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Computers, Materials & Continua 2024年第8期80卷 1927-1945页

作者： Muhammad Ayoub Kamal Muhammad Mansoor Alam Aznida Abu Bakar Sajak Mazliham Mohd Su’ud malaysian institute of information technology(MIIT) Universiti Kuala LumpurKuala Lumpur50250Malaysia Faculty of Computing and Informatics Multimedia UniversityCyberjaya63100Malaysia Depertment of Computer Science DHA Suffa UniversityKarachiSindh75500Pakistan Riphah institute of System Engineering(RISE) Faculty of ComputingRiphah International UniversityIslamabad46000Pakistan malaysian France institute(MFI) Universiti Kuala LumpurKuala Lumpur50250Malaysia Faculty of Engineering and information technology School of Computer ScienceUniversity of Technology SydneyUltimoNSW 2007Australia

In situations when the precise position of a machine is unknown,localization becomes *** research focuses on improving the position prediction accuracy over long-range(LoRa)network using an optimized machine learning-based *** order to increase the prediction accuracy of the reference point position on the data collected using the fingerprinting method over LoRa technology,this study proposed an optimized machine learning(ML)based *** signal strength indicator(RSSI)data from the sensors at different positions was first gathered via an experiment through the LoRa network in a multistory round layout *** noise factor is also taken into account,and the signal-to-noise ratio(SNR)value is recorded for every RSSI *** study concludes the examination of reference point accuracy with the modified KNN method(MKNN).MKNN was created to more precisely anticipate the position of the reference *** findings showed that MKNN outperformed other algorithms in terms of accuracy and complexity.

关键词： Indoor localization MKNN LoRa machine learning classification RSSI SNR localization

A deep learning model enabled multi-event recognition for distributed optical fiber sensing

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Science China(information Sciences) 2024年第3期67卷 291-307页

作者： Yujiao LI Xiaomin CAO Wenhao NI Kuanglu YU institute of information Science School of Computer and Information TechnologyBeijing Jiaotong University Beijing Key Laboratory of Advanced information Science and Network technology Beijing Jiaotong University

Fiber optic sensors that utilize backscattered light offer distributed real-time measurements and have been seen tremendous improvements in sensing distance and spatial resolution over the last ***, these improvements in sensor capabilities lead to a significant increase in the amount of data that needs to be processed. Traditional processing schemes are no longer adequate, so the development of novel signal processing methods is critical. Phase-sensitive optical time domain reflectometry(Φ-OTDR) is now applied in various applications for multi-event recognition, and it would usually be difficult, sometimes even unrealistic to label all the acquired samples due to its real-time and seamless monitoring nature. To fully take advantage of the information contained within the large number of unlabeled samples, which were formerly not utilized and hence wasted, we propose a semi-supervised model to boost the event classification performance of Φ-OTDR. The model extracts respectively the temporal features and the spatial bidirectional features together with a dual attention mechanism. Its classification accuracy has been improved up to 96.9%with only 1230 labeled samples. In addition, our model shows significant advantages when the number of labeled samples is reduced. Importantly, our method improves the accuracy of multi-event classification without any modification to the optical setup.

关键词： $\Phi$-OTDR event recognition semi-supervised learning mean teacher MT-ACNN-SA-BiLSTM

An adaptive 3D reconstruction method for asymmetric dual-angle multispectral stereo imaging system on UAV platform

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Science China(information Sciences) 2024年第8期67卷 285-299页

作者： Chen WANG Xian LI Yanfeng GU Zixu WANG School of Electronics and information Engineering Harbin Institute of Technology Beijing institute of Control and Electronic technology

A multispectral imaging system often cannot capture 3D spatial information owing to hardware limitations, which diminishes the effectiveness across various domains. To address this problem, we have developed a multispectral stereo imaging system along with an adaptive 3D reconstruction algorithm. Unlike existing unmanned aerial vehicle stereo imaging systems, our multispectral stereo imaging system uses two multispectral cameras with asymmetric spectral bands positioned at different angles. This design enables the acquisition of a higher number of bands and lateral spatial information while maintaining a lightweight structure. This system introduces challenges such as large geometric distortions and intensity differences between multiple bands. To accurately recover 3D spatial information, we propose an adaptive 3D reconstruction method. This method employs a position and orientation system-assisted projection transformation and a normalized threshold adjustment strategy. Finally, mutual information is used to reconstruct the multispectral images densely, effectively addressing nonlinear differences and generating a comprehensive multispectral point cloud. Our stereo system was used for two real data collections in different regions, and the efficacy of the proposed 3D reconstruction method was validated by comparing it with existing methods and commercial software.

关键词： multispectral images 3D reconstruction stereo imaging system unmanned aerial vehicle feature extraction

Intelligent secure near-field communication

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Science China(information Sciences) 2024年第9期67卷 340-341页

作者： Nan ZHANG Jifa ZHANG Chengwen XING Na DENG Nan ZHAO School of information and Communication Engineering Dalian University of Technology School of information and Electronics Beijing Institute of Technology

The research and development efforts for the sixth generation(6G) wireless communication are underway to fulfill the growing demands for wireless communications. 6G is expected to become the key enabler for diverse new applications and services [1]. To achieve the excellent performance, 6G will implement extremely large-scale antenna arrays(ELAAs), terahertz [2], and new types of antennas with metamaterials, leading to a paradigm shift for the electromagnetic characteristics.

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Self-supervised recalibration network for person re-identification

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Defence technology（防务技术） 2024年第1期31卷 163-178页

作者： Shaoqi Hou Zhiming Wang Zhihua Dong Ye Li Zhiguo Wang Guangqiang Yin Xinzhong Wang Shenzhen institute of information technology Shenzhen518172China University of Electronic Science and technology of China Chengdu611731China Kash institute of Electronics and information Industry Kashi844099China

The attention mechanism can extract salient features in images,which has been proved to be effective in improving the performance of person re-identification(Re-ID).However,most of the existing attention modules have the following two shortcomings:On the one hand,they mostly use global average pooling to generate context descriptors,without highlighting the guiding role of salient information on descriptor generation,resulting in insufficient ability of the final generated attention mask representation;On the other hand,the design of most attention modules is complicated,which greatly increases the computational cost of the *** solve these problems,this paper proposes an attention module called self-supervised recalibration(SR)block,which introduces both global and local information through adaptive weighted fusion to generate a more refined attention *** particular,a special"Squeeze-Excitation"(SE)unit is designed in the SR block to further process the generated intermediate masks,both for nonlinearizations of the features and for constraint of the resulting computation by controlling the number of ***,we combine the most commonly used Res Net-50 to construct the instantiation model of the SR block,and verify its effectiveness on multiple Re-ID datasets,especially the mean Average Precision(m AP)on the Occluded-Duke dataset exceeds the state-of-the-art(SOTA)algorithm by 4.49%.

关键词： Person re-identification Attention mechanism Global information Local information Adaptive weighted fusion

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Robustness of interdependent networks with weak dependency links and reinforced nodes

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Science China(information Sciences) 2024年第2期67卷 329-330页

作者： Qian LI Hongtao YU Weitao HAN Ruiyang HUANG Shaomei LI Jianpeng ZHANG institute of information technology PLA Strategic Support Force Information Engineering University

Interdependent networks are more vulnerable than single,non-interacting networks under cascading failure [1–3]. Percolation theory provides a quantifiable theoretical framework to quantify and evaluate the robustness of networked systems. Most existing models [1–3] on the robustness of interdependent networks mainly focused on the giant connected component(GCC) to explore the structural robustness from the macro perspective,

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Gas sensor array based on carbon-based thin-film transistor for selective detection of indoor harmful gases

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Rare Metals 2024年第9期43卷 4401-4411页

作者： Can Liu Yu Sun Jia-Yi Guo Xiu-Lei Li Lu Tao Jin-Yong Hu Jue-Xian Cao Ping-Hua Tang Yong Zhang School of Electrical and information Engineering Hunan Institute of Engineering Physics and Optoelectronics&Hunan institute of Advanced Sensing and information technology Xiangtan University

The identification of indoor harmful gases is imperative due to their significant threats to human health and *** achieve accurate identification,an effective strategy of constructing a sensor array combined with the pattern recognition algorithm is ***-based thin-film transistors are selected as the sensor array unit,with semiconductor carbon nanotubes （CNTs） within the TFT channels modified with different metals （Au,Cu and Ti） for selective responses to NH3,H2S and HCHO,*** accurate gas species identification,an identification mode that combines linear discriminant analysis algorithms and logistic regression classifier is *** test results demonstrate that by preprocessing the sensor array’s sensing data with the LDA algorithm and subsequently employing the LR classifier for identification,a 100% recognition rate can be achieved for three target gases （NH3,H2S and HCHO）.This work provides significant guidance for future applications of chip-level gas sensors in the realms of the Internet of Things and Artificial Intelligence.

关键词： Carbon-based thin-film transistors Gas sensor arrays Linear discriminant analysis Multi-gas detection Semiconductor carbon nanotubes

Track-before-detect for bistatic radar based on pseudo-spectrum

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Chinese Journal of Aeronautics 2024年第1期37卷 236-246页

作者： Tao HAN Gongjian ZHOU School of Electronics and information Engineering Harbin Institute of TechnologyHarbin 150001China Key Laboratory of Marine Environmental Monitoring and information Processing Ministry of Industry and Information TechnologyHarbin 150001China

Track-Before-Detect(TBD) is an efficient method to detect dim targets for radars. Conventional TBD usually follows an approximate motion model of the target, which may cause an inaccurate integration of the target energy. A TBD technique on basis of pseudo-spectrum in mixed coordinates adopting an accurate motion model for bistatic radar system is developed in this *** predicted position in bistatic polar plane is derived according to a nonlinear function that exactly describes the constant Cartesian velocity motion. Then around the predicted position, a pseudo-spectrum is formulated and its samples are accumulated to the integration frame for energy integration. The evolution of the state and the procedure of accumulation of the target energy are derived elaborately. The superior performance of the proposed method is demonstrated by some simulations.

关键词： Weak target detection Bistatic radar Track-before-detect Pseudo-spectrum Multiframe integration

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Formation behaviors of rod-like reactive shaped charge penetrator and their effects on damage capability

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Defence technology（防务技术） 2024年第2期32卷 242-253页

作者： Tao Sun Haifu Wang Shipeng Wang Chao Ge Die Hu Pengwan Chen Yuanfeng Zheng Beijing institute of technology State Key Laboratory of Explosion Science and TechnologyBeijing100081China Xi'an institute of Electromechanical information technology Xi'an710065China

Formation behaviors of rod-like reactive shaped charge penetrator(RRSCP)and their effects on damage capability are investigated by experiments and numerical *** pulsed X-ray technology and a spaced aluminum/steel plate with the thicknesses of 5 mm/100 mm are *** types of sphericalsegment aluminum-polytetrafluoroethylene-copper(Al-PTFE-Cu)reactive liners with Cu contents of 0%,46.6%,and 66%are fabricated and *** experimental results show that the reactive liners can form excellent rod-shaped penetrators with tail skirts under the shaped charge effect,but the tail skirts disappear over ***,rupturing damage to the aluminum plate and penetration to the steel plate are caused by the RRSCP *** simulation analysis,the RRSCP is formed by a mechanically and chemically coupled response with the reactive liner activated by shock in its outer walls and bottom and then backward overturning,forming a leading reactive penetrator and a following chemical energy *** unique formation structure determines the damage modes of the aluminum plate and the steel *** analysis indicates that the formation behaviors and damage capability of Al-PTFE-Cu RRSCP strongly depend on Cu *** increasing Cu content,the velocity,activation extent,and reaction extent of Al-PTFE-Cu RRSCP decrease,which contribute to elongation and alleviate the negative effects of chemical reactions on elongation,significantly increasing the length-diameter ratio and thus enhancing the capability of steel plate ***,the lower activation extent and energetic density will weaken the RRSCP's capability of causing rupturing damage to the aluminum plate.

关键词： Reactive materials Al-PTFE composites Reactive liner X-ray Penetration

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Repeat-pass space-surface bistatic SAR tomography:accurate imaging and first experiment

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Science China(information Sciences) 2024年第9期67卷 245-262页

作者： Zhiyang CHEN Yuanhao LI Cheng HU Shenglei WANG Xinpeng CHEN Mihai DATCU Andrea Virgilio MONTI-GUARNIERI Radar technology Research institute School of Information and Electronics Beijing Institute of Technology Beijing Key Laboratory of Embedded Real-Time information Processing technology Beijing Institute of Technology Advanced technology Research institute Beijing Institute of Technology CEOSpace Tech University Politehnica of Bucharest Dipartimento di Elettronica Informazione e Bioingegneria Politecnico di Milano

Space-surface bistatic synthetic aperture radar(SS-BiSAR) offers an additional observation angle for monostatic spaceborne SAR, making it a promising technology for high-accuracy deformation retrieval technology in local regions. Repeat-pass SS-BiSAR tomography can accurately estimate the surfaces of buildings and steep areas, effectively removing terrain phases during deformation retrieving. However, inaccuracies in the orbital ephemeris can lead to image geometry distortion, reducing image pair coherence,introducing interferometric phase errors, and consequently deteriorating tomographic precision. This paper precisely models the image geometry distortion and interferometric phase error caused by repeat-pass ephemeris error. We propose an ephemeris correction method based on the chirp-Z transform to address these issues. Furthermore, we introduce an accurate tomography model to improve 3D reconstruction *** first SS-BiSAR tomography experiment, conducted using the Chinese Lutan-1 satellite, demonstrates that the correlation coefficient is improved by 0.16 after ephemeris error correction. Moreover, the density and precision of the tomographic point cloud are improved by 13.7% and 12.1%, respectively.

关键词： space-surface SAR tomography orbit error image distortion Lutan-1