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Applied Sciences, Volume 13; https://doi.org/10.3390/app13031969
A multitarget search algorithm for a robot swarm in an unknown 3D mountain environment is proposed. Most existing 3D environment obstacle avoidance algorithms are potential field methods, which need to consider the location information of all obstacles around the robot, and they easily fall into local optima, and their calculation is complex. Furthermore, they cannot well meet the requirements of real-time obstacle avoidance characteristics of swarm robots in multiobject searches. This paper first focuses on solving the obstacle avoidance problem of swarm robots in mountain environments. A new 3D curved obstacle tracking algorithm (3D-COTA) is designed by discretizing the mountains within the detection range of robot obstacles. Then, a task assignment model and virtual force model in 2D space are extended to 3D, and a particle swarm search model with kinematic constraints is constructed, which considers the kinematic constraints and the limitations of the communication ability of the robots. Finally, a new multitarget search algorithm for a robot swarm in an unknown 3D mountain environment is proposed by means of the designed 3D surface obstacle tracking algorithm. Numerical simulation results demonstrate the effectiveness of the proposed algorithm.
Applied Sciences, Volume 13; https://doi.org/10.3390/app13031970
Abnormal sensory perception is among the earliest symptoms of autism spectrum disorders (ASD). Despite mixed findings, olfactory perception seems to be altered in ASD. There is also evidence that automatic responses to odours can serve as biomarkers of ASD. However, this potential use of odour-based biomarkers for ASD is still underexplored. In this study, we aimed to investigate whether physiological responses to social and non-social odours, measured with electrocardiography (ECG) and facial electromyography (EMG), can be used to characterise and predict ASD in adults. For that, we extracted 32 signal features from a previously collected database of 11 adults with ASD and 48 adults with typical development (TD). Firstly, non-parametric tests were performed, showing significant differences between the ASD and the TD groups in 10 features. Secondly, a k-nearest-neighbour classifier with a leave-one-out strategy was employed, obtaining an F1-score of 67%. Although caution is needed due to the small sample size, this study provides preliminary evidence supporting the use of physiological responses to social and non-social odours as a potential diagnostic tool for ASD in adults.
Applied Sciences, Volume 13; https://doi.org/10.3390/app13031967
The paper presents a sufficiently simple technique for designing a low-energy flight trajectory of a spacecraft (SC) from the Earth to the Moon with insertion into a low circular orbit of the latter. The proposed technique is based on the solution and subsequent analysis of a special model problem, which is a variant of the restricted circular four-body problem (RC4BP) Earth-Sun-SC-Moon; for which it is assumed that the planes of the orbits of all considered bodies coincides. The planar motion of the center of mass of the SC relative to the Earth is considered as perturbed (Sun, Moon). To describe it, equations in osculating elements are used, obtained by using the method of variation of constants based on the analytical solution of the planar circular restricted problem of two bodies (RC2BP)—Earth-SC, for which the rotation of the main axes of the coordinate system (the main plane) is synchronized with the motion of the Sun. The trajectory problem of designing a SC flight from a low circular near-Earth orbit to a low circular selenocentric one (“full” motion model—a restricted four-body problem (R4BP), an ephemeris model) is considered as an optimization one in the impulse formulation. The solution of the main problem is carried out in few (three) stages, on each the appropriate solution of the current variant of the auxiliary problem is determined, which is subsequently used as the basis of the initial approximation to the main one.
Applied Sciences, Volume 13; https://doi.org/10.3390/app13031968
Accurate expression interpretation occupies a huge proportion of human-to-human communication. The control of expressions can facilitate more convenient communication between people. Expression recognition technology has also been transformed from relatively mature laboratory-controlled research to natural scenes research. In this paper, we design a multi-channel attention network based on channel weighting for expression analysis in natural scenes. The network mainly consists of three parts: Multi-branch expression recognition feature extraction network, which combines residual network ResNet18 and ConvNeXt network ideas to improve feature extraction and uses adaptive feature fusion to build a complete network; Adaptive Channel Weighting, which designs adaptive weights in the auxiliary network for feature extraction, performs channel weighting, and highlights key information areas; and Attention module, which designs and modifies the spatial attention mechanism and increases the proportion of feature information to accelerate the acquisition of important expression feature information areas. The experimental results show that the proposed method achieves better recognition efficiency than existing algorithms on the dataset FER2013 under uncontrolled conditions, reaching 73.81%, and also achieves good recognition accuracy of 89.65% and 85.24% on the Oulu_CASIA and RAF-DB datasets, respectively.
Applied Sciences, Volume 13; https://doi.org/10.3390/app13031966
The alloys that crystallize in a tetragonal ThMn12-type (space group I4/mmm) structure and are based on Fe and rare earth elements are believed to have a potential to plug the performance gap between ferrite and Nd-based magnets. Nevertheless, the progress is hindered by their poor structural stability, compared with other phases competing during the synthesis process, e.g., Th2Zn17-type. In this work, the enthalpies of the formation (and other thermodynamic parameters) of various phases in (Zr, Nd, Ce)-Fe-Si systems were calculated, with paramount focus on the Fe-rich compositions. We compared and discussed the stability range and stabilization routes for amorphous phases, solid solutions, and intermetallics. The beneficial influence of Zr and Si on the crystallization of intermetallic compounds was confirmed, simultaneously being valid for other phases. Among all of the analyzed Fe-rich phases, the lowest values for enthalpy of the formation of the amorphous phase and solid solution were determined for ZrFe10Si2 (−17.5 and −18.2 kJ/mol, respectively). Moreover, substitution by elements with a large atomic radius is indicated as a method for the introduction of topological disorder, giving possibility for the synthesis of metastable phases (even amorphous) and the utilization of more sophisticated synthesis routes in the future.
Applied Sciences, Volume 13; https://doi.org/10.3390/app13031960
In this study, the degradation of wood pellets and dry roasted coffee beans in a pneumatic conveyor was evaluated for high-speed impacts. The change in particle size and generation of fine particles were used as an indicating parameter for the degradation. A four-bends industrial scale conveying system was used for the degradation study in lean phase pneumatic conveying. The effects of operating parameters on the degradation were investigated, including the conveying velocity of particles and particle concentration. The experimental results showed that the degradation and the fines generation increased with an increase in particle velocity. An opposite trend was observed with an increased solid concentration in the pipeline. It was found that the two types of wood pellets traveled at different particle velocities with the same operating conditions, which resulted in significant differences in the degradation. Compared to the wood pellets, roasted coffee beans were found to travel at air velocity. In conclusion, the degradation in a pneumatic conveying system is complex and challenging to evaluate because there are many influential factors, such as the type of materials, equipment, and operation conditions. Early assessments in a laboratory will be beneficial to evaluate the degradation at all controlled operative conditions.
Applied Sciences, Volume 13; https://doi.org/10.3390/app13031965
In this study, we propose and analyze three designs of a novel aerial system that aims for autonomous firefighting missions in the body or border of water areas. In such areas, it is difficult and even dangerous for human firefighters, and firefighting robots, to approach and put out the fire. Thus, the systems proposed in this paper make use of the available water source not only for suppressing the fire, but also for propelling and maneuvering themselves. The three designs are different in their ways of actuating, namely flow rate control, nozzle rotation control, and weight distribution control. The designs are first introduced. Then, mathematical models are formulated and reveal the motion characteristics of each system. A linear control framework is developed and implemented for all of them. Simulation studies were conducted to verify their motion performance and subsequently, to select the best solution. The results indicate that the weight distribution control system struggled to follow the required reference while the two other designs both provided adequate maneuverability. The nozzle rotation control system is the better one, with greater tracking results of the head part and smaller fluctuations of the water hose.
Applied Sciences, Volume 13; https://doi.org/10.3390/app13031953
Lightweight aggregate concrete (LWAC) is an increasingly important material for modern construction. However, although it has several advantages compared with conventional concrete, it is susceptible to segregation due to the low density of the incorporated aggregate. The phenomenon of segregation can adversely affect the mechanical properties of LWAC, reducing its compressive strength and its durability. In this work, several machine learning techniques are used to study the influence of the segregation of LWAC on its compressive strength, including the K-nearest neighbours (KNN) algorithm, regression tree-based algorithms such as random forest (RF) and gradient boosting regressors (GBRs), artificial neural networks (ANNs) and support vector regression (SVR). In addition, a weighted average ensemble (WAE) method is proposed that combines RF, SVR and extreme GBR (or XGBoost). A dataset that was recently used for predicting the compressive strength of LWAC is employed in this experimental study. Two different types of lightweight aggregate (LWA), including expanded clay as a coarse aggregate and natural fine limestone aggregate, were mixed to produce LWAC. To quantify the segregation in LWAC, the ultrasonic pulse velocity method was adopted. Numerical experiments were carried out to analyse the behaviour of the obtained models, and a performance improvement was shown compared with the machine learning models reported in previous works. The best performance was obtained with GBR, XGBoost and the proposed weighted ensemble method. In addition, a good choice of weights in the WAE method allowed our approach to outperform all of the other models.
Applied Sciences, Volume 13; https://doi.org/10.3390/app13031964
Due to the effective guidance of prior information, feature map-based pruning methods have emerged as promising techniques for model compression. In the previous works, the undifferentiated treatment of all information on feature maps amplifies the negative impact of noise and background information. To address this issue, a novel filter pruning strategy called Filter Pruning via Attention Consistency (FPAC) is proposed, and a simple and effective implementation method of FPAC is presented. FPAC is inspired by the notion that the attention of feature maps on one layer is in high consistency of spatial dimension. The experiments also show that feature maps with lower consistency are less important. Hence, FPAC measures the importance of filters by evaluating the attention consistency on the feature maps and then prunes the filters corresponding to feature maps with lower consistency. The present experiments on various datasets further confirm the effectiveness of FPAC. For instance, applying VGG-16 on CIFAR-10, the classification accuracy even increases from 93.96% to 94.03% with 58.1% FLOPs reductions. Furthermore, applying ResNet-50 on ImageNet achieves 45% FLOPs reductions with only 0.53% accuracy loss.
Applied Sciences, Volume 13; https://doi.org/10.3390/app13031963
This article concerns the application of the FEM method for the prediction of stress and deformation states in the workpiece during diamond sliding burnishing (DSB). An updated Lagrange (UL) description was used to describe the phenomena at a typical incremental step. The states of strain and strain rate are described by non-linear relationships without linearization. The material parameters were estimated during tensile tests to determine the characteristics of the 41Cr4 steel. Its hardness was also tested. Its aim was to prepare a table with the material properties of the above-mentioned steel and its implementation for numerical analyses. A Cowper–Symonds material model was used to model the displacement process of the wedge on an elastic/visco-plastic body reflecting the DSB process. The computer model was validated, and a good convergence of the results was obtained. Applications in the ANSYS/LS-Dyna program were developed to simulate the process of DSB. The results of numerical analyses were presented, among others, to explain the influence of the rake angle on the condition of the surface after machining, as well as the phenomenon of chip formation. The results of numerical simulations were verified experimentally on a test stand.