• Proceedings of the Korean Vacuum Society Conference
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• 2011.02a
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• pp.431-431
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• 2011

Graphene, two dimensional sheet of sp2-hybridized carbon, has attracted an enormous amount of interest due to excellent electrical, chemical and mechanical properties for the application of transparent conducting films, clean energy devices, field-effect transistors, optoelectronic devices and chemical sensors. Especially, graphene is promising candidate to detect the gas molecules and biomolecules due to the large specific surface area and signal-to-noise ratios. Despite of importance to the disease diagnosis, there are a few reports to demonstrate the graphene- and rGO-FET for biological sensors and the sensing mechanism are not fully understood. Here we describe scalable and facile fabrication of rGO-FET with the capability of label-free, ultrasensitive electrical detection of a cancer biomarker, prostate specific antigen/${\alpha}1$-antichymotrypsin (PSA-ACT) complex, in which the ultrathin rGO sensing channel was simply formed by a uniform self-assembly of two-dimensional rGO nanosheets on aminated pattern generated by inkjet printing. Sensing characteristics of rGO-FET immunosensor showed the highly precise, reliable, and linear shift in the Dirac point with the analyte concentration of PSA-ACT complex and extremely low detection limit as low as 1 fg/ml. We further analyzed the charge doping mechanism, which is the change in the charge carrier in the rGO channel varying by the concentration of biomolecules. Amenability of solution-based scalable fabrication and extremely high performance may enable rGO-FET device as a versatile multiplexed diagnostic biosensor for disease biomarkers.

• Agricultural and Biosystems Engineering
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• v.7 no.1
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• pp.27-41
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• 2006

Assessment of nitrogen and chlorophyll content from crop leaves can help growers adjust N fertilizer rates to meet the demands of the crop. Numerous researchers have presented their studies about spectral signature of plant leaves to characterize the plant features. However, interrelational review and summary were limited and a communication gap exists between the plant science and optical engineering. Understanding the mechanism of leaf interaction to electromagnetic radiation and factors affecting spectrophotometric measurements can enhance the foundation of optical remote sensing technologies. This paper provides extensive review of previous works in optical sensing and explains the basics of plant optics, spectral measurements for plant stress, factors that affect sensitivity to spectral analysis, and applications that deploy optical remote sensing technologies.

• Journal of the Korean Society for Precision Engineering
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• v.22 no.12 s.177
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• pp.42-50
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• 2005

This paper presents an ultra precision machining system using a high sensitive force sensing module to measure machining forces and penetration displacement in a tip-based nanopatterning. The force sensing module utilizes a leaf spring mechanism and a capacitive displacement sensor and it has been designed to provide a measuring range from 80 ${\mu}N$ to 8 N. This force sensing module is mounted on a PZT driven in-feed motion stage with 1 nm resolution. The sample can be moved by X-Y scanning motion stage with 5 nm resolution. In nano indentation experiments and patterning experiments, the machining forces were controlled and monitored by the force sensing module. Then, the patterned samples were measured by AFM. Experimental results demonstrated that the developed system can be used as an effective device in nano indentation and nanopatterning operation.

• Smart Structures and Systems
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• v.6 no.3
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• pp.211-223
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• 2010

Accurate sensing of mechanical strains in civil structures is critical for optimizing structure reliability and lifetime. For instance, combined with intelligent control systems, electromechanical sensor output feedback has the potential to be employed for nondestructive damage evaluation. Application of Ionic Polymer Transducers (IPTs) represents a relatively new sensing approach with more than an order of magnitude higher sensitivity than traditional piezoelectric sensors. The primary reason this sensor has not been widely used to date is an inadequate understanding of the physics responsible for IPT sensing. This paper presents models and experiments defending the hypothesis of a streaming potential sensing mechanism.

• Geomechanics and Engineering
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• v.24 no.4
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• pp.337-348
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• 2021

Brillouin Optical Frequency Domain Analysis (BOFDA) is a distributed fiber optic sensing (DFOS) technique that has unique advantages for performance monitoring of piles. However, the complicated production process and harsh operating environment of offshore PHC pipe piles make it difficult to apply this method to pile load testing. In this study, sensing cables were successfully pre-installed into an offshore PHC pipe pile directly for the first time and the BOFDA technique was used for in-situ monitoring of the pile under axial load. High-resolution strain and internal force distributions along the pile were obtained by the BOFDA sensing system. A finite element analysis incorporating the Degradation and Hardening Hyperbolic Model (DHHM) was carried out to evaluate and predict the performance of the pile, which provides an improved insight into the offshore pile-soil interaction mechanism.

• Fiber Technology and Industry
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• v.2 no.4
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• pp.479-484
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• 1998

• Journal of Internet Computing and Services
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• v.12 no.2
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• pp.1-8
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• 2011

In this paper, we propose an effective method for cooperative spectrum sensing in cognitive radios where cognitive user(CR) with the highest reliability sensing data is only selected and allowed to report its local decision to FC as only decision making node. The proposed scheme enables CR users to implicitly compare their sensing data reliabilities based on their likelihood ratio, without any collaboration among cognitive radio users. Due to the mechanism, the proposed cooperative scheme can achieves a high spectrum sensing performance while only requiring extremely low cooperation resources such as signaling overhead and cooperative time in comparison with other existing methods such as maximum ratio combination (MRC) based, equal gain combination (EGC) based and conventional hard combination based cooperative sensing methods.

• Proceedings of the KSRS Conference
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• 2003.11a
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• pp.277-279
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• 2003

The study utilizes remote sensing as the main monitoring means. With different spatial high-resolution, multichannel ASTER remote sensing image as the main information in Beijing city zone; with regional border and statistical data as auxiliary factor a study between the thermal space distribution character and the underground medium is analyzed based on the GIS logical algorithm and synthetic analysis technology. Results show thermal forming mechanism and the rule of distribution is mainly related to the underground medium and the change of the city distribution. Different underground medium has different degree and intensity influence on the thermal space distribution. Furthermore, urban greenbelt and water areas can reduce the thermal effect and large-scale greenbelt creates green island effect. In addition, Road net, residential area, population density, heat resources and so on have some positive effect on the thermal distribution, which increase the local temperature and intensity on the other hand. It is important to study the thermal distribution and its related factors, which contributes to the plan, construction and development of the city.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.28 no.4
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• pp.999-1007
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• 2018

To implement crowdsensing system in reality, trustiness between service provider server and user is necessary. Service provider server could manipulate the evaluation of sensing data to reduce incentive. Moreover, user could send a fake sensing data to get unjust incentive. In this paper, we adopt private blockchain on crowdsensing system, and thus paid incentives and sent data are unmodifiablely recorded. It makes server and users act as watcher of each others. Through adopting smart contract, our system automates sensing data evaluation and opens to users how it works. Finally, we show the feasibility of proposing system with performance evaluation and comparison with other systems.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.13 no.9
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• pp.4572-4586
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• 2019

Mobile Edge Computing (MEC) and Information-Centric Networking (ICN) are essential network architectures for the future Internet. The advantages of MEC and ICN such as computation and storage capabilities at the edge of the network, in-network caching and named-data communication paradigm can greatly improve the quality of video streaming applications. However, the packet loss in wireless network environments still affects the video streaming performance and the existing loss recovery approaches in ICN does not exploit the capabilities of MEC. This paper proposes a Deep Learning based Loss Recovery Mechanism (DL-LRM) for video streaming over MEC based ICN. Different with existing approaches, the Forward Error Correction (FEC) packets are generated at the edge of the network, which dramatically reduces the workload of core network and backhaul. By monitoring network states, our proposed DL-LRM controls the FEC request rate by deep reinforcement learning algorithm. Considering the characteristics of video streaming and MEC, in this paper we develop content caching detection and fast retransmission algorithm to effectively utilize resources of MEC. Experimental results demonstrate that the DL-LRM is able to adaptively adjust and control the FEC request rate and achieve better video quality than the existing approaches.