• The Transactions of the Korean Institute of Electrical Engineers D
• /
• v.52 no.8
• /
• pp.471-481
• /
• 2003

The acts of biological immune system are similar to the navigation for autonomous mobile robots under dynamically changing environments. In recent years, many researchers have studied navigation algorithms using artificial immune networks. Conventional artificial immune algorithms consist of an obstacle-avoidance behavior and a goal-reaching behavior. To select a proper action, the navigation algorithm should combine the obstacle-avoidance behavior with the goal-reaching behavior. In this paper, the neural network is employed to combine the behaviors. The neural network is trained with the surrounding information. the outputs of the neural network are proper combinational weights of the behaviors in real-time. Also, a velocity control algorithm is constructed with the artificial immune network. Through a simulation study and experimental results for a autonomous mobile robot, we have shown the validity of the proposed navigation algorithm.

• IMMUNE NETWORK
• /
• v.2 no.3
• /
• pp.125-132
• /
• 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.

• Proceedings of the Korean Society for Agricultural Machinery Conference
• /
• 2000.11c
• /
• pp.690-697
• /
• 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.

• Proceedings of the KOSOMBE Conference
• /
• v.1995 no.11
• /
• pp.189-192
• /
• 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
• /
• v.14 no.5
• /
• pp.563-575
• /
• 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
• /
• 1995.10a
• /
• pp.60-64
• /
• 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
• /
• 2000.10a
• /
• pp.532-532
• /
• 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.

• Journal of the Korea Institute of Information and Communication Engineering
• /
• v.12 no.6
• /
• pp.1134-1141
• /
• 2008

As sensor network technologies developed, the sphere field of application is escalated unfortunately, the applicable size is smaller than the actual quantity of cattle in feedlot. In this paper, we simulated and evaluated biological data transmission performance of virtual cattle feedlot. Deducted conclusions show us a more efficient cattle control scenario is required and effective routing protocol design and modification are needed.

• Journal of the Korea Institute of Information and Communication Engineering
• /
• v.24 no.1
• /
• pp.145-148
• /
• 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.

• Proceedings of the Polymer Society of Korea Conference
• /
• 2006.10a
• /
• pp.220-220
• /
• 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.