• Journal of the Korean Society for Precision Engineering
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• v.14 no.9
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• pp.139-145
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• 1997

This study is concerned with the optimizing method of control parameters for a hydraulic speed control system by using genetic algorithms which are general purpose search algorithms based on natural evolution and genetics. It is shown that the genetic altorithms satisfactorily oiptimized control gains of the PI speed control system of an electrohydraulic servomotor and that optimization of control para- meters can be achived without much experience and knowledge for tuning. It is also shown that optimal gains may be determined from fitness distribution curves plotted in given gain spaces.

• Proceedings of the Korean Society of Computer Information Conference
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• 2021.01a
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• pp.283-284
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• 2021

본 논문에서는 서로 다른 진화 전략의 병렬화를 구현하기 위해 섬 모델을 도입하고 자원 간의 균형을 유지하기 위해 Monod 모델을 활용하는 PDE-EM이라는 생태 모델 알고리즘을 기반으로 한 새로운 병렬 DE를 제안하도록 한다. 각 섬은 동일한 자원으로 서로 다른 전략으로 진화한다. 지정된 세대 수마다 섬의 진화 정도에 따라 등급이 매겨지고, Monod 모델을 활용하여 각 섬에 다양한 자원이 할당된다.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2022.10a
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• pp.416-417
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• 2022

In this paper, we propose a hybrid DE based on an ecological model algorithm called SparkHDE-EM. This model implements the parallelization of various DE variants by introducing an island model based on Spark, and utilizes the Monod model to maintain a balance between resources.

• The Bulletin of The Korean Astronomical Society
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• v.46 no.1
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• pp.58.4-59
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• 2021

This presentation introduces Korea's SNIPE (Small scale magNespheric and Ionospheric Plasma Experiment) mission, formation flying CubeSat constellation. Observing particles and waves on a single satellite suffers from inherent space-time ambiguity. To observe spatial and temporal variations of the micro-scale plasma structures on the topside ionosphere, four 6U CubeSats (~ 10 kg) will be launched into a polar orbit of the altitude of ~500 km in 2021. The distances of each satellite will be controlled from 10 km to more than 100 km by formation flying algorithm. The SNIPE mission is equipped with identical scientific instruments, solid-state telescope, magnetometer, and Langmuir probe. All the payloads have a high temporal resolution (sampling rates of about 10 Hz). Iridium modules provide an opportunity to upload changes in operational modes when geomagnetic storms occur. SNIPE's observations of the dimensions, occurrence rates, amplitudes, and spatiotemporal evolution of polar cap patches, field-aligned currents (FAC), radiation belt microbursts, and equatorial and mid-latitude plasma blobs and bubbles will determine their significance to the solar wind-magnetosphere-ionosphere interaction and quantify their impact on space weather.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.12 no.4
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• pp.1638-1654
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• 2018

The heterogeneous network (HetNet) has been one of the key technologies in Long Term Evolution-Advanced (LTE-A) with growing capacity and coverage demands. However, the introduction of femtocells has brought serious co-layer interference and cross-layer interference, which has been a major factor affecting system throughput. It is generally acknowledged that the resource allocation has significant impact on suppressing interference and improving the system performance. In this paper, we propose a hybrid-clustering algorithm based on the $Mat{\acute{e}}rn$ hard-core process (MHP) to restrain two kinds of co-channel interference in the HetNet. As the impracticality of the hexagonal grid model and the homogeneous Poisson point process model whose points distribute completely randomly to establish the system model. The HetNet model based on the MHP is adopted to satisfy the negative correlation distribution of base stations in this paper. Base on the system model, the spectrum sharing problem with restricted spectrum resources is further analyzed. On the basis of location information and the interference relation of base stations, a hybrid clustering method, which takes into accounts the fairness of two types of base stations is firstly proposed. Then, auction mechanism is discussed to achieve the spectrum sharing inside each cluster, avoiding the spectrum resource waste. Through combining the clustering theory and auction mechanism, the proposed novel algorithm can be applied to restrain the cross-layer interference and co-layer interference of HetNet, which has a high density of base stations. Simulation results show that spectral efficiency and system throughput increase to a certain degree.

• Journal of Korea Multimedia Society
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• v.21 no.2
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• pp.188-198
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• 2018

With recent development of high-speed wide-area wireless networks and wide spread of highperformance wireless devices, the demand on seamless video streaming services in Long Term Evolution (LTE) network environments is ever increasing. To meet the demand and provide enhanced Quality of Experience (QoE) with mobile users, the Dynamic Adaptive Streaming over HTTP (DASH) has been actively studied to achieve QoE enhanced video streaming service in dynamic network environments. However, the existing DASH algorithm to select the quality of requesting video segments is based on a procedural algorithm so that it reveals a limitation to adapt its performance to dynamic network situations. To overcome this limitation this paper proposes a novel quality selection mechanism based on a Deep Q-Network (DQN) model, the DQN-based DASH ABR($DQN_{ABR}$) mechanism. The $DQN_{ABR}$ mechanism replaces the existing DASH ABR algorithm with an intelligent deep learning model which optimizes service quality to mobile users through reinforcement learning. Compared to the existing approaches, the experimental analysis shows that the proposed solution outperforms in terms of adapting to dynamic wireless network situations and improving QoE experience of end users.

• Journal of Korean Tunnelling and Underground Space Association
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• v.18 no.2
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• pp.183-193
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• 2016

Estimation of the stability of an operating tunnel through a back analysis is a difficult concept to analyze. Specially, when a relatively thick lining is constructed as in case of a subsea tunnel, there will be a limit to the use of displacement-based tunnel back analysis because the corresponding displacement is too small. In this study, DEA is adopted for tunnel back analysis and the feasibility of DEA for back analysis is evaluated. It is implemented in the finite difference code FLAC3D using its built-in FISH language. In addition, the stability of a tunnel lining will be evaluated from the development of displacement-based algorithm and its expanded algorithm with conformity of several parameters such as stress measurements.

• Convergence Security Journal
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• v.15 no.2
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• pp.63-68
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• 2015

Current ICT(Information & Communication Technology) infrastructures (Internet and server/client communication) are struggling for a wide variety of devices, services, and business and technology evolution. Cloud computing originated simply to request and execute the desired operation from the network of clouds. It means that an IT resource that provides a service using the Internet technology. It is getting the most attention in today's IT trends. In the distributed cloud environments, management costs for the network and computing resources are solved fundamentally through the integrated management system. It can increase the cost savings to solve the traffic explosion problem of core network via a distributed Micro DC. However, traditional flooding methods may cause a lot of traffic due to transfer to all the neighbor DCs. Restricted Path Flooding algorithms have been proposed for this purpose. In large networks, there is still the disadvantage that may occur traffic. In this paper, we developed Lightweight Path Flooding algorithm to improve existing flooding algorithm using hop count restriction.

• Journal of the Korean Institute of Intelligent Systems
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• v.11 no.5
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• pp.426-432
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• 2001

This paper is implementation of cellular automata neural network system using evolving hardware concept. This system is a living creatures'brain based on artificial life techniques. Cellular automata neural network system is based on the development and the evolution, in other words, it is modeled on the ontogeny and phylogney of natural living things. The phylogenetic mechanism are fundamentally non-deterministic, with the mutation and recombination rate providing a major source of diversity. Ontogeny is deterministic and local physics. Cellular automata is developed from initial cells, and evaluated in given environment. And genetic algorithms take a part in adaptation process. In this paper we implement this system using evolving hardware concept. Evolving hardware is reconfigurable hardware whose configuration si under the control of an evolutionary algorithm. We design genetic algorithm process for evolutionary algorithm and cells in cellular automata neural network for the construction of reconfigurable system. The effectiveness of the proposed system if verified by applying it to Exclusive-OR.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.37 no.12
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• pp.1513-1519
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• 2013

A genetic algorithm (GA) is an optimization technique based on natural evolution theory to find the global optimal solution. Unlike the gradient-based method, it can design nanoscale structures in the electric field because it does not require sensitivity calculation. This research intends to design a nanoaperture with an unprecedented shape by the topology optimization scheme based on the GA and ON/OFF method in the visible frequency range. This research mainly aims to maximize the transmission rate at a measuring area located 10nm under the exit plane and to minimize the electric distribution at other locations. The finite element analysis (FEA) and optimization process are performed by using the commercial package COMSOL combined with the Matlab programming. The final results of the optimized model are analyzed by a comparison of the electric field intensity and the spot size of near field with those of the initial model.