Robust Backdoor Attacks on Object Detection in Real World

Deep learning models are widely deployed in many applications, such as object detection in various security fields. However, these models are vulnerable to backdoor attacks. Most backdoor attacks were intensively studied on classified models, but little on object detection. Previous works mainly focused on the backdoor attack in the digital world, but neglect the real world. Especially, the backdoor attack's effect in the real world will be easily influenced by physical factors like distance and illumination. In this paper, we proposed a variable-size backdoor trigger to adapt to the different sizes of attacked objects, overcoming the disturbance caused by the distance between the viewing point and attacked object. In addition, we proposed a backdoor training named malicious adversarial training, enabling the backdoor object detector to learn the feature of the trigger with physical noise. The experiment results show this robust backdoor attack (RBA) could enhance the attack success rate in the real world.Comment: 22 pages, 13figure

Design of Sensorless Control System for Permanent Magnet Linear Synchronous Motor Based on Parametric Optimization Super-Twisting Sliding Mode Observer

To improve the chattering problem caused by the terminal sliding mode control (TSMC) and sliding mode observer (SMO) in permanent magnet synchronous linear motor (PMLSM) control systems, this study presents the design of a continuous terminal sliding mode control (CTSMC) controller and an improved SMO. By enhancing the sliding mode surface, CTSMC enhances the dynamic response and robustness of the system. The observer replaces the traditional sliding mode switching law with a super-twisting (ST) algorithm, a twisting algorithm that makes use of the structural characteristics of the second-order sliding mode to ensure output continuity and reduce the observed buffeting. The sliding mode gain of the ST algorithm is optimized using the particle swarm optimization (PSO) algorithm to acquire the optimal parameters and fully exploit the observer’s performance potential. Finally, the proposed method is simulated and tested. The comparison results show that the proposed method boosts the system’s dynamic response and robustness and reduces chattering

Design and Locomotion Study of Two-DOF Actuator Driven by Piezoelectric–Electromagnetic Hybrid Mode

A piezoelectric actuator (PEA) has the characteristics of high control precision and no electromagnetic interference. To improve the degree of freedom (DOF) to adapt to more working scenes, a piezoelectric–electromagnetic hybrid-driven two-DOF actuator is proposed. The PEA adopts the composite structure of the lever amplification mechanism and triangular amplification mechanism. The structure effectively amplifies the output displacement of the piezoelectric stack and increases the clamping force between the driving foot and the mover. The electromagnetic actuator (EMA) adopts a multi-stage fractional slot concentrated winding permanent magnet synchronous actuator, which can better match the characteristics of PEA. The structure and working principle of the actuator are introduced, the dynamic analysis is carried out, and the factors affecting the clamping force are obtained. At the same time, the air gap magnetic field is analyzed, and the structural size of the actuator is optimized. The experiment shows that the maximum driving speed can reach 348 mm/s, the load capacity is 3 kg, the optimal initial rotor angle is 49°, the maximum torque is 2.9 N·m and the maximum speed is 9 rad/s, which proves the stability and feasibility of the actuator

Integrated Predictive Control of PMLSM Current and Velocity Based on ST-SMO

To enhance the control performance of a permanent magnet linear synchronous motor (PMLSM) and to improve its dynamic response performance and steady-state accuracy, a PMLSM model predictive integrated control (MPC) system based on a super-twisting sliding mode observer (ST-SMO) is proposed. According to the mathematical model of a PMLSM, this paper designs a three-step model to predict the comprehensive control correction factor, optimize the prediction speed and current, reduce the response time, and enhance the system’s stability. Meanwhile, in order to solve the problem of the PMLSM’s high dependence on mechanical sensors, the ST-SMO is introduced to observe the rotation speed of PMLSM, which has better tracking performance and observation accuracy than a traditional sliding mode observer (SMO). Finally, the experimental verification is carried out on the PMLSM experimental platform. The software simulation and hardware experiment results show that the control system designed in this paper not only simplifies the overall structure of the system, but it also has better control performance and tracking ability. Compared with traditional control methods and SMO, it has better control performance, stability, and speed-tracking performance

Recent advances of solid-state nmr spectroscopy for microporous materials

International audienceMicroporous materials have attracted a rapid growth of research interest in materials science and the multidisciplinary area because of their wide applications in catalysis, separation, ion exchange, gas storage, drug release, and sensing. A fundamental understanding of their diverse structures and properties is crucial for rational design of high-performance materials and technological applications in industry. Solid-state NMR (SSNMR), capable of providing atomic-level information on both structure and dynamics, is a powerful tool in the scientific exploration of solid materials. Here, advanced SSNMR instruments and methods for characterization of microporous materials are briefly described. The recent progress of the application of SSNMR for the investigation of microporous materials including zeolites, metal-organic frameworks, covalent organic frameworks, porous aromatic frameworks, and layered materials is discussed with representative work. The versatile SSNMR techniques provide detailed information on the local structure, dynamics, and chemical processes in the confined space of porous materials. The challenges and prospects in SSNMR study of microporous and related materials are discussed

An Ultra-Micro-Volume Adhesive Transfer Method and Its Application in fL–pL-Level Adhesive Distribution

This study is aimed at addressing the urgent demand for ultra-micro-precision dispensing technology in high-performance micro- and nanometer encapsulation, connection, and assembly manufacturing, considering the great influence of colloid viscosity and surface tension on the dispensing process in micro- and nanometer scale. According to the principle of liquid transfer, a method of adhesive transfer that can realize fL–pL levels is studied in this paper. A mathematical model describing the initial droplet volume and the transfer droplet volume was established, and the factors affecting the transfer process of adhesive were analyzed by the model. The theoretical model of the transfer droplet volume was verified by a 3D scanning method. The relationships between the transfer droplet volume and the initial droplet volume, stay time, initial distance, and stretching speed were systematically analyzed by a single-factor experiment, and the adhesive transfer rate was calculated. Combined with trajectory planning, continuous automatic dispensing experiments with different patterns were developed, and the problems of the transfer droplet size, appearance quality, and position accuracy were analyzed comprehensively. The results show that the average relative deviation of the transfer droplet lattice position obtained by the dispensing method in this paper was 6.2%. The minimum radius of the transfer droplet was 11.7 μm, and the minimum volume of the transfer droplet was 573.3 fL. Furthermore, microporous encapsulation was realized using the method of ultra-micro-dispensing

Design of a Deflection Switched Reluctance Motor Control System Based on a Flexible Neural Network

Deflection switched reluctance motors (DSRM) are prone to chattering at low speeds, which always affects the output efficiency of the DSRM and the mechanical loss of the motor. Combining the characteristics of a traditional reluctance motor with the strong nonlinear and high coupling of the DSRM, a control system for a DSRM based on a flexible neural network (FNN) is proposed in this paper. Based on the better robustness and fault tolerance of fuzzy PI control, the given speed signal is adjusted and converted into a torque control signal. As a result, the FNN control module possesses the strong self-learning ability and adaptive adjustment ability necessary to obtain the control voltage signal. Through simulations and experiments, it was verified that the control system can run stably on DSRM and shows good dynamic performance and anti-interference ability

Co-Upregulation of 14-3-3ζ and P-Akt is Associated with Oncogenesis and Recurrence of Hepatocellular Carcinoma

Background/Aims: 14-3-3ζ is involved in the regulation of PI3K/Akt pathway which is closely associated with carcinogenesis. However, the clinical significance of combined detection of 14-3-3ζ and p-Akt in hepatocellular carcinoma (HCC) remains unclear. Methods: Two-hundred pairs of HCC and adjacent liver specimens were subjected to tissue microarray. The association of 14-3-3ζ and p-Akt levels with the postoperative survival and recurrence in HCC patients was analyzed with univariate and multivariate methods. Moreover, the effects of 14-3-3ζ overexpression on the growth of HCC and the expressions of p-Akt and HIF-1α were assessed in a xenograft mouse model. Results: Elevated levels of 14-3-3ζ and p-Akt were detected in HCC and a positive correlation between the levels of 14-3-3ζ and p-Akt was verified. HCC patients with satellite nodules, microvascular invasion, portal vein tumor thrombosis, poor tumor differentiation and an advanced tumor stage tended to have higher levels of 14-3-3ζ and p-Akt. In addition, the postoperative 3-, 5-, and 7-year overall survival rates in HCC patients with 14-3-3ζhigh and p-Akthigh were significantly lower compared with those with 14-3-3ζlow and p-Aktlow, and the cumulative recurrence rate in HCC patients with 14-3-3ζhigh and p-Akthigh was significantly higher than that in those with 14-3-3ζlow and p-Aktlow. The multivariate Cox proportional hazard analysis indicated that concomitant upregulation of 14-3-3ζ and p-Akt was an independent factor that predicted poor survival and high recurrence in HCC patients. Furthermore, animal experiment showed that overexpression of 14-3-3ζ accelerated the growth of HCC xenograft tumors and induced the expressions of p-Akt and HIF-1α in vivo. Conclusion: Co-upregulation of 14-3-3ζ and p-Akt predicts poor prognosis in patients with HCC, and 14-3-3ζ-induced activation of the Akt signaling pathway contributes to HCC progression

Temperature Characteristic Analysis of Electromagnetic Piezoelectric Hybrid Drive Motor

Temperature rise has always been one of the main researchfocusesof the motor. When the temperature is too high, it will have a serious impact on the stability and reliability of motor performance. Due to the special structure of electromagnetic piezoelectric hybrid drive motor (EPHDM), the loss and temperature distribution of electromagnetic drive part and piezoelectric drive part werestudied. By analyzing the operation principle of the motor, the loss of each part wasresearched. On this basis, the loss of the electromagnetic driving part and piezoelectric driving part werecomputed by using the coupling iterative calculation method. The temperature contour map of the motor wasanalyzed by simulation, and the temperature characteristics of each part of the motor werestudied. Finally, the experimental verification of the prototype, the reliability of the theoretical model, and simulation results wereproved. The results showed that the temperature distribution of the motor is reasonable, the winding temperature is relatively high, and the core temperature and piezoelectric stator temperature are relatively low. The analytical and experimental methods are provided for the further study of heat source optimization