Efficient Identification of water conveyance tunnels siltation based on ensemble deep learning

The inspection of water conveyance tunnels plays an important role in water diversion projects. Siltation is an essential factor threatening the safety of water conveyance tunnels. Accurate and efficient identification of such siltation can reduce risks and enhance safety and reliability of these projects. The remotely operated vehicle (ROV) can detect such siltation. However, it needs to improve its intelligent recognition of image data it obtains. This paper introduces the idea of ensemble deep learning. Based on the VGG16 network, a compact convolutional neural network (CNN) is designed as a primary learner, called Silt-net, which is used to identify the siltation images. At the same time, the fully-connected network is applied as the meta-learner, and stacking ensemble learning is combined with the outputs of the primary classifiers to obtain satisfactory classification results. Finally, several evaluation metrics are used to measure the performance of the proposed method. The experimental results on the siltation dataset show that the classification accuracy of the proposed method reaches 97.2%, which is far better than the accuracy of other classifiers. Furthermore, the proposed method can weigh the accuracy and model complexity on a platform with limited computing resources.     

起重机械移动综合检测平台的研制开发

起重机械作为工业发展的基础性产业，其安全使用一直备受关注，有关的检测技术和手段日新月异。文中结合起重机械检验检测工作特点和流程，基于目前日趋成熟的移动实验室技术，提出了起重机械移动综合检测平台的设计方案。对现有检测手段、业务流程、办公软件、网络系统等进行整合，将检测平台结构分为车载基础和业务测试2个功能模块，实现了起重机械一站式的业务服务、检验检测、远程联检等功能，推进检验检测工作提质增效，并具有一定的扩展性，为智慧特检提供了一种思路。     

Experimental and computational analysis of the coolant distribution considering the viscosity of the cutting fluid during machining with helical deep hole drills

An experimental analysis regarding the distribution of the cutting fluid is very difficult due to the inaccessibility of the contact zone within the bore hole. Therefore, suitable simulation models are necessary to evaluate new tool designs and optimize drilling processes. In this paper the coolant distribution during helical deep hole drilling is analyzed with high-speed microscopy. Micro particles are added to the cutting fluid circuit by a developed high-pressure mixing vessel. After the evaluation of suitable particle size, particle concentration and coolant pressure, a computational fluid dynamics (CFD) simulation is validated with the experimental results. The comparison shows a very good model quality with a marginal difference for the flow velocity of 1.57% between simulation and experiment. The simulation considers the kinematic viscosity of the fluid. The results show that the fluid velocity in the chip flutes is low compared to the fluid velocity at the exit of the coolant channels of the tool and drops even further between the guide chamfers. The flow velocity and the flow pressure directly at the cutting edge decrease to such an extent that the fluid cannot generate a sufficient cooling or lubrication. With the CFD simulation a deeper understanding of the behavior and interactions of the cutting fluid is achieved. Based on these results further research activities to improve the coolant supply can be carried out with great potential to evaluate new tool geometries and optimize the machining process.The full text can be downloaded at https://link.springer.com/article/10.1007/s40436-021-00383-w     

Multi-View Multi-Modal Head-Gaze Estimation for Advanced Indoor User Interaction

Gaze estimation is one of the most promising technologies for supporting indoor monitoring and interaction systems. However, previous gaze estimation techniques generally work only in a controlled laboratory environment because they require a number of high-resolution eye images. This makes them unsuitable for welfare and healthcare facilities with the following challenging characteristics: 1) users’ continuous movements, 2) various lighting conditions, and 3) a limited amount of available data. To address these issues, we introduce a multi-view multi-modal head-gaze estimation system that translates the user’s head orientation into the gaze direction. The proposed system captures the user using multiple cameras with depth and infrared modalities to train more robust gaze estimators under the aforementioned conditions. To this end, we implemented a deep learning pipeline that can handle different types and combinations of data. The proposed system was evaluated using the data collected from 10 volunteer participants to analyze how the use of single/multiple cameras and modalities affect the performance of head-gaze estimators. Through various experiments, we found that 1) an infrared-modality provides more useful features than a depth-modality, 2) multi-view multi-modal approaches provide better accuracy than single-view single-modal approaches, and 3) the proposed estimators achieve a high inference efficiency that can be used in real-time applications.     

水文水资源学家陈守煜先生学术研究的知识图谱分析

为探索水文水资源学家陈守煜先生学术研究历程及其演变规律,以其335篇文献作为数据基础,采用共现分析等文献计量可视化分析方法,通过文献发表的时间分布、学科和期刊分布、高被引文献分布和研究主题等方面的知识图谱分析,系统分析了陈先生的学术研究历程。结果显示:陈守煜先生学术研究生命周期历时达62年,在其60岁后出现了2个学术创新高峰期;其学术研究特色荟萃于其河渠非恒定流计算、模糊集理论的水文水资源应用、模糊水文水资源学基本理论、模糊聚类-识别-优选统一理论、可变模糊集理论和可变模糊集理论的水文水资源应用6个研究主题,其中主题1为后续的5个模糊水文水资源学创新主题奠定了数值计算的研究方法论,主题2为模糊集现有理论的应用探索,主题3至主题5为面向工程应用的模糊集理论不断深入创新,主题6为可变模糊集理论的应用探索,形成了"紧密结合应用-持续理论创新-创新理论再应用"这种理论与实践互馈的研究特色。他每一阶段的研究目标比较集中、明确,与其研究主题密切对应,显著提高了研究效率;他的学术研究影响广泛,合计被引8554次,缘于他的源头理论创新。陈先生的研究,理论与应用不断互馈,贵在厚积薄发、深入钻研、持续创新,其研究理念和方法论,对水利科学的学术创新研究具有重要的启示作用和深远影响。     

CSAMT方法在仓上金矿外围及深部找矿中的应用

仓上金矿位于三山岛—仓上断裂西南部，西邻渤海湾，是我国大型露天金矿之一。至2005年闭坑后，在矿山外围及深部找矿一直未取得新进展。为加大勘探深度，探查矿区外围和深部断裂及岩体的空间展布情况，寻找深部金矿资源，采用CSAMT方法在该区开展了测深剖面勘查工作，并与以往的物探资料及331号地质剖面进行了综合对比分析，结果显示F1推断断层与三山岛—仓上断裂相吻合，提出验证钻孔1个。经钻探工程验证见金矿体，取得了较好的应用找矿效果，为下一步开展地质找矿提供了有价值的地球物理信息依据。     

水泥工厂视频监控智能预警平台研究及规划

视频监控系统作为智能化工厂体系架构的子模块，在水泥工厂得到了广泛的部署和应用，为安全、生产流程等管理需求提供了远程可视化的技术支撑手段。为进一步提升工厂智能化水平，提高管理效率，本文提出了基于视频图像分析技术的智能监控预警平台的路线规划，实施步骤和方法，并对该平台的初步应用效果进行了量化评估，为后续平台建设提供科学决策依据。     

数字花卉植物的全息可视化与交互实现

花卉植物形态、结构与生长过程的数字化和可视化是现代林业科研的重要研究内 容，数字花卉植物在科普、教育、展示等方面都有着广泛的应用与需求。全息影像技术是一种 新兴的前沿技术，其原理源自佩珀尔幻象，通常用于生成立体感强的影像，实现数字幻象与真 实世界的融合，拥有良好的观赏性，用户接受度较高。将全息影像技术与数字花卉植物相关研 究进行结合，可以加强数字花卉植物的可视化效果，从而实现更好的科普、教育、展示效果。 因此在现有的研究基础之上，考虑实现数字花卉植物的全息可视化，并在可视基础上增加了用 户交互实现，设计出一套兼具展示性和交互性的流程，力求总结出一种具有完整可行性的方案， 从而对数字花卉植物的新型表现形式进行深入研究，以期对数字植物研究与应用的进一步发展 提供参考。