Hierarchical learning using deep optimum-path forest

Bag-of-Visual Words (BoVW) and deep learning techniques have been widely used in several domains, which include computer-assisted medical diagnoses. In this work, we are interested in developing tools for the automatic identification of Parkinson’s disease using machine learning and the concept of BoVW. The proposed approach concerns a hierarchical-based learning technique to design visual dictionaries through the Deep Optimum-Path Forest classifier. The proposed method was evaluated in six datasets derived from data collected from individuals when performing handwriting exams. Experimental results showed the potential of the technique, with robust achievements.     

增强现实中基于位置安全性的LBS位置隐私保护方法

为了解决基于位置的服务(LBS)和增强现实(AR)技术快速发展带来的用户位置隐私泄露的隐患,分析了现有的位置隐私保护方法的优缺点,提出基于位置安全性的位置隐私保护方法。将区域安全度和伪装区域引入该方法中,将提示某区域是否需要保护这一度量标准定义为区域安全度,非安全区域(即需要给予保护的区域)的区域安全度设置为1,安全区域(即不需要保护的区域)设置为0,通过扩大区域安全度和识别等级来计算位置安全度。实验结果表明,该方法与未引入位置安全性的方法相比降低了平均定位误差,提高了平均安全性,从而有效地保护了用户的位置隐私,提高了LBS的服务质量。     

某综合楼火灾后的检测鉴定

文章介绍了某综合楼火灾后的调查情况,经过初步鉴定、详细鉴定两个阶段,阐述了该房屋火灾后的检测鉴定过程,推断出火场温度分布情况,并对受损构件作鉴定评级,提出了处理建议,为加固设计提供参考依据。     

粉煤灰合成沸石对Cr3＋的吸附性能研究

利用粉煤灰合成沸石吸附重金属Cr3＋,探讨吸附剂量、初始pH值以及反应温度对Cr3＋吸附效果的影响,同时进行吸附等温线和吸附动力学的数据模拟。结果表明：沸石投加量、初始pH值以及反应温度均对Cr3＋的去除效果影响显著。随着吸附剂投加量的不断增大,Cr3＋去除效果不断提高,饱和吸附量逐渐减小。初始pH值为4时沸石吸附Cr3＋的去除率为100％。反应温度的上升不利于沸石对Cr3＋吸附,沸石对Cr3＋的吸附效果随着反应温度的升高逐渐降低。沸石吸附Cr3＋的过程符合Freundlich吸附等温式;准二级反应动力学方程能较好描述沸石对Cr3＋的吸附行为。     

Large scale automatic image annotation based on convolutional neural network

Automatic image annotation is one of the most important challenges in computer vision, which is critical to many real-world researches and applications. In this paper, we focus on the issue of large scale image annotation with deep learning. Firstly, considering the existing image data, especially the network images, most of the labels of themselves are inaccurate or imprecise. We propose a Multitask Voting (MV) method, which can improve the accuracy of original annotation to a certain extent, thereby enhancing the training effect of the model. Secondly, the MV method can also achieve the adaptive label, whereas most existing methods pre-specify the number of tags to be selected. Additionally, based on convolutional neural network, a large scale image annotation model MVAIACNN is constructed. Finally, we evaluate the performance with experiments on the MIRFlickr25K and NUS-WIDE datasets, and compare with other methods, demonstrating the effectiveness of the MVAIACNN.     

Multiple structure recovery with T-linkage

This work addresses the problem of robust fitting of geometric structures to noisy data corrupted by outliers. An extension of J-linkage (called T-linkage) is presented and elaborated. T-linkage improves the preference analysis implemented by J-linkage in term of performances and robustness, considering both the representation and the segmentation steps. A strategy to reject outliers and to estimate the inlier threshold is proposed, resulting in a versatile tool, suitable for multi-model fitting “in the wild”. Experiments demonstrate that our methods perform better than J-linkage on simulated data, and compare favorably with state-of-the-art methods on public domain real datasets.     

从双语语料中获取翻译模板

翻译模板自动获取是提高MT译文输出质量和领域适应能力的关键性因素。利用Tree-to-String方法抽取等价对,使用错误驱动的学习方法从中获取翻译模板并进行优化。将优化后的翻译模板用于一个基于转换的机器翻译系统中,同时使用“863”对话语料对其进行评测。实验结果表明：当使用自动获取并经优化的模板进行翻译时,开放测试语料的译文评测分数有一定程度的提高。     

一种双离自动变速器液压系统计算分析

为了分析不同工况下某双离合自动变速器(DCT)液压控制系统的工作性能,采用AMESim软件对稳态工况下的换挡力和润滑冷却子系统的出口流量进行计算,并通过自动变速器台架试验对计算结果进行验证。计算和试验结果吻合度较高,表明VBS阀能够精确控制换挡力,液压控制系统能够快速实现换挡。另外在DCT液压系统的仿真模型中,计算油温对换挡力的影响。通过计算得知油温在30~90 ℃范围内,均对换挡力的影响不大。