Matching Degree Research Articles

Research on the Innovation of Piano Music Teaching in Colleges and Universities Based on the Characteristics of Music Culture

Abstract Starting from the communication characteristics of piano music culture in colleges and universities, this paper proposes a piano music signal detection technology that includes two parts: note onset and fundamental frequency detection. Based on the characteristics of the harmonic structure of the music signal, the degree of harmonic matching between the signal to be recognized and the standard note signal is calculated, and the task of multi-fundamental frequency estimation is accomplished by using the timbre characteristics and harmonic structure. The detection technology of piano music signals is applied to the recognition of teaching short notes, playing music and playing evaluation to get a new model of piano music teaching in colleges and universities. The results show that the algorithm in this paper can recognize piano music correctly by more than 91%, and the method has no obvious decrease in recognition rate in the process of gradually increasing noise, which is conducive to improving the effect of piano music teaching in colleges and universities.

Protein folding and mental health: The impact of protein misfolding on neurological disorders

Major depressive disorder (MDD), bipolar disorder (BD), and schizophrenia (SCZ) are psychiatric disorders that significantly impact an individual's ability to function effectively within society. MDD is characterized by persistent low mood, leading to symptoms such as anhedonia, feelings of worthlessness, and cognitive impairments. BD, another mood disorder, is typified by recurrent episodes of depression and mania or hypomania. The disorder is associated with increased risk of suicide, comorbid psychiatric conditions, and impaired functioning across various domains. SCZ, a severe psychiatric disorder primarily characterized by hallucinations, delusions, and disorganized thinking, affects approximately 1% of the global population. The cognitive, social, and occupational impairments associated with SCZ impose a substantial burden on affected individuals and their families. Even though it sounds like three completely different mental disorders, because of the high degree of matching of symptoms, we firmly believe that there is a relationship between these mental disorders. Protein folding is crucial for proper protein function, and misfolding can lead to neurodegenerative disorders. Through recent research findings, we found that the changes in A plaques and tau tangles appeared in the typical psychiatric diseases mentioned above. This paper explored the impact of protein misfolding, changes in A plaques, and tau tangles on neurological disorders, with a focus on depression, bipolar disorder, and schizophrenia, also examines the role of molecular chaperones in preventing misfolding and the impact of protein misfolding.

Radiation Force Modeling for a Wave Energy Converter Array

The motivation and focus of this work is to generate passive transfer function matrices that model the radiation forces for an array of WECs. Multivariable control design is often based on linear time-invariant (LTI) systems such as state-space or transfer function matrix models. The intended use is for designing real-time control strategies where knowledge of the model’s poles and zeros is helpful. This work presents a passivity-based approach to estimate radiation force transfer functions that accurately replace the convolution operation in the Cummins equation while preserving the physical properties of the radiation function. A two-stage numerical optimization approach is used, the first stage uses readily available algorithms for fitting a radiation damping transfer function matrix to the system’s radiation frequency response. The second stage enforces additional constraints on the form of the transfer function matrix to increase its passivity index. After introducing the passivity-based algorithm to estimate radiation force transfer functions for a single WEC, the algorithm was extended to a WEC array. The proposed approach ensures a high degree of match with the radiation function without degrading its passivity characteristics. The figures of merit that will be assessed are (i) the accuracy of the LTI systems in approximating the radiation function, as measured by the normalized root mean squared error (NRMSE), and (ii) the stability of the overall system, quantified by the input passivity index, ν, of the radiation force transfer function matrix.

Adaptive multi-mode control system for stability and tracking control of distributed drive automated electric vehicle

Conventional tracking control algorithms of Distributed Drive Automated Electric Vehicles (DDAEVs) are typically designed for a unique control mode, which may lead to poor lateral stability under various driving conditions. Aimed this problem, an Adaptive Multi-mode Control System (AMCS) is proposed. Firstly, according to the adhesion utilization between tires and road surface, the driving condition is classified into three categories, and three control modes corresponding to them are proposed. Secondly, an Adaptive Neuro-fuzzy Inference-based Mode Matching Control System (ANFI-MMCS) is constructed to calculate the matching degree between vehicle states and control modes. Then, in order to achieve the ideal distribution of road wheel angle and yaw moment while avoiding approaching the limit speed corresponding to the reference trajectory, a model predictive control trajectory tracking controller and a speed controller with limitations were built. Finally, to achieve smooth switching between control modes, the outputs of AMCS are weighted according to the matching degree. In the experimental section, AMCS is evaluated on Carsim-Simulink co-simulation platform, and the results under different tests reveal that the proposed controller is more adaptable.

Movie Recommendation System Based on Machine Learning

In today’s era, with the growth of businesses on an individual basis, many applications are trying to provide more effective services to individual users, and eventually launched personalized services. Simply put, when a user enters certain keywords in a search engine, the recommendation system can push certain information or products to the user. Based on this principle, there are personalized recommendation videos on the homepage of short video platforms, and various music software have launched personalized radio stations. Even if you want to watch a movie on Netflix, it can recommend it to you. These applications are all looking for similar content in the content that users are interested in and recommending it. A simple movie recommendation system only matches similar movies through user history records, and the accuracy of matching is not high and easily affects efficiency. Therefore, a simple movie recommendation system can no longer meet user needs. The movie recommendation system that incorporates Spark and machine learning algorithms can better serve the public. This article will explore the impact of adding different algorithms to machine learning content on the matching degree of recommended content.

How does urbanization impact the supply–demand relationship of agroecosystem services? Insights from farmland loss in the Huaihe River Basin, China

China’s urbanization has gradually become the dominant factor in farmland loss, but it remains unclear how urbanization impacts the supply–demand relationship of agroecosystem services at different rates of farmland loss, which in turn poses new challenges to the ecological security of farmland. Taking the Huaihe River Basin as a case, this paper analyzes farmland loss from 2000 to 2020, as well as changes in the supply–demand relationship of four types of agroecosystem services: food production, socio-economic security, carbon sequestration, and soil conservation, revealing the driving mechanisms of urbanization on the supply–demand relationship of agroecosystem services in sub-regions with different rates of farmland loss. The results show that: (1) A total of 13588.11 km2 of farmland was converted to construction land from 2000 to 2020, accounting for 75.62 % of the total amount of farmland converted to different land types, and 95.57 % of the total amount of farmland converted to construction land. (2) There was a surplus supply of grain production services and socio-economic security services, while there was a deficit in the supply of carbon sequestration services, and a balance in the supply–demand of soil conservation services. (3) The matching degree of supply–demand for agroecosystem services was lower in the Rapid Loss Area compared to the Medium Loss Area and Slow Loss Area. (4) Urbanization was divided into population, economic, and spatial urbanization. The supply–demand relationships of agroecosystem services were impacted greatly by spatial urbanization in the Rapid Loss Area and by economic urbanization in the Medium Loss Area and Slow Loss Area.

Screening and optimization of metal-insulator-metal selective emitter in thermophotovoltaic system

In thermophotovoltaic (TPV) systems, it is crucial that the selective emitters can tailor emission spectrum to match the bandgap of photovoltaic (PV) cells and largely enhance the system efficiency. In this work, a metamaterial emitter based on the metal-insulator-metal (MIM) structure is proposed to obtain the high energy conversion efficiencies. The geometric parameters of MIM emitter have been investigated to obtain an excellent radiation spectrum of emitter composed of W and HfO2. The excellent emission performance of MIM emitter is attributed to the excitation of surface plasmon polariton (SPP) and cavity resonance, and the structure of MIM emitter is insensitive for different polarization modes. The 21 material combinations of MIM emitters have been screened to obtain the optimal emitter matching GaSb and InGaAsSb cells. This work identifies the crucial role of structure and materials into the emitter of a TPV system. In the evaluation of MIM emitter and TPV System, when the operating temperature of emitter increases from 1400[Formula: see text]K to 2000[Formula: see text]K, the system efficiency of optimal W/HfO2/W MIM emitter increases from 20.26% to 30.41%, while the output electric power increases from 3.59[Formula: see text]kW/m2 to 42.48[Formula: see text]kW/m2. The phenomenon indicates that the MIM emitter with the optimal material combinations and geometric parameters can significantly improve the matching degree with GaSb and InGaAsSb cells. Our results will be helpful to expand the optimization scope of metamaterial emitters in TPV systems.

Application of Deep Neural Network and Human-Computer Interaction Technology Based on Multimodal Perception in Art Design

Abstract The essence of art design is the process of emotional interaction with humans. In this paper, emotions are classified using multimodal fusion features, and abstract fusion features are obtained by sampling the multimodal matching tensor using average pooling. The matching fusion matrix in the tensor operator is used to convert from two-modal to multi-modal matching. Virtual interaction model in art design controls the design objectives, and the optimized virtual world is constructed by using virtual reality technology, so as to build an immersive art design model. Finally, a study was conducted to examine the impact of the use of emotion perception and interaction technology in art product design with students from the School of Design and Art, University of G. The results show that the liking degree of three-color matching in the cognitive experiment test is 0.307, which is higher than the liking degree of two-color matching of 0.223, indicating that overall three-color matching samples are more popular in art design. This study provides effective evaluation and guidance for designing art products that are emotional and innovative.

Robust Elastic Full-Waveform Inversion Based on Normalized Cross-Correlation Source Wavelet Inversion

The elastic full-waveform inversion (EFWI) method efficiently utilizes the amplitude, phase, and travel time information present in multi-component seismic recordings to create detailed parameter models of subsurface structures. Within full-waveform inversion (FWI), accurate source wavelet estimation significantly impacts both the convergence and final result quality. The source wavelet, serving as the initial condition for the wave equation’s forward modeling algorithm, directly influences the matching degree between observed and synthetic data. This study introduces a novel method for estimating the source wavelet utilizing cross-correlation norm elastic waveform inversion (CNEWI) and outlines the EFWI algorithm flow based on this CNEWI source wavelet inversion. The CNEWI method estimates the source wavelet by employing normalized cross-correlation processing on near-offset direct waves, thereby reducing the susceptibility to strong amplitude interference such as bad traces and surface wave residuals. The proposed CNEWI method exhibits a superior computational efficiency compared to conventional L2-norm waveform inversion for source wavelet estimation. Numerical experiments, including in ideal scenarios, with seismic data with bad traces, and with multi-component data, validate the advantages of the proposed method in both source wavelet estimation and EFWI compared to the traditional inversion method.

Research on the Application of NbS in Watershed Ecological Restoration: A Case Study of Jiulong River Watershed Shan-Shui Initiative

Nature-based solutions (NbS) rapidly develop globally to address societal challenges and provide human well-being and biodiversity. Watershed restoration plays an essential role in enhancing the ecological and socio-economic benefits of the region. The design and implementation of watershed restoration projects are crucial to their effectiveness, and NbS has been applied as a concept in ecosystem-related projects. This paper proposes an evaluation method to assess the implementation of the Shan-Shui Initiative in the Jiulong River Watershed restoration projects based on the eight criteria proposed by the International Union for the Conservation of Nature (IUCN) Global Standard for Nature-Based Solutions. The aim is to standardize the implementation process of watershed restoration projects to achieve more significant benefits and practically apply the concept of NbS in watershed restoration. The implementation scheme of the Shan-Shui Initiative in the Jiulong River Watershed is designed to evaluate and improve the design and implementation scheme of ecological restoration projects in the actual basin. According to the assessment results, the degree of matching based on NbS for the implementation scheme of the Jiulong River Watershed Shan-Shui Initiative is 73%, which meets the criteria of NbS but needs to be improved in terms of monitoring and assessment, synergistic management, and benefit trade-offs.

Cascading failure mechanism of major drainage system in mountainous city: Taking the basin of the main urban area of Chongqing as an example, China

Failure of major drainage systems is almost always accompanied by waterlogging. Understanding the operation and failure mechanism of major drainage systems is an important prerequisite for understanding and managing waterlogging. The natural and artificial environments in mountainous cities are more complex, and the major drainage system, as an open system for excessive surface runoff discharge and storage, is more prone to local overload and cascading failure. Existing theories and methods are difficult to explain and analyze the cascading failure characteristics and principles of major drainage systems in mountainous cities. Based on the complex network technology and the principle of runoff balance, the cascade failure model of major drainage system was constructed, and the characteristics and laws of cascade failure under six kinds of terrain, six kinds of short duration rainstorm and two kinds of surface environments were quantitatively analyzed. Research has found that the cascading failure of major drainage systems and waterlogging in mountainous cities should be the same phenomenon from different perspectives, and the simulated matching degree between the two can reach 79.5%. Meanwhile, 456 potential waterlogging locations were discovered in the study area, which is much larger than the actual 73 locations. When urban construction and rainfall conditions change, these unstable potential waterlogging locations are easily apparent. Among them, terrain is the main factor restricting the cascading failure of major drainage systems. Low lying valley areas often quickly accumulate a large amount of overflow, while flat areas are prone to overflow spreading to the surrounding areas; Slope areas are not prone to overflow, but are prone to local flooding. The change of short duration rainstorm and the difference of surface environmental openness will further interfere with the cascade failure of the major drainage system. The longer the return period of the short duration rainstorm or the increase of the peak value of the rainfall pattern, the greater the discharge and storage pressure of the major drainage system per unit time, resulting in intensified waterlogging. The open and unobstructed surface environment will lead to the small-scale spread of waterlogging, but this will significantly reduce the overall degree of waterlogging in the late rainstorm. The study revealed the spatiotemporal principles and basic laws of cascading failure of major drainage systems in mountainous cities. The conclusion is helpful for mountainous cities to formulate urban construction management strategies and climate change adaptation strategies, and to cope with current and future potential waterlogging disasters.

Consensus Model of Social Network Group Decision-Making Based on Trust Relationship Among Experts and Expert Reliability

Due to people's increasing dependence on social networks, it is essential to develop a consensus model considering not only their own factors but also the interaction between people. Both external trust relationship among experts and the internal reliability of experts are important factors in decision-making. This paper focuses on improving the scientificity and effectiveness of decision-making and presents a consensus model combining trust relationship among experts and expert reliability in social network group decision-making (SN-GDM). A concept named matching degree is proposed to measure expert reliability. Meanwhile, linguistic information is applied to manage the imprecise and vague information. Matching degree is expressed by a 2-tuple linguistic model, and experts' preferences are measured by a probabilistic linguistic term set (PLTS). Subsequently, a hybrid weight is explored to weigh experts' importance in a group. Then a consensus measure is introduced and a feedback mechanism is developed to produce some personalized recommendations with higher group consensus. Finally, a comparative example is provided to prove the scientificity and effectiveness of the proposed consensus model.

The Operational Mechanism of Agricultural Products Supply Chain Finance Based on the Mode-Capability-Customer Matching Approach

The key to successful agricultural product supply chain finance of commercial banks lies in coordinating the relationship among the “supply chain finance model”, “banking serviceability”, and “user satisfaction”. Previous research on agricultural products supply chain finance rarely incorporated the operational level of commercial banks. To fill this gap, this paper transforms the operational problem of the agricultural product supply chain finance of commercial banks into a matching problem between the agricultural product supply chain finance model and customers under the constraint of serviceability. First, a matching model of “mode-capability-customer” of agricultural products supply chain finance is constructed based on the theory of bilateral matching; second, a measurement index system of matching degree and satisfaction is constructed, where matching degree and satisfaction are calculated; finally, the optimal matching model is studied. This paper proposes a model that matches agricultural supply chain finance with customer satisfaction, considering bank serviceability constraints. It improves the implementation of agricultural product supply chain finance by commercial banks. The study uses surveys and evaluations to assess stakeholder satisfaction and preferences. An operational research model optimizes the matching process between supply chain finance models and recipients, ensuring suitability. The paper provides a theoretical basis for rural financial services and practical recommendations for commercial bank supply chain finance, with valuable real-world applications.

Service Recommendation Method based on Multi Model Fusion

<p>In recent years, the rapid development of service-oriented computing technology has increased the burden of choice for software developers when developing service-based applications. Existing Web service recommendation systems often face two challenges. First, developers are required to input keywords for service search, but due to their lack of knowledge in the relevant field, the keywords entered by the developers are usually freestyle, causing an inability to accurately locate services. Second, it is exceedingly difficult to extract services that meet the requirements due to the 99.8% sparseness of the application service interaction records. To address the above challenges, a framework for service recommendation through multi-model fusion (SRM) is proposed in this paper. Firstly, we employ graph neural network algorithms to deeply mine historical records, extract the features of applications and services, and calculate their preferences. Secondly, we use the BERT model to analyze text information and use the attention mechanism and fully connected neural networks to deeply mine the matching degree between candidate services and development requirements. The two models mentioned above are further merged to obtain the final service recommendation list. Extensive experiments on datasets demonstrate that SRM can significantly enhance the effectiveness of recommendations in service recommendation scenarios.</p> <p> </p>

Hong–Ou–Mandel interference of spin–orbit hybrid entangled photons

Structured photons are a crucial resource in both classical and quantum technologies, particularly in spin–orbit hybrid photons, enabling various practical applications ranging from ultra-sensitive metrology techniques to quantum-enhanced information processing tasks. However, the two-photon interference of spin–orbit hybrid photons, which combines polarization modes and complex transverse spatial structures across the beam profile, remains unexplored. Here, we present an experimental observation of Hong–Ou–Mandel (HOM) interference of spin–orbit hybrid photons. The tunable q-plates that work as spin–orbit coupler devices are used to prepare various forms of spin–orbit hybrid entangled photons. By harnessing the match degree in the temporal domain, the coalescence and anti-coalescence effects resulting from the symmetric and anti-symmetric properties of the incident quantum states are observed. Moreover, we demonstrated the feasibility of quantum-enhanced photon polarization gears through HOM interference and theoretically analyze the noise-resilient advantages based on coherent HOM measurements. These results provide an alternative route toward quantum experiments with structured photons that allows for controlling their quantum interference in a compact, stable, and efficient way.

Benefit allocation of electricity–gas–heat–hydrogen integrated energy system based on Shapley value

Abstract The integrated energy system is an important development direction for achieving energy transformation in the context of the low-carbon development era, and an integrated energy system that uses renewable energy can reduce carbon emissions and improve energy utilization efficiency. The electric power network and the natural gas network are important transmission carriers in the energy field, so the coupling relationship between them has been of wide concern. This paper establishes an integrated energy system considering electricity, gas, heat and hydrogen loads; takes each subject in the integrated energy system as the research object; analyses the economic returns of each subject under different operation modes; applies the Shapley value method for benefit allocation; and quantifies the contribution value of the subject to the alliance through different influencing factors to revise the benefit allocation value. Compared with the independent mode, the overall benefits of the integrated energy system increase in the cooperative mode and the benefits of all subjects increase. Due to the different characteristics of different subjects in terms of environmental benefits, collaborative innovation and risk sharing, the benefit allocation is reduced for new-energy subjects and increased for power-to-gas subjects and combined heat and power generation units after revising the benefit allocation, to improve the matching degree between the contribution level and the benefit allocation under the premise of increased profit for each subject. The cooperative mode effectively enhances the economic benefits of the system as a whole and individually, and provides a useful reference for the allocation of benefits of integrated energy systems. The analysis shows that the revised benefit distribution under the cooperative model increases by 3.86%, 4.08% and 3.13% for power-to-gas subjects, combined heat and power generation units, and new-energy units, respectively, compared with the independent function model.

A New Approach on Bipolar Second Degree Perfect Fuzzy Matching for Bipolar Fuzzy Graphs Based on Vertices

Graph is a visual representation of data. In mathematics, graph is a structure which creates the pairwise relation between objects. The objects are known as nodes or vertices and the connection between two nodes are known as links or edges. A graph is a symmetric binary relation on a non-empty set whereas Fuzzy graph is a symmetric binary fuzzy relation on a fuzzy subset. Bipolar Fuzzy graph is a generalization of graph theory by using bipolar Fuzzy set. The bipolar Fuzzy sets are the extension of Fuzzy sets. Our main objective is to introduce Bipolar Second Degree Perfect Fuzzy Matching for Bipolar Fuzzy Graph based on vertices. Secondly, we proved the necessary conditions under which they are equivalent and also proved that for a particular condition a perfect second-degree fuzzy matching is not a regular bipolar fuzzy graph. Next, we discussed about perfect second-degree Fuzzy matching and second degree fuzzy matching number for bipolar fuzzy graph on the cycle.

On the Hybrid Modelling of Rigid Sonic Crystal Embedded in Plenum Chamber at Low Frequencies Using the Effective Medium Approach and Finite Element Method

This study explores the application of homogenization schemes in modelling acoustic wave propagation in a finite array of circular scatterers embedded into a 2D cavity. The cavity is integrated into the 2D waveguide attached to the cavity inlet and outlet. Square-lattice sonic crystal (SC), composed of rigid and radially symmetric circular cylinders, is used to represent the finite array in this study. The model is aimed at informing the novel designs of plenum windows with superior soundproofing performance. The sound transmission performance is analysed with hybrid numerical simulation using the Finite Element Method (FEM) and homogenization scheme. A theoretical homogenization method based on the Effective Medium Approach (EMA) is reviewed and implemented on the modelling of the SC array inside the cavity at low frequencies and then implemented in FEM. Comparison of the transmission loss (TL) reveals a high degree of matching between settings with and without homogenization at low-frequency range. It is observed that performance of the hybrid model maintains a high degree of matching provided the cavity modes are dominated by a single characteristic scale in the low frequency. This includes the case of a narrow plenum chamber with only a single cylinder placed inside the cavity with a width of one lattice constant. This homogenization method is proven to be more computationally efficient in FEM compared to the modelling of exact geometry of the problem.

6DOF pose estimation of a 3D rigid object based on edge-enhanced point pair features

The point pair feature (PPF) is widely used for 6D pose estimation. In this paper, we propose an efficient 6D pose estimation method based on the PPF framework. We introduce a well-targeted down-sampling strategy that focuses on edge areas for efficient feature extraction for complex geometry. A pose hypothesis validation approach is proposed to resolve ambiguity due to symmetry by calculating the edge matching degree. We perform evaluations on two challenging datasets and one real-world collected dataset, demonstrating the superiority of our method for pose estimation for geometrically complex, occluded, symmetrical objects. We further validate our method by applying it to simulated punctures.

The nutritive quality comparison of the processed fresh sweet-waxy corn from three regions in China

This study established a nutritive evaluation system to assess fresh sweet-waxy corn and compare the differences in nutritive quality between frozen fresh and vacuum fresh corn. The evaluation system was divided into five parts according to nutrients: (1) fatty acids quality assessed by the fatty acid profiles, nutritional indices, and factor analysis; (2) amino acids evaluation system including amino acids profiles, chemical evaluation indices, amino acids standard spectra, fresh corn and human needs’ matching degree, flavor evaluation, and factor analysis; (3) vitamins and (4) carbohydrates which were evaluated according to their content, (5) minerals quality were decided by content and recommended nutrient intake. Results demonstrated these nutrients had significant differences between the two processing methods. The quality of the fresh corn in different processing methods was examined from a nutritional perspective, and the results would provide reference to the fresh corn nutritive evaluation system’s establishment.