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Paper-cut elements in the design of boat space can effectively improve the homogenisation tendency of existing boat space design, effectively enhance the characteristics of traditional Chinese culture and enrich the development ideas of boat space design. Therefore, based on the Chinese folk art of paper cutting, this paper combines theoretical analysis and empirical research to deeply analyse the artistic expression of paper-cut elements in the spatial design of boats. This paper mainly studies the artistic integration of paper-cut elements in the decorative design of boats and the artistic integration of paper-cut elements in the practical design of boats. Through the calculation and analysis of the sparse autoencoder algorithm model, it can be seen that the decorative integration of paper-cut elements in wallpaper is 82%, which is higher than that of traditional materials (24%). The integration of paper-cut elements in the space design of cabins and guest rooms is as high as 97% and 94%, respectively, which is far better than the integration of traditional materials in the space design of cabins and guest rooms. This shows that the application of folk paper-cut elements to the space design of boats not only highlights the theme of boats but also enhances the cultural value of boats.

English is a universal language and is widely used. In order to deepen the cognition of language, this paper proposes to analyse the variation of metadiscourse verb patterns in English academic papers from within and between disciplines. By comparing the metadiscourse chunks used in various disciplines, it is concluded that there are obvious differences in the verb types of the subject papers. Analysing various identification algorithms of verb types, it is obtained that the combination of the word movement distance (WMD) model and the R&L density peak clustering algorithm is the best. Using the R&L density peak clustering, identification parameters are easy to determine, and when combined with the WMD model to calculate the similarity of words, it improve the accuracy of verb pattern clustering. By comparison, it is proved that the accuracy of the algorithm combining the WMD model and R&L density peak clustering reaches 30.06%, and the effect of identifying verb pattern variation is the best.

To deeply analyze the performance of paper-cutting elements in interior space design, this paper explores the artistic expression of paper-cutting elements. The BIM model is constructed based on the TVL algorithm, and a noise-reducing style migration method with an additional total variable loss function is used to fuse the texture features of a specific paper-cutting style so that the paper-cutting texture is generated in the target object area more intensively. The algorithm is supplemented with a U-shaped network structure to obtain the mask map of the target object, modify and expand the ScanNet training data set, and input a content map and a style map to generate the stylized paper cutout image automatically. The results show that compared with other elements, the stability of paper-cut elements reaches 96.31%, the image smoothness reaches 89.34%, and the retention of significant regions reaches 93.26%. In modern design, the peak signal-noise of paper-cut elements improved by 13.418d on average, the structural similarity also improved by 0.34807, and the recognition rate of paper-cut elements in the furnishing category reached 95%. Applying paper-cut art in interior space design can give interior furnishing design better visual effects, provide inspiration and ideas for interior space design innovation, and contribute to improving aesthetics.

In this paper, through the collection and analysis of data, the art of Guangling paper-cutting is theoretically researched, and the general features and shapes of Guangling paper-cutting are summarized. In order to overcome the limitations of traditional algorithms in the extraction of features of Guangling paper-cutting, the combination of spatial pyramid matching and context-dependent histogram methods are used to extract the shape features of paper-cutting images with stronger differentiation. The support vector machine is used to solve the problem of recognizing and classifying the image patterns in the digitized display. The design of the digital promotion of the Shanxi Guangling paper-cutting brand is carried out. Research variables are designed to analyze the effect of digital transformation and promotion of paper-cutting brands. The results show that the discrepancy of Guangling paper-cutting features extracted by the algorithm in this paper is very low, the e1 difference is maintained within 0.1, and the total recognition rate of SVM on Guangling paper-cutting features can reach 88.06%, and the overall effect is more satisfactory, and the regression equation of the influence of paper-cutting = −0.807+0.111*history+0.122* style+0.234*paper-cutting+0.216*display+0.136 * linkage, and propose strategies to enhance the influence of paper-cutting brand. The technical methods used in this study guarantee the quality of the digital transformation of Guangdong paper-cutting from the source.

The study of metadiscourse word resources is an important way to reveal academic knowledge constructs and genre features in English papers. This paper selects intra- and interdisciplinary English academic papers as data samples, and the text representation is based on the vector space model. The text similarity is calculated using the word movement distance model to complete the clustering based on the density peak, and then the semantic annotation of metadiscourse verb patterns is performed using the conditional random field. Then, the intra- and interdisciplinary metadiscourse annotations are compared to analyze the variation of verb patterns. The intra-disciplinary variation of metadiscourse verb patterns was mainly found using attitude markers, where the log-likelihood ratios of 48.56, 30.25, and 35.64 were obtained for affirmative, critical, and critical declarative attitudes, respectively. In interdisciplinary studies, basic disciplines preferred to use verb patterns as transitions, while applied disciplines preferred to express the author’s point of view. The study of metadiscourse verb patterns effectively enriches the linguistic resources in academic English teaching and deepens the understanding of the characteristics of disciplinary essay genres.

In the realm of Chinese traditional arts, paper-cutting symbols embody deep-seated aesthetic and cultural values. Within the framework of artificial intelligence, the fusion of these conventional symbols with contemporary pattern design through intelligent reconstruction processes promotes innovation in modern design. This paper introduces a novel pattern feature extraction algorithm specifically designed for identifying and extracting the essence of traditional paper-cutting art. Utilizing Deep Convolutional Generative Adversarial Networks (DCGAN), an automated method for generating woven patterns is developed, integrating conventional motifs with modern design elements. Additionally, a segmentation model based on DeepLabV3+ semantics is constructed to facilitate this integration. The study focuses on the fusion of traditional paper-cutting symbols with fabric patterns, providing a new direction for textile design research. The empirical evaluation involved seven experimenters who predominantly favored patterns that blended abstract and traditional styles, with the average style rating exceeding 3.2. Moreover, the color performance analysis of the reconstructed fabric patterns across five regions showed color difference values greater than 4, indicating superior color fidelity. These findings underscore the potential of combining AI-driven techniques with traditional art forms to enhance and revolutionize modern design practices.

This investigation delves into the evolving patterns and regional variances in industry-academia collaboration (IAC) within Functional Nucleic Acids (FNAs) research. Analyzing publications and patents from 1990 to 2021, we dissected IAC at individual and collective levels, documenting the count and share of IAC endeavors, key partners, and regional differences. Results indicate a rising trend in IAC publications and collaborating institutions, while patent trends display a mix of increases, decreases, and steady states. The United States leads in IAC activities, correlating with its prowess in scientific research and technological innovation. Notably, regional discrepancies in IAC are mainly due to intra-regional variations, with Asia and Europe experiencing the most pronounced disparities.

Leveraging artificial intelligence (AI), this study revolutionizes examination management and education in universities by developing an intelligent system encompassing comprehensive management, pre-examination activities, scheduling, and preparation. The system also features a quality management component for educational outcomes. An enhanced genetic algorithm introduces an adaptation function to optimize intelligent grouping, facilitating effective exam paper distribution. Applied at Y University, our innovative approach significantly refines exam paper difficulty (ranging between 0.5016 and 0.5581) and differentiation (0.3845 to 0.4596), showcasing the intelligent algorithm’s effectiveness in exam management and contributing valuable insights to educational research.

With the innovation and development of commercial shopping centers in China, the shopping environment is becoming more and more colorful. However, in today’s social environment, the central function of low-level consumption experience can no longer meet the needs of the masses. Therefore, in the design of indoor environment, we should start from a new perspective, focusing on the difference of internal space and the experience of consumption mode, so as to meet the development needs of commercial shopping in the future. Based on the research on the indoor environment of comprehensive commercial shopping center, comprehensive commercial shopping center in a certain area as the research target, the corresponding mathematical model was constructed, and using the measured method validation build the model of reliability and validity, thus obtains using CFD numerical simulation software of thermal and moisture environment of building an in-depth exploration, The effective countermeasures are put forward for the original air distribution mode. Comparing the improved scheme with the original scheme, it is found that the former can provide effective basis for the interior environment design of similar comprehensive commercial shopping malls.

Chaotic behaviour of dynamical systems, their routes to chaos, and the intermittency in particular are interesting and investigated subjects in nonlinear dynamics. The studying of these phenomena in non-smooth dynamical systems is of the special scientists’ interest. In this paper we study the type-III intermittency route to chaos in strongly nonlinear non-smooth discontinuous 2-DOF vibroimpact system. We apply relatively new mathematical tool – continuous wavelet transform CWT – for investigation this phenomenon. We show that CWT applying allows to detect and determine the chaotic motion and the intermittency with great confidence and reliability, gives the possibility to demonstrate intermittency route to chaos, to distinguish and analyze the laminar and turbulent phases.

Artificial intelligence (AI) and machine learning have become increasingly important in modern society and are poised to play an increasingly prominent role in education. This paper seeks to provide a theoretical framework for interrogating the integration of AI in education spaces. The paper argues that the eventual response of educators to recent developments in artificial intelligence is eerily like the earlier cycles of integrating ICT in education and, decades earlier, calculators into mathematics instruction. Premised on the argument that there are similarities between the calculator revolution in mathematics education and the ICT revolution in education several decades ago and the current ongoing developments in artificial intelligence, this paper offers a theoretical lens. The theoretical lens is composed of the Technology-Organization-Environment (TOE) framework, Technology Acceptance Model, Technological Pedagogical Content Knowledge, Socio-technical system theory, and Diffusion of Innovation theory. The paper concludes that despite spatial differences between the ICT revolution and the artificial intelligence revolution, there are shared similarities warranting adoption of a similar theoretical lens. Furthermore, factors that were considered pivotal in the integration of ICT are still relevant to the revolution of artificial intelligence. [ABSTRACT FROM AUTHOR]

Researching different solutions of nonlinear models has been interesting in different fields of science and application. In this study, we investigated different solutions of fourth-order nonlinear Ablowitz– Kaup–Newell–Segur wave equation. We have used the sine-Gordon expansion method (SGEM) during this research. We have given the 2D, 3D, and contour graphs acquired from the values of the solutions obtained using strong SGEM.

We extend the Boltzmann’s ideas that describe the evolution to the equilibrium of many body systems to the multifractal decomposition of the unitary interval 𝕀, in terms of sets Jα conformed by points with the same pointwise dimension, and obtain the D(α) singularity spectrum.

The study of everyday phenomena involving friction continues to maintain a high level of difficulty despite its long history. The causes of this problem lie in the different scale of the characteristics of the phenomenon, macroscopic and microscopic. Thus, very different models, valid in a narrow scope which prevents generalization, have been appearing. This survey presents the application of network simulation method to the numerical solution to the study of friction at very different scales. On the one hand, on a microscopic scale an atomic force microscope model has been studied, related to the analysis of soft surfaces at the atomic scale. Furthermore, on a macroscopic scale model related to the analysis of an industrial device, such as a brake mechanism has been studied. After presenting herein is a review of the different formulations of the friction force, the nature of the surfaces involved in the phenomenon, as well as the definition of the problems to be analyzed. The design of network models and the implementation of the initial conditions are explained. The results of the application of network models to selected problems are presented. In order to verify the reliability of the proposed models, their results are compared with the solutions obtained by other numerical methods or experimental results, one from a device developed during the preparation of this report.

We analyzed the first set of complete CCD light curves of the W UMa type eclipsing binary IK Boo in the BVRI bands by using the PHOEBE code and deduced its first photometric parameters with, mass ratio q = 0.648 and orbital inclination i = 63o. We have applied a spotted model due to the light curves asymmetry. The system shows a distinct O’Connell effect. The best solution fit to the light curves suggested the influence of star spot(s) on both components. Such presence of star spot(s) is common among the RS CVn and W UMa chromospheric active late type stars.

In this short paper, I recall the history of dealing with the lack of compactness of a sequence in the case of an unbounded domain and prove the vanishing Lions-type result for a sequence of Lebesgue-measurable functions. This lemma generalizes some results for a class of Orlicz–Sobolev spaces. What matters here is the behavior of the integral, not the space. [ABSTRACT FROM AUTHOR]

In this article, we have studied the uniqueness problem of Dirichlet series, which is convergent in a right half-plane and having analytic continuation in the complex plane as a meromorphic function sharing some sets and values. Our first result partially improve a result of [Ann. Univ. Sci. Budapest., Sect. Comput., 48(2018), 117-128] by relaxing the sharing conditions. Most importantly, we have pointed out a number of big gaps in a recent paper [J. Contemp. Math. Anal., 56(2021), 80-86], which makes the existence of the paper under question. Finally, under a different approach, we have provided the corrected form of the result of [J. Contemp. Math. Anal., 56(2021), 80-86] as much as practicable. [ABSTRACT FROM AUTHOR]

This paper is motivated by the paper [2]. The main aim of this paper is to extend the stability result from [16], related to the θ-Euler- Maruyama method (θ ∈ (12{1 \over 2}, 1)) for a class of neutral stochastic differential equations with time-dependent delay. The theta method is defined such that, in general case, it is implicit in both drift coefficient and neutral term. Sufficient conditions of the a.s. exponential stability of the θ-Euler-Maruyama method, including the linear growth condition on the drift coefficient of the equation, are revealed. The stability result is established for larger class of neutral terms than that considered in the second cited paper. An example is provided to support the main results of the paper.

The origin of sampled tissue and characteristics of healthy organs is important for potential abnormality detection in veterinary medicine. Most often such information is given during the sampling process, but in some cases there is a possibility of mislabeling, especially in the education sector where some microscopic preparations might be made by students without proper knowledge or the inspected tissues are not of fully known origin. Occasionally, it is possible to determine the affiliation by searching characteristics of the organ in a sample; however, this is not always possible even for a skilled professional as some tissues vary too little between their counterparts in different species or even in different organs of the same species. Because of this, an automatic system able to perform such classification in a fraction of a second and with high accuracy can be helpful in such cases, especially considering the low cost of adding that solution to the current workflow. This paper presents a new dataset for healthy organ classification based on light microscope imagery containing 25 abstract classes of different organs of a few species. During the sampling process, 3680 images of healthy tissues were collected. Additionally, a custom deep learning architecture was created that is able to classify those samples between organs and species with a validation accuracy reaching 98.34%. Such performance is in some cases higher than that of a human specialist, especially when some examples have very small visual differences between one another or the classification is made on previously non-determining regions of the organ. Additionally, the collection of such a dataset provides a great opportunity for further work containing abnormality detection as it already provides information on the healthy organ description, which can be used for a deep learning model searching for illnesses or mutations. What is more, such a dataset and the corresponding artificial neural network constitute one of the first solutions of this kind in veterinary medicine, as most state-of-the-art papers focus on human medicine.

In this paper we are focusing on finding the transcendental entire solution of Fermat-type trinomial and binomial equations, by restricting the hyper-order to be less than one. As the hyper-order is a crucial parameter that characterizes the growth of entire functions, it will be interesting to investigate this unexplored domain, as far as practible, with certain restriction on hyper order. Our results are the improvements of previous results reported in recent papers [12], [13]. We have provided a series of examples to demonstrate and validate the effectiveness of our proposed solutions.

The paper deals with the estimation of sensor faults for dynamic systems as well as the assessment of the uncertainty of the resulting estimates. For that purpose, it is assumed that the external disturbances are bounded within an ellipsoidal domain. This allows considering both stochastic and deterministic process and measurement uncertainties. Under such an assumption, a fault diagnosis scheme is developed with a prescribed convergence rate and accuracy. To achieve fault estimation, a conversion into an equivalent descriptor system is utilized. The paper provides a full stability and convergence analysis of the estimator including observability analysis. As a result, a set of complementary fault uncertainty intervals is obtained, which are minimized in such a way as to obtain a minimum detectable sensor fault. The final part of the paper exhibits a numerical example concerning fault estimation of a multi-tank system. The obtained results clearly confirm the performance of the proposed estimator expressed in the minimum detectable fault intervals.

The paper discusses the inventory management problem with a single product stored in two warehouses, where each has its unique suppliers with certain lead times. Moreover, one of the warehouses may act as a backup supplier for the other. In other words, product exchange between two different warehouses within one company is allowed. The first warehouse operates under an a priori known time-variant contractual demand and a bounded random one. Its secondary goal is to accumulate emergency stock that can be delivered to the second warehouse within one time period. For this warehouse we use a desired trajectory generator to shape the required stock level and then utilize a trajectory following control law. The demand in the second warehouse is unknown but bounded, and its suppliers have limited delivery capacity. The challenge is to fulfill the customers’ needs, although they might exceed the order limit. Therefore, occasional backup supplies from the first warehouse are necessary. For the control of the second warehouse, a simple sliding mode (SM) scheme is applied. The paper proves that, with appropriate compensation of the emergency deliveries in the first warehouse, our proposed control scheme ensures full demand satisfaction in both warehouses despite the second one’s control limit.

The paper proposes a non-iterative training algorithm for a power efficient SNN classifier for applications in self-learning systems. The approach uses mechanisms of preprocessing of signals from sensory neurons typical of a thalamus in a diencephalon. The algorithm concept is based on a cusp catastrophe model and on training by routing. The algorithm guarantees a zero dispersion of connection weight values across the entire network, which is particularly important in the case of hardware implementation based on programmable logic devices. Due to non-iterative mechanisms inspired by training methods for associative memories, the approach makes it possible to estimate the capacity of the network and required hardware resources. The trained network shows resistance to the phenomenon of catastrophic forgetting. Low complexity of the algorithm makes in-situ hardware training possible without using power-hungry accelerators. The paper compares the complexities of hardware implementations of the algorithm with the classic STDP and conversion procedures. The basic application of the algorithm is an autonomous agent equipped with a vision system and based on a classic FPGA device.

In this paper, we present the Sugeno integral of Hermite–Hadamard inequality for the case of quasi-arithmetically convex (q-ac) functions which acts as a generator for all quasi-arithmetic means in the frame work of Sugeno integral. [ABSTRACT FROM AUTHOR]

In this paper, we introduce one-parameter generalization of dual-hyperbolic Jacobsthal numbers – dual-hyperbolic r-Jacobsthal numbers. We present some properties of them, among others the Binet formula, Catalan, Cassini, and d'Ocagne identities. Moreover, we give the generating function and summation formula for these numbers. The presented results are a generalization of the results for the dual-hyperbolic Jacobsthal numbers. [ABSTRACT FROM AUTHOR]

Let P (z) = ∑ j = 0 n a j z j be a polynomial of degree n such that an ≥ an−1 ≥... ≥ a1 ≥ a0 ≥ 0. Then according to Eneström-Kakeya theorem all the zeros of P (z) lie in |z| ≤ 1. This result has been generalized in various ways (see [1, 3, 4, 6, 7]). In this paper we shall prove some generalizations of the results due to Aziz and Zargar [1, 2] and Nwaeze [7]. [ABSTRACT FROM AUTHOR]

In many digital systems, various sequential blocks are used. This paper is devoted to the case where the model of a Mealy finite state machine (FSM) represents the behaviour of a sequential block. The chip area occupied by an FSM circuit is one of the most important characteristics used in logic synthesis. In this paper, a method is proposed which aims at reducing LUT counts for FPGA-based Mealy FSMs with transformation of state codes into FSM outputs. This is done using the combined state codes. Such an approach allows excluding a block of transformation of binary state codes into extended state codes. The proposed method leads to LUT-based Mealy FSM circuits having exactly three levels of logic blocks. Under certain conditions, each function for any logic level is represented by a circuit including a single LUT. The proposed approach is illustrated with an example of synthesis. The results of experiments conducted using standard benchmarks show that the proposed method produces LUT-based FSM circuits with significantly smaller LUT counts than is the case for circuits produced by other investigated methods (Auto and One-hot of Vivado, JEDI, and transformation of binary codes into extended state codes). The LUT count is decreased by an average of 17.96 to 91.8%. Moreover, if some conditions are met, the decrease in the LUT count is accompanied with a slight improvement in the operating frequency compared with circuits based on extended state codes. The advantages of the proposed method multiply with increasing the numbers of FSM inputs and states.

A steady-state sinusoidal and distortion-free excitation source is very important for the accuracy and consistency of the calibration parameters of micro-electro-mechanical systems (MEMS) inertial sensors. To solve the problem that the current MEMS inertial measurement unit (IMU) calibration device is unable to reproduce the spatial motion of linear and angular vibration coupling, research topics on the coupling vibration characteristics and parameter identification for an electromagnetic linear-angular vibration exciter are proposed. This research paper used Ampere’s law and Lorentz force to establish the analytical expressions for the electromagnetic force and electromagnetic torque of the electromagnetic linear-angular vibration exciter. Then, the main purpose of this paper is to establish uniaxial and coupled vibration electromechanical analogy models containing mechanical parameters based on the admittance-type electromechanical analogy principle, and the parameter identification model is also obtained by combining the impedance formula with the additional mass method. Finally, the validity of the coupling vibration characteristics and the parameter identification model are verified by the frequency response simulation and the additional mass method, and the relative error of each parameter identification is within 5% in this paper.

This paper explores the concept of normal structure by introducing a generalized form known as P-proximal normal structure. Focusing on the framework of Hausdorff locally convex spaces, the study establishes optimal proximity outcomes for both cyclic and noncyclic relatively P-nonexpansive mappings. Furthermore, the paper presents in the realm of probabilistic normed spaces, considered as instances of Hausdorff locally convex spaces, some theorems that address the existence of best proximity points within this context.

In this paper we generalize a result of R. Urbański from paper [7] which states that for subsets A, B, C of topological vector space X the following implication holds A+B⊂B+C⇒A⊂CA + B \subset B + C \Rightarrow A \subset C provided that B is bounded and C is closed and convex. The generalization is given in Theorem 5 where we prove this result for k- convex subsets of a topological vector space. Also we introduce a notion of some abstract like-closure operation for subsets of linear space and we study its connections to order cancellation law.

In this paper, we introduce and study a new class k - eUSs(a, c, μ, γ, t) of analytic functions in the open unit disc U with negative coefficients and obtain coefficient estimates, neighborhoods and partial sums for functions f belonging to this class. [ABSTRACT FROM AUTHOR]

In this paper we establish some natural consequences of the Wirtinger integral inequality. Applications related to the trapezoid unweighted and weighted inequalities, of Fej'er's inequality for convex functions and of Gr¨uss' type inequalities are also provided. [ABSTRACT FROM AUTHOR]

In this paper, we consider new subclasses TSn(μ, a, b, ℓ, τ, γ) and TRn(μ, a, b, ℓ, τ, γ) of analytic univalent functions defined by Erdelyi-Kober integral operator. We obtain coefficient inequalities, inclusion relationships involving the (n, δ)-neighborhoods, partial sums and integral mean inequalities for the functions that belongs to these classes. Also, subordinating factor sequence for the functions in the classes Sn(μ, a, b, ℓ, τ, γ) and Rn(μ, a, b, ℓ, τ, γ) are derived. [ABSTRACT FROM AUTHOR]

The paper presents a comprehensive design of metrological equipment for torque sensor verification and calibration, detailing the process from conception to construction and highlighting the specifics of the structural design to meet metrological requirements. The measuring device’s functionality and the individual structural components are described, as is the methodology for creating a complete product. The paper addresses the crucial issue of measurement uncertainty and the required accuracy, achieved through the construction of a special measuring arm made of carbon material. FEM analyses of the carbon arm are presented and compared with the required metrological accuracies. In addition, we discuss the different properties of various carbon structures in Pre-preg materials used in the construction of the measuring arm and present the results of measurements on such carbon materials. This paper provides a comprehensive insight into the design and construction of metrological equipment for torque sensors, with a focus on its compliance with metrological requirements. The proposed device aims to establish the foundations for primary metrology of torque in Slovakia and has potential applications in a wide range of industries.

Customer portrait is the customer information that is labelled and digitised. Collecting and studying consumer data is highly helpful to enterprises because it empowers them to use these data to locate target groups and meet various customer needs. With the continuous rise of the e-commerce market, major e-commerce websites list providing customer value and being data-driven as company values. Traditional customer portraits rely excessively on objective and past experience; so, a simple but powerful customer portrait system is required to make the customer analysis platform simple and intelligent, and to make the data accumulated at ordinary times bring practical value to e-commerce companies. Based mainly on addressing this requirement, this paper proposes an effective customer portrait system for e-commerce. First, the research background and significance is expounded, which lays a theoretical foundation for this research. Then, the customer portrait system is designed, including the overall design scheme and functional framework of the system. The improved FCM algorithm is used as the basis for building the customer portrait model, and the performance of this algorithm is analysed and compared with that of the improved algorithm used in this paper.

The survival soil on which the traditional martial arts culture depends is becoming thinner and thinner. A large number of superb martial arts skills and martial arts experience disappear with the passing of the older generation of martial artists. In order to realize the information preservation of traditional Wushu, this paper puts forward the establishment and application of traditional Wushu intelligent learning resource database under the background of big data. In the context of big data, data mining technology is used to realize personalized recommended learning services, obtain the feature structure of intelligent learning system through operation, extract the average dynamic features of specific data in the resource database, obtain fuzzy constraints according to the value, determine the membership function, and adjust the membership function parameters through training fuzzy neural network, so as to gradually improve the reasoning accuracy. Finally, the matching rule set is used to filter the resource data packets to achieve the purpose of communication. In order to verify the effect of the model, compared with the traditional model, the results show that when the number of nodes is 500, the average transmission rate is as high as 90%, the average delay is 12 seconds, and the throughput performance is 91%. It can be verified that the model designed in this paper can effectively improve the propagation rate, reduce the average delay and strengthen the throughput performance.

This paper builds and evaluates a self-learning system for spoken English pronunciation suitable for PC mobile terminal or mobile terminal users, and the core technology of speech recognition is built on Hidden Markov Model (HMM), which is used to decode the speech signal in spoken English learning. This paper studies the related speech recognition theory and signal processing technology, builds a comprehensive English self-learning system in more complex situations and more user types and conducts a comprehensive evaluation of the system. The results show that the overall accuracy of the HMM model in the spoken English recognition and evaluation system built in this paper is good, and the accuracy of the input audio for people of all ages is greater than 90%. In the younger population, the accuracy of male speech signals was the highest in both closed space and open space, reaching 98.12% and 96.53%, respectively. In addition, it is observed that the accuracy gradually decreases as more wrong judgements are made on the speech input signal. When the evaluation is poor, the accuracy of the scoring results decreases to 55%, and when there are fewer voice judgement errors, it is in the excellent range, where the accuracy reached 88%.

In the construction of intelligent teaching resources, a large number of resources are collected to meet the teaching needs, and its organisational structure, resource content and teaching quality are not fully recognised. At present, there are few studies on the performance evaluation of intelligent teaching, and the research angles are also different. Based on this, this paper constructs the application performance evaluation model of intelligent teaching resource organisation mode. Based on the simple analysis of intelligent teaching research and the development of big data mining algorithm, this paper uses data mining algorithm to realise resource mining, uses ant colony algorithm and association rules to mine information, carries out student evaluation on this basis, and uses ID3 algorithm to construct decision tree to analyse the main factors affecting teaching. Then the performance evaluation model is built, and the concept of fuzzy mathematics is introduced to realise the comprehensive evaluation based on analytic hierarchy process. Finally, simulation tests and experiments are used to analyse the effectiveness of the algorithm and the application of the model. The results show that the data mining algorithm based on association rules can mine more information and shorten the running time. The performance evaluation model based on fuzzy comprehensive evaluation can be applied to the evaluation of intelligent teaching, find the shortcomings in teaching, and confirm the effectiveness of the model.

With the rapid development of Internet technology, the field of hotel management has begun to carry out informatisation construction, through which the management level and operational efficiency of hotels can be improved. The traditional hotel management work with a complex structure and cumbersome process is facing huge challenges. Therefore, this paper aims to design, develop and implement a small and medium-sized hotel management system based on customer relationship management (CRM), according to the characteristics of small and medium-sized hotel management. Management and system setting management of small and medium-sized hotels can reduce the hotel operating costs and increase the profitability by using this system. The department and employee performance appraisal can be divided into four dimensions, finance, customer, internal business process, and learning and growth for job analysis and design, using the key performance indicator method to lock key appraisal indicators, and ignore or omit irrelevant or insignificant indicators. Then the analytic hierarchy process is used to scientifically determine the indicator weights. The Delphi and in-depth interview methods are used to complete construction of the performance appraisal system, and the constructed CRM performance management system is used to achieve the hotel’s strategic goals, thus completing the fundamental goal of using the CRM model. The slacks-based measure model is based on the assumption of variable returns to scale, considering that the input redundancy and output deficiency of ineffective decision-making units are measured based on their slack. This paper defines input inefficiency as the ratio of input slack to actual input, and output inefficiency as the ratio of output slack to actual output. The total input inefficiency rate of the hotel industry in China’s ineffective provinces and regions is 0.458, while the total output inefficiency rate is 0.077, indicating that if the total investment in the hotel industry is reduced by 47.8% on average and the total output is increased by 6.9% on average, the hotels in these ineffective provinces and regions can all be relatively effective. Finally, the overall performance of the system will be evaluated, and a set of safe, convenient and friendly hotel management system will be developed.

In recent years, influenced by the deepening reform of colleges teaching English in China, teaching English for college students has gradually been favoured and promoted. At present, many universities still use traditional English teaching methods. The traditional English teaching method only allows college students to learn basic grammar and vocabulary, without the ability of independent learning. Given these problems, this paper first proposes a framework for cultivating college students’ autonomous learning ability in English teaching based on output-based education (OBE) theory. Then, the OBE theory is introduced in detail. At the same time, the framework is applied in a university. After a semester of study, the results are combined with teachers’ and college students’ questionnaire surveys. Finally, after the questionnaire results and analysis, the framework proposed in this paper is better than other traditional English teaching methods. The experiment also shows that it not only improves the adaptability of college students’ English teaching but also improves their independent learning ability while learning English.

In the process of designing animation characters and background elements, there may be a high degree of visual blur, resulting in a strong sense of picture distortion, and it is easy to expose the incomplete picture. Accordingly, this paper proposes to use directional derivatives to deal with animation-like visual problems. This method is based on the theoretical basis of directional derivatives, combined with the current mathematical methods of animation character and background element design, and defines the important role of directional derivatives in animation and background design, and more effectively enhances the visual results of animation characters. In the research of clarity and distortion, this paper uses directional derivative derivation as the cutting-in method to test the algorithm for visual simulation and restoration of animated characters and background elements so that the algorithm can be used for each animation character and background element. The defect point is calculated, and the clarity and self-healing ability of the video itself are improved by the influence of the mathematical parameters of the surrounding known points on itself and the key variable of the directional derivative in the field. The results show that the directional derivative can play a role in promoting sublimation in the design of animated characters and background elements.

This paper examines the current supply chain network model (SCNM) in order to effectively apply cost accounting information to strengthen supply chain management and solve the problem of low overall efficiency of the model. This paper constructs the SCNM of cost accounting, analyses the characteristics of the model and designs the variables of the model. In order to optimise enterprise cost accounting, the corresponding mathematical model is constructed, and the preconditions and constraints for solving the model are set up. In addition, particle swarm optimisation (PSO) algorithm is used to solve the model, and the moving speed of particle swarm is updated by dynamic relaxation factor. Finally, the validity of the model and the accounting cost are simulated. The results show that the model can effectively solve the optimisation problem of SCN in accounting cost.

This paper applies a nonlinear differential equation to the information management system of college course selection. A teaching information management system based on an approximate learning strategy is presented by using statistical linearization technology. An imprecise controller is obtained by numerical simulation of Riccati differential equations with statistical linearization. This kind of Riccati differential equation differs significantly from the ordinary one. Then the system proposes a collaborative filtering method based on nonlinear differentiation based on student feature classification. At last, this paper systematically analyzes the differences between course selection systems, business recommendations, and student attributes—the system experiments on college students' choice of a learning platform. The study found that the method was correct 34.6% of the time. This system can provide practical guidance for students to choose courses.

As an emerging business model and economic form, the sharing economy is a new trend to promote global economic growth in the future. Public participation is the basic condition for the prosperity and development of the sharing economy and is the basic requirement for the realisation of collaborative governance. Encouraging the public to actively participate in the collaborative supervision of my country’s sharing economy has become an inevitable requirement to improve governance efficiency and create a social governance pattern of co-construction, co-governance and sharing. First of all, this paper refers to the rapid development of my country’s sharing economy in recent years, which has also brought many negative problems. Secondly, this paper establishes a game model of sharing economy-related enterprises, regional governments and the public to drive the public’s shared economy in my country, which forms the driving principle and guiding strategy of collaborative supervision. Through research, it is concluded that the size of the initial probability is proportional to the convergence speed of the game subject’s selection strategy; different game subjects have different sensitivities to parameter changes, and the public is more sensitive to the cost and punishment of participating in innovation involving different game subjects The strategy choices between them are mutually reinforcing, and the evolutionary stable strategy is ‘active participation, supervision, active participation. Finally, the simulation experiments are used to verify the results of the tripartite game model constructed in this paper.

With the rapid development of the Internet, security issues are becoming more and more prominent, and since most information is transmitted through the Internet today, Internet security is particularly important. When the Internet was designed, only mutual compatibility and interoperability between networks were considered, and security issues were not fully considered. As a result, as the Internet continues to grow, security issues are becoming more and more serious. One of the more difficult attacks is the Distributed Denial of Service (DDoS) attack, which has many forms of attacks, is harmful, and is difficult to identify and defend. Therefore, building a global Internet security protection system to achieve effective protection against DDoS attacks is the main work of this research paper. In this paper, we propose an artificial intelligence DDoS attack protection system, which implements a controller and switch auto-detection model by extending the protocol and establishing an optimization model to realize a low-load and low-latency traffic monitoring scheme; for DDoS attacks. We propose the attack inspection algorithm SCVAE based on Variational Encoder (VAE) and Spectral Clustering. in order to mitigate DDoS attack traffic, the protection system uses the QoS traffic control method, builds the application flow hierarchy model, and filters the attack traffic endured by the system by setting the application flow bandwidth limit as well as the traffic priority dual policy. Finally, a Mininet-based simulation test environment is built to evaluate the model, and different test indexes are set for different system modules to evaluate their actual performance. The results of this paper show that in the network traffic monitoring test, the artificial intelligence DDoS attack protection algorithm can respond to the attack more quickly by reducing the average 73ms per sampling compared with other algorithms; in the attack traffic identification test, the comparison accuracy (P) is improved by 15.14%, the accuracy (AC) is improved by 13.26%, the recall (R) is reduced by 9.23%, and the F1 measurement criteria improved by 23%. The test verifies that the artificial intelligence DDoS attack protection system can achieve real-time monitoring of each performance parameter and also illustrates the feasibility and practicality of the research content of this paper, which strengthens the construction of the technical means of Internet security protection and further enhances the Internet security defense capability.

This study conducted a questionnaire survey on the physical condition of high school students based on FIT. The correlation between sedentary behavior, exercise level and physical fitness was studied. In this paper, the fuzzy C-average clustering method of the BP neural network is used to make statistics and classification of students’ physical condition. This paper collates the biological quality data of college students. Then this paper makes a comprehensive classification, classification and quantitative assessment of the data. The study found that college students’ sedentary habits varied from individual and family backgrounds. Family factors influence students’ physical exercise. Physical exercise was positively correlated with sedentary behavior and body mass index in adolescents. The accuracy of clustering combined with the BP neural network can reach 94%.

Against the social background of the gradual transformation of the social pension mode and the arrival of the ageing age, the tool design of fitness walkers for the elderly was studied. In this paper, the physiological and psychological status of the elderly with mild or moderate stroke or unable to exercise due to the decline of physical function was analysed. In addition, the corresponding elderly fitness walker product market research was studied. Aiming at these problems, this paper proposes a set of elderly fitness walker frames based on the ergonomic semiotic approach of the product architecture design (SAPAD) model. First, the development and structure of artificial engineering is introduced in detail. Then the framework of walking aid for the elderly based on the SAPAD model is proposed, and the SAPAS model and walking aid for the elderly are introduced, respectively, along with the framework of simulation design and application. The experimental results show that the framework of elderly fitness walker based on the ergonomic SAPAD model can be implemented. It can be applied to the elderly’s fitness assistance. A fitness walker can be suitable for the elderly who want to continue to exercise; it also hopes to care for the elderly who need to exercise from the perspective of the product.