通讯机构：
[Bin Li#] S;[Shilin Yan; Yane Ma] H;Hubei Key Laboratory of Theory and Application of Advanced Materials Mechanics, Wuhan University of Technology, Wuhan, China<&wdkj&>School of Mechanical Engineering, Wuhan Polytechnic University, Wuhan, China<&wdkj&>Hubei Institute of Specialty Vehicle, Wuhan, China
关键词：
Acoustic radiation;cylindrical shell;porous material;annular plates;finite element method
摘要：
Acoustic radiation through a system of double-walled shells, lined with porous foams, and stiffened by annular plates simultaneously is studied. Based on modeling, the porous foams as absorbent fluid property, acoustic characteristics of structure are presented for various sandwich construction by means of vibro-acoustic finite element method with automatic matching layer technology. It is noted that equipping porous foams and annular plates simultaneously enhances the acoustic insulation of structure in the entire frequency domain. The overall sound power level is modified by the density of shell. Moreover, the increase of structural stiffness is shown to effectively reduce the acoustic radiation via rising the thickness of inner shell and the number of annular plates. The foam cores decrease the peak value of structural sound power level through using polyurethane foam cores and increasing filling ratio.
摘要：
Based on the concept of microstructure control and multiphase doping, a novel strong-textured porous (STP) Cu-Al-Mn (CAM) shape memory alloy was fabricated through multi-stage sintering process. Porosity ranging from 31.1 to 11.4 % and the largest near-elastic deformation approached 8.0% were achieved in the STP Cu71Al18Mn11 alloy. Through in-depth characterization, it is confirmed that STP-CAM has less γ2 phase compared to porous ordinary polycrystalline alloy, and exhibits strong 〈0 0 1〉 and 〈1 0 1〉 -oriented texture along the direction of sintering pressure, as well as low angle grain boundaries, which contributes to the large near-elastic deformation observed in this novel porous SMAs.
作者机构：
[Hu, Zhigang; Li, Bin; Li, Dong; Wang, Ying; Yang, Junsheng] Wuhan Polytech Univ, Sch Mech Engn, Wuhan 430000, Peoples R China.;[Gong, Pan; Jin, Junsong; Wang, Xinyun; Zhang, Mao] Huazhong Univ Sci & Technol, Sch Mat Sci & Engn, State Key Lab Mat Proc & Die & Mould Technol, 1037 Luoyu Rd, Wuhan 430074, Peoples R China.
通讯机构：
[Junsong Jin; Junsheng Yang] A;Authors to whom correspondence should be addressed.<&wdkj&>School of Mechanical Engineering, Wuhan Polytechnic University, Wuhan 430000, China<&wdkj&>Authors to whom correspondence should be addressed.<&wdkj&>State Key Laboratory of Materials Processing and Die & Mould Technology, School of Materials Science and Engineering, Huazhong University of Science and Technology, 1037 Luoyu Road, Wuhan 430074, China
关键词：
high entropy alloy;grain size;tribological behavior;wear mechanism
摘要：
The effect and mechanism of grain sizes on the tribological behavior of CoCrFeMnNi high entropy alloy (HEA) were studied by friction experiments and wear morphology analysis. Under normal low load and low sliding speed, the primary wear mechanism of the HEA samples is adhesive wear. With the increase in sliding speed, the wear mechanisms of the samples are adhesive wear and oxidation wear. The oxide layer formed under the action of friction heat of the coarse grain (CG) sample is easy to break due to the softening of the CG. With the increase of normal load and sliding speed, the wear mechanisms of the HEA samples are mainly adhesive wear, oxidation wear, and plastic deformation. The oxide layer of CG sample has many cracks, and the worn surface also has plastic deformation, which leads to the increase of friction coefficient and specific wear rate and the decrease of wear resistance. Therefore, the fine grain size HEA sample has better wear resistance than the CG sample due to its high surface strength.
摘要：
Accurate classification and identification of chicken parts are critical to improve the productivity and processing speed in poultry processing plants. However, the overlapping of chicken parts has an impact on the effectiveness of the identification process. To solve this issue, this study proposed a real-time classification and detection method for chicken parts, utilizing YOLOV4 deep learning. The method can identify segmented chicken parts on the assembly line in real time and accurately, thus improving the efficiency of poultry processing. First, 600 images containing multiple chicken part samples were collected to build a chicken part dataset after using the image broadening technique, and then the dataset was divided according to the 6:2:2 division principle, with 1200 images as the training set, 400 images as the test set, and 400 images as the validation set. Second, we utilized the single-stage target detector YOLO to predict and calculate the chicken part images, obtaining the categories and positions of the chicken leg, chicken wing, and chicken breast in the image. This allowed us to achieve real-time classification and detection of chicken parts. This approach enabled real-time and efficient classification and detection of chicken parts. Finally, the mean average precision (mAP) and the processing time per image were utilized as key metrics to evaluate the effectiveness of the model. In addition, four other target detection algorithms were introduced for comparison with YOLOV4-CSPDarknet53 in this study, which include YOLOV3-Darknet53, YOLOV3-MobileNetv3, SSD-MobileNetv3, and SSD-VGG16. A comprehensive comparison test was conducted to assess the classification and detection performance of these models for chicken parts. Finally, for the chicken part dataset, the mAP of the YOLOV4-CSPDarknet53 model was 98.86% on a single image with an inference speed of 22.2 ms, which was higher than the other four models of YOLOV3-Darknet53, YOLOV3-MobileNetv3, SSD-MobileNetv3, and SSD-VGG16 mAP by 3.27%, 3.78%, 6.91%, and 6.13%, respectively. The average detection time was reduced by 13, 1.9, 6.2, and 20.3 ms, respectively. In summary, the chicken part classification and detection method proposed in this study offers numerous benefits, including the ability to detect multiple chicken parts simultaneously, as well as delivering high levels of accuracy and speed. Furthermore, this approach effectively addresses the issue of accurately identifying individual chicken parts in the presence of occlusion, thereby reducing waste on the assembly line. PRACTICAL APPLICATION: The aim of this study is to offer visual technical assistance in minimizing wastage and resource depletion during the sorting and cutting of chicken parts in poultry production and processing facilities. Furthermore, considering the diverse demands and preferences regarding chicken parts, this research can facilitate product processing that caters specifically to consumer preferences.
摘要：
This study aimed to determine the integrated freshness index (IFI) of eggs using Vis-NIR spectroscopy and optimized support vector regression, which gave the first insight into the freshness quality of eggs from the biochemical essence of quality changes. In this work, Vis-NIR transmission spectra of brown-shell and pink-shell egg samples were analyzed between 500 nm and 900 nm. Standard normal variables (SNV) were used to normalize the spectral data, and the Shuffled Frog Leaping Algorithm (SFLA) and Competitive Adaptive Reweighted Sampling (CARS) were used to choose the optimal wavelengths. The quantitative analysis model of IFI was developed using a support vector regression (SVR) that was optimized using Grid Search (GS), Genetic Algorithm (GA), and Particle Swarm Optimization (PSO). After conducting a comparative analysis, it was determined that the GA-SVR model based on 63 wavelengths screened by the SFLA best predicted IFI with a training set coefficient of determination (R-c (2)) of 0.900, root means square error (RMSEC) of 0.005, a prediction set coefficient of determination (R-p (2)) of 0.816, root mean square error (RMSEP) of 0.012 and relative analysis error (RPD) of 2.077. The results demonstrate that the model can be used to simultaneously perform nondestructive detection of two distinct egg IFI variants, suggesting broader applicability and enhanced model reliability.
作者机构：
[Gong, Pan; Wang, Dongliang; Wang, Xinyun; Zhang, Cheng] Huazhong Univ Sci & Technol, Sch Mat Sci & Engn, State Key Lab Mat Proc & Die & Mould Technol, Wuhan 430074, Peoples R China.;[Gong, Pan] Huazhong Univ Sci & Technol Shenzhen, Res Inst, Shenzhen 518057, Peoples R China.;[Wang, Ying] Wuhan Polytech Univ, Sch Mech Engn, Wuhan 430000, Peoples R China.;[Jamili-Shirvan, Zahra] Esfarayen Univ Technol, Esfarayen, North Khorasan, Iran.;[Yao, Kefu] Tsinghua Univ, Sch Mat Sci & Engn, Beijing 100084, Peoples R China.
通讯机构：
[Gong, Pan; Wang, Xinyun] S;State Key Laboratory of Materials Processing and Die & Mould Technology, School of Materials Science and Engineering, Huazhong University of Science and Technology, Wuhan, China<&wdkj&>Research Institue of Huazhong University of Science and Technology in Shenzhen, Shenzhen, China<&wdkj&>State Key Laboratory of Materials Processing and Die & Mould Technology, School of Materials Science and Engineering, Huazhong University of Science and Technology, Wuhan, China
摘要：
The corrosion behavior of TiZrHfBeCu(Ni) high-entropy bulk metallic glasses (HE-BMGs) has been investigated. The TiZrHfBeCu(Ni) HE-BMGs exhibited high corrosion resistance in 3.5 wt. % NaCl solution because of accumulation of ZrO2 and TiO2 in the passive film. Ni promoted increases of the ZrO2, TiO2, and HfO2 contents and a decrease of the BeO content, which improved the HE-BMG corrosion behavior. Compared with Zr41.2Ti13.8Ni10Cu12.5Be22.5 BMG, the high-entropy effect of HE-BMGs can significantly reduce the atomic mobility, which inhibits outward migration of Cu, reduces the kinetics of the dissolution reaction, and inhibits inward erosion by Cl−, thereby improving the corrosion performance.
作者机构：
[Peng, Yuhua] Wuchang University of Technology, Artificial Intelligence School, HuBei, China;[Wang, Ying] School of Mechanical Engineering, Wuhan Polytechnic University, HuBei, China;[Raffik, R.] Department of Mechatronics Engineering, Kumaraguru College of Technology, Tamilnadu, Coimbatore, India;[Jagota, Vishal] Department of Mechanical Engineering, Madanapalle Institute of Technology & Science, AP, Madanapalle, India;[Bhatia, Komal Kumar] Department of Computer Engineering, J.C. Bose University of Science & Technology, Ertwhile YMCA University of Science & Technology, Haryana, Faridabad, India
期刊：
FRONTIERS IN PSYCHOLOGY,2022年12:724175 ISSN：1664-1078
通讯作者：
Hong, J.;Mao, Q.
作者机构：
[Hong, Jianzhong; Diao, Chunting] Cent China Normal Univ, Sch Psychol, Key Lab Adolescent Cyber Psychol & Beha, Wuhan, Peoples R China.;[Diao, Chunting] Hubei Univ Chinese Med, Sch Humanities, Wuhan, Peoples R China.;[Zhou, Xuan] Wuhan Polytech Univ, Sch Mech Engn, Wuhan, Peoples R China.;[Mao, Qiming] Cent China Normal Univ, Sch Educ, Wuhan, Peoples R China.
通讯机构：
[Hong, J.; Mao, Q.] S;School of Psychology, Key Laboratory of Adolescent Cyber Psychology and Behavior, Central China Normal University, Wuhan, China
关键词：
activity theory;change laboratory;elementary school teacher;teaching research activities;transformative agency
摘要：
In this paper, the random matrix big data analysis model is thoroughly studied and constructed, the ecological model of college students' innovation and entrepreneurship education is analyzed, and the optimization model of college students' Innovation and entrepreneurship education environmental model based on the random matrix big data analysis model is designed. This paper briefly explains the random matrix and its M-P rate theory deduces the idea of feature extraction by the difference of eigenvalue limit spectrum distribution between different nonrandom matrices and random matrices, gives the data matrix representation method of FEMPL and the specific feature composition basis, and describes the steps of FEMPL feature extraction. A performance model for predicting the running time of Hadoop jobs is constructed using a random matrix. In this paper, innovation and entrepreneurship education has been carried out gradually, and the innovation and entrepreneurship education curriculum, platform, and mechanism have been progressively established. However, there is still a gap between the proper level of innovation and entrepreneurship education development. This study takes education ecology as the research perspective, analyzes the ecosystem of typical schools of innovation and entrepreneurship education, summarizes the dimensions and parameters of the invention and entrepreneurship education ecosystem, constructs an ecological model of innovation and entrepreneurship education for college students, and analyzes the problems and causes of the current innovation and entrepreneurship education ecology for college students based on the model, to propose specific strategies to promote the ecological development of innovation and entrepreneurship education for college students.
摘要：
In this research, the influence of plastic deformation on the corrosion behaviors of CrCoFeMnNi high entropy alloy were comprehensively investigated. As the degree of plastic deformation increases, both the acceptor density of the passive film and the thickness of the space charge layer increase, while the resistance of the passive film gradually weakens. The Fe and Cr oxides on the passive films decrease with the increasing plastic deformation degree, resulting in the weaker resistance of the passive film. Numerous dislocations formed after plastic deformation promote the increase of electrochemical dynamics and galvanic corrosion rate. Therefore, severe plastic deformation lowers the corrosion resistance of the alloy. (c) 2021 Elsevier B.V. All rights reserved.
