• Journal of Broadcast Engineering
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• v.12 no.2
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• pp.102-111
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• 2007

Currently, the efficient adaptive video streaming services and coding techniques are required to ensure quality of service (QoS) in diverse multimedia environments. To maintain optimal video quality in these environments, it is required to support scalable video coding (SVC) technique and proper QoS metric methods. In this paper, we propose a new quality metric that takes in to the temporal, the SNR, the spatial scalability on SVC. Experimental results shows that proposed method has a higher correlation with the subjective quality. We expect that the proposed metric plays an important role in deciding the coding parameter to optimize the quality of the SVC based video.

• Journal of KIISE:Software and Applications
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• v.36 no.8
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• pp.633-641
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• 2009

In this paper, we proposed a new pattern classifier which can be incrementally learned, be added new class in learning time, and handle with analog data. Proposed pattern classifier has hierarchical structure and the classification rate is improved by using different metric for each levels. Proposed model is based on the Gaussian ARTMAP which is an artificial neural network model for the pattern classification. We hierarchically constructed the Gaussian ARTMAP and proposed the Principal Component Emphasis(P.C.E) method to be learned different features in each levels. And we defined new metric based on the P.C.E. P.C.E is a method that discards dimensions whose variation are small, that represents common attributes in the class. And remains dimensions whose variation are large. In the learning process, if input pattern is misclassified, P.C.E are performed and the modified pattern is learned in sub network. Experimental results indicate that Hierarchical Gaussian ARTMAP yield better classification result than the other pattern recognition algorithms on variable data set including real applicable problem.

• The KIPS Transactions:PartC
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• v.12C no.4 s.100
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• pp.543-550
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• 2005

Many routing algorithms, proposed for ad-hoc wireless networks, we based on source routing scheme and shortest path route has short lifetime especially in highly dense ad-hoc wireless networks. So some routing protocols such as SSA and ABR are considering the link stability and try finding more stable route. In this paper we propose a new routing algorithm considering utilization metric based on SSA routing algerian in Ad-Hoc networks. To reduce the bottleneck by specific metric of SSA, proposed scheme makes load balancing in networks by distributing the connections to several routes. For the evaluation of the performance we compare our scheme with existent routing protocol AODV and SSA. And the results, obtained using the ns-2 network simulation platform, show good performance that reduced the number of reconstructions remarkably by distributing the whole traffic to several routes when there are several stable routes.

• Journal of Convergence for Information Technology
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• v.10 no.10
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• pp.65-70
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• 2020

With the appearance of Bitcoin that builds peer-to-peer networks for transaction of digital content and issuance of cryptocurrency, lots of blockchain networks have been developed to improve transaction performance. Recently, Joseph Lubin discussed Decentralization Transaction per Second (DTPS) against alleviating the value of biased TPS. However, this Lubin's trust model did not enough consider a security issue in scalability trilemma. Accordingly, we proposed a trust metric based on blockchain size, stale block rate, and average block size, using a sigmoid function and convex optimization. Via numerical analysis, we presented the optimal blockchain size of popular blockchain networks and then compared the proposed trust metric with the Lubin's trust model. Besides, Bitcoin based blockchain networks such as Litecoin were superior to Ethereum for trust satisfaction and data volume.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.42 no.1
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• pp.31-38
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• 2017

In this paper, we have designed MIMO system using F-OFDM modulation. And then, we have evaluated and analyzed synchronization performance of the system. In this paper we have considered Schmidl's method, Minn's method, and Park's method. As simulation results, Schmidl's method has wide plateau of timing metric and Park's method has impulse-shape timing metric. Also, we can confirm that timing metric characteristic of synchronization estimator can be degraded by adjusting filter length of F-OFDM system. Especially, we can confirm that timing metric of synchronization estimator is shifted according to filter length of MIMO system using F-OFDM modulation and this timing metric movement can be compensated by using designed filter length.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.20 no.1
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• pp.171-176
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• 2020

Reinforcement learning is a well-known method for training an artificial software agent for a video game. Even though many reinforcement learning algorithms have been proposed, their performance was varies depending on an application area. This paper compares the performance of the algorithms when we train our reinforcement learning agent for a 2D racing game. We defined performance metrics to analyze the results and plotted them into various graphs. As a result, we found ACER (Actor Critic with Experience Replay) achieved the best rewards than other algorithms. There was 157% gap between ACER and the worst algorithm.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2011.10a
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• pp.646-649
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• 2011

Differential detection algorithm for DBO-CSS based on maximum signal energy detection (MSED) using viterbi algorithm is proposed. In order to mitigate SNR degradation caused by differential decoding, a modified viterbi algorithm with so called correlation metric (CM) in every state is proposed. It is shown that the performance gain of the proposed algorithm when compared with that of the conventional differential detection with the block decoding algorithm is about 2.5dB at BER = $10^{-5}$.

• Journal of KIISE
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• v.42 no.8
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• pp.1057-1064
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• 2015

The tactical network is system based on wireless networking technologies that ties together surveillance reconnaissance systems, precision strike systems and command and control systems. Several alternative paths exist in the network because it is connected as a grid to improve its survivability. In addition, the network topology changes frequently as forces and combatants change their network access points while conducting operations. However, most Internet routing standards have been designed for use in stable backbone networks. Therefore, tactical networks may exhibit a deterioration in performance when these standards are implemented. In this paper, we propose Priority based Multi-Path routing with Local Optimization(PMPLO) for a tactical backbone network. The PMPLO separately manages the global and local metrics. The global metric propagates to other routers through the use of a routing protocol, and it is used for a multi-path configuration that is guaranteed to be loop free. The local metric reflects the link utilization that is used to find an alternate path when congestion occurs, and it is managed internally only within each router. It also produces traffic that has a high priority privilege when choosing the optimal path. Finally, we conducted a simulation to verify that the PMPLO can effectively distribute the user traffic among available routers.

• The Journal of the Korea Contents Association
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• v.10 no.6
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• pp.134-143
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• 2010

This paper proposes a framework for classifying metric-based software quality prediction models, especially case of software criticality, into four types. Models are classified along two vectors: input metric forms and the necessity of past project data. Each type has its own characteristics and its strength and weakness are compared with those of other types using newly defined criteria. Through this qualitative evaluation each organization can choose a proper model to suit its environment. My earlier studies of criticality prediction model implemented specific models in each type and evaluated their prediction performances. In this paper I analyze the experimental results and show that the characteristics of a model type is the another key of successful model selection.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2002.05a
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• pp.568-573
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• 2002

In this paper, the Viterbi decoder containing new branch metrics of the squared Euclidean distance with multiple order phase differences is introduced in order to improve the bit error rate (BER) in the differential detection of the trellis-coded MDPSK-OFDM. The proposed Viterbi decoder is conceptually same as the Continuous multiple phase differential detection method that uses the branch metric with multiple phase differences. Also, we describe the Viterbi algorithm in order to use this branch metrics. Our study shows that such a Viterbi decoder improves BER performance without sacrificing bandwidth and power efficiency Also. the proposed algorithm ran be used in the single carrier modulation.