• Current Optics and Photonics
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• v.7 no.2
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• pp.200-206
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• 2023

Near-infrared (NIR) sensing technology using CMOS image sensors is used in many applications, including automobiles, biological inspection, surveillance, and mobile devices. An intuitive way to improve NIR sensitivity is to thicken the light absorption layer (silicon). However, thickened silicon lacks NIR sensitivity and has other disadvantages, such as diminished optical performance (e.g. crosstalk) and difficulty in processing. In this paper, a pixel structure for NIR sensing using a stacked CMOS image sensor is introduced. There are two photodetection layers, a conventional layer and a bottom photodiode, in the stacked CMOS image sensor. The bottom photodiode is used as the NIR absorption layer. Therefore, the suggested pixel structure does not change the thickness of the conventional photodiode. To verify the suggested pixel structure, sensitivity was simulated using an optical simulator. As a result, the sensitivity was improved by a maximum of 130% and 160% at wavelengths of 850 nm and 940 nm, respectively, with a pixel size of 1.2 ㎛. Therefore, the proposed pixel structure is useful for NIR sensing without thickening the silicon.

• Korean Journal of Remote Sensing
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• v.33 no.4
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• pp.391-400
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• 2017

Geo-based application services linked with the Open Geospatial Consortium (OGC) Web Processing Service (WPS) protocol have been regarded as an important standardized framework for of digital earth building in the web environments. The WPS protocol provides interface standards for analysis functionalities within geo-spatial processing in web-based service systems. Despite its significance, there is few performance tests of WPS applications. The main motivation in this study is to perform the comparative performance test on WPS standards. Test system, which was composed of WPS servers, WPS framework, data management module, geo-based data processing module and client-sided system, was implemented by fully open source stack. In this system, two kinds of geo-based image processing functions such as cloud detection and gradient magnitude computation were applied. The performance test of different server environments of non-WPS, synchronous WPS 1.0 and asynchronous WPS 2.0 was carried out using 100 threads and 400 threads corresponds client users on a web-based application service. As the result, at 100 threads, performance of three environments was within an adjacent range in the average response time to complete the processing of each thread. At 400 threads, the application case of WPS 2.0 showed the distinguished characteristics for higher performance in the response time than the small threads cases. It is thought that WPS 2.0 contributes to settlement of without performance problems such as time delay or thread accumulation.

• The Journal of the Acoustical Society of Korea
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• v.39 no.3
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• pp.179-190
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• 2020

In this paper, we estimated the Direction of Arrival (DOA) using Conventional BeamForming (CBF), adaptive beamforming and compressive beamforming. Minimum Variance Distortionless Response (MVDR) and Multiple Signal Classification (MUSIC) are used as the adaptive beamforming, and grid-free compressive sensing is applied for the compressive sensing beamforming. Theoretical background and limitations of each technique are introduced, and the performance of each technique is compared through simulation and real experiments. The real experiments are conducted in the presence of reflected signal, transmitting a sound using two speakers and receiving acoustic data through a linear array consisting of eight microphones. Simulation and experimental results show that the adaptive beamforming and the grid-free compressive beamforming have a higher resolution than conventional beamforming when there are uncorrelated signals. On the other hand, the performance of the adaptive beamforming is degraded by the reflected signals whereas the grid-free compressive beamforming still improves the conventional beamforming resolution regardless of reflected signal presence.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.12 no.6
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• pp.2492-2512
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• 2018

Multicast communication can effectively reduce network resources consumption in contrast with unicast. With the advent of SDN, current researches on multicast traffic are mainly conducted in the SDN scenario, thus to mitigate the problems of IP multicast such as the unavoidable difficulty in traffic engineering and high security risk. However, migration to SDN cannot be achieved in one step, hybrid SDN emerges as a transitional networking form for ISP network. In hybrid SDN, for acquiring similar TE and security performance as in SDN multicast, we redirect every multicast traffic to an appropriate SDN node before reaching the destinations of the multicast group, thus to build up a core-based multicast tree substantially which is first introduced in CBT. Based on the core SDN node, it is possible to realize dynamic control over the routing paths to benefit traffic engineering (TE), while multicast traffic manageability can also be obtained, e.g., access control and middlebox-supported network services. On top of that, multiple core-based multicast trees are constructed for each multicast group by fully taking advantage of the routing flexibility of SDN nodes, in order to further enhance the TE performance. The multicast routing and splitting (MRS) algorithm is proposed whereby we jointly and efficiently determine an appropriate core SDN node for each group, as well as optimizing the traffic splitting fractions for the corresponding multiple core-based trees to minimize the maximum link utilization. We conduct simulations with different SDN deployment rate in real network topologies. The results indicate that, when 40% of the SDN switches are deployed in HSDN as well as calculating 2 trees for each group, HSDN multicast adopting MRS algorithm can obtain a comparable TE performance to SDN multicast.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.36 no.8C
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• pp.529-535
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• 2011

After permission for utilization of TV white space by FCC, a lot of attentions are focused on spectrum sensing, and various spectrum sensing methods have been proposed. However, they do not consider real environment, thus they are hard to achieve the required performance. In this paper, we propose resolutions for the problem which could be occurred in implementation of spectrum sensing module and verify performance of the proposed methods with computer simulation. The first proposed method utilizes channel status information to separate received signal and spurious for reducing false alarm probability caused by system internal spurious. The another proposed scheme is subband normalization method to prevent miss detection caused by multiple narrow band signals with different received signal strength. The simulation results verify that we can prevent false alarm cause by spurious components with the proposed system internal spurious cognition. Moreover, the proposed subband normalization method shows that it could overcome performance degradation caused by received signal strength difference.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.8 no.5
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• pp.121-127
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• 2009

Wireless devices can communicate between each other without existing infrastructure in mobile Ad-hod network. Ad hoc networks can be used under difficult conditions, where it is difficult to construct infrastructures, such as shadowing areas, disaster areas, war area, and so on. In order to support to considerable and various wireless services, more spectrum resources are needed. However, efficient utilization of the frequency resource is difficult because of spectrum scarcity and the conventional frequency regulation. Ad-hoc networks employing cognitive radio (CR) system that guarantee high spectrum utilization provide effective way to increase the network capacity. In this paper, we simulate and compare the performance of conventional single and cooperative spectrum sensing with CR system using ad-hoc networks. And we demonstrate performance improvement by analyzing the system performance.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.10 no.10
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• pp.4661-4680
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• 2016

Cognitive radio (CR) technology is an effective solution to the spectrum scarcity issue. Collaborative spectrum sensing is known as a promising technique to improve the performance of spectrum sensing in cognitive radio networks (CRNs). However, collaborative spectrum sensing is vulnerable to spectrum data falsification (SSDF) attack, where malicious users (MUs) may send false sensing data to mislead other secondary users (SUs) to make an incorrect decision about primary user (PUs) activity, which is one of the key adversaries to the performance of CRNs. In this paper, we propose a coalition based malicious users detection (CMD) algorithm to detect the malicious user in CRNs. The proposed CMD algorithm can efficiently detect MUs base on the Geary'C theory and be modeled as a coalition formation game. Specifically, SSDF attack is one of the key issues to affect the resource allocation process. Focusing on the security issues, in this paper, we analyze the power allocation problem with MUs, and propose MUs detection based power allocation (MPA) algorithm. The MPA algorithm is divided into two steps: the MUs detection step and the optimal power allocation step. Firstly, in the MUs detection step, by the CMD algorithm we can obtain the MUs detection probability and the energy consumption of MUs detection. Secondly, in the optimal power allocation step, we use the Lagrange dual decomposition method to obtain the optimal transmission power of each SU and achieve the maximum utility of the whole CRN. Numerical simulation results show that the proposed CMD and MPA scheme can achieve a considerable performance improvement in MUs detection and power allocation.

• Computers and Concrete
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• v.30 no.5
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• pp.301-310
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• 2022

Cement-based sensors have been widely used as structural health monitoring systems, however, their long-term sensing performance have not actively investigated. In this study, a deep learning-based methodology is adopted to predict the long-term piezoresistive properties of cement-based sensors. Samples with different multi-walled carbon nanotube contents (0.1, 0.3, and 0.5 wt.%) are fabricated, and piezoresistive tests are conducted over 10,000 loading cycles to obtain the training data. Time-dependent degradation is predicted using a modified long short-term memory (LSTM) model. The effects of different model variables including the amount of training data, number of epochs, and dropout ratio on the accuracy of predictions are analyzed. Finally, the effectiveness of the proposed approach is evaluated by comparing the predictions for long-term piezoresistive sensing performance with untrained experimental data. A sensitivity of 6% is experimentally examined in the sample containing 0.1 wt.% of MWCNTs, and predictions with accuracy up to 98% are found using the proposed LSTM model. Based on the experimental results, the proposed model is expected to be applied in the structural health monitoring systems to predict their long-term piezoresistice sensing performances during their service life.

• Journal of the Institute of Electronics Engineers of Korea TC
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• v.47 no.8
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• pp.42-46
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• 2010

Energy detection based spectrum sensing compares the energy of a received signal from a primary user with a detection threshold and decides whether it is active or not in the frequency band of interest. Here the detection threshold depends on not only a target false alarm probability but also the level of the noise energy in the band. So, if the noise energy changes, the detection threshold must be adjusted accordingly to maintain the given false alarm probability. Most previous works on energy detection for spectrum sensing are based on the assumption that noise energy is known a priori. In this paper, we present a new energy detection scheme updating its detection threshold under the assumption that the noise is white, and analyze its detection performance. Analytic results show that the proposed scheme can maintain a target false alarm rate without regard to the noise energy level and its spectrum sensing performance gets better as the time bandwidth product of the signal used to estimate the noise energy increases.

• Korean Journal of Remote Sensing
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• v.28 no.3
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• pp.319-327
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• 2012

In this paper, we introduce a newly developed photogrammetric software for automatic generation of high quality geo-products and its performance assessment carried out using various satellite images. Our newly developed software provides the latest techniques of an optimized sensor modelling, ortho-image generation and automated Digital Elevation Model (DEM) generation for diverse remote sensing images. In particular, images from dual- and multi-sensor images can be integrated for 3D mapping. This can be a novel innovation toward a wider applicability of remote sensing data, since 3D mapping has been limited within only single-sensor so far. We used Kompsat-2, Ikonos, QuickBird, Spot-5 high resolution satellite images to test an accuracy of 3D points and ortho-image generated by the software. Outputs were assessed by comparing reliable reference data. From various sensor combinations 3D mapping were implemented and their accuracy was evaluated using independent check points. Model accuracy of 1~2 pixels or better was achieved regardless of sensor combination type. The high resolution ortho-image results are consistent with the reference map on a scale of 1:5,000 after being rectified by the software and an accuracy of 1~2 pixels could be achieved through quantitative assessment. The developed software offers efficient critical geo-processing modules of various remote sensing images and it is expected that the software can be widely used to meet the demand on the high-quality geo products.