• Journal of the Korea Institute of Information and Communication Engineering
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• v.13 no.12
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• pp.2719-2730
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• 2009

In this paper, we implement the measurement functionality for performance measurements of EDGE (Enhanced Data Rates for GSM Evolution) terminal by using software. Generally speaking, the receiving algorithms in normal MODEM cannot be used directly to a measurement system due to the lack of accuracy. Therefore, we propose a new receiver algorithm for precise EDGE signal measurements. In the proposed algorithm, 2-stage (coarse stage, fine stage) parameters estimation (symbol-timing, frequency offset, carrier phase) scheme is used. To improve the estimation accuracy, we increase the number of the received signal samples by interpolation. The proposed EDGE signal measurement algorithm can be used for verifying the hardware measurement system, and also can be used for the commercial systems through software optimization.

• Journal of Navigation and Port Research
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• v.31 no.10
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• pp.869-877
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• 2007

This paper proposes a realtime scheduling method using local search algorithm for non-crossable yard cranes in automated container terminal. To take into consideration the dynamic property of yard crane operation and satisfy the real time constraint, the proposed method repeatedly builds crane schedule for the jobs in a fixed length look-ahead horizon whenever a new job is requested In addition, the proposed method enables the co-operation between yard cranes through prior re-handling and re-positioning in order to resolve the workload imbalance problem between the two cranes, which is one of the primary causes that lower the performance of yard cranes. Simulation-based experiments have shown that the proposed method outperforms the heuristic based methods, and the cooperation scheme contributes a lot to the performance improvement.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.14 no.5
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• pp.1193-1200
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• 2010

This paper presents a new adaptive macroblock quantization algorithm which generates the output bits corresponding to the target bit budget. The H.264 standard uses various coding modes and optimization methods to improve the compression performance, which makes it difficult to control the amount of the generated traffic accurately. In the proposed scheme, linear regression analysis is used to analyze the relationship between the bit rate of each macroblock and the quantization parameter and to predict the MAD values. Using the predicted values, the quantization parameter of each macroblock is determined by the Lagrange multiplier method and then modified according to the difference between the bit budget and the generated bits. It is shown by experimental results that the new algorithm can generate output bits accurately corresponding to the target bit rates.

• KIPS Transactions on Computer and Communication Systems
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• v.1 no.2
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• pp.99-102
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• 2012

The performance of P2P application services may be improved by reducing unnecessary inter-network traffic through intelligent peer selection. However, since a logical link between peers in a P2P overlay network is composed of a set of physical links in an underlay network, the traffic pattern determined by the sending rates of selected peers imposes loads on each underlay links. Thus, if the sending rates are not determined carefully, the loads between underlay links may not be balanced, which means some links are underloaded while the other links are congested. In this paper, we take an optimization approach to determine the sending rates of peers strategically to avoid the inefficient use of underlay links. The proposed scheme also guarantee the minimum receiving rates of peers while minimizing the maximum link utilization of underlay links, which is beneficial both to P2P applications and an underlay network.

• The KIPS Transactions:PartD
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• v.14D no.5
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• pp.459-470
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• 2007

A data stream is a massive unbounded sequence of data elements continuously generated at a rapid rate. Query processing for such a data stream should also be continuous and rapid, which requires strict time and space constraints. In most DSMS(Data Stream Management System), the selection predicates of continuous queries are grouped or indexed to guarantee these constraints. This paper proposes a new scheme tailed an ASC(Attribute Selection Construct) that collectively evaluates selection predicates containing the same attribute in multiple continuous queries. An ASC contains valuable information, such as attribute usage status, partially pre calculated matching results and selectivity statistics for its multiple selection predicates. The processing order of those ASC's that are corresponding to the attributes of a base data stream can significantly influence the overall performance of multiple query evaluation. Consequently, a method of establishing an efficient evaluation order of multiple ASC's is also proposed. Finally, the performance of the proposed method is analyzed by a series of experiments to identify its various characteristics.

• KIPS Transactions on Computer and Communication Systems
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• v.7 no.8
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• pp.203-210
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• 2018

Mobile traffic is increasing consistently, and mobile carriers are becoming more and more hard to meet this ever-increasing mobile traffic demand by means of additional installation of base stations. To overcome this problem, heterogeneous networks, which can reuse space and frequency by installing small cells such as femto cells in existing macro cells, were introduced. However, existing macro cell users are difficult to increase the spectral efficiency without the cooperation of femto owners. Femto owners are also reluctant to accommodate other mobile stations in their femto stations without proper incentive. In this paper, a method of obtaining the optimal incentive is proposed, which adopts a utility function based on the logarithm of throughput of mobile stations, and the incentive is calculated to maximize the utility of the entire network.

• The KIPS Transactions:PartB
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• v.11B no.2
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• pp.207-212
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• 2004

This paper presents a reinforcement learning framework for stock trading systems. Trading system parameters are optimized by Q-learning algorithm and neural networks are adopted for value approximation. In this framework, cooperative multiple agents are used to efficiently integrate global trend prediction and local trading strategy for obtaining better trading performance. Agents Communicate With Others Sharing training episodes and learned policies, while keeping the overall scheme of conventional Q-learning. Experimental results on KOSPI 200 show that a trading system based on the proposed framework outperforms the market average and makes appreciable profits. Furthermore, in view of risk management, the system is superior to a system trained by supervised learning.

• The Transactions of the Korea Information Processing Society
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• v.5 no.3
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• pp.671-680
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• 1998

Network services, such as teleconferencing, remote diagnostics and education, and CSCW require multicasting. Multicast routing methods can be divided into two categories. One is the shortest path tree method and the other is the minimal Steiner tree method. The latter has an advantage over the former in that only one Steiner tree is needed for a group. However, finding a minimal Steiner tree is an NP-complete problem and it is necessary to find an efficient heuristic algorithm. In this paper, we present an evolutionary optimization method for finding minimal Steiner trees without sacrificing too much computational efforts. In particular, we describe a tree-based genetic encoding scheme which is in sharp constast with binary string representations usually adopted in convetional genetic algorithms. Experiments have been performed to show that the presented method can find optimal Steiner trees for given vetwork configurations. Comparitivie studies have shown that the evolutionary method finds on average a better solution than other conventional heustric algorithms.

• Environmental and Resource Economics Review
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• v.11 no.2
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• pp.211-231
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• 2002

This paper summarizes the results of a study that assess how a demand side management (DSM) system addresses key economic and environmental challenges facing in the Korean natural gas sector considering; ${\bullet}$ high discrepancies of seasonal consumption volume and of load factor in unmatured domestic LNG market, ${\bullet}$ unfavorable and volatile international LNG market, imposing with the contestable "take-or-pay" contract terms, ${\bullet}$ low profile of LNG and existence of market barriers against an optimal fuel mix status in the industrial energy sector. A particular focus of this study is to establish an 'extended' DSM system in the unmatured gas market, especially in industry sector, that could play a key role to assure an optimum fuel mix scheme. Under the concept of 'extended' DSM, a system dynamics modeling approach has been introduced to explore the option to maximize economic benefits in terms of the national energy system optimization, entailing different ways of commitments accounting for different DSM measures and time delay scenarios. The study concludes that policy options exist that can reduce inefficiencies in gas industry and end-use system at no net costs to national economy. The most scenarios find that, by the year 2015, it is possible to develop a substantial potential of increased industrial gas end-uses under more reliable and stable load patterns. Assessment of sensitivity analysis suggests that time delay factor, in formulating DSM scenarios, plays a key role to overcome various market barriers in domestic LNG market and provides a strong justification for the policy portfolios 'just in time' (time accurateness), which eventually contribute to establish an optimum fuel mix strategy. The study indicates also the needs of advanced studies based on SD approach to articulate uncertainty in unmatured energy market analysis, including gas.

• Journal of Electrical Engineering and Technology
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• v.13 no.3
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• pp.1043-1051
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• 2018

The coordination of directional overcurrent relay (DOCR) is employed in this work, considering gray wolf optimizer (GWO), a recently designed optimizer that employs the hunting and leadership attitude of gray wolves for searching a global optimum. In power system protection coordination problem, the objective function to be optimized is the sum of operating time of all the main relays. The coordination of directional overcurrent relays is formulated as a linear programming problem. The proposed optimization technique aims to minimize the time dial settings (TDS) of the relays. The calculation of the Time Dial Setting (TDS) setting of the relays is the core of the coordination study. In this article two case studies of IEEE 6-bus system and IEEE 30-bus system are utilized to see the efficiency of this algorithm and the results had been compared with the other algorithms available in the reference and it was observed that the proposed scheme is quite competent for dealing with such problems. From analyzing the obtained results, it has been found that the GWO approach provides the most globally optimum solution at a faster convergence speed. GWO has achieved a lot of relaxation due to its easy implementation, modesty and robustness. MATLAB computer programming has been applied to see the effectiveness of this algorithm.