• Journal of the Institute of Electronics and Information Engineers
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• v.51 no.5
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• pp.51-57
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• 2014

In this paper, we introduce the adaptive threshold detection scheme based on an evolutionary arithmetic algorithm for the M-ary holographic data storage(HDS) system. The genetic algorithm is a particular class of evolutionary arithmetic based on the process of biological evolution, which is a very promising technique for optimization problem and estimation applications. In this study, to improve the detection performance that is degraded by the HDS channel environment and the pixel misalignment, the threshold value was assumed to be a population set of the evolutionary algorithm. The proposed method can find an appropriate population set of bit threshold, which minimizes bit error rate(BER) as increased generation. For performance evaluation, we consider severe misalignment effect in the 4-ary holographic data storage system. Furthermore, we measure the BER performance and compare the proposed methods with the conventional threshold detection scheme, which verifies the superiority of the proposed scheme.

• Journal of Broadcast Engineering
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• v.16 no.1
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• pp.123-132
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• 2011

Recently, DVC (Distributed Video Coding) is receiving a lot of attention as one of the low complexity video encoding techniques suitable for various applications with computation-limited and/or power-limited environment, and is being actively studied for improving the coding efficiency. This paper proposes a rate-distortion based selective block encoding scheme. First, the motion information is obtained in the process of generating side information at decoder and received through the feedback channel, and then, based on this information, the proposed method performs a selective block encoding based on rate-distortion optimization. Experimental results show that the performance of the proposed scheme reaches up to 2.2 dB PSNR gain over the existing scheme. Moreover, it is shown that the complexity can be reduced by encoding parts of region considering rate-distortion cost.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.2 no.1
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• pp.23-35
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• 2008

Mobile IP (MIP) is the solution supporting the mobility of Mobile Nodes (MNs), however, it is known to lack the support for NEtwork MObility (NEMO). NEMO manages situations when an entire network, composed of one or more subnets, dynamically changes its point of attachment to the Internet. NEMO Basic Support (NBS) protocol ensures session continuity for all the nodes in a mobile network, however, there exists a serious pinball routing problem. To overcome this weakness, there are many Route Optimization (RO) solutions such as Bi-directional Tunneling (BT) mechanism, Aggregation and Surrogate (A&S) mechanism, Recursive Approach, etc. The A&S RO mechanism is known to outperform the other RO mechanisms, except for the Binding Update (BU) cost. Although Improved Prefix Delegation (IPD) reduces the cost problem of Prefix Delegation (PD), a well-known A&S protocol, the BU cost problem still presents, especially when a large number of Mobile Routers (MRs) and MNs exist in the environment such as train, bus, ship, or aircraft. In this paper, a solution to reduce the cost of delivering the BU messages is proposed using a multicast mechanism instead of unicasting such as the traditional BU of the RO. The performance of the proposed multicast-based BU scheme is examined with an analytical model which shows that the BU cost enhancement is up to 32.9% over IPDbased, hence, it is feasible to predict that the proposed scheme could benefit in other NEMO RO protocols.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.46 no.2
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• pp.65-74
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• 2009

In optimizing the neural network structure, there are two methods of the pruning scheme and the constructive scheme. In this paper we use the pruning scheme to optimize neural network structure, and the genetic algorithm to find out its optimum node pruning. In the conventional researches, the input and hidden layers were optimized separately. On the contrary we attempted to optimize the two layers simultaneously by encoding two layers in a chromosome. The offspring networks inherit the weights from the parent. For teaming, we used the existing error back-propagation algorithm. In our experiment with various databases from UCI Machine Learning Repository, we could get the optimal performance when the network size was reduced by about $8{\sim}25%$. As a result of t-test the proposed method was shown better performance, compared with other pruning and construction methods through the cross-validation.

• The KIPS Transactions:PartA
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• v.13A no.6 s.103
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• pp.501-510
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• 2006

The self-organizing super peer ring P2P search scheme improves search performance of the existing unstructured peer-to-peer systems, in which super peers with high capacity constitute a ring structure and all peer in the system utilize the ring for publishing or querying their keys. In this paper, we further improves the performance of the self-organizing ring by adaptively changing its super peer ratio according to the status of the entire system. By using PSO, the optimized super peer ratio can be maintained within the system. Through simulations, we show that our self-organizing super peer ring optimized by PSO outperforms not only the fixed super peer ring but also the self-organizing super ring with fixed ratio in the aspect of query success rate.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.37A no.9
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• pp.762-771
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• 2012

In this paper, we propose an adaptive power control scheme employing a self-optimization concept in femtocell systems, in order to improve system capacity, thereby reducing call-drop probability. In the proposed scheme, each femto base station(FBS) controls individual channel's transmission power base on two parameters; the neighboring cell's transmission power for each individual channel which is delivered from a femto-gateway and the received power strength from neighboring cells which is periodically measured by means of a spectrum sensing. Adaptive adjustment of individual channel's transmission power in accordance with femto mobile station(FMS) mobility features can also reduce undesirable handovers and evenly distribute traffic load over all femtocells. In addition, the manipulative control of channel's transmission power is able to keep the system coverage and the call-drop probability within an acceptable range, regardless of density of femtocells. Computer simulation shows that the proposed scheme outperforms existing schemes in terms of the system coverage and the call-drop probability.

• Wind and Structures
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• v.30 no.4
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• pp.325-338
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• 2020

In this paper, the improvement of the anti-snow performance of a high-speed train (HST) is studied using the unsteady Reynolds-Averaged Navier-Stokes simulations (URANS) coupled with the Discrete Phase Model (DPM). The influences of the proposed flow control scheme on the velocity distribution of the airflow and snow particles, snow concentration level and accumulated mass in the bogie cavities are analyzed. The results show that the front anti-snow structures can effectively deflect downward the airflow and snow particles at the entrance of the cavities and alleviate the strong impact on the bogie bottom, thereby decrease the local accumulated snow. The rotational rear plates with the deflecting angle of 45° are found to present well deflecting effect on the particles' trajectories and force more snow to flow out of the cavities, and thus significantly reduce the accretion distribution on the bogie top. Furthermore, running speeds of HST are shown to have a great effect on the snow-resistance capability of the flow control scheme. The proposed flow control scheme achieves more snow reduction for HST at higher train's running speed in the cold regions.

• Journal of the Korea Society of Computer and Information
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• v.12 no.5
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• pp.139-144
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• 2007

The mobile terminal's frequent changes to the access point introduce significant network overhead in mobile IP networks. To solve this problem, we introduce a hierarchical structure with consideration given to the dynamic value of neighbor scope in IP regional registration[1]. When a mobile terminal moves within the neighbor given by the scope value, it makes registration locally without registration with its home agent. We analyze the algorithm mathematically and show the numerical results. As a result, optimization of the scope value for the localized registration under the hierarchical structure makes the proposed scheme outperform the standard mobile IP protocol[2]. This can be explained from the fact that there is only local registration for terminal's movement within the scope region. Moreover, as the signaling cost for home agent increases, the proposed scheme becomes more advantageous.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 1998.10a
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• pp.211-217
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• 1998

Many practical control problems for the complex, uncertain or large-scale plants, need to simultaneously achieve a number of objectives, which may conflict or compete with each other. If the conventional optimization methods are applied to solve these control problems, the solution process may be time-consuming and the resulting solution would ofter lose its original meaning of optimality. Nevertheless, the human operators usually performs satisfactory results based on their qualitative and heuristic knowledge. In this paper, we investigate the control strategies of the human operators, and propose a fuzzy model-based multi-objective satisfactory controller. We also apply it to the automatic train operation(ATO) system for the magnetically levitated vehicles(MAGLEV). One of the human operator's strategies is to predict the control result in order to find the meaningful solution. In this paper, Takagi-Sugeno fuzzy model is used to simulated the prediction procedure. Another str tegy is to evaluate the multiple objectives with respect to their own standards. To realize this strategy, we propose the concept of a satisfactory solution and a satisfactory control scheme. The MAGLEV train is a typical example of the uncertain, complex and large-scale plants. Moreover, the ATO system has to satisfy multiple objectives, such as seed pattern tracking, stop gap accuracy, safety and riding comfort. In this paper, the speed pattern tracking controller and the automatic stop controller of the ATO system is designed based on the proposed control scheme. The effectiveness of the ATO system based on the proposed scheme is shown by the experiments with a rotary test bed and a real MAGLEV train.

• Journal of the Korea Society of Computer and Information
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• v.11 no.3
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• pp.141-149
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• 2006

In this paper, we introduce an improved algorithm for computing matrix triple product that commonly arises in primal-dual optimization method. In computing $P=AHA^{t}$, we devise a single pass algorithm that exploits the block diagonal structure of the matrix H. This one-phase scheme requires fewer floating point operations and roughly half the memory of the generic two-phase algorithm, where the product is computed in two steps, computing first $Q=HA^{t}$ and then P=AQ. The one-phase scheme achieved speed-up of 2.04 on Intel Itanium II platform over the two-phase scheme. Based on memory latency and modeled cache miss rates, the performance improvement was evaluated through performance modeling. Our research has impact on performance tuning study of complex sparse matrix operations, while most of the previous work focused on performance tuning of basic operations.