This work proposes a wearable system for the non‐invasive measurement of the blood glucose level. In particular, the blood glucose variations are related with the skin resistance measured with a suitable sensor. A microcontroller is aimed to measure, store and transmits on a wireless channel, the blood glucose level in a simple, non‐invasive and unsupervised way. The system is particularly useful to monitoring the glucose level in diabetic patients, and to perform the oral glucose tolerance test (OGTT) useful to identify metabolic diseases and to diagnose diabetes mellitus in the early stage. The preliminary obtained results are quite promising and demonstrated the potentialities of the device as diagnostic and home care tool.

Nowadays, processing of data via neuromorphic non‐linear dynamics is a key element for brain‐inspired computers. In particular, an appropriate neuromorphic device is essential to emulate neuromorphic functions. In this brief, it is found that the Chua Corsage memristor has rich neuromorphic behaviours, which has potential values to realise the hardware construction for neuromorphic computing. The theory of local activity and edge of chaos are applied to analyse the neuromorphic dynamics of the second‐order Chua Corsage memristor based neuron model, and find that the periodic spikes (action potentials) appear either on or near the edge of chaos domain, which are excited by the subcritical Hopf bifurcation or the unstable state of the neuron model, respectively. Furthermore, the third‐order Chua Corsage memristor based neuron model can generate self‐sustained oscillations, periodic spikes, and chaos near the edge of chaos domain.

Here, a common‐mode rejection ratio (CMRR) enhancement circuit is proposed by employing an auxiliary buffer (AB) to the pseudo resistors of the capacitively coupled instrumentation amplifier (CCIA). After applying AB to CCIA, the differential‐mode gain remains the same with an extended bandwidth, and the common‐mode gain is reduced, and therefore, the CMRR is enhanced.

To deal with the restriction of vehicle space on a flywheel battery, a 5‐degrees of freedom (DOF) hybrid excitation bearingless motor (HEBM) was proposed. The 5‐DOF suspension force required for the flywheel battery is provided by HEBM. The use of a permanent magnet to provide a suspension bias magnetic field reduces power consumption. The relationship between the torque and suspension systems is weak coupling, which is beneficial to the decoupling control. To verify the aforementioned advantages of HEBM, its topology and principle are introduced, and its electromagnetic characteristics are analysed by finite element method. The HEBM is compared with the single‐winding bearingless switch reluctance motor by focusing on suspension loss and force density.

One critical issue for existing face recognition (FR) systems is to ensure its accuracy and robustness, which calls for the development of face anti‐spoofing (FAS) algorithms to work against presentation attacks (PA). This letter proposes a novel Multi‐level Attention Constraint Network with a Refined Triplet Loss (MACN‐RTL) for the task of FAS. Specifically, an MACN which consists of two components is designed, that is, Multi‐level Attention Network (MAN) and Distribution Constraint (DC). MAN aims to exploit effective information from different levels, while DC helps to learn a more compact and discriminative feature embedding for classification. Besides, a Refined Triplet Loss for better model optimisation is devised. Compared with existing FAS works, MACN is designed for better feature extraction and a better solution for optimisation by RTL. Experimental results demonstrate the superiority of the proposed approach.

• i.

  To ensure the security of FR systems towards PA, a novel MACN‐RTL is proposed, which can generate a more informative and discriminative feature embedding for accurate classification.

• ii.

  The designed MACN leverages attention mechanisms to obtain effective representations and reduces the distributional discrepancy of cross‐domain samples.

• iii.

  An RTL is devised to refine the widely used triplet loss by adding a refinement term to achieve a better optimisation of the model.

This paper proposes a full body virtual try‐on which handles both top and bottom garments and generates realistic try‐on images. For the full body virtual try‐on, this paper addresses lack of suitable training data to align and fit top and bottom naturally. The proposed system consists of three modules: Clothing Guide Module (CGM), Geometric Matching Module (GMM), and Try‐On Module (TOM). CGM is introduced to generate a clothing guide map (CGMap) which describes the shape of a garment on a model. Unlike the single‐garment virtual try‐on scheme, it is impractical to collect meaningful data at a large scale for the multi‐garment system. To address this problem, two novel training strategies are proposed to leverage the existing training data. First, a pseudo triplet of model‐top‐bottom is generated from a pair of model‐top or model‐bottom which are already secured. Second, the CGM network is arranged to be exposed to both top and bottom garments during training. Then, the following GMM networks warp and align the top and bottom garments. Finally, TOM synthesizes a realistic try‐on image with the aligned garment and the CGMap. Experimental results prove remarkable performance of the proposed method in the full body virtual try‐on.

In this letter, we propose a simple yet effective texture descriptor, symmetric mean and directional contour pattern (SMDCP), for texture classification. In particular, first the robust symmetric mean pattern (RSMP) that extracts the sign and amplitude information of the local difference through the neighbourhood average in a new scheme of encoding to further enhance the robustness to noise is constructed. Then a local directional and contour pattern (LDCP) to represent the contour information and direction information of adjacent sampling points is extracted. By concatenating the RSMP and LDCP, a robust and effective texture descriptor (SMDCP) for classification is built. Experimental results reveal that the proposed method obtains significant performance and high discrimination in comparison with 10 representative approaches.

Light field (LF) cameras capture scenes from multiple views and provide additional angular information for image super‐resolution (SR). Existing CNN‐based LF image SR methods commonly develop specific models for different angular resolutions. However, since the angular resolution can vary significantly with different LF devices, these methods have limited flexibility for real‐world applications. Here, an angular‐flexible network to use a single model to super‐resolve LF images of arbitrary angular resolution is proposed. In this method, spatial and angular feature extractors are designed to achieve angular‐flexible feature extraction, and develop a decouple‐and‐fuse module for SR reconstruction. Moreover, a mixed‐angular‐resolution training strategy is proposed to further enhance the angular flexibility. Experimental results on five public datasets demonstrate the state‐of‐the‐art performance of the method. Source codes are available at https://github.com/ZhengyuLiang24/LF‐AFnet. Here, an angular‐flexible network for light field image super‐resolution is proposed. The network can handle LFs captured by different kinds of devices with arbitrary angular resolutions. Experimental results demonstrate the effectiveness and superior performance of the method.

Recently, ithas been observed that ‐ternary codes, which are simply generated from deep features by hard thresholding, tend to outperform ‐binary codes in image retrieval. To obtain better ternary codes, the authors for the first time propose to jointly learn the features with the codes by appending a smoothed function to the networks. During training, the function could evolve into a non‐smoothed ternary function by a continuation method, and then generate ternary codes. The method circumvents the difficulty of directly training discrete functions and reduces the quantization errors of ternary codes. Experiments show that the proposed joint learning indeed could produce better ternary codes. For the first time, the authors propose to generate ternary hash codes by jointly learning the codes with deep features via a continuation method. Experiments show that the proposed method outperforms existing methods.

The standard cellular vehicular communication uses channel utilization as the input to the congestion control. When its measurement period is identical to the application messaging interval, oscillation and unfairness problems can arise. The exponential weighted moving average with random noise for the measured channel utilization can be used to prevent the problems.

UWB suspended stripline (SSL) bandpass filter with an adjustable notched band and four transmission zeros (Tzs) is proposed here. To prevent interference signals from the wireless local‐area network (WLAN) entering UWB system, a short‐stub resonant network is introduced to this UWB filter. In addition, utilizing different resonant modes of the two short–stubs, four Tzs are generated to improve the skirt selectivity. Both the centre frequency of the notched band and the positions of Tzs can be controlled by tuning the structural parameters. The UWB SSL bandpass filter is designed, fabricated and tested. The measured results are in good agreement with the simulated results.

The authors propose a new non‐destructive inspection method for underground fiberglass‐reinforced plastic mortar pipelines utilizing the periodic patterns of microwave guided‐modes on a hollow cylindrical dielectric waveguide. By the spatial synthesis of the microwaves utilizing the periodicity in the circumferential direction of a pipe, the authors found that a periodic pattern of the microwaves such as the Talbot effect with producing self‐images at the Talbot distance, was observed over the pipe‐wall. Further, adjusting the phase relationship between adjoining antenna elements changed the positions of the peak and null in the periodic pattern on the pipe‐wall. Additionally, when an unwanted foreign object was attached to the pipe, the periodic pattern of the microwaves can be disturbed according to the size and position of the object, and it is possible to inspect the pipeline using narrow‐band microwave signals. This paper experimentally demonstrated the successful detection of a foreign object on the pipe‐wall by scanning Talbot‐like patterns with a sensor along the pipe‐wall. This technique enables the non‐destructive inspection of pipelines using only narrow‐band, licence‐free microwave signals.

A slotted Y‐branch laser diode that emits two spectral modes at a difference frequency of about 1 THz is investigated in the context of photonic based cw‐THz measurements. The beating frequency of the emitted laser light can be tuned by ±10.5 GHz around 1 THz by changing the applied laser current, which allows for potentially fast measurements. A second spectral window of ±6.5 GHz was found at 850 GHz. Pointwise scanning of the difference frequency is demonstrated with thickness determination of HRFZ‐Si wafer samples as a possible application scenario.

The hybrid HVDC with cascaded multi‐infeed MMC inverters suffers from the fragile characteristic of its MMC inverters and is easy to be over current and over voltage. To solve such a problem, this letter proposes a fault ride‐through strategy based on the fault current limiter with a novel topology. With the proposed limiter, the hybrid HVDC system can ride through both the DC side pole‐to‐ground fault and the commutation failure caused by the AC side fault. When the commutation failure happens, the current‐limiting resistor of the fault current limiter will be put on to decrease the current into the safety boundary. When the DC side pole‐to‐ground fault happens, the MMC capacitor discharge path will be cut off automatically by the topology of the fault current limiter. The simulations finally validate the analysis.

Navigation in the absence of initial environmental information is a situation in which a robot is faced with the difficulty of traversing an unknown area for exploration with obtaining the environmental information simultaneously. Therefore, to complete and optimize the exploration efficiently, the robot needs an autonomous path‐planning algorithm. This work proposes a new autonomous path‐planning algorithm for exploration in an unknown environment based on paired frontiers, which we call internal and external frontiers algorithm (IEFA), that defines extended area for navigation of the mobile robot. For each exploration round, the robot defines external frontiers using the maximum range of sensors. Then, the robot generates internal frontiers, that is, pairs of external frontiers by varying the range of sensors. According to the size of each pair of frontiers, the algorithm generates the target point for robot navigation. The frontiers of internal layer are utilized as a main parameter for generation of next exploration point. We evaluated the proposed algorithm in simulation environments using the ROS toolbox of MATLAB and compared it with two previous exploration algorithms. From the experimental results, the proposed algorithm showed from 31% to 85% better performance in the path distance than previous algorithms.

In a conventional radar system, the hardware cost increases with the sampling rate of the receiver. Sub‐Nyquist radar systems operate at lower sampling rates and hence reduce the hardware cost and complexity. A sub‐Nyquist radar system uses the knowledge of the transmit pulse shape to determine the targets. However, the pulse shape is often distorted in practice and unknown to the receiver. An alternative sub‐Nyquist radar system that uses multiple receiver was proposed that estimates the targets without knowledge of the pulse shape. In this demo, the authors build a hardware prototype to demonstrate the proposed multi‐receiver sub‐Nyquist radar. The proposed two‐receiver system with an unknown pulse has comparable pre‐forms to a conventional sub‐Nyquist system is shown. This paper shows a hardware demonstration of sub‐Nyquist sampling of finite‐rate‐of‐innovation signals when the basic pulse shape is unknown. The results are particularly interesting in radar imaging, where the transmit pulse is distorted while propagation and unknown at the receiver.

This article reports a high throughput 150‐nm‐gate AlGaN/GaN high electron mobility transistor (HEMT) process using i‐line stepper lithography and a thermal reflow technique. Optimizing thermal reflow conditions, fabrication of a 150‐nm gate structure was successfully realized with the initial resist opening of 0.7 μm. AlGaN/GaN field‐plated HEMTs were fabricated on a semi‐insulating SiC substrate by using this process. In spite of unoptimized structures, fabricated 150‐nm gate devices exhibited the maximum drain current of 0.65 A/mm and the gate‐drain breakdown voltage exceeding 200 V. Based on cold HEMT extraction measurements, the average gate length of 187 nm and the standard deviation of 30 nm were obtained on a quarter 4‐in. wafer.