• Korean Journal of Materials Research
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• v.20 no.5
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• pp.235-240
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• 2010

We investigated the carbon monoxide (CO) gas-sensing properties of nanostructured Al-doped zinc oxide thin films deposited on self-assembled Au nanodots (ZnO/Au thin films). The Al-doped ZnO thin film was deposited onto the structure by rf sputtering, resulting in a gas-sensing element comprising a ZnO-based active layer with an embedded Pt/Ti electrode covered by the self-assembled Au nanodots. Prior to the growth of the active ZnO layer, the Au nanodots were formed via annealing a thin Au layer with a thickness of 2 nm at a moderate temperature of $500^{\circ}C$. It was found that the ZnO/Au nanostructured thin film gas sensors showed a high maximum sensitivity to CO gas at $250^{\circ}C$ and a low CO detection limit of 5 ppm in dry air. Furthermore, the ZnO/Au thin film CO gas sensors exhibited fast response and recovery behaviors. The observed excellent CO gas-sensing properties of the nanostructured ZnO/Au thin films can be ascribed to the Au nanodots, acting as both a nucleation layer for the formation of the ZnO nanostructure and a catalyst in the CO surface reaction. These results suggest that the ZnO thin films deposited on self-assembled Au nanodots are promising for practical high-performance CO gas sensors.

• Proceedings of the Polymer Society of Korea Conference
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• 2006.10a
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• pp.309-309
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• 2006

Latest developments on hybrid nanostructured materials fabricated by applying self-assembly strategies on organic/inorganic nanotemplates are discussed. Within this frame, numerous functional nanomaterials including arrays of composite metal/semiconductor nanoparticles, planar waveguides and functional multilayer thin films are generated using self-assembled polymers as templates or building blocks. In particular, surface plasmon resonance based optical sensing is employed to investigate nanofabrication processes occurring in nanoscale dimention. We also suggest unprecedented pathways to hybrid supramolecular multilayer nanoarchitectures in 1D or 2D geometry via layer-by-layer self-assembly.

• Journal of Communications and Networks
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• v.14 no.2
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• pp.188-194
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• 2012

Cognitive networks (CNs) are capable of enabling dynamic spectrum allocation, and thus constitute a promising technology for future wireless communication. Whereas, the implementation of CN will lead to the requirement of an increased energy-arrival rate, which is a significant parameter in energy harvesting design of a cognitive user (CU) device. A well-designed spectrum-sensing scheme will lower the energy-arrival rate that is required and enable CNs to self-sustain, which will also help alleviate global warming. In this paper, spectrum sensing in a multi-user cognitive ad hoc network with a wide-band spectrum is considered. Based on the prospective spectrum sensing, we classify CN operation into two modes: Distributed and centralized. In a distributed network, each CU conducts spectrum sensing for its own data transmission, while in a centralized network, there is only one cognitive cluster header which performs spectrum sensing and broadcasts its sensing results to other CUs. Thus, a wide-band spectrum that is divided into multiple sub-channels can be sensed simultaneously in a distributed manner or sequentially in a centralized manner. We consider the energy consumption for spectrum sensing only of an analog-to-digital convertor (ADC). By formulating energy consumption for spectrum sensing in terms of the sub-channel sampling rate and whole-band sensing time, the sampling rate and whole-band sensing time that are optimal for minimizing the total energy consumption within sensing reliability constraints are obtained. A power dissipation model of an ADC, which plays an important role in formulating the energy efficiency problem, is presented. Using AD9051 as an ADC example, our numerical results show that the optimal sensing parameters will achieve a reduction in the energy-arrival rate of up to 97.7% and 50% in a distributed and a centralized network, respectively, when comparing the optimal and worst-case energy consumption for given system settings.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.39 no.6
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• pp.675-689
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• 2019

Development of smart construction materials with both self-strain and self-damage sensing capacities is still difficult because of little information about the self-damage sensing source. Herein, we investigate the effects of the matrix strength, fiber geometry, and fiber content on the electrical resistivity of steel-fiber-reinforced cement composites by multi-fiber pullout testing combined with electrical resistivity measurements. The results reveal that the electrical resistivity of steel-fiber-reinforced cement composites clearly decreased during fiber-matrix debonding. A higher fiber-matrix interfacial bonding generally leads to a higher reduction in the electrical resistivity of the composite during fiber debonding due to the change in high electrical resistivity phase at the fiber-matrix interface. Higher matrix strengths, brass-coated steel fibers, and deformed steel fibers generally produced higher interfacial bond strengths and, consequently, a greater reduction in electrical resistivity during fiber debonding.

• Fashion & Textile Research Journal
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• v.18 no.6
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• pp.755-765
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• 2016

Recently, interest in monitoring health and sports is growing because of the emphasis on wellness, which is accelerating the development and commercialization of smart clothing for biosignal monitoring. In addition to exerciseeffect monitoring clothing that tracks heart rate and respiration, recently developed clothing makes it possible to monitor muscle balance using electromyogram (EMG). The electrode for EMG have to attached to an accurate location in order to obtain high-quality signals in surface EMG measurement. Therefore, this study develops monitoring clothing suitable for different types of human bodies and aims to extract suitable range of EMG according to movements in order to develop self-fitness monitoring clothing based on EMG measurement. This study identified and attached electrodes on six upper muscles and two lower muscles of ten males in their 20s. After selecting six main motions that create a load on muscles, the 8-ch wireless EMG system was used to measure amplitude value, noise, SNR and SNR (dB) in each part and statistical analysis was conducted using SPSS 20.0. As a result, the suitable range for EMG measurement to apply to clothing was identified as four parts in musculus pectoralis major; three parts in muscle rectus abdominis, two parts each in shoulder muscles, backbone erector, biceps brachii, triceps brachii, and musculus biceps femoris; and four part in quadriceps muscle of thigh. This was depicted diagrammatically on clothing, and the EMG-monitoring sensing locations were presented for development of self-fitness monitoring.

• Journal of Mechanical Science and Technology
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• v.18 no.3
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• pp.379-387
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• 2004

A novel flatness sensing system which is called the Flatness Sensing Inter-stand Looper(FlatSIL) system is suggested and a self-tuning PI control system using the FlatSIL is designed for improving the flatness of hot strip in finishing mill processes. The FlatSIL system measures the tension along the direction of the strip width by using segmented rolls, and the tension profile is approximated through the tension of each segmented roll. The flatness control system is operated by using the tension profile. The proposed flatness control system as far as the tension profile-measuring device works for the full strip length during the strip rolling in finishing mills. The generalized minimum variance self-tuning (GMV S-T) PI control method is applied to control the flatness of hot strip which has a design parameter as weighting factor for updating the PI gains. Optimizing the design parameter in the GMV S-T PI controller, the Robbins-Monro algorithm is used. It is shown by the computer simulation and experiment that the proposed GMV S-T PI flatness control system has better performance than the fixed PI flatness control system.

• International Journal of Internet, Broadcasting and Communication
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• v.12 no.3
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• pp.32-38
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• 2020

The deployment of geographically distributed wireless sensors has greatly elevated the capability of monitoring structural health in social-overhead capital (SOC) public infrastructures. This paper deals with the utilization of a distributed mobility management (DMM) approach for the deployment of wireless sensing devices in a structural health monitoring system (SHM). Then, a wireless sensing mechanism utilizing low-energy adaptive clustering hierarchy (LEACH)-based clustering algorithm for smart sensors has been analyzed to support the seamless data transmission of structural health information which is essentially important to guarantee public safety. The clustering of smart sensors will be able to provide real-time monitoring of structural health and a filtering algorithm to boost the transmission of critical information over heterogeneous wireless and mobile networks.

• KIEE International Transaction on Electrical Machinery and Energy Conversion Systems
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• v.5B no.4
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• pp.392-398
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• 2005

This paper presents technologies that have strategic importance in future motor drives. The underlying strategic issue for motor drives is maintaining cost while increasing certain dimensions of functionality. The dimensions of functionality which should increase include reliability and added value features such as providing continuous energy optimization, providing sensing of the driven system suitable for application specific diagnostic purposes, and providing continuously optimal thermal utilization of the capability of the drive. This paper will address each of these issues and discuss the technology status for each case, with a focus on research needed to fully deliver the needed functionality.

• Journal of Institute of Control, Robotics and Systems
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• v.4 no.1
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• pp.88-99
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• 1998

In assembly, misalignment must be detected and compensated for during the mating period, regardless of the complexity of the cross-sectional shape. To this end, we propose a novel omnidirectional image sensing system for assembling parts with complicated shapes(OISSA) and its feasibility for detecting the misalignment between mating parts is shown by a series of simulations. This system encompasses a camera with an optical unit attached to the front of the camera. The optical unit consists of a pair of plane mirrors and a pair of conic mirrors. Utilizing the proposed sensing system, a 2$\pi$ coaxial image of the misalignment along the mating boundary interface between mating parts can be immediately obtained without experiencing self-occlusion.

• Nuclear Engineering and Technology
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• v.55 no.5
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• pp.1533-1540
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• 2023

Self-Powered Neutron Detectors(SPNDs) are used to calculate core power distributions, an essential factor in the safe operation of nuclear power plants. Some detectors may fail during normal operation, and signals from failed detectors are isolated from intact signals. The calculated detailed power distribution accuracy depends on the number of available detector signals. Failed detectors decrease the operating margin by enlarging the power distribution measurement error. Therefore, a thorough reconstruction of the failed detector signals is critical. This note suggests a compressive sensing based methodology that rationally reconstructs the readings of failed detectors. The methodology significantly improves reconstruction accuracy by sorting signals and removing high-frequency components from conventional compressive sensing methodology.