• Journal of the Institute of Electronics Engineers of Korea SD
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• v.46 no.4
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• pp.28-36
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• 2009

Sequence-Pair(SP) model represents the topological relation between modules. In general, SP model based floorplanners search solutions using Simulated-Annealing(SA) algorithm. Several SA based floorplanning techniques using SP model have been published. To improve the performance of those techniques they tried to improve the speed for evaluation function for SP model, to find better scheduling methods and perturb functions for SA. In this paper we propose a two phase SA based algorithm. In the first phase, white space between modules is reduced by applying compaction technique to the floorplan obtained by an SP. From the compacted floorplan, the corresponding SP is determined. Solution space has been searched by changing the SP in the SA framework. When solutions converge to some threshold value, the first phase of the SA based search stops. Then using the typical SA based algorithm, ie, without using the compaction technique, the second phase of our algorithm continues to find optimal solutions. Experimental results with MCNC benchmark circuits show that how the proposed technique affects to the procedure for SA based floorplainning algorithm and that the results obtained by our technique is better than those obtained by existing SA-based algorithms.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.26 no.10
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• pp.1517-1524
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• 2022

In this paper, we consider a heterogeneous network (HetNet) consisting of one macro base station and multiple small base stations, and assume the coordinated multi-point transmission between the base stations. In addition, we assume that the channel between the base station and the user consists of path loss and Rayleigh fading. Under these assumptions, we present the energy efficiency (EE) achievable by the user for a given base station and we formulate an optimization problem of dynamic cell selection and transmit power allocation to maximize the total EE of the HetNet. In this paper, we propose an unsupervised deep learning method to solve the optimization problem. The proposed deep learning-based scheme can provide high EE while having low complexity compared to the conventional iterative convergence methods. Through the simulation, we show that the proposed dynamic cell selection scheme provides higher EE performance than the maximum signal-to-interference-plus-noise ratio scheme and the Lagrangian dual decomposition scheme, and the proposed transmit power allocation scheme provides the similar performance to the trust region interior point method which can achieve the maximum EE.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.23 no.2
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• pp.157-172
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• 2024

Autonomous driving technology, when commercialized, has the potential to improve the safety, mobility, and environmental performance of transportation networks. However, safe autonomous driving may be hindered by poor sensor performance and limitations in long-distance detection. Therefore, cooperative autonomous driving that can supplement information collected from surrounding vehicles and infrastructure is essential. In addition, since HDVs, AVs, and CAVs have different ranges of perceivable information and different response protocols, countermeasures are needed for mixed traffic that occur during the transition period of autonomous driving technology. There is a lack of research on traffic flow optimization that considers the penetration rate of autonomous vehicles and the different characteristics of each road segment. The objective of this study is to develop weights based on safety, operational, and environmental factors for each infrastructure control use case and autonomous vehicle MPR. To develop an integrated evaluation index, infra-guidance AHP and hybrid AHP weights were combined. Based on the results of this study, it can be used to give right of way to each vehicle to optimize mixed traffic.

• Journal of the Korea Society of Computer and Information
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• v.16 no.5
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• pp.23-31
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• 2011

Improving system boot time has become one of the most important issues in the system software arena. As Linux is widely used in the embedded system environment, extensive research has been conducted in order to mitigate Linux boot time delay. In this respect, this paper mainly focuses on the Hibernation-based boot mechanism, which is the boot mechanism based on Hibernation, as an alternative to the conventional boot sequence. The contributions of this work are as follows. First, we implement the Hibernation-based boot mechanism on a real embedded Linux system and describe the implementation details. Second, we observe the Hibernation-based boot procedures so that we can investigate the possibility whether the boot mechanism has room for improvement in terms of the boot time. Through the in-depth observation and analysis based on the real implementation, we anticipate that the Hibernation-based boot mechanism which adopts various optimization methods can provide maximum of 3.1 times faster booting performance compared to the conventional way.

• Journal of the Korea Society of Computer and Information
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• v.27 no.5
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• pp.101-107
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• 2022

Modeling and simulation is a technique used for operational verification, performance analysis, operational optimization, and prediction of target systems. Discrete Event System Specification (DEVS) of this representative technology defines models with a strict formalism and stratifies the structures between the models. When the atomic DEVS models operate with an intention different the target system, the simulation may lead to erroneous decision-making. However, most DEVS systems have the exclusion of the model test or provision of the manual test, so developers spend a lot of time verifying the atomic models. In this paper, we propose a script-based automated test system for accurate and fast validation of atomic models in Python-based DEVS. The proposed system uses both the existing method of manual testing and the new method of the script-based testing. As Experimental results in our system, the script-based test method was executed within 24 millisecond when the script was executed 10 times consecutively. Thus, the proposed system guarantees a fast verification time of the atomic models in our script-based test and improves the reusability of the test script.

• Journal of Ship and Ocean Technology
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• v.11 no.2
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• pp.10-25
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• 2007

With the sharp increase of the oil price, the issue of the energy saving requires even higher propulsive efficiency of the propellers. Traditionally the propellers have been designed with the criteria such as that of Lerbs optimum based on the lifting line theory and the empirical formulae of Lerbs and van Manen giving relations of the wake pitch with the wake non-uniformity. With the aid of the high speed computer, it is now possible to apply the time-consuming iterative approaches for the solution of the lifting surface problems. In this paper we formulate the variational problem to optimize the efficiency of the propeller operating in the given ship wake using the lifting surface method. The variational formulation relating the spanwise circulation distribution with the propulsive efficiency to be maximized is however non-linear in circulation distribution functions, thus the iterative method is applied to the quasi-linearized equations. The blade shape design also requires the iterative procedures, because the shape of the blade which is represented by the lifting surface is unknown a priori. The numerical code was validated with the DTNSRDC propeller 4119 which is well-known to be optimum in uniform inflow condition. In addition existing (well-designed) commercial propellers were selected and compared with the results of the open water tests and the self-propulsion tests.

• Journal of KIISE:Computing Practices and Letters
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• v.14 no.1
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• pp.13-21
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• 2008

In general, data communication among sensor nodes requires more energy than internal processing or sensing activities. In this paper, we propose a noble technique to reduce the number of packet transmissions necessary for sending/receiving queries/results among neighboring nodes with the help of context-aware routing tables. The important information maintained in the context-aware routing table is which physical properties can be measured by descendent nodes reachable from the current node. Based on the information, the node is able to eliminate unnecessary packet transmission by filtering out the child nodes for query dissemination or result relaying. The simulation results show that up to 80% of performance gains can be achieved with our technique.

• Journal of the Korean Data and Information Science Society
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• v.23 no.5
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• pp.881-893
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• 2012

This paper proposes to develop system trading strategy using rough set, decision tree in futures market. While there is a great deal of literature about the analysis of data mining, there is relatively little work on developing trading strategies in futures markets. There are three objectives in this paper. The first objective is to analysis performance of decision tree in rule-based system trading. The second objective is to find proper profitable trading interval. The last objective is to find optimized training period of trading rule training. The results of this study show that proposed model is useful trading strategy in foreign exchange market and can be desirable solution which gives lots of investors an important investment information.

• Journal of the Institute of Electronics and Information Engineers
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• v.53 no.7
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• pp.3-8
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• 2016

We propose a modified form of the decision-directed least mean square (DD LMS) algorithm that is widely used in the optimization of self-adaptive equalizers, and show the modified version greatly improves the initial convergence properties of the conventional algorithm. Existing DD LMS regards the difference between a equalizer output and a quantization value for it as an error, and achieves an optimization of the equalizer based on minimizing the mean squared error cost function for the equalizer coefficients. This error generating method is useful for binary signal or a single-level signals, however, in the case of multi-level signals, it is not effective in the initialization of the equalizer. The modified DD LMS solves this problem by modifying the error generation. We verified the usefulness and performance of the modified DD LMS through experiments with multi-level signals under distortions due to intersymbol interference and additive noise.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.44 no.3
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• pp.23-32
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• 2007

The H.264/AVC video coding standard uses rate distortion optimization (RDO) method to improve the compression performance in the intra prediction. The complexity and computational load are increased more than previous standard by using this method, even though this standard selects the best coding mode for the current macroblock. This paper proposes a fast intra mode decision algorithm for H.264/AVC encoder based on dominant edge direction (DED). To apply the idea, this algorithm uses the approximation of discrete cosine transform (DCT) coefficient. By detecting the DED, 3 modes instead of 9 modes are chosen for RDO calculation to decide the best mode in the $4{\times}4$ luma block. As for the $16{\times}16$ luma and $8{\times}8$ chroma block, instead of 4 modes, only 2 modes are searched. Experimental results show that the computation time of the proposed algorithm is decreased to about 72% of the full search method with negligible quality loss.