• Journal of the Korean Society for Precision Engineering
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• v.22 no.4
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• pp.136-143
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• 2005

Open architecture controller (OAC) is well known technology in factory automation. To better understand the requirements of OAC, authors have discussed the OAC related topics with a number of control experts who represents different segments of the machining industry. There is no common concept that is accepted or used, however, the common ideas for OAC is the control system that is hardware independent, interchangeable, and easily scalable. This paper presents summary of the understaning and requirements of OAC. Based on the requirements of OAC, authors developed the software based PC-CNC. The main focus of the PC-CNC was on the user customization capability and open interface between control networks in manufacturing system. This paper introduces the developed PC-CNC briefly. In addition to introduction of the PC-CNC, to fill the gap between end users and vendors of OAC, this paper presents two applications using OAC. One is a remote monitoring system. The OPC (Ole for Process Control) standard interface was used to monitor the status of open architecture CNC across network. The other is the remote production management module for machine tools using standard database interface.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.7 no.11
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• pp.2804-2823
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• 2013

Wireless sensor network (WSN) is a promising technology for monitoring physical phenomena at fine-grained spatial and temporal resolution. However, the typical approach of sending each sensed measurement out of the network for detailed spatial analysis of transient physical phenomena may not be an efficient or scalable solution. This paper focuses on in-network physical phenomena detection schemes, particularly the distributed computation of the boundary of physical phenomena (i.e. event), to support energy efficient spatial analysis in wireless sensor networks. In-network processing approach reduces the amount of network traffic and thus achieves network scalability and lifetime longevity. This study investigates the recent advances in distributed event detection based on in-network processing and includes a concise comparison of various existing schemes. These boundary detection schemes identify not only those sensor nodes that lie on the boundary of the physical phenomena but also the interior nodes. This constitutes an event geometry which is a basic building block of many spatial queries. In this paper, we introduce the challenges and opportunities for research in the field of in-network distributed event geometry boundary detection as well as illustrate the current status of research in this field. We also present new areas where the event geometry boundary detection can be of significant importance.

• IEMEK Journal of Embedded Systems and Applications
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• v.7 no.6
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• pp.291-300
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• 2012

This paper deals with the design and implementation of wireless sensor network protocol for smart power outlet system capable of fire detection, power monitoring, standby power cutoff, and home automation. The proposed protocol integrates both the CSMA and the TDMA protocols for low power consumption and good scalability. A prototype smart power outlet system employing the proposed protocol and a simple home automation network including the power outlet system have been implemented for evaluating the feasibility of the proposed protocol The result shows that the proposed protocol allows the power outlet system to be scalable with high power efficiency.

• Journal of Environmental Health Sciences
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• v.36 no.4
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• pp.255-263
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• 2010

In many fields, nanotechnology is leading to the development of purposely-engineered nanoparticles and devices demonstrating new, unique and non-scalable properties. However, concern has been expressed that these same properties may present unique challenges in terms of the potential health impact. Airborne particles associated with engineered nanoparticles are of particular concern, as they can readily enter the body through inhalation. Research into the potential occupational health risks associated with inhaling engineered nanoparticles is actively being conducted in the U.S. and globally. In this article, the potential occupational health effects of inhaled nanoparticles and methods for measuring exposure to nanoparticles are discussed. Critical research needs in this field are also briefly addressed.

• International Journal of Computer Science & Network Security
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• v.22 no.10
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• pp.67-72
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• 2022

A wireless sensor network (WSN), with its constrained sensor node energy supply, needs an energy-efficient routing technique that maximises overall system performance. When rumours are routed using a random-walk routing algorithm, which is not highly scalable, spiral pathways may appear. Because humans think a straight line is the quickest route between two sites and two straight lines in a plane are likely to intersect, straight-line routing (SLR) constructs a straight path without the aid of geographic information. This protocol was developed for WSNs. As a result, sensor nodes in WSNs use less energy when using SLR. Using comprehensive simulation data, we show that our upgraded SLR systems outperform rumour routing in terms of performance and energy conservation.

• Journal of Sensor Science and Technology
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• v.31 no.2
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• pp.71-78
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• 2022

Wearable devices have the potential to revolutionize future medical diagnostics and personal healthcare. The integration of biosensors into scalable form factors allow continuous and noninvasive monitoring of key biomarkers and various physiological indicators. However, conventional wearable devices have critical limitations owing to their rigid and obtrusive interfaces. Recent developments in functional biocompatible materials, micro/nanofabrication methods, multimodal sensor mechanisms, and device integration technologies have provided the foundation for novel skin-interfaced bioelectronics for advanced and user-friendly wearable devices. Nonetheless, it is a great challenge to satisfy a wide range of design parameters in fabricating an authentic skin-interfaced device while maintaining its edge over conventional devices. This review highlights recent advances in skin-compatible materials, biosensor performance, and energy-harvesting methods that shed light on the future of wearable devices for digital health and personalized medicine.

• Journal of the Korea Society of Computer and Information
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• v.17 no.7
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• pp.97-106
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• 2012

Management of biosignal data in mobile devices causes many problems in real-time transmission of large volume of multimedia data or storage devices. Therefore, this research paper intends to suggest an m-Health system, a clinical data processing system using mobile in order to provide quick medical service. This system deployed health system on IP network, compounded outputs from many bio sensing in remote sites and performed integrated data processing electronically on various bio sensors. The m-health system measures and monitors various biosignals and sends them to data servers of remote hospitals. It is an Android-based mobile application which patients and their family and medical staff can use anywhere anytime. Medical staff access patient data from hospital data servers and provide feedback on medical diagnosis and prescription to patients or users. Video stream for patient monitoring uses a scalable transcoding technique to decides data size appropriate for network traffic and sends video stream, remarkably reducing loads of mobile systems and networks.

• Journal of Broadcast Engineering
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• v.13 no.5
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• pp.696-706
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• 2008

In this paper we show the performance of the network-adaptive high-definition scalable video streaming using QWLAN board with IEEE 802.11e MAC monitoring and control. Realtime collected MAC parameters are used to determine which video data is extracted for the predicted available bandwidth. To achieve performance, extraction through R-D is proposed instead of the standard video packet extraction. It is shown through experiments that streaming video quality can be enhanced by fast adaptation to network conditions by using the proposed method.

• The Journal of the Korea Contents Association
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• v.11 no.4
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• pp.101-111
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• 2011

Due to recent development in wireless communication technologies and mobile information devices, the services on ubiquitous computing technology without time and place restriction have been spotlighted. Moreover, the interest of the Wireless Sensor Networks (WSNs) and context-awareness technologies have largely been escalating and their technologies utilization is active in the various applications such as healthcare, farm management and so on. However, the direct adaption of the existing context-awareness technique to the WSN technology has several drawbacks as follows. First, such systems waste precious energy of sensor nodes, due to unnecessary data transmissions. Secondly, since the existing work was designed to support only specific applications, it is required to implement a new context-awareness application for a specific purpose. Therefore, we, in this paper, propose a new real-time monitoring system based on context-awareness in WSNs. Our system not only enhances energy efficiency by reducing data transmissions by doing context-awareness on a sensor node, but also is scalable in terms of supporting new context-awareness functionalities through modularization.

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