Appl. Sci., Volume 14, Issue 3 (February-1 2024) – 371 articles

In this paper, we propose an Iterative Greedy-Universal Adversarial Perturbations (IGUAP) approach based on an iterative greedy algorithm to create universal adversarial perturbations for acoustic prints. A thorough, objective account of the IG-UAP method is provided, outlining its framework and approach. The method leverages a greedy iteration approach to formulate an optimization problem for solving acoustic universal adversarial perturbations, with a new objective function designed to ensure that the attack has higher accuracy in terms of minimizing the perceptibility of adversarial perturbations and increasing the accuracy of successful attacks. The perturbation generation process is described in detail, and the resulting acoustic universal adversarial perturbation is evaluated in both target-attack and no-target-attack scenarios. Experimental analysis and testing were carried out using comparable techniques and dissimilar target models. The findings reveal that the acoustic generality adversarial perturbation produced by the IG-UAP method can obtain effective attack results even when the audio training data sample size is minimal, i.e., one for each category. Moreover, the human ear finds it difficult to detect the loss of original data information and the addition of adversarial perturbation (for the case of a target attack, the ASR values range from 82.4% to 90.2% for the small sample data set). The success rates for untargeted and targeted attacks average 85.8% and 84.9%, respectively. Full article

A mathematical model for an electric field induced by an angularly oscillating magnetic dipole was proposed with magnetic vector potential to analyze the characteristics of the electric field induced by a rotating and angularly oscillating magnetic object. This mathematical model was constructed for the electric field induced by a magnetic object oscillating at a certain angle. On this basis, the phase relationship among the three components of the induced electric field was analyzed (defining the right-hand Cartesian coordinate system). Evidently, a phase difference of π/2 always existed between the horizontal components of the electric field induced by a magnetic dipole rotating around the z-axis. The phase difference between the vertical and transverse components in the x–z plane was also π/2. A phase difference of π was observed in the y–z plane. The above theoretical analysis was verified through simulation and experiment. The results showed that the frequency of the induced electric field was related to the angular velocity and angle of rotation. The amplitude was associated with the magnetic moment and the angular velocity and angle of oscillation. The maximum amplitude did not exceed the amplitude of the electric field induced by a magnetic object angularly oscillating at the same velocity. With regard to the amplitude and phase relationship, the three components of the induced electric field measured in the experiment were consistent with the results of the theoretical analysis. Full article

Cardiovascular diseases (CVDs) are chronic diseases associated with a high risk of mortality and morbidity. Early detection of CVD is crucial to initiating timely interventions, such as appropriate counseling and medication, which can effectively manage the condition and improve patient outcomes. This study introduces an innovative ontology-based model for the diagnosis of CVD, aimed at improving decision support systems in healthcare. We developed a database model inspired by ontology principles, tailored for the efficient processing and analysis of CVD-related data. Our model’s effectiveness is demonstrated through its integration into a web application, showcasing significant improvements in diagnostic accuracy and utility in resource-limited settings. Our findings indicate a promising direction for the application of artificial intelligence (AI) in early CVD detection and management, offering a scalable solution to healthcare challenges in diverse environments. Full article

The popularity of fog-enabled smart cities is increasing due to the advantages provided by modern communication and information technologies, which contribute to an improved quality of life. Wireless networks make them more vulnerable when the network is under malicious attacks that cause a collision in the medium. Furthermore, diverse applications of smart cities demand a contention-free medium access control (MAC) protocol to meet adaptive data requirements. In this work, a time-slot-based medium access control protocol to meet adaptive data requirements (TMPAD) for IoT nodes in fog-enabled smart cities is proposed. TMPAD proposes a trust mechanism to differentiate malicious and legitimate data requests. In addition, it accommodates more legitimate data-requesting nodes to transfer their data during a session by applying the technique for order performance by similarity to ideal solution (TOPSIS) and 0/1 knapsack algorithm. The performance of TMPAD is compared with well-known techniques such as first come first serve (FCFS), shortest job first (SJF), and longest job first (LJF) in different prospective scenarios. The results show that TMPAD scrutinizes more data-requesting nodes in slot allocation, allowing more data transmission in a session, with better mean trust value, as compared to other algorithms. Full article

Sunspot daily time series have been available for almost two centuries providing vast and complicated information about the behavior of our star and especially the interaction of the motion of the planets and other possible interstellar phenomena and their effects on the surface of the Sun. The main result obtained from the sunspot time series analysis is the imprint of various periodicities, such as the planets’ orbital periods and the planetary synodic periods on the sunspots signature. A detailed spectrum representation is achieved by means of a periodogram and a virtual extension of the time length segments with zeroed samples for longer representations. Furthermore, the dependence or coupling of these periodicities is explored by means of a bispectrum. We establish the exact interdependencies of the periodic phenomena on the sunspot time series. Specific couplings are explored that are proved to be the key issues for the coupled periodicities on the sunspot time series. In this work, contrary to what has been presented in the literature, all periodic phenomena are limited within the time period of an 11-year cycle as well as the periodicities of the orbits of the planets. The main findings are the observed strong coupling of the Mercury, Venus, and Mars periodicities, as well as synodic periodicities with all other periodicities that appear on the sunspot series. Simultaneously, the rotation of the Sun around itself (25.6 to 33.5 days) provides an extensive coupling of all recorded periodicities. Finally, there is strong evidence of the existence of a quadratic mechanism, which couples all the recorded periodicities, but in such a way that only frequency pairs that sum up to specific periods are coupled. The justification for this kind of coupling is left open to the scientific community. Full article

This study was conducted on vegetable soup with rabbit meat and vegetable soup with rabbit meat, beef balls, and carrots. The qualitative characteristics of the soups were adapted to the needs of elderly consumers. The soups used in the experiments were industrially produced. The aim of this study was to analyse changes in the mechanical, sensory, and microbiological properties of the soups occurring during their storage (1, 7, 14, and 21 days). Strength tests were performed at temperatures of 20 °C and 55 °C. Both soups had a high protein content (4.7–6.5%), low sugar (0.3–0.5%) and salt content (0.8%), and a fibre content of 1.4%. The texture analysis showed great similarity in the mechanical characteristics of both soups. The samples were characterised by low measured values for firmness (0.72 N) and cohesiveness (−0.14 N) in both temperatures. The average shear force of the beef balls with carrots at 20 °C was 12.3 N, but after heating, it decreased to 8.8 N (p < 0.05). The rheological tests on the soups showed that they were characterised by a relatively high viscosity (15–20 Pas at 55 °C). Storage of the soups for 21 days did not significantly affect their rheological parameters (p > 0.05). The soup with beef balls and carrots was rated higher by the sensory panel. On the 21st day of storage, the permitted limit of the count of bacteria was not exceeded in either of the samples. This study shows that the soups had desirable structural, nutritional, and sensory characteristics, which are important for this group of consumers. The values of the mechanical parameters of all the samples were low, and they were even significantly more reduced when the products were heated. This may suggest that the products should not be difficult to consume for seniors. Full article

Metalenses, with their unique modulation of light, are in great demand for many potential applications. As a proof-of-principle demonstration, we focus on designing SiO₂ metalenses that operate in the deep ultraviolet region, specifically around 193 nm. Based on the deep ultraviolet metalens proposed in this paper, an integrated deep ultraviolet doublet metalens is further offered. When the incident light is a plane wave with a wavelength of 193 nm, the integrated doublet metalens can reduce the beam size by a factor of 4:1, and the emitted light is flat. The integrated doublet metalens can project the reticle image proportionally, making the projection image clear. The integrated doublet metalens has the best imaging effect at the propagation distance of 2 μm and can tolerate ±3 degrees of incident angle deviation. Our findings establish general and systematic strategies to guide the design of traditional optical lens arrays with excellent integrated doublet metalenses and pave the way for enhanced optical performance in the application of large-relative-aperture deep ultraviolet detection, deep ultraviolet microscope systems, laser beam combining systems, deep ultraviolet lithography systems, etc. Full article

Coffee chains are very popular around the world. Because overly worn coffee grinder burrs can downgrade the taste of coffee, coffee experts and professional cuppers in an anonymous coffee chain have developed a manual method to classify coffee grinder burr wear so that worn burrs can be replaced in time to maintain the good taste of coffee. In this paper, a remote access server system that can mimic the ability of those recognized coffee experts and professional cuppers to classify coffee grinder burr wear has been developed. Users only need to first upload a photo of coffee granules ground by a grinder to the system through a chatbot interface; then, they can receive the burr wear classification result from the remote server in a minute. The system first uses image processing to obtain the coffee granules’ size distribution. Based on the size distributions, unified length data inputs are then obtained to train and test the deep learning model so that it can classify the burr wear level into initial wear, normal wear, and severe wear with more than 96% accuracy. As only a mobile phone is needed to use this service, the proposed system is very suitable for both coffee chains and coffee lovers. Full article

Aim: The objective of this systematic review was to offer quantitative evidence regarding the influence of surface properties on the mechanical stability of miniscrews. Materials and Methods: The comprehensive search strategy involved querying databases, namely PubMed, Web of Science, and Scopus. PRISMA guidelines were followed to determine relevant studies according to specific eligibility criteria. The final search was conducted on 30 August 2023. In this systematic review, in vivo studies published in the English language were included. Results: A total of 364 articles were viewed, and 17 of them were considered for evaluation. Two of the articles are about human studies, while the rest are about animal studies. The number of miniscrew samples ranged between 18 and 144 (totaling 1097 with a mean of 64.52). Among the surface modifications in the articles, the sandblasting with large grit and acid etching (SLA) method was most frequently applied, followed by acid etching in second place. The control groups’ (machined surface) maximum removal torque (MRT) values varied from 2.05 to 50.50 Ncm, while maximum insertion torque (MIT) values varied from 7.23 to 19.25 Ncm. Conclusions: The development of novel applications to improve the surface properties and survival rates of miniscrews is ongoing. In future studies, emerging surface modifications should be evaluated clinically, taking into account their cost and associated harm to the environment. Full article

Conventional subsoiling has the problem of excessive draught resistance, which has long been a major concern. A great reduction in draught is urgently required to make better use of the subsoiling technique with many agronomic benefits. In this study, an attempt was made to test the draught reduction performance of a series of tools with continuous belt motions. Comparative simulations between regular tools and belt tools were carried out using the discrete element method (DEM) to investigate the effects of belt motion on tool force, soil disturbance characteristics, particle velocity distribution, and soil deformation and movement patterns. The results indicated that the belt motion reduced the draught force by 13.18%, 25.21%, 37.98%, and 44.64% for the rake angles of 30°, 45°, 60°, and 75°, respectively, and caused acceptable increases in downward vertical force. The changes in soil disturbance, particle velocity distribution, and soil deformation and movement patterns contributed to the reduction in draught force. Negative effects on soil disturbance were acceptable considering the 13.18% to 44.64% reductions in draught force. The present study suggests that the belt motion has a great application potential for draught reduction in subsoiling. Also, this can serve as a theoretical foundation for future studies. Full article

In the port domain, quayside container cranes are an indispensable component of maritime freight transport. These cranes are not only costly but also associated with safety accidents that often result in casualties and property loss, severely impacting port operations and the surrounding environment. Given their complex operational environment, rapid technological updates, high dependency on human factors, and the challenges of maintenance and inspection, the safety of quayside container cranes is a significant concern for port enterprises and managers. This paper, based on the operational modes and structural characteristics of the cranes, divides them into five main systems and identifies twenty-eight safety evaluation indicators, covering a comprehensive range of risk factors from equipment integrity to operator behavior, as well as environmental factors. However, numerous pain points exist in the safety risk evaluation process of quayside container cranes, such as fuzziness, uncertainty, and complex multi-criteria decision-making (MCDM) environments. These issues make traditional safety evaluation methods inadequate in accurately reflecting the actual safety conditions. Therefore, this paper proposes a safety evaluation method for quayside container cranes based on the Best–Worst Method (BWM) and Pythagorean hesitant fuzzy VIKOR. This method effectively overcomes the uncertainties and fuzziness of traditional safety evaluation methods by integrating the decision maker’s preference information from the BWM and the fuzzy handling capability of Pythagorean hesitant fuzzy sets, enhancing the accuracy and reliability of the evaluation results. A case study was conducted on a quayside container crane at a specific port. Through empirical analysis, the feasibility of the proposed method was validated. Overall, the safety evaluation method for quayside container cranes based on the BWM and Pythagorean hesitant fuzzy VIKOR proposed in this paper enriches the theoretical research on the safety risk assessment of quayside container cranes and offers a new approach and tool for port enterprises and managers in practice. Full article

This paper explores the synchronization and implementation of a novel hyperchaotic system using an adaptive observer. Hyperchaotic systems, known for possessing a greater number of positive Lyapunov exponents compared to chaotic systems, present unique challenges and opportunities in control and synchronization. In this study, we introduce a novel hyperchaotic system, thoroughly examining its dynamic properties and conducting a comprehensive phase space analysis. The proposed hyperchaotic system undergoes validation through circuit simulation to confirm its behavior. Introducing an adaptive observer synchronization technique, we successfully synchronize the dynamics of the novel hyperchaotic system with an identical counterpart. Importantly, we extend the application of this synchronization method to the domain of secure communication, showcasing its practical usage. Simulation outcomes validate the effectiveness of our methodology, demonstrating favorable results in the realm of adaptive observer-based synchronization. This research contributes significantly to the understanding and application of hyperchaotic systems, offering insights into both the theoretical aspects and practical implementation. Our findings suggest potential advancements in the field of chaotic systems, particularly in their applications within secure communication systems. By presenting motivations, methods, results, conclusions and the significance of our work in a more appealing manner, we aim to engage readers and highlight the innovative contributions of this study. Full article

As the frequency and intensity of natural and social disasters increase due to climate change, damage caused by disasters affects urban areas and facilities. Of those disasters, inundation occurs in urban areas due to rising water surface elevation because of concentrated rainfall from storm surges or urban drainage system failures. For this research, a scenario generation method for estimating flood inundation was developed to analyze the flood effects on urban areas to prepare for disasters and minimize damage. A scenario generation method using various distribution functions and return periods was developed and applied to create input values for the flow model for inundation analysis. By simulating multiple scenarios using a two-dimensional flow model and storing its results into a graph-form database called an inundation graph, it is possible to assess the probability and potential impact of different flood events quickly, which could be later used for disaster response and prevention. The flood risk and flood vulnerability of each section of the urban area could be evaluated based on the input data from the scenarios and the results of the flood analysis. Full article

Aiming to solve the problems of the large harvesting loss and low harvesting efficiency of wide- and narrow-row corn harvesting header in China, a method for the side installation of a header is proposed. A wide–narrow-row corn harvesting header with high working efficiency and low harvesting loss was designed. The collision energy balance equation of corn ears was established. The analysis shows that the kinetic energy change before and after the collision between the ear and the picking plate is the main cause of the shedding of and damage to corn kernels. Based on this, the main structural parameters of the corn harvesting header were designed. Based on the principle of Box–Behnken test, the response surface test was designed. The effects of the plant feeding speed, feeding angle, and rotation speed of a stem pulling roller on harvesting performance were analyzed. The best combination of working parameters was determined: The plant feeding speed was 1.08 m/s, the feeding angle was 52.46°, and the rotation speed of the stem pulling roller was 835.25 r/min. At this time, the grain damage rate was 1.09% and the grain loss rate was 0.14%. The corresponding parameters are verified by experiments. The results show that the grain damage rate was 1.12% and the grain loss rate was 0.14%. The optimization results are essentially consistent with the verification results, which meet the requirements of corn harvesting performance. Full article

The direct ink writing (DIW) process, used for creating components with functionally graded materials, holds significant promise for advancement in various advanced fields. However, challenges persist in achieving complex gradient variations in small-sized parts. In this study, we have developed a customized pin shape for an active screw mixer using a combination of quadratic B-Spline, the response surface method, and global optimization. This tailored pin design was implemented in a two-material extrusion-based printing system. The primary objective is to facilitate the transformation of material components with shorter transition distances, overcoming size constraints and enhancing both printing flexibility and resolution. Moreover, we characterized the transition delay time for material component changes and the mixing uniformity of the extruded material by constructing a finite element simulation model based on computational fluid dynamics. Additionally, we employed a particle tracking method to obtain the Lyapunov exponent and Poincaré map of the mixing process. We employed these metrics to represent and compare the degree of chaotic mixing and dispersive mixing ability with two other structurally similar mixers. It was found that the optimized pin-type mixer can reduce the transition delay distance by approximately 30% compared to similar structures. Finally, comparative experiments were carried out to verify the printing performance of the optimized pin-type active mixer and the accuracy of the finite element model. Full article

Regional oxygen saturation (rSO₂) assessed by near-infrared spectroscopy (NIRS) reflects the perfusion and metabolism of the assessed tissue. The study aimed to determine the reference values of rSO₂ for selected body areas, considering gender, age and body composition. We studied 70 healthy volunteers divided into two age groups (18–30 and >60 years). The rSO₂ was measured using NIRS in eighteen selected regions of interest (ROIs). Body composition analysis was carried out using dual-energy X-ray absorptiometry (DXA). Significant differences in rSO₂ values were found between almost all analyzed ROIs (p < 0.05) with a simultaneous lack of asymmetry between contralateral side of the body. The average rSO₂ values from the ROIs analyzed ranged from 40.34 ± 17.65% (Achilles tendon) to 69.94 ± 6.93% (tibialis anterior muscle). Age and the values of adiposity indices and the fat mass content are factors that may significantly reduce the rSO₂ value. In most ROIs, higher rSO₂ values were recorded for the younger group (p < 0.0001). The rSO₂ values at rest are area-specific in young and elderly healthy subjects. The changes in rSO₂, both in clinical assessment and research, should be interpreted taking into account the body area being assessed and individual factors such as age and body fat content. Full article

Airport arrival and departure movements are characterized by high dynamism, stochasticity, and uncertainty. Therefore, it is of paramount importance to predict and analyze surface taxi time accurately and scientifically. This paper conducts a comprehensive review of existing studies on surface taxi time prediction and analysis. Firstly, the overall research framework of surface taxi time prediction and analysis is categorized from three perspectives: taxi time type, movement type, and modeling method. Then, focusing on the two means of taxi time analytical modeling and simulation modeling, the existing mainstream models and methods are categorized, and the main ideas and scope of application of the various methods are analyzed. Finally, the paper presents the future development direction of surface taxi time prediction prospects. The research results are aimed at providing basic support and methodological guidance for reducing the uncertainty in airport surface operation and enhancing the level of control and decision-making ability of airport surface operation. Full article

A system has been developed to remotely, continuously, and quantitatively measure the physiological activity of trees. The developed tree physiological activity monitoring (TPAM) system is equipped with electrical impedance, temperature, and light intensity measurement functions. In the two-contact impedance measurement method used in the previous plant impedance measurement, errors due to the polarization impedance of the electrodes could not be avoided. The developed TPAM system adopted a four-contact measurement method that could avoid polarization impedance errors, and, with it, the long-term monitoring of zelkova trees was performed. The monitoring of seasonal changes was conducted from July to November, and an impedance change pattern that repeated on a daily basis was observed in the short term, and an overall increase in the impedance was observed in the long term. Impedance changes related to daily temperature changes were observed even after all the tree leaves had fallen, meaning that this effect should be excluded when using impedance to evaluate tree vitality. For this reason, the influence of temperature fluctuations was excluded by using only the impedance values at the same daily temperature of 25 degrees from July to November. The analysis results at 25 degrees showed that the tree impedance value increased linearly by 8.7 Ω per day. The results of this series of long-term monitoring and analysis revealed that the ambient temperature must be taken into account in the evaluation of tree physiological activity based on electrical impedance. Full article

The torsional stiffness parameter significantly influences the natural frequency of a leaf spring torsional vibration damper and its proper match with a diesel engine, and the nonlinear characteristics of torsional stiffness avoid reduced reliability due to the excessive torsion angle of the damper. An efficient mechanical model for the damper with nonlinear characteristics is established by integrating the Euler–Bernoulli beam theory and accounting for the geometric nonlinearity of leaf spring deformation during operation. The model’s validity is confirmed through finite element analysis. This study then explores the influence of design parameters on the mechanical characteristics of the damper. The results reveal a gradual increase in the torsional stiffness of the damper with the expanding arc radius of the clamping groove. Simultaneously, the torsional stiffness curve exhibits more pronounced nonlinear characteristics. In contrast, an elongation of the leaf spring leads to a sharp decline in torsional stiffness, accompanied by a diminishing prominence of nonlinear traits. Thus, both the arc radius of the clamping groove and the spring length significantly impact the torsional stiffness and nonlinear features of the leaf spring torsional vibration damper. The nonlinear characteristics intensify with an enlarged arc radius of the clamping groove and a reduced leaf spring length. Additionally, the damper’s torsional stiffness is influenced by the leaf spring thickness and the red copper gasket length. Future damper designs should comprehensively consider these relevant parameters. Full article

Cell and gene therapies represent promising new treatment options for many diseases, but also face challenges for clinical translation and delivery. Hospital-based GMP facilities enable rapid bench-to-bedside development and patient access but require significant adaptation to implement pharmaceutical manufacturing in healthcare infrastructures constrained by space, regulations, and resources. This article reviews key considerations, constraints, and solutions for establishing hospital facilities for advanced therapy medicinal products (ATMPs). Technologies like process analytical technology (PAT), continuous manufacturing, and artificial intelligence (AI) can aid these facilities through enhanced process monitoring, control, and automation. However, quality systems tailored for product quality rather than just compliance, and substantial investment in infrastructure, equipment, personnel, and multi-departmental coordination, remain crucial for successful hospital ATMP facilities and to drive new therapies from research to clinical impact. Full article

At present, the automatic generation of tolerance types based on rule-based reasoning has an obvious characteristic: for the same assembly feature, tolerance items are recommended that satisfy all feature characteristics, with a large number of recommendations. For this reason, automatically selecting tolerance types and reducing designer autonomy remains a challenging task, especially for complex mechanical products designed using heterogeneous CAD systems. This article proposes a tolerance specification design method for the automatic selection of assembly tolerance types. Based on the construction of a hierarchical representation model of assembly tolerance information with tolerance-zone degrees of freedom (DOFs), a semantic model of geometric tolerance information with tolerance-zone DOFs and a meta-ontology model of assembly tolerance information representation are constructed. Descriptive logic is used to express the attribute relationships between different classes in the assembly tolerance information meta-ontology model, and screening inference rules are constructed based on the mechanism for selecting assembly tolerance types based on tolerance-zone DOFs. On this basis, a process for selecting assembly geometric tolerance types based on the ontology of tolerance-zone DOFs is formed. Finally, the effectiveness and feasibility of this method were verified through examples. Full article

The South China Sea is in the convergence zone of the Pacific plate, the Indo-Australian plate, and the Eurasian plate. Its formation and tectonic evolution were influenced by continental margin spreading and plate interaction between the three plates and their microcontinents. It has a complex geodynamic background. To understand how continents break up to form ocean basins, the South China Sea Basin is taken as an example to study the dynamic mechanism of its formation and evolution and the driving force of seafloor spreading, so as to understand the relationship between oceanic–continental lithosphere plates. The South China Sea basin’s opening mechanism and its principal factors of control remain controversial. To explore the influence of different extension rates, we summarized the different genesis mechanisms of the South China Sea, and combined with the tectonic section of the basin, the numerical simulation was obtained based on the finite difference method. The results obtained from numerical simulations show that the rapid extension rate was one of the important factors in the asymmetric expansion of the model, with other factors such as the thickness and rheological properties of the lithosphere held constant. The lithospheric mantle continued thinning in the stress concentration area, with the crust being pulled apart before the lithospheric mantle, eventually forming an ocean basin corresponding to the east sub-basin. However, when the extension rate was low, the model expanded almost symmetrically, and the lithosphere thinning occurred at a slow rate. The simulation results confirm that, compared with the southwest sub-basin of the South China Sea, the spreading rate of the east sub-basin was even higher. We believe that the subduction of the proto-South China Sea played a crucial role in the opening of the South China Sea, providing a more reasonable mechanism. The opposite movement of the Indo-Australian plate and Kalimantan may have inhibited the formation of the southwest sub-basin of the South China Sea, resulting in a later spreading of the southwest sub-basin than the east sub-basin, as well as a lower rate of spreading than the east sub-basin. Full article

A convolutional neural network (CNN) transducer decoder was proposed to reduce the decoding time of an end-to-end automatic speech recognition (ASR) system while maintaining accuracy. The CNN of 177 k parameters and a kernel size of 6 generates the probabilities of the current token at the token level, at the token transition of the output token sequence. Two probabilities of the current token, one from the encoder and the other from the CNN are added to the frame level to reduce the decoding step to the number of input frames. An encoder composed of an 18-layer conformer was combined with the proposed decoder for training with the Librispeech data set. The forward-backward algorithm was used for training. The space and re-appearance tokens are added to the 300-word piece tokens to represent the token string. A space token appears at a frame between two words. A comparison with the autoregressive decoders such as transformer and RNN-T decoders demonstrates that this work provides comparable WERs with much less decoding time. A comparison with non-autoregressive decoders such as CTC indicates that this work enhanced WERs. Full article

Life detection is important in earthquake rescue, but weak vital signal is susceptible to interference by clutters. Due to the undesirable characteristics of the hardware, there are two main types of clutter generated by the frequency modulation continuous wave (FMCW) radar when transmitting signals. One is generated by periodic nonlinearity during frequency modulation, and the other is generated by the phase-locked loop spuriousness (PLLS) in frequency division. They cause additional beat frequencies to appear beside those from the target, leading to false alarms. Since the suppression measures for them are different, it is necessary to distinguish the types of clutter and choose appropriate suppression methods. In this paper, the accurate theoretical modeling of the effects of the periodic nonlinearity and phase-locked loop spuriousness on the beat signal is performed to determine distinctions between them. The clutter occurring in the system used is identified as originating from phase-locked loop spuriousness through fiber-optic experiments. A method using long delay lines and cross-correlation is proposed to identify and remove it. In experiments, the false alarm rate is reduced from over 50 percent to nearly 0 percent, providing strong evidence for the effectiveness of the proposed method in through-wall detection. Full article

When the dual rotor system of the aircraft engine is operating, the mass eccentricity of the power turbine rotor and the misalignment of the shaft coupling or the bearing will cause too large vibration of the rotor; this vibration leads to the rub-impact between the rotor and the casing. The power turbine rotor from the dual rotor system is taken as the research object in this paper. Considering the misalignment, the resulting rub-impact faults, the imbalance of rotor and the disk offset, the equation of motion for the system is developed according to the Lagrangian Equation, and then the Range-Kutta Method is adopted to solve the equation. The influence of the key parameters such as the rotating speed, the misalignment angle and the rub-impact clearance on the dynamics of the system is studied; the finite element analysis was carried out to validate the correctness of the theoretical modeling method. The results show that the rub-impact increases the stiffness of the system; the Hopf bifurcation occurs in the misalignment and rub-impact coupling system; the vibrational stability near the half of the switching speed slumps with the increase of the misalignment angle; with increasing of the stiffness, the number of the chaotic zone increases, and the range of the chaos is widening; enlarging the rub-impact clearance is beneficial to reduce the degree of the rub-impact system and enhance the stability of the system. Full article

The passivation behavior of steel reinforcements in concrete is significantly influenced by the environment, concrete pore solution, and the passive film formed on the steel surface. The present study used electrochemical methods to successfully characterize the passivation process of steel reinforcements in concrete. The passivation behavior of commonly used HRB400 steel reinforcement material in concrete was studied using various electrochemical parameters quantitatively. As the soaking test time increased, the OCP gradually increased and stabilized after 5 days, indicating that the steel electrode transitioned from an active state to a passive state in the simulated liquid environment of concrete. The steel reinforcement developed a protective passive film that reduced its tendency to corrode. According to EIS, after soaking for one day, the steel electrode showed significant early passivation, indicated by an increase in its arc diameter. The WE arc gradually increased in the first 5 days of immersion, suggesting dynamic passive film formation and development. Beyond 5 days, the passive film stabilized with minimal further changes in its impedance spectrum, indicating carbon steel electrode passivation. The working electrode’s impedance increased significantly on the fifth day, and gradually increased slightly after 10 days, indicating comprehensive coverage by the oxide film. Attributed to the growth and development of the oxide film, the electrode resistance reached a relatively stable state after the fifth day. The shift in corrosion potential offers an indication of the level of passivation of the steel reinforcements. The decrease in the anode Tafel slope and increase in the corrosion potential indicate the formation and stabilization of an oxide film on the steel surface, which is beneficial for its long-term durability in concrete structures. By analyzing the OCP, EIS, and dynamic potential polarization curve method data, it is possible to gain insights into the passivation behavior of steel reinforcements in concrete structures. This study aims to provide a basis for optimizing the corrosion protection of steel reinforcements in concrete structures. The significance of this study lies in a deep understanding of the passivation behavior of steel bars in concrete, providing a theoretical basis for improving the durability and lifespan of steel bars in concrete structures. Full article

The importance of the usage of renewable energy sources in powering wireless sensor nodes in IoT and sensor networks grows together with the increasing number of utilized sensor nodes. Considering the other types of renewable energy sources, solar power differs as the most suitable one and emerges as the major source for powering sensor nodes. Thus, the consideration of using sensor nodes and collected sensor data for estimating solar panel performances and therefore solar power potential can improve the efforts in this direction. This paper presents the methodology for implementing edge intelligence on wireless sensor nodes for solar panel output voltage estimation and forecasting. The methodology covers the usage of the Python Scikit-learn package and micromlgen library for the implementation of edge intelligence on Arduino clone-based sensor nodes, particularly the development boards based on the ESP8266 chips. Scikit-learn is used for analyzing the efficiency of various regressors on collected solar data. The micromlgen library is then used for implementing those regressors on Arduino and clone nodes. The prediction of solar panel voltage generation is based on a single-sensor reading—UV or BH1750 light sensor. The Random Forest and Decision Tree regressors are implemented on the ESP8266-based development board—Wemos D1 R2. The estimation accuracy of the RF model is an MSE of approximately 0.10, MAE of 0.07 for UV and 0.04 for BH1750, and an R² of approximately 0.93 for both UV and BH1750 light sensors. The Decision Tree model has a lower accuracy with an MSE between 0.13 and 0.14, MAE of 0.07 for UV and 0.04 for BH1750, and R² of 0.90 and 0.89 for the UV and BH1750 sensors, respectively. The methodology and its efficiency are presented and discussed in this paper. Full article

By the method of molecular dynamics, computer simulation of the processes of isobaric cooling of argon particle systems under initial conditions with a temperature of 150 K at pressure values from 0.1 to 4 MPa to a temperature of 40 K with cooling rates of 10⁸, 10⁹, 10¹⁰, 10¹¹ and 10¹² K/s was performed. As a result of a computer experiment, coordinate arrays of particles were obtained, which were subjected to the procedure of three-dimensional Voronoi partitioning to identify and calculate the number of elementary cells of the crystal structure. Analysis of the structure of argon solid phases formed during isobaric cooling allowed us to deduce an estimated pattern between the concentration of FCC (face-centered cubic) cells in solid argon and the cooling rate from the liquid state. The evaluation of the orientation of the axes of translation of crystal cells in the array of particle coordinates made it possible to classify the solid phases formed as a result of cooling as single crystals, glassy media with the inclusion of clusters and single cells of FCC structures. It was revealed that during isobaric cooling at a rate not exceeding 10⁸ K/s, argon completely crystallizes, at isobaric cooling rates of 10⁹–10¹⁰ K/s, the union of elementary cells of the crystal structure into clusters is observed in glassy argon, and at rates of 10¹¹ K/s and higher at pressures of 1 MPa and lower, solid vitreous phases of argon are formed in which no crystal structure cells are detected. Full article

Rolling bearings are one of the most important and indispensable components of a mechanical system, and an accurate prediction of their remaining life is essential to ensuring the reliable operation of a mechanical system. In order to effectively utilize the large amount of data collected simultaneously by multiple sensors during equipment monitoring and to solve the problem that global feature information cannot be fully extracted during the feature extraction process, this research presents a technique for forecasting the remaining lifespan of rolling bearings by integrating many features. Firstly, a parallel multi-branch feature learning network is constructed using TCN, LSTM, and Transformer, and a parallel multi-scale attention mechanism is designed to capture both local and global dependencies, enabling adaptive weighted fusing of output features from the three feature extractors. Secondly, the shallow features obtained by the parallel feature extractor are residually connected with the deep features through the attention mechanism to improve the efficiency of utilizing the information of the front and back features. Ultimately, the combined characteristics produce the forecasted findings for the RUL of the bearing using the fully connected layer, and RUL prediction studies were performed with the PHM 2012 bearing dataset and the XJTU-SY bearing accelerated life test dataset, and the experimental results demonstrate that the suggested method can effectively forecast the RUL of various types of bearings with reduced prediction errors. Full article

High-resolution remote sensing images (HRRSI) have important theoretical and practical value in urban planning. However, current segmentation methods often struggle with issues like blurred edges and loss of detailed information due to the intricate backgrounds and rich semantics in high-resolution remote sensing images. To tackle these challenges, this paper proposes an end-to-end attention-based Convolutional Neural Network (CNN) called Double Hybrid Attention U-Net (DHAU-Net). We designed a new Double Hybrid Attention structure consisting of dual-parallel hybrid attention modules to replace the skip connections in U-Net, which can eliminate redundant information interference and enhances the collection and utilization of important shallow features. Comprehensive experiments on the Massachusetts remote sensing building dataset and the Inria aerial image labeling dataset demonstrate that our proposed method achieves effective pixel-level building segmentation in urban remote sensing images by eliminating redundant information interference and making full use of shallow features, and improves the segmentation performance without significant time costs (approximately 15%). The evaluation metrics reveal significant results, with an accuracy rate of 0.9808, precision reaching 0.9300, an F1 score of 0.9112, a mean intersection over union (mIoU) of 0.9088, and a recall rate of 0.8932. Full article