Mismatch Problem Research Articles

Reflection-type surface lattice resonances in all-metal metasurfaces for refractive index sensing

Surface lattice resonance (SLR) is a pretty effective mechanism to realize ultranarrow linewidths in the spectrum. Herein, we propose and demonstrate reflection-type SLRs in all-metal metasurfaces experimentally, compared with the traditional transmission-type SLR, which can avoid the refractive index (RI) mismatch problem and are more suitable for high-efficiency RI sensing due to direct contact and strong light–matter interaction. The measured SLR linewidth is 13.5 nm influenced by the meta-atom size, which needs a compromise design to keep a balance between the narrow linewidth and noise immunity. Notably, the SLR sensitivity is determined by the lattice period along the polarization direction with regularity, which establishes an intuitive link between structures and optical responses and provides a theoretical guide for metasurface designs. Additionally, incident angle multiplexing will make the resonance wavelength red shift or blue shift in the case of orthogonal polarization. The rectangular array metasurface can realize dual SLRs with different sensing performances. Flexibly, the SLR can also be formed by the different meta-atoms and arrays. This research supports SLR multifarious applications involving not only RI sensing but also nonlinear optics, nano-lasers, etc.

High-Q, temperature-stable, and medium-permittivity composite ceramics of tungstenbronze-type and perovskite titanates through layer-stacking process

High-Q and temperature-stable ceramics are indispensable in microwave engineering. However, medium-permittivity (εr ∼ 60, named as K60) microwave dielectric ceramics that meet the above demands are yet to be synthesized. High-Q Ba4Sm9.33Ti16.5Al2O54 (BSTA) and Ca0.6Sm0.27Ti0.8Al0.27O3 (CSTA) ceramics have large resonant frequency temperature coefficients (τf) with opposite signs. The composites of the two are expected to have good dielectric properties, but there will be obvious diffusion when they are compounded with each other by sintering after directly mixing the raw powder, which would lead to severe deterioration in dielectric properties. In this work, the undesired diffusion can be effectively avoided by stacking two or three ceramic layers together, which are achieved by two methods named adhesive bonding and spark-plasma-sintering (SPS) cofiring. The finite element method (FEM) analysis with COMSOL Multiphysics proposed in this work can precisely predict the microwave dielectric properties of layered ceramics, helping to determine the ratio of different layers to reach near-zero τf. The adhesive-bonded layered ceramics exhibit excellent dielectric properties: εr = 62.2, Q×f = 21,400 GHz, and τf = –0.7 ppm/°C. The SPS-cofired layered ceramics can be fabricated in one time, partially solving the problem of sintering mismatch between different layers, together with superior properties of εr = 59.8, Q×f = 19,780 GHz, and τf = –0.6 ppm/°C. These layered ceramics could fill the gap of high-Q and temperature-stable K60 microwave dielectric ceramics. The layer-stacking process and related FEM simulations can be used to design more high-Q and temperature-stable microwave dielectric ceramics and devices.

The Effect of Appropriate Placement of Employees with Disabilities on Work Productivity

Disabled employee placement is an increasingly important topic in the context of employment equity. The problem of imbalance or mismatch in the placement of employees with disabilities in the work environment can affect work productivity and career continuity. The purpose of this study is to analyze the effect of appropriate placement of employees with disabilities on work productivity. This research uses quantitative methods. Data were collected through questionnaires distributed to employees with disabilities in various companies in Indonesia. The population in this study were employees with disabilities in Indonesia. The sampling technique was carried out using random sampling technique. The data collected was analyzed using simple linear regression statistical tests. The results showed that appropriate placement has a positive influence on the work productivity of employees with disabilities. Disabled employees who are placed in positions that match their abilities have higher work productivity than disabled employees who are placed in inappropriate positions. Therefore, companies need to place employees with disabilities carefully and pay attention to their abilities.

Charging the battery via an electric machine fed by dual power source in fuel cell vehicles

In the powertrain of the available fuel cell vehicle, a direct current to direct current (DC/DC) converter is needed to solve the problem of voltage mismatch between the fuel cell and the battery. To cut down the cost and reduce the space occupation, the DC/DC converter is omitted from the powertrain in this study, where the electric machine has two sets of windings supplied by the fuel cell and the battery directly. This study aims to realize charging the battery through no DC/DC converters but only a dual winding electric machine in fuel cell vehicles. Four battery charging modes for the fuel cell vehicle are analyzed under different driving conditions. With a full consideration of the power source characteristic, a strategy based on a power distribution factor is proposed to charge the battery and satisfy the power demand of the vehicle simultaneously. To charge the battery without DC/DC converters when the vehicle is stopped, a method of changing d-axis flux linkage is proposed to make the electric machine perform like a transformer and conduct energy transfer between the fuel cell and the battery. The feasibility of the proposed charging method is verified by both simulations and experiments.

Speech Perception Improvement Algorithm Based on a Dual-Path Long Short-Term Memory Network.

Current deep learning-based speech enhancement methods focus on enhancing the time-frequency representation of the signal. However, conventional methods can lead to speech damage due to resolution mismatch problems that emphasize only specific information in the time or frequency domain. To address these challenges, this paper introduces a speech enhancement model designed with a dual-path structure that identifies key speech characteristics in both the time and time-frequency domains. Specifically, the time path aims to model semantic features hidden in the waveform, while the time-frequency path attempts to compensate for the spectral details via a spectral extension block. These two paths enhance temporal and spectral features via mask functions modeled as LSTM, respectively, offering a comprehensive approach to speech enhancement. Experimental results show that the proposed dual-path LSTM network consistently outperforms conventional single-domain speech enhancement methods in terms of speech quality and intelligibility.

Equivalent transmission line characterization and multi‐layer material measurement analysis of the signal conversion process in the pulsed electro‐acoustic method

AbstractThis paper studies the equivalent transmission line model of the pulsed electro‐acoustic (PEA) method with its applications. Based on the consistency of acoustic wave behaviour inside lossy acoustic materials and voltage wave propagation in transmission line, an equivalent simulation model of the PEA system is developed, whose reliability is verified by the output from the transducer and amplifier models and the comparison with measured waveforms. For the problem of acoustic impedance mismatch between different modules, simulation indicates that the unequal impedances of semiconducting electrode and sample can affect the amplitude of the measured signal at the upper electrode side, and the reflected acoustic waves caused by the transducer can affect the charge waveform. Further simulation for multi‐layer materials finds that the reflected acoustic waves of different samples and sound absorbing module can superimpose on the charge signal. Accordingly, a selection criterion is proposed to avoid the effect of the reflected waves at the interface. As for the acoustic reflection caused by internal charge, it needs to be dealt with sequentially in calibration process, starting from the result inside the sample near ground electrode. The research can provide a foundation for analyzing the acoustic properties of the PEA method.

Capacity optimization and performance analysis of wind power-photovoltaic-concentrating solar power generation system integrating different S-CO2 Brayton cycle layouts

This study investigates a wind power-photovoltaic-concentrated solar power (WP-PV-CSP) system that incorporates different supercritical CO2 (S-CO2) Brayton cycle layouts to address grid-connected safety issues associated with solar and wind energy. Additionally, it aims to enhance the system's techno-economic performance. Notably, prior research has not explored the optimal capacity configuration of the WP-PV-CSP system or identified the most effective S-CO2 Brayton cycle layout for system optimization. Reasonable capacity allocation can guarantee the system's reliability and feasibility, while an appropriate operation schedule can better handle the problem of mismatch between output and demand, and capacity and operation interact with each other. Consequently, this paper proposes a bi-level capacity-operation collaborative optimization approach to optimize the system's main components' capacity and operation scheduling with the optimization objectives of levelized cost of energy (LCOE) and CO2 emissions. Moreover, it seeks to pinpoint the most advantageous S-CO2 Brayton cycle layout. The results demonstrate that employing the S-CO2 intercooling Brayton cycle as the CSP system's power cycle yields the WP-PV-CSP system's best techno-economic performance. Compared with the WP-PV-CSP system integrating the steam Rankine cycle, the LCOE, CO2 emissions, and power discard are reduced by 13.81%, 40.36%, and 37.06%, respectively, and the system efficiency experiences a noteworthy 36.36% increase. These findings comprehensively highlight the substantial techno-economic and environmental advantages of adopting the S-CO2 Brayton cycle. In summary, this research contributes valuable insights into optimizing WP-PV-CSP systems, explicitly addressing capacity and operational challenges, and underscores the potential benefits of selecting the S-CO2 Brayton cycle in advancing renewable energy solutions.

Fabrication of a Counter-Directional Pump/Signal Combiner with Built-In Mode Field Adapter

This article introduces a novel counter-directional pump/signal combiner with a built-in mode field adapter. This combiner offers additional functionality to address the problem of mode field mismatch between the gain fiber and delivery fiber, which occurs when using a large-core (50 μm) signal fiber to suppress stimulated Raman scattering. The combiner exhibits negligible degradation in beam quality as a result of implementing mode field matching and employing an effective feedback alignment technique. The beam quality of the mode field adapter integrated in the combiner is improved by 10%, compared to the conventional approach, thanks to the reduction in splicing points and the prevention of fusion loss caused by tapering-induced cladding diameter mismatch. The combiner demonstrates an average pump coupling efficiency of 98.5% and a temperature rise coefficient of less than 10 °C/kW without active cooling. Furthermore, an integrated device based on the combiner is fabricated to shorten the length of delivery fiber, therefore mitigating the effects of stimulated Raman scattering. All those techniques mentioned above are utilized in a narrow linewidth laser system, resulting in an output of approximately 5840 W with a nearly single-mode characteristic.

Preparation of NaYF4:Tm, Yb, and Gd Luminescent Nanorods/SiO2 Nanospheres Composite Thin Film and Its Application in Perovskite Solar Cells.

In this study, we aim to minimize light loss and achieve high power conversion efficiencies (PCE) in perovskite solar cells (PSCs) by employing a spectral conversion film component with antireflection properties. In our scheme, NaYF4:Tm, Yb, and Gd luminescent nanorod/silica nanosphere-based thin films are applied on CH3NH3PbI3 PSCs to improve the device efficiency. The film was fabricated by spin coating an aged silica sol containing NaYF4:Tm, Yb, and Gd luminescent nanorods. The size and the spectral conversion properties of the NaYF4:Tm, Yb, and Gd luminescent nanorods were controlled by tuning the Gd3+ ion concentration. The microstructure and the transmittance properties of the thin film were controlled by changing the concentration of NaYF4:Tm, Yb, and Gd luminescent nanorod in silica sol. The thin films have excellent spectral conversion properties while exhibiting a maximum transmittance. The photovoltaic performance of PSCs with NaYF4:Tm, Yb, and Gd luminescent nanorod/silica nanosphere-based thin films was systematically investigated. The light transmittance was optimized to 95.1% on a cleaned glass substrate, which resulted in an average increase of about 3.0% across the broadband range of 400-800 nm. The optimized films widen the spectrum of light absorbed by conventional PSC cells and reduce reflections across a broad range, enhancing the photovoltaic performance of PSCs. As a result, the PCE of the PSC increased from 14.51% for the reference device without a thin film to 15.67% for the PSC device with an optimized thin film. This study presents a comprehensive solution to the problem of Fresnel reflection and spectral response mismatch of the PSCs, which provides new ideas for the light management of PSCs.

Research on virtual color restoration algorithm for printmaking art images based on semantic segmentation and convolutional neural network

Abstract In this paper, semantic segmentation based on a convolutional neural network is used to guide the image color restoration process. In order to avoid the problem of content mismatch, higher-order features are first extracted from the basic dimensions of the input image, and the convolutional operation is done on the feature map by the excitation function. Then the network parameters are optimized and updated by the backpropagation algorithm to minimize the error between the prediction result and the real result. Finally, in image processing, the dilated convolution technique is introduced to perform noise reduction on the semantic segmented image pixels to optimize the restoration quality. In order to prove the effectiveness of the method in this paper, an experimental analysis of the method is conducted. The experimental results show that the peak signal-to-noise ratio of the model proposed in this paper is higher than 42.986db on average, the structural similarity reaches 0.8%, and the fit is around 0.75. And its color difference can reach at least 11.2% with the increase of iterations. It indicates that the reduction algorithm of semantic segmentation and convolutional neural network greatly improves the accuracy of color reduction results and can obtain printmaking images with higher color quality.

Design optimization of energy systems for zero energy buildings based on grid-friendly interaction with smart grid

Zero-energy buildings usually achieve annual net-zero energy balance by generating electricity using on-site renewable energies and interconnecting with the power grid. However, the impact of energy mismatch problem in zero-energy buildings design on the grid is often overlooked, which potentially compromises grid's stability. To address this issue, this paper presents an optimization design method based on "grid-friendly interaction" which optimizes the energy system of zero-energy buildings to ensure better alignment between the building's electricity purchase/sale and grid demand. In this study, an indicator of "grid-friendly interaction", which represents the ratio of the net building friendly interaction power to the total annual interaction power, is firstly established to guide buildings in improving their interaction with the grid. Next, the energy supply, demand, and storage schemes of renewable energy systems in the zero-energy building are iteratively adjusted to achieve the best match with grid's expectations. This optimization design method was applied to a practical case in Hong Kong. Results show that, compared to the benchmark building, the optimal system design scheme increases grid friendliness by 83 %, reduces carbon dioxide emissions by 77 %, but also incurs a total cost increase of 180 %. The optimization design method proposed in this paper can effectively mitigate the impact of zero-energy buildings on the power grid, fostering enhanced interplay between the building structures and the grid. The study significantly contributes to the advancement of exploring the potential for energy flexibility in zero-energy buildings, which is of great significance for the safe and stable operation of future grids. The purpose of this study is to explore the energy flexibility potential of zero-energy buildings, which is of great significance for the safe and stable operation of future grids.

Robust Adaptive Beamformer Based on Constant Modulus Penalty Criteria

In this study, a robust adaptive beamformer based on constant modulus (CM) criteria is developed to improve the robustness of the array beamforming, which is a reconstructing minimal optimization for solving the mismatch problem of weight vector caused by steering vector mismatch. In the global positioning system (GPS) L1 band, firstly, a GPS array signal is modelled by designing a dual-polarized antenna array. Secondly, the distortion problem of beamforming is formulated in the traditional minimum variance distortionless response (MVDR) beamformer. For repairing the weight vector mismatch problem, a novel beamformer based on the CM envelope response is proposed to reconstruct MVDR beamforming in the array processing. Besides, min-max penalty criteria are used to enable the beamformer to allocate more degrees of freedom (DOFs) when penalizing the MVDR beamformer responses. Finally, an auxiliary two-element real variable is designed to plan the proposed beamformer. But it is still a nonconvex quadratic programming problem, so an alternating direction method of multipliers (ADMM) is employed to transform the objective function into several subproblems. Illustrative numerical simulation results are provided for validating the effectiveness of the proposed beamformer by comparing it with other existing approaches.

Automatic Loss Function Search for Adversarial Unsupervised Domain Adaptation

Unsupervised domain adaption (UDA) aims to reduce the domain gap between labeled source and unlabeled target domains. Many prior works exploit adversarial learning that leverages pre-designed discriminators to drive the network for aligning distributions between domains. However, most of them do not consider the degeneration of the domain discriminators caused by the gradually dominating gradients of aligned target samples during training, and they still suffer from the cross-domain semantic mismatch problem in the learned feature space. Hence, this paper attempts to understand and solve both issues from the lens of optimization loss and propose an automatic loss function search for adversarial domain adaptation (ALSDA). First, we extend the common adversarial loss by adding an adjustable hyper-parameter that can re-weight the gradients assigned to target samples, so that the domain discriminator can impose consecutive and influential driving forces for domain alignment. Meanwhile, we upgrade the traditional orthogonality loss with class-wisely adjustable hyper-parameters that can strengthen the cross-domain feature separation. Since manually determining the optimal loss functions requires expensive expert efforts, we leverage the popular AutoML to automatically search for the optimal loss functions from a pre-defined novel and unique search space for UDA. Further, to enable the loss function search when the target domain is unlabeled, we introduce a simple-but-effective entropy-guided search strategy with the aid of REINFORCE learning. Extensive experiments on various typical baselines and benchmark datasets such as Office-Home, Office-31, and Birds-31 have been conducted, and the results validate the generalization and superiority of the proposed ALSDA.

Shift-variant deconvolution beamforming using Implicit Neural Representation for near-field acoustic image measurement

The conventional beamforming (CBF) output can be expressed as a convolution of the source distribution and the array dependent point spread function (PSF), which is defined as the response of the beamformer to a point source. The resolution and accuracy of sound source localization can be improved by deconvolution of CBF. The shift-invariant PSF assumption is only a good approximation when the source region is small compared to the distance between the array and the source. However, the PSF of the near-field underwater acoustic map measurement is shift-variant, whose mismatch with the beam could lead to performance degradation. In this paper, we proposed an optimized deconvolution method by using the neural network called implicit neural representation (INR) to solve the beam mismatch problem, due to its strong performance in learning and reconstructing spatial scenes. Rather than recompute the PSF for each pixel in the scene, INR predicts the complex-valued weight matrix in two-dimensional space that encapsulates both the spatially varying properties of the PSF and the scatter distribution of the scene. Numerical simulations and experimental results verify the effectiveness of our method. And this work can be broadly applied to arrays with shift-variant PSFs.

A Systematic Review of Automated Query Reformulations in Source Code Search

Fixing software bugs and adding new features are two of the major maintenance tasks. Software bugs and features are reported as change requests. Developers consult these requests and often choose a few keywords from them as an ad hoc query. Then they execute the query with a search engine to find the exact locations within software code that need to be changed. Unfortunately, even experienced developers often fail to choose appropriate queries, which leads to costly trials and errors during a code search. Over the years, many studies have attempted to reformulate the ad hoc queries from developers to support them. In this systematic literature review, we carefully select 70 primary studies on query reformulations from 2,970 candidate studies, perform an in-depth qualitative analysis (e.g., Grounded Theory), and then answer seven research questions with major findings. First, to date, eight major methodologies (e.g., term weighting, term co-occurrence analysis, thesaurus lookup) have been adopted to reformulate queries. Second, the existing studies suffer from several major limitations (e.g., lack of generalizability, the vocabulary mismatch problem, subjective bias) that might prevent their wide adoption. Finally, we discuss the best practices and future opportunities to advance the state of research in search query reformulations.

Computation-guided design of flexible piezoelectric composites by optimizing charge-stress transmission

Flexible piezoelectric materials have attracted increasing attention as active components in wearable and flexible electronics, soft robotics and artificial skins or muscles. Although constructing polymer-based composites is becoming a common solution to balance their piezoelectricity and flexibility, challenges associated with the electrical and mechanical mismatch between the polymer matrix and the ceramic fillers remain. Here, taking the piezoelectric composite of lead zirconate titanate-polydimethylsiloxane (PZT/PDMS) as the example, we perform phase-field simulations to spatially and temporally study the electrical and mechanical response. It is found that good connectivity of fillers could provide a load transfer path and break topological restriction of filler morphology on polarization dipoles. Then, we propose an interface design strategy to address the mismatch problem in ‘3–3’ composites, which could greatly enhance the overall piezoelectric response under different modes of compressing, stretching and bending. Finally, we experimentally fabricate high-performance flexible composites with an ultrahigh piezoelectric charge coefficient of 155 pC N−1 and a low Young’s modulus of 63 MPa. This research offers a promising route for designing flexible piezoelectric composites by synergistically regulating connectivity and mismatch problems, which is also expected to guide the optimization of other actuators or sensors related with electromechanical coupling effect.

Machine Translation of Electrical Terminology Constraints

In practical applications, the accuracy of domain terminology translation is an important criterion for the performance evaluation of domain machine translation models. Aiming at the problem of phrase mismatch and improper translation caused by word-by-word translation of English terminology phrases, this paper constructs a dictionary of terminology phrases in the field of electrical engineering and proposes three schemes to integrate the dictionary knowledge into the translation model. Scheme 1 replaces the terminology phrases of the source language. Scheme 2 uses the residual connection at the encoder end after the terminology phrase is replaced. Scheme 3 uses a segmentation method of combining character segmentation and terminology segmentation for the target language and uses an additional loss module in the training process. The results show that all three schemes are superior to the baseline model in two aspects: BLEU value and correct translation rate of terminology words. In the test set, the highest accuracy of terminology words was 48.3% higher than that of the baseline model. The BLEU value is up to 3.6 higher than the baseline model. The phenomenon is also analyzed and discussed in this paper.

State estimation for one‐dimensional agro‐hydrological processes with model mismatch

AbstractThe importance of accurate soil moisture data for the development of modern closed‐loop irrigation systems cannot be overstated. Due to the diversity of soil, it is difficult to obtain an accurate model for the agro‐hydrological system. In this study, soil moisture estimation in one‐dimensional (1D) agro‐hydrological systems with model mismatch is the focus. To address the problem of model mismatch, a nonlinear state‐space model derived from the Richards equation is utilized, along with additive unknown inputs. The determination of the number of sensors required is achieved through sensitivity analysis and the orthogonalization projection method. To estimate states and unknown inputs in real‐time, a recursive expectation maximization (EM) algorithm derived from the conventional EM algorithm is employed. During the E‐step, the extended Kalman filter (EKF) is used to compute states and covariance in the recursive Q‐function, while in the M‐step, unknown inputs are updated by locally maximizing the recursive Q‐function. The estimation performance is evaluated using comprehensive simulations. Through this method, accurate soil moisture estimation can be obtained, even in the presence of model mismatch.

Research on the Impact of Tourism on the Urban-rural Income Disparity and Countermeasures

At present, the most important issue for economic development is how to ensure the coordinated development of all aspects. At present, the country's focus has shifted from all-round moderate prosperity to the issue of average development. Therefore, how to ensure and implement the average of resources and the exploration of implementation plans are currently more important research. Tourism is a recent emerging economic industry and plays a great role in promoting China's economic level. Starting from the current development status of China, this paper comprehensively analyzes whether tourism will affect the income difference between urban and rural residents through literature retrieval and case analysis. Explore how this element can be positively promoted. After research, we conclude that the development of tourism can indeed promote the balance of urban and rural development, but at the same time, it will also cause the problem of improper resource development and mismatch between the speed of tourism development. Therefore, countries need to respond to the situation. For example, strengthen the management of tourism resources, strengthen the publicity and governance of scenic areas, and so on. These optimization policies will definitely effectively alleviate and optimize the existing differences and differences, and realize the average quality of life of residents as soon as possible.

Optimization model for home energy management system of rural dwellings

In the context of the increasing popularity of distributed energy, this paper proposes a home energy management system method considering the working state of flexible load to deal with the problem of mismatch between home energy supply and demand. Specifically, in this paper, the flexible load in the system is studied, and the model of flexible load and its working state are established. On this basis, combined with the real-time electricity price of the grid, the model of home energy management system is constructed to minimize the electricity purchase cost and improve the utilization rate of renewable energy, the genetic algorithm is used to solve it, and the influence of time step, flexible load ratio and whether to use energy storage equipment on the optimization degree of the model are analyzed. The research results show that, while meeting the requirements of human comfort and electricity demand, the daily electricity purchase cost of the system with flexible load scheduling is 22.5% lower than that of the system without flexible load scheduling, and the utilization rate of renewable energy is increased by 16.5%. In terms of model optimization, shortening the prediction time step, increasing the proportion of flexible load and using energy storage equipment can further reduce the electricity purchase cost. The case study confirms the effectiveness of the proposed home energy management system model, which can provide an efficient optimal scheduling scheme for household energy saving.