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.     

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。     

Automatic restraint and visual detection of fatigue crack growth when applying an anti-fatigue smart paste to bolt holes

An anti-fatigue smart paste, which consists of fine alumina particles and silicone grease with low viscosity, was applied to a bolt hole (and its periphery in some cases) in a steel plate specimen, and the effects of the smart paste on automatic restraint and visual detection of fatigue crack growth were experimentally investigated through fatigue tests. Fractographic observations using a scanning electron microscope were also carried out. As a result, approximately 20～410% increase in failure life was produced by the wedge effect of the alumina particles in the smart paste. When the smart paste was applied, remarkable black colour developed in the white paste along the paths of crack growth, exceedingly facilitating the visual detection of the crack growth.     

云南铜厂沟铜钼矿低贫损分段崩落与浅孔留矿耦合采矿法探索

铜厂沟矿区多为破碎、中厚、急倾斜矽卡岩型铜钼矿体，原设计采用上向水平分层充填采矿法，在采矿实验中存在作业安全性差、劳动生产效率低、损失贫化大、采矿成本高等缺陷，严重制约了试生产组织。矿山急迫需要一种安全、高效、成本能够控制的采矿方法满足试生产矿石持续供应。通过充分研究，提出了低贫损分段崩落与浅孔留矿耦合采矿方法的设想，进一步降低了安全风险、简化工艺、控制损失贫化等。通过采矿方法的优化设计，解决了企业生产存在的实际问题，提高了采矿效率，对其它同类矿山具有一定的参考借鉴意义。     

鑫达黄金矿业急倾斜薄矿体中深孔采矿方法的研究与优化

近年来，随着开采技术的发展，急倾斜薄矿脉采用中深孔采矿越来越多。为了降低生产成本，提高经济效益和安全系数。通过在矿房对扇形中深孔和平行中深孔进行现场试验，得到扇形中深孔比平行中深孔工程量少、千吨采切比小的结论。将扇形中深孔采矿方法在急倾斜薄矿脉中进行推广应用，取得了一定经济效益。     

矿山深部开采岩体稳定性监测技术研究

针对矿山深部开采过程中易发生地压动力灾害的问题，基于微震监测技术，结合矿山实际特点建立岩体稳定性监测系统。优化台网设计，通过定点爆破的方法进行波速校正，最终建立了定位误差在10m,灵敏度在-2.2的监测台网。对监测数据进行波形拾取，分析微震事件时空演化特征，圈定潜在危险区域，并对潜在危险区域围岩变形损伤进行分析。最终总结出微震事件大幅度上升且处于较高水平、空间分布高度集聚、能量指数突然下降而累计视体积迅速上升的动力灾害预警前兆。研究结果可为深部开采岩体稳定性监测提供参考。     

熔模铸件砂眼缺陷分析

阐述了熔模铸造铸件出现砂眼缺陷的特征与出现的部位,分析了砂眼缺陷产生的内、外部原因并提出了相应的对策。结果表明,砂眼是由于型壳内、外部的型砂和/或耐火材料进入型腔形成的,尽量减少影响型壳质量的人为因素,提高型壳质量是防止铸件砂眼最有效的措施。     

基于深度脊波神经网络的电力系统短期负荷预测模型

针对电力系统负荷的非线性预测问题,本文构造了一种基于深度脊波神经网络的电力系统短期负荷预测模型。该模型的隐含层采用脊波神经元,神经元的激励函数采用脊波变换函数。对该预测模型采用受限的玻尔兹曼机学习原理进行预训练,最后利用粒子群优化算法对其进行深度优化精调。通过对某地区实际电网负荷系统进行仿真预测,结果表明,与传统的BP神经网络、脊波神经网络和常规深度神经网络模型相对比,深度脊波神经网络预测模型的日平均绝对误差百分比分别降低了1.96%、1.12%和0.3%,日最大绝对误差分别降低了3.91%、2.19%和1.78%,验证了深度脊波神经网络预测模型具有较好的预测准确度和稳定性。