A Wearable Localized Surface Plasmons Antenna Sensor for Communication and Sweat Sensing

Zhang, Chao; Xiao, Pei; Zhao, Zitong; Liu, Zhu; Yu, Jie; Hu, Xinyu; Chu, Hongbo; Xu, Jiazhu; Liu, Mengyao; Zou, Qi; Zhang, Li; Liu, Qi; Li, Gaosheng

doi:10.1109/jsen.2023.3266262

Cited by 28 publications

(2 citation statements)

References 41 publications

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“…The envelope of a signal is its amplitude independent of its phase. One can quantify the degree of similarity between the signal envelopes received by various antennas by employing a metric known as the ECC is computed by utilizing equation (5). The relationship between the DG and ECC is characterized by the opposite sign in the equation [59].…”

Section: Analysis For Diversity Parametersmentioning

confidence: 99%

Design and diversity performance analysis of C shape engraved miniaturised, and high gain Quad-Port MIMO antenna for 5 G and P2P communication

Almawgani,

Lavadiya,

Sorathiya

et al. 2024

Phys. Scr.

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The 4-Port multiband operated MIMO antenna operating at 4GHz, 6GHz and 9GHz is proposed to target the 5G and P2P communication applications. The electrical size of the 4-Port antenna structure is 0.8λ x 0.48λ. The unique shape of a single radiating patch element is identified by engraving a circular shape patch element and modifying the shape of the feedline. The optimisation in terms of return loss was achieved based on the defected ground structure and changing radius of different elements of the patch structure. The 2-Port and 4-Port MIMO antenna structures are designed using the FR4 substrate and their return loss is compared and examined. The proposed design provides a minimum return loss of -22dB, peak bandwidth of 2.25GHz, peak gain of 4.67dB, and normalised directivity of 1870. Different MIMO diversity parameters are analysed. The proposed design provides an envelope correlation coefficient of 0.01, Diversity gain near 10dB, mean effective gain of almost zero, channel capacity loss of almost zero and Mean effective gain within the acceptable range. The overall Performance of the Proposed Design is compared with other 4-Port design structures and it represents healthy gain, multiple band response and proper diversity parameters making it suitable for the 5G and P2P communication applications.

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Section: Analysis For Diversity Parametersmentioning

confidence: 99%

Design and diversity performance analysis of C shape engraved miniaturised, and high gain Quad-Port MIMO antenna for 5 G and P2P communication

Almawgani,

Lavadiya,

Sorathiya

et al. 2024

Phys. Scr.

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show abstract

“…The Oriented FAST and Rotated BRIEF (ORB) is an efficient feature extractor. To identify key points, it uses the FAST (Features from Accelerated Segment Test) keypoint Sustainability 2023, 15, 14597 9 of 19 detector [98][99][100]. It makes more complex use of the BRIEF (Binary Robust Independent Elementary Features) description.…”

Section: Orb Featuresmentioning

confidence: 99%

Vehicle Detection and Classification via YOLOv8 and Deep Belief Network over Aerial Image Sequences

Al Mudawi,

Qureshi,

Abdelhaq

et al. 2023

Sustainability

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Vehicle detection and classification are the most significant and challenging activities of an intelligent traffic monitoring system. Traditional methods are highly computationally expensive and also impose restrictions when the mode of data collection changes. This research proposes a new approach for vehicle detection and classification over aerial image sequences. The proposed model consists of five stages. All of the images are preprocessed in the first stage to reduce noise and raise the brightness level. The foreground items are then extracted from these images using segmentation. The segmented images are then passed onto the YOLOv8 algorithm to detect and locate vehicles in each image. The feature extraction phase is then applied to the detected vehicles. The extracted feature involves Scale Invariant Feature Transform (SIFT), Oriented FAST and Rotated BRIEF (ORB), and KAZE features. For classification, we used the Deep Belief Network (DBN) classifier. Based on classification, the experimental results across the three datasets produced better outcomes; the proposed model attained an accuracy of 95.6% over Vehicle Detection in Aerial Imagery (VEDAI) and 94.6% over Vehicle Aerial Imagery from a Drone (VAID) dataset, respectively. To compare our model with the other standard techniques, we have also drawn a comparative analysis with the latest techniques in the research.

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Image segmentation using convolutional neural networks in multi-sensor information fusion

Zhang,

Dong,

Jiang

2023

Soft Comput

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A Wearable Localized Surface Plasmons Antenna Sensor for Communication and Sweat Sensing

Cited by 28 publications

References 41 publications

Design and diversity performance analysis of C shape engraved miniaturised, and high gain Quad-Port MIMO antenna for 5 G and P2P communication

Design and diversity performance analysis of C shape engraved miniaturised, and high gain Quad-Port MIMO antenna for 5 G and P2P communication

Vehicle Detection and Classification via YOLOv8 and Deep Belief Network over Aerial Image Sequences

Image segmentation using convolutional neural networks in multi-sensor information fusion

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