Search Results (4,071)

WSN coverage optimization faces two key challenges: firstly, traditional algorithms are prone to getting stuck in local optima, leading to ‘coverage holes’ in node deployment; Secondly, in dynamic scenarios (such as imbalanced energy consumption of nodes), the convergence speed of the algorithm is slow, making it difficult to maintain high coverage in real time. This study focuses on the coverage optimization problem of wireless sensor networks (WSNs) and proposes improvements to the Flamingo Search Optimization Algorithm (FSA). Specifically, the algorithm is enhanced by integrating the elite opposition-based learning strategy and the stagewise step-size control strategy, which significantly improves its overall performance. Additionally, the introduction of a cosine variation factor combined with the stagewise step-size control strategy enables the algorithm to effectively break free from local optima constraints in the later stages of iteration. The improved Flamingo Algorithm is applied to optimize the deployment strategy of sensing nodes, thereby enhancing the coverage rate of the sensor network. First, an appropriate number of sensing nodes is selected according to the target area, and the population is initialized using a chaotic sequence. Subsequently, the improved Flamingo Algorithm is adopted to optimize and solve the coverage model, with the coverage rate as the fitness function and the coordinates of all randomly distributed sensing nodes as the initial foraging positions. Next, a search for candidate foraging sources is performed to obtain the coordinates of sensing nodes with higher fitness; the coordinate components of these candidate foraging sources are further optimized through chaos theory to derive the foraging source with the highest fitness. Finally, the coordinates of the optimal foraging source are output, which correspond to the coordinate values of all sensing nodes in the target area. Experimental results show that after 100 and 200 iterations, the coverage rate of the improved Flamingo Search Optimization Algorithm is 7.48% and 5.68% higher than that of the original FSA, respectively. Furthermore, the findings indicate that, by properly configuring the Flamingo population size and the number of iterations, the improved algorithm achieves a higher coverage rate compared to other benchmark algorithms. Full article

This work explores NH₃/air non-premixed combustion in a mixing layer, with the objective of quantifying the influence of key parameters on ignition and flame dynamics. A series of two-dimensional simulations were conducted with forced ignition. The evolutions of the Damköhler number (Da) and flame stretch at the peak heat release rate for cases with successful/unsuccessful ignition were examined. It was found that for the cases with successful ignition, the Damköhler number is always larger than unity, the flame stretch maintains a positive value, and the tangential diffusion consistently dominates the normal diffusion all the time. On the contrary, for the cases with unsuccessful ignition, the Damköhler number gradually becomes less than unity, and the value of the flame stretch changes from positive to negative as time advances. During flame quenching, the value of the normal diffusion term becomes larger than that of the tangential diffusion term. The effects of mixing layer thickness on the ignition kernel evolution were assessed. It was shown that a thicker mixing layer promotes ignition kernel development. The ignition process is also influenced by the location of the spark in the mixture fraction space. Finally, the flame dynamics were analyzed in terms of scalar dissipation rate ($\chi$), displacement speed $S_d$, and flame stretch ($\kappa$) for various cases. The results showed that the $S_d$ is negatively correlated with the $\kappa$ and $\chi$. The Markstein length was evaluated, and it does not differ between the cases with varying mixing layer thickness. Full article

Background: This study aimed to analyze and compare the internal and external training load responses in U16 female basketball players participating in a micro-cycle with the U18 team from the same club. Methods: Twelve U16 and six U18 female basketball players completed two U18-team training sessions (MD-3 and MD-1; 90 min each). The internal load (heart rate metrics) and external load (accelerations, decelerations, speed, and distance) were measured using Polar Team Pro sensors. Differences between groups were analyzed using t-tests and Cohen’s d effect sizes. Results: No significant differences (p > 0.05) were found between age categories for either the internal or external load variables. U16 players showed slightly higher maximum heart rate percentages (96.5% vs. 94.7%, ES = 0.29) but similar average heart rate and time in heart rate zones. For the external load, both groups exhibited comparable values in total distance, average speed, and movement across speed and acceleration/deceleration zones. Effect sizes were mostly small, with moderate differences found in specific acceleration and deceleration zones. Conclusions: U16 players training with the U18 team experienced similar internal and external loads, suggesting that they can cope with the physical and physiological demands of older-age-group training. These findings support the inclusion of younger players in higher-age-group training environments as part of their long-term athletic development. Full article

The research aims to propose a basic parameter estimation method for high-speed vertical take-off and landing (HSVTOL) aircraft, balancing rotor and fixed-wing mode requirements. Flight profiles and performance indicators are defined based on mission phases, and maximum take-off weight is estimated using the fuel fraction method. A pre-estimation model for a turboshaft–turbofan variable cycle engine (TSFVCE) was established, and the conversion between thrust and power was conducted. Constraints related to different performance requirements were analyzed, and the relationship between the rotor and the wing was established, resulting in the generation of constraint diagrams for the selection of basic parameters. This method allows for the rapid and effective estimation of basic parameters, including maximum take-off weight, rotor disk loading, and wing loading. Two tiltrotor aircraft were analyzed using this method. The estimated results closely matched actual values, with errors within a reasonable range. These findings demonstrate the method’s reliability and provide a reference for HSVTOL conceptual design and engine power matching. Full article

This study investigates the influence of laser processing parameters on the surface roughness and color formation of AISI 304 stainless steel. Experiments were conducted to explore how raster step, scanning speed, frequency, linear energy density, and overlap coefficient affect the surface characteristics of laser-marked zones. It was found that increasing the raster step from 20 µm to 80 µm led to a consistent increase in surface roughness (from 1.23 µm to 1.47 µm at 20 kHz and 25 mm/s), accompanied by a shift in color from dark brown to lighter yellow hues. In contrast, increasing scanning speed (from 25 mm/s to 125 mm/s) caused a nonlinear reduction in roughness (e.g., from 1.23 µm to 0.76 µm at 20 kHz and Δx = 20 µm), resulting in a lighter surface color. Frequency was identified as a critical factor; increasing it from 20 kHz to 100 kHz resulted in a threefold decrease in roughness (from 1.23 µm to 0.25 µm at 20 µm raster step and 125 mm/s), which correlated with a shift to brighter yellow tones. Higher linear energy density values (1.60–8.00 J/cm) increased roughness and darkened the surface color, while higher overlap coefficients produced the opposite trend. The study highlights the relationship between surface nanostructuring and the formation of stable interference colors, providing quantitative parameters for achieving desired chromatic effects. These findings establish a basis for the industrial application of laser color marking, where both aesthetic differentiation and functional enhancements—such as corrosion resistance, hydrophobicity, and antibacterial properties—are essential. Future research will focus on quantitatively evaluating the functional properties, including corrosion resistance, hydrophobicity, and durability, of the colored surfaces produced under optimized parameters. This research aims to further develop laser marking as a foundational tool for both aesthetic and functional surface engineering. Full article

Global road safety reports identify human factors as the leading causes of traffic accidents, particularly behaviors such as speeding, drunk driving, and driver distraction, emphasizing the need for autonomous driving technologies to enhance transport safety. This research aims to provide a practical model for the development of autonomous driving systems as part of an autonomous transportation system for inter-building passenger mobility, intended to enable safe and efficient short-distance transport between buildings in semi-open environments such as university campuses. This work presents a fully integrated autonomous platform combining LiDAR, cameras, and IMU sensors for mapping, perception, localization, and control within a drive-by-wire framework, achieving superior coordination in driving, braking, and obstacle avoidance and validated under real campus conditions. The electric golf cart prototype achieved centimeter-level mapping accuracy (0.32 m), precise localization (0.08 m), and 2D object detection with an mAP value exceeding 70%, demonstrating accurate perception and positioning under real-world conditions. These results confirm its reliable performance and suitability for practical autonomous operation. Field tests showed that the vehicle maintained appropriate speeds and path curvature while performing effective obstacle avoidance. The findings highlight the system’s potential to improve safety and reliability in short-distance autonomous mobility while supporting scalable smart mobility development. Full article

In the present experiment, the abrasive water jet machining parameters, such as water pressure, standoff distance, and traverse speed, are selected to study the effect of each parameter on the kerf taper angle and surface roughness during the machining of glass, jute, and carbon hybrid composite. The other machining parameters are kept constant. For each parameter, three levels are fixed on the basis of previous literature reviews. The Response Surface Methodology is used to design the required number of experiments and to optimize the machining parameters to obtain the minimum kerf taper angle and surface roughness. The levels selected for water pressure are 150, 220, and 250 MPa; traverse speeds are 20, 40, and 60 mm/min; and, similarly, stand-off distances are 2, 5, and 8 mm. Experimental results confirm that the parameter inversely affects both kerf angle and surface roughness. On the other hand, parameters traverse speed and stand-off distance, directly affecting both outputs. According to RSM optimization, to obtain the minimum kerf taper angle and surface roughness, we should fix the pressure at a higher level and other parameters at a lower level. For the considered range, the obtained minimum kerf angle and roughness values are 1.4982 radians and 2.0920 μm. Full article

The operational phase of offshore wind farms, lasting up to 20–25 years, exceeds the construction phase in duration. The ecological effects of underwater noise demand serious consideration, necessitating urgent research into its acoustic characteristics. This review conducts a systematic analysis of measurements of underwater noise from operational offshore wind farms, considering the correlations between turbine noise and distance, wind speed, turbine power, and foundation type. Propagation distance is the most critical factor influencing the underwater sound pressure level (SPL) of wind turbines, exhibiting a negative correlation with the SPL, with an attenuation of approximately 20.4 dB/decade. In contrast, wind speed and turbine power show a positive correlation with the SPL, with increase rates of 18.5 dB/decade and 12.4 dB/decade, respectively. Further analysis shows that foundation type and drive technology also have a significant impact on underwater SPL. With technological innovation, specifically the upgrade from conventional geared drive to direct-drive technology, the level of underwater noise can be reduced by approximately 9 dB, with the primary peak frequency being shifted to a lower range. Moreover, significant variations in SPLs were noted with the utilization of various types of foundation structures, with monopile foundations exhibiting the highest SPLs of underwater noise. These conclusions have important reference value for the scientific assessment of the health of aquatic organisms and ecosystems. Full article

Objectives: The present study was conducted to examine the effects of a one-year multicomponent exercise training (MCET) program on the physical function and cardiovascular risk factors of community-dwelling older adults at risk of sarcopenic obesity. Methods: Data of 78 Brazilian community-dwelling older adults at risk of sarcopenic obesity, identified as the simultaneous presence of probable sarcopenia and overweight, were examined. The MCET program was performed twice a week over one year. Physical performance evaluations included (i) a timed “up-and-go” (TUG), (ii) one-leg stand, (iii) walking speed (WS) at normal pace and fast pace, (iv) a 5-time sit-to-stand (5STS) test, and (v) isometric handgrip strength (IHG). Cardiovascular risk factors involved blood pressure (BP) values and waist-to-hip ratio. Results: Significant improvements in balance and WS at a normal pace were observed following the MCET program, while no changes were noted in other physical performance markers. Additionally, a significant reduction in diastolic BP was recorded. Conclusions: Findings indicated significant improvements in mobility and balance, as well as a notable reduction in diastolic BP, among community-dwelling older adults at risk of sarcopenic obesity following a one-year MCET program. These improvements may play a critical role in reducing the risk of adverse outcomes such as falls, disability, cardiovascular events, hospitalization, and mortality. However, the quasi-experimental design of the present study, the absence of a control group, and other methodological limitations restrict the generalizability of the results. Future research using more rigorous study designs is necessary to confirm and expand upon these findings. Full article

This paper addresses the long-standing question of understanding the origin and evolution of low-frequency unsteadiness interactions associated with shock waves impinging on a turbulent boundary layer in transonic flow (Mach: $1.1$ to $1.3$). To that end, high-speed experiments in a blowdown open-channel wind tunnel have been performed across a convergent–divergent nozzle for different expansion ratios (PR = 1.44, 1.6, and 1.81). Quantitative evaluation of the underlying spectral energy content has been obtained by processing time-resolved pressure transducer data and Schlieren images using the following spectral analysis methods: Fast Fourier Transform (FFT), Continuous Wavelet Transform (CWT), as well as coherence and time-lag evaluations. The images demonstrated the presence of increased normal shock-wave impact for PR = 1.44, whereas the latter were linked with increased oblique $\lambda$-foot impact. Hence, significant disparities associated with the overall stability, location, and amplitude of the shock waves, as well as quantitative assertions related to spectral energy segregation, have been inferred. A subsequent detailed spectral analysis revealed the presence of multiple discrete frequency peaks (magnitude and frequency of the peaks increasing with PR), with the lower peaks linked with large-scale shock-wave interactions and higher peaks associated with shear-layer instabilities and turbulence. Wavelet transform using the Morlet function illustrates the presence of varying intermittency, modulation in the temporal and frequency scales for different spectral events, and a pseudo-periodic spectral energy pulsation alternating between two frequency-specific events. Spectral analysis of the pixel densities related to different regions, called spatial FFT, highlights the increased influence of the feedback mechanism and coupled turbulence interactions for higher PR. Collation of the subsequent coherence analysis with the previous results underscores that lower PR is linked with shock-separation dynamics being tightly coupled, whereas at higher PR values, global instabilities, vortex shedding, and high-frequency shear-layer effects govern the overall interactions, redistributing the spectral energy across a wider spectral range. Complementing these experiments, time-resolved numerical simulations based on a transient 3D RANS framework were performed. The simulations successfully reproduced the main features of the shock motion, including the downstream migration of the mean position, the reduction in oscillation amplitude with increasing PR, and the division of the spectra into distinct frequency regions. This confirms that the adopted 3D RANS approach provides a suitable predictive framework for capturing the essential unsteady dynamics of shock–boundary layer interactions across both temporal and spatial scales. This novel combination of synchronized Schlieren imaging with pressure transducer data, followed by application of advanced spectral analysis techniques, FFT, CWT, spatial FFT, coherence analysis, and numerical evaluations, linked image-derived propagation and coherence results directly to wall pressure dynamics, providing critical insights into how PR variation governs the spectral energy content and shock-wave oscillation behavior for nozzles. Thus, for low PR flows dominated by normal shock structure, global instability of the separation zone governs the overall oscillations, whereas higher PR, linked with dominant $\lambda$-foot structure, demonstrates increased feedback from the shear-layer oscillations, separation region breathing, as well as global instabilities. It is envisaged that epistemic understanding related to the spectral dynamics of low-frequency oscillations at different PR values derived from this study could be useful for future nozzle design modifications aimed at achieving optimal nozzle performance. The study could further assist the implementation of appropriate flow control strategies to alleviate these instabilities and improve thrust performance. Full article

Many problems in science, engineering, and economics require solving of nonlinear equations, often arising from attempts to model natural systems and predict their behavior. In this context, iterative methods provide an effective approach to approximate the roots of nonlinear functions. This work introduces five new parametric families of multipoint iterative methods specifically designed for solving nonlinear equations. Each family is built upon a two-step scheme: the first step applies the classical Newton method, while the second incorporates a convex mean, a weight function, and a frozen derivative (i.e., the same derivative from the previous step). The careful design of the weight function was essential to ensure fourth-order convergence while allowing arbitrary parameter values. The proposed methods are theoretically analyzed and dynamically characterized using tools such as stability surfaces, parameter planes, and dynamical planes on the Riemann sphere. These analyses reveal regions of stability and divergence, helping identify suitable parameter values that guarantee convergence to the root. Moreover, a general result proves that all the proposed optimal parametric families of iterative methods are topologically equivalent, under conjugation. Numerical experiments confirm the robustness and efficiency of the methods, often surpassing classical approaches in terms of convergence speed and accuracy. Overall, the results demonstrate that convex-mean-based parametric methods offer a flexible and stable framework for the reliable numerical solution of nonlinear equations. Full article

With the acceleration of urbanization, environmental degradation is increasingly restricting the improvement of residents’ quality of life, and promoting the transformation of old communities has become a key path for sustainable urban development. However, existing buildings generally face challenges, such as the deterioration of the performance of the envelope structure and the rising energy consumption of the air conditioning system, which pose a serious test for the realization of green renovation. Inspired by the application of bionics in the field of architecture, this study innovatively designed five types of bionic envelope structures for outdoor air conditioning units, namely scales, honeycombs, spider webs, leaves, and bird nests, based on the aerodynamic characteristics of biological prototypes. The ventilation performance of these structures was evaluated at three scales—namely, single building, townhouse, and community—under natural ventilation conditions, using a CFD simulation system. The study shows the following: (1) the spider web structure has the best comprehensive performance among all types of enclosures, which can significantly improve the uniformity of the flow field and effectively eliminate the low-speed stagnation area on the windward side; (2) the structure reorganizes the flow structure of the near-wall area through the cutting and diversion of the porous grid, reduces the wake range, and weakens the negative pressure intensity, making the pressure distribution around the building more balanced; (3) in the height range of 1.5–27 m, the spider web structure performs particularly well at the townhouse and community scales, with an average wind speed increase of 1.1–1.4%; and (4) the design takes into account both the safety of the enclosure and the comfort of the pedestrian area, achieving a synergistic optimization of function and performance. This study provides new ideas for the micro-renewal of buildings, based on bionic principles, and has theoretical and practical value for improving the wind environment quality of old communities and promoting low-carbon urban development. Full article

To compare lower limb joint angle variability between functional ankle instability (FAI) and healthy controls (CONs) at different running speeds using linear and nonlinear methods. Fifteen males with right-side FAI and fifteen matched CONs ran on a treadmill at self-selected, 20% faster, and 20% slower speeds. From 25 gait cycles, the mean coefficient of variation (CV), Sample Entropy (SampEn), and largest Lyapunov Exponent (LyE) of hip, knee, and ankle angles were computed. A two-way (two groups × three speeds) mixed-design ANOVA was applied (α = 0.05). No significant interaction effects were observed. No significant differences were observed in the CV. SampEn showed group effects: FAI had lower values in hip horizontal, knee sagittal/coronal, and ankle coronal planes, but higher in the hip sagittal plane. Speed effects showed greater SampEn in the ankle sagittal and lower in the hip coronal plane at slow speed. LyE was reduced in FAI for hip, knee, and ankle sagittal planes. Speed effects indicated higher LyE in the knee sagittal and lower in the hip coronal plane at slow speed. FAI showed reduced variability, particularly in the sagittal plane, reflecting rigid control. Slower speeds increased ankle and knee sagittal variability but decreased hip coronal variability. Full article

Background: This study investigates the precision of an inertial measurement unit (IMU) in evaluating the Finger Tapping Test (FTT) to differentiate motor control competencies in women with fibromyalgia, a clinical population characterized by motor impairments. Methods: The sample consisted of 240 FTT trials collected from 20 women, half of whom were diagnosed with fibromyalgia (F = 46.4 ± 12.714; C = 45.9 ± 12.950). Procedures consisted of participants completing FTT while data were collected from a high-speed camera and an IMU for linear acceleration and angular velocity, respectively. Analyses employed the Bland–Altman technique with both parametric and bootstrap-derived limits of agreement and intraclass correlation coefficients to assess levels of agreement between traditional and IMU-derived methods. Results: The results showed a strong agreement at subject×hand aggregation for the number of taps (RPC = 4.3 and ICC = 0.94) and for the inter-tap interval (RPC = 0.02 and ICC = 0.89), indicating minimal differences between measurements and demonstrating the potential for highly sensitive motor function assessment using an IMU. Conclusions: These findings suggest that IMU technology can effectively detect subtle aspects of motor control, supporting its use in exercise, rehabilitation, and clinical physiotherapy settings, including functional training, adapted rehabilitation exercises, and home-based monitoring for fibromyalgia. This approach offers detailed insights into subtle motor impairments, emphasizing its value for both clinical and exercise applications. Full article

The precise prediction of high-speed railway bridge pier settlement plays a crucial role in construction, maintenance, and long-term operation; however, current mainstream prediction methods mostly rely on independent analyses based on traditional or hybrid models, neglecting the impact of geological and environmental factors on subsidence. To address this issue, this paper proposes a multi-factor settlement prediction model for high-speed railway bridge piers named the Reversible Instance Normalization Multi-Scale Adaptive Resolution Stream CMamba, abbreviated as RMCMamba. During the data preprocessing process, the Enhanced PS-InSAR technology is adopted to obtain the time series data of land settlement in the study region. Utilizing the cubic improved Hermite interpolation method to fill the missing values of monitoring and considering the environmental parameters such as groundwater level, temperature, precipitation, etc., a multi-factor high-speed railway bridge pier settlement dataset is constructed. RMCMamba fuses the reversible instance normalization (RevIN) and the multiresolution forecasting head (MARSHead), enhancing the model’s long-range dependence capture capability and solving the time series data distribution drift problem. Experimental results demonstrate that in the multi-factor prediction scenario, RMCMamba achieves an MAE of 0.049 mm and an RMSE of 0.077 mm; in the single-factor prediction scenario, the proposed method reduces errors compared to traditional prediction approaches and other deep learning-based methods, with MAE values improving by 4.8% and 4.4% over the suboptimal method in multi-factor and single-factor scenarios, respectively. Ablation experiments further verify the collaborative advantages of combining reversible instance normalization and the multi-resolution forecasting head, as RMCMamba’s MAE values improve by 5.8% and 4.4% compared to the original model in multi-factor and single-factor scenarios. Hence, the proposed method effectively enhances the prediction accuracy of high-speed railway bridge pier settlement, and the constructed multi-source data fusion framework, along with the model improvement strategy, provides technological and experiential references for relevant fields. Full article