Jiahao Wang, Guodong Xia, Ran Li, Dandan Ma, Wenbin Zhou and Jun Wang
This study aims to satisfy the thermal management of gallium nitride (GaN) high-electron mobility transistor (HEMT) devices, microchannel-cooling is designed and optimized in this…
Abstract
Purpose
This study aims to satisfy the thermal management of gallium nitride (GaN) high-electron mobility transistor (HEMT) devices, microchannel-cooling is designed and optimized in this work.
Design/methodology/approach
A numerical simulation is performed to analyze the thermal and flow characteristics of microchannels in combination with computational fluid dynamics (CFD) and multi-objective evolutionary algorithm (MOEA) is used to optimize the microchannels parameters. The design variables include width and number of microchannels, and the optimization objectives are to minimize total thermal resistance and pressure drop under constant volumetric flow rate.
Findings
In optimization process, a decrease in pressure drop contributes to increase of thermal resistance leading to high junction temperature and vice versa. And the Pareto-optimal front, which is a trade-off curve between optimization objectives, is obtained by MOEA method. Finally, K-means clustering algorithm is carried out on Pareto-optimal front, and three representative points are proposed to verify the accuracy of the model.
Originality/value
Each design variable on the effect of two objectives and distribution of temperature is researched. The relationship between minimum thermal resistance and pressure drop is provided which can give some fundamental direction for microchannels design in GaN HEMT devices cooling.
Details
Keywords
Lu Wang, Jiahao Zheng, Jianrong Yao and Yuangao Chen
With the rapid growth of the domestic lending industry, assessing whether the borrower of each loan is at risk of default is a pressing issue for financial institutions. Although…
Abstract
Purpose
With the rapid growth of the domestic lending industry, assessing whether the borrower of each loan is at risk of default is a pressing issue for financial institutions. Although there are some models that can handle such problems well, there are still some shortcomings in some aspects. The purpose of this paper is to improve the accuracy of credit assessment models.
Design/methodology/approach
In this paper, three different stages are used to improve the classification performance of LSTM, so that financial institutions can more accurately identify borrowers at risk of default. The first approach is to use the K-Means-SMOTE algorithm to eliminate the imbalance within the class. In the second step, ResNet is used for feature extraction, and then two-layer LSTM is used for learning to strengthen the ability of neural networks to mine and utilize deep information. Finally, the model performance is improved by using the IDWPSO algorithm for optimization when debugging the neural network.
Findings
On two unbalanced datasets (category ratios of 700:1 and 3:1 respectively), the multi-stage improved model was compared with ten other models using accuracy, precision, specificity, recall, G-measure, F-measure and the nonparametric Wilcoxon test. It was demonstrated that the multi-stage improved model showed a more significant advantage in evaluating the imbalanced credit dataset.
Originality/value
In this paper, the parameters of the ResNet-LSTM hybrid neural network, which can fully mine and utilize the deep information, are tuned by an innovative intelligent optimization algorithm to strengthen the classification performance of the model.
Details
Keywords
This paper discusses the use of three-dimensional mapping software SolidWorks as a platform to build a parametric model of coal mine filling equipment and a model library of the…
Abstract
This paper discusses the use of three-dimensional mapping software SolidWorks as a platform to build a parametric model of coal mine filling equipment and a model library of the equipment. The Solidworks software is used to create a near-realistic virtual environment to simulate and analyze the process of building a high-water filling station. In this way, designers can detect potential design flaws early and then optimize the design as much as possible before actual construction.
Details
Keywords
Dangshu Wang, Mingyao Liu, Ruchuan Zhang, Jiahao Yang and Jing Wang
The purpose of this study is to solve the problem of longer dead-time in the rear bridge leg switches and lower efficiency in the Four-Switch Buck-Boost LLC Resonant Converter.
Abstract
Purpose
The purpose of this study is to solve the problem of longer dead-time in the rear bridge leg switches and lower efficiency in the Four-Switch Buck-Boost LLC Resonant Converter.
Design/methodology/approach
The paper adopts time-domain analysis to derive the time-domain expression for optimal dead time, analyzing the conditions for achieving soft switching of the transistors. It further explores the relationship between the dead time of the bridge arm switching transistors and the input/output of the converter under different operating conditions. Specifically, the dead time of the upper bridge arm transistors increases with the converter input voltage and decreases with the output current. In contrast, the dead time of the lower bridge arm transistors is independent of the converter output current and decreases with increasing converter input voltage.
Findings
By simulating and constructing a 500 W experimental prototype, experimental results indicate that designing the dead time of the switch according to the optimal dead time proposed in this paper significantly improves efficiency when the converter operates from heavy load to full load. When the transformer takes minimum input, maximum input and intermediate bus voltage inputs respectively, its peak efficiency is increased by 0.6%, 1.7% and 1.1%, respectively, compared to the traditional four-switch Buck–Boost LLC resonant converter.
Originality/value
Experimental validation confirms the correctness of the optimal dead time design and analyzes the impact of different operating conditions of the converter on the dead time. This is of significant importance for the rational design of switch dead times and the enhancement of converter efficiency.
Details
Keywords
Xiaona Wang, Jiahao Chen and Hong Qiao
Limited by the types of sensors, the state information available for musculoskeletal robots with highly redundant, nonlinear muscles is often incomplete, which makes the control…
Abstract
Purpose
Limited by the types of sensors, the state information available for musculoskeletal robots with highly redundant, nonlinear muscles is often incomplete, which makes the control face a bottleneck problem. The aim of this paper is to design a method to improve the motion performance of musculoskeletal robots in partially observable scenarios, and to leverage the ontology knowledge to enhance the algorithm’s adaptability to musculoskeletal robots that have undergone changes.
Design/methodology/approach
A memory and attention-based reinforcement learning method is proposed for musculoskeletal robots with prior knowledge of muscle synergies. First, to deal with partially observed states available to musculoskeletal robots, a memory and attention-based network architecture is proposed for inferring more sufficient and intrinsic states. Second, inspired by muscle synergy hypothesis in neuroscience, prior knowledge of a musculoskeletal robot’s muscle synergies is embedded in network structure and reward shaping.
Findings
Based on systematic validation, it is found that the proposed method demonstrates superiority over the traditional twin delayed deep deterministic policy gradients (TD3) algorithm. A musculoskeletal robot with highly redundant, nonlinear muscles is adopted to implement goal-directed tasks. In the case of 21-dimensional states, the learning efficiency and accuracy are significantly improved compared with the traditional TD3 algorithm; in the case of 13-dimensional states without velocities and information from the end effector, the traditional TD3 is unable to complete the reaching tasks, while the proposed method breaks through this bottleneck problem.
Originality/value
In this paper, a novel memory and attention-based reinforcement learning method with prior knowledge of muscle synergies is proposed for musculoskeletal robots to deal with partially observable scenarios. Compared with the existing methods, the proposed method effectively improves the performance. Furthermore, this paper promotes the fusion of neuroscience and robotics.
Details
Keywords
Jiahao Shi, Ling Weng, Xiaoming Wang, Xue Sun, Shuqiang Du, Feng Gao and Xiaorui Zhang
Epoxy resin (EP) is a kind of thermosetting resin, and its application is usually limited by poor toughness. In this case, a type of new flexible chain blocking hyperbranched…
Abstract
Purpose
Epoxy resin (EP) is a kind of thermosetting resin, and its application is usually limited by poor toughness. In this case, a type of new flexible chain blocking hyperbranched polyester (HBP) was designed and synthesized. The purpose of this study is to enhance the toughness and dielectric properties of EP.
Design/methodology/approach
P-toluene sulfonic acid was used as the catalyst, with dimethy propionic acid as the branch unit and pentaerythritol as the core in the experiment. Then, n-hexanoic acid and n-caprylic acid were, respectively, put to gain HBP with a n-hexanoic acid and n-caprylic acid capped structure. The microstructure, mechanical properties, insulation properties and dielectric properties of the composite were characterized for the purpose of finding the appropriate proportion of HBP.
Findings
HBP enhanced the toughness of epoxy-cured products by interpenetrating polymer network structure between the flexible chain of HBP and the EP molecular chain. Meanwhile, HBP reduced the ε and tgδ of the epoxy anhydride-cured product by reducing the number of polar groups per unit volume of the EP through free volumes.
Research limitations/implications
Yet EP is a kind of thermosetting resin, which is widely used in coating, aerospace, electronics, polymer composites and military fields, but it is usually limited by poor toughness. In a word, it is an urgent priority to develop new EP with better toughness and mechanical properties.
Originality/value
At present, HBP has been applied as a new kind of toughening strategy and as a modifier for EP. According to the toughening mechanism of HBP modified EP, the free volume of HBP creates a space for the EP molecule to move around when loaded. Moreover, the free volume could cause the dielectric constant of EP to diminish by reducing the content of polarizable groups. Meanwhile, the addition of HBP with flexible chains grafted to the EP could develop an interpenetrating network structure, thus further enhancing the toughness of EP
Details
Keywords
In the Information Age, an increasing number of firms and researchers focus on consumer privacy. Meanwhile, many firms that collect consumer information through, information…
Abstract
Purpose
In the Information Age, an increasing number of firms and researchers focus on consumer privacy. Meanwhile, many firms that collect consumer information through, information disclosure, consumer privacy, agency model, distribution contracts products or services often adopt the agency contract or the wholesale contract to sell through the online platform. This study aims to examine how different distribution contracts affect supply chain decisions when the firm can profit from disclosing consumer information.
Design/methodology/approach
The authors use Stackelberg model to describe the relationship between consumer privacy and distribution contracts. Solve the model and analyze the monotonicity of the equilibrium results. The optimal contract choice and win-win conditions are obtained by comparing the profits under different contracts.
Findings
The authors find that when consumers’ maximal valuation is low in the market, the firm prefers to profit from disclosing consumer information under both the agency contract and the wholesale contract. As consumers’ maximal valuation increases, the firm turns to profit from product sales. Under the agency contract, the platform only generates profit when the consumers’ maximal valuation is high. By comparing the profits of the platform under the two types of contracts, the authors find the platform’s optimal contract choice under different consumers’ maximal valuations and platform commission rates. Combined with the comparison results of the firm’s profit, the authors provide the win-win conditions under the agency contract and wholesale contract.
Originality/value
This study analyzes the supply chain decision under the agency contract and wholesale contract, and it helps deepen the understanding of the interaction between consumer information disclosure and channel distribution contract.
Details
Keywords
Zhouhai Chen, Hong Wang and Jiahao Hu
Food labels are increasingly used to provide information to consumers. As a common design strategy used for food package labels globally, label frame is often used to expand the…
Abstract
Purpose
Food labels are increasingly used to provide information to consumers. As a common design strategy used for food package labels globally, label frame is often used to expand the perceived breadth of a brand and create a broader brand image. We evaluated the effect of the presence or absence of a non-genetically modified organism (non-GMO) label frame on consumers' preferences for non-GMO foods.
Design/methodology/approach
This study collected data from 120 MBA students at a university in Sichuan, China, and 126 foreign volunteers in a shopping mall in Chengdu, Sichuan Province. The study investigates the effect of the presence or absence of non-GMO label frame (i.e. label with or without an outline) on non-GMO food preferences through a field survey and two controlled experiments. To empirically analyse the psychological mechanisms by which non-GMO label frames affect consumers' preferences for non-GMO food, we set up the mediating variable of food association of safety.
Findings
For ordinary consumers, a framed non-GMO label is more likely to evoke food association of safety and further enhance consumer preference for non-GMO foods. It facilitates consumers' choice of healthier foods. This finding did not otherwise vary across demographic characteristics.
Originality/value
This study is the first to examine the influence of non-GMO label frames on consumers' non-GMO food preferences, which is an innovative research question. The findings of this study are instructive for food manufacturers and policymakers to better design and use non-GMO label frames to attract more consumers to choose non-GMO foods.
Details
Keywords
The purpose of this paper is to understand the consumption and demand of Chinese citizens for public digital culture, and make suggestions for government-supported public digital…
Abstract
Purpose
The purpose of this paper is to understand the consumption and demand of Chinese citizens for public digital culture, and make suggestions for government-supported public digital culture providers.
Design/methodology/approach
Through a questionnaire survey, this study investigates the provision of public digital cultural services (PDCS) from the perspective of consumption and demands.
Findings
The results indicate: the Chinese populace as a whole had low expenses on digital cultural services, and had not effectively utilized them to support their own development; significant disparities exist between demographics, particularly between urban and rural residents; the populace were strongly interested in participation in public digital culture, but the services had low actual utilization rates; and the services had been unable to meet the users’ quality-related demands.
Originality/value
The first study to approach the provision of PDCS from the side of consumption and user demand.
Details
Keywords
Jiahao Zhang and Yu Wei
This study conducts a comparative analysis of the diversification effects of China's national carbon market (CEA) and the EU ETS Phase IV (EUA) within major commodity markets.
Abstract
Purpose
This study conducts a comparative analysis of the diversification effects of China's national carbon market (CEA) and the EU ETS Phase IV (EUA) within major commodity markets.
Design/methodology/approach
The study employs the TVP-VAR extension of the spillover index framework to scrutinize the information spillovers among the energy, agriculture, metal, and carbon markets. Subsequently, the study explores practical applications of these findings, emphasizing how investors can harness insights from information spillovers to refine their investment strategies.
Findings
First, the CEA provide ample opportunities for portfolio diversification between the energy, agriculture, and metal markets, a desirable feature that the EUA does not possess. Second, a portfolio comprising exclusively energy and carbon assets often exhibits the highest Sharpe ratio. Nevertheless, the inclusion of agricultural and metal commodities in a carbon-oriented portfolio may potentially compromise its performance. Finally, our results underscore the pronounced advantage of minimum spillover portfolios; particularly those that designed minimize net pairwise volatility spillover, in the context of China's national carbon market.
Originality/value
This study addresses the previously unexplored intersection of information spillovers and portfolio diversification in major commodity markets, with an emphasis on the role of CEA.