Search Results (216)

Background: Skilled human movement, such as the golf swing, emerges from coordinated rotational and translational dynamics. This study investigates pitch—a screw-theoretic invariant defined as the ratio of linear to angular velocity along the instantaneous screw axis (ISA)—as a compact metric for quantifying motor coordination. Methods: We reanalyzed a validated motion capture dataset involving a proficient and a novice female golfer. ISA trajectories and pitch values were computed from 3D marker data, and synchronized with vertical ground reaction force (GRF) signals collected via force plate. Results: The proficient golfer exhibited tightly bounded pitch oscillations (approximately ±0.0025 cm/rad) that were temporally aligned with a single, well-defined GRF peak. In contrast, the novice showed irregular pitch fluctuations (−0.025 to +0.01 cm/rad) and asynchronous GRF patterns with multiple peaks. Conclusions: These findings demonstrate that pitch can serve as a biomechanical indicator of skilled performance, reflecting the degree of intersegmental coordination and force timing. Screw theory thus offers a rigorous framework for evaluating movement efficiency in sport and rehabilitation contexts. Full article

Vehicle suspension significantly influences the safety of cargo transportation. This study presents a 14-degree-of-freedom vehicle–cargo coupling model that explicitly incorporates the frequency-dependent stiffness of air springs. Systematic parametric investigations of air spring orifice resistance, loading mass, and cargo stiffness reveal the following: (a) Compared with leaf spring suspension, air suspension vehicles attenuated the first peak of acceleration power spectral density by over 50%, while slightly amplifying the second peak; (b) When replacing leaf spring suspension with air suspension, the upper-layer cargo exhibited significantly larger vibration reductions (14% vertical, 28% pitch) than the lower-layer cargo under identical cargo parameters. The roll angle should be controlled to prevent the cargo overturning when equipping air suspensions; (c) Under light loading conditions, the vertical vibration response in upper-layer cargo is amplified. This amplification can be effectively suppressed through two complementary approaches, i.e., employing low-stiffness cushion materials and reducing orifice resistance through tunable orifices, which collectively attenuate characteristic peaks in the frequency-domain response and comprehensively mitigate the vertical vibration of cargo. These findings provide guidance for designing transportation schemes for cargo in air suspension vehicles to enhance cargo safety. Full article

This paper proposes a novel hierarchical control architecture that combines Model Predictive Control (MPC) with Explicit Model-Following Control (EMFC) to enable accurate and efficient trajectory tracking for quadrotor electric Vertical Takeoff and Landing (eVTOL) aircraft operating in urban environments. The approach addresses the challenges of strong nonlinear dynamics, multi-axis coupling, and stringent safety constraints by separating the planning task from the fast-response control task. The MPC layer generates constrained velocity and yaw rate commands based on a simplified inertial prediction model, effectively reducing computational complexity while accounting for physical and operational limits. The EMFC layer then compensates for dynamic couplings and ensures the rapid execution of commands. A high-fidelity simulation model, incorporating rotor flapping dynamics, differential collective pitch control, and enhanced aerodynamic interference effects, is developed to validate the controller. Four representative ADS-33E-PRF tasks—Hover, Hovering Turn, Pirouette, and Vertical Maneuver—are simulated. Results demonstrate that the proposed controller achieves accurate trajectory tracking, stable flight performance, and full compliance with ADS-33E-PRF criteria, highlighting its potential for autonomous urban air mobility applications. Full article

The development of Global Positioning System (GPS) technology has contributed in various ways to improving the physical condition of modern football players by enabling the quantification of physical load. Previous studies have reported that the running demands of matches vary depending on playing position and formation. Over the past decade, despite the widespread use of GPS technology, studies that have investigated the running performance of young football players within the 1-4-3-3 formation are particularly limited. Therefore, the aim of the present study was to create the match running profile of playing positions in the 1-4-3-3 formation among high-level youth football players. An additional objective of the study was to compare the running performance of players between the two halves of a match. This study involved 25 football players (Under-19, U19) from the academy of a professional football club. Data were collected from 18 league matches in which the team used the 1-4-3-3 formation. Positions were categorized as Central Defenders (CDs), Side Defenders (SDs), Central Midfielders (CMs), Side Midfielders (SMs), and Forwards (Fs). The players’ movement patterns were monitored using GPS devices and categorized into six speed zones: Zone 1 (0.1–6 km/h), Zone 2 (6.1–12 km/h), Zone 3 (12.1–18 km/h), Zone 4 (18.1–21 km/h), Zone 5 (21.1–24 km/h), and Zone 6 (above 24.1 km/h). The results showed that midfielders covered the greatest total distance (p = 0.001), while SDs covered the most meters at high and maximal speeds (Zones 5 and 6) (p = 0.001). In contrast, CDs covered the least distance at high speeds (p = 0.001), which is attributed to the specific tactical role of their position. A comparison of the two halves revealed a progressive decrease in the distance covered by the players at high speed: distance in Zone 3 decreased from 1139 m to 944 m (p = 0.001), Zone 4 from 251 m to 193 m (p = 0.001), Zone 5 from 144 m to 110 m (p = 0.001), and maximal sprinting (Zone 6) dropped from 104 m to 78 m (p = 0.01). Despite this reduction, the total distance remained relatively stable (first half: 5237 m; second half: 5046 m, p = 0.16), indicating a consistent overall workload but a reduced number of high-speed efforts in the latter stages. The results clearly show that the tactical role of each playing position in the 1-4-3-3 formation, as well as the area of the pitch in which each position operates, significantly affects the running performance profile. This information should be utilized by fitness coaches to tailor physical loads based on playing position. More specifically, players who cover greater distances at high speeds during matches should be prepared for this scenario within the microcycle by performing similar distances during training. It can also be used for better preparing younger players (U17) before transitioning to the U19 level. Knowing the running profile of the next age category, the fitness coach can prepare the players so that by the end of the season, they are approaching the running performance levels of the next group, with the goal of ensuring a smoother transition. Finally, regarding the two halves of the game, it is evident that fitness coaches should train players during the microcycle to maintain high movement intensities even under fatigue. Full article

High-precision positioning is the foundation for the functionality of various intelligent agents. In complex environments, such as urban canyons, relative pose estimation using cameras is a crucial step in high-precision positioning. To take advantage of the ability of an inertial measurement unit (IMU) to provide relatively accurate gravity prior information over a short period, we propose a minimal solution method for the relative pose estimation of a stereo camera system assisted by the IMU. We rigidly connect the IMU to the camera system and use it to obtain the rotation matrices in the roll and pitch directions for the entire system, thereby reducing the minimum number of corresponding points required for relative pose estimation. In contrast to classic pose-estimation algorithms, our method can also calculate the camera focal length, which greatly expands its applicability. We constructed a simulated dataset and used it to compare and analyze the numerical stability of the proposed method and the impact of different levels of noise on algorithm performance. We also collected real-scene data using a drone and validated the proposed algorithm. The results on real data reveal that our method exhibits smaller errors in calculating the relative pose of the camera system compared with two classic reference algorithms. It achieves higher precision and stability and can provide a comparatively accurate camera focal length. Full article

Surrogate modeling has been rapidly evolving in the field of aerospace engineering, further reducing the cost of computational analyses. These models often require large amounts of information to learn the underlying process, which is at odds with obtaining and using the highest-fidelity data. This study assesses the efficacy of multi-fidelity modeling (MFM) to improve simulation accuracy while reducing computational cost. A database of hovering rotor simulations with perturbations of the rotor design and operating conditions was first generated using two different fidelity levels of the OVERFLOW 2.4D Computational Fluid Dynamics software. MFM was then used to quantify the effectiveness of this approach for the development of accurate surrogate models. Multi-fidelity models based on Gaussian Process Regression (GPR) were derived for hovering rotor performance prediction given the geometric rotor blade inputs that currently include twist, planform, airfoil, and the collective pitch angle. The MFM approach was consistently more accurate at predicting the hold-out test data than the surrogate model with high-fidelity data alone. An MFM using just 20% of the available high-fidelity training data was as accurate as a solely high-fidelity model trained on 80% of the available data, representing an approximate fourfold reduction in computational cost. Full article

With the increasing importance of animal welfare, behavioral indicators such as changes in head and ear posture are widely recognized as non-invasive and field-applicable markers for evaluating the emotional state and stress levels of animals. However, traditional visual observation methods are often subjective, as assessments can vary between observers, and are unsuitable for long-term, quantitative monitoring. This study proposes an artificial intelligence (AI)-based system for the detection and pose estimation of cattle heads and ears using deep learning techniques. The system integrates Mask R-CNN for accurate object detection and FSA-Net for robust 3D pose estimation (yaw, pitch, and roll) of cattle heads and left ears. Comprehensive datasets were constructed from images of Japanese Black cattle, collected under natural conditions and annotated for both detection and pose estimation tasks. The proposed framework achieved mean average precision (mAP) values of 0.79 for head detection and 0.71 for left ear detection and mean absolute error (MAE) of approximately 8–9° for pose estimation, demonstrating reliable performance across diverse orientations. This approach enables long-term, quantitative, and objective monitoring of cattle behavior, offering significant advantages over traditional subjective stress assessment methods. The developed system holds promise for practical applications in animal welfare research and real-time farm management. Full article

Background: Dog agility is a rapidly growing sport involving a partnership between a dog and the handler, running through an obstacle course. Despite its increasing popularity and physical benefits, research on handler injuries remains limited. This study aimed to assess injury epidemiology of athletes practicing dog agility. Methods: This cross-sectional study was conducted using a comprehensive online survey consisting of 124 items, available in both English and Italian. The questionnaire was divided into four sections: Introduction collected demographic data and medical history; Materials and Methods focused on agility-related activities; Results explored injuries sustained in the past 12 months; Discussion examined training habits unrelated to agility. Results: Among 389 participants, the most represented age group ranged between 30 and 40 years old. Overall, 7% reported upper limb injuries, while 27% experienced at least one lower limb injury. Additionally, 20% of participants used medication, and 25% reported at least one chronic illness. On average, handlers trained twice per week and competed in two events per month. Lower limb injuries were predominantly muscular (49%) or ligamentous (14%) and most commonly occurred on grass pitches (56%). These injuries were more common in participants with a higher BMI, those using dynamic handling styles, and those competing at higher levels. Conclusions: This cross-sectional study highlighted the importance of identifying risk factors associated with dog agility handlers. Lower limb injuries were the most common, often associated with increased physical demands and handling styles involving intensive running and correlated with reduced physical fitness. Athletic conditioning, including structured warm-up and cool-down practices, might help decline injury risks. Full article

This article represents a full estimation of helicopter rotor aerodynamic characteristics in ground effect conditions through the application of a coupled empirical blade element–momentum theory algorithm. The main focus of this research includes the evaluation of the required weighted power coefficients $\left({\displaystyle \raisebox{1ex}{$C_P$}\!\left/ \!\raisebox{-1ex}{$\sigma $}\right.}\right)$ for a hovering state in close proximity to obstacles and their relation to the weighted thrust force coefficients’ values $\left({\displaystyle \raisebox{1ex}{$C_T$}\!\left/ \!\raisebox{-1ex}{$\sigma $}\right.}\right),$ varying the relative distance from the helicopter rotational plane to the ground surface $\left({\displaystyle \raisebox{1ex}{$H$}\!\left/ \!\raisebox{-1ex}{$R$}\right.}\right)$ and the rotor’s collective pitch angle (θ). The represented numerical and experimental results show that an increase in the collective pitch angles (θ) leads to a rise in the generated weighted thrust force coefficients $\left({\displaystyle \raisebox{1ex}{$C_T$}\!\left/ \!\raisebox{-1ex}{$\sigma $}\right.}\right)$ and in the weighted power coefficients $\left({\displaystyle \raisebox{1ex}{$C_P$}\!\left/ \!\raisebox{-1ex}{$\sigma $}\right.}\right)$ for every individual fixed normalized distance from the ground surface $\left({\displaystyle \raisebox{1ex}{$H$}\!\left/ \!\raisebox{-1ex}{$R$}\right.}\right)$. Moreover, a decline in the relative distance from the ground $\left({\displaystyle \raisebox{1ex}{$H$}\!\left/ \!\raisebox{-1ex}{$R$}\right.}\right)$ requires less power to keep the rotation going in hover. The dependencies indicate that the ground effect zone covers a distance of up to 2R from the rotational plane to the ground surface. Full article

This study explores how Speech and Elocution Training (SET) activates language potential and fosters career-oriented development among higher vocational students through self-efficacy mechanisms. Through qualitative interviews with four vocational graduates who participated in SET 5 to 10 years ago, the research identifies three key findings. First, SET comprises curriculum content (e.g., workplace communication modules such as hosting, storytelling, and sales pitching) and classroom training using multimodal TED resources and Toastmasters International-simulated practices, which spark language potential through skill-focused, realistic exercises. Second, these pedagogies facilitate a progression where initial language potential evolves from nascent career interests into concrete job-seeking intentions and long-term career plans: completing workplace-related speech tasks boosts confidence in career choices, planning, and job competencies, enabling adaptability to professional challenges. Third, SET aligns with Bandura’s four self-efficacy determinants; these are successful experiences (including personalized and virtual skill acquisition and certified affirmation), vicarious experiences (via observation platforms and constructive peer modeling), verbal persuasion (direct instructional feedback and indirect emotional support), and the arousal of optimistic emotions (the cognitive reframing of challenges and direct desensitization to anxieties). These mechanisms collectively create a positive cycle that enhances self-efficacy, amplifies language potential, and clarifies career intentions. While highlighting SET’s efficacy, this study notes a small sample size limitation, urging future mixed-methods studies with diverse samples to validate these mechanisms across broader vocational contexts and refine understanding of language training’s role in fostering linguistic competence and career readiness. Full article

The accuracy of the blade pitch angle (BPA) motion in controllable pitch propellers (CPPs) is considered crucial for the efficacy and reliability of marine propulsion systems. The pitch adjustment process of CPPs is highly complex and influenced by various uncertain factors. A parametric kinematic model for the pitch adjustment process for CPPs was established, incorporating the geometric dimensions and material surface friction coefficients caused during workpiece production as uncertainty parameters. The aim was to establish the correspondence between these uncertainty parameters and the BPA of CPPs. A large dataset was generated by batch calling on Adams. Based on the collected dataset, five surrogate models (e.g., deep neural network (DNN), Kriging, support vector regression (SVR), random forest (RF), and polynomial chaos expansion Kriging (PCK)) were constructed to predict the BPA. Among these, the DNN approach demonstrated the highest prediction accuracy. Accordingly, the influence of uncertainties on the BPA was investigated using the DNN model, focusing on variations in the slider width, crank pin diameter, crank disc diameter, piston rod–slider friction coefficient, crank pin–slider friction coefficient, and hub bearing–crank disc friction coefficient. The high-fidelity model established in this study can replace the kinematic model of the CPP pitch adjustment process, significantly improving computational efficiency. The research findings also provide important references for the design optimization of CPPs. Full article

Background: There are no data in the literature regarding the optimal pitch training load (PTL) for elite soccer teams during congested seasons. Objectives: This study had three goals: (1) identify whether there is an adaptation in match physical performance (MPP) in response to PTL throughout a congested season in elite soccer players; (2) identify whether MPP adaptation is specific to the coach’s PTL philosophy; and (3) identify the optimal PTL for MPP during a congested season. Method: Over two seasons, we collected data from 11,658 PTL sessions and 3068 MPP data from 54 elite male soccer players. The PTL sessions were clustered in weekly training blocks and paired with MPP for statistical and machine learning analysis. Results: Over the season, MPP increased in the mid-season and this trend decreased during the end-season. Also, MPP reflected the coach’s PTL philosophy. Further, using a machine learning (k-means) approach, we identified three different PTLs (and classified them as low-, medium-, and high-load PTL blocks). The high-load PTL block was associated with a higher MPP, while the lower PTL was associated with a lower MPP. Conclusions: PTL is closely related to MPP, and this change also reflects the coach’s PTL philosophy. Here, we report an optimal PTL that could be useful for soccer teams playing a congested season. Full article

Wind turbines align with the wind direction and adjust to wind speed by rotating their nacelle and blades using electromechanical or hydraulic actuators. Due to the fact that the rated capacity of wind turbines is increasing and that the actuators are reaching some size limits, the current solution is to install several actuators at each joint until the required torque is reached. The problem with this approach is that, despite the fact the actuators can be selected from the same type and series, they typically have distinct parameters, resulting in different behaviours. The synchronisation of actuators of wind turbines has still not been studied in the specialised literature. Therefore, a control approach for the synchronisation of the pitch actuators is proposed in this work. Two cases are considered: the synchronisation of torque outputs and the synchronisation of position angle. The simulation results indicate that the proposed solution is effective for synchronising actuators, either when they are placed together on the same blade or when they are on separate blades while simultaneously following the collective pitch control command. Full article

A newly designed tilt-wing unmanned aerial vehicle (Tilt-wing UAV) requires a unified control strategy across rotary-wing, fixed-wing, and transition modes, introducing significant challenges. Existing control strategies typically rely on accurate modeling or extensive parameter tuning, which limits their adaptability to dynamically changing flight configurations. Although online reinforcement learning algorithms offer adaptability, they depend on real-world exploration, posing considerable safety and cost risks for safety-critical UAV applications. To address this challenge, we propose Temporal Sequence Constrained Q-learning (TSCQ), an offline RL framework that integrates an encoder–decoder with recurrent networks to capture temporal dependencies. The policy is further constrained within an offline dataset collected via hardware-in-the-loop simulation using a variational autoencoder, and a sequence-level prediction mechanism is introduced to ensure temporal consistency across action trajectories, thereby mitigating extrapolation error while preserving data fidelity. Experimental results demonstrate that TSCQ significantly outperforms gain scheduling, Model Predictive Control (MPC), and Batch-Constrained Q-learning (BCQ), reducing the RMSE of pitch angle by up to 53.3% and vertical velocity RMSE by approximately 33%. These findings underscore the potential of data-driven, safety-aware offline RL paradigms to enable robust and generalizable control strategies for tilt-wing UAVs. Full article

This study examines the acoustic properties of vowels in foreigner-directed speech (FDS) in interactions between female Omani-Arabic-speaking employers and their foreign domestic helpers (FDHs). Particularly, it investigates whether Arabic corner vowels /i:/, /a:/, and /u:/ undergo acoustic adaptations in FDS. The study also explores the influence of foreign interlocutors’ psycholinguistic characteristics, such as degree of foreign accent, religion, and length of residence (LoR), on the extent of these adaptations. Data were collected from 22 Omani-Arabic-speaking women interacting with their 22 FDHs and with a native speaker (NS) confederate using a spot-the-difference task. Acoustic measures including vowel space area, formant frequency measures (F1 and F2), fundamental frequency (f0), intensity, and duration were compared across speech directed at FDHs and the NS. The results revealed that FDS exhibited greater vowel space expansion, higher F1, and increased pitch (f0) and intensity compared to speech directed at the NS confederate. However, FDS did not significantly affect F2 values. Unexpectedly, vowel duration in FDS was shorter than in speech directed at the NS. Furthermore, the psycholinguistic factors of foreign interlocutors had no significant effect on vowel space expansion in FDS. These findings provide evidence that FDS is characterized by heightened prosodic and acoustic features, potentially contributing to clearer speech. Additionally, the study highlights that NSs employ FDS when interacting with foreigners perceived to have a foreign accent. Full article