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Mixed volume is an important notion in convex geometry, which is the extension of volume and surface area. The Minkowski inequality for mixed volume plays a vital role in convex geometry. This paper obtains that mixed volume under Steiner symmetrization is monotonic and decreasing, and a concise proof of the general Minkowski inequality by Steiner symmetrization is obtained. [ABSTRACT FROM AUTHOR]

In this paper, we present a new approach to check the existence of best proximity points for R‐proximal contractions in the framework of metric spaces equipped with a w0‐distance and present elementary proofs of recent results by using the corresponding fixed point problems without the continuity assumption of the considered self‐mapping. We also discuss on cyclic Geraghty contractions and resolve the problem of the existence and convergence of the best proximity point for such a class of mappings. [ABSTRACT FROM AUTHOR]

This paper introduces the concept of triple‐composed metric space as a new generalization of double‐composed metric space and rectangular b‐metric space. We also prove fixed point results of nonlinear FT‐contractions in such spaces, which is an improvement and extension of previous results concerning F‐contraction. Furthermore, we discuss the application to nonlinear integral equations. [ABSTRACT FROM AUTHOR]

In this paper, a new matrix splitting iteration method is presented to solve the absolute value equation. The proposed method has three parameters, and it is expected that its convergence efficiency can be improved by selecting appropriate parameters. The convergence of the proposed method is studied. Numerical examples of the absolute value equation with M‐matrices are given to show the effectiveness and feasibility of the proposed method. [ABSTRACT FROM AUTHOR]

This paper concerns the universality of the two-layer neural network with the k -rectified linear unit activation function with k = 1 , 2 , ... with a suitable norm without any restriction on the shape of the domain in the real line. This type of result is called global universality, which extends the previous result for k = 1 by the present authors. This paper covers k -sigmoidal functions as an application of the fundamental result on k -rectified linear unit functions. [ABSTRACT FROM AUTHOR]

In this paper, we consider the initial boundary value problem for a class of singular parabolic equations with viscoelastic term and logarithmic term. By using the technique of cut‐off and the method of Faedo‐Galerkin approximation, the local existence of the weak solution is established. Based on the potential well method, the global existence of the weak solution is derived. Furthermore, we prove that the weak solution blows up in finite time by taking the concavity analysis method. [ABSTRACT FROM AUTHOR]

It has been shown that the findings of d -metric spaces may be deduced from S -metric spaces by considering d ϖ , ϰ = Λ ϖ , ϖ , ϰ . In this study, no such concepts that translate to the outcomes of metric spaces are considered. We establish standard fixed point theorems for integral type contractions involving rational terms in the context of complete S -metric spaces and discuss their implications. We also provide examples to illustrate the work. This paper's findings generalize and expand a number of previously published conclusions. In addition, the abstract conclusions are supported by an application of the Riemann-Liouville calculus to a fractional integral problem and a supportive numerical example. [ABSTRACT FROM AUTHOR]

Let X be a nonempty set, A be a commutative Banach algebra, and 1 ≤ p < ∞. In this paper, we present a concise proof for the result concerning the BSE (Banach space extension) property of ℓ p X , A . Specifically, we establish that ℓ p X , A possesses the BSE property if and only if X is finite and A is BSE. Additionally, we investigate the BSE module property on Banach ℓ p X , A -modules and demonstrate that a Banach space ℓ p X , Y serves as a BSE Banach ℓ p X , A -module if and only if X is finite and Y represents a BSE Banach A -module. [ABSTRACT FROM AUTHOR]

In this paper, the Parseval K - g -frames are constructed from a given K - g -frame by scaling the elements of the K - g -frame with the help of diagonal operators, and these frames are named scalable K - g -frames. Also, we prove some properties of scalable K - g -frames and construct new scalable K - g -frames from a given K - g -frame. The necessary and sufficient conditions for a K - g -frame to be scalable are given. Further, equivalent conditions for the scalability of K - g -frames and the K -frames induced by K - g -frames are obtained. Finally, it is shown that the direct sum of two scalable K - g -frames is again a scalable K - g -frame for some suitable bounded linear operator K. [ABSTRACT FROM AUTHOR]

In this paper, we consider the weighted m -biharmonic equation with nonlinear damping and source terms. We proved the global existence of solutions. Later, the decay of the energy is established by using Nakao's inequality. Finally, we proved the blow-up of solutions in finite time. [ABSTRACT FROM AUTHOR]

In this paper, we investigate a class of a third-order neutral-type differential equation with time-varying delays. Some sufficient conditions on the existence of a periodic solution are established for the considered system. Different from the previously reported research results, by utilizing the properties of neutral operators and a special variable substitution, we transform a high-order neutral equation into a first-order three-dimensional nonneutral system. The existence of a periodic solution such as the high-order neutral equation has not been given much attention in past papers due to the difficulty of estimation of prior bounds of solutions. This paper is devoted to the use of properties of neutral-type operators with a variable parameter and Mawhin's continuation theorem for overcoming the above difficulties. The neutral term in the third-order neutral differential equation in this paper contains a variable parameter which is different from third-order neutral-type equations that have been studied. The third-order neutral-type equation studied in this paper is more general, and similar equations studied in the past are special cases of the equations studied in this paper. Finally, an example is given to elucidate the effectiveness and values of the present results. Our results are new and complement the related results of third-order functional differential equations. [ABSTRACT FROM AUTHOR]

This study establishes a new method to investigate bounds of a k ; k ≥ n , for certain general classes of bi-univalent functions. The results include a number of improvements and generalizations for well-known estimations. We also discuss bounds of n a n 2 − a 2 n − 1 and consider several corollaries, remarks, and consequences of the results presented in this paper. [ABSTRACT FROM AUTHOR]

This paper investigates the existence of solutions for Hadamard fractional differential equations with integral boundary conditions at resonance on infinite domain. By constructing two suitable Banach spaces, establishing an appropriate compactness criterion, and defining appropriate projectors, we study an existence theorem upon the coincidence degree theory of Mawhin. An example is given to illustrate our main result. [ABSTRACT FROM AUTHOR]

In this paper, we employ a q -Noor integral operator to perform a q -analogue of certain fractional integral operator defined on an open unit disc. Then, we make use of the Hadamard convolution product to discuss several related results. Also, we derive a class of convex functions by utilizing the q -fractional integral operator and apply the inspired presented theory of the differential subordination, to geometrically explore the most popular differential subordination properties of the aforementioned operator. In addition, we discuss an exciting inclusion for the given convex class of functions. Over and above, we investigate the q -fractional integral operator and obtain some applications for the differential subordination. [ABSTRACT FROM AUTHOR]

Let A p n be the class of functions f z given by f z = z p + a p + n z p + n + a p + n + 1 z p + n + 1 + ⋯ which are analytic in the open unit disk U. For f z ∈ A p n , new integral operators O − j f z and O j f z j = 0 , 1 , 2 , ⋯. are considered. The operators O − j f z and O j f z satisfy O j O − j f z = O − j O j f z = f z and O − j ∗ O j f z = O j ∗ O − j f z = f ∗ f z for the convolution ∗ of O − j f z and O j f z. In the present paper, the dominants for both operators O − j f z and O j f z and subordinations for O − j f z and O j f z are discussed. Also, new subclass T p γ m , δ , ρ ; m , j concerning with m different boundary points is defined and discussed. Moreover, some interesting problems of T p γ m , δ , ρ ; m , j associated with O j f z are obtained. Furthermore, some interesting examples for our results are considered. [ABSTRACT FROM AUTHOR]

In this paper, by using the mountain pass theorem and the concentration compactness principle, we prove the existence of a positive solution for a p -Kirchhoff-type problem with critical Sobolev exponent. [ABSTRACT FROM AUTHOR]

In this paper, we mainly prove the existence of (weak) solutions of an inclusion problem with the Dirichlet boundary condition of the following form: L ∈ A x , u , D u + F x , u , D u , in Ω , and u = 0 , on ∂ Ω , in Musielak-Orlicz-Sobolev spaces W 0 1 L Φ Ω by using the surjective theorem, where Ω ⊂ ℝ N is a bounded Lipschitz domain, L belongs to the dual space W 0 1 L Φ Ω ∗ of W 0 1 L Φ Ω , A is a multivalued maximal monotone operator, and F is a multivalued convection term. Some examples for A and F are given in the paper. Then, we give some properties of the solution set of the inclusion problem. We also show the existence of (weak) solutions of the inclusion problem with an obstacle effect. [ABSTRACT FROM AUTHOR]

Traditional logistics delivery route optimization algorithm has some problems such as long time to find the optimal route. Based on this, this paper discusses swarm intelligence optimization algorithm and logistics delivery route optimization. To solve the logistics vehicle routing problem, considering that the basic ACO (ant colony optimization) has the disadvantages of slow convergence speed and easy to fall into local optimum, this paper proposes a new hybrid population optimization algorithm and applies it to VRPTW (vehicle routing problem with time windows). In addition, the concept of crowding degree in AFSA (artificial fish swarm algorithm) is introduced into ACO. In the early stage of the optimization process, a strong crowding degree limit is set to ensure that most ants are not affected by pheromone concentration to conduct random optimization. The simulation results show that the AC (accuracy rate) of this algorithm is 95.08%, which is higher than the traditional PSO (particle swarm optimization) algorithm and general heuristic algorithm. The hybrid algorithm can effectively improve the optimization efficiency of VRPTW, lay a foundation for solving large-scale VRPTW, and provide new research ideas and methods. At the same time, the results fully show that the algorithm in this paper has certain advantages in performance, and it can be applied to logistics delivery route optimization. [ABSTRACT FROM AUTHOR]

In the present paper, a new efficient technique is described for solving nonlinear mixed partial integrodifferential equations with continuous kernels. Using the separation of variables, the nonlinear mixed partial integrodifferential equation is converted to a nonlinear Fredholm integral equation. Then, using different numerical methods, the Bernoulli polynomial method and the Chebyshev polynomials of the sixth kind, the nonlinear Fredholm integral equation has been reduced into a system of nonlinear algebraic equations. The Banach fixed-point theory is utilized in order to have a conversation about the nonlinear mixed integral equation's solution, namely, its existence and uniqueness. In addition, we talk about the convergence and stability of the solution. Finally, a comparison between the two different methods and some other famous methods is presented through various examples. All the numerical results are calculated and obtained using the Maple software. [ABSTRACT FROM AUTHOR]

In this paper, we consider a new extension of the Banach contraction principle, which is called the θ − ω − contraction inspired by the concept of θ − contraction in λ , μ -generalized metric spaces and to study the existence and uniqueness of fixed point for the mappings in metric space. Moreover, we discuss some illustrative examples to highlight the improvements that were made, and we also give an iterated application of linear integral equations. [ABSTRACT FROM AUTHOR]

In this paper, we give a characterization of Fredholmness of the Toeplitz operators on the Bergman spaces A φ p with exponential weights in D when 0 < p < ∞. Also, we obtain the sufficient and necessary conditions which the Toeplitz and Hankel operators on A φ 2 belong to h -Schatten class, where h is a continuous increasing convex function. [ABSTRACT FROM AUTHOR]

In the present paper, in view of the variational approach, we discuss the Neumann problems with p x -Laplacian-like operator and nonstandard growth condition, originated from a capillary phenomena. By using the least action principle and fountain theorem, we prove the existence and multiplicity of solutions to the class of Neumann problems under suitable assumptions. [ABSTRACT FROM AUTHOR]

The main goal of the paper is to approximate two types of inverse problems for conformable heat equation (or called parabolic equation with conformable operator); as follows, we considered two cases: the right hand side of equation such that F x , t and F x , t = φ t f x . Up to now, there are very few surveys working on the results of regularization in L p spaces. Our paper is the first work to investigate the inverse problem for conformable parabolic equations in such spaces. For the inverse source problem and the backward problem, use the Fourier truncation method to approximate the problem. The error between the regularized solution and the exact solution is obtained in L p under some suitable assumptions on the Cauchy data. [ABSTRACT FROM AUTHOR]

To revitalize talents and give full play to the maximum utility of HR (human resources), it is not enough to accumulate talents alone. HR must be effectively allocated to realize the matching of people and posts. Competency is a personal characteristic of an organization that distinguishes its performance level in a specific job and organizational environment. In order to solve the problem that job seekers' job-seeking ability is difficult to match the job requirements, this paper combines neural network with traditional HRM (human resource management) algorithm based on ability perception and designs a depth model of accurate matching of people and posts in HR field, which can improve the quality of data training of traditional algorithm. The results show that compared with other algorithms, the F 1 value of the proposed algorithm is obviously improved, and the proposed algorithm performs best, with the F 1 value of 0.829. In this paper, the method of global network plus local network is used, which can effectively improve the hidden features of data and then improve the matching degree and recommendation accuracy of the algorithm. [ABSTRACT FROM AUTHOR]

The study of farmers' migration choice behavior can reflect people's needs for the future living environment from the side and has practical and important guiding significance for adjusting and improving the focus of future development. In order to make a detailed analysis of the prediction of migrant workers' behavior in cities, this paper studies the internal mechanism of the change of commuters' commuting patterns under the background of urban suburbanization. Using Bayesian network, this paper establishes a model of commuting mode transfer of urban immigrants, taking personal and family attributes as control variables. The influence of factors such as migration attributes and changes in building environment perception before and after migration is analyzed. Based on the survey data, a Bayesian network of farmers' land use behavior is established by using Bayesian network method to investigate the choice of farmers' migration direction. In the research process of migration direction, the research structure shows that 60.1% of farmers want to stay in the countryside, rather than migrate through Bayesian network algorithm. The results of regression analysis by establishing a multivariate logistic model show that there is a strong willingness to choose small towns and large cities. However, the willingness to choose not to relocate to local villages is relatively weak. [ABSTRACT FROM AUTHOR]

In order to define the positioning of the urban brand image, design the urban brand image, integrate and optimize the communication channels, improve the public participation awareness, and enhance the core competitiveness of the city. In this paper, a personalized recommendation search engine based on big data identifies keywords input by urban users. And give more accurate results based on some relevant information that can be extracted. This paper analyzes how to make better use of big data for tourism destination brand image management, and the existing shortcomings, and puts forward relevant suggestions. The industries related to cultural creative design and tourism elements constitute an intertwined cultural and tourism industry chain, and data technology plays an important role in the cultural and tourism industry chain. Through the development of tourism, tourists will produce comprehensive and diversified consumption in the city. Based on the analysis of big data, it can provide strong decision support for the government and industry managers, and realize the image design and communication of the urban brand identification system. Through the big data platform, establish the brand management strategy, improve the communication content of the city's brand image, and timely feedback the opinions and suggestions of tourists on the tourism destination, so as to adjust the communication strategy of the tourism image according to the feedback information of tourists. The results show that the big data personalized recommendation system can achieve ideal results in urban brand value and urban tourism related factors. [ABSTRACT FROM AUTHOR]

In today's big data context, the composition of virtual networks is becoming increasingly complex, so it is neither easy nor difficult to strengthen the control of network security issues. This paper studies the important content of network big data mining-assisted laboratory management. On the basis of discussing the connotation of laboratory safety, combined with management practice, this paper puts forward some suggestions on laboratory safety management. This paper puts forward some views and thoughts on some problems existing in the management and experimental teaching of chemistry laboratory. By judging the stability of instruments and equipment, we know whether the calibration status of instruments and equipment has changed during this period, so as to ensure the sustainable use of instruments and equipment and the accuracy and traceability of laboratory test results. The use of laboratory management system can greatly improve the utilization rate of laboratory equipment, promote students' autonomous learning, and promote the standardization of laboratory construction. Improve the network monitoring method of big data mining technology and the application mechanism of big data network monitoring, in one type of laboratory. Teachers and students in the laboratory can reasonably arrange their own time according to their own interests to guide and operate experiments. Through continuous operation and practice, students' practical ability and experimental knowledge level should be improved as much as possible. [ABSTRACT FROM AUTHOR]

Distribution process is the core of logistics enterprise system. Efficient distribution process is the key for enterprises to improve logistics service level, gain competitive advantage, and win customers. In order to reduce the design error of the system and ensure the effective operation of the system, this paper establishes the system model and analyzes the properties of the model through the evaluation and analysis of various resources of the distribution system. The future development of intelligent logistics system is not only the key for logistics enterprises to win competition, but also a new measure to promote China's economic development. This is not only a typical NP hard problem, but also a major challenge for the rational and scientific development of the intelligent logistics industry. Based on the previous theoretical research results, this paper intends to explore the intelligent logistics distribution route selection scheme by using mathematical modeling methods such as particle swarm optimization, so as to provide new technologies and methods for logistics distribution operation and management decision-making. The results show that compared with the traditional genetic algorithm, the accuracy of the improved particle swarm optimization algorithm is improved by 10.36%. This method effectively improves the operation cycle and link efficiency and achieves the purpose of optimization. The improved particle swarm optimization algorithm proposed in this paper is not only more suitable and effective for enterprise decision makers to deal with subjective judgments in an imprecise environment. It is also based on the evaluation sequence of each indicator of the alternative obtained from the evaluation and the comprehensive evaluation of all indicators. By weighting and considering the results, the best solution for enterprise logistics and distribution is selected. [ABSTRACT FROM AUTHOR]

At present, the economic development of the world's major economies is showing a positive and positive state. Driven by the development of related industries, the development of the financial field is also changing with each passing day. Various activities in the financial industry are in full swing, and the forecasts of related prospects are also full of uncertainties. Summarizing the laws of financial activities through technical means and making accurate predictions of future trends and trends is a hot research direction that relevant researchers pay attention to. Accurate financial forecasts can provide reference for financial activities and decision-making to a certain extent, promote the steady development of the market, and improve the conversion rate of financial profits. As an algorithm model that can simulate the biological visual system, the convolutional neural network can predict the numerical trend of the next period of time based on known data. Therefore, this paper integrates the support vector machine with the established model by establishing a convolutional neural network model and applies the prediction model to the prediction of financial time series data. The experimental results show that the model proposed in this paper can more accurately predict the trend of the stock index. [ABSTRACT FROM AUTHOR]

The popular trend of today's music can be obtained by deep excavation, analysis, and prediction of the audience's preferences. Using huge music library resources and user behavior to form music big data and truly realizing the aggregation of audience preferences determine the popular development trend of music. Therefore, this paper will apply data mining (DM) technology, introduce neural network (NNS) theory, establish a prediction model of music fashion trend, predict and evaluate the music fashion trend according to the selected evaluation index, find the change of music fashion trend in time, and provide decision-making basis for music fashion trend. In this paper, the prediction of music popularity trend based on NNS and DM technology is studied. In the prediction of the number of songs played by 10 artists, the NNS algorithm proposed in this paper reduces the prediction effect from the original 0.074 and 0.045 to 0.044 and 0.032, respectively, and the error rates are reduced by 35.7% and 29.4%, respectively, compared with the learning algorithm and the decision tree algorithm. Among the three methods, the NNS algorithm in this paper has the highest accuracy. Therefore, it can be proved that the model proposed in this paper is more suitable for predicting the trend of music popularity. In the end, it can accurately control the trend of pop music and also realize the aggregation of user preferences to determine the trend of pop music. [ABSTRACT FROM AUTHOR]

The development of information technology such as the continuous improvement of mobile Internet infrastructure and the performance of computers has made it easy to process and share information. The huge market demand for location-based information services provides huge impetus to the generation and development of mobile terminal positioning technology. Generally speaking, the main causes of climate change can be summarized into two categories: natural climate fluctuations and the impact of human activities which is a major measure taken by China to actively respond to climate change. This is a successful approach to actively explore the rapid development of China's industrialization and urbanization, which not only develops the economy and improves people's livelihood but also responds to climate change and reduces carbon intensity. Firstly, this paper mainly is aimed at the connotation of regional low-carbon economic development mode, studying the basic mode of regional low-carbon economic development, and analyzing the characteristics and applicable conditions of each mode. Secondly, based on the machine learning algorithm of data mining, the main mode selection of regional low-carbon economic development is discussed. Thirdly and finally, when choosing the regional low-carbon economic development mode, comprehensive consideration should be given to the economic development basis, energy structure, resource characteristics, industrial status, development mode, geographic location, and other factors. This paper studies the basic conditions and applicable conditions of regional economic development models. The conclusion shows that from the perspective of regional economic evolution, low-carbon economy can be regarded as the decarbonization process of economic development. It is an economic form combining its own characteristics and an inevitable requirement for the transformation of regional economy from other economic models to low-carbon economic models. And other factors of Selection of regional economic development foundation, energy structure, resource characteristics, industrial status, development mode, geographical location, were also discussed. [ABSTRACT FROM AUTHOR]

Tax forecast has an important impact on financial budget and tax plan. The amount of tax data is greatly increased, the difficulty of tax forecast is improved, and the accuracy is always difficult to keep up with the development demand. Analyze the application of optimized support vector machine model in tax prediction system. Based on the simple analysis of the research situation of tax prediction and the research status of data mining algorithm in tax data classification and prediction, this paper constructs a tax prediction model. Aiming at the problem of too many influencing factors of tax prediction, this paper puts forward the use of principal component analysis to extract the main factors, reduce the dimension of tax data, and reduce the difficulty of analysis. Support vector machine is used to realize tax prediction, aiming at the problem of parameter optimization proposed to optimize the parameters. Finally, the prediction accuracy is evaluated by comparing the error between tax prediction value and real value. The results show that the algorithm used in this paper can optimize the parameters of support vector machine. The tax prediction results show that the predicted value is similar to the real value curve. After grid search optimization, the introduction of principal component analysis reduces the redundancy and improves the prediction accuracy. [ABSTRACT FROM AUTHOR]

Based on virtual reality technology, landscape 3D modeling provides users with the possibility to construct a simulated garden landscape environment design effect online, so it has high requirements for accuracy. With the continuous improvement of precision requirements, the number of people involved in the construction of 3D models is also increasing, which puts forward higher requirements for modeling. Based on this, this paper studies the optimization strategy of landscape space 3D model based on big data analysis. Based on the analysis of the establishment of the 3D model and the related algorithm research, this paper analyzes the optimal design of the 3D model under the background of big data. In the 3D modeling of the edge folded area, it is based on the traditional quadratic error measurement grid simplification algorithm, combined with the vertex error matrix to simplify, so as to shorten the modeling time. Based on an efficient search algorithm, an adaptive nonsearch fractal image compression and decoding method is proposed in the image compression and decoding stage of 3D modeling. The search is performed by specifying the defined area block. Finally, an experiment is designed to analyze the performance of the optimization algorithm. The results show that the improved edge folding region algorithm can reduce errors on the basis of ensuring image quality, and the adaptive search algorithm can shorten the search time and improve the compression rate. This method provides a technical reference for the visualization experience and simulation system of garden landscape design and improves the presentation quality of virtual garden landscape design scenes. [ABSTRACT FROM AUTHOR]

This paper is devoted to studying a second-order nonlinear equation with mixed delays. Some sufficient conditions for the existence and exponential stability of the almost periodic solutions are established. The results of this paper extend the existing ones. [ABSTRACT FROM AUTHOR]

The main goal of the paper is to approximate two types of inverse problems for conformable heat equation (or called parabolic equation with conformable operator); as follows, we considered two cases: the right hand side of equation such that F x , t and F x , t = φ t f x . Up to now, there are very few surveys working on the results of regularization in L p spaces. Our paper is the first work to investigate the inverse problem for conformable parabolic equations in such spaces. For the inverse source problem and the backward problem, use the Fourier truncation method to approximate the problem. The error between the regularized solution and the exact solution is obtained in L p under some suitable assumptions on the Cauchy data. [ABSTRACT FROM AUTHOR]

With the support of big data technology, the field of education is also facing new problems and opportunities. Network teaching has become the mainstream means of higher education. In order to explore the changes of students' learning effect in the process of online teaching, this paper proposes to build an online teaching effect evaluation model with the support of data mining technology and decision tree algorithm. This paper records the factors and objects that reflect the teaching effect in network teaching and traditional teaching, respectively. A decision tree algorithm is used to divide the attributes of influencing factors from relevant rules. Using the Kirschner model to build the evaluation system, add two attribute elements: students' teaching evaluation and teachers' self-evaluation. Data mining technology is used to preprocess and clean up the sample set, which improves the accuracy of the calculation results. In the evaluation model, the association rule algorithm is also constructed to classify the data of the same element type and delete the data of different elements after marking. Through this evaluation model, teachers can accurately judge students' learning interests and improve students' academic performance. The results show that compared with the traditional data mining algorithm, the decision tree algorithm has obvious advantages in computing speed and accuracy. [ABSTRACT FROM AUTHOR]

Knowledge map is a new method of knowledge management with the information revolution. This paper is aimed at forming a systematic and standardized huge redundant knowledge structure, which can be used to mine the knowledge structure and the relationship between knowledge and visualize it in a graphical way, in order to obtain more representative information and improve the classification accuracy of text classification model. In this paper, a knowledge map construction method based on the Text CNN algorithm is proposed for the subject of Nautical English. It is of practical significance and academic value to make use of knowledge map to study Chinese Maritime English, which is helpful to the development of Chinese Maritime English and provides guidance. In order to maintain the diversity of particle swarm optimization, the Text CNN algorithm is combined with the construction of Maritime English subject knowledge map, and the network parameters and structure are optimized. Using knowledge map to study China Maritime English has important practical significance and academic value and has certain guiding significance for the development of China Maritime English. [ABSTRACT FROM AUTHOR]

In this paper, we present a new refinement of the integral Jensen inequality by utilizing certain functions and give its applications to various means. We utilize the refinement to obtain some new refinements of the Hermite-Hadamard and Hölder's inequalities as well. Also, we present its applications in information theory. At the end of this paper, we give a more general form of the proposed refinement of the Jensen inequality, associated to several functions. [ABSTRACT FROM AUTHOR]

With the rapid development of mobile communication technology, the data transmission rate of mobile communication has been significantly improved and emerging Internet of things applications need a lot of computing resources to meet their own computing needs. However, the existing intelligent terminals have limited computing power and cannot meet the low-latency computing requirements with limited energy consumption. Mobile edge computing technology is considered to be one of the technical solutions that can efficiently solve this problem. Through mobile edge computing technology, intelligent terminals can actively divert some computing tasks to the computing servers deployed in edge network nodes and return the computing results to intelligent terminals after the edge computing servers have finished computing, thus greatly reducing the computing delay of users. In this paper, aiming at multiple edge server networks, combined with dual-connection technology, based on the research of a single edge computing server network, it is further extended to two edge computing servers and a joint optimization problem of computing task allocation and security performance requirements of intelligent terminals and edge computing servers is proposed, so as to minimize the global time delay for completing the computing tasks of intelligent terminals. By layering the problem, this paper proposes a corresponding algorithm, which can efficiently obtain the optimal solution of the initial problem. Compared with the linear search algorithm, the algorithm proposed in this paper can significantly reduce the computation time. [ABSTRACT FROM AUTHOR]

With the rapid development of smart cities, intelligent navigation, and autonomous driving, how to quickly obtain 3D spatial information of urban buildings and build a high-precision 3D fine model has become a key problem to be solved. As the two-dimensional mapping results have constrained various needs in people's social life, coupled with the concept of digital city and advocacy, making three-dimensional, virtualization and actualization become the common pursuit of people's goals. However, the original point cloud obtained is always incomplete due to reasons such as occlusion during acquisition and data density decreasing with distance, resulting in extracted boundaries that are often incomplete as well. In this paper, based on the study of current mainstream 3D model data organization methods, geographic grids and map service specifications, and other related technologies, an intelligent urban 3D modeling model based on multisource data point cloud algorithm is designed for the two problems of unified organization and expression of urban multisource 3D model data. A point cloud preprocessing process is also designed: point cloud noise reduction and downsampling to ensure the original point cloud geometry structure remain unchanged, while improving the point cloud quality and reducing the number of point clouds. By outputting to a common 3D format, the 3D model constructed in this paper can be applied to many fields such as urban planning and design, architectural landscape design, urban management, emergency disaster relief, environmental protection, and virtual tourism. [ABSTRACT FROM AUTHOR]

The demand for energy in factories is huge. With abundant energy supply, factories can raise their production capacity to a new height. Energy is the material basis of domestic economic development. As the largest developing country in the world, energy shortage has become an urgent problem for China. In this paper, an Internet of Things based on big data ecosystem is proposed to analyze the energy consumption of the factory and build a model. The Internet of Things technology of big data ecosystem can be summarized as a technology that uses information sensing devices to complete the transaction and network connection according to the protocol content. A total of 853,000 power distribution operations were carried out in the power grid. In 2019, the average ratio of decision tree algorithm, machine learning algorithm, and machine learning algorithm was 36.8%, 37.4%, and 43.5%, respectively. Compared with the three methods, the method in this paper increased by 37.9% year-on-year and reduced the power outage by 2.63 million households, which is equivalent to a corresponding reduction of 35 users per operation. The functional requirements of the IoT energy consumption analysis system in factories based on big data ecosystem are reflected in three aspects: energy consumption monitoring and management, power control and management, and energy consumption supervision and analysis. Based on the management of energy consumption monitoring and power control through the software platform, the functional requirements of the system are analyzed. [ABSTRACT FROM AUTHOR]

In this paper, we have used the new integral transformation known as Karry-Kalim-Adnan transformation (KKAT) to solve the ordinary linear differential equations as well as partial differential equations. We have used KKAT to solve the problems of engineering and sciences specially electrical and mechanical problems. Also, we have established the comparison between KKAT and existing transformations. We have determined the KKAT of error functions and complementary error function. The fundamental purpose of this research paper is to transform the given problem into the easier form to get its solution. [ABSTRACT FROM AUTHOR]

The study of convex functions is an interesting area of research due to its huge applications in pure and applied mathematics special in optimization theory. The aim of this paper is to introduce and study a more generalized class of convex functions. We established Schur (S), Hermite-Hadamard (HH), and Fejér (F) type inequalities for introduced class of convex functions. The results presented in this paper extend and generalize many existing results of the literature. [ABSTRACT FROM AUTHOR]

In this paper, we deal with the following Schrödinger-Kirchhoff equation with potentials vanishing at infinity: − ε 2 a + ε b ∫ ℝ 3 ∇ u 2 Δ u + V x u = K x u p − 1 u in ℝ 3 and u > 0 , u ∈ H 1 ℝ 3 , where V x ~ x − α and K x ~ x − β with 0 < α < 2 , and β > 0. We first prove the existence of positive ground state solutions u ε ∈ H 1 ℝ 3 under the assumption that σ < p < 5 for some σ = σ α , β , then we show that u ε concentrates at a global minimum point of A x = V 2 / p − 1 − 1 / 2 x / K 2 / p − 1 x . [ABSTRACT FROM AUTHOR]

The option butterfly portfolio is the commonly option arbitrage strategy. In reality, because the distribution of the option state price density (SPD) function is not normal and unknown, so the nonparametric deep learning methods to estimate option butterfly portfolio returns are proposed. This paper constructs the single-index nonparametric option pricing model which contains multiple influencing factors and presents the nonparametric estimation form for option butterfly portfolio returns. The empirical analysis shows that the SPD function estimated by using single-index nonparametric option model can effectively calculate the option butterfly portfolio returns with the minimum option strike price interval and provide an effective reference tool for risk-averse investors with limited risk preferences. [ABSTRACT FROM AUTHOR]

In this paper, we study a generalized version of strongly reciprocally convex functions of higher order. Firstly, we prove some basic properties for addition, scalar multiplication, and composition of functions. Secondly, we establish Hermite-Hadamard and Fejér type inequalities for the generalized version of strongly reciprocally convex functions of higher order. We also include some fractional integral inequalities concerning with this class of functions. Our results have applications in optimization theory and can be considered extension/generalization of many existing results. [ABSTRACT FROM AUTHOR]

A small part of real line which is very close to zero has rich combinatorial properties. The aim of this paper is to express and then prove some locally combinatorial concepts near a virtual idempotent by considering the wap -compactification of a semitopological semigroup S. The wap -compactification of a semitopological semigroup S , denoted by S w , is the collection of all ultrafilters near η ∈ S w that forms a compact subsemigroup of β S d , where S d denotes S as discrete space. [ABSTRACT FROM AUTHOR]

In this paper, we propose the concept of ∈ , ∈ ∨ j ∗ , q j -fuzzy p-ideals in " B C I -algebras." We show that " ∈ , ∈ ∨ q -fuzzy p-ideals" and " ∈ ∨ j ∗ , q j , ∈ ∨ j ∗ , q j -fuzzy p -ideals" are " ∈ , ∈ ∨ j ∗ , q j -fuzzy p -ideals." However, the converse is not true, then presented examples. For a BCI-algebra Y ^ , it has been shown that every ∈ , ∈ ∨ j ∗ , q j -fuzzy p-ideal of Y ^ is an ∈ , ∈ ∨ j ∗ , q j -fuzzy ideals of Y ^ but not conversely, and then, an example is given. Furthermore in Y ^ , a connection between ∈ , ∈ ∨ j ∗ , q j -fuzzy p-ideals and p-ideals is established. [ABSTRACT FROM AUTHOR]

This paper concerns a linear porous thermoelastic system, where the heat conduction is given by Cattaneo's law. By using the theory of the semigroup of the linear operator, the well-posedness is proven. By constructing some suitable multipliers, we establish exponential and polynomial decay rates of the system depending on a stability number π. In addition, we remove the assumption that the constant b is positive in the previous works, which extends some existing results in the literature. [ABSTRACT FROM AUTHOR]

The fractional integral inequalities are crucial to deal applied problems. The present paper deals with the generalize midpoint type inequalities for a certain class of convex functions, namely, MT-convex functions in the setting of weighted fractional integral. It can be observed from the remarks given in the paper that our results or more generalized than existing results of literature and many of them can be obtained immediately from our results. [ABSTRACT FROM AUTHOR]