Search Results (217)

Quadrotor unmanned aerial vehicles demonstrate broad application prospects, yet existing research still lacks a comprehensive solution that simultaneously addresses efficiency, disturbance rejection, environmental adaptability, and precision in their control performance. To achieve prescribed-time convergence and prescribed tracking performance, this work proposes a composite control scheme that integrates prescribed-performance control, disturbance estimation, and terminal sliding-mode control. First, a prescribed-time adaptive composite disturbance observer is developed to estimate and compensate for system composite disturbances, and a stability analysis shows that the disturbance estimation error converges to a small neighborhood of the origin within a prescribed time. Second, the system is decomposed into position and attitude subsystems, enabling tailored hierarchical control-law design and analysis based on their distinct dynamics. For position control, a prescribed-performance control method is employed, incorporating a prescribed-time performance function that accommodates large initial deviations, thereby guaranteeing convergence of the position-tracking errors to a small neighborhood within a specified time. For attitude control, a prescribed-time terminal sliding-mode surface and corresponding control law are designed to eliminate singularities and ensure convergence of the attitude errors to a small neighborhood within a predetermined time. The stability of both subsystems is rigorously substantiated through theoretical analysis. Finally, comparative simulation results confirm the effectiveness and superiority of the proposed control strategy. Full article

The global demand for argan oil has grown considerably in recent years, creating economic opportunities while raising concerns about ecosystem degradation and the sustainability of production systems. To support long-term viability, several initiatives have promoted environmentally friendly practices and fair value-chain models. However, the effective market integration of these initiatives depends on understanding consumer behavior and preferences toward sustainable products. This study aims to identify the determinants influencing consumers’ purchase intention for sustainable argan oil using an extended framework of the Theory of Planned Behavior (TPB). A structural equation modeling approach was applied to analyze responses from adult consumers with a minimum education level of secondary education. The results show that consumer attitude, perceived behavioral control, and willingness to pay have significant positive effects on purchase intention, while ecological literacy exerts an indirect influence through attitude, social norms, perceived behavioral control, and willingness to pay. In contrast, ecological literacy has no significant direct impact. These findings improve the understanding of behavioral mechanisms underlying green product consumption and offer insights into designing marketing strategies that align with sustainability values and promote responsible consumer choices. Full article

This study examines the socio-economic and behavioral factors influencing sustainable consumption through secondhand clothing purchases among young consumers in Hanoi, Vietnam. By addressing the changing consumption patterns, this research contributes to understanding how youth behavior supports the transition toward sustainability in emerging urban markets. This research integrates the Theory of Planned Behavior (TPB) with additional constructs such as perceived economic benefits, environmental concern, perceived risk, shopping experience, and gender differences to provide an integrated socio-economic framework. Data were collected through a structured questionnaire administered to university students and analyzed using Partial Least Squares Structural Equation Modeling (PLS-SEM). Results indicate that perceived economic benefits and subjective norms are the strongest predictors of purchase intention across both general and luxury secondhand fashion segments, emphasizing affordability and social acceptance. Environmental concern and attitude also positively influence general secondhand purchase intentions, while perceived behavioral control notably impacts luxury secondhand purchases. Contrary to prior studies, perceived risk was found to be insignificant, and male consumers exhibited a higher engagement rate than females in this context. These findings underscore the complex interplay of economic, social, and environmental dimensions shaping sustainable fashion consumption among youth. This study suggests targeted marketing and policy strategies to promote sustainable consumption and supports the expansion of circular economy practices in emerging urban markets. Limitations related to sample scope and self-reported data warrant further research to generalize the findings and explore additional moderating variables. Full article

During the transposition of a target satellite, dynamic coupling between the target satellite, the manipulators, and the base frequently leads to disturbances in the base’s attitude. To deal with the issue, this paper proposed a pose stabilization method for the base of the post-capture combined system using the feedforward compensation PD control. Firstly, the mission sequence for repositioning a target satellite using a discrete-serpentine heterogeneous dual-arm space robot (DSHDASR) was analyzed. The dynamics model of the combined system, composed of the DSHDASR and a target satellite, was established based on the Newton–Euler recursive formulation. Then, the pose stabilization method integrating dynamic feedforward compensation and PD control was developed to stabilize the base of the combined system. Finally, the mission of target satellite transposition was simulated through the co-simulation model. Compared with the traditional control algorithms, the position accuracy and attitude accuracy for the proposed method showed an overall improvement. The results demonstrated that the proposed method significantly reduced base pose errors under high-load and disturbed conditions. Full article

As a representative case that embodies both the attributes of a Buddhist sacred site and those of a UNESCO World Heritage site, Mount Wutai provides a distinctive research setting for examining behavioral mechanisms in temple tourism. This study aims to construct an integrated model to systematically test the effects of enjoyment, memorability, attitude, subjective norm, and perceived behavioral control (PBC) on revisit intention (RI), while incorporating social media exposure as a moderating variable. Based on data collected through a two-wave on-site survey, this study analyzed 617 tourists in Mount Wutai and employed structural equation model to examine the relationships among the variables. The results indicate that all five psychological antecedents exert significant positive effects on revisit intention, among them, PBC demonstrating the most substantial impact. Further analysis reveals that social media exposure significantly moderates the relationships among enjoyment, memorability, attitude, subjective norm, and revisit intention, most notably in the “memorability–RI” relationship, whereas its moderating effect on the “PBC–RI” relationship is not significant. These findings not only enrich the theoretical framework by integrating emotional attribution, behavioral cognition, and digital media engagement but also provide practical implications for sacred tourism destinations, enabling them to enhance visitor loyalty through digital communication and experience optimization. Full article

Reducing energy demand and carbon emissions in residential buildings requires more than technological upgrades; it demands a nuanced understanding of occupant behaviour. Residential energy use is shaped by both physical design and human actions, yet behavioural factors remain underexplored, contributing to the energy performance gap. This study addresses this issue by developing and validating a behavioural framework grounded in the Theory of Planned Behaviour (TPB) to examine how attitudes, social norms, perceived control, and environmental awareness influence energy-related decisions. Data were collected through an online survey of 310 households in metropolitan Sydney and analysed using Stata v17 software employing principal component analysis and regression modelling. Results reveal that environmental awareness is the most significant predictor of pro-environmental intention, which strongly correlates with actual behavioural outcomes. While attitudes and perceived control were generally positive, subjective norms and awareness remained moderate, limiting behavioural change. The proposed framework demonstrates strong validity and reliability, offering a practical tool for policymakers, designers, and educators to integrate behavioural insights into sustainable building strategies. By prioritising awareness campaigns and normative interventions, stakeholders can complement technical retrofits with behavioural measures, accelerating progress towards low-carbon housing and benefiting both households and the broader community. Full article

This study presents the design and implementation of a real-time flight-path tracking control system for a quadrotor unmanned aerial vehicle (UAV) capable of accurately following a mobile ground target under dynamic and uncertain environmental conditions. The proposed framework integrates classical fixed-gain PID regulation executed on Pixhawk with its built-in adaptive mechanisms, namely autotuning, hover-throttle learning, and dynamic harmonic notch filtering, to enhance robustness under communication latency and disturbances. No machine learning PID tuning is used on Pixhawk; adaptive features are estimator based rather than ML based. The proposed system addresses critical challenges in trajectory tracking, including real-time delay compensation between the UAV and rover, external perturbations, and the requirement to maintain stable six-degree-of-freedom (DOF) control of altitude, yaw, pitch, and roll. A dynamic mathematical model, formulated using ordinary differential equations with embedded delay elements, is developed to emulate real-world flight behavior and validate control performance. Experimental evaluation demonstrates robust path-tracking accuracy, attitude stability, and responsiveness across diverse terrains and weather conditions, achieving a mean positional error below one meter and effective resilience against an 8.2 ms communication delay. Overall, this work establishes a scalable, computationally efficient, and high-precision control framework for UAV guidance and cooperative ground-target tracking, with potential applications in autonomous navigation, search-and-rescue operations, infrastructure inspection, and intelligent surveillance. The term “delay-aware” in this work refers to the explicit modeling of the measured 8.2 ms end-to-end delay and the use of Pixhawk’s estimator-based adaptive mechanisms, without any machine learning-based PID tuning. Full article

Background: nowadays, traditional delivery options are challenging to the urban last-mile logistics and sustainability goals. The purpose of this study is to investigate the practical factors that drive frequent e-shoppers to actively switch their intention from conventional delivery options to utilizing smart lockers. Methods: the hypothetical framework tested integrating constructs from the Technology Acceptance Model (TAM) and the Theory of Planned Behavior (TPB), and supplementary constructs such as privacy and convenience. Data were collected via a structured online questionnaire from 513 respondents in major Egyptian cities, including Alexandria and Cairo. The framework was tested using Structural Equation Modeling (SEM) via SmartPLS 4.0 software to assess the relationship between constructs and switching intention. Results: the analysis confirms that switching intention to use smart lockers is positively driven by Perceived Usefulness, Perceived Ease of Use, Convenience, Privacy, and Perceived Behavioral Control. Notably, a positive attitude towards smart lockers was found to have a non-significant effect on the intention to switch in the Egyptian context. Conclusions: this research contributes to addressing the gap in the extant literature by focusing on analyzing the unique contextual determinants in the emerging last-mile logistics within a developing market context. Full article

A fast and stable flight control system is crucial for improving the efficiency of unmanned aerial vehicle (UAV) missions. Focusing on the trajectory tracking control of quadrotor UAVs, this paper proposes a trajectory tracking control method based on the global fast terminal sliding mode control (GFTSMC) algorithm to address the slow response speed and insufficient anti-disturbance capability inherent in the widely used Proportional–Integral–Derivative (PID) control algorithm and conventional sliding mode control (SMC) algorithm. Firstly, considering the gyroscopic moment of a quadrotor UAV’s rotors, an accurate kinematic and dynamic model of a quadrotor UAV is established, and the trajectory tracking problem faced by such UAVs is decoupled into the command tracking problems of the position loop and the attitude loop. Secondly, GFTSMC controllers are designed for these loops, and the Lyapunov principle is adopted to prove the stability of the designed controllers. Finally, simulation verification is carried out. The simulation results show that, compared to PID control, GFTSMC-based trajectory tracking control for quadrotor UAVs exhibits the characteristics of no overshoot, higher tracking accuracy, and stronger anti-disturbance capability. Compared to nonsingular terminal sliding mode control (NTSMC) and SMC, GFTSMC-based trajectory tracking control reduces the steady-state convergence time by 33.8% and 36.5% and the steady-state disturbance error by 83.1% and 97.3%, respectively, demonstrating faster response speed and stronger anti-disturbance capability. Therefore, the application of GFTSMC significantly improves the trajectory tracking control performance of quadrotor UAVs, thereby supporting them in performing operations in scenarios requiring high real-time performance, precision, and anti-disturbance capability. Full article

Rapid and precise intervention in disaster and medical-aid scenarios demands aerial platforms that can both survey and physically interact with their environment. This study presents the design, fabrication, modeling, and experimental validation of a one-piece, 3D-printed quadcopter with an integrated six-degree-of-freedom aerial manipulator robotic arm tailored for emergency response. First, we introduce an ‘X’-configured multi-rotor frame printed in PLA+ and optimized via variable infill densities and lattice cutouts to achieve a high strength-to-weight ratio and monolithic structural integrity. The robotic arm, driven by high-torque servos and controlled through an Arduino-Pixhawk interface, enables precise grasping and release of payloads up to 500 g. Next, we derive a comprehensive nonlinear dynamic model and implement an Extended Kalman Filter-based sensor-fusion scheme that merges Inertial Measurement Unit, barometer, magnetometer, and Global Positioning System data to ensure robust state estimation under real-world disturbances. Control algorithms, including PID loops for attitude control and admittance control for compliant arm interaction, were tuned through hardware-in-the-loop simulations. Finally, we conducted a battery of outdoor flight tests across spatially distributed way-points at varying altitudes and times of day, followed by a proof-of-concept medical-kit delivery. The system consistently maintained position accuracy within 0.2 m, achieved stable flight for 15 min under 5 m/s wind gusts, and executed payload pick-and-place with a 98% success rate. Our results demonstrate that integrating a lightweight, monolithic frame with advanced sensor fusion and control enables reliable, mission-capable aerial manipulation. This platform offers a scalable blueprint for next-generation emergency drones, bridging the gap between remote sensing and direct physical intervention. Full article

Satellite hovering missions involve an active propulsion phase for precise maneuvering and a subsequent passive dynamics phase wherein the satellite responds to external forces, such as from a manipulator. Therefore, a ground-testing method capable of seamlessly integrating these operational regimes is required. This paper presents a novel methodology that leverages the symmetry between active wheel-driven control and passive air-bearing dynamics to establish a unified testing platform. A mathematical model is established for the dual independent steering-wheel drive system, and an error model for tracking both the translational (position) trajectory and the rotational (attitude) trajectory of the satellite during hovering is derived. Based on this, a Model Predictive Control (MPC) scheme is designed to generate optimal driving speeds and steering angles for the wheels, ensuring accurate trajectory tracking while explicitly adhering to their driving and steering constraints. Furthermore, our work involves the integrated design of a gravity-compensated platform and its steering wheels, incorporating design methods to enhance air-bearing safety and a seamless switching method to maintain test continuity by minimizing transient disturbances. Experiments demonstrate that this integrated platform delivers both high-precision satellite trajectory tracking and high-fidelity passive air-bearing micro-gravity simulation for the active and passive phases of a satellite hovering mission. Full article

Providing effective feedback on writing remains a challenge for teachers. Among the tools and strategies being explored to address this issue is generative artificial intelligence (AI), due to its potential to deliver immediate and tailored feedback that complements teacher input. However, successful implementation requires understanding the views of those likely to integrate such tools into their future teaching practice. This quasi-experimental study explores pre-service teachers’ perceptions of the inclusion of generative AI-generated feedback. A control group received teacher feedback on their writing, while an experimental group received a combination of teacher and AI-generated feedback. After the intervention, participants’ views on the feedback received and their preparedness for assessing writing were analyzed. Results reveal more positive perceptions among the experimental group, along with greater confidence in their ability to teach and assess writing. Although both groups acknowledged the need to improve their own linguistic knowledge and assessment strategies, and emphasized the importance of teacher-led feedback, participants in the experimental group also advocated for including AI tools. This highlights the need to strengthen linguistic knowledge and assessment training in teacher education, as well as the positive attitudes and openness towards generative AI among those who have experienced its potential in feedback provision. Full article

This study examined changes in the attitudes of early childhood teachers resulting from their participation in the ONDAS Training Program, a Colombian government strategy designed to strengthen professional skills and dispositions through reflective practice and the integration of research into training. A quantitative, non-experimental longitudinal design with a descriptive-comparative scope was employed. The sample consisted of 56 female teachers evaluated before and after the program. The 12-month intervention combined a three-module virtual course on innovation, research, and academic writing with an editorial stage and expert mentoring. Data were collected through a validated survey on three dimensions: support and resources, research skills, and pedagogical appropriation. Analyses applied descriptive statistics and intra-group non-parametric tests, with the Benjamini–Hochberg adjustment used to control Type I error. The results revealed improvements in research skills, stronger pedagogical appropriation, and more positive evaluations of support and resources. These transformations also included shifts in teachers’ attitudes toward research, greater openness to feedback, and increased confidence in implementing innovative proposals. Findings confirm that early childhood teacher education is a complex process that benefits from reflective, collaborative, and situated approaches, underscoring the program’s role in strengthening professional competences and enhancing teachers’ ability to critically examine practice and adapt to diverse educational contexts. Importantly, these results provide evidence to inform national teacher training strategies in Colombia, offering practical guidance for policymakers and institutions seeking to strengthen research-based, reflective, and contextually responsive professional development programs. Full article

Context: For decades, maize monoculture practices dominated Northeast China, causing significant damage to the local soil and ecological environment. Crop rotation has, in recent years, been promoted as an environmentally friendly and sustainable technology in China. Despite its numerous benefits for the environment and crop productivity, farmers’ willingness to adopt crop rotation remains low. Objective: This study aims to investigate the social–psychological factors influencing farmers’ intentions to adopt maize–soybean rotation, with the goal of informing strategies for promoting sustainable agricultural practices. Methods: Based on a farm-level survey of 298 rural households in Northeast China, this study integrates value orientation into the Theory of Planned Behavior and employs structural equation modeling to investigate the social–psychological factors that affect farmers’ willingness to adopt soybean-based rotation. Results and Conclusions: The findings confirm the applicability of the extended Theory of Planned Behavior in explaining farmers’ decision-making. Farmers’ attitudes (0.384) and perceived behavioral control (0.323) had significant positive effects on adoption intentions, whereas subjective norms (0.018) were not significant. More favorable attitudes and greater perceived behavioral control, reflecting higher risk tolerance and better access to external support, promoted adoption. Value orientations strongly shaped farmers’ attitudes: altruism (0.148) and biospheric values (0.180) had positive effects, while egoism (0.044) showed no significant impact. These results offer guidance for policymakers to design targeted interventions promoting sustainable crop rotation. Significance: These results can help policymakers better understand what factors influence farmers’ adoption of rotation and what targeted measures can be taken to popularize the improved agricultural system. To foster farmers’ adoption of rotation, it is important to go beyond traditional supporting policies and to leverage innovative approaches to promote value orientation on sustainable farming practices. Full article

Charitable giving plays a vital role in advancing sustainable development, yet little is known about its determinants in transitional economies. This study addresses this gap by examining the socioeconomic and psychological drivers of prosocial financial behavior in Uzbekistan, integrating the Theory of Planned Behavior (TPB), Norm Activation Theory (NAT), and Well-Being Theory. Data from a sample of 348 individuals reveal two distinct pathways of giving: one shaped by resources (income, age) and another by subjective well-being (happiness). While income, age, and happiness emerged as significant positive predictors of charitable behavior, traditional TPB factors such as attitude, subjective norms, and perceived behavioral control were not supported in this context. A surprising finding was the negative association between personal norms and charitable giving, challenging assumptions of Western-centric models and pointing to the importance of cultural and institutional conditions, such as trust in charities and informal giving practices. The study contributes to sustainability research by showing that fostering well-being and targeting specific demographic groups can enhance philanthropy, while also emphasizing the need for culturally sensitive approaches in understanding prosocial behavior within emerging economies. Full article