The rapid development of neuro-inspired computing demands synaptic devices with ultrafast speed, low power consumption, and multiple non-volatile states, among other features. Here, a high-performance synaptic device is designed and established based on a Ag/PbZr0.52Ti0.48O3 (PZT, (111)-oriented)/Nb:SrTiO3 ferroelectric tunnel junction (FTJ). The advantages of (111)-oriented PZT (~1.2 nm) include its multiple ferroelectric switching dynamics, ultrafine ferroelectric domains, and small coercive voltage. The FTJ shows high-precision (256 states, 8 bits), reproducible (cycle-to-cycle variation, ~2.06%), linear (nonlinearity <1) and symmetric weight updates, with a good endurance of >109 cycles and an ultralow write energy consumption. In particular, manipulations among 150 states are realized under subnanosecond (~630 ps) pulse voltages ≤5 V, and the fastest resistance switching at 300 ps for the FTJs is achieved by voltages <13 V. Based on the experimental performance, the convolutional neural network simulation achieves a high online learning accuracy of ~94.7% for recognizing fashion product images, close to the calculated result of ~95.6% by floating-point-based convolutional neural network software. Interestingly, the FTJ-based neural network is very robust to input image noise, showing potential for practical applications. This work represents an important improvement in FTJs towards building neuro-inspired computing systems. 

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High-precision and linear weight updates by subnanosecond pulses in ferroelectric tunnel junction for neuro-inspired computing

/pdf/high-precision-and-linear-weight-updates-by-subnanosecond-1w0dt1gr.pdf

Continuous imaging of cardiac functions is highly desirable for the assessment of long-term cardiovascular health, detection of acute cardiac dysfunction and clinical management of critically ill or surgical patients1-4. However, conventional non-invasive approaches to image the cardiac function cannot provide continuous measurements owing to device bulkiness5-11, and existing wearable cardiac devices can only capture signals on the skin12-16. Here we report a wearable ultrasonic device for continuous, real-time and direct cardiac function assessment. We introduce innovations in device design and material fabrication that improve the mechanical coupling between the device and human skin, allowing the left ventricle to be examined from different views during motion. We also develop a deep learning model that automatically extracts the left ventricular volume from the continuous image recording, yielding waveforms of key cardiac performance indices such as stroke volume, cardiac output and ejection fraction. This technology enables dynamic wearable monitoring of cardiac performance with substantially improved accuracy in various environments. 

/pdf/a-wearable-cardiac-ultrasound-imager-1qyw29ur.pdf

A wearable cardiac ultrasound imager

The purpose of this study is to investigate the unsafe conditions of pedestrian crossings at signalized intersections under the mixed traffic environment in Changsha, China. For this purpose, based...

Safety evaluation of pedestrian-vehicle interaction at signalized intersections in Changsha, China

A review on key challenges in intelligent vehicles: Safety and driver-oriented features

Environmental perception technology is the guarantee of the safety of driverless vehicles. At present, there are a lot of researches and reviews on environmental perception, aiming to realize unmanned driving while ensuring the safety of human life. However, the technology is facing new challenges in the new era. This review paper attempts to systematically summarize environment perception technology and discuss the new challenges currently faced. To this end, we first summarized the advantages, disadvantages and applicable occasions of several commonly used sensing methods to provide a clear selection guide. The new challenges faced by environmental perception technology are discussed from three aspects: technology, external environment and applications. Finally, the article also points out the future development trends and efforts of environmental perception technology.

Sensing system of environmental perception technologies for driverless vehicle: A review of state of the art and challenges

A reliable non-destructive testing technique that enables effective detection and quantification of defects within safety-critical curved structures is highly demanded both in manufacture and service. Conventional Ultrasonic Testing (UT) methods usually adopt planar ultrasonic probes and it is preferable to adjust the probe axis direction perpendicular to the curved surface, because both the transmitting and receiving sensitivities in the probe axis direction are the highest. This paper proposes a new UT method using a hemispherical-omnidirectional ultrasonic probe. This probe has an omnidirectional directivity pattern and can cover curved surfaces with normal incident ultrasounds at different scan positions without the necessity of adjusting the probe attitude and position to follow the curved surface profiles. A surface reconstruction algorithm is firstly proposed to estimate curved surface profiles, which is based on a fast-imaging algorithm for ultra-wideband radar called the Shape Estimation Algorithm based on the Boundary scattering transform and Extraction of Directly scattered waves (SEABED). This method only uses surface reflection echoes, and thus can inspect curved structures without knowing the surface profiles a prior. Further, the Synthetic Aperture Focusing Technique (SAFT) is implemented to generate a focused image of internal defects by performing delay-and-sum beamforming on defect echoes based on the reconstructed surface profile. The proposed UT method is eventually experimentally verified on a curved plexiglass specimen with 29.4 mm surface curvature radius containing three Ø 3.5 mm Side Drilled Holes (SDHs) at different depths. Results show that compared with the planar ultrasonic probe, the reconstructed surface profile via SEABED is much wider and accurate with a relative error ≤ 0.47%. All SDHs are not only clearly positioned with relative errors ≤ 7.43%, but also can be accurately quantified from the curvature radius of SDH indications in the SAFT images with relative errors ≤ 8.60%. This work proves that the UT method based on the hemispherical-omnidirectional ultrasonic probe can emerge as a promising technique to inspect curved structures with high efficiency and accuracy, which has great potential in practical applications. 

Ultrasonic inspection of curved structures with a hemispherical-omnidirectional ultrasonic probe via linear scan SAFT imaging

Parallel Parking Path Planning Based on Improved Arctangent Function Optimization

Regenerative braking control strategy based on pavement recognition controller for electric vehicle

When a permanent magnet synchronous motor (PMSM) is designed according to the traditional motor design theory, the performance of the motor is often challenging to achieve the desired goal, and further optimization of the motor design parameters is usually required. However, the motor is a strongly coupled, non-linear, multivariate complex system, and it is a challenge to optimize the motor by traditional optimization methods. It needs to rely on reliable surrogate models and optimization algorithms to improve the performance of the PMSM, which is one of the problematic aspects of motor optimization. Therefore, this paper proposes a strategy based on a combination of a high-precision combined surrogate model and the optimization method to optimize the stator and rotor structures of interior PMSM (IPMSM). First, the variables were classified into two layers with high and low sensitivity based on the comprehensive parameter sensitivity analysis. Then, Latin hypercube sampling (LHS) is used to obtain sample points for highly sensitive variables, and various methods are employed to construct surrogate models for variables. Each optimization target is based on the acquired sample points, from which the most accurate combined surrogate model is selected and combined with non-dominated ranking genetic algorithm-II (NSGA-II) to find the best. After optimizing the high-sensitivity variables, a new finite element model (FEM) is built, and the Taguchi method is used to optimize the low-sensitivity variables. Finally, finite element analysis (FEA) was adopted to compare the performance of the initial model and the optimized ones of the IPMSM. The results showed that the performance of the optimized motor is improved to prove the effectiveness and reliability of the proposed method.

/pdf/multi-objective-optimization-strategy-for-permanent-magnet-3rsht4x0.pdf

Qiping Chen

Papers

Sensing system of environmental perception technologies for driverless vehicle: A review of state of the art and challenges

Ultrasonic inspection of curved structures with a hemispherical-omnidirectional ultrasonic probe via linear scan SAFT imaging

Parallel Parking Path Planning Based on Improved Arctangent Function Optimization

Regenerative braking control strategy based on pavement recognition controller for electric vehicle

Multi-Objective Optimization Strategy for Permanent Magnet Synchronous Motor Based on Combined Surrogate Model and Optimization Algorithm