• Current Optics and Photonics
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• 제4권6호
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• pp.530-539
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• 2020

Hyperspectral images feature a relatively narrow band and are easily disturbed by noise. Accurate estimation of the types and parameters of noise in hyperspectral images can provide prior knowledge for subsequent image processing. Existing hyperspectral-noise estimation methods often pay more attention to the use of spectral information while ignoring the spatial information of hyperspectral images. To evaluate the noise in hyperspectral images more accurately, we have proposed a spectral-spatial cooperative noise-evaluation method. First, the feature of spatial information was extracted by Gabor-filter and K-means algorithms. Then, texture edges were extracted by the Otsu threshold algorithm, and homogeneous image blocks were automatically separated. After that, signal and noise values for each pixel in homogeneous blocks were split with a multiple-linear-regression model. By experiments with both simulated and real hyperspectral images, the proposed method was demonstrated to be effective and accurate, and the composition of the hyperspectral image was verified.

• Current Optics and Photonics
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• 제6권5호
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• pp.473-478
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• 2022

To overcome the capture-range problem in phase-diversity phase retrieval (PDPR), a geometrical-optics initial-estimate method is proposed to avoid a local minimum and to improve the accuracy of laser-wavefront measurement. We calculate the low-order aberrations through the geometrical-optics model, which is based on the two spot images in the propagation path of the laser, and provide it as a starting guess for the PDPR algorithm. Simulations show that this improves the accuracy of wavefront recovery by 62.17% compared to other initial values, and the iteration time with our method is reduced by 28.96%. That is, this approach can solve the capture-range problem.

• International journal of advanced smart convergence
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• 제12권3호
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• pp.186-191
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• 2023

This study would investigate the generative AIs currently in service in the era of hyperscale AIs and explore measures for the use of generative AIs, focusing on 'ChatGPT,' which has received attention as a leader of generative AIs. Among the various generative AIs, this study selected ChatGPT, which has rich application cases to conduct research, investigation, and use. This study investigated the concept, learning principle, and features of ChatGPT, identified the algorithm of conversational AI as one of the specific cases and checked how it is used. In addition, by comparing various cases of the application of conversational AIs such as Google's Bard and MS's NewBing, this study sought efficient ways to utilize them through the collected cases and conducted research on the limitations of conversational AI and precautions for its use. If connected to city-related databases, it can provide information on city infrastructure, transportation systems, and public services, so residents can easily get the information they need. We want to apply this research to enrich the lives of our citizens.

• Journal of Information Processing Systems
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• 제18권6호
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• pp.822-829
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• 2022

According to existing study into the remote fault diagnosis procedure, the current diagnostic approach has an imperfect decision model, which only supports communication in a close distance. An Internet of Things (IoT)-based remote fault diagnostic approach for wind power equipment is created to address this issue and expand the communication distance of fault diagnosis. Specifically, a decision model for active power coordination is built with the mechanical energy storage of power generation equipment with a remote diagnosis mode set by decision tree algorithms. These models help calculate the failure frequency of bearings in power generation equipment, summarize the characteristics of failure types and detect the operation status of wind power equipment through IoT. In addition, they can also generate the point inspection data and evaluate the equipment status. The findings demonstrate that the average communication distances of the designed remote diagnosis method and the other two remote diagnosis methods are 587.46 m, 435.61 m, and 454.32 m, respectively, indicating its application value.

• Journal of Communications and Networks
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• 제18권1호
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• pp.65-74
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• 2016

Ship ad-hoc network (SANET) extends the coverage of the maritime communication among ships with the reduced cost. To fulfill the growing demands of real-time services, the SANET requires an efficient clock time synchronization algorithm which has not been carefully investigated under the ad-hoc maritime environment. This is mainly because the conventional algorithms only suggest to decrease the beacon collision probability that diminishes the clock drift among the units. However, the SANET is a very large-scale network in terms of geographic scope, e.g., with 100 km coverage. The key factor to affect the synchronization performance is the signal propagation delay, which has not being carefully considered in the existing algorithms. Therefore, it requires a robust multi-hop synchronization algorithm to support the communication among hundreds of the ships under the maritime environment. The proposed algorithm has to face and overcome several challenges, i.e., physical clock, e.g., coordinated universal time (UTC)/global positioning system (GPS) unavailable due to the atrocious weather, network link stability, and large propagation delay in the SANET. In this paper, we propose a logical clock synchronization algorithm with multi-hop function for the SANET, namely multi-hop clock synchronization for SANET (MCSS). It works in an ad-hoc manner in case of no UTC/GPS being available, and the multi-hop function makes sure the link stability of the network. For the proposed MCSS, the synchronization time reference nodes (STRNs) are efficiently selected by considering the propagation delay, and the beacon collision can be decreased by the combination of adaptive timing synchronization procedure (ATSP) with the proposed STRN selection procedure. Based on the simulation results, we finalize the multi-hop frame structure of the SANET by considering the clock synchronization, where the physical layer parameters are contrived to meet the requirements of target applications.

• Journal of Electrical Engineering and Technology
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• 제10권1호
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• pp.92-101
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• 2015

As one type of power quality (PQ) disturbance sources, high-speed rail (HSR) can have major impacts on the power supply grid. Providing timely and accurate warning information for PQ problems of HSR is important for the safe and stable operation of traction power supply systems and the power supply grid. This study proposes a novel warning approach to identify PQ problems and provide warning prompts based on the monitored data of HSR. To embody the displacement and status change of monitored data, multi-features of different sliding windows are computed. To reflect the relative importance degree of these features in the overall evaluation, an analytic hierarchy process (AHP) is used to analyse the weights of multi-features. Finally, a multi-features similarity algorithm is applied to analyse the difference between monitored data and the reference data of HSR, and PQ warning results based on dynamic thresholds can be analysed to quantify its severity. Cases studies demonstrate that the proposed approach is effective and feasible, and it has now been applied to an actual PQ monitoring platform.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제5권12호
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• pp.2355-2373
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• 2011

Vision-based vehicle detector systems are becoming increasingly important in ITS applications. Real-time operation, robustness, precision, accurate estimation of traffic parameters, and ease of setup are important features to be considered in developing such systems. Further, accurate vehicle detection is difficult in varied complex traffic environments. These environments include changes in weather as well as challenging traffic conditions, such as shadow effects and jams. To meet real-time requirements, the proposed system first applies a color background to extract moving objects, which are then tracked by considering their relative distances and directions. To achieve robustness and precision, the color background is regularly updated by the proposed algorithm to overcome luminance variations. This paper also proposes a scheme of feedback compensation to resolve background convergence errors, which occur when vehicles temporarily park on the roadside while the background image is being converged. Next, vehicle occlusion is resolved using the proposed prior split approach and through reasoning for rule-based tracking. This approach can automatically detect straight lanes. Following this step, trajectories are applied to derive traffic parameters; finally, to facilitate easy setup, we propose a means to automate the setting of the system parameters. Experimental results show that the system can operate well under various complex traffic conditions in real time.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제6권4호
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• pp.1203-1222
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• 2012

To provide active notification and enhance drivers'awareness of their surroundings, a vision-based collision warning system that detects and monitors surrounding vehicles is proposed in this paper. The main objective is to prevent possible vehicle collisions by monitoring the status of surrounding vehicles, including the distance to the other vehicles in front, behind, to the left and to the right sides. In addition, the proposed system collects and integrates this information to provide advisory warnings to drivers. To offer the correct notification, an algorithm based on features of edge and morphology to detect vehicles is also presented. The proposed system has been implemented in embedded systems and evaluated on real roads in various lighting and weather conditions. The experimental results indicate that the vehicle detection ratios were higher than 97% in the daytime, and appropriate for real road applications.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제8권6호
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• pp.1914-1925
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• 2014

Inter-symbol interference (ISI) problem is inevitable when the guard interval (GI) is shorter than the delay spread (DS) for an orthogonal frequency division multiplexing (OFDM) system. Iterative techniques have been proposed to overcome such a problem. However, most of existing algorithms are not efficient for an OFDM system with a small GI working under the channel with a large DS. Especially in the case of the DS spans a longer time than the half of the OFDM symbol duration. On the other hand, conventional algorithms, which can reduce the effects of the severe ISI, often employ several impractical assumptions to support the conclusions. In this paper, we present a robust decision feedback equalizer (DFE) for the OFDM system to overcome the severe ISI problem. The proposed DFE removes the ISI in a same manner as the residual inter-symbol interference cancellation (RISIC) algorithm. However, the inter-carrier interference (ICI) is reduced via cyclicity removal instead of the cyclicity restoration used in the conventional algorithms. The link-level simulation (LLS) results indicate that our proposed DFE scheme can dramatically improve the BER performance when the DS spans longer than the half of ODFM symbol duration.

• Journal of Electrical Engineering and Technology
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• 제13권5호
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• pp.2134-2143
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• 2018

This work introduces a fault diagnosis method for transformer based on self-powered radio frequency identification (RFID) sensor tag and improved Hilbert-Huang transform (HHT). Consisted by RFID tag chip, power management circuit, MCU and accelerometer, the developed RFID sensor tag is used to acquire and wirelessly transmit the vibration signal. A customized power management including solar panel, low dropout (LDO) voltage regulator, supercapacitor and corresponding charging circuit is presented to guarantee constant DC power for the sensor tag. An improved band restricted empirical mode decomposition (BREMD) which is optimized by quantum-behaved particle swarm optimization (QPSO) algorithm is proposed to deal with the raw vibration signal. Compared with traditional methods, this improved BREMD method shows great superiority in reducing mode aliasing. Then, a promising fault diagnosis approach on the basis of Hilbert marginal spectrum variations is brought up. The measured results show that the presented power management circuit can generate 2.5V DC voltage for the rest of the sensor tag. The developed sensor tag can achieve a reliable communication distance of 17.8m in the test environment. Furthermore, the measurement results indicate the promising performance of fault diagnosis for transformer.