• The Journal of Korean Institute of Communications and Information Sciences
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• v.33 no.8C
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• pp.583-590
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• 2008

In this paper, we present a spatially adaptive post-processing algorithm for H.264 video coding standard to remove blocking artifacts. The loop filter of H.264 increases computational complexity of the encoder. Furthermore it doesn't clearly remove the blocking artifacts, resulting in over-blurring. For overcoming them, we combine the projection method with the Constraint Least Squares(CLS) method to restore the high quality image. To reflect the Human Visual System, we adopt the weight norm CLS method. Particularly pixel location-based local variance and laplacian operator are newly defined for the CLS method. In addition, the fact that correlation among adjoining pixels is high is utilized to constrain the solution space when the projection method is applied. Quantization Index(QP) of H.264 is also used to control the degree of smoothness. The simulation results show that the proposed post-processing filter works better than the loop filter of H.264 and converges more quickly than the CLS method.

• Journal of Advanced Navigation Technology
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• v.13 no.4
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• pp.523-531
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• 2009

In this study, we propose a joint source/channel rate control algorithm for video encoder targeting packet erasure channel. Based on the buffer constraints of video communication systems, encoding rate constraint is presented. After defining source distortion models for coded and skipped video frames and a channel distortion model for packet errors and their propagation, an average distortion model of received video is proposed for a given encoding window. Finally, we define an optimization problem to minimize the average distortion for given channel rates and packet loss rates by controlling spatio-temporal parameters of source video and FEC block sizes. Then, we propose a window-based algorithm to solve the problem in real-time.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.14 no.11
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• pp.4268-4289
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• 2020

Advanced traffic signal timing method plays very important role in reducing road congestion and air pollution. Reinforcement learning is considered as superior approach to build traffic light timing scheme by many recent studies. It fulfills real adaptive control by the means of taking real-time traffic information as state, and adjusting traffic light scheme as action. However, existing works behave inefficient in complex intersections and they are lack of feasibility because most of them adopt traffic light scheme whose phase sequence is flexible. To address these issues, a novel adaptive traffic signal timing scheme is proposed. It's based on actor-critic reinforcement learning algorithm, and advanced techniques proximal policy optimization and generalized advantage estimation are integrated. In particular, a new kind of reward function and a simplified form of state representation are carefully defined, and they facilitate to improve the learning efficiency and reduce the computational complexity, respectively. Meanwhile, a fixed phase sequence signal scheme is derived, and constraint on the variations of successive phase durations is introduced, which enhances its feasibility and robustness in field applications. The proposed scheme is verified through field-data-based experiments in both medium and high traffic density scenarios. Simulation results exhibit remarkable improvement in traffic performance as well as the learning efficiency comparing with the existing reinforcement learning-based methods such as 3DQN and DDQN.

• The Journal of the Korea institute of electronic communication sciences
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• v.12 no.2
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• pp.315-324
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• 2017

The smart grid with distributed power supply introduces a number of problems including not only the problems of the existing power grid but also the problem of protection co-operation due to new electric phenomenon because it has a mixed operation structure combining the existing radial operation structure and the new loop operation structure. The EMTP based power system analysis method has flexibility and convenience from the view of system configuration but it requires another experimental verification because of uncertainty of design and analysis results. On the other hand, the real demonstration system has difficulties in observing accurate fault on large scale system due to considerable economical and spatial construction cost, system configuration constraint, and it is difficult to demonstrate the distributed, autonomous and adaptive control strategy of smart grid. In this paper, a basic theory for a micro smart grid simulator design using MEMS(Micro Electro-Mechanical Systems) miniaturization technology is studied which can safely and freely experiment and observe electrical phenomena, and distribution, autonomous adaptive control strategy for disturbances on 22.9kV smart grid under minimum economic and spatial cost.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.9 no.5
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• pp.233-242
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• 2009

The security of medical information need continued research about steady and flexible security model because of privacy of patient's as well as directly relation in the patient's life. In particular, u-healthcare environment is need flexible and detailed access control by variety changes of context. Control model analyzed relation of resource and authority, and analyzed authority about all accessible resource from access point using K2BASE. The context-based access control model can change flexibly authority change and role, and can obtain resource of authority granted and meaningly connected resource. As a result, this thesis can apply flexible and adaptive access control model at u-healthcare domain which context change various.

• Journal of Korean Society of Transportation
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• v.18 no.5
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• pp.83-97
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• 2000

The traffic management schemes through traffic signal control and information provision could be effective when the link-level data and trip-level data were used simultaneously in analysis Procedures. But, because the trip-level data. such as origin, destination and departure time, can not be obtained through the existing surveillance systems directly. It is needed to estimate it using the link-level data which can be obtained easily. Therefore the objective of this study is to develop the model to estimate O-D demand using only the link flows in highway network as a real time. The methodological approaches in this study are kalman filer, least-square method and normalized least-square method. The kalman filter is developed in the basis of the bayesian update. The normalized least-square method is developed in the basis of the least-square method and the natural constraint equation. These three models were experimented using two kinds of simulated data. The one has two abrupt changing Patterns in traffic flow rates The other is a 24 hours data that has three Peak times in a day Among these models, kalman filer has Produced more accurate and adaptive results than others. Therefore it is seemed that this model could be used in traffic demand management. control, travel time forecasting and dynamic assignment, and so forth.

• The Transactions of the Korea Information Processing Society
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• v.4 no.7
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• pp.1770-1780
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• 1997

Our problem is improvement of image quality because it is inevitable cell loss of image data when traffic congestion occurs. If cells are discarded indiscriminately in transmission of MPEG video data, it occurs severe degradation in quality of service(QOS). In this paper, to solve this problem, we propose two method. The first, we analyze the traffic characteristics of an MPEG encoder and generate high priority and low priority data stream. During network congestion, only the least low priority cells are dropped, and this ensures that the high priority cells are successfully transmitted, which, in turn, guarantees satisfactory QoS. In this case, the prioritization scheme for the encoder assigns components of the data stream to each priority level based on the value of a parameter ${\beta}$. The second, Number of high priority cells are increased when value of ${\beta}$ is large. It occurs the loss of high priority cell in the congestion. To prevent it, this paper is regulated to data stream rate as buffer occupancy with UPC controller. Therefore, encoder's bandwidth can be calculated renegotiation of the encoder and networks. In this paper, the encoder's bandwidth requirements are characterized by a usage parameter control (UPC) set consisting of peak rate, burstness, and sustained rate. An adaptive encoder rate control algorithm at the Networks Interface Card(NIC) computes the necessary UPC parameter to maintain the user specified quality of service. Simulation results are given for a rate-controlled VBR video encoder operating through an ATM network interface which supports dynamic UPC. These results show that dynamic bandwidth renegotiation of prioritized data stream could provided bandwidth saving and significant quality gains which guarantee high priority data stream.