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11.
针对现有基于视频监控的人流量统计方案成本高、算法复杂且不利于个人隐私保护的局限性,利用毫米波雷达体积小、成本低、分辨率高的特点,提出了一种基于双时间点检测的人流量监测方法。该方法先获取人体目标散射点位置和多普勒频移信息来构成点云数据,然后根据多普勒频移正负来判断人体的运动方向,并筛选具有高多普勒频移值的点云数据以降低干扰点对聚类结果的影响;在双时间点对特定区域内人员数量进行统计,并根据双时间点之间所获取的点云数据聚类结果对所统计人员数据进行修正。实验结果表明,该方法能够用匿名的方式以较高的正确率统计人员进出。 相似文献
12.
为了降低机床等待过程中的能耗,提出了一种实时数据驱动的机床等待时间预测与节能控制方法。首先,建立了射频识别驱动的生产进度评估方法,并以生产进度数据作为输入,构建了基于堆栈降噪自编码的机床等待时间预测模型;其次,依据预测的机床等待时间,提出了机床状态切换方法,以降低机床能耗;最后,通过一个电梯零部件制造车间的案例分析,表明该方法的预测误差仅为4.1%,同时将机床等待过程能耗降低了57%,实现了制造车间的节能减排。 相似文献
13.
PC2425破碎机是较为常用的锤式破碎机规格之一,主要用于石灰石的破碎,台时产量800~1 000 t,出料粒度≤70 mm,筛余5%,配套4 500~5 000 t水泥生产线。PC2425破碎机篦条为易损件,由于物料的冲击会导致篦条变形,但其原有的弓形架与篦条型式,更换时很难将篦条从弓形架中抽出,导致更换非常不便。此次改造,用户最初适量降低破碎机的出料粒度,以提高生料磨的产量及降低生料粉磨的电耗,虽然通过调整篦条与锤头的间距及篦条间隙可以达到降低出料粒度的要求。但是为了彻底解决篦条更换困难问题,重新设计了篦架结构。 相似文献
14.
Lauren Folk Kiara Gonzales John Gales Michael Kinsey Elisabetta Carattin Tim Young 《火与材料》2020,44(4):585-606
Practitioners are continuing to develop egress modelling software for the design of the built environment. These models require data about human behaviour and factors for calibration, validation and verification. This study aims to address the specific data and knowledge gap: emergency egress of the elderly. Such data are difficult to collect given privacy and consent concerns, with strong relationships generally being required between residences and researchers. Through the observation of nine fire drills at six Canadian long-term care (LTC) and retirement homes, specific evacuation actions and behaviour were observed for 37 staff members and information about the evacuation of 56 residents was collected. These drills demonstrated that emergency egress in LTC and retirement homes is highly staff dependent with 72% of residents recorded requiring full assistance at all stages of movement in evacuation, and that the type of announced/unannounced drill and level of resident care will affect the type of data collected. The development of travel speed and pre-movement is discussed subject to limitation with qualitative behavioural insights of residents that were observed. This study provides valuable methodological discussion on how to conduct behavioural studies in similar highly restricted research environments. Specific attention is given to understanding the considerations that must be made when using fire drills as data sources, and the impact that these can have on using such data for modelling. This study may inform the initial setup and programming of evacuation models from an actions and behavioural perspectives of staff members and residents. 相似文献
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AbstractData mining techniques have been successfully utilized in different applications of significant fields, including medical research. With the wealth of data available within the health-care systems, there is a lack of practical analysis tools to discover hidden relationships and trends in data. The complexity of medical data that is unfavorable for most models is a considerable challenge in prediction. The ability of a model to perform accurately and efficiently in disease diagnosis is extremely significant. Thus, the model must be selected to fit the data better, such that the learning from previous data is most efficient, and the diagnosis of the disease is highly accurate. This work is motivated by the limited number of regression analysis tools for multivariate counts in the literature. We propose two regression models for count data based on flexible distributions, namely, the multinomial Beta-Liouville and multinomial scaled Dirichlet, and evaluated the proposed models in the problem of disease diagnosis. The performance is evaluated based on the accuracy of the prediction which depends on the nature and complexity of the dataset. Our results show the efficiency of the two proposed regression models where the prediction performance of both models is competitive to other previously used regression models for count data and to the best results in the literature. 相似文献
17.
Traditionally, in supervised machine learning, (a significant) part of the available data (usually 50%-80%) is used for training and the rest—for validation. In many problems, however, the data are highly imbalanced in regard to different classes or does not have good coverage of the feasible data space which, in turn, creates problems in validation and usage phase. In this paper, we propose a technique for synthesizing feasible and likely data to help balance the classes as well as to boost the performance in terms of confusion matrix as well as overall. The idea, in a nutshell, is to synthesize data samples in close vicinity to the actual data samples specifically for the less represented (minority) classes. This has also implications to the so-called fairness of machine learning. In this paper, we propose a specific method for synthesizing data in a way to balance the classes and boost the performance, especially of the minority classes. It is generic and can be applied to different base algorithms, for example, support vector machines, k-nearest neighbour classifiers deep neural, rule-based classifiers, decision trees, and so forth. The results demonstrated that (a) a significantly more balanced (and fair) classification results can be achieved and (b) that the overall performance as well as the performance per class measured by confusion matrix can be boosted. In addition, this approach can be very valuable for the cases when the number of actual available labelled data is small which itself is one of the problems of the contemporary machine learning. 相似文献
18.
By leveraging the secret data coding using the remainder storage based exploiting modification direction (RSBEMD), and the pixel change operation recording based on multi-segment left and right histogram shifting, a novel reversible data hiding (RHD) scheme is proposed in this paper. The secret data are first encoded by some specific pixel change operations to the pixels in groups. After that, multi-segment left and right histogram shifting based on threshold manipulation is implemented for recording the pixel change operations. Furthermore, a multiple embedding policy based on chess board prediction (CBP) and threshold manipulation is put forward, and the threshold can be adjusted to achieve adaptive data hiding. Experimental results and analysis show that it is reversible and can achieve good performance in capacity and imperceptibility compared with the existing methods. 相似文献
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本文以云杉八齿小蠹Ips typographus Linnaeus为例,经标本选取,观察虫体整体形态,绘制整体结构草图,电子显微镜观察局部、得到局部数字图像,分别建立虫体每一部分的高精度细节。把模型每部分拼装在一起组成整体模型,构建出了云杉八齿小蠹三维虚拟昆虫数字化模型。 相似文献