Scene text image super-resolution aims to enhance text legibility by recovering high-resolution text images from low-resolution inputs. However, maintaining fine details such as text strokes, edges, and textual accuracy remains challenging, particularly in low-light environments and high-speed motion scenarios, where degradation is more severe. Event cameras, with their high temporal resolution and ability to capture intensity changes, offer a promising solution for restoring lost fine details and mitigating degradation in these challenging conditions. In this paper, we propose EvTSR, the first framework that integrates Event data for scene Text image Super-Resolution. The core of EvTSR is the dual-stream frequency boost (DSFB) mechanism, which separates image features into high- and low-frequency components. High-frequency details like edges and strokes are enhanced using event data via the event-guided high-frequency (EGH) mechanism, while low-frequency components, responsible for global structure, are refined using the Text-Guided Low-frequency (TGL) mechanism with a pre-trained text recognizer, ensuring textual coherence. To further improve cross-modal integration, we introduce the cross-modal fusion (CMF) mechanism, which effectively aligns event and image features, enabling robust information fusion. Extensive experiments demonstrate that EvTSR achieves superior performance over existing methods.

Atmospheric turbulence induces coupled spatio-temporal distortions, including blur, geometric deformation, and temporal jitter, which severely degrade image quality. We propose EvTurM, a practical framework leveraging event camera data for dynamic turbulence mitigation with precise motion cues and stable temporal modeling. Leveraging the high temporal resolution and dynamic range of events, EvTurM achieves robust restoration under diverse turbulence conditions. EvTurM comprises two key modules: (1) the event-aware modality enhancement module, which uses event-derived motion to enrich RGB features and recover structural details, and (2) the bidirectional modality calibration module, which jointly aligns RGB and event features in forward and backward propagation to reduce misalignment and enhance temporal consistency. Extensive experiments show EvTurM consistently surpasses existing methods and achieves superior performance.

Summary Sliding mode control is one of the common control methods for manipulators, but the discontinuity of sliding mode control can cause jitter and vibration of the manipulator system. This article takes the Dobot Magician manipulator as the research object and constructs a simplified model of the manipulator dynamics. And the adaptive fuzzy sliding mode control method is designed in combination with fuzzy control theory, which effectively solves the jitter problem of the control torque. In the MATLAB/Simulink simulation environment analysis show that the proposed adaptive fuzzy sliding mode control method solves the jitter problem in sliding mode control with good stability, robustness and tracking performance. By combining the adaptive fuzzy sliding mode control method with the manipulator and comparing the motion time of the same motion trajectory with the PID control method in Dobot Studio, the hardware experiment results effectively verify the feasibility and effectiveness of the designed control method.

Since vehicles are not restricted by lane lines when driving inside intersections, they travel freely and their paths have many possibilities, which are related to the traffic order of other road users. It is necessary to understand and describe vehicle paths through intersections. Previous studies on modeling vehicle paths through intersections have predominantly been limited to vehicles turning in one single direction or specific intersections, ignoring the application universality. This study set out to establish a unified model to describe non-conflict paths of vehicles through intersections. An entrance lane-based coordinate system with geometric parameters was established to describe the position relationships of entrance and exit lanes. Three-order Bezier curves with control parameters were used to describe vehicle paths. By extracting the parameter values from driving simulator-based experiments, the entrance and exit lane-based vehicle path model was proposed to represent the relationship between geometric and control parameters. Actual path data captured by an unmanned aerial vehicle were used for model validation, and results show the validity of the proposed model with a mean Root Mean Square Error of 0.4613 m between observed and fitted paths. More validation considering position distributions of path origins and destinations and angle deviations when entering and leaving intersections was performed. Cases from HighD open dataset also demonstrated the model’s potential for lane-changing scenarios. This study provides an exciting opportunity to commonly describe vehicle paths without conflicts at geometrically regular and irregular intersections and is hoped to have the possibility of planning local paths for autonomous vehicles.

Abstract A manipulator is a complex electromechanical system that is nonlinear, strongly coupled, and uncertain. Achieving its precise and high‐quality trajectory control is difficult. Sliding mode control (SMC) is one of the common control methods for manipulators. However, discontinuities in SMC can cause jitter and vibration in the manipulator system, leading to a reduction in the performance of the control system. For the self‐adaptive capability jitter vibration problem of SMC, the Dobot magician manipulator is treated as the research object in this article. The dynamics equations of the manipulator are established by Lagrange method, and a simplified model of the manipulator dynamics is constructed. The method of self‐adaptive sliding mode control is proposed. Self‐adaptive parameters are added to the SMC to achieve self‐adaptive adjustment of the SMC parameters. In the MATLAB/Simulink simulation environment analysis show that the self‐adaptive SMC method has better self‐tuning ability and trajectory tracking ability than the traditional SMC, and weakens the jitter phenomenon existing in the traditional SMC.

This paper presents the design of a fully self-timed 8-bit 80-Ms/s single-core SAR ADC with interleaved comparators and a high order compensated opamp-less bandgap reference. A 3/2 interleaving algorithm was designed for better SFDR performance, where two of the three comparators are orderly chosen for interleaving in each conversion while offset calibration is applied to the idle comparator. Asynchronized SAR logic with a DAC settling timer is designed for fully self-timing of the ADC. The ADC was designed with a PVT stabilized on-chip reference source which promises a stable reference for the ADC at extreme temperature environments such as aerospace exploration or quantum computing. Technique for compensating the temperature coefficient (TC) of a bandgap reference (BGR) using temperature characteristics of transistor's current gain β is proposed. Measured results show 42.8dB SNDR, 56.8 dB SFDR and -53.3dBc THD for the proposed SAR ADC, drawing 1.07mW from a 1.1v supply. Measured average TC of the HBT proposed BGR is 23ppm/°C and 39 ppm/°C over the commercial (0~70°C) and space (-260~125°C) temperature ranges, respectively. The BGR reaches PSRR of -50dB at 1MHz, and -38dB at 1GHz. The entire chip was implemented on 0.13um 8HP SiGe process with an active area of 0.2952 mm2.