Mathematical Problems in Engineering

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ISSN / EISSN : 1024-123X / 1563-5147
Published by: Hindawi Limited (10.1155)
Total articles ≅ 16,875
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Hongyu Wei, Wenqi Tang, Xuan Chu, ,
Mathematical Problems in Engineering, Volume 2021, pp 1-8; https://doi.org/10.1155/2021/8555280

Abstract:
A grading method of potted Anthurium based on machine vision is proposed. A detection system is designed to acquire color images and depth images of potted Anthurium, and the three-dimensional point-cloud image is reconstructed after registration. According to the testing requirements of potted Anthurium, the minimum enclosing rectangle method is used to measure the width of crowns and spathes. The bubble sequencing method is used to measure the plant height, and the clustering segmentation method is used to calculate the number of spathes. Online automatic grading software for potted Anthurium is developed. Compared with manual measurement, the average measurement accuracies of machine vision for crown width, plant height, spathe width, and spathe number are 98.4%, 98.4%, 98.8%, and 86.7%, respectively. The accuracy rate of grading is 85.86%, which can meet the requirements of automatic grading of potted Anthurium.
Alireza Jafari Doudaran, , Ahmad Makui, Mostafa Jafari
Mathematical Problems in Engineering, Volume 2021, pp 1-13; https://doi.org/10.1155/2021/1784232

Abstract:
This paper provides a method to numerically measure the quality of working life based on the reduction of human resource risks. It is conducted through the improved metaheuristic grasshopper optimization algorithm in two phases. First, a go-to study is carried out to identify the relationship between quality of working life and human resource risks in the capital market and to obtain the factors from quality of working life which reduce the risks. Then, a method is presented for the numerical measurement of these factors using a fuzzy inference system based on an adaptive neural network and a new hybrid method called the improved grasshopper optimization algorithm. This algorithm consists of the grasshopper optimization algorithm and the bees algorithm. It is found that the newly proposed method performs better and provides more accurate results than the conventional one.
Chenyang Tang, Hanwen Zhang, Songze Liu, Guanlin Zhu, Minghao Sun, Yushuai Wu, Yongde Gan
Mathematical Problems in Engineering, Volume 2021, pp 1-15; https://doi.org/10.1155/2021/5783713

Abstract:
The Australian wildfires in 2019–2020 have brought suffering to the Australian people. It is essential to use models to help the Victorian government monitor and predict the occurrence and development of fires to the greatest extent possible under the principles of safety and economy to facilitate rapid response. Through the idea of K -means algorithm and greedy algorithm, we, respectively, analyzed cities and rural areas at different altitudes and combined the altitude with the obtained clusters; the analysis from the established model shows that, for cities, cluster areas with smaller clusters with an altitude of less than 1600 meters and areas with smaller clusters with an altitude of greater than or equal to 1800 meters are covered by an EOC; for areas with larger clusters less than or equal to 600 meters above the sea level and areas with larger clusters greater than or equal to 1000 meters above the sea level, we use two EOCs for coverage; for rural areas, all areas with smaller clusters are covered by one EOC, while for areas with larger clusters where the altitude is less than or equal to 1000 meters and the altitude is greater than or equal to 1600 meters, we use two EOCs for coverage; also, obtained through greedy algorithm analysis, one EOC corresponds to 14 SSA UAVs and 8 repeater UAVs, and two EOCs correspond to 12 repeater UAVs and 26 SSA UAVs. We have a reason to believe that, through our mathematical model and the leaps in drone technology, it will have a long-term and profound impact on Australia’s wildfire control.
Xia Zhou, Kaili Xiang, Rongmei Sun
Mathematical Problems in Engineering, Volume 2021, pp 1-11; https://doi.org/10.1155/2021/2142876

Abstract:
The wealth substitution rate, which describes the substitution relationship between agents’ investment in wealth, is introduced into the collision kernel of the Boltzmann equation to study wealth distribution. Using the continuous trading limit, the Fokker–Planck equation is derived and the steady-state solution is obtained. The results show that the inequality of wealth distribution decreases as the wealth substitution rate increases under certain assumptions. The wealth distribution has a bimodal shape if the wealth substitution rate does not equal one.
Mathematical Problems in Engineering, Volume 2021, pp 1-14; https://doi.org/10.1155/2021/3517145

Abstract:
In the context of cloud computing, one problem that is frequently encountered is task scheduling. This problem has two primary implications, which are the planning of tasks on virtual machines and the attenuation of performance. In order to address the problem of task scheduling in cloud computing, requisite nontraditional optimization attitudes to attain the optima of the problem, the present paper puts forth a hybrid multiple-objective approach called hybrid grey wolf and whale optimization (HGWWO) algorithms, that integrates two algorithms, namely, the grey wolf optimizer (GWO) and the whale optimization algorithm (WOA), with the purpose of conjoining the advantages of each algorithm for minimizing costs, energy consumption, and total execution time needed for task implementation, beside that improving the use of resources. Assessment of the aims of the proposed approach is carried out with the help of the tool known as CloudSim. As pointed out by the results of the experimental work undertaken, the proposed approach has the capability of performing at a superior level by comparison to the original algorithms GWO and WOA on their own with regard to costs, energy consumption, makespan, use of resources, and degree of imbalance.
Muhammad Imran Asjad, Abdul Basit, , Taseer Muhammad
Mathematical Problems in Engineering, Volume 2021, pp 1-9; https://doi.org/10.1155/2021/5403879

Abstract:
The unsteady flow of Jeffrey fluid along with a vertical plate is studied in this paper. The equations of momentum, energy, and generalized Fourier’s law of thermal flux are transformed to non-dimensional form for the proper dimensionless parameters. The Prabhakar fractional operator is applied to acquire the fractional model using the constitutive equations. To obtain the generalized results for velocity and temperature distribution, Laplace transform is performed. The influences of fractional parameters α , β , γ , thermal Grashof number Gr , and non-dimensional Prandtl number Pr upon velocity and temperature distribution are presented graphically. The results are improved in the form of decay of energy and momentum equations, respectively. The new fractional parameter contains the Mittag-Leffler kernel with three fractional parameters which are responsible for better memory of the fluid properties rather than the exponential kernel appearing in the Caputo–Fabrizio fractional operator. The Prabhakar fractional operator has advantage over Caputo–Fabrizio in the real data fitting where needed.
Kongze Zhu, Lei Zheng
Mathematical Problems in Engineering, Volume 2021, pp 1-10; https://doi.org/10.1155/2021/9017181

Abstract:
Artificial intelligence is a recently emerging system that uses computers and big data as the basis to simulate human-like behavior with machines. Artificial intelligence is a way to imitate human thinking by learning massive data knowledge and using algorithms to reason and analyze the data. In the current age of advanced technology, many jobs in the justice system can be replaced by artificial technology technologies. Many courts have now scrutinized the use of artificial intelligence in the judiciary. With artificial intelligence, timely warnings on all aspects of admissions can effectively protect random or outdated trials and allocate social resources appropriately. In addition, it may better redress cases of misconduct and irregular conduct in the judiciary, which is conducive to justice. Based on BP neural network, research on related content and other methods has drawn relevant arguments, which will provide a certain theoretical basis for artificial intelligence to assist the judicial field in the future. The research in this article shows that artificial intelligence is conducive to suppressing duty crimes in the judicial field, promoting the transformation of extensive processing to intensive processing, and is conducive to judicial efficiency. In 2017, there were more than 8 million first-instance civil cases, but only 100,000 cases were closed. But by 2020, with the construction of smart courts, millions of cases out of more than 10 million first-instance civil cases are expected to be closed. The situation has been greatly improved. But at the same time, we also need to prevent the leakage of artificial intelligence to personal privacy, establish and improve corresponding laws and regulations, and coordinate the judgment relationship between the human brain and the machine brain. Artificial intelligence may be more suitable for assisting judicial judgments.
Tingzhong Wang, Binbin Zhang, Mengyan Zhang, Sen Zhang
Mathematical Problems in Engineering, Volume 2021, pp 1-8; https://doi.org/10.1155/2021/6964875

Abstract:
Aiming at the problem that traditional heuristic algorithm is difficult to extract the empirical model in time from large sample terrain data, a multi-UAV collaborative path planning method based on attention reinforcement learning is proposed. The method draws on a combined consideration of influencing factors, such as survival probability, path length, and load balancing and endurance constraints, and works as a support system for multimachine collaborative optimizing. The attention neural network is used to generate the cooperative reconnaissance strategy of the UAV, and a large amount of simulation data is tested to optimize the attention network using the REINFORCE algorithm. Experimental results show that the proposed method is effective in solving the multi-UAV path planning issue with high real-time requirements, and the solving time is less than the traditional algorithms.
Dongling Yu, Huiling Zhang, Xiaohui Zhang, Dahai Liao, Nanxing Wu
Mathematical Problems in Engineering, Volume 2021, pp 1-9; https://doi.org/10.1155/2021/4922315

Abstract:
In order to improve the detection accuracy and efficiency of silicon nitride ceramic ball surface defects, a defect detection algorithm based on SWT and nonlinear enhancement is proposed. In view of the small surface defect area and low contrast of the silicon nitride ceramic ball, a machine vision-based nondestructive inspection system for surface images is constructed. Sobel operation is used to eliminate the nonuniform background, and the silicon nitride ceramic ball surface image is decomposed by SWT. And frequency-domain index low-pass filtering is used to modify the decomposition coefficients, and an adaptive nonlinear model is proposed to enhance defects; finally, the image is reconstructed and segmented by the stationary wavelet inverse transform and the dynamic threshold method, respectively. The enhanced algorithm can effectively identify surface defects and is superior to traditional defect detection algorithms.
Haihua Zhou, Jing Liu, Xiaodong Cui
Mathematical Problems in Engineering, Volume 2021, pp 1-13; https://doi.org/10.1155/2021/5082594

Abstract:
Many scholars have conducted extensive research on the adoption behavior of mobile readers, and there are obvious differences in the degree and direction of conclusions drawn from different individual studies. In this study, a meta-analysis method was used to comprehensively analyze a total of 74,964 independent samples of 31 relevant empirical research documents at home and abroad. The results show that the main influencing factors of mobile reading are perceived usefulness, perceived ease of use, perceived mobility, perceived entertainment, social influence, cognitive adjustment, perceived value, usage attitude, interface design, etc. Cognitive adjustment and usage attitude have the greatest impact on intention to use, followed by perceived usefulness, perceived mobility, subjective norms, perceived ease of use; perceived ease of use has a significant positive impact on perceived usefulness; interface design has a significant positive effect on perceived ease of use; behavioral intention has a significant positive effect on actual behavior; and perceived usefulness and perceived ease of use have a significant positive effect on usage attitude.
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