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Battery management systems (BMS) in electric vehicles (EVs) require robust communication interfaces to accurately monitor and control lithium-ion battery cells. The communication interface of daisy chain architecture has attracted more and more attention because of its lower deployment cost compared with the communication architecture of the controller area network (CAN). However, in automotive electronics, in order to meet safety standards, it is difficult to implement circuits that are highly robust to electromagnetic interference, which has also attracted many practitioners to study it. The problem of partial electromagnetic interference and clock jitter can be addressed not only by employing methods commonly used in the field of analog signals, but also by leveraging algorithms utilized in the domain of digital signals. This paper proposes an EMI-immune daisy chain interface circuit with a PID-based clock-data-recovery (CDR) algorithm, utilizing either a capacitor or a transformer as an isolator. The system includes a transmitter, an active receiver, a wake-up receiver, and the corresponding algorithm digital circuits, achieving a successful transmission under 39-dBm DPI injection. Simulation results demonstrate a CMTI of 100kV/ $\mu $ s and low power consumption. The proposed CDR algorithm enables effective operation in the presence of clock frequency offset and EMI between chips. This paper thoroughly examines the underlying principles of the algorithm, supplemented by comprehensive test environments and accompanying data visuals.

Spectral polarization filtering in the range–Doppler domain plays an important role in weather radar clutter mitigation. However, when ground clutter and precipitation overlap, these methods tend to filter out clutter-contaminated precipitation, leading to estimation errors. To address this problem, this article proposes a ground clutter and noise mitigation method based on range–Doppler spectral processing for polarimetric Doppler weather radars. The proposed method can filter out clutter and noise and retain precipitation overlapped with clutter by analyzing the property differences between precipitation and clutter and noise in the range–Doppler spectrogram. Specifically, due to the spatial continuity of precipitation in the range–Doppler domain, the spectral moments (e.g., velocity and spectral width) are also continuous. In addition, polynomial fitting is used to compensate for the missing spectral moments, and the missing precipitation is recovered by Gaussian fitting using the computed spectral moments. The results demonstrate performance improvements after applying the proposed method to radar data collected by Chinese operational weather radars. The proposed method is compared with several other algorithms, and the comparison results show that the proposed method performs best in clutter and noise suppression and precipitation retention performance.

For better applications of low-frequency sonophoresis in transdermal interstitial fluid extraction and transdermal drug delivery, the microscopic mechanism of skin permeabilization by low-frequency sonophoresis have drawn much attention. In the present work, influence of skin texture density on a single cavitation bubble in an ultrasonic field is studied. A novel experimental system based on high-speed photography has been designed to investigate the temporary evolution of single bubble near skin-like walls with different texture densities exposed to a 20.51kHz ultrasound in liquids. In addition, the dynamic characteristics of single bubbles near skin-like walls with different texture densities are analyzed. It is found that the influences of the texture density on the bubble dynamics are obvious, which reflect on the changes in the maximum size of the bubble margin during bubble oscillating and the moving speed of the bubble to the wall, as well as the collapse time and the jet speed during collapses, especially for the bubble with an ultra-high texture density. These effects of the texture density on the bubble dynamics can explain the mechanism of skin texture structure for promoting acoustic cavitation in related application fields.

Composition layout is crucial in the portrait location recommendation of photography. The existing studies require both landscape background images and portrait foreground images, which limits the scope of practical applications. In this paper, we propose an end-to-end portrait location recommendation model, which mainly consists of three sub-networks: the first sub-networks is the portrait generation network, which generates relatively real portrait foreground images based on random input noise; the second sub-networks is the spatial transformation network, which mainly changes the size and location of the generated portrait based on the input landscape image; The third sub-networks is the compose network to generate a realistic portrait landscape image, which considers not only the correlation between the portrait foreground and the landscape background but also the overall composition aesthetics. Last, the proper standing position is obtained by computing the difference between the generated and input landscape images. We also construct a portrait landscape photo dataset PLDataset to train and verify our method. The experimental results on our dataset show that our proposed method can recommend a relatively reasonable standing position by only providing a landscape image in portrait landscape photography, which greatly increases the availability.

This paper is concerned with the joint state and input estimation problem for linear discrete time-varying systems over peer-to-peer sensor networks, in which deception attacks are taken into account. By resorting to singular value decomposition, a local estimator structure is proposed to jointly estimate the system states and unknown inputs. Then, a distributed state estimator is constructed by fusing local estimates and covariance matrices. In addition, a sufficient condition is provided to ensure the uniformly bounded estimation error (in mean square) in each node. Finally, a numerical example is provided to show the effectiveness of the proposed estimation algorithm.

This study developed a snowfall detection algorithm over ocean, sea ice, and coast for the advanced technology microwave sounder (ATMS) onboard both NPP and NOAA-20 satellites. The detection algorithm was trained from collocated observations between ATMS-NPP and CloudSat cloud profiling radar (CPR) snowfall product. Both brightness temperature (TB) variables and global forecast system (GFS) output variables are evaluated for snowfall detection in this algorithm. Results show that combining TB variables and GFS variables provide the optimal snowfall detection performance. The Heidke skill score (HSS) values are about 0.56 over all three surface types, and the probability of detection (POD) values are 0.76, 0.70, and 0.72 over ocean, sea ice, and coast, respectively. The importance of the GFS variables differs greatly among these three surface types. The detection algorithm primarily depends on TB variables over ocean and HSS only increased by 0.05 by adding GFS variables. In contrast, GFS variables are critically important to snowfall detection over sea ice and coastal regions. Without GFS variables, the HSS values over both sea ice and coastal regions decrease sharply from about 0.56 to about 0.40. Over ocean, we also developed a regional snowfall detection model in each 10° grid box, which greatly outperform the global detection model over certain regions (e.g., sea of Okhotsk and Labrador Sea). Case studies and validation against NOAA-20 observations showed that the snowfall detection algorithm performs well, which will benefit coastal communities by providing information on snowstorms offshore before they transition to land.

In this article, a spectral polarimetric filter named moving spectral depolarization ratio (MsDR) filter is proposed to mitigate the effects of clutter and noise for dual-polarization weather radar without cross-polar measurements. The filter is based on a spectral polarimetric variable termed as spectral depolarization ratio (sDR). sDR can be estimated by any polarimetric weather radar, making the MsDR filter widely applicable. Taking advantage of the spectral polarimetric features and the range-Doppler continuity of precipitation, the MsDR filter is implemented in the range-Doppler spectrogram. The performance of the MsDR filter is assessed using data collected by 1) an X-band full-polarimetric radar interfered by narrow-band clutter (both stationary and moving) and sidelobe wind turbine clutter; 2) a C-band operational dual-polarization radar affected by radio frequency interference. In addition, the implementation of the MsDR filter is straightforward, and the computational complexity is relatively low. Hence, the MsDR filter has great potential to be applied in real-time for operational radar systems at different frequencies.

This paper is concerned with the issue of platoon fault-tolerant control of the system with time-varying actuator faults. By obtaining the relative state information of neighboring vehicles, two event-triggered fault-tolerant controllers are designed for the two cases of the leader vehicle speed. Then the vehicle platoon system is transformed into error system, and the event-triggered control strategy is designed, in an effort to further save resources. Moreover, by the related theory of Lyapunov, it is shown that the error system is bounded. Finally, two simulation examples are given to show the effectiveness of the proposed approach.

With rapid development of smart grid, terminal power load is paid more and more attention, especially that of air conditioning system, which constitute an integral part of summer peak electricity load. In this paper, through controlling indoor air temperature deduced by equivalent thermal parameters-model, daily energy consumption and energy consumption during peak hours can be adjusted and reduced to realize demand side management. To reduce peak load of grid and ensure stable and reliable operation of grid, four temperature control strategies, including constant setting temperature control strategy, pre-cooling control strategy, curtailment control strategy and improved curtailment control strategy were proposed. Meanwhile, three operation schemes of the chiller were also employed. Furthermore, considering the power consumption and curtailment, five indicators including hourly average load, hourly average load ratio, energy saving ratio, load-shedding ratio during peak hours and coefficient of performance (COP) have been proposed to evaluate the performance. Results showed that the operation scheme of operating numbers control obtained better effect. Energy saving ratio was highest of 32.5% with curtailment control strategy, while load-shedding ratio during peak hours was optimal with improved curtailment control strategy. However, COP was maximum at 3.66 when pre-cooling control strategy was employed. This study can guide the operation of water-cooled air conditioning system through energy saving ratio and COP, also it has more benefits on economy of power system by hourly average load and load-shedding ratio.

A reconstruction technique of the antenna pattern for correcting the polarization measurement bias is proposed in this paper. In the case of the prior knowledge of patterns at some scanning angles, the pattern at other beam position can be estimated by application of the minimum norm least-square solution. Once the pattern is reconstructed, the corresponding projection matrix could be obtained in the presence of the mutual coupling and edge effects in the polarimetric phased array antenna. Thereby, the correction matrix for the polarization scattering matrix is repaired. A microstrip patch array antenna is designed to demonstrate the validity of the proposed method, and the performance of bias correction is manifested using several polarimetric variables. Specifically, the bias of differential reflectivity (Zb DR), the bias of linear depolarization ratio (LbDR) and the phase difference are less than 0.14 dB, 46.85 dB, 3.31° in a wide scanning angle range, respectively.

Progressive secret image sharing (PSIS) scheme attracts the interests of researchers in recent years. Many approaches have been proposed to construct PSIS schemes. In most of these schemes, the size of the shadow is expanded from the original image. On the contrary, polynomial-based PSIS can reduce shadow size from the original image. Recently, Yang and Huang proposed a polynomial-based (k, n) PSIS, where the image can be progressively reconstructed from k to n shadows. However, the problem of Yang-Huang's scheme is that the percentage of the recovered partial image from t shadows is extremely low when t is close to k. Later, Yang and Chu constructed another polynomial-based (k, n) PSIS with smooth property to solve this problem, but the size of the shadow is expanded greatly from Yang-Huang' scheme. In this paper, we propose a new (k, n) PSIS based on polynomial to overcome the drawbacks of these two schemes. In our scheme, t shadows (t is close to k) can recover more percentage partial image than Yang-Huang's scheme with a little shadow size expansion; comparing with Yang-Chu's scheme, our scheme achieves almost the same smooth property with much smaller shadow size.

Chaff centroid jamming released by vessel causes the indicated angle of radar seeker of anti-ship missile to deviate from the target. The failure to track the target is catastrophic for the radar seeker. In this paper, the angle estimation of the target in the presence of chaff centroid jamming is investigated. In the circumstance of chaff centroid jamming, the jamming is usually in the same range and angle resolution cells as the target. Under these circumstances, the essence of this problem is to estimate two unresolved targets' angles in the main beam of the radar seeker. To this end, two alternative methods are proposed to estimate the direction of arrival of the target in this paper. First, we present a maximum likelihood (ML) method implemented by a 2-D numerical search, which has high estimation accuracy but large computational load. Subsequently, considering both the accuracy and computational load, an improved ML (IML) method is developed. Based on the ML method, the proposed IML method adopts a search optimization processing by moment estimation. Furthermore, the effects of some key factors on the estimation performance are analyzed. The accuracy of the proposed methods is compared with the existing methods and the Cramer Rao lower bound as well.