Mathematical Problems in Engineering
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Acceptance rate42%
Submission to final decision60 days
Acceptance to publication21 days
CiteScore1.800
Journal Citation Indicator0.400
Impact Factor1.305

Underwater Imaging Formation Model-Embedded Multiscale Deep Neural Network for Underwater Image Enhancement

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 Journal profile

Mathematical Problems in Engineering is a broad-based journal publishing results of rigorous engineering research across all disciplines, carried out using mathematical tools.

 Editor spotlight

Chief Editor, Professor Guangming Xie, is currently a full professor of dynamics and control with the College of Engineering, Peking University. His research interests include complex system dynamics and control and intelligent and biomimetic robots.

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We currently have a number of Special Issues open for submission. Special Issues highlight emerging areas of research within a field, or provide a venue for a deeper investigation into an existing research area.

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Research Article

Research on National Costume Design Based on Virtual Reality Technology

Cheongsam has the unique costume culture characteristics of the Chinese nation and is a classic style of traditional Chinese costumes. At the same time, with the rapid development of science and technology, 3D virtual technology plays an increasingly important role in the garment intelligent manufacturing industry. Therefore, how to combine 3D virtual technology with the development of women’s cheongsam clothing products is of great significance, which can overcome the limitations of time and space and effectively improve the efficiency of clothing pattern design. To solve this problem, a design method for national costume based on virtual reality technology is proposed. First of all, the modeling and structural characteristics of cheongsam are analyzed. Secondly, different curve fitting methods are applied to human body feature recognition, and cubic polynomial fitting is selected to complete the feature recognition of the human body model in a virtual environment. Then, in order to prevent the penetration between clothing and the human body, the collision detection function based on the AABB bounding box is added, and a method based on linear sensitivity is used to map 2D to 3D. Finally, the model of a cheongsam costume is created by using the clothing simulation Marvelous Designer software, and the effectiveness of the proposed virtual cheongsam costume simulation design method is verified by subjective evaluation indexes.

Research Article

Human Resource Management of Energy Companies Based on Big Data Analysis

Human resource management mode refers to a comprehensive summary of management objectives, processes, content, methods, and other elements. The more common two modes are control mode and commitment mode. The enterprise human resource management model has many different types. The generation pair promotes the development of enterprise human resource management from the traditional model to the platform model, processing complex data with the help of data-based technical means, and realizing the integration and sharing of resource data. This paper takes an energy company as an example to carry out a detailed study. The article takes the big data as the background and the company as the research object. From the perspective of human resource management, this paper tries to find out the performance management, compensation and benefits management, and other issues of the company in human resource management under the background of the big data era and puts forward corresponding solutions for the current problems. In particular, the company gave certain opinions on how to build a human resource management system in the context of the current big data era. By conducting field research on the company and issuing questionnaires, this paper finds out the current problems of the company in human resource management and proposes corresponding solutions for these problems.

Research Article

Finite-Buffer M/G/1 Queues with Time and Space Priorities

Many communication systems have finite buffers and service delay-sensitive and loss-sensitive types of traffic simultaneously. To meet the diverse QoS requirements of these heterogeneous types of traffic, it is desirable to offer delay-sensitive traffic time priority over loss-sensitive traffic, and loss-sensitive traffic space priority over delay-sensitive traffic. To analyze the performance of such systems, we study a finite-buffer M/G/1 priority queueing model where nonpreemptive time priority is given to delay-sensitive traffic and push-out space priority is given to loss-sensitive traffic. Compared to the previous study on finite-buffer M/M/1 priority queues with time and space priority, where service times are identical and exponentially distributed for both types of traffic, in our model we assume that service times are different and are generally distributed for different types of traffic. As a result, our model is more suitable for the performance analysis of communication systems accommodating multiple types of traffic with different service-time distributions. For the proposed queueing model, we derive the queue-length distributions, loss probabilities, and mean waiting times of both types of traffic, as well as the push-out probability of delay-sensitive traffic. With numerical examples, we also explore how the performance measures are affected by system parameters such as the buffer size, and the arrival rates and mean service times of both types of traffic for different service-time distributions.

Research Article

Study on Coupling and Coordinated Development of Ecological Environment-Energy Consumption-Regional Economic Growth in Greater Bay Area around Hangzhou Bay

Environment, energy, and economy often constitute an interrelated and contradictory ternary system. In this study, Greater Bay Area around Hangzhou Bay Area is taken as the main research object, and Guangdong-Hong Kong-Macao Greater Bay Area is taken as the reference object. By constructing the index system of 3E system coordination evaluation model, the coordination degree and coordination status of ecological environment, energy consumption, and economic growth subsystems of the two areas are compared and analyzed, and the coupling relationship between 2E and 3E systems of Greater Bay Area around Hangzhou Bay and Guangdong-Hong Kong-Macao Greater Bay Area is further studied. The results show that the eco-environmental coordination degree and energy consumption coordination degree of the cities in Greater Bay Area around Hangzhou Bay are between 0.4248–0.5668 and 0.4528–0.5874, respectively, which are in the state of weak coordination to primary coordination, while the economic growth coordination degree is between 0.5022 and 0.6878, which is in the state of primary coordination to intermediate coordination. The coupling of 2E system in Greater Bay Area around Hangzhou Bay and Guangdong-Hong Kong-Macao Greater Bay Area shows linear growth and nonlinear growth, respectively (R2 = 0.997), presenting a good coupling development overall. The coupling levels of ecological environment-energy consumption, ecological environment-economic growth, and energy consumption-economic growth in Greater Bay Area around Hangzhou Bay increase by 18.94, 86.72, and 98.20% respectively. The coupling of 3E systems between Greater Bay Area around Hangzhou Bay and Guangdong-Hong Kong-Macao Greater Bay Area presents a nonlinear development trend that is increasing year by year (R2 > 0.99), but the coupling level of 3E systems between the two is still low, both of which are in the primary/weak coordination state, while the overall growth rate of 3E system coupling in Greater Bay Area around Hangzhou Bay is higher than that of Guangdong-Hong Kong-Macao Greater Bay Area.

Research Article

Systematic Mode Construction of Mixed Teaching from the Perspective of Deep Learning

Deep learning will be one of the key technologies to promote learning in the next five years. With the rapid advancement of the information era, significant changes in students’ learning and thinking patterns have occurred. How to further encourage the development of students’ professional skills and innovative capacity has become the focus of society under the influence of the notion of deep learning. With the application of information technology in education, blended learning, as the only key trend mentioned in the new media alliance report for five consecutive years, has injected fresh vitality into the reform of traditional classrooms and laid a foundation for better promoting in-depth learning. Therefore, how to effectively use blended learning to change these phenomena has become an urgent problem to be solved. The goal of this research is to encourage pupils to learn in depth. This study specifies the design idea of a hybrid teaching mode supported by an information environment based on the promotion of high-order thinking capacity. Firstly, this study uses the literature research method to sort out the relevant literature on deep learning and hybrid teaching, which provides a theoretical basis for the later construction. Second, a questionnaire is utilized to assess the existing state of in-depth learning as well as the need for blended teaching. The mixed teaching mode has effectively promoted the development of students’ high-level thinking abilities such as autonomous learning, problem-solving, and application innovation; played a positive role in cultivating students’ in-depth learning; and finally won the unanimous recognition of students.

Research Article

Enterprise Financing Risk Analysis and Internal Accounting Management Based on BP Neural Network Model

A BP neural network-based model is proposed to study corporate financial risk analysis and internal accounting management. Using MATLAB software and the BP neural network model, it is possible to obtain enterprise financing risk situations over a period by simulating and predicting enterprise financing risks by creating an early warning model for enterprise financing risks. Finally, from the point of view of the company's internal and external operations, the company's financial risk prevention measures and proposals are proposed to improve the financing efficiency of the companies and to prevent financial risks. This study predicts the financing risk of companies listed on the Mongolian Stock Exchange and analyzes the causes of the risk status. According to the test results, the learning speeds for successive substitutions are as follows: 0.005, 0.01, 0.02, 0.03, and 0.04. Finally, it was found that the error was minimal and the stability was best when the learning speed was exactly 0.01. The error is 0.0031011, and the step size is 157, which is only slightly lower than the target error value, which indicates that the learning speed is good. In addition, the novelty of this study is the use of the BP neural network model to conduct an early warning study of corporate financial risks. The BP neural network assessment model for corporate lending risk in this document is highly accurate. In addition to providing theoretical insights to researchers, it can be a good tool for banks to realistically assess the credit risk of SME supply chain financing.

Mathematical Problems in Engineering
 Journal metrics
See full report
Acceptance rate42%
Submission to final decision60 days
Acceptance to publication21 days
CiteScore1.800
Journal Citation Indicator0.400
Impact Factor1.305
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Article of the Year Award: Outstanding research contributions of 2020, as selected by our Chief Editors. Read the winning articles.