• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2000.05a
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• pp.224-227
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• 2000

In this Paper, we prepose a method of constructing neural networks using bio-inspired emergent and evolutionary concepts. This method is algorithm that is based on the characteristics of the biological DNA and growth of plants. Here is, we propose a constructing method to make a DNA coding method for production rule of L-system. L-system is based on so-called the parallel rewriting mechanism. The DNA coding method has no limitation in expressing the production rule of L-system. Evolutionary algorithms motivated by Darwinian natural selection are population based searching methods and the high performance of which is highly dependent on the representation of solution space. In order to verify the effectiveness of our scheme, we apply it to one step ahead prediction of Mackey-Glass time series, Sun spot data and KOSPI data.

• Proceedings of the Korea Information Processing Society Conference
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• 2016.04a
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• pp.127-128
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• 2016

오픈플로우 네트워크에서 컨트롤과 데이터 플레인은 스위치나 라우터로 분리되어있다. 이 중 인밴드(in-band) 오픈플로우 네트워크에서 컨트롤 트래픽은 데이터 트래픽과 같은 채널을 사용한다. 그러므로 데이터 트래픽 경로의 오류 발생은 컨트롤과 데이터 트래픽에 영향을 미친다. 기존의 오픈플로우 네트워크에서 오류 복구는 컨트롤러와 스위치 간 모니터링을 필요로 한다. 하지만 수백만 개 이상의 플로우가 흐르는 네트워크에서 이는 오버헤드를 발생시킨다. 이 논문은 기존 모니터링 오버헤드를 줄이기 위해 개미 행동양식을 활용한 인밴드 오픈플로우 네트워크에서 오류 복구 기법을 제안한다.

• Proceedings of the Korean Vacuum Society Conference
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• 2013.08a
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• pp.280-280
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• 2013

In green plants, energy generation is accomplished through light-harvesting photosystem, which utilize abundant visible light and multi-stepwise redox reaction to oxidize water and reduce NADP+, transferring electrons efficiently with active cofactors1. Inspired by natural photosynthesis, artificial solar water-splitting devices are being designed variously. However, the several approaches involving immobilization2, conjugation3, and surface modification4 still have limitations. We have made artificial photosynthesis templates by self-assembling tyrosine-based peptide to mimick photosystem II. Porphyrin sensitizer absorbing blue light strongly was conjugated with the templates and they were hybridized with cobalt oxide through the reduction of cobalt ions in an aqueous solution. The formation of hybrid templates was characterized using TEM, and their water oxidation performance was measured by fluorescence oxygen probe. Our results suggest that the bio-templated assembly of functional compounds has a great potential for artificial photosynthesis.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.7 no.3
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• pp.176-181
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• 2007

This paper presents evolvable neural networks based on a developmental model for navigation control of autonomous mobile robots in dynamic operating environments. Bio-inspired mechanisms have been applied to autonomous design of artificial neural networks for solving practical problems. The proposed neural network architecture is grown from an initial developmental model by a set of production rules of the L-system that are represented by the DNA coding. The L-system is based on parallel rewriting mechanism motivated by the growth models of plants. DNA coding gives an effective method of expressing general production rules. Experiments show that the evolvable neural network designed by the production rules of the L-system develops into a controller for mobile robot navigation to avoid collisions with the obstacles.

• Journal of the Korean Society of Mechanical Technology
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• v.20 no.6
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• pp.912-916
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• 2018

Crawling robots are advantageous in overcoming obstacles. These robots have characteristics such as light weight and outstanding mobility. In case of large robots, they have difficulties passing narrow gaps or entering the cave. In this paper, we propose a milli-scale hexapedal robot using 4-bar linkages. Two conditions are necessary to enable efficient walking. In short, the trajectory of the foot must be elliptical, and the lowest point of the foot should be the same. These conditions are satisfied with a novel leg design. The robot has a pair of three legs and the legs are coupled to operate simultaneously. Each set of the legs are installed to robot's both sides and the legs satisfy the equal lowest foot point and elliptical trajectory. As a result, this hexapedal robot can crawl with 0.56m/s speed.

• Journal of Ginseng Research
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• v.45 no.2
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• pp.199-210
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• 2021

Ginseng has been used as a traditional herb in Asian countries for thousands of years. It contains a large number of active ingredients including steroidal saponins, protopanaxadiols, and protopanaxatriols, collectively known as ginsenosides. In the last few decades, the antioxidative and anticancer effects of ginseng, in addition to its effects on improving immunity, energy and sexuality, and combating cardiovascular diseases, diabetes mellitus, and neurological diseases, have been studied in both basic and clinical research. Ginseng could be a valuable resource for future drug development; however, further higher quality evidence is required. Moreover, ginseng may have drug interactions although the available evidence suggests it is a relatively safe product. This article reviews the bioactive compounds, global distribution, and therapeutic potential of plants in the genus Panax.

• Journal of Sensor Science and Technology
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• v.31 no.1
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• pp.16-23
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• 2022

Cardiac disease is the most common cause of death worldwide. Therefore, detection and classification of electrocardiogram (ECG) signals are crucial to extend life expectancy. In this study, we aimed to implement an artificial intelligence signal recognition system in field programmable gate array (FPGA), which can recognize patterns of bio-signals such as ECG in edge devices that require batteries. Despite the increment in classification accuracy, deep learning models require exorbitant computational resources and power, which makes the mapping of deep neural networks slow and implementation on wearable devices challenging. To overcome these limitations, spiking neural networks (SNNs) have been applied. SNNs are biologically inspired, event-driven neural networks that compute and transfer information using discrete spikes, which require fewer operations and less complex hardware resources. Thus, they are more energy-efficient compared to other artificial neural networks algorithms.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.16 no.2
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• pp.405-423
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• 2022

The distance vector-hop (DV-Hop) is one of the emblematic algorithms that use node connectivity for locating, which often accompanies by a large positioning error. To reduce positioning error, the bio-inspired algorithm and weight optimization model are introduced to address positioning. Most scholars argue that the weight value decreases as the hop counts increases. However, this point of view ignores the intrinsic relationship between the error and weight. To address this issue, this paper constructs the relationship model between error and hop counts based on actual communication characteristics of sensor nodes in wireless sensor network. Additionally, we prove that the error converges to 1/6CR when the hop count increase and tendency to infinity. Finally, this paper presents a modified error-oriented weight positioning model, and implements it with genetic algorithm. The experimental results demonstrate excellent robustness and error removal.

• Geomechanics and Engineering
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• v.37 no.3
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• pp.263-277
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• 2024

Artificial Neural Networks (ANNs) are artificial learning algorithms that provide successful results in solving many machine learning problems such as classification, prediction, object detection, object segmentation, image and video classification. There is an increasing number of studies that use ANNs as a prediction tool in soil classification. The aim of this research was to understand the role of hyperparameter optimization in enhancing the accuracy of ANNs for soil type classification. The research results has shown that the hyperparameter optimization and hyperparamter optimized ANNs can be utilized as an efficient mechanism for increasing the estimation accuracy for this problem. It is observed that the developed hyperparameter tool (HyperNetExplorer) that is utilizing the Covariance Matrix Adaptation Evolution Strategy (CMAES), Genetic Algorithm (GA) and Jaya Algorithm (JA) optimization techniques can be successfully used for the discovery of hyperparameter optimized ANNs, which can accomplish soil classification with 100% accuracy.

• Proceedings of the Korea Information Processing Society Conference
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• 2007.11a
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• pp.27-29
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• 2007

패턴 인식 문제를 푸는데 있어 특징 선택을 해주는 것은 패턴 인식의 성능 향상을 위해 중요한 과정 중 하나이다. 본 연구에서는 대표적인 생태계 모방 알고리즘 2 가지를 선택하여 특징 선택 문제에 적용하여 보고, 그 성능을 비교 분석하였다. 데이터의 특징을 줄여주는 기능과 패턴 인식 성능의 향상 여부를 중심으로 평가하였으며, 이를 통해 생태계 모방 알고리즘이 특징 선택 문제에 효과적으로 사용될 수 있는지에 대해 논의해보고, 두 방법의 장단점과 특징에 대해 생각해 본다.