膨胀弯管在管道柔性设计中的定性分析

为防止管道因热胀冷缩、管道支撑或端点附加位移造成的应力问题,对管线中设置的膨胀弯管进行定性分析.通过2个参数的变化对膨胀弯管进行编号得到多种设计方案,用ANSYS建立管道的有限元模型,并分析各方案中膨胀管道的变形、应力和弯矩等;根据分析结果对膨胀弯管设计半径、设置位置和形状进行定性分析.该定性分析结果可为膨胀弯管概念设计和管道柔性设计提供参考.     

No-reference stereoscopic image quality assessment using quaternion wavelet transform and heterogeneous ensemble learning

As the demand for high-quality stereo images has grown in recent years, stereoscopic image quality assessment (SIQA) has become an important research area in modern image processing technology.In this paper, we propose a no-reference stereoscopic image quality assessment (NR-SIQA) model using heterogeneous ensemble learning ‘quality-aware’ features from luminance image, chrominance image, disparity and cyclopean images via quaternion wavelet transform (QWT). Firstly, luminance image and chrominance image are generated by CIELAB color space as monocular perception, and the novel disparity and cyclopean images are utilized to complement with monocular information. Then, a number of ‘quality-aware’ features in the quaternion wavelet domain are discovered, including entropy, texture features, energy features, energy differences features and MSCN coefficients of high frequency sub-band. Finally, a heterogeneous ensemble model via support vector regression (SVR) & extreme learning machine (ELM) & random forest (RF) is proposed to predict quality score, and bootstrap sampling and rotated feature space are used to increase the diversity of data distribution. Comparing with the state-of-the-art NR-SIQA models, experimental results on four public databases prove the accuracy and robustness of the proposed model.     

航空发动机传感器故障鲁棒检测方法

研究发动机传感器故障准确检测问题,现代航空发动机数字电子控制系统对传感器的可靠性要求日益提高。针对航空发动机结构复杂,又工作在高温和高压下,常规采用的传感器故障检测方法的准确性易受到建模误差与外界扰动的影响,造成漏报或误报。为了提高检测精度,提出建立航空发动机数控系统传感器未知输入故障模型,采用特征结构配置的方法,通过配置闭环系统左特征向量实现故障检测残差对不确定性因素的干扰解耦,降低扰动对故障诊断结果的影响。用某型涡扇发动机数控系统传感器故障数字仿真试验表明,所设计的方法对范数有界的不确定量可以实现干扰解耦,抑制干扰对故障检测的影响,改善检测算法的鲁棒性,提高检测结果的准确性,同时满足在线运算的实时性要求。提高了航空发动机的可靠性,保证了安全飞行。     

热压变形对灰口铸铁石墨形态的影响

研究了灰口铸铁(HTl50)在900℃大压下量塑性变形后石墨的分布形态，结果表明：随着压下量的增加，石墨片逐渐趋于平行分布；变形过程中发生了碳的回溶，同时伴随着石墨片的断裂；石墨片体积分数及片间距随压下量的增加而逐渐减少。     

降低玻璃钢产品的收缩及变形的实验研究

本文介绍了如何通过控制原材料的选用、玻璃钢产品的成型工艺、加入填料、模具结构设计来最大限度的减少铁路客车用玻璃钢(FRP)产品的收缩及变形。     

Discourse cues to deception in the case of multiple receivers

Behavioral cues to deception are instrumental in detecting deception. As one of the primary sources of deception behavior, text has been analyzed at the level of sub-sentence or message but not the discourse of interaction. Additionally, empirical studies on cues to deception in the case of multiple receivers remain nonexistent. To fill these voids, we propose a discourse framework and six hypotheses about deception behaviors in a multi-receiver environment. The deception behaviors are operationalized by discourse features based on an analysis of real-world data. The results of statistical analysis validate the efficacy of discourse features in discriminating deceivers from truth-tellers.     

软土地基油罐底板变形分析

分析了造成油罐底板变形的原因、形式及其危害，结合工程实例，提出了减少油罐底板不均匀变形的措施。     

Augment low-field intra-operative MRI with preoperative MRI using a hybrid non-rigid registration method

Background

Preoperatively acquired diffusion tensor image (DTI) and blood oxygen level dependent (BOLD) have been proved to be effective in providing more anatomical and functional information; however, the brain deformation induced by brain shift and tumor resection severely impairs the correspondence between the image space and the patient space in image-guided neurosurgery.

Method

To address the brain deformation, we developed a hybrid non-rigid registration method to register high-field preoperative MRI with low-field intra-operative MRI in order to recover the deformation induced by brain shift and tumor resection. The registered DTI and BOLD are fused with low-field intra-operative MRI for image-guided neurosurgery.

Results

The proposed hybrid registration method was evaluated by comparing the landmarks predicted by the hybrid registration method with the landmarks identified in the low-field intra-operative MRI for 10 patients. The prediction error of the hybrid method is 1.92 ± 0.54 mm, and the compensation accuracy is 74.3 ± 5.0%. Compared to the landmarks far from the resection region, those near the resection region demonstrated a higher compensation accuracy (P-value = .003) although these landmarks had larger initial displacements.

Conclusions

The proposed hybrid registration method is able to bring preoperatively acquired BOLD and DTI into the operating room and compensate for the deformation to augment low-field intra-operative MRI with rich anatomical and functional information.     

HMM-based state classification of a user with a walking support system using visual PCA features

The improvement of safety and dependability in systems that physically interact with humans requires investigation with respect to the possible states of the user’s motion and an attempt to recognize these states. In this study, we propose a method for real-time visual state classification of a user with a walking support system. The visual features are extracted using principal component analysis and classification is performed by hidden Markov models, both for real-time fall detection (one-class classification) and real-time state recognition (multi-class classification). The algorithms are used in experiments with a passive-type walker robot called “RT Walker” equipped with servo brakes and a depth sensor (Microsoft Kinect). The experiments are performed with 10 subjects, including an experienced physiotherapist who can imitate the walking pattern of the elderly and people with disabilities. The results of the state classification can be used to improve fall-prevention control algorithms for walking support systems. The proposed method can also be used for other vision-based classification applications, which require real-time abnormality detection or state recognition.