• 유체기계공업학회:학술대회논문집
• /
• 2003.12a
• /
• pp.535-540
• /
• 2003

In this Paper, a LON based distributed control system for HVAC is described. We developed multi-protocol converter based on SoC, Neuron Chip, embedded Linux. It utilizes the network environment and therefore requires an appropriate operating system for handling protocols and an advanced development environment. The open source licensing, reliability, and broad hardware support are key reasons for use of embedded Linux in embedded industry. The multi-prootocol converter integrates LonWorks devices to a client with Java applet. The system consists of three-tier architecture, such as clients, multi-protocol converter, and LonWorks devices. The experiment result show that multi-protocol converter using embedded Linux is a flexible and effective way to build a Web-based monitoring and control system.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
• /
• v.1 no.2
• /
• pp.7-11
• /
• 2008

In order to enhance standardization and interoperability of local level systems, AHU control network was designed with basement(8 point) and basis story(15 point) and then the network was constructed by power line communication. Each devices of AHU system were programed with neuron C of $L_{ON}W_{ORKS}$ as an open protocol. As a result of a study, each devices of the network were controlled with self dispersion process by $L_{ON}W_{ORKS}$ protocol and wiring could be reduced by power line communication.

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
• /
• v.18 no.1
• /
• pp.115-121
• /
• 2004

In this paper, a new distributed intelligent control module based on LonWoks fieldbus for air handling unit(AHU) of heating, ventilating and air-conditioning(HVAC) is proposed to replace with a conventional direct digital control(DDC) system with 32 bit microprocessor. The proposed control architecture has a excellent features such as highly compact and flexible function design, a low priced smart front-end and reliable performance with various functions. This also addresses issues in control network configuration, logical design of field devices by S/W tool, Internet networking and electronic element installation. Experimental results for showing the system performance are also included in this paper.

• Journal of the Korean Institute of Intelligent Systems
• /
• v.26 no.5
• /
• pp.368-374
• /
• 2016

This paper presents an experimental study on an electrical circuit model of the TiO2-based nano-wired memristor device for neuromophic applications. The electrical circuit equivalent model of the proposed memristor device consists of several electronics components and some passive devices including operational amplifiers, multipliers, resistors and capacitors. In order to verify the proposed design, both of simulation (using PSPICE) as well as hardware implementation were performed for the analysis of the memristor circuit with time waveforms, frequency spectra, I-V curves and power curves. The gained results from the measured data showed a good agreement with the simulation result that confirm the proposed idea.

• Proceedings of the KIEE Conference
• /
• 1993.07a
• /
• pp.235-237
• /
• 1993

Semiconductor devices generate harmonics which induced bad effects against power distribution systems. To surpress harmonics, the filter design and the identification of harmonic load sources are needed. In this paper, artificial neural networks are used to identify the nonlinear relationship between harmonic loads and harmonic currents that vary at times. To find the best adequate network for solving this identification problem, we compared with recognition rates of neural networks by changing hidden layer neuron number.

• BioChip Journal
• /
• v.12 no.4
• /
• pp.332-339
• /
• 2018

The future neuro-prosthetic devices would be required spikes data monitoring through sub-nanoscale transistors that enables to neuroscientists and clinicals for scalable, wireless and implantable applications. This research investigates the spikes monitoring through integrated CNT front-end amplifier for neuro-prosthetic diagnosis. The proposed carbon nanotube-based architecture consists of front-end amplifier (FEA), integrate fire neuron and pseudo resistor technique that observed high electrical performance through neural activity. A pseudo resistor technique ensures large input impedance for integrated FEA by compensating the input leakage current. While carbon nanotube based FEA provides low-voltage operation with directly impacts on the power consumption and also give detector size that demonstrates fidelity of the neural signals. The observed neural activity shows amplitude of spiking in terms of action potential up to $80{\mu}V$ while local field potentials up to 40 mV by using proposed architecture. This fully integrated architecture is implemented in Analog cadence virtuoso using design kit of CNT process. The fabricated chip consumes less power consumption of $2{\mu}W$ under the supply voltage of 0.7 V. The experimental and simulated results of the integrated FEA achieves $60G{\Omega}$ of input impedance and input referred noise of $8.5nv/{\sqrt{Hz}}$ over the wide bandwidth. Moreover, measured gain of the amplifier achieves 75 dB midband from range of 1 KHz to 35 KHz. The proposed research provides refreshing neural recording data through nanotube integrated circuit and which could be beneficial for the next generation neuroscientists.

• 제어로봇시스템학회:학술대회논문집
• /
• 2005.06a
• /
• pp.414-420
• /
• 2005

The ShortStack Micro Server enables any product that contains a microcontroller or microprocessor to quickly and inexpensively become a networked, Internet-accessible device. The ShortStack Micro Server provides a simple way to add LonWorks networking to new or existing smart devices. . It implements the LonTalk protocol and provides the physical interface with the LonWorks communication. The ShortStack host processor can be an 8, 16, or 32-bit microprocessor or microcontrollers. The ShortStack API and driver typically require about 4kbytes of program memory on the host processor and less than 200 bytes of RAM. The interface between host processor and the ShortStack Micro Server may be a Serial Communication Interface (SCI). The LonWorks control module with a high performance is developed, which is composed of the 8 bit PIC Microprocessor for host processor and the smart neuron chip for the ShortStack Micro Server. This intelligent control board is verified as proceeding the various function tests from experimental system with an boost pump and inverter driving systems. It is also confirmed that the developed control module provides stably 0-10VDC linear signal to the input signal of inverter driving system for varying the induction motor speed. Thus, the experimental results show that the fabricating intelligent board carried out very well the various functions in the wide operating ranges of boost pump system. This developed control module expect to apply to industrial fields to require the comparatively exact control and monitoring such as multi-motor driving system with inverter, variable air volume system and the boost pump water supply systems.

• JSTS:Journal of Semiconductor Technology and Science
• /
• v.16 no.5
• /
• pp.657-663
• /
• 2016

In this work, a novel silicon (Si) based floating body synaptic transistor (SFST) is studied to mimic the transition from short-term memory to long-term one in the biological system. The structure of the proposed SFST is based on an n-type metal-oxide-semiconductor field-effect transistor (MOSFET) with floating body and charge storage layer which provide the functions of short- and long-term memories, respectively. It has very similar characteristics with those of the biological memory system in the sense that the transition between short- and long-term memories is performed by the repetitive learning. Spike timing-dependent plasticity (STDP) characteristics are closely investigated for the SFST device. It has been found from the simulation results that the connectivity between pre- and post-synaptic neurons has strong dependence on the relative spike timing among electrical signals. In addition, the neuromorphic system having direct connection between the SFST devices and neuron circuits are designed.

• Biomolecules & Therapeutics
• /
• v.27 no.3
• /
• pp.265-275
• /
• 2019

Technological advances of mankind, through the development of electrical and communication technologies, have resulted in the exposure to artificial electromagnetic fields (EMF). Technological growth is expected to continue; as such, the amount of EMF exposure will continue to increase steadily. In particular, the use-time of smart phones, that have become a necessity for modern people, is steadily increasing. Social concerns and interest in the impact on the cranial nervous system are increased when considering the area where the mobile phone is used. However, before discussing possible effects of radiofrequency-electromagnetic field (RF-EMF) on the human body, several factors must be investigated about the influence of EMFs at the level of research using in vitro or animal models. Scientific studies on the mechanism of biological effects are also required. It has been found that RF-EMF can induce changes in central nervous system nerve cells, including neuronal cell apoptosis, changes in the function of the nerve myelin and ion channels; furthermore, RF-EMF act as a stress source in living creatures. The possible biological effects of RF-EMF exposure have not yet been proven, and there are insufficient data on biological hazards to provide a clear answer to possible health risks. Therefore, it is necessary to study the biological response to RF-EMF in consideration of the comprehensive exposure with regard to the use of various devices by individuals. In this review, we summarize the possible biological effects of RF-EMF exposure.

• Journal of Life Science
• /
• v.25 no.8
• /
• pp.953-959
• /
• 2015

Optogenetics is the combination of optical and molecular strategies to control designated molecular and cellular activities in living tissues and cells using genetically encoded light-sensitive proteins. It involves the use of light to rapidly gate the membrane channels that allows for ion movement. Optogenetics began with the placing of light-sensitive proteins from green algae inside specific types of brain cells. The cells can then be turned on or off with pulses of blue and yellow light. Using the naturally occurring algal protein Channelrhodopsin-2 (ChR2), a rapidly gated light-sensitive cation channel, the number and frequency of action potentials can be controlled. The ChR2 provides a way to manipulate a single type of neuron while affecting no others, an unprecedented specificity. This technology allows the use of light to alter neural processing at the level of single spikes and synaptic events, yielding a widely applicable tool for neuroscientists and biomedical engineers. An improbable combination of green algae, lasers, gene therapy and fiber optics made it possible to map neural circuits deep inside the brain with a precision that has never been possible before. This will help identify the causes of disorders like depression, anxiety, schizophrenia, addiction, sleep disorder, and autism. Optogenetics could improve upon existing implanted devices that are used to treat Parkinson’s disease, obsessive-compulsive disorder and other ailments with pulses of electricity. An optogenetics device could hit more specific subsets of brain cells than those devices can. Applications of optogenetic tools in nonneuronal cells are on the rise.