• IMMUNE NETWORK
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• 제2권3호
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• pp.125-132
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• 2002

In the past, bioinformatics was often regarded as a difficult and rather remote field, practiced only by computer scientists and not a practical tool available to biologists. However, the various on-going genome projects have had a serious impact on biological sciences in various ways and now there is little doubt that bioinformatics is an essential part of the research environment, with a wealth of biological information to analyze and predict. Fully sequenced genomes made us to have additional insights into the functional properties of the encoded proteins and made it possible to develop new tools and schemes for functional biology on a proteomic scale. Among those are the yeast two-hybrid system, mass spectrometry and microarray: the technology of choice to detect protein-protein interactions. These functional insights emerge as networks of interacting proteins, also known as "pathway informatics" or "interactomics". Without exception it is no longer possible to make advances in the signaling/regulatory pathway studies without integrating information technologies with experimental technologies. In this paper, we will introduce the databases of protein interaction worldwide and discuss several challenging issues regarding the actual implementation of databases.

• 한국농업기계학회:학술대회논문집
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• 한국농업기계학회 2000년도 THE THIRD INTERNATIONAL CONFERENCE ON AGRICULTURAL MACHINERY ENGINEERING. V.III
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• pp.690-697
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• 2000

The objective of this study is to develop a method that is able to realize autonomous traveling for tractor-like robot on the slope terrain. A neural network (NN) and genetic algorithms (GAs) have been used for resolving nonlinear problems in this system. The NN is applied to create a vehicle simulator that is capable to describe the motion of the tractor robot on the slope, while it is impossible by the common dynamics way. Using this vehicle simulator, a control law optimized by GAs was established and installed in the computer to control the steering wheel of tractor robot. The autonomous traveling carried out on a 14-degree slope had initial successful results.

• 대한의용생체공학회:학술대회논문집
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• 대한의용생체공학회 1995년도 추계학술대회
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• pp.189-192
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• 1995

In Visually Evoked Potentials(VEP) or Auditory Evoked Potentials(AEP), the components by the stimulation and the components which are irrelevant to the stimulation(noise or nonstationary spontaneous EEG) are mixed together. So one should average hundreds of EP waves to extract the components by the stimulation only. In this study, we have classified EP's, which are the responses of the different stimulations and different states of subjects. To classify the EP waves, the cross-correlation coefficients and neural network method(error back propagation) are used and compared.

• Computers and Concrete
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• 제14권5호
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• pp.563-575
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• 2014

Concrete which is a composite material is frequently used in construction works. Properties and behavior of concrete are significant under the effect of different loading cases. Impact loading which is a sudden dynamic one may have destructive effects on structures. Testing apparatuses are designed to investigate the impact effect on test members. Artificial Neural Network (ANN) is a computational model that is inspired by the structure or functional aspects of biological neural networks. It can be defined as an emulation of biological neural system. In this study, impact parameters as acceleration and impact force values of a reinforced concrete slab are obtained by using a testing apparatus and essential test devices. Afterwards, ANN analysis which is used to model different physical dynamic processes depending on several variables is performed in the numerical part of the study. Finally, test and predicted results are compared and it's seen that ANN analysis is an alternative way to predict the results successfully.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 1995년도 Proceedings of the Korea Automation Control Conference, 10th (KACC); Seoul, Korea; 23-25 Oct. 1995
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• pp.60-64
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• 1995

The conventional neural network models are a parody of biological neural structures, and have very slow learning. In order to emulate some dynamic functions, such as learning and adaption, and to better reflect the dynamics of biological neurons, M.M. Gupta and D.H. Rao have developed a 'dynamic neural model'(DNU). Proposed neural unit model is to introduce some dynamics to the neuron transfer function, such that the neuron activity depends on internal states. Integrating an dynamic elementry processor within the neuron allows the neuron to act dynamic response Numerical examples are presented for a model system. Those case studies showed that the proposed DNU is so useful in practical sense.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 2000년도 제15차 학술회의논문집
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• pp.532-532
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• 2000

Conventional artificial intelligence systems are not properly responding under dynamically changing environments. To overcome this problem, reactive planning systems implementing new Al principles, called behavior-based Al or emergent computation, have been proposed and confirmed their usefulness. As another alternative, biological information processing systems may provide many feasible ideas to these problems. Immune system, among these systems, plays important roles to maintain its own system against dynamically changing environments. Therefore, immune system would provide a new paradigm suitable for dynamic problem dealing with unknown environments. In this paper, a new approach to behavior-based Al by paying attention to biological immune system is investigated. The feasibility of this method is confirmed by applying to behavior control of an autonomous mobile robot in cluttered environment.

• 한국정보통신학회논문지
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• 제12권6호
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• pp.1134-1141
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• 2008

센서네트워크 기술의 발전에 따라 그 활용 범위는 가축에까지 확대 되고 있는 추세이다. 그러나 대단위 가축에게 실시되기에는 비용이나, 효율 등에서 문제가 발생한다. 본 논문에서는 대단위로 가축의 생체 데이터 측정을 시뮬레이션을 통해 구현하였으며, 실제와 보다 유사하게 하기 위해 전파모델을 축사환경에 맞게 변경하여 시뮬레이션 하였다. 도출된 결론을 통해 축우 통제를 통한 수집 시나리오가 필요함을 알 수 있었고, 효과적인 라우팅 프로토콜의 수정도 필요함을 알 수 있었다.

• 한국정보통신학회논문지
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• 제24권1호
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• pp.145-148
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• 2020

Wearable computing is growing rapidly as research on body area communication network using wireless sensor network technology is actively conducted. In particular, there is an increasing interest in smart clothing measuring unrestrained and insensitive bio signals, and research is being actively conducted. However, research on smart clothing is mainly based on 1: 1 wireless communication. In this paper, we propose a multi-access monitoring system that can measure bio-signals by multiple users wearing smart clothing. The proposed system consists of wireless access device, multiple access control server and monitoring system. It also provides a service that allows multiple users to monitor and measure bio signals at the same time.

• 한국고분자학회:학술대회논문집
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• 한국고분자학회 2006년도 IUPAC International Symposium on Advanced Polymers for Emerging Technologies
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• pp.220-220
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• 2006

Rheological and electrical properties of the polycarbonate (PC) / multi-walled carbon nanotube (MWNT) were studied. The MWNT was funtoinalized by treating with the hydrogen peroxide ($H_{2}O_{2}$). The electrical conductivity showed higher value for the PC/MWNT ($H_{2}O_{2}$ treated, freeze drying) composites compared that of the PC/MWNT ($H_{2}O_{2}$ treated, thermal drying) composites. From the results of the morphological, rheological, and electrical properties of the PC/MWNT composites, it is suggested that the electrical and rheological properties of the PC/MWNT composites are affected by the MWNT-MWNT network structure which is related with the MWNT morphologies such as the degree of aggregation and aspect ratio of the MWNT.

• Molecules and Cells
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• 제42권9호
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• pp.617-627
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• 2019

Brain organoids are an exciting new technology with the potential to significantly change our understanding of the development and disorders of the human brain. With step-by-step differentiation protocols, three-dimensional neural tissues are self-organized from pluripotent stem cells, and recapitulate the major millstones of human brain development in vitro. Recent studies have shown that brain organoids can mimic the spatiotemporal dynamicity of neurogenesis, the formation of regional neural circuitry, and the integration of glial cells into a neural network. This suggests that brain organoids could serve as a representative model system to study the human brain. In this review, we will overview the development of brain organoid technology, its current progress and applications, and future prospects of this technology.