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  Subjects -> SCIENCES: COMPREHENSIVE WORKS (Total: 374 journals)
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Applied Mathematics and Nonlinear Sciences
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  This is an Open Access Journal Open Access journal
ISSN (Online) 2444-8656
Published by Sciendo Homepage  [370 journals]
  • Development of main functional modules for MVB and its application in rail

    • Abstract: In this work, multi-function vehicle bus (MVB) controller-based Field Programmable Gate Array (FPGA) and MVB manager based on the real-time multitasking operating system were explored and developed. The function of the MVB controller data link layer was realised by using FPGA. The embedded real-time multitasking operating system uCOS-II was applied to the development of MVB manager’s processing data, device state management, message data and bus management function. The network consistency test was performed to validate data communication of MVB link layer control protocol and the management function of MVB manager; the equipment was shown to be compatible with each other and met the requirements of IEC61375-1.
      PubDate: Fri, 29 Apr 2022 00:00:00 GMT
  • Innovations to Attribute Reduction of Covering Decision System Based on
           Conditional Information Entropy

    • Abstract: Traditional rough set theory is mainly used to reduce attributes and extract rules in databases in which attributes are characterised by partitions, which the covering rough set theory, a generalisation of traditional rough set theory, covers. In this article, we posit a method to reduce the attributes of covering decision systems, which are databases incarnated in the form of covers. First, we define different covering decision systems and their attributes’ reductions. Further, we describe the necessity and sufficiency for reductions. Thereafter, we construct a discernible matrix to design algorithms that compute all the reductions of covering decision systems. Finally, the above methods are illustrated using a practical example and the obtained results are contrasted with other results.
      PubDate: Fri, 15 Apr 2022 00:00:00 GMT
  • Satisfactory consistency judgement and inconsistency adjustment of
           linguistic judgement matrix

    • Abstract: In this study, first, the definitions of the preference relation matrix and the 0-1 permutation preference matrix of the linguistic judgement matrix are given. The method of judging the satisfactory consistency of the linguistic judgement matrix by the standard 0-1 arrangement matrix is obtained. This method not only solves the problem of satisfactory consistency when there are no equivalent objects but is also simple and effective. Then, the definition of the cyclic circle matrix of the three objects is given. According to the size of the preference value of the object line, the cyclic cycle and the adjusted language judgement matrix are obtained. Finally, the rationality and validity of the method are verified by examples.
      PubDate: Fri, 15 Apr 2022 00:00:00 GMT
  • Motion about equilibrium points in the Jupiter-Europa system with

    • Abstract: The study of motion of a test mass in the vicinity of an equilibrium point under the frame of restricted three body problem (RTBP) plays an important role in the trajectory design for different space missions. In this paper, motion of an infinitesimal mass has been described under the frame of Jupiter-Europa system with oblateness. At first, we have determined equilibrium points and then performed linear stability tests under the influence of oblateness of both the primaries. We found that due to oblateness, a considerable deviation in the existing results has occurred. Next, we have computed tadpole and horseshoe orbits in the neighbourhood of triangular equilibrium points and then the oblateness effect is recorded on these orbits. Finally, the evolution of orbits of infinitesimal mass about triangular equilibrium points have been estimated by using Poincaré surface of section technique and it is noticed that in presence of oblateness, quasi-periodic orbit dominates over the chaotic zones. These results will help in further study of more generalised models with perturbations.
      PubDate: Fri, 15 Apr 2022 00:00:00 GMT
  • A review of the treatment techniques of VOC

    • Abstract: Volatile organic compounds (VOC) are important sources of environmental pollution. Several commonly used techniques for the treatment of VOC are reviewed. Recovery techniques can be classified into absorption, adsorption, condensation and membrane separation. Destruction techniques include biodegradation, photocatalysis, low-temperature plasma and combustion. The basic principle, applicable conditions, advantages and disadvantages of the above technologies are discussed. By contrast, the rotational regenerative combustion method has a broad prospect. Suggestions on the improvement of rotary regenerative combustion technology are presented. The treatment of VOC requires comprehensive consideration of the advantages and disadvantages of various technologies.
      PubDate: Fri, 15 Apr 2022 00:00:00 GMT
  • Spatial–temporal graph neural network based on node attention

    • Abstract: Recently, the method of using graph neural network based on skeletons for action recognition has become more and more popular, due to the fact that a skeleton can carry very intuitive and rich action information, without being affected by background, light and other factors. The spatial–temporal graph convolutional neural network (ST-GCN) is a dynamic skeleton model that automatically learns spatial–temporal model from data, which not only has stronger expression ability, but also has stronger generalisation ability, showing remarkable results on public data sets. However, the ST-GCN network directly learns the information of adjacent nodes (local information), and is insufficient in learning the relations of non-adjacent nodes (global information), such as clapping action that requires learning the related information of non-adjacent nodes. Therefore, this paper proposes an ST-GCN based on node attention (NA-STGCN), so as to solve the problem of insufficient global information in ST-GCN by introducing node attention module to explicitly model the interdependence between global nodes. The experimental results on the NTU-RGB+D set show that the node attention module can effectively improve the accuracy and feature representation ability of the existing algorithms, and obviously improve the recognition effect of the actions that need global information.
      PubDate: Fri, 08 Apr 2022 00:00:00 GMT
  • Performance evaluation of college laboratories based on fusion of decision
           tree and BP neural network

    • Abstract: Performance evaluation can promote the continuous improvement of the laboratories in a college. It is necessary to take into account the scientific evaluation method during the process of the performance evaluation. In this paper, a performance evaluation method based on the fusion of the decision tree and BP neural network is presented. In detail, the decision tree model is used to select performance evaluation indexes with high weight. The BP neural network was adopted aiming to reduce the impact of assessment prediction of classification by non-core factors. First, the data were pre-processed by trapezoidal membership function. Then, the decision tree was generated by the C4.5 algorithm to select the evaluation indexes with high weight. Then, the BP neural network was trained with as many samples as possible by evaluation indexes; it possesses experts’ experience which can be used to predict the performance evaluation results. The method overcomes the shortages of the separate model, eliminates the disturbance of human factors and improves the accuracy of the evaluation. Experiments show that the model is feasible and effective in performance evaluation of college laboratories. The outcomes of this work can provide a scientific evaluation method for people such as researchers, college administrators and laboratory managers. Also, this paper will help them to improve the management of laboratories and provide them with decision references for constructing the laboratories.
      PubDate: Fri, 08 Apr 2022 00:00:00 GMT
  • Research on the sustainable development and renewal of Macao inner harbour
           under the background of digitisation

    • Abstract: With the passage of time, the Inner Harbour of Macao has experienced changes, prosperity and decline. For a long time, the twin problems of flood and transformation of the traditional business district have been the ones primarily responsible for affecting the development of the Inner Harbour. This paper analyses the Inner Harbour region through the form of five layers. Based on these factors, the cultural, economic and ecological characteristics of the Inner Harbour are summarised. The paper mainly studies solutions to the problems of flooding, and presents flood control initiatives that can prevent waterlogging in the Inner Harbour, so as to enhance and activate the old city waterfront.
      PubDate: Fri, 08 Apr 2022 00:00:00 GMT
  • Mathematical analysis of civil litigation and empirical research of
           corporate governance

    • Abstract: In addition to reducing R&D investment and changing senior managers or corporate name, the significant uncertainty and reputation shock brought by civil litigation may also have a vital impact on corporate governance of the sued company. We use A-share listed companies in Shanghai and Shenzhen stock exchanges from 2011 to 2018 to empirically examine the impact of civil litigation on corporate governance and its mechanism. It is found that, civil litigation is negatively correlated with corporate governance, and financing liabilities (FL) play an intermediary role in the negative correlation. Furthermore, judicial local protectionism weakens the negative correlation between civil litigation and corporate governance. Finally we close with directions for future research.
      PubDate: Fri, 08 Apr 2022 00:00:00 GMT
  • ARMA analysis of the green innovation technology of core enterprises under
           the ecosystem – Time series data

    • Abstract: From the perspective of innovation ecology, the green innovation of core enterprises is a key to high-quality economic development. This paper researches BYD, makes a discussion on the evolution and characteristics of green innovation, and clarifies the driving force of green innovation of core enterprises in the green innovation ecosystem. In addition, the 2002–2019 green patent authorisation data of BYD is selected as the green output indicator of the core enterprise. And through testing the data, the findings are that the perturbation term ε is white noise, which meets the zero expectation E(εt) = 0, and the same variance Var(εt) = σ2 and that there is no autocorrelation Cov(εt, εs) = 0, t ≠ s. The ARMA model is hence constructed for analysis. Through analysis, conclusions are drawn that when the core enterprises and other entities in the green innovation ecosystem collaborate to innovate, the complexity and dynamics could be found in the green innovation evolution process and that as an important driving force for green innovation, innovation input not only raises current green output but also facilitates future green output.
      PubDate: Thu, 31 Mar 2022 00:00:00 GMT
  • Study on the crushing mechanism and parameters of the two-flow crusher

    • Abstract: Based on a Chinese enterprise's single-mouth crusher, the ‘waterfall flow’ inlet crusher is developed from a foreign two-flow crusher. The two-inlet crushing mode has advantages of continuous particle feeding, controlled particle flow and low wear of housing. By analysing the working principle of the equipment, the three-dimensional model of the crusher is established. Based on the discrete element method, the simulation data are obtained by EDEM simulation software. The crushing energy, the wear of the housing and the counter boards are analysed to obtain the optimal parameters. The crushing efficiency is significantly improved and the wear of the housing is controlled to some extent. The overall performance of the crusher is improved and the cost is reduced.
      PubDate: Thu, 31 Mar 2022 00:00:00 GMT
  • Reconstruction of multimodal aesthetic critical discourse analysis

    • Abstract: The paper starts with a theoretical discussion of the possible introduction of aesthetic linguistics into the research field of multimodal critical discourse analysis for analysing tourist news of two modalities: visual and text. Thanks to the successful stories of analysis concerning aesthetic linguistics, systemic functional grammar and visual grammar; first, a framework of multimodal aesthetic critical discourse analysis is carefully redesigned based on multimodal aesthetic critical discourse analysis framework of version 1, originally designed for the same purpose. Then, the validity of the reconstructed framework is verified via analysing a piece of Shannxi tourist news with it. The result indicated that the multimodal aesthetic critical discourse analysis framework re-designed in this paper is of practical significance and can be applied to the analysis of news of multiple modalities.
      PubDate: Thu, 31 Mar 2022 00:00:00 GMT
  • What does students’ experience of e-portfolios suggest

    • Abstract: This research presents a critical examination of 102 undergraduate students’ experience with e-portfolios in a university based in Northwest China. Qualitative data are collected via interviews to explore the advantages and disadvantages of e-portfolios in order to examine the possibility for popularization of the application and further improvement as well. Findings reveal that e-portfolios are beneficial in the aspects of new knowledge creation, learning management, reflective learning, test anxiety elimination, as well as student performance assessment. Meanwhile, some problems have also been revealed, which have pedagogical implications.
      PubDate: Thu, 31 Mar 2022 00:00:00 GMT
  • Radioactive source search problem and optimisation model based on
           meta-heuristic algorithm

    • Abstract: In the process of rational development and utilisation of nuclear energy, people often face nuclear accidents such as lost and stolen radioactive sources; so, the means of searching for these sources quickly in highly radioactive environments is an important security challenge. In the past, these jobs were limited to workers specialising in nuclear technology. They used gamma-ray detection equipment to search for radioactive sources, but the search efficiency was low. The main purpose of this article is to design a meta-heuristic algorithm based on imitating professional technicians to locate radioactive sources in a computer-aided manner. At the same time, due to the complexity that may characterise the actual search, the search strategy must be optimised. The article established an intelligent random search model with human thinking. Finally, it was proved based on the mathematical theory that the complexity of the model search algorithm is linear, and the simulation experiment results show that the optimisation algorithm has good efficiency and fault tolerance.
      PubDate: Thu, 31 Mar 2022 00:00:00 GMT
  • Research of neural network for weld penetration control

    • Abstract: A method has been proposed for welding penetration status prediction in the paper. First, an experimental system was set up and welding experiments were performed. Some groups of welding images could been obtained. A composite filtering system composed of a neutral light reduction filter and a narrow band filter was developed to filter the weld arc disturbance. Some operations were performed to the images, namely the median filter and gray transformation. Then a neural network was setup, containing three layers. The inner widths of pool xn, the outer widths of pool xw, the width difference values e between the inner and outer of pool, ratios of inner pool widths Rn and ratios of outer pool widths Rw between two adjacent images were determined to be the input parameters. The penetration parameter p was chosen to be the output. Based on the images, groups of pool parameter data have been obtained and used to train the network. In this way, the weld penetration prediction model can be deduced. Finally, verification tests have been done. It showed that weld penetration situation predicted by the model is fit to its real condition. The accuracy rate is up to 96%, which affords a new way for penetration detection.
      PubDate: Thu, 31 Mar 2022 00:00:00 GMT
  • Corporate social responsibility fulfilment, product-market competition and
           debt risk: Evidence from China

    • Abstract: Based on the financial data for Chinese A-share companies listed in the Shanghai and Shenzhen stock exchanges and the corporate social responsibility (CSR) score data published in the Hexun website‡from 2010 to 2019, we carried out an empirical study and found that CSR fulfilment helps to restrain debt risk faced by firms, and that product-market competition can promote the inhibitory effect of CSR fulfilment on debt risk. The further study found that CSR fulfilment of monetary capital layer and human capital layer on debt risk will be significantly stronger than that of social capital layer.
      PubDate: Thu, 31 Mar 2022 00:00:00 GMT
  • The incentive contract of subject librarians in university library under
           the non-linear task importance

    • Abstract: Under the information asymmetry, we consider the impact of task importance on the income of university managers, introducing the non-linear income function of university managers. Based on the principal-agent theory, we construct a non-linear incentive optimisation model for subject librarians. We discussed how university managers allocate incentive intensity and how the subject librarians allocate the effort level to achieve the best net expected income for university administrators and subject librarians while satisfying the constraints of participation and incentive compatibility. The results show that the optimal incentive contract for subject librarians is related to task importance, ability level, risk aversion characteristics and the randomness of the external environment in university libraries. The relative incentive intensity increases with the increase of task importance, risk aversion, ability level and randomness of information retrieval tasks, and decreases with the increase of randomness of subject service tasks.
      PubDate: Thu, 31 Mar 2022 00:00:00 GMT
  • TOPSIS missile target selection method supported by the posterior
           probability of target recognition

    • Abstract: Addressing the problem of being easily interfered by false targets such as chaff and corner reflector when selecting missile targets, a multi-feature multi-model target selection method based on the technique for order preference by similarity to ideal solution (TOPSIS) is proposed if only single-target characteristics such as target position or radar cross section (RCS) size is used in the selection of missile targets. The target selection problem under the comprehensive utilisation of multiple features is regarded as a problem in decision-making based on multiple attributes. The BP network based on the target RCS frequency domain statistical features, the radial basis network based on the target polarisation feature and the radial size feature based on high-resolution range profile (HRRP) are realised. The comprehensive utilisation of C-support vector machine (SVM) and other target recognition methods and the comprehensive sorting of target selection, to a certain extent, enable anti-ship missiles to make the correct target selection more accurately. The simulation results display that the effective selection of ship targets can be achieved in the case of passive interference by surface ships.
      PubDate: Thu, 31 Mar 2022 00:00:00 GMT
  • A generative design method of building layout generated by path

    • Abstract: The floor plan is a key part of architectural design and has the characteristics of multi-objective evaluation. Traditional methods are often laborious and may lead to re-work due to optimisation, which affects efficiency. Related research uses various algorithms to generate floor plans to improve efficiency. Based on the leading role of architects on floor plans, this paper proposes a generative design method that combines the design process. It takes the space shape as the starting point, simplifies the design process into a mathematical model, and uses Rhino and Grasshopper to complete the algorithm development. Using different algorithm combinations, a large number of new layouts can be explored, and building layouts can be adjusted freely through data optimisation without having to redesign. The design evolution of floor plans of different cases shows that such a generative design method is feasible, reusable, and more efficient than traditional methods.
      PubDate: Thu, 31 Mar 2022 00:00:00 GMT
  • Selection by differential mortality rates

    • Abstract: In this work, a partial differential equation model for evolutionary dynamics is presented that describes changes in densities of phenotypes in a population. We consider that the traits of individuals of a population are distributed at an interval of real numbers where a mortality rate is assigned for each value of this interval. We present some conditions for stability of stationary solutions and apply the model in theoretical scenarios of natural selection. Particularly we approach cases of stabilising, disruptive and directional selection, including the scenario of the survival of the flattest. Some computational simulations are performed to illustrate the results obtained.
      PubDate: Wed, 26 May 2021 00:00:00 GMT
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