• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.12 no.6
• /
• pp.2697-2710
• /
• 2018

Owing to the development of Internet of Things (IoT), the fifth-generation (5G) wireless communication is going to foresee a substantial increase of mobile traffic demand. Energy efficiency and spectral efficiency are the challenges in a 5G network. Non-orthogonal multiple access (NOMA) is a promising technique to increase the system efficiency by adaptive power control (PC) in a 5G network. This paper proposes an efficient PC scheme based on evolutionary game theory (EGT) model for uplink power-domain NOMA system. The proposed PC scheme allows users to adaptively adjusts their transmit power level in order to improve their payoffs or throughput which results in an increase of the system efficiency. In order to separate the user signals, a successive interference cancellation (SIC) receiver installed at the base station (BS) site. The simulation results demonstrate that the proposed EGT-based PC scheme outperforms the traditional game theory-based PC schemes and orthogonal multiple access (OMA) in terms of energy efficiency and spectral efficiency.

• Journal of the Korean Institute of Landscape Architecture
• /
• v.28 no.2
• /
• pp.49-60
• /
• 2000

The purpose of this study is to overview domestic and foreign trends in the study of the landscape evaluation through new framework of landscape evaluation studies. 108 studies on the landscape evaluation are summarized and categorized into theoretical studies, verification of theories, development of evaluation methods and applications in physical planning. Major theories in the landscape evaluation came from the psycho-physics, the evolutionary theory ann the cultural-learning theory, and were verified and applied into physical planning. Early experimental researches on landscape evaluation, based on psycho-physics, were focused on relatively simple responses to landscapes. But many studies have been gradually related to the evolutionary theory and the cultural learning theory, emphasizing biological and cultural effects on landscape evaluation. Especially, Appleton's Prospect-Refuge theory' and Kaplans' 'Information Processing model' have very strong influence in landscape evaluation. Relatively there have been many application researches in Korea, which tells there have been strong needs to solve pending practical problems caused by the rapid economic and social growth for several decades. Almost of applications in physical planning are focused on physical features of landscapes, but for more comprehensive landscape evaluation, many other factors such as cognitive and sociocultural variables should be integrated into the whole evaluation system. As a result of reviewing of landscape evaluation studies, I found the overall domestic and foreign trends and the necessity of more research on the applications in physical planning. Because this study mainly focused on academic researches, for more appropriate landscape evaluation and management there should be more practical researches including various approaches.

• Journal of Korean Association for Spatial Structures
• /
• v.1 no.1 s.1
• /
• pp.125-134
• /
• 2001

The objective of this study is the development of size discrete optimum design algorithm which is based on the GAs(genetic algorithms). The algorithm can perform size discrete optimum designs of space trusses. The developed algorithm was implemented in a computer program. For the optimum design, the objective function is the weight of space trusses and the constraints are limite state design codes(1998) and displacements. The basic search method for the optimum design is the GAs. The algorithm is known to be very efficient for the discrete optimization. This study solves the problem by introducing the GAs. The GAs consists of genetic process and evolutionary process. The genetic process selects the next design points based on the survivability of the current design points. The evolutionary process evaluates the survivability of the design points selected from the genetic process. In the genetic process of the simple GAs, there are three basic operators: reproduction, cross-over, and mutation operators. The efficiency and validity of the developed discrete optimum design algorithm was verified by applying GAs to optimum design examples.

• Journal of Hospice and Palliative Care
• /
• v.27 no.2
• /
• pp.51-63
• /
• 2024

Purpose: This study aimed to clarify the concept of pediatric hospice and palliative care through conceptual analysis. It also sought to identify the differences between related concepts such as pediatric death care and pediatric spiritual care, in order to provide foundational data for the development of nursing theory and knowledge. Methods: A conceptual analysis of pediatric hospice and palliative care was conducted using Rodgers' evolutionary method. Out of 5,013 papers identified, 28 were selected for detailed reading and analysis. Results: Pediatric hospice and palliative care encompasses physical, psychological, social, mental, spiritual, and family care for children with acute and chronic diseases with uncertain prognoses ahead of death, as well as their families. Effective pediatric hospice and palliative care will require multidisciplinary team nursing, effective communication, and supportive policies. Conclusion: The findings of this study suggest that providing pediatric hospice and palliative care will lead to improvements in pain relief for children and families, the efficiency of responses to death in children, and the quality of life for children and families. The significance of this study is that it clearly clarifies the concept by analyzing pediatric hospice and palliative care using an evolutionary method.

• Journal of Korean Society of Steel Construction
• /
• v.13 no.6
• /
• pp.673-681
• /
• 2001

The objective of this study is the development of size, shape and topology discrete optimum design algorithm which is based on the genetic algorithm. The algorithm can perform both shape and topology optimum designs of trusses. The developed algorithm was implemented in a computer program. For the optimum design, the objective function is the weight of trusses and the constraints are stress and displacement. The basic search method for the optimum design is the genetic algorithm. The algorithm is known to be very efficient for the discrete optimization. The genetic algorithm consists of genetic process and evolutionary process. The genetic process selects the next design points based on the survivability of the design points selected form the genetic process. The evolutionary process evaluates the survivability of the design points. The evolutionary process evaluates the survivability of the design points selected form the genetic process. The efficiency and validity of the developed size, shape and topology discrete optimum design algorithm was verified by applying the algorithm to optimum design examples.

• Proceedings of the Korean Society of Crop Science Conference
• /
• 2022.10a
• /
• pp.219-219
• /
• 2022

Granule-bound starch synthase I (GBSSI), encoded by the waxy gene, is responsible for the accumulation of amylose during the development of starch granules in rice endosperm. Despite many findings on waxy alleles, the genetic diversity and evolutionary studies are still not fully explored regarding their functional effects. Comprehensive evolutionary analyses were performed to investigate the genetic variations and relatedness of the GBSSI gene in 374 rice accessions composed of 54 wild accessions and 320 bred cultivars (temperate japonica, tropical japonica, indica, aus, aromatic, and admixture). GBSS1 coding regions were analyzed from a VCF file retrieved from whole-genome resequencing data, and eight haplotypes were identified in the GBSSI coding region of 320 bred cultivars. The genetic diversity indices revealed the most negative Tajima's D value in the tropical-japonica, followed by the aus and temperate-japonica, while Tajima's D values in indica were positive, indicating balancing selection. Diversity reduction was noticed in temperate japonica (0.0003) compared to the highest one (wild, 0.0044), illustrating their higher genetic differentiation by F_ST-value (0.604). The most positive Tajima's D value was observed in indica (0.5224), indicating the GBSSI gene domestication signature under balancing selection. In contrast, the lowest and negative Tajima's D value was found in tropical japonica (-0.5291), which might have experienced a positive selection and purified due to the excess of rare alleles. Overall, our study offers insights into haplotype diversity and evolutionary fingerprints of GBSSI. It ako provides genomic information to increase the starch content of cooked rice.

• Smart Structures and Systems
• /
• v.21 no.4
• /
• pp.435-448
• /
• 2018

This paper reports the development of a theoretically rigorous method for permanent way engineers to assess the condition of railway ballast under a concrete sleeper with the potential to be extended to a smart system for long-term health monitoring of railway ballast. Owing to the uncertainties induced by the problems of modeling error and measurement noise, the Bayesian approach was followed in the development. After the selection of the most plausible model class for describing the damage status of the rail-sleeper-ballast system, Bayesian model updating is adopted to calculate the posterior PDF of the ballast stiffness at various regions under the sleeper. An obvious drop in ballast stiffness at a region under the sleeper is an evidence of ballast damage. In model updating, the model that can minimize the discrepancy between the measured and model-predicted modal parameters can be considered as the most probable model for calculating the posterior PDF under the Bayesian framework. To address the problems of non-uniqueness and local minima in the model updating process, a two-stage hybrid optimization method was developed. The modified evolutionary algorithm was developed in the first stage to identify the important regions in the parameter space and resulting in a set of initial trials for deterministic optimization to locate all most probable models in the second stage. The proposed methodology was numerically and experimentally verified. Using the identified model, a series of comprehensive numerical case studies was carried out to investigate the effects of data quantity and quality on the results of ballast damage detection. Difficulties to be overcome before the proposed method can be extended to a long-term ballast monitoring system are discussed in the conclusion.

• Proceedings of the Korea Society of Design Studies Conference
• /
• 2004.10a
• /
• pp.194-195
• /
• 2004

• Journal of the military operations research society of Korea
• /
• v.29 no.2
• /
• pp.131-147
• /
• 2003

The complexity of modern weapon systems using the intelligence technology demands that rapid and effective transition from force requirements to deployment and fielding. Thus this paper deals with the integration of development procedure, evolutionary acquisition, integrated test and evaluation, improvement of the requirements decision process, use of commercial products of high quality and low cost, specification deviation, and the effective use of dual use technology. In general, decision­makers, and military field users shall first consider the moving technology rapidly into use. This study is aimed to improve the defence acquisition management directive for timely force integration of weapon system.

• Proceedings of the Korean Institute of Intelligent Systems Conference
• /
• 2001.12a
• /
• pp.255-258
• /
• 2001

This paper is implementation of cellular automata neural network system which is a living creatures' brain using evolving hardware concept. Cellular automata neural network system is based on the development and the evolution, in other words, it is modeled on the ontogeny and phylogeny of natural living things. The proposed system developes each cell's state in neural network by CA. And it regards code of CA rule as individual of genetic algorithm, and evolved by genetic algorithm. In this paper we implement this system using evolving hardware concept Evolving hardware is reconfigurable hardware whose configuration is 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 is verified by applying it to time-series prediction.