• Journal of the Architectural Institute of Korea Planning & Design
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• v.34 no.4
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• pp.123-131
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• 2018

This study discusses that the US zoning system came from "progressive movement" in the early 20th century. The US progressive movement was closely related with the scientific management movement in terms of efficiency. In that context, the ontological significance of zoning is found in realizing public interests by blocking external effects based on the value-neutral expertise. Another aspect of the US zoning system is the political one. It is closely related to progressive movement in common with efficiency. The zoning system was introduced as a measure to prevent the racial and class mixture resulting from the influx of immigrants. Today, the racial aspect of zoning is succeeded to exclusionary zoning. This study examines the fact that exclusive interests of US mainstream society have served as more important background than the fundamental aspect preventing external effects in the introduction and evolution of the zoning system.

• The Journal of Engineering Geology
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• v.33 no.4
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• pp.725-736
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• 2023

The compliance of deep geological disposal facilities for high-level radioactive waste with safety objectives requires consideration of uncertainties owing to temporal changes in the disposal system. A comprehensive review and analysis of the characteristics of this evolution should be undertaken to identify the effects on multiple barriers and the biosphere. We analyzed the evolution of the buffer, backfill, plug, and closure regions during the early phase of the post-closure period as part of a long-term performance assessment for an operating license application for a deep geological repository in Finland. Degradation mechanisms generally expected in engineered barriers were considered, and long-term evolution features were examined for use in performance assessments. The importance of evolution features was classified into six categories based on the design of the Finnish case. Results are expected to be useful as a technical basis for performance and safety assessment in developing the Korean deep geological disposal system for high-level radioactive waste. However, for a more detailed review and evaluation of each feature, it is necessary to obtain data for the final disposal site and facility-specific design, and to assess its impact in advance.

• Journal of the Korean Institute of Intelligent Systems
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• v.18 no.5
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• pp.712-717
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• 2008

In swarm robot systems, each robot must act by itself according to the its states and environments, and if necessary, must cooperate with other robots in order to carry out a given task. Therefore it is essential that each robot has both learning and evolution ability to adapt the dynamic environments. In this paper, reinforcement learning method with SVM based on structural risk minimization and distributed genetic algorithms is proposed for behavior learning and evolution of collective autonomous mobile robots. By distributed genetic algorithm exchanging the chromosome acquired under different environments by communication each robot can improve its behavior ability. Specially, in order to improve the performance of evolution, selective crossover using the characteristic of reinforcement learning that basis of SVM is adopted in this paper.

• Advances in Computational Design
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• v.1 no.4
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• pp.315-327
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• 2016

Damage detection and localisation in structures is essential since it can be a means for preventive maintenance of those structures under service conditions. The use of structural modal data for detecting the damage is one of the most efficient methods. This paper presents comparative performance of various state-of-the-art meta-heuristics for use in structural damage detection based on changes in modal data. The metaheuristics include differential evolution (DE), artificial bee colony algorithm (ABC), real-code ant colony optimisation (ACOR), charged system search (ChSS), league championship algorithm (LCA), simulated annealing (SA), particle swarm optimisation (PSO), evolution strategies (ES), teaching-learning-based optimisation (TLBO), adaptive differential evolution (JADE), evolution strategy with covariance matrix adaptation (CMAES), success-history based adaptive differential evolution (SHADE) and SHADE with linear population size reduction (L-SHADE). Three truss structures are used to pose several test problems for structural damage detection. The meta-heuristics are then used to solve the test problems treated as optimisation problems. Comparative performance is carried out where the statistically best algorithms are identified.

• Journal of the Korean Institute of Intelligent Systems
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• v.19 no.2
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• pp.279-284
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• 2009

In swarm robot systems, each robot must behaves by itself according to the its states and environments, and if necessary, must cooperates with other robots in order to carry out a given task. Therefore it is essential that each robot has both learning and evolution ability to adapt the dynamic environments. In this paper, reinforcement learning method using many SVM based on structural risk minimization and distributed genetic algorithms is proposed for behavior learning and evolution of collective autonomous mobile robots. By distributed genetic algorithm exchanging the chromosome acquired under different environments by communication each robot can improve its behavior ability. Specially, in order to improve the performance of evolution, selective crossover using the characteristic of reinforcement learning that basis of Cascade SVM is adopted in this paper.

• Journal of the Korean Institute of Telematics and Electronics S
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• v.35S no.4
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• pp.67-75
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• 1998

In general, Evoluationary Algorithm(EAs) are refered to as methods of population-based optimization. And EAs are considered as very efficient methods of optimal sytem design because they can provice much opportunity for obtaining the global optimal solution. This paper presents a co-evolution scheme of artifical neural networks, which has two different, still cooperatively working, populations, called as a host popuation and a parasite population, respectively. Using the conventional generatic algorithm the host population is evolved in the given environment, and the parastie population composed of schemata is evolved to find useful schema for the host population. the structure of artificial neural network is a diagonal recurrent neural netork which has self-feedback loops only in its hidden nodes. To find optimal neural networks we should take into account the structure of the neural network as well as the adaptive parameters, weight of neurons. So we use the genetic algorithm that searches the structure of the neural network by the co-evolution mechanism, and for the weights learning we adopted the evolutionary stategies. As a results of co-evolution we will find the optimal structure of the neural network in a short time with a small population. The validity and effectiveness of the proposed method are inspected by applying it to the stabilization and position control of the invered-pendulum system. And we will show that the result of co-evolution is better than that of the conventioal genetic algorithm.

• Journal of electromagnetic engineering and science
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• v.14 no.4
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• pp.353-359
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• 2014

Recently, the use of mobile devices has increased, and mobile traffic is growing rapidly. In order to deal with such massive traffic, cognitive radio (CR) is applied to efficiently use limited-spectrum resources. However, there can be multiple communication systems trying to access the white space (unused spectrum), and inevitable interference may occur to cause mutual performance degradation. Therefore, understanding the effects of interference in CR-based systems is crucial to meaningful operations of these systems. In this paper, we consider a long-term evolution (LTE) system using additional spectra by accessing the TV white space, where low-power devices (LPDs) are licensed primary users, in addition to TV broadcasting service providers. We model such a heterogeneous system to analyze the co-existence problem and evaluate the interference effects of LPDs on LTE user equipment (UE) throughput. We then present methods to mitigate the interference effects of LPDs by 'de-selecting' some of the UEs to effectively increase the overall sector throughput of the CR-based LTE system.

• Journal of Electrical Engineering and Technology
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• v.13 no.6
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• pp.2301-2309
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• 2018

In a field-oriented vector-controlled permanent magnet synchronous motor (PMSM) control system, the d-axis current control loop can offer a free degree of freedom which can be used to improve control performances. However, in the industry the desired d-axis current command is usually set as zero without using the free degree of freedom. This paper proposes a method to use the degree of freedom for control performance improvement. It is assumed that both the inner loop proportional-integral (PI) current controller and the q-axis outer loop PI speed controller are tuned by the well-known tuning rules. This paper gives an optimal d-axis reference current command generator such that some useful performance indexes are minimized and/or a tradeoff between conflicting performance criteria is made. This paper uses a differential evolution algorithm to autotune the parameter values of the optimal d-axis reference current command generator. This paper implements the proposed control system in real time on a Texas Instruments TMS320F28335 floating-point DSP. This paper also gives experimental results showing the practicality and feasibility of the proposed control system, along with simulation results.

• Korean System Dynamics Review
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• v.15 no.4
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• pp.101-127
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• 2014

This study aims to understand how and why each stage of capitalism grows and changes into the new direction in the moment of crisis, based on the systems thinking approach through the causal loop feedback structure. To achieve the research purpose, it classifies the evolution process of the capitalistic economic system into 4 types: Capitalism 1.0(Classical Laissez-Faire Capitalism), 2.0(Revised Capitalism), 3.0(Neo-liberalism), and 4.0(New Capitalism for the Future). This study focuses particularly on by which feedback structure the growth, crisis, and new transition of capitalism could be explained. The main research results are as follows. The intended positive feedback structure caused the growth at each early stage of capitalism. After that time, as a result of the uncontrolled growth, the negative feedback structure controlling its growth operated on the one hand, while the positive feedback structure amplifying the crisis did on the other hand. The study suggests the Resilient Capitalism as the new evolutional direction of Capitalism 4.0. It can contribute to strengthening its resilience by which all the economic players can recover promptly and flexibly from the crises such as the failure of competition and unemployment.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.33 no.6A
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• pp.607-613
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• 2008

In this paper, we investigate the performance of SMP-assisted 3GPP GERAN evolution system employing high order modulation and turbo coding. When applying the SMP which maps systematic bits into highly reliable bit positions, it is confirmed that there is the performance gain for the modulation and coding schemes of 16QAM(DAS-8) as well as 32QAM(DAS-11) by link level simulation.