高职模具类人才培养新模式的研究与实践

为了解决传统教学无法全面培养人才的问题,采用"课程融合+时空耦合+过程结合"的方式开展人才培养研究。以注射模设计与制造生产过程为导向,构建大项目牵引下的跨越课程、跨越学期的课程融合新模式,利用信息通信技术及互联网平台,将互联网与传统教学进行深度融合,创造新的教学生态,构建多元多维互动的时空耦合教学新关系,以全方位评价为引导,构建课程多元多维的评价新机制。以3个班级为对象开展不同模式下的教学,对试验班级成绩进行分析,研究结果表明:课程融合+时空耦合+过程结合新模式培养的学生更好地完成了综合项目,获得了较好的教学效果。     

Enhanced wide-activated residual network for efficient and accurate image deblocking

To save bandwidth and storage space as well as speed up data transmission, people usually perform lossy compression on images. Although the JPEG standard is a simple and effective compression method, it usually introduces various visually unpleasing artifacts, especially the notorious blocking artifacts. In recent years, deep convolutional neural networks (CNNs) have seen remarkable development in compression artifacts reduction. Despite the excellent performance, most deep CNNs suffer from heavy computation due to very deep and wide architectures. In this paper, we propose an enhanced wide-activated residual network (EWARN) for efficient and accurate image deblocking. Specifically, we propose an enhanced wide-activated residual block (EWARB) as basic construction module. Our EWARB gives rise to larger activation width, better use of interdependencies among channels, and more informative and discriminative non-linearity activation features without more parameters than residual block (RB) and wide-activated residual block (WARB). Furthermore, we introduce an overlapping patches extraction and combination (OPEC) strategy into our network in a full convolution way, leading to large receptive field, enforced compatibility among adjacent blocks, and efficient deblocking. Extensive experiments demonstrate that our EWARN outperforms several state-of-the-art methods quantitatively and qualitatively with relatively small model size and less running time, achieving a good trade-off between performance and complexity.     

Cryptographic Lightweight Encryption Algorithm with Dimensionality Reduction in Edge Computing

Edge Computing is one of the radically evolving systems through generations as it is able to effectively meet the data saving standards of consumers, providers and the workers. Requisition for Edge Computing based items have been increasing tremendously. Apart from the advantages it holds, there remain lots of objections and restrictions, which hinders it from accomplishing the need of consumers all around the world. Some of the limitations are constraints on computing and hardware, functions and accessibility, remote administration and connectivity. There is also a backlog in security due to its inability to create a trust between devices involved in encryption and decryption. This is because security of data greatly depends upon faster encryption and decryption in order to transfer it. In addition, its devices are considerably exposed to side channel attacks, including Power Analysis attacks that are capable of overturning the process. Constrained space and the ability of it is one of the most challenging tasks. To prevail over from this issue we are proposing a Cryptographic Lightweight Encryption Algorithm with Dimensionality Reduction in Edge Computing. The t-Distributed Stochastic Neighbor Embedding is one of the efficient dimensionality reduction technique that greatly decreases the size of the non-linear data. The three dimensional image data obtained from the system, which are connected with it, are dimensionally reduced, and then lightweight encryption algorithm is employed. Hence, the security backlog can be solved effectively using this method.     

极限工况下的管网“互联互通”改进方案

在全国天然气管道“主干互联、区域成网”(以下简称“互联互通”)基础格局逐渐形成的背景下,天然气管网规模日益扩大、管道分支和气源增加,并且分布不集中、输送方向可变,使得输气方案更加灵活,可以更好地解决某些地域的供气紧张问题;但受现有站场和设备的限制,暂不能满足某些多线组合极限工况,使得“互联互通”的初衷难以全部实现。为了使得现有的各输气干线在实现“互联互通”之后可以满足更多的多线组合工况,在分析“互联互通”背景下M管网工况变化的基础上,研发了可以进行水力仿真和压气站方案制订的计算软件,并对3种极限工况下的不同输气量情况进行了可行性试算,进而基于试算结果提出了相应的管网改进建议。研究结果表明:(1)经验证,软件计算误差满足要求;(2)在M管道某处增设压气站或在某些输气站场配置压缩机组;(3) M管网改进调整后,可以完成大部分的多线组合极限工况,真正实现“互联互通”的输气方案。结论认为,该研究成果有助于推进全国天然气管网早日实现“互联互通”。     

基于主成分分析法的熟化菠萝蜜种子品质评价

以菠萝蜜种子为原料,研究水煮、汽蒸、焙烤3种熟化方式对其感官品质、色泽、质构、糊化度、基本营养含量、脂肪酶抑制率、质量损失率和微观结构的影响,并对其品质指标进行主成分分析。结果表明:水煮、汽蒸、焙烤3种熟化方式对不同指标有较大影响,水煮方式糊化度最高且质量损失率最大;焙烤显著加深菠萝蜜种子色泽且脂肪酶抑制率最大;汽蒸熟化后菠萝蜜种子感官评分最高;通过主成分分析可知,焙烤方式获得的品质评价综合得分最高,可作为菠萝蜜种子预熟化的较优选择。     

米糠的功能组分及其在化妆品中的应用

为促进我国米糠资源的多样化利用和开发,介绍了米糠中的功能组分及其在化妆品领域的应用。米糠的功能组分主要有米糠油、米糠蛋白、植物甾醇、米糠多糖、维生素等。米糠在化妆品中的应用主要有两种途径,一是直接使用,二是提取的功效成分的应用。米糠中提取的功效成分如米糠油、谷维素、植物甾醇、二十八烷醇、维生素、植酸等,可赋与化妆品保湿、防晒、抗衰老、抗氧化、抗皱等功效。     

计及RSC控制的DFIG短路电流直流分量解析表达

现有文献针对计及转子变流器(RSC)控制的双馈感应风电机组(DFIG)定子短路电流解析表达,将定子磁链当作一阶直流衰减分量或忽略功率外环控制。基于DFIG电压、磁链和RSC控制方程,得到定子电流关于定子电压和定子功率的传递函数,提出定子电流的精确解析表达式。基于RSC内、外环PI参数关系,推导直流分量衰减时间常数和角频率关于PI参数的表达式。分析了RSC内外环PI参数对定子电流直流衰减分量的影响。仿真结果验证了解析表达式的准确性,为PI参数选取和保护装置测量、整定提供依据。     

Stability of electronic nose (e-nose) as determined by considering date-pits heated at different temperatures

Variability and sensitivity of a portable electronic nose (32 sensors) was assessed by considering different variables for measurement (i.e., reference, standard, first and second purges, sample draw time, waiting time for the volatiles released in the headspace, and mass of sample or headspace volume of the jar containing sample). In this study, dried date-pits were used a model sample. The highest stability was achieved when both reference and standard (i.e., dried date-pits, no heating treatment) were used before test sample measurement. Higher sample draw time more than 10 s significantly decreased the stability, whereas optimum second purge was observed at 50 s. Optimum time to generate volatile was observed as 24 h. A sample of 100 g increased the signal intensity compared to the 50 g sample for the 60°C and 100°C treated samples, while an opposite trend was observed for the 150°C treated sample. Finally, the responses of volatile components in date-pits heated at different temperatures (60°C, 100°C, and 150°C) were measured using the optimum operating conditions. Principal component analysis explored the relationships between the volatile features and classified date-pits heated at different temperatures. The results showed that an electronic nose was able to classify date-pits based on their volatile components generated by different degrees of heating (93.3% accuracy).     

Hollow mesoporous silica nanoparticles as nanocarriers employed in cancer therapy: A review

Hollow mesoporous silica nanoparticles (HMSNs) have become an attractive drug carrier because of their unique characteristics including stable physicochemical properties, large specific surface area and facile functionalization, especially made into intelligent drug delivery systems (DDSs) for cancer therapy. HMSNs are employed to transport traditional anti-tumor drugs, which can solve the problems of drugs with instability, poor solubility and lack of recognition, etc., while significantly improving the anti-tumor effect. And an unexpected good result will be obtained by combining functional molecules and metal species with HMSNs for cancer diagnosis and treatment. Actually, HMSNs-based DDSs have developed relatively mature in recent years. This review briefly describes how to successfully prepare an ordinary HMSNs-based DDS, as well as its degradation, different stimuli-responses, targets and combination therapy. These versatile intelligent nanoparticles show great potential in clinical aspects.