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  • MDPI AG  (4)
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  • MDPI AG  (4)
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  • 1
    Online Resource
    Online Resource
    Quantitative Analysis of φ-OTDR Spatial Resolution Influenced by NLM Parameters
    MDPI AG ; 2023
    In:  Photonics Vol. 10, No. 5 ( 2023-05-04), p. 529-
    Details
    In: Photonics, MDPI AG, Vol. 10, No. 5 ( 2023-05-04), p. 529-
    Abstract: Non-local mean (NLM) can significantly improve the signal-to-noise ratio (SNR), but it inevitably reduces the spatial resolution of distributed optical fiber sensors (DFOS), which hinders its practical application and the improvement of DFOS performance. In this paper, the quantitative relationship between the signal broadening of a phase-sensitive optical time-domain reflectometer (φ-OTDR) and the NLM parameters is analyzed to identify the cause and extent of the spatial resolution degradation. The denoising results for the mimic periodic and φ-OTDR vibration signals indicate that the signal broadening is mainly due to the similarity window size of NLM, and the signal amplitude reduction is caused by the Gaussian smoothing parameter. Compared with the reference signals, the signal broadening of the mimic and φ-OTDR signals after denoising are 2.56% and 2.74%, respectively, which is much less than the previous results. The signal amplitude is reduced by 9.25% and 13.62%, respectively. This work promotes the application of NLM and improves the performance of DFOS.
    Type of Medium: Online Resource
    ISSN: 2304-6732
    URL: Article
    DOI: 10.3390/photonics10050529
    Language: English
    Publisher: MDPI AG
    Publication Date: 2023
    detail.hit.zdb_id: 2770002-1
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    Online Resource
  • 2
    Online Resource
    Online Resource
    Energy-Efficient Multiple Autonomous Underwater Vehicle Path Planning Scheme in Underwater Sensor Networks
    MDPI AG ; 2023
    In:  Electronics Vol. 12, No. 15 ( 2023-08-03), p. 3321-
    Details
    In: Electronics, MDPI AG, Vol. 12, No. 15 ( 2023-08-03), p. 3321-
    Abstract: The issue of limited energy resources is crucial for underwater wireless sensor networks (UWSNs) because these networks operate in remote and harsh environments where access to power sources is limited. Overcoming the energy constraints is necessary to ensure the long-term functionality and sustainability of UWSN, enabling continuous data collection and communication for various applications such as environmental monitoring and surveillance. To solve the problems of limited energy and the difficulty of battery replacement in UWSN, a path planning and energy-saving scheme for charging underwater sensor nodes using AUVs (autonomous underwater vehicles) is proposed. Applying multiple AUVs to charge the sensing network nodes will maximize the size of the underwater sensing network as well as meet the transmission reliability, and the optimal path of AUVs is solved by using a genetic algorithm. Simulation results show that the AUV path planning scheme convergence is faster than that of conventional algorithms, and the lifetime of UWSN is prolonged while energy balancing according to the network size and node density. In high-density networks, the average energy consumption generated by AUVs for exploration is reduced by 15 percent for each additional AUV with our path planning.
    Type of Medium: Online Resource
    ISSN: 2079-9292
    URL: Article
    DOI: 10.3390/electronics12153321
    Language: English
    Publisher: MDPI AG
    Publication Date: 2023
    detail.hit.zdb_id: 2662127-7
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  • 3
    Online Resource
    Online Resource
    Visual Multitask Real-Time Model in an Automatic Driving Scene
    MDPI AG ; 2023
    In:  Electronics Vol. 12, No. 9 ( 2023-05-04), p. 2097-
    Details
    In: Electronics, MDPI AG, Vol. 12, No. 9 ( 2023-05-04), p. 2097-
    Abstract: In recent years, automatic driving technology has developed rapidly, and environmental perception is one of the important aspects of the technology of automatic driving. To design a real-time automatic driving perception system with limited computational resources, we first proposed a network with faster reasoning speed and fewer parameters by using multitask learning and vision-based recognition technology, which can target the three tasks of traffic target detection, drivable road segmentation, and lane detection that need to be performed simultaneously. Based on the Apollo Scape dataset, the experiment results show that our network is superior to the baseline network in terms of accuracy and reasoning speed and can perform various challenging tasks.
    Type of Medium: Online Resource
    ISSN: 2079-9292
    URL: Article
    DOI: 10.3390/electronics12092097
    Language: English
    Publisher: MDPI AG
    Publication Date: 2023
    detail.hit.zdb_id: 2662127-7
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  • 4
    Online Resource
    Online Resource
    Eye-Visible Oxygen Sensing via In-Situ Synthesizing Blue-Emitting Cu(I) Cluster in Red-Emitting COF: Characterization and Performance
    MDPI AG ; 2022
    In:  Materials Vol. 15, No. 13 ( 2022-06-27), p. 4525-
    Details
    In: Materials, MDPI AG, Vol. 15, No. 13 ( 2022-06-27), p. 4525-
    Abstract: Covalent organic frameworks (COFs) have shown virtues of well-defined and uniform pores with structural diversity, including the shape, size and even chemical nature of pores. These features are excellent for the application of O2 gas optical sensors. In this paper, two oxygen probes based on halogen-bridged Cu cluster were in-situ synthesized in the micropores of COFs, to allow a uniform distribution. The resulting composite samples were characterized in detail to confirm the successful probe loading. The doping level was determined as ~22%. The halogen-bridged Cu clusters showed blue emission peaking at ~440 nm, while COF host showed red emission peaking at 630 nm. These halogen-bridged Cu clusters had long emissive lifetime of ~6.7 μs and high emission quantum yield of 0.30 in pure N2 atmosphere. Given pure O2 atmosphere, lifetime and quantum yield were quenched to 2.5 μs and 0.11, showing oxygen-sensing possibility. A linear oxygen-sensing calibration curve was observed, with sensitivity of 12.25, response time of 13 s and recovery time of 38 s. Sample emission color was changed from blue to red when testing atmosphere was changed from pure N2 to pure O2, which was detectable by eyes.
    Type of Medium: Online Resource
    ISSN: 1996-1944
    URL: Article
    DOI: 10.3390/ma15134525
    Language: English
    Publisher: MDPI AG
    Publication Date: 2022
    detail.hit.zdb_id: 2487261-1
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