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Date Added: Jun 9, 2021
Authors: Ying Miao, Danyang Shao, Zhimin Yan
Journal: Complexity
Date Added: Jun 9, 2021
Authors: Ying Miao, Danyang Shao, Zhimin Yan
Journal: Complexity
In this paper, we analyze the location-following processing of the image by successive approximation with the need for directed privacy. To solve the detection problem of moving the human body in the dynamic background, the motion target detection module integrates the two ideas of feature information detection and human body model segmentation detection and combines the deep learning framework to complete the detection of the human body by detecting the feature points of key parts of the human body. The detection of human key points depends on the human pose estimation algorithm, so the research in this paper is based on the bottom-up model in the multiperson pose estimation method; firstly, all the human key points in the image are detected by feature extraction through the convolutional neural network, and then the accurate labelling of human key points is achieved by using the heat map and offset fusion optimization method in the feature point confidence map prediction, and finally, the human body detection results are obtained. In the study of the correlation algorithm, this paper combines the HOG feature extraction of the KCF algorithm and the scale filter of the DSST algorithm to form a fusion correlation filter based on the principle study of the MOSSE correlation filter. The algorithm solves the problems of lack of scale estimation of KCF algorithm and low real-time rate of DSST algorithm and improves the tracking accuracy while ensuring the real-time performance of the algorithm.
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Date Added: Jun 9, 2021
Authors: Yuanxun Zheng, Zhanlin Cao, Pan Guo, Pu Gao, Peng Zhang
Journal: Complexity
Date Added: Jun 9, 2021
Authors: Yuanxun Zheng, Zhanlin Cao, Pan Guo, Pu Gao, Peng Zhang
Journal: Complexity
The fatigue performance of the bridge deck significantly affects the safety and durability of the overall steel-concrete composite beam bridge. Based on the vehicle flow information of the highway within 10 years, the fatigue performance of a two-way four-lane steel-concrete composite continuous beam bridge deck is studied in this research. The results indicate that the effect of the wheel track position is negligible for two-way four-lane bridge when the wheel track sways laterally, and the fatigue stress of bridge deck concrete is the most unfavorable while the loading position is 7.0 m away from the bridge center line. The fatigue damage decreases by 30%–40% when the centerline of the lane deviates from the most unfavorable stress position by 1 m. The punching fatigue of the concrete is more sensitive to the changes in slab thickness, and the thickness of the deck concrete slab is recommended to be ≥35 cm.
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1
Date Added: Jun 9, 2021
Authors: Qiang Wei, Xinyu Gou, Tianyu Deng, Chunguang Bai
Journal: Complexity
Date Added: Jun 9, 2021
Authors: Qiang Wei, Xinyu Gou, Tianyu Deng, Chunguang Bai
Journal: Complexity
Collusion can increase the transaction value among supply chain members to obtain higher loans from supply chain finance (SCF) service provider, which will bring some serious risks for SCF. However, it is difficult to be identified and restrain the SCF service provider due to its stability and hiddenness. Different SCF transaction structures will affect the profits of supply chain members from collusion. This paper develops various game models for collusion and not collusion for different SCF transaction structures and investigates the impact of SCF transaction structures on the boundary conditions of collusion. Through comparative analysis, the findings of models are as follows: (1) in a two-echelon supply chain, the supplier and retailer are more likely to conduct collusion under the sequential game than under the simultaneous game; (2) collusion in the two-echelon supply chain can obtain higher loans than that in the three-echelon supply chain, so it has more serious hidden danger; (3) in the two-echelon supply chain, collusion is easier to form than in the three-echelon SCF supply chain that has spontaneous endogenous constraints. We also develop two types of mechanisms to restrain collusion behavior from profit sharing and incomplete information perspectives. Finally, we summarize the theoretical implications and analyze the management implications through a case study.
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Date Added: Jun 9, 2021
Authors: Chuanshuang Hu, Yongmei Ma, Ting Chen
Journal: Complexity
Date Added: Jun 9, 2021
Authors: Chuanshuang Hu, Yongmei Ma, Ting Chen
Journal: Complexity
Sustainable development education respects differences and encourages different assessment methods to evaluate students. During the epidemic, many colleges’ examinations changed from offline to online. How to fully consider students’ process learning status and make a reasonable evaluation of students is worthy of research. Based on the process learning data of a course in a university in China, this study establishes a discrete Hopfield neural network model to classify the test samples. In the process of modelling, the grey correlation analysis method is used to optimize the elements affecting students’ comprehensive evaluation index, and it solves the problem of failure of the model due to the large gap between the factors in the traditional discrete Hopfield neural network model. Then, the entropy right TOPSIS method is used to rank samples with the same evaluation grade. Teachers can objectively evaluate each student’s process learning performance according to the ranking results. Finally, the article compares and analyzes the evaluation results of various different methods. The analysis results believe that the optimized discrete Hopfield neural network is feasible in the process learning evaluation, and the model evaluation results are more objective and comprehensive.
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Date Added: Jun 9, 2021
Authors: Qin, Ling, et al
Journal: Complexity
Date Added: Jun 9, 2021
Authors: Qin, Ling, et al
Journal: Complexity
Biomass energy, contributing to about 80% of the total energy supply, is considered an important energy source in Madagascar. Although around 80% of energy use comes from biomass energy, the current application method of biomass in Madagascar is still in the earliest stage, which is not safe and sustainable. This is because the main form of biomass energy used in Madagascar is still solid charcoal and wood, and the technology is limited. Thus, it is necessary to search for better ways to utilize biomass energy in Madagascar because of high prices of traditional energy carriers and massive environmental pollution. This paper reviews the following: (1) a variety of available biomass wastes for energy in Madagascar including farming residuals, animal wastes, and forest wastes, as well as urban and industrial organic wastes; (2) advanced technologies, such as gasification, torrefaction, and fermentation, that can convert these wastes to biomass energy in forms with higher energy efficiency such as biogas, biocoal briquette, and ethanol fuel, which can not only help to achieve resource utilization of wastes and circular economy but also ease the energy crisis faced by Madagascar; and (3) Madagascar focused on the development of biomass energy with strategic policies and programs. International assistance also contributes to future promotion of biomass energy. It identifies several areas where research is urgently required to adopt instrumental policies to ensure that both rural development objectives and renewable energy targets are met with financial support from the government and international assistance.
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Date Added: Jun 9, 2021
Authors: Xuesong Shao, Gaoying Cui, Xiao Chen, Xinrong Ji, Yongxian Yi
Journal: Complexity
Date Added: Jun 9, 2021
Authors: Xuesong Shao, Gaoying Cui, Xiao Chen, Xinrong Ji, Yongxian Yi
Journal: Complexity
In recent years, with the continuous growth of China’s power peak load and the rapid development of renewable energy, a large number of renewable energy sources are connected to the power grid, increasing the uncertainty of power grid operation and posing new major challenges to the power system regulation capacity. Flexible load has the characteristics of wide distribution, fast response, and high economy, which is an important control resource for the future power system. Based on the flexible load of commercial buildings and residential users, this paper studies the resource characteristics and response characteristics, clarifies the resource characteristics and demand response characteristic indexes of commercial and residential users, and establishes the response characteristics model of commercial buildings and residential users. Considering the influence of weather, holidays, incentive mechanism, and other factors on the response of flexible load, the quantitative analysis method of flexible load resource regulation potential for regional power grid dispatching was studied, and the feasibility of flexible load resources directly participating in the load control system was analyzed. Based on the uncertainty and mathematical characterization method of the active response of flexible loads, the optimal combination control strategy of demand response resources was proposed to eliminate the problems of heavy load and overload of regional power grid equipment by using the active response ability of flexible loads. Finally, the IEEE 14-node system is selected for simulation verification, which provides a theoretical basis for alleviating the power grid operation pressure in the peak load period of the power grid in the urban core area, improving the safety and economic operation level of regional power grid dispatching and the utilization rate of power grid equipment assets.
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Date Added: Jun 9, 2021
Authors: Dan Chen
Journal: Complexity
Date Added: Jun 9, 2021
Authors: Dan Chen
Journal: Complexity
Government debt risk is an important factor affecting macroeconomic stability and public expectation. The key to its prevention and control lies in early warning and early prevention. This paper builds an effective government debt risk assessment system based on machine learning algorithm. According to forming the performance of local government debt risk and its internal and external influencing factors, this study applies the analytic hierarchy process, entropy method, and BP neural network method to construct the local government risk assessment index system, which includes the primary and secondary indexes including the explicit debt risk, the contingent implicit debt risk, and the financial and economic operation risk. Using this system, this study carries on the government debt risk comprehensive weight assignment, the fiscal revenue forecast, the default probability calculation, the safety scale forecast, and finally the government debt risk assessment of the validity analysis. The system can provide signal guidance and policy reference for finance to cope with risks in advance, arrange the priority order of debt repayment, optimize the structure of fiscal revenue and expenditure, etc.
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Date Added: Jun 10, 2021
Authors: Boxun Li
Journal: Complexity
Date Added: Jun 10, 2021
Authors: Boxun Li
Journal: Complexity
Artificial intelligence (AI) is an important driving force of the new round of technological revolution and industrial change, and the development of a new generation of AI can help improve comprehensive national power and promote healthy and sustainable economic development. AI can promote economic development through four ways. First, AI replaces labor, expands labor connotation, increases labor supply, and enriches labor wealth; AI empowers laborers and improves labor productivity. Second, AI empowers the three industries and improves production efficiency. Third, AI creates consumer surplus and improves social welfare. Fourth, AI empowers government to correct government failure and improve government efficiency, which in turn corrects market failure and improves economic efficiency. The economic subsystem covers both quantitative and qualitative aspects of economic growth, economic structure, economic efficiency, and economic support. Environmental subsystems are divided into environmental quality, environmental pollution, and environmental protection. While using AI to promote economic development, it is also important to strengthen the research and prevention of potential risks of AI development to ensure that AI is safe, reliable, and controllable.
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Date Added: Jun 10, 2021
Authors: Jiayi Lu, Dongqi Sun
Journal: Complexity
Date Added: Jun 10, 2021
Authors: Jiayi Lu, Dongqi Sun
Journal: Complexity
With the development of globalization and informatization, the relationships among cities have become closer, and a “network” paradigm in urban studies is gaining attention. To examine China’s urban network evolution in a long time series, we used flow-based data to measure enterprise linkages from 1978 to 2019. We investigated the spatiotemporal evolution and complexity characteristics of urban networks in China and arrived at the following conclusions. (1) Intercity enterprise linkages in China have been continuously strengthened. The scale and density of urban networks have increased rapidly. Although the distribution of node cities’ importance and influence has been significantly unbalanced, the degree of which has lessened over time. (2) Network density has significantly improved since 1978, gradually forming a monocentric (Beijing) radial pattern. From the beginning of the twenty-first century, the status of core nodes (e.g., Shanghai) has gradually become prominent. Finally, four vertices stood out in 2019, forming a stable diamond structure. The spatial connection flows of enterprises constituted the core networks with Beijing as the center, skeleton networks with trunk lines formed by subnodes, and regional networks covering a wide range of peripheral areas. (3) China’s urban networks were typically small-scale and scale-free. However, the scale-free characteristics were weakened after 2010. The overall scale gap of intercity enterprise linkages gradually narrowed, and the structure of urban networks became optimized. Meanwhile, the urban networks were heterogeneous. There were more cities with headquarter-branches and active investment behaviors, which had strong influence and control over networks, playing their functions of “broker” and “transfer.”
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Date Added: Jun 10, 2021
Authors: Hyun Sik Sim
Journal: Complexity
Date Added: Jun 10, 2021
Authors: Hyun Sik Sim
Journal: Complexity
To realize intelligent manufacturing, a controllable factory must be built, and manufacturing competitiveness must be achieved through the improvement of product quality and yield. The yield in the micromanufacturing process is gaining importance as a management factor used in deciding the production cost and product quality as product functions becomes more sophisticated. Because the micromanufacturing process involves manufacturing products through multiple steps, it is difficult to determine the process or equipment that has encountered failure, which can lead to difficulty in securing high yields. This study presents a structural model for building a factory integration system to analyze big data at manufacturing sites and a hierarchical factor analysis methodology to increase product yield and quality in an intelligent manufacturing environment. To improve the product yield, it is necessary to analyze the fault factors that cause low yields and locate and manage the critical processes and equipment factors that affect these fault factors. However, yield management is a difficult problem because there exists a correlation between equipment, and in the sequence of process equipment that the lot passed through, the downstream and the upstream cause complex faults. This study used data-mining techniques to identify suspected processes and equipment that affect the yield of products in the manufacturing process and to analyze the key factors of the equipment. Ultimately, we propose a methodology to find the key factors of the suspected process and equipment that directly affect the implementation of the intelligent manufacturing scheme and the yield of the product. To verify the effect of key parameters of critical processes and equipment on the yield, the proposed methodology was applied to actual manufacturing sites.
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