• Journal of the Korea Society of Computer and Information
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• v.22 no.5
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• pp.81-88
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• 2017

Solar-powered wireless sensor nodes can use extra energy to obtain additional data to increase the precision. However, if the amount of data sensed is increased indiscriminately, the overhead of relay nodes may increase, and their energy may be exhausted. In this paper, we introduce a sensing and compression rate selection scheme to increase the amount of data obtained while preventing energy exhaustion. In this scheme, the neighbor nodes of the sink node determine the limit of data to be transmitted according to the allocated energy and their descendant nodes, and the other nodes select a compression algorithm appropriate to the allocated energy and the limitation of data to be transmitted. A simulation result verifies that the proposed scheme gathers more data with a lower number of blackout nodes than other schemes. We also found that it adapts better to changes in node density and the amount of energy harvested.

• Journal of the Korean Society of Radiology
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• v.15 no.3
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• pp.281-291
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• 2021

This study aimed to measure the quantitative changes in images according to the use of compressed sensing in expressing the slow flow rate in TOF MRA test using magnetic resonance imaging. This study set different blood flow rate sections by using auto-injector and flow phantom and compared changes in the SNR, CNR, SSIM, and RMSE measurements by different CS factors between TOF with CS and TOF without CS. One-way ANOVA was performed to test the effect on the image induced by the increase of the CS factor. The results revealed that TOF MRA with CS significantly decreased scan time without significantly affecting SNR and CNR compared to TOF MRA with CS. On the other hand, the differences in SSIM and RMSE between TOF with CS and TOF without CS increased as the CS factor increased. Therefore, it is necessary to efficiently reduce scan time by adapting the CS technique while considering the appropriate range of the CS factor. Additionally, more studies are needed to evaluate CS factors and the similarity precision of images further.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.25 no.9
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• pp.952-958
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• 2014

In this paper, we propose a parametric sparse recovery algorithm(SRA) applied to a radar signal model, based on the compressive sensing(CS), for the ISAR(Inverse Synthetic Aperture Radar) image reconstruction from an incomplete radar-cross-section(RCS) data and for the estimation of rotation rate of a target. As the SRA, the iteratively-reweighted-least-square(IRLS) is combined with the radar signal model including chirp components with unknown chirp rate in the cross-range direction. In addition, the particle swarm optimization(PSO) technique is considered for searching correct parameters related to the rotation rate. Therefore, the parametric SRA based on the IRLS can reconstruct ISAR image and estimate the rotation rate of a target efficiently, although there exists missing data in observed RCS data samples. The performance of the proposed method in terms of image entropy is also compared with that of the traditional interpolation methods for the incomplete RCS data.

• Smart Structures and Systems
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• v.6 no.5_6
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• pp.731-748
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• 2010

Impact detection and health monitoring are very important tasks for civil infrastructures, such as bridges. Piezoceramic based transducers are widely researched for these tasks due to the piezoceramic material's inherent advantages of dual sensing and actuation ability, which enables the active sensing method for structural health monitoring with a network of piezoceramic transducers. Wireless sensor networks, which are easy for deployment, have great potential in health monitoring systems for large civil infrastructures to identify early-age damages. However, most commercial wireless sensor networks are general purpose and may not be optimized for a network of piezoceramic based transducers. Wireless networks of piezoceramic transducers for active sensing have special requirements, such as relatively high sampling rate (at a few-thousand Hz), incorporation of an amplifier for the piezoceramic element for actuation, and low energy consumption for actuation. In this paper, a wireless network is specially designed for piezoceramic transducers to implement impact detection and active sensing for structural health monitoring. A power efficient embedded system is designed to form the wireless sensor network that is capable of high sampling rate. A 32 bit RISC wireless microcontroller is chosen as the main processor. Detailed design of the hardware system and software system of the wireless sensor network is presented in this paper. To verify the functionality of the wireless sensor network, it is deployed on a two-story concrete frame with embedded piezoceramic transducers, and the active sensing property of piezoceramic material is used to detect the damage in the structure. Experimental results show that the wireless sensor network can effectively implement active sensing and impact detection with high sampling rate while maintaining low power consumption by performing offline data processing and minimizing wireless communication.

• Journal of information and communication convergence engineering
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• v.11 no.4
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• pp.223-228
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• 2013

Cognitive radio has been recently considered a promising technology to improve spectrum utilization by enabling secondary access to licensed bands that are not used by primary users temporarily or spatially. A prerequisite to this secondary access is the lack of interference to the primary system. This requirement makes spectrum sensing a key process for cognitive radio. In this study, we consider amplify and forward (AF)-based cooperative spectrum sensing for cognitive radio networks where multiple relay nodes are utilized to amplify and forward the primary user signal for better spectrum sensing, and maximum ratio combining is used for fusion detection by a cognitive coordinator. Further, the detection probability and the bit error rate of AF-based cooperative spectrum sensing are analyzed in fading multiple cognitive relay channels. The simulation results show that the AF-based cooperative spectrum sensing scheme outperforms the conventional scheme.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.38B no.9
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• pp.765-774
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• 2013

In this paper, we present a cooperative compressed spectrum sensing scheme for correlated signals in decentralized wideband cognitive radio networks. Compressed sensing is a signal processing technique that can recover signals which are sampled below the Nyquist rate with high probability, and can solve the necessity of high-speed analog-to-digital converter problem for wideband spectrum sensing. In compressed sensing, one of the main issues is to design recovery algorithms which accurately recover original signals from compressed signals. In this paper, in order to achieve high recovery performance, we consider the multiple measurement vector model which has a sequence of compressed signals, and propose a cooperative sparse Bayesian recovery algorithm which models the temporal correlation of the input signals.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.7 no.6
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• pp.101-109
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• 2008

In this paper, we introduce clustering scheme to calculate probability of detection which is practically required for conventional weighted-collaborative sensing technique. We also propose an improved weighted-collaborative spectrum sensing scheme using new weight generation algorithm to achieve better performance in Cognitive Radio systems. We calculate Pd in each cluster which is a CR users group with similar channel situation. New weight factor is generated using square sum of all cluster's Pds. Simulations under slow fading show that we can get better total detection probability and lower false alarm rate when PU (Primary User) suddenly terminates their transmission.

• Smart Structures and Systems
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• v.18 no.6
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• pp.1203-1215
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• 2016

When strain sensing cables are under long-term stress and cyclic loading, creep may occur in the jacket material and each layer of the cable structure may slide relative to other layers, causing fatigue in the cables. This study proposes a device for testing the fatigue characteristics of three types of cables operating under different conditions to establish a decay model for observing the patterns of strain decay. The fatigue characteristics of cables encased in polyurethane (PU), GFRP-reinforced, and wire rope-reinforced jackets were compared. The findings are outlined as follows. The cable strain decayed exponentially, and the decay process involved quick decay, slow decay, and stabilization stages. Moreover, the strain decay increased with the initial strain and tensile frequency. The shorter the unstrained period was, the more similar the initial strain levels of the strain decay curves were to the stabilized strain levels of the first cyclic elongation. As the unstrained period increased, the initial strain levels of the strain decay curves approached those of the first cyclic elongation. The tested sensing cables differed in the amount and rate of strain decay. The wire rope-reinforced cable exhibited the smallest amount and rate of decay, whereas the GFRP-reinforced cable demonstrated the largest.

• Journal of Sensor Science and Technology
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• v.22 no.3
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• pp.233-237
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• 2013

We fabricated electrolyte-insulator-semiconductor (EIS) devices using a solution process and measured the sensing properties of EIS devices according to the thicknesses of sensing membrane. For high pH sensitivity and better stability properties, we used $SiO_2/HfO_x$ (OH) layer as a sensing membrane. In this work, $HfO_x$ sensing membranes were deposited on 5 nm thick $SiO_2$ buffer layer by spin coater with thicknesses of 15, 31, 42, 55 nm, respectively. As a result, we founded that the thickness of $HfO_x$ sensing membrane affects to sensitivity and chemical stability of EIS device. Especially, the EIS device with 42 nm thick $HfO_x$ membrane showed superior sensing ability in terms of pH-sensitivity, linearity, hysteresis voltage and drift rate characteristics than the other devices. In conclusion, we confirmed that it is possible to improve the sensing ability and the chemical stability properties using optimized thickness of sensing membrane and proper annealing process.

• Science of Emotion and Sensibility
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• v.21 no.1
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• pp.35-44
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• 2018

This study suggests the sensing method of the Three-dimensional respiration rate sensor based on surface area changes, and exploring the design direction of the three-dimensional breathing sensor and the design orientation of the garment. To achieve this, two types of three-dimensional respiration rate sensor were produced, and the study of the dummy and the subjects studied. The study I investigated the possibility of measurement of the three-dimensional respiration sensor by the study variables of the sensor type and speed of respiration. The study II proposes a suitable type of sensor for each of the three measuring positions in addition to the study variables in the study I. To evaluate accuracy, reproducibility, and reliability of the three-dimensional respiration rate sensor, the BIOPAC was used to measure the respiration rate simultaneously with the three-dimensional respiration rate sensor. Through all these results of the experiment, it explored the possibility of measurement of the three-dimensional respiration sensor for the dummy. It also proposed a suitable type of sensor by measuring the respiration rate for the human body.