Search Results (1,278)

A concept towards current measurement in low and medium voltage power distribution networks is presented. The concentric magnetic field around the current-carrying conductor should be measured using a nitrogen-vacancy quantum magnetic field sensor. A bottleneck in current measurement systems is the readout electronics, which are usually based on optically detected magnetic resonance (ODMR). The idea is to have a hardware that tracks up to four resonances simultaneously for the detection of the three-axis magnetic field components and the temperature. Normally, expensive scientific instruments are used for the measurement setup. In this work, we present an electronic device that is based on a Zynq 7010 FPGA (Red Pitaya) with an add-on board, which has been developed to control the excitation laser, the generation of the microwaves, and interfacing the photodiode, and which provides additional fast digital outputs. The T1 measurement was chosen to demonstrate the ability to read out the spin of the system. Full article

This study presents the design, fabrication, and clinical validation of a lightweight, body-powered prosthetic index finger actuated via metacarpophalangeal (MCP) joint motion. The proposed system incorporates an underactuated, cable-driven mechanism combining rigid and compliant elements to achieve passive adaptability and embodied intelligence, supporting intuitive user interaction. Results indicate that the prosthesis successfully mimics natural finger flexion and adapts effectively to a variety of grasping tasks with minimal effort. This study was conducted in accordance with ethical standards and approved by the Institutional Review Board (IRB), Project No. 670161, titled “Biologically-Inspired Synthetic Finger: Design, Fabrication, and Application.” The findings suggest that the device offers a viable and practical solution for individuals with partial hand loss, particularly in settings where electrically powered systems are unsuitable or inaccessible. Full article

Green innovation is a key driver of sustainable development, yet Chinese firms, as major innovators, still underperform in this area. While directors play a central role in corporate governance, the influence of their green backgrounds on green innovation remains underexplored. This study investigates how directors with green backgrounds impact corporate green innovation. We consider both the appointment and the power of green-background directors. At the same time, we use the manually collected data from China’s heavily polluting listed firms between 2014 and 2020. We also conduct regulatory effect and mediation effect analyses. We found the following: (1) Green-background directors significantly promote corporate green innovation. Appointing directors with environmental expertise enhances firms’ green innovation performance, and this positive effect strengthens as these directors’ power increases. (2) Mechanistically, green-background directors facilitate green innovation by raising firms’ environmental awareness and helping secure government environmental subsidies. (3) Contextual influences matter. Moderating effect tests reveal that the impact of green-background directors is strengthened in firms with diligent boards, firm size, and green investors, but weakened in regions with higher marketization levels. (4) Further analysis shows that green-background directors enhance both strategic and substantive green innovation while also ensuring the long-term continuity of green innovation efforts. Full article

Surgery remains a healthcare intervention with significant risks for patients. Novel technologies can now enhance the peri-operative workflow, with artificial intelligence (AI) and extended reality (XR) to assist with pre-operative planning. This review focuses on innovation in AI, XR and imaging for hepato-biliary surgery planning. The clinical challenges in hepato-biliary surgery arise from heterogeneity of clinical presentations, the need for multiple imaging modalities and highly variable local anatomy. AI-based models have been developed for risk prediction and multi-disciplinary tumor (MDT) board meetings. The future could involve an on-demand and highly accurate AI-powered decision tool for hepato-biliary surgery, assisting the surgeon to make the most informed decision on the treatment plan, conferring the best possible outcome for individual patients. Advances in AI can also be used to automate image interpretation and 3D modelling, enabling fast and accurate 3D reconstructions of patient anatomy. Surgical navigation systems utilizing XR are already in development, showing an early signal towards improved patient outcomes when used for hepato-biliary surgery. Live visualization of hepato-biliary anatomy in the operating theatre is likely to improve operative safety and performance. The technological advances in AI and XR provide new applications in pre-operative planning with potential for patient benefit. Their use in surgical simulation could accelerate learning curves for surgeons in training. Future research must focus on standardization of AI and XR study reporting, robust databases that are ethically and data protection-compliant, and development of inter-disciplinary tools for various healthcare applications and systems. Full article

Since its publication in the 1960s, the Kalman Filter (KF) has been a powerful tool in optimal state estimation. However, the KF and most of its variants have mainly focused on the state estimation of smooth systems. In this work, we propose a new algorithm called the Discrete Unilateral Constrained Extended Kalman Filter (DUCEKF) that expands the capabilities of the Extended Kalman Filter (EKF) to a class of hybrid mechanical systems known as systems with unilateral constraints. Such systems are non-smooth in position and discontinuous in velocity. Lyapunov stability theory is invoked to establish sufficient conditions for the estimation error stability of the proposed algorithm. A comparison of the proposed algorithm with the EKF is conducted in simulation through a case study to demonstrate the superiority of the DUCEKF for the state estimation tasks in this class of systems. Simulations and an experiment were developed in this case study to validate the performance of the proposed algorithm. The experiment was conducted using electronic hardware that consists of an Embedded System (ES) called “Mikromedia for dsPIC33EP” and an external DAC-12 Click board, which includes a Digital-to-Analog Converter (DAC) from Texas Instruments. Full article

This paper presents a complete workflow for the evaluation of GaN transistors in voltage source inverters. With the associated high switching speed of transistors based on GaN, it is important to consider some critical points in the design phase as well as in the measurement setup in order to be able to utilise and verify the advantages of GaN properly. For this reason, the presented circuit board’s design focuses on a minimised power loop inductance. Simulation models, an analytical approach and measurement results with the aim of determining this inductance are compared with each other. A good compliance results between the presented methods. Additionally, the description of a test bench is given, which enables the performance of the opposition method. This setup allows the measurement of the designed H-bridge’s arising losses and the GaN-transistor’s switching behaviour. In comparison to the conventional double pulse method, this approach enables results that are more accurate for determining losses. Full article

Driven by the rapid advancement of Vehicle-to-Grid (V2G) and Grid-to-Vehicle (G2V) technologies, improving power quality and system stability during charging and discharging has become a research focus. To address this, this paper proposes a Model Predictive Control (MPC) strategy for Active Neutral-Point Voltage Balancing (ANPVB) in a single-phase three-level converter used in on-board V2G chargers. Traditional converters rely on passive balancing using redundant vectors, which cannot ensure neutral-point (NP) voltage stability under sudden load changes or frequent power fluctuations. To solve this issue, an auxiliary leg is introduced into the converter topology to actively regulate the NP voltage. The proposed method avoids complex algorithm design and weighting factor tuning, simplifying control implementation while improving voltage balancing and dynamic response. The results show that the proposed Model Predictive Current Control-based ANPVB (MPCC-ANPVB) and Model Predictive Direct Power Control-based ANPVB (MPDPC-ANPVB) strategies maintain the NP voltage within ±0.7 V, achieve accurate power tracking within 50 ms, and reduce the total harmonic distortion of current (THDi) to below 1.89%. The proposed strategies are tested in both V2G and G2V modes, confirming improved power quality, better voltage balance, and enhanced dynamic response. Full article

Silicon carbide (SiC) half-bridge power modules are widely utilized in new energy power generation, electric vehicles, and industrial power supplies. To address the research gap in collaborative validation between electro-thermal coupling models and process reliability, this paper proposes a closed-loop methodology of “design-simulation-process-validation”. This approach integrates in-depth electro-thermal simulation (LTspice XVII/COMSOL Multiphysics 6.3) with micro/nano-packaging processes (sintering/bonding). Firstly, a multifunctional double-pulse test board was designed for the dynamic characterization of SiC devices. LTspice simulations revealed the switching characteristics under an 800 V operating condition. Subsequently, a thermal simulation model was constructed in COMSOL to quantify the module junction temperature gradient (25 °C → 80 °C). Key process parameters affecting reliability were then quantified, including conductive adhesive sintering (S820-F680, 39.3 W/m·K), high-temperature baking at 175 °C, and aluminum wire bonding (15 mil wire diameter and 500 mW ultrasonic power/500 g bonding force). Finally, a double-pulse dynamic test platform was established to capture switching transient characteristics. Experimental results demonstrated the following: (1) The packaged module successfully passed the 800 V high-voltage validation. Measured drain current (4.62 A) exhibited an error of <0.65% compared to the simulated value (4.65 A). (2) The simulated junction temperature (80 °C) was significantly below the safety threshold (175 °C). (3) Microscopic examination using a Leica IVesta 3 microscope (55× magnification) confirmed the absence of voids at the sintering and bonding interfaces. (4) Frequency-dependent dynamic characterization revealed a 6 nH parasitic inductance via Ansys Q3D 2025 R1 simulation, with experimental validation at 8.3 nH through double-pulse testing. Thermal evaluations up to 200 kHz indicated 109 °C peak temperature (below 175 °C datasheet limit) and low switching losses. This work provides a critical process benchmark for the micro/nano-manufacturing of high-density SiC modules. Full article

IoT devices with sensors and actuators are frequently deployed in environments without access to the power grid. These devices are battery powered and might make use of energy harvesting if battery lifetime is too limited. This article focuses on automatically adapting the duty cycle frequency to the predicted available solar energy so that a continuous operation of IoT applications is guaranteed. The implementation is based on a low-cost solar control board that is integrated with the Serverless IoT Framework (SIF), which provides an event-based programming paradigm for microcontroller-based IoT devices. The paper presents a case study where the IoT device sleep time is pro-actively adapted to a predicted sequence of cloudy days to guarantee continuous operation. Full article

With the rapid development of heterogeneous satellite networks integrating geostationary earth orbit (GEO) and low earth orbit (LEO) satellite systems, along with the significant growth in the number of satellite users, it is essential to consider frequency compatibility and coexistence between GEO and LEO systems, as well as to design effective system resource allocation strategies to achieve efficient utilization of system resources. However, existing beam-hopping (BH) resource allocation algorithms in LEO systems primarily focus on beam scheduling within a single time slot, lacking unified beam management across the entire BH cycle, resulting in low beam-resource utilization. Moreover, existing algorithms often employ iterative optimization across multiple resource dimensions, leading to high computational complexity and imposing stringent requirements on satellite on-board processing capabilities. In this paper, we propose a BH-based beam scheduling and resource allocation framework. The proposed framework first employs geographic isolation to protect the GEO system from the interference of the LEO system and subsequently optimizes beam partitioning over the entire BH cycle, time-slot beam scheduling, and frequency and power resource allocation for users within the LEO system. The proposed scheme achieves frequency coexistence between the GEO and LEO satellite systems and performs joint optimization of system resources across four dimensions—time, space, frequency, and power—with reduced complexity and a progressive optimization framework. Simulation results demonstrate that the proposed framework achieves effective suppression of both intra-system and inter-system interference via geographic isolation, while enabling globally efficient and dynamic beam scheduling across the entire BH cycle. Furthermore, by integrating the user-level frequency and power allocation algorithm, the scheme significantly enhances the total system throughput. The proposed progressive optimization framework offers a promising direction for achieving globally optimal and computationally tractable resource management in future satellite networks. Full article

While electric unmanned aerial vehicles (UAVs) offer advantages in noise reduction, safety, and operational efficiency, their endurance is limited by current battery technology. Extending flight autonomy without compromising performance is a critical challenge in UAV system development. Previous studies introduced hybrid micro-turbogenerator architectures, but limitations in control stability and output power constrained their practical implementation. This study aimed to finalize the design and experimental validation of an optimized hybrid power system featuring a micro-turboprop engine mechanically coupled to an upgraded electric generator. A fuzzy logic-based control algorithm was implemented on a single-board computer to enable autonomous voltage regulation. The test bench architecture was reinforced and instrumented to allow stable multi-stage testing across increasing power levels. Results demonstrated stable voltage control at 48 VDC and electrical power outputs up to 3 kW, with an estimated maximum of 3.5 kW at full throttle. Efficiency was calculated at approximately 67%, and analysis of the generator’s KV constant revealed that using a lower KV variant (KV80) could reduce required rotational speed (RPM) and improve performance. These findings underscore the value of adaptive hybridization in UAVs and suggest that tuning generator electromechanical parameters can significantly enhance overall energy efficiency and platform autonomy. Full article

Naval ships are of paramount importance to national security, culture, and naval operations. A primary challenge for naval authorities is to balance the imperatives of maritime dominance with the operational demands of achieving sufficient, sustainable reliability. Shaft generators (SGs) are crucial to the energy conversion systems on naval ships, functioning as part of the main power systems on board and providing both propulsion and power for various operational loads. In this sense, the design of shaft generators is an engineering element that has a major impact on the overall ship performance. The design process will be conducted within the MATLAB/Simulink environment, a platform that facilitates the study of the dynamic behaviors of the system through simulation. The increasing demand for efficiency, reliability, and sustainability in the military, along with the impact of emerging technologies, will further underscore the significance of shaft generators. Analyses carried out in MATLAB/Simulink demonstrate that the selection of the most suitable power system for naval ships is dictated by the system requirements and operational demands. The main construction is such that this work is the first of its kind in the field of shaft generator research for naval ships. Full article

Structural Health Monitoring (SHM) is an essential technique for continuously assessing structural conditions using integrated sensor systems during operation. SHM technologies have evolved to address the increasing demand for efficient maintenance strategies in advanced engineering fields, such as civil infrastructure, aerospace, and transportation. However, developing a miniaturized, cost-effective, and multi-sensor solution based on Wireless Sensor Networks (WSNs) remains a significant challenge, particularly for SHM applications in weight-sensitive aerospace structures. To address this, the present study introduces a novel WSN-based Multi-Sensor System (MSS) that integrates multiple sensing capabilities onto a 3 × 3 cm flexible Printed Circuit Board (PCB). The proposed system combines a Piezoelectric Transducer (PZT) for impact detection; a strain gauge for mechanical deformation monitoring; an accelerometer for capturing dynamic responses; and an environmental sensor measuring temperature, pressure, and humidity. This high level of functional integration, combined with real-time Data Acquisition (DAQ) and precise time synchronization via Bluetooth Low Energy (LE), distinguishes the proposed MSS from conventional SHM systems, which are typically constrained by bulky hardware, single sensing modalities, or dependence on wired communication. Experimental evaluations on composite panels and aluminum specimens demonstrate reliable high-fidelity recording of PZT signals, strain variations, and acceleration responses, matching the performance of commercial instruments. The proposed system offers a low-power, lightweight, and scalable platform, demonstrating strong potential for on-board SHM in aircraft applications. Full article

Stealthy chip-level tamper attacks, such as hardware Trojan insertions or security-critical circuit modifications, can threaten modern microelectronic systems’ security. While traditional inspection and side-channel methods offer potential for tamper detection, they may not reliably detect all forms of attacks and often face practical limitations in terms of scalability, accuracy, or applicability. This work introduces a non-invasive, contactless tamper detection method employing a complementary split-ring resonator (CSRR). CSRRs, which are typically deployed for non-destructive material characterization, can be placed on the surface of the chip’s package to detect subtle variations in the impedance of the chip’s power delivery network (PDN) caused by tampering. The changes in the PDN’s impedance profile perturb the local electric near field and consequently affect the sensor’s impedance. These changes manifest as measurable variations in the sensor’s scattering parameters. By monitoring these variations, our approach enables robust and cost-effective physical integrity verification requiring neither physical contact with the chips or printed circuit board (PCB) nor activation of the underlying malicious circuits. To validate our claims, we demonstrate the detection of various chip-level tamper events on an FPGA manufactured with 28 nm technology. Full article

The recent advancements in high-frequency, high-power switching devices require the development of non-invasive, cost-effective sensors for signal diagnostics. In this context, planar sensors have emerged as promising candidates for voltage and current sensing due to their compatibility with printed circuit boards (PCBs). However, previously proposed voltage planar sensors exhibit trade-offs between high bandwidths and responsivity, limiting their usage to sub-GHz applications. This study introduces a planar voltage sensor that leverages geometric optimization using software-assisted design to enhance bandwidth without compromising sensitivity. The optimized sensors demonstrate an extended bandwidth response up to 4 GHz and accurate recovery of fast transient signals validated through experimental measurements, which represents a significant step forward in broadband sensing for high-power applications. Full article