive to initial weights and a learning rate, and have a faster convergence rate than conventional neural networks. We can estimate nonlinear models in realtime by ESRN and learning algorithm and control nonlinear models. To show the performance of this one. we control 7 degree of freedom full car model with several control method. From this simulation. this estimation and controller were proved to be effective to the measurements of nonlinear road environment systems.

• The Journal of Korea Robotics Society
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• v.17 no.3
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• pp.264-272
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• 2022

Human-robot cooperative tasks are increasingly required in our daily life with the development of robotics and artificial intelligence technology. Interactive reinforcement learning strategies suggest that robots learn task by receiving feedback from an experienced human trainer during a training process. However, most of the previous studies on Interactive reinforcement learning have required an extra feedback input device such as a mouse or keyboard in addition to robot itself, and the scenario where a robot can interactively learn a task with human have been also limited to virtual environment. To solve these limitations, this paper studies training strategies of robot that learn table balancing tasks interactively using deep reinforcement learning with human's facial expression feedback. In the proposed system, the robot learns a cooperative table balancing task using Deep Q-Network (DQN), which is a deep reinforcement learning technique, with human facial emotion expression feedback. As a result of the experiment, the proposed system achieved a high optimal policy convergence rate of up to 83.3% in training and successful assumption rate of up to 91.6% in testing, showing improved performance compared to the model without human facial expression feedback.

• Journal of Internet Computing and Services
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• v.24 no.2
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• pp.1-10
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• 2023

The Multi-access Edge Computing (MEC) paradigm equips network edge telecommunication infrastructure with cloud computing resources. It seeks to transform the edge into an IT services platform for hosting resource-intensive and delay-stringent services for mobile users, thereby significantly enhancing perceived service quality of experience. However, erratic user mobility impedes seamless service continuity as well as satisfying delay-stringent service requirements, especially as users roam farther away from the serving MEC resource, which deteriorates quality of experience. This work proposes a deep reinforcement learning based service mobility management approach for ensuring seamless migration of service instances along user mobility. The proposed approach focuses on the problem of selecting the optimal MEC resource to host services for high mobility users, thereby reducing service migration rejection rate and enhancing service availability. Efficacy of the proposed approach is confirmed through simulation experiments, where results show that on average, the proposed scheme reduces service delay by 8%, task computing time by 36%, and migration rejection rate by more than 90%, when comparing to a baseline scheme.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.17 no.11
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• pp.3204-3217
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• 2023

In this paper, the downlink of the multicast based spatial modulation systems is investigated. Specifically, physical layer multicasting is introduced to increase the number of access users and to improve the communication rate of the spatial modulation system in which only single radio frequency chain is activated in each transmission. To minimize the bit error rate (BER) of the multicast based spatial modulation system, a joint optimizing algorithm of antenna selection and multicast precoding is proposed. Firstly, the joint optimization is transformed into a mixed-integer non-linear program based on single-stage reformulation. Then, a novel iterative algorithm based on the idea of branch and bound is proposed to obtain the quasioptimal solution. Furthermore, in order to balance the performance and time complexity, a low-complexity deflation algorithm based on the successive convex approximation is proposed which can obtain a sub-optimal solution. Finally, numerical results are showed that the convergence of our proposed iterative algorithm is between 10 and 15 iterations and the signal-to-noise-ratio (SNR) of the iterative algorithm is 1-2dB lower than the exhaustive search based algorithm under the same BER accuracy conditions.