Mismatch Problem Research Articles

HMS-TENet: A hierarchical multi-scale topological enhanced network based on EEG and EOG for driver vigilance estimation

Driving vigilance estimation is an important task for traffic safety. Nowadays, electroencephalography (EEG) and electrooculography (EOG) have made some achievements in vigilance estimation, but there are still some challenges: 1) The traditional approachs with direct multimodal fusion may face the problems of information redundancy and data dimensionality mismatch; 2) Capture key discriminative features during multimodal fusion without losing specific patterns to each modality. In order to solve the above problems, this paper proposes a approach with fusion of EEG and EOG features in split bands, which not only preserves the information about brain activities in different bands of EEG, but also effectively integrates the relevant information of EOG. On this basis, we further propose a hierarchical multi-scale topological enhanced network (HMS-TENet). This network first introduces a pyramid pooling structure (PPS) to capture contextual relationships from different discriminative perspectives. And then we design a selective convolutional structure (SCS) for adaptive sense-field selection, which enables us to mine the desired discriminative information in small-size features. In addition, we design a topology self-aware attention to enhance the learning of representations of complex topological relationships among EEG channels. Finally, the output of the model can be selected for both regression and classification tasks, providing higher flexibility and adaptability. We demonstrate the robustness, generalizability, and utility of the proposed method based on intra-subject and cross-subject experiments on the SEED-VIG public dataset. Codes are available at https://github.com/tangmeng28/HMS-TENet.

Lightweight dielectric-magnetic synergistic necklace-shaped Co@NCP/carbon nanofiber composites for enhanced electromagnetic wave absorption

In order to solve the problem of impedance mismatch of carbon fiber absorbing materials, it is crucial to create a carbon-based absorbing material with a special structure, synergistic magnetic and dielectric properties. In this paper, necklace-shaped Co@N-doped carbon polyhedron /carbon nanofiber (Co@NCP/CNF) composites with synergistic magnetic and dielectric properties are successfully fabricated by electrospinning. Compared with Co@NCP and CNF, the optimal minimum reflection loss of Co@NCP/CNF composite is -66.14 dB at 2.89 mm and the maximum effective absorption bandwidth is 6.24 GHz (11.76-18.00 GHz) at 2.25 mm at a low filler load of 10 wt.%. The necklace-like structure, the coupling effect of dielectric and magnetic materials and the heterogeneous interface form multiple polarizations, conductive losses and multiple loss mechanisms to optimize impedance matching and attenuation performance, which is conducive to excellent absorption performance. More importantly, the radar cross section (RCS) reduction is as high as 24.02 dB·m2, which has proven to have a good absorption effect in actual application environments. This work combines the advantages of Co@NCP and CNF very well, which provides guidance for designing EM waves nanocomposite fiber absorbers with lightweight and strong absorbing properties.

Research progress of three-dimensional printed customized prosthesis and its application in acetabular reconstruction of hip revision surgery

To review research progress on the design, manufacturing, and clinical application of three-dimensional (3D) printed customized prosthesis in acetabular reconstruction of hip revision surgery. The related research literature on 3D printed customized prosthesis and its application in acetabular reconstruction of hip revision surgery was searched by key words of "3D printed customized prosthesis", "revision hip arthroplasty", "acetabular bone defect", and "acetabular reconstruction" between January 2013 and May 2024 in Chinese and English databases, such as CNKI, Wanfang database, PubMed, etc. A total of 34 271 articles were included. After reading the literature titles, abstracts, or full texts, the literature of unrelated, repetitive, low-quality, and low evidence level was screened out, and a total of 48 articles were finally included for analysis and summary. The bone growth and mechanical properties of 3D printed customized prosthesis materials are better than those of non-3D printed customized prosthesis, which further solves the problem of elastic modulus mismatch between the implant and natural bone caused by "stress shielding"; the porous structure and antibacterial coating on the surface of 3D printed customized prosthesis have good anti-bacterial effect. 3D printed customized prosthesis can perfectly match the patient's individual acetabular anatomical characteristics and defect type, thus improving the accuracy of acetabular reconstruction and reducing the surgical time and trauma. 3D printed customized prosthesis can be used for precise and efficient individualized acetabular reconstruction in hip revision surgery with good early- and mid-term effectiveness. More optimized production technics and procedures need to be developed to improve the efficiency of clinical application and long-term effectiveness.

Adaptive Sliding Mode Control for AUV based on Backstepping and Neural Networks

Abstract Automatic Underwater Vehicle (AUV) inevitably suffers from various interference issues in the marine environment. Due to the limitations of underwater measurement methods and tools, as well as the complexity of AUV's control parameters in the underwater environment, dynamic measurement errors are easily cascaded and amplified, leading to the failure of the control system. In response to this phenomenon, this paper focuses on overcoming the influence of internal and external unknown factors in the tracking and control process of AUV trajectories. The internal factors are mainly the uncertainties generated by the model mismatch problem, and the external factors are mainly from the dynamic ocean currents. The AUV disturbances mainly affect the kinematics and dynamics levels directly or indirectly. In order to achieve the control of internal and external dynamic disturbances, we have designed a control system that employs backstepping (BS) and a sliding mode controller (SMC) with RBF neural networks to achieve the cascaded control of kinematics and dynamics. Comparison of multiple sets of simulations shows that our proposed algorithm has excellent anti-disturbance performance for dynamic conditions with low measurement accuracy.

Joint Mixing Data Augmentation for Skeleton-based Action Recognition

Skeleton-based action recognition is beneficial for understanding human behavior in videos, and thus has received much attention in recent years as an important research area in action recognition. Current research focuses on designing more advanced algorithms to better extract spatio-temporal information from skeleton data. However, due to the small amount of data in the existing skeleton dataset and the lack of effective data augmentation methods, it is easy to lead to overfitting in model training. To address this challenge, we propose a mix-based data augmentation method, Joint Mixing Data Augmentation (JMDA), which can generally improve the effectiveness and robustness of various skeleton-based action recognition algorithms. In terms of spatial information, we introduce SpatialMix (SM), a method that projects the original 3D skeleton discrete information into a 2D space. Then, SM mixes the projected spatial information between two random samples during the training process to achieve the spatial-based mixing data augmentation. Concerning temporal information, we propose TemporalMix (TM). Leveraging the temporal continuity in skeleton data, we perform a temporal resize operation on the original skeleton data, and then merge two random samples during training to achieve the temporal-based mixed data augmentation. Additionally, we analyze the Feature Mismatch (FM) problem caused by introducing mix-based data augmentation into skeleton data. Then we propose a new data preprocessing method called Feature Alignment (FA) to effectively address this problem and improve model performance. Moreover, we propose a novel training pipeline, Joint Training Strategy (JTS), which combines multiple mix-based data augmentation methods for further improvement of model performance. Specifically, our proposed JMDA is plug-and-play and widely applicable to skeleton-based action recognition models. At the same time, the application of JMDA does not increase the model parameters and there is almost no additional training cost. We conduct extensive experiments on NTU RGB+D 60 and NTU RGB+D 120 datasets to demonstrate the effectiveness and robustness of the proposed JMDA on several mainstream skeleton-based action recognition algorithms.

An Energy Management System for Distributed Energy Storage System Considering Time-Varying Linear Resistance

As the proportion of renewable energy in energy use continues to increase, to solve the problem of line impedance mismatch leading to the difference in the state of charge (SOC) of each distributed energy storage unit (DESU) and the DC bus voltage drop, a distributed energy storage system control strategy considering the time-varying line impedance is proposed in this paper. By analyzing the fundamental frequency harmonic components of the pulse width modulation (PWM) signal carrier of the converter output voltage and output current, we can obtain the impedance information and, thus, compensate for the bus voltage drop. Then, a novel, droop-free cooperative controller is constructed to achieve SOC equalization, current sharing, and voltage regulation. Finally, the validity of the system is verified by a hardware-in-the-loop experimental platform.

“Bridging the Skill Gaps”: Analyzing the Mismatch between Hospitality Education and Industry Needs in Uganda

This is a persistent problem of skill mismatch between graduates and employers’ needs in the Ugandan hospitality industry, resulting in skill deficits that hamper employability and industry advancement. Identifying the causes of these skill gaps is the aim of this study, together with establishing recommendations to narrow the gap existing between hospitality education and the industry. The study adopted the qualitative case study research design and sampled 26 respondents from recent hospitality graduates and employers, educators or trainers, and policymakers in Kabale District, Uganda. The findings were encoded through thematic analysis. Theoretical orientation is scant with practical and interpersonal skills. Some employers also reported a concern that more attention should be paid to enhancing the practical readiness of graduates at workplaces and that there should be an increased dialog between educational institutions and employers in the hospitality sector. According to the results of the study, there is a need for a closer connection between curricula and industry demands, interconnecting the abilities needed for practical work and soft skills. Recommendations include increasing communication between teachers and supervisors from industry, enhancing internship programs, and including practical aspects. It is recommended that such collaborations be promoted through policy and funding to guarantee the appropriate match of education to the labor market requirements. These steps are relevant for reducing the existing skill gap and making graduates fit for employment opportunities in the industry

Efficient gridless wideband sparse array synthesis with tapped delay-lines

In this paper, we propose a new wideband sparse array synthesis method based on gridless compressed sensing to solve the basis mismatch problem for discrete grids. Considering the tapped delay-lines (TDL) structure for space-time domain processing, and using successive frequency-varying atoms for sparse representation of wideband signals, an arbitrary sampling-atomic norm minimization is introduced to model the group sparsity-constrained wideband arrays in which the positions and the excitation values of array element are obtained with a high freedom. The above nonconvex problem is then transformed into a convex relaxation, which is solved using the Prolate Spheroidal Wave Functions (PSWFs). The experimental results show that the proposed sparse array design has higher matching accuracy and sparsity, compared with the discretized wideband sparse array design, which verifies the effectiveness and efficiency of this method.

Self-adhesive, mechanically strong, and conductive organogel for flexible/wearable electronics and underwater electronic skin

Due to their flexibility, self-healing ability, and biocompatibility, conductive hydrogels have become excellent candidates for flexible electronics. However, challenges remain, such as water evaporation when exposed to air, resulting in a loss of flexibility and conductivity. Additionally, traditional hydrogels quickly swell underwater, which causes irreversible damage to their structure and electrical properties. As a promising alternative, organogels have gained attention for overcoming these drawbacks. Here, we report a transparent, multifunctional organogel using ultraviolet-initiated polymerization, which exhibits excellent adhesion, robustness, electrical and interfacial stability, and super stretchability. By adjusting the concentration of the lithium bis(trifluoromethanesulfonyl)imide (LiTFSI), the conductivity of organogel could be easily regulated from non-conductive to conductive, obtaining non-conducting elastomer (NCE, without LiTFSI) and ion-conducting elastomer (ICE, with LiTFSI) with identical mechanical properties and superior adhesion due to the same composing polymer chains. This unique characteristic overcomes the interface mismatch problem of traditional flexible electronic devices. Moreover, a high-performance triboelectric nanogenerator (TENG) was designed (ICE-TENG) to achieve a maximum power density of 151.3 μW cm−2, which was utilized to power small electronics. Additionally, a strain sensor was constructed using the ICE, realizing underwater sensing and communication with high stability. This multifunctional organogel is promising for multi-functional human–machine interaction.

Design and Implementation of a Width-Adjustable Asynchronous FIFO for Cross-Clock Domain Data Transmission

Existing research shows that asynchronous FIFO has been widely used in a variety of complex system designs, such as FPGA-based image processing systems, USB communication systems, and so on. To make the designed asynchronous FIFO more programmable and flexible, so that it can adapt to various application scenarios more quickly, this paper studies and designs an asynchronous FIFO with adjustable input and output bit width. In this study, according to the relationship between 24-bit input data and 32-bit storage space, four 24-bit data are selected to fill three RAM storage spaces at one time. According to the multiple relationships between 32-bit storage space and 128-bit output data, the reading pointer is enlarged by 4 times to realize the function of reading four 32-bit data at one time. This whole process realizes the conversion of data bit width through data splicing. Finally, the 24-bit RGB888 image data is successfully converted into 128-bit data and transmitted to the bus, which successfully solves the problem of data width mismatch.

Structure preservation constraints for unsupervised domain adaptation intracranial vessel segmentation.

Unsupervised domain adaptation (UDA) has received interest as a means to alleviate the burden of data annotation. Nevertheless, existing UDA segmentation methods exhibit performance degradation in fine intracranial vessel segmentation tasks due to the problem of structure mismatch in the image synthesis procedure. To improve the image synthesis quality and the segmentation performance, a novel UDA segmentation method with structure preservation approaches, named StruP-Net, is proposed. The StruP-Net employs adversarial learning for image synthesis and utilizes two domain-specific segmentation networks to enhance the semantic consistency between real images and synthesized images. Additionally, two distinct structure preservation approaches, feature-level structure preservation (F-SP) and image-level structure preservation (I-SP), are proposed to alleviate the problem of structure mismatch in the image synthesis procedure. The F-SP, composed of two domain-specific graph convolutional networks (GCN), focuses on providing feature-level constraints to enhance the structural similarity between real images and synthesized images. Meanwhile, the I-SP imposes constraints on structure similarity based on perceptual loss. The cross-modality experimental results from magnetic resonance angiography (MRA) images to computed tomography angiography (CTA) images indicate that StruP-Net achieves better segmentation performance compared with other state-of-the-art methods. Furthermore, high inference efficiency demonstrates the clinical application potential of StruP-Net. The code is available at https://github.com/Mayoiuta/StruP-Net .

Temporal-enhanced Radar and Camera Fusion for Object Detection

Recently, object detection methods based on multimodal fusion have gained widespread adoption in autonomous driving, proving to be valuable for detecting objects in dynamic environments. Among them, millimetre wave (mmWave) radar is commonly utilized as an effective complement to cameras, as it is almost unaffected by harsh weather conditions. However, current approaches that fuse mmWave radar and camera often overlook the correlation between the two modalities, failing to fully exploit their complementary features. To address this, we propose a temporal-enhanced radar and camera fusion network to explore the correlation between these two modalities and learn a comprehensive representation for object detection. In our model, a temporal fusion model is introduced to fuse mmWave radar features from different moments, thus mitigating the problem of mmWave radar point-object mismatch due to object movement. Moreover, a new correlation-based fusion strategy using the dedicated mask cross attention is proposed to fuse mmWave radar and vision features more effectively. Finally, we design a gate feature pyramid network that selects shallow texture information based on deep semantic information to obtain more representative features. The experimental results on the nuScenes benchmark demonstrate the effectiveness of our proposed method.

Thermal cycling and steam corrosion behavior of Yb3Al5O12‐based multilayered environmental barrier coatings for SiCf/SiC

AbstractTo alleviate thermal mismatch problem of environmental barrier coatings (EBCs) on SiC fiber‐reinforced SiC ceramic matrix composites (SiCf/SiC CMCs) surface and improve their high‐temperature durability for aircraft engines, by fully utilizing the appropriate thermal expansion coefficient, low oxygen transmittance, low thermal conductivity, and other advantages of ytterbium aluminum garnet (Yb3Al5O12), the double ceramic layered Yb3Al5O12/Yb2Si2O7 (DCL‐Yb3Al5O12) and the triple ceramic layered Yb3Al5O12/Yb2SiO5/Yb2Si2O7 (TCL‐Yb3Al5O12) EBC systems were prepared on SiCf/SiC CMCs by atmospheric plasma spraying (APS). Their phase composition and microstructures were investigated comparatively. The thermal cycling and water vapor/oxygen corrosion behavior of these coating systems were compared at 1300°C. The results showed that the thermal cycling life of the DCL‐Yb3Al5O12 and TCL‐Yb3Al5O12 EBC systems were 295 and 320 times, respectively. The failure of both the coating systems occurred between the Yb2Si2O7 layer and Si bond coat. The strength retention rate of DCL‐Yb3Al5O12 and TCL‐Yb3Al5O12 EBC systems after water vapor/oxygen corrosion for 70 h was 12.8% and 23.1%, respectively, and the fracture modes of both the systems exhibited “pseudoplastic” characteristic. TCL‐Yb3Al5O12 EBC systems with a gradient structure of more layers exhibit more excellent high‐temperature durability than DCL‐Yb3Al5O12 EBCs.

Deep-time origin of tympanic hearing in crown reptiles

The invasion of terrestrial ecosystems by tetrapods (c. 375 million years [Ma]) represents one of the major evolutionary transitions in the history of life on Earth. The success of tetrapods on land is linked to evolutionary novelties. Among these, the evolution of a tympanic ear contributed to mitigating the problem of an impedance mismatch between the air and the fluid embedding sound-detecting hair cells in the inner ear.1,2,3 Pioneering studies advocated that similarities in the tympanic ear of tetrapods could only result from a single origin of this structure in the group,4,5 an idea later challenged by paleontological and developmental data.4,6,7,8 Current evidence suggests that this sensory structure evolved independently in amphibians, mammals, and reptiles,1,6 but it remains uncertain how many times tympanic hearing originated in crown reptiles.9,10 We combine developmental information with paleontological data to evaluate the evolution of the tympanic ear in reptiles from two complementary perspectives. Phylogenetically informed ancestral reconstruction analyses of a taxonomically broad sample of early reptiles point to the presence of a tympanic membrane as the ancestral condition of the crown group. Consistently, comparative analyses using embryos of lizards and crocodylians reveal similarities, including the formation of the tympanic membrane within the second pharyngeal arch, which has been previously reported for birds. Therefore, both our developmental and paleontological data suggest a single origin for the tympanic middle ear in the group, challenging the current paradigm of multiple acquisitions of tympanic hearing in living reptiles.

Thermo-flexible coupled dynamics of composite laminated plates based on absolute nodal coordinate formulation

In this paper, a thermo-flexible coupled dynamic model of composite laminates is established by Absolute Nodal Coordinate Formulation (ANCF). In order to solve the problem of mesh mismatch and precision inconsistency between the displacement and temperature fields in the traditional thermo-flexible coupled modeling method, the ANCF hybrid element with integrated temperature description is constructed to achieve a unified description of the displacement and temperature fields. A new ANCF thin shell element with thermal effects is proposed. Based on the first law of thermodynamics, the heat capacity matrix, thermal conduction matrix, blackbody radiation matrix, internal heat source vector, and heat flux density vector caused by solar radiation for the ANCF thin shell element considering thermal effects are derived. The dynamic equation of ANCF composite laminates under a unified description is derived, and its dynamic model is established. The thermo-flexible dynamic response of ANCF composite laminates under thermal conduction, space thermal radiation, and solar radiation is analyzed by numerical simulation. The simulation results reveal the evolution process of the transient temperature field and the phenomenon of thermal-induced vibration, thus confirming that the thermal effects have an important influence on the dynamic behavior of ANCF composite laminates. The research provides a theoretical basis for the ground test of solar panels.

Active damping control based bus voltage resonance suppression in electrolytic capacitorless PMSM application

Abstract The structure of electrolytic capacitorless in automotive electronic applications has the advantages of lower cost and better reliability. However, motor drive systems using this structure may experience unstable bus voltage. To this end, this paper proposes an active damping control strategy based on virtual impedance. By modelling the electric drive system and conducting stability analysis, the cause of bus voltage resonance due to the use of small capacitors is revealed. Based on the extracted DC bus voltage harmonic signal, additional voltage vectors are added in the d-axis and q-axis voltage vectors, eliminating the impedance mismatch problem in the drive system caused by the reduction of bus capacitance, effectively suppressing the voltage oscillation on the machine side of the drive system. Simulation data shows that under the condition of using small-capacity ceramic capacitors, the method proposed in this paper achieves a harmonic suppression capability similar to that of large-capacity electrolytic capacitors, effectively ensuring the application safety of automotive drivers with electrolytic capacitorless architecture.

Review on hard particle reinforced laser cladding high-entropy alloy coatings

Since their advent in 2004, high-entropy alloys have allured the field of materials science and engineering. Laser cladding technology, with its advantages of a small heat-affected zone and rapid heating and cooling, has become a popular technique for preparing high-entropy alloy coatings. Traditional high-entropy alloys have the problem of strength-plasticity mismatch, which limits the further application of laser cladding high-entropy alloys in industry. As a method to solve these challenges, hard particle reinforced alloy coating technology can effectively control the comprehensive properties of high-entropy alloy coatings. This paper first explores and analyzes the five strengthening mechanisms and four main influencing factors of hard particle reinforced laser cladding alloy coatings. Then, from the perspective of introducing particle types, the research status of ceramic particles, rare earth particles and other types of hard particle reinforced laser cladding high entropy alloy coatings is introduced. Finally, the characteristics of hard particle reinforced laser cladding high-entropy alloy coatings are summarized, and future recommendations for hard particle reinforced alloy coatings technology and its application in laser cladding high-entropy alloys are proposed, which will be helpful for researchers and producers in this field.

Improved maize leaf area index inversion combining plant height corrected resampling size and random forest model using UAV images at fine scale

ContextAccurate monitoring of leaf area index (LAI) is conducive to timely and targeted management measures. Unmanned aerial vehicle (UAV) remote sensing provides an important way for non-destructive monitoring of crop leaf area index. ObjectiveIn this study, visible light (RGB) and multispectral remote sensing data from the UAV and ground-measured LAI data from the Plant Canopy Analyzer LAI-2200 C were used to conduct inversion of maize LAI on a fine scale. MethodsTo address the problem of spatial scale mismatch between the spatial resolution of UAV images and the ground-measured LAI, the scale difference between UAV image data and ground-measured data was reduced by removing the outermost ring data measured by the LAI-2200 C instrument, calculating the spatial resolution of the UAV images after resampling based on the height of the plant, and the resampling method based on the circle. Finally, through the above method to resample the UAV images, we extract the vegetation index and canopy height features as the input variables of the random forest model to build the maize LAI inversion model in vegetative stages and reproductive stages respectively, which is referred to as the Vis_H+RF method. Results and conclusionsThe Vis_H+RF method of Tongliao experimental station has an R2 of 0.96 in the vegetative stages and a R2 of 0.61 in the reproductive stages, both of which perform well and have certain migration capabilities. SignificanceThe LAI inversion model constructed based on the method in this study is basically consistent with the actual situation and can provide data support for maize growth monitoring.

Fabrication of MXene-encapsulated Co@C nanoparticles for efficient microwave absorption in the X-band

Two-dimensional MXene has structural advantages in electromagnetic wave scattering due to its layered structure, but MXene materials can lead to impedance mismatch problems due to their high dielectric constants, so it is still a challenge to design highly efficient wave-absorbing materials based on MXene with low reflection loss, thin thickness, and wide absorption frequency. In this study, composite wave-absorbing materials were fabricated from Co–Co PBA precursors and MXene using liquid nitrogen flash freezing and freeze-drying techniques. By treating MXene and the PBA precursor at a high temperature of 750 °C, a rich heterogeneous interface was formed between Co@C and MXene (CCM7), and the impedance matching was optimized to improve the reflection loss capability. The optimized sample has an effective absorption bandwidth of 4.1 GHz at 2.5 mm covering the entire X-band with a minimum reflection loss of −61.42 dB. It is also demonstrated that CCM7 is satisfactory for Radar Cross-Section of flat panels and unmanned aerial vehicles by CST calculations, and this work provides a fresh perspective on the use of effective MXene composites for microwave absorption.

High temperature flexible 2D metasurface based on optimal design for thermal insulation and electromagnetic wave absorption skin

The development of radar stealth skin with long term stable service and flexible deformability is the premise and foundation of improving the battlefield survivability of deformable aircraft. Aiming at the bottleneck problem of mismatch between the flexible configuration and the electromagnetic configuration of the existing stealth composite materials, a new type of SiO2 fiber paper (SFP) with flame retardant, thermal insulation, low dielectric constant and super-hydrophobic was prepared by combining the papermaking process with surface modification. The effects of solid content and high temperature environment on the mechanical properties, thermal insulation properties, dielectric properties and hydrophobic properties of SFP materials were studied in detail. Based on this, the optimal design and construction method of radar stealth metasurface suitable for flexible deformation are proposed, and the high temperature resistant flexible stealth skin metasurface is obtained. The metasurface has been demonstrated to achieve an effective wave absorption of −8 dB in the 10.9–16.4 GHz range at 400 μm thickness, making it an ideal candidate for flame retardant, flexible, thermal insulation and radar stealth skin under extreme conditions. It provides theoretical basis and technical support for the innovative development of high-speed deformable stealth aircraft.