Search Results (63)

With accelerating digital transformation, firms must renew how they create, deliver, and capture value to remain competitive and to advance sustainable competitiveness. This study examines how ambidextrous market orientation drives digital business model innovation (DBMI) through the mediating role of digital resource bricolage and the moderating effect of environmental turbulence. Using survey data and structural equation modeling (SEM), we find that both proactive and responsive market orientations positively affect DBMI. Digital resource bricolage partially mediates both relationships, with a stronger mediation effect for responsive orientation. Environmental turbulence strengthens the association between ambidextrous market orientation and digital resource bricolage. Complementing variable-centric tests, fuzzy-set qualitative comparative analysis (fsQCA) identifies three configurational pathways sufficient for high DBMI, revealing alternative routes to business-model renewal under different contextual conditions. The findings extend ambidextrous market orientation research to digital contexts, enrich the resource-recombination perspective on DBMI, and provide actionable guidance for firms seeking to orchestrate data, platforms, and legacy assets to reconfigure activity systems. By clarifying when and how market sensing and shaping translate into effective digital recombination, this study informs strategies for sustainable competitiveness in turbulent environments. Full article

With the rapid growth of unmanned aerial vehicles (UAVs) and IoT users, spectrum resources are becoming increasingly scarce, making cognitive radio (CR) technology a key approach to improving spectrum utilization. However, traditional antennas are difficult to meet the lightweight, compact, and low-drag requirements of small UAVs due to spatial constraints. This paper proposes a tri-mode frequency reconfigurable flexible antenna that can be conformally integrated onto UAV wing arms to enable CR dynamic frequency communication. The antenna uses a polyimide (PI) substrate and has compact dimensions of 31.4 × 58 × 0.05 mm³. A microstrip line-based frequency-selective network is designed, incorporating PIN and varactor diodes to realize three operation modes, dual-band (2.25~3.55 GHz, 5.6~6.75 GHz), single-band (3.35~5.3 GHz), and continuous tuning (4.3~6.1 GHz), covering WLAN, WiMAX, and 5G NR bands. Test results show that the antenna maintains stable performance under conformal conditions, with frequency shifts less than 4%, gain (3.65~4.77 dBi), and radiation efficiency between 67.2% and 82.9%. The tuning ratio reaches 38.8% in the continuous mode. This design offers a new solution for CR communication in compact UAV platforms and shows promising application potential. Full article

To meet the in-orbit performance verification requirements of a drag-free control system for gravitational wave detection satellites, this study develops a ground simulation platform using the H-infinity ($H_{\infty }$) control method in Simulink. The FPGA implementation accelerates the core algorithm of drag-free control. A frequency-domain linear robust control design is employed, with a frequency pre-warped bilinear transformation method used to discretize the multi-degree-of-freedom controller. The established control system model includes 18 degrees of freedom, with 12 from the dual test masses (TM) and 6 from the satellite body. The two test masses are spatially arranged in a symmetric configuration, and their control structure also exhibits symmetry. A rapid reconfigurable hardware architecture is utilized, and the Vitis Model Composer tool is employed to efficiently translate the Simulink algorithm model into hardware description language, reducing the processing delay of the core control algorithm to the nanosecond level. Through a 15-channel gradient test comparison, the FPGA platform maintains numerical equivalence with the Simulink platform (maximum error of ${10}^{-13}$). Experimental results show that the hardware acceleration improves dynamic response speed by an order of magnitude, achieving position control accuracy of ±5 μm and attitude accuracy of ±10 μrad, with overall processing latency at the microsecond level. This method provides a reliable engineering validation approach for ultra-precision control systems in gravitational wave detection. Full article

This study presents a high-fidelity digital twin (DT) framework designed to evaluate and improve vertiport operations for Advanced Air Mobility (AAM). By integrating Unreal Engine, AirSim, and Cesium, the framework enables real-time simulation of Unmanned Aerial Vehicles (UAVs), including unmanned electric vertical take-off and landing (eVTOL) operations under nominal and disrupted conditions, such as adverse weather and engine failures. The DT supports interactive visualisation and risk-free analysis of decision-making protocols, vertiport layouts, and UAV handling strategies across multi-scenarios. To validate system realism, mixed-reality experiments involving physical UAVs, acting as surrogates for eVTOL platforms, demonstrate consistency between simulations and real-world flight behaviours. These UAV-based tests confirm the applicability of the DT environment to AAM. Intelligent algorithms detect Final Approach and Take-Off (FATO) areas and adjust flight paths for seamless take-off and landing. Live environmental data are incorporated for dynamic risk assessment and operational adjustment. A structured capacity evaluation method is proposed, modelling constraints including turnaround time, infrastructure limits, charging requirements, and emergency delays. Mitigation strategies, such as ultra-fast charging and reconfiguring the layout, are introduced to restore throughput. This DT provides a scalable, drone-integrated, and data-driven foundation for vertiport optimisation and regulatory planning, supporting safe and resilient integration into the AAM ecosystem. Full article

Wind turbine blades feature complex geometries and operate under harsh conditions, including high curvature gradients, nonlinear deformations, elevated humidity, and particulate contamination. This study presents the design and kinematic analysis of a novel climbing robot based on a 10R folding metamorphic mechanism. The robot employs a hybrid wheel-leg drive and adaptively reconfigures between rectangular and hexagonal topologies to ensure precise adhesion and efficient locomotion along blade leading edges and windward surfaces. A high-order kinematic model, derived from a modified Grubler–Kutzbach criterion augmented by rotor theory, captures the mechanism’s intricate motion characteristics. We analyze the degrees of freedom (DOF) and motion branch transitions for three representative singular configurations, elucidating their evolution and constraint conditions. A scaled-down prototype, integrating servo actuators, vacuum adhesion, and multi-modal sensing on an MDOF control platform, was fabricated and tested. Experimental results demonstrate a configuration switching time of 6.3 s, a single joint response time of 0.4 s, and a maximum crawling speed of 125 mm/s, thereby validating stable adhesion and surface tracking performance. This work provides both theoretical insights and practical validation for the intelligent maintenance of wind turbine blades. Full article

This paper presents a power-aware Reconfigurable Parameterizable Pseudorandom Pattern Generator (RP-PRPG) for a number of applications, including built in self-testing (BIST) and cryptography. Linear Feedback Shift Registers (LFSRs) are broadly utilized in pattern generation due to their efficiency and simplicity. However, the diversity of generated patterns, as well as their power consumption, improves through circuit modifications. This work explores enhancements to LFSR structures to achieve broader range of patterns with reduced power consumption for BIST-based applications. The proposed circuit constructed on the LFSR platform can be programmed to generate patterns with varying degrees of different LFSR configurations. Diverse set of patterns of any circuit arrangement can be created using any characteristic polynomial and by utilizing the reseeding capacity of the circuit. The circuit combines a double-tier linear feedback circuit with zero forcing methods, resulting in more than 70% transition reduction, thus significantly lowering power dissipation. The behaviour of the proposed circuit is assessed for characteristic polynomials with degrees ranging from 4 to 128 using various Linear Feedback Shift Register (LFSR) topologies. For reconfigurable HDL and ASIC synthesis, the power-aware RP-PRPG can be used to generate an efficient set of stream ciphers as well as applications involving the scan-for-test protocol. Full article

The integration of robots into collaborative environments, where they physically interact with humans, requires systems capable of ensuring both safety and performance. This work introduces the development of a Variable Stiffness Impact Testing Device (VSITD), designed to emulate physical human–robot interaction by replicating biomechanical properties such as muscle elasticity and joint compliance. The proposed system integrates a Variable Stiffness Mechanism (VSM) with a multi-sensor configuration that includes a high-resolution Force Sensitive Resistors (FSR) matrix, piezoelectric load cells, and an FPGA-based acquisition unit. The FPGA enables fast acquisition of contact forces and pressures, while the mechanical stiffness configuration of the VSM can be rapidly reconfigured to simulate a wide range of impact scenarios. The device aims to validate compliance with the standard ISO/TS 15066 safety standard of robotic work cell in the context of collaborative application. The modularity and flexibility of the VSITD make it suitable for evaluating a wide range of collaborative robotic platforms, providing a reliable tool for pre-deployment validation in shared workspaces. By combining real-time sensing with adaptable stiffness control, the VSITD establishes a new benchmark for safety testing in human–robot collaboration scenarios. Full article

Biological systems can adaptively navigate multi-terrain environments via morphological and behavioral flexibility. While robotic systems increasingly achieve locomotion versatility in one or two domains, integrating terrestrial, aquatic, and aerial mobility into a single platform remains an engineering challenge. This work tackles this by introducing a bipedal robot equipped with a reconfigurable locomotion framework, enabling seven adaptive policies: (1) thrust-assisted jumping, (2) legged crawling, (3) balanced wheeling, (4) tricycle wheeling, (5) paddling-based swimming, (6) air-propelled drifting, and (7) quadcopter flight. Field experiments and indoor statistical tests validated these capabilities. The robot achieved a 3.7-m vertical jump via thrust forces counteracting gravitational forces. A unified paddling mechanism enabled seamless transitions between crawling and swimming modes, allowing amphibious mobility in transitional environments such as riverbanks. The crawling mode demonstrated the traversal on uneven substrates (e.g., medium-density grassland, soft sand, and cobblestones) while generating sufficient push forces for object transport. In contrast, wheeling modes prioritize speed and efficiency on flat terrain. The aquatic locomotion was validated through trials in static water, an open river, and a narrow stream. The flight mode was investigated with the assistance of the jumping mechanism. By bridging terrestrial, aquatic, and aerial locomotion, this platform may have the potential for search-and-rescue and environmental monitoring applications. Full article

The widespread availability of artificial intelligence (AI) tools has facilitated the development of complex, high-performance applications across a broad range of domains. Among these, processes related to the surveillance and assisted verification of indoor environments have garnered significant interest. This paper presents the implementation, testing, and validation of an autonomous mobile platform designed for the intelligent and flexible inspection of such spaces. The artificial vision system, the main component on which the study focuses, was built using a Raspberry Pi 5 development module supplemented by a Raspberry Pi AI Kit to enable hardware acceleration for image recognition tasks using AI techniques. Some of the most recognized neural network models were evaluated in line with the application’s specific requirements. Utilizing transfer learning techniques, these models were further developed and trained with additional image datasets tailored to the inspection tasks. The performance of these networks was then tested and validated on new images, facilitating the selection of the model with the best results. The platform’s flexibility was ensured by mounting the artificial vision system on a mobile structure capable of autonomously navigating indoor environments and identifying inspection points, markers, and required objects. The platform could generate reports, make decisions based on the detected conditions, and be easily reconfigured for alternative inspection tasks. Finally, the intelligent and flexible inspection system was tested and validated for its deep learning-based vision system performance. Full article

In capacitance-coupled voltage-sensing technology, the degree of coupling capacitance is affected by the sensing area, relative position deviation, and other factors, and thus the measurement coefficient is often difficult to determine accurately and presents greater implementation difficulties in actual deployment. This paper proposes a dynamic reconfiguration based on the measurement circuit topology of the voltage sensor adaptive calibration method in order to measure voltage sensor gain in the process of automatic measuring. Firstly, the basic principle of voltage measurement is introduced, and the self-calibration method is proposed, considering the influence of the sensing area and the relative position error on the change in the coupling capacitance. On this basis, the influence of calibration accuracy on sensor structure parameters is analyzed using network sensitivity analysis, and the parameter selection principle is given, according to which the selection criterion of parameter optimization is formulated to complete the sensor design. By analyzing the coupling effect of the three-phase measurement, the installation method of the sensing structure is proposed. An experimental platform is built to test the accuracy of the voltage measurement of the sensor under laboratory conditions. The experimental results show that the maximum relative error of the voltage measurement amplitude is 2.24%. In order to verify the feasibility of the sensor technology designed, the measurement models that integrate communication, acquisition, and processing are installed on both ends of the circuit breaker wire, and the voltage waveform generated during the circuit breaker closing process is recorded in real time. The experimental results show that the sensor technology can accurately record the voltage waveform of the signal to be measured, and the feasibility of its application in switchgear equipment signal measurement is preliminarily verified by the results. Full article

With the increasing demand for accurate and robust positioning solutions, the use of GNSS antenna arrays has gained significant attention. However, their development and testing are frequently constrained by the inflexibility of traditional hardware platforms, often requiring extensive reconfiguration throughout the development cycle. This paper presents a platform based on a system on chip to develop a highly flexible software-controlled system that is capable of directly sampling up to 16 antenna elements. Multibeam digital beamforming is implemented using the available FPGA resources and the resulting signal is reproduced by the integrated DAC and can be connected to any conventional single antenna GNSS receiver. This paper presents the architecture of the platform, detailing its components and capabilities. Our experimental results demonstrate that the system can phase shift every channel with errors of less than 0.5° and can reconfigure 4 simultaneous beams of a 16-antenna array at speeds of 1.2 kHz, and 20 beams at around 400 Hz. The average delay introduced by each channel of the system is around 381 ns with a maximum deviation of 1.05 ns. The delay was also measured for the implementation using 4 beams, which achieves a slightly bigger average delay of 384.6 ns while keeping the variation to 5 to 6 ns. This system is intended to be used as the backbone for the development of antenna arrays and beamforming algorithms. Given its flexibility, it is not necessary to develop new hardware between development iterations or even for different systems, as only the software layer needs to be modified. Consequently, it is possible to expedite the development stage before producing dedicated solutions for industrial applications. Full article

Field-Programmable Gate Arrays (FPGAs) play a significant and evolving role in various industries and applications in the current technological landscape. They are widely known for their flexibility, rapid prototyping, reconfigurability, and design development features. FPGA designs are often constructed as compositions of interconnected modules that implement the various features/functionalities required in an application. This work develops a novel tool FEINT, which facilitates this module composition process and automates the design-level modifications required when introducing new modules into an existing design. The proposed methodology is architected as a “template” insertion tool that operates based on a user-provided configuration script to introduce dynamic design features as plugins at different stages of the FPGA design process to facilitate rapid prototyping, composition-based design evolution, and system customization. FEINT can be useful in applications where designers need to tailor system behavior without requiring expert FPGA programming skills or significant manual effort. For example, FEINT can help insert defensive monitoring, adversarial Trojan, and plugin-based functionality enhancement features. FEINT is scalable, future-proof, and cross-platform without a dependence on vendor-specific file formats, thus ensuring compatibility with FPGA families and tool versions and being integrable with commercial tools. To assess FEINT’s effectiveness, our tests covered the injection of various types of templates/modules into FPGA designs. For example, in the Trojan insertion context, our tests consider diverse Trojan behaviors and triggers, including key leakage and denial of service Trojans. We evaluated FEINT’s applicability to complex designs by creating an FPGA design that features a MicroBlaze soft-core processor connected to an AES-accelerator via an AXI-bus interface. FEINT can successfully and efficiently insert various templates into this design at different FPGA design stages. Full article

A new dual-frequency, dual-mode reconfigurable digital receiver based on Field-Programmable Gate Array (FPGA) dynamic reconfiguration is proposed, which is based on a common hardware platform of high-bandwidth RF front-end, high-speed data acquisition, and real-time signal processing. The receiver adopts the design of dynamically reconfigurable down-conversion, filter extraction, and matched filtering in the digital domain. In this study, we completed the design and development of the digital receiver, experimental platform construction, and field detection test with hardware and software cooperation. The experimental results show that the receiver achieves full digital reception and signal processing for 53.8 MHz stratosphere–troposphere (ST) detection and 35.0 MHz meteor detection and successfully acquired the number of meteors versus time, the meteor trail, and low-altitude atmospheric radial winds. This dual-frequency, dual-mode reconfigurable digital receiver can be applied to new-generation multifunction integrated radar systems such as dual-frequency ST/meteor radars. Full article

Using a combination of experimental and numerical methods, this study examines the stability of the slope of Waste Dump#1 in Ziluoyi Iron Mine. We conducted direct shear tests on soil samples taken from the waste dump, which provided important insights into slope stability. The tests identified key mechanical parameters, including an average cohesion of 4.80 kPa and an internal friction angle of 25.63°. By implementing GEO-SLOPE software, we could determine that the slope stability factor is 1.047, which is far from the required safety standards. To address this issue, we proposed an appropriate rectification strategy including the construction of safety platforms and reconfiguration of the slope structure. This approach effectively improved the slope stability factor to 1.219 and met the safety criteria. In addition, particle flow code (PFC) simulations were methodically performed to model the slope morphology and particle displacement before and after rectification. The obtained results revealed a remarkable reduction in sliding areas and particle displacement post-rectification, enhancing mine safety and efficiency. Our findings provide valuable insights into the application of combined experimental and numerical methods to assess and improve slope stability in open-pit mines, which will substantially contribute to the field of geotechnical engineering and mining safety. Full article

The main objective of this work is to evaluate the energy efficiency improvement obtained in grid-connected photovoltaic systems based on a dynamic reconfiguration strategy. The MIX and team reconfigurable photovoltaic system topologies have been considered since both minimize the operation of the inverters in low-load conditions. A numerical method is used to analyze the energy flows within the photovoltaic system, with a specific focus on the plant-oriented configuration. In this work, MIX systems are only presented briefly, while team reconfigurable photovoltaic systems are analyzed in more detail. This is because team systems can be implemented using conventional commercial inverters, electromechanical switches to redirect power flows, and a simple digital controller (as based on the Arduino platforms). The energy supplied to the grid by two grid-connected photovoltaic systems will be evaluated: one based on a classic non-reconfigurable strategy and another based on the team strategy. The measurement of the energy generated by these two systems, tested under various irradiance levels (emulating different climatic conditions), shows that reconfigurable systems always exhibit greater energy efficiency. However, this energy improvement can only be considered substantial in certain situations. Full article