高稳高效海上风电安装平台关键制造技术研究

海上风电作为可再生清洁能源之一,受到世界各国的高度重视与大力发展。我国将海上风电提升至解决能源危机、减缓气候变化、调整能源结构的国家战略高度,到2030年我国单位国内生产总值二氧化碳排放将比2005年下降65%以上,非化石能源占一次能源消费比重将达到25%左右。安装平台不足将是我国海上风电场无法如期建成投产的主要障碍。对自升自航式海上风电安装平台系列高端装备及其设计制造的三大技术难题——腿站立作业易“失稳”、大平台大跨距大倾覆力矩自升易“失控”、高空吊装巨型叶片逾百螺栓精准定位易“失准”,以及焊缝缺陷修复和局部裂纹损伤的激光锻造修复再制造进行了介绍,研制的具有不同规格的系列装备在中国、英国、丹麦、德国等国家的著名海上风电场建设应用情况良好。     

微纳层叠聚丙烯腈凝胶流动特性的数值模拟研究

建立了层叠流道的三维模型和有限元网格模型，根据流变测试数据，采用Polymat对物料的黏度模型参数进行拟合，并利用Polyflow软件对聚丙烯腈（PAN）凝胶在层叠流道内的三维等温流动过程进行了数值模拟分析。研究发现，当入口流量增大时，层叠流道出口速度的不均匀性增加；沿流动方向流道内压力逐渐降低，并在出口处降低至同一最低值；流道进出口压力差与入口流量大小具有正相关性；在流道的中心截面上剪切速率分布均匀，波动较小。     

FPGA-based implementation of classification techniques: A survey

Recently, a number of classification techniques have been introduced. However, processing large dataset in a reasonable time has become a major challenge. This made classification task more complex and expensive in calculation. Thus, the need for solutions to overcome these constraints such as field programmable gate arrays (FPGAs). In this paper, we give an overview of the various classification techniques. Then, we present the existing FPGA based implementation of these classification methods. After that, we investigate the confronted challenges and the optimizations strategies. Finally, we highlight the hardware accelerator architectures and tools for hardware design suggested to improve the FPGA implementation of classification methods.     

Matrix Manipulation of Directly-Synthesized PbS Quantum Dot Inks Enabled by Coordination Engineering

The direct-synthesis of conductive PbS quantum dot (QD) ink is facile, scalable, and low-cost, boosting the future commercialization of optoelectronics based on colloidal QDs. However, manipulating the QD matrix structures still is a challenge, which limits the corresponding QD solar cell performance. Here, for the first time a coordination-engineering strategy to finely adjust the matrix thickness around the QDs is presented, in which halogen salts are introduced into the reaction to convert the excessive insulating lead iodide into soluble iodoplumbate species. As a result, the obtained QD film exhibits shrunk insulating shells, leading to higher charge carrier transport and superior surface passivation compared to the control devices. A significantly improved power-conversion efficiency from 10.52% to 12.12% can be achieved after the matrix engineering. Therefore, the work shows high significance in promoting the practical application of directly synthesized PbS QD inks in large-area low-cost optoelectronic devices.     

基于卓越工程师教育的频率特性分析课堂教学研究

频率特性分析在工程应用中具有重要的作用,在电路分析、模拟电子技术、信号与系统、自动控制理论等相关课程中都涉及到相关章节内容,在不同课程中如何根据工程应用和学生学习阶段把握具体的讲解内容和讲解方式非常重要。本文从频率特性的求解方法和具体物理意义角度开展在不同课程中讲解的方法,从时域和频域角度分别讨论其物理意义和具体的分析方法。通过渐进深化的教学过程和教学方法不断提高学生的知识掌握和应用技能,提高学生的工程意识、工程素质和工程创新能力,强化学生对于频率特性课程知识的综合应用能力。     

小型核桃脱壳分选一体机的设计

核桃不仅营养价值极高,而且核桃壳的药用价值也非常高,国内小企业和家庭在核桃硬壳脱壳加工环节,一般采用人工破壳取仁的方式,这种方式劳动强度大,人工成本高且不卫生;针对这个问题设计了一款小型的硬壳脱壳,壳仁分离分选的机器来提高生产效率,减少成本,提高收入。     

WavNet — Visual saliency detection using Discrete Wavelet Convolutional Neural Network

In the recent advancements in image and video analysis, the detection of salient regions in the image becomes the initial step. This plays a crucial role in deciding the performance of such algorithms. In this work, a Multi-Resolution Feature Extraction (MRFE) technique that makes use of Discrete Wavelet Convolutional Neural Network (DWCNN) for generating features is employed. An Enhanced Feature Extraction (EFE) module extracts additional features from the high level features of the DWCNN, which are used to frame both channel as well as spatial attention models for yielding contextual attention maps. A new hybrid loss function is also proposed, which is a combination of Balanced Cross Entropy (BCE) loss and Edge based Structural Similarity (ESSIM) loss that effectively identifies and segments the salient regions with clear boundaries. The method is tested exhaustively with five different benchmark datasets and is proved superior to the existing state-of-the-art methods with a minimum Mean Absolute error (MAE) of 0.03 and F-measure of 0.956.     

A Modified Imperialist Competitive Algorithm for Spoofing Attack Detection in Single-Frequency GPS Receivers

Wireless Personal Communications - A GPS spoofing attack broadcasts counterfeit signals to resemble standard GPS satellite signals to take control of the correlation peaks of GPS signals to force...     

Vulnerable objects detection for autonomous driving: A review

Object detection performed by Autonomous Vehicles (AV)s is a crucial operation that comes ahead of various autonomous driving tasks, such as object tracking, trajectories estimation, and collision avoidance. Dynamic road elements (pedestrians, cyclists, vehicles) impose a greater challenge due to their continuously changing location and behaviour. This paper presents a comprehensive review of the state-of-the-art object detection technologies focusing on both the sensory systems and algorithms used. It begins with a brief introduction on the autonomous driving operations and challenges. Then, different sensory systems employed on existing AVs are elaborated while illustrating their advantages, limitations and applications. Also, sensory systems employed by different research are reviewed. Moreover, due to the significant role Deep Neural Networks (DNN)s are playing in object detection tasks, different DNN-based networks are also highlighted. Afterwards, previous research on dynamic objects detection performed by AVs are reviewed in tabular forms. Finally, a conclusion summarizes the outcomes of the review and suggests future work towards the development of vehicles with higher automation levels.     

Technology enhanced learning of quantitative critical thinking

A Quantitative Critical Thinking (QCT) software tool was developed in this study to facilitate students’ learning of quantitative critical thinking via repeated practice by chemical engineering students reading a core module called fluid-solid systems. The software tool generated detailed calculation steps to typical engineering design problems encountered in this module that contained weaknesses, flaws or even errors. Students utilized the software tool to practice identifying these weaknesses, flaws or errors in the design solutions and then present a better or correct design by applying the concepts and knowledge acquired in the module. Since the QCT software tool was built upon an existing design software tool that was able to generate the correct, detailed design calculation steps to design problems, students were able to check their own design calculations against those presented by the software tool during this second learning step, thereby engaging in and learning quantitative critical thinking via a repeated practice approach. The software tool was successful in enhancing the performance of second-year undergraduate students in solving a question that required quantitative critical thinking in the final examination of the module. The average percentage scores achieved by students for the question who reported higher frequencies of usage of the software were generally higher than those who reported lower frequencies of usage or did not utilize the software tool throughout the semester.