四川工程职业技术学院（Sichuan Engineering Technical College）是四川省人民政府批准建立的公办全日制普通高等学校，由四川省经济和信息化委员会和德阳市人民政府共建。入选国家优质专科高等职业院校、国家示范性高等职业院校、四川省首批高端技术技能型本科人才培养改革试点单位、第三批国家现代学徒制试点单位、四川省优质高等职业院校建设计划；主持四川省装备制造业产教联盟，是全国职业教育先进单位、全国毕业生就业典型经验高校、全国“五一劳动奖状”获得单位、国家技能人才培育突出贡献奖获得院校。学校创建于1959年，原名第一机械工业部德阳重型机器制造学校。60年代，经国务院批准，改办为西南重型机电学院，培养大学本科学生。1962年，恢复中专建制。1982年，学校更名为四川省机械工业学校。2001年，四川省人民政府批准四川省机械工业职工大学、四川省工程技术学校合并建立四川工程职业技术学院。2006年，德阳教育学院整体并入四川工程职业技术学院。截至2020年5月，学校占地1166余亩，有专任教师750人，其中正高52名、副高216名，拥有国家万人计划、国家级教学名师、四川省教学名师等6名、省级教学团队4个。与中航集团共建航空材料检验检测中心，设有3个省级工程实验室、与德国KUKA共建四川省应用创新中心，仪器设备总值1.86亿元，固定资产达5.25亿元，馆藏图书98余万册。设有12个教学系部，开设33个专业或专业方向，其中2个本科专业；在校学生13000余人。
The Super-Resolution Convolutional Neural Network (SRCNN) was employed in this study to enhance the clarity and minimize blur in sports training photographs. High-resolution cameras were utilized to capture sports training images and perform denoising on the images. To improve the nonlinear expression capabilities, the SRCNN model and activation function were introduced after the input image was reduced in size using downsampling techniques. Upsampling was used to transform the feature map back into a high-resolution image. The experimental results showed that the average peak signal-to-noise ratio (PSNR) of SRCNN was 93dB, and its average structural similarity (SSIM) index was 0.94. SRCNN can be used to produce clearer, higher-quality sports training photos.
Based on the ecological-economic-social system, green development efficiency is divided into green ecological efficiency, green economic efficiency and green social efficiency. Their corresponding indicator systems are constructed, and the Super-SBM model, Super-SBM-Undesirable model and kernel density estimation are applied to measure and analyze green development efficiency and its dynamic evolution in western China from 2007 to 2019. Tobit model is constructed and used to empirically analyze the influencing factors of the green development efficiency in western China. The study shows that: (1) green ecological efficiency and green economic efficiency in western China are generally at a low level, and mainly dragged by northwest China, while green social efficiency in western China is generally at a high level, and mainly dragged by southwest China; (2) green ecological efficiency, green economic efficiency and green social efficiency in western China all show a slight trend of first decreasing and then increasing; (3) all three sub-efficiencies of green development in western China have a decreasing trend of absolute difference, right trailing and polarization; (4) the lower green ecological efficiency in western China is due to the negative impacts from the level of government intervention, the level of economic development, and foreign direct investment. The lower green economic efficiency is due to the positive impacts from population density, the level of government intervention, the level of financial development, and foreign direct investment. The higher green social efficiency is due to the positive impacts from population density, the level of financial development, the level of economic development, and the green technological innovation. The study is based on countermeasure recommendations focusing on improving green social efficiency in southwest China, as well as green ecological efficiency and green economic efficiency in northwest China, which are of reference value to promote green development more comprehensively in western China.
A physical modeling approach was adopted to build a Digital Electro-Hydraulic Control (DEH) system simulation model and the fault models using the SIMULINK tool. This research combined the advantages of the gray system and neural network to build a multi-parameter gray error neural network fault prediction model for the first time. Furthermore, an embedded platform for intelligent fault diagnosis and prediction was developed using an Application Specific Integrated Circuit chip. The results show that the simulation model of the DEH system has good performance. A jam fault, internal leakage, and a device fault could be accurately identified through the fault diagnosis model. The multi-parameter gray error neural network prediction model improves the accuracy of fault prediction. The embedded platform developed by the Application Specific Integrated Circuit chip solves the problem of transmission limitation and insufficient computing power. It realizes the intelligent diagnosis and prediction of DEH system faults and guarantees the regular operation of the DEH system.
To overcome the low efficiency of traditional pyrotechnic solid-state laser energy conversion, we design a dust cloud pyrotechnic-pumped Nd :YAG laser based on the thermal radiation model and Lambert–Beer law, which effectively addresses the issue of self-absorption during the combustion of traditional pyrotechnic compositions. Therefore, the laser output energy increases significantly. A laser energy of 2.15 J with a pulse width of 50 ms is achieved using 150 mg KClO 4 /Zr/Al in this work. The energy-to-mass ratio reaches 14.34 J/g. Compared with the traditional pyrotechnic solid-state laser, the Nd :YAG laser pumped by a dust cloud showed a lower light threshold, higher energy efficiency, higher saturation limit, and better safety. In this work, we presents a novel and feasible solution for the development of compact and safe high-energy lasers.
