• Korean Journal of Remote Sensing
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• v.33 no.4
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• pp.445-454
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• 2017

The performance of spatial downscaling models depends on the quality of input coarse scale products. Thus, the impact of intrinsic errors contained in coarse scale satellite products on predictive performance should be properly assessed in parallel with the development of advanced downscaling models. Such an assessment is the main objective of this paper. Based on a synthetic satellite precipitation product at a coarse scale generated from rain gauge data, two synthetic precipitation products with different amounts of error were generated and used as inputs for spatial downscaling. Geographically weighted regression, which typically has very high explanatory power, was selected as the trend component estimation model, and area-to-point kriging was applied for residual correction in the spatial downscaling experiment. When errors in the coarse scale product were greater, the trend component estimates were much more susceptible to errors. But residual correction could reduce the impact of the erroneous trend component estimates, which improved the predictive performance. However, residual correction could not improve predictive performance significantly when substantial errors were contained in the input coarse scale data. Therefore, the development of advanced spatial downscaling models should be focused on correction of intrinsic errors in the coarse scale satellite product if a priori error information could be available, rather than on the application of advanced regression models with high explanatory power.

• Journal of the Institute of Electronics Engineers of Korea TC
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• v.45 no.1
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• pp.72-77
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• 2008

In this paper, we propose a novel structure where the energy detector has multiples of verification using time delay in order to improve its performance. Additionally, the performance is investigated by simulation and compared to that of the original energy detector. The simulation result shows that the proposed scheme improves the performance when SNR is compared with the mis-detection probability for both 1% and 10% of false alarm probability. The performance is also described in terms of ROC.

• International Journal of High-Rise Buildings
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• v.11 no.2
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• pp.125-135
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• 2022

While buildings in recent days become taller and larger, many problems occur during the management of construction. Particularly, as the vertical movement of manpower and materials during construction has become longer while the lifting frequency and load increase, the need for a good lifting management practice is also increasing. Therefore, this study presents a real-time lifting performance monitoring system that can store and manage lifting records for construction management. Through review of literature and preceding studies related to construction lift, the concept of lift planning and operation management was understood, leading to the development of a system to monitor lifting operation and performance information. This system enabled quick measurement of the lifting performance during construction phase while responding to changes in the project schedule. To verify this system, a case study was conducted in which the current status and characteristics of the sensing-based lifting performance were derived.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.12 no.4
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• pp.1471-1488
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• 2018

Interference mitigation is a significant issue in the cognitive heterogeneous networks, this paper studied how to reduce the interference to macrocell users (MU) and improve system throughput. Establish the interference model with imperfect spectrum sensing by analyzing the source of interference complexity. Based on the user topology, the optimize problem was built to maximize the downlink throughput under given interference constraint and the total power constraint. We decompose the resource allocation problem into subcarrier allocation and power allocation. In the subcarrier assignment step, the allocated number of subcarriers satisfies the requirement of the femtocell users (FU).Then, we designed the power allocation algorithm based on the Lagrange multiplier method and the improved water filling method. Simulation results and performance analyses show that the proposed algorithm causes less interference to MU than the algorithm without considering imperfect spectrum sensing, and the system achieves better throughput performance.

• Advances in aircraft and spacecraft science
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• v.4 no.5
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• pp.543-553
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• 2017

Vibration is a source of performance degradation in all optical imaging systems. Performance of high resolution remote sensing payloads is often limited due to satellite platform vibrations. Effects of Linear and high frequency sinusoidal vibrations on the system MTF are known exactly in closed form but the low frequency vibration effects is a random process and must be considered statistically. Usually the vibration MTF budget is defined based on the mission requirements and the overall MTF limitations. For analyzing low frequency effects, designer must know all the systems specifications and parameters. With a good understanding of harmful vibration frequencies and amplitudes in the system preliminary design phase, their effects could be removed totally or partially. This procedure is cost effective and let the designer to eliminate just harmful vibrations and avoids over-designing. In this paper we have analyzed the effects of low-frequency platform vibrations on the payload's modulation transfer function. We have used a statistical analysis to find the probability of imaging with a MTF equal or greater than a pre-defined budget for different missions. The worst and average cases have been discussed and finally we have proposed "look-up figures". Using these look-up figures, designer can choose the electro-optical parameters in such a way that vibration effects be less than its pre-defined budget. Furthermore, using the results, we can propose a damping profile based on which vibration frequencies and amplitudes must be eliminated to stabilize the payload system.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.31 no.12C
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• pp.1216-1223
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• 2006

In many imaging devices, a single image sensor is used, which is covered by a color filter array to filter out the specific color components from light. Since an image acquired from this image sensors have a color components at each pixel, it is needed to be reconstructed to a perfect image. In this paper, a new color interpolation method for the imaging devices having a single image sensor is proposed. The proposed method improves a edge sensing function to obtain satisfactory results in edges of an image, md presents a new inter-channel correlation for improving interpolation performance in smooth region. We have compared our method with several exiting methods, and our experimental results have proved better interpolation performance in comparing with the other results.

• ETRI Journal
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• v.28 no.1
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• pp.59-66
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• 2006

Learning behaviors of a radial basis function network (RBFN) using a singular value decomposition (SVD) and stochastic gradient (SG) algorithm, together named RBF-SVD-SG, for odor sensing systems are analyzed, and a fast training method is proposed. RBF input data is from a conducting polymer sensor array. It is revealed in this paper that the SG algorithm for the fine-tuning of centers and widths still shows ill-behaving learning results when a sufficiently small convergence coefficient is not used. Since the tuning of centers in RBFN plays a dominant role in the performance of RBFN odor sensing systems, our analysis is focused on the center-gradient variance of the RBFN-SVD-SG algorithm. We found analytically that the steadystate weight fluctuation and large values of a convergence coefficient can lead to an increase in variance of the center-gradient estimate. Based on this analysis, we propose to use the least mean square algorithm instead of SVD in adjusting the weight for stable steady-state weight behavior. Experimental results of the proposed algorithm have shown faster learning speed and better classification performance.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.9 no.12
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• pp.5189-5208
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• 2015

To address the contradiction between data aggregation and data security in wireless sensor networks, a Recoverable Privacy-preserving Integrity-assured Data Aggregation (RPIDA) scheme is proposed based on privacy homomorphism and aggregate message authentication code. The proposed scheme provides both end-to-end privacy and data integrity for data aggregation in WSNs. In our scheme, the base station can recover each sensing data collected by all sensors even if these data have been aggregated by aggregators, thus can verify the integrity of all sensing data. Besides, with these individual sensing data, base station is able to perform any further operations on them, which means RPIDA is not limited in types of aggregation functions. The security analysis indicates that our proposal is resilient against typical security attacks; besides, it can detect and locate the malicious nodes in a certain range. The performance analysis shows that the proposed scheme has remarkable advantage over other asymmetric schemes in terms of computation and communication overhead. In order to evaluate the performance and the feasibility of our proposal, the prototype implementation is presented based on the TinyOS platform. The experiment results demonstrate that RPIDA is feasible and efficient for resource-constrained sensor nodes.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.14 no.5
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• pp.61-65
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• 2014

In this paper, we propose a method using cooperative spectrum sensing to avoid multipath and frequency selective fading. One of methods in conventional scheme was multi input multi output (MIMO) solution. However, in the wireless environment, mobile device hardly supports multi antenna because of limitation of hardware. Motivated from above problems, the proposed method provides the information of excellent channel to transmitter. As a result, quality of service (QoS) required by users can be satisfied. Finally, performance of the proposed protocol is analyzed in term of bit error rate (BER).

• International Journal of Control, Automation, and Systems
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• v.6 no.3
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• pp.351-363
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• 2008

This paper is concerned with tasking and guidance of networked airborne sensors to achieve fault-tolerant sensing. The sensors are coordinated to locate hostile transmitters by intercepting and processing their signals. Faults occur when some sensor-carrying vehicles engaged in target location missions are lost. Faults effectively change the network architecture and therefore degrade the network performance. The first objective of the paper is to optimally allocate a finite number of sensors to targets to maximize the network life and availability. To that end allocation policies are solved from relevant Markov decision problems. The sensors allocated to a target must continue to adjust their trajectories until the estimate of the target location reaches a prescribed accuracy. The second objective of the paper is to establish a criterion for vehicle guidance for which fault-tolerant sensing is achieved by incorporating the knowledge of vehicle loss probability, and by allowing network reconfiguration in the event of loss of vehicles. Superior sensing performance in terms of location accuracy is demonstrated under the established criterion.