Potential applications of three-way multidimensional scaling and related techniques to integrate knowledge from multiple experts

Theknowledge transfer problem in artificial intelligence consists of finding effective ways to elicit information from a human expert and represent it in a form suitable for use by an expert system. One approach to formalizing and guiding this knowledge transfer process for certain types of expert systems is to use psychometric scaling methods to analyze data on how the human expert compares or groups solutions. For example, Butler and Corter [1] obtained judgments of thesubstitutability of solutions from an expert, then analyzed the resulting data via techniques for fitting trees and extended trees [2]. The expert's interpretation of certain aspects of the solutions were directly encoded as production rules, allowing rapid prototyping. In this paper we consider the problem of combining information from multiple experts. We propose the use of three-way or individual differences multidimensional scaling, tree-fitting, and unfolding models to analyze two types of data obtainable from the multiple experts: judgments of the substitutability of pairs of solutions, and judgments of the appropriateness of specific solutions to specific problems. An application is described in which substitutability data were obtained from three experts and analyzed using the SINDSCAL program [3] for three-way multidimensional scaling [4].     

基于码本模型和多特征的早期烟雾检测

提出一种基于码本模型和多特征的早期烟雾检测算法。首先,利用码本模型进行前景提取;然后,结合烟雾的颜色模型和形状特征模型检测前景中的疑似烟雾区域;最后,利用烟雾的动态特性,有效地降低误检率,提高算法的鲁棒性。通过ROC曲线对比,实验结果表明,该算法具有良好的烟雾检测能力。同时,能够满足实时性要求,具有较高的实用价值。     

IgGs-Abzymes from the Sera of Patients with Multiple Sclerosis Recognize and Hydrolyze miRNAs

Autoantibodies-abzymes hydrolyzing DNA, myelin basic protein, and oligosaccharides have been revealed in the sera of patients with multiple sclerosis (MS). In MS, specific microRNAs are found in blood and cerebrospinal fluid, which are characterized by increased expression. Autoantibodies, specifically hydrolyzing four different miRNAs, were first detected in the blood of schizophrenia patients. Here, we present the first evidence that 23 IgG antibodies of MS patients effectively recognize and hydrolyze four neuroregulatory miRNAs (miR-137, miR-9-5p, miR-219-2-3p, and miR-219-5p) and four immunoregulatory miRNAs (miR-21-3p, miR-146a-3p, miR-155-5p, and miR-326). Several known criteria were checked to show that the recognition and hydrolysis of miRNAs is an intrinsic property of MS IgGs. The hydrolysis of all miRNAs is mostly site-specific. The major and moderate sites of the hydrolysis of each miRNA for most of the IgG preparations coincided; however, some of them showed other specific sites of splitting. Several individual IgGs hydrolyzed some miRNAs almost nonspecifically at nearly all internucleoside bonds or demonstrated a combination of site-specific and nonspecific splitting. Maximum average relative activity (RA) was observed in the hydrolysis of miR-155-5p for IgGs of patients of two types of MS—clinically isolated syndrome and relapsing-remitting MS—but was also high for patients with primary progressive and secondary progressive MS. Differences between RAs of IgGs of four groups of MS patients and healthy donors were statistically significant (p < 0.015). There was a tendency of decreasing efficiency of hydrolysis of all eight miRNAs during remission compared with the exacerbation of the disease.     

基于多学习单元卷积神经网络的雷达辐射源信号识别

现有基于人工提取特征的复杂体制雷达辐射源信号识别方法时效性低,识别准确率不佳. 为此,提出了一种基于多学习单元卷积神经网络的识别方法. 首先对辐射源信号的模糊函数进行高斯平滑,以校正噪声带来的毛刺与畸变;然后提取其正交切片作为进一步的特征提取对象;最后构建多学习单元卷积神经网络,学习和提取正交切片深层、泛在的特征,并通过softmax分类器进行分类识别. 仿真实验结果表明,所提方法在信噪比为-2 dB时对6类典型雷达信号的整体平均识别率均保持在99.86%以上,即便是在-6 dB环境中,雷达信号的识别率也可达到88.50%,在极低信噪比条件下具有良好的性能和可行性.     

基于动态模式分解的移动用户信道容量预测算法

在多输入多输出环境下,为了能够连续预测出移动用户的信道容量并以此合理地分配用户资源,提出了一种基于动态模式分解（DMD）的信道容量预测方法及其优化方法：基于经验模态分解的选择性归一化动态模式分解（ESN-DMD）.仿真结果表明,DMD算法只适用于预测低移速低复杂度的用户信号,ESN-DMD算法可以预测不同移速的用户信道容量.     

考虑限制性卖空的多期模糊投资组合优化模型

在实际证券交易中, 卖空操作是一种重要的投资手段, 因此本文研究考虑限制性卖空的多期模糊投资组合优化问题。将风险资产的收益视为梯形模糊数。在允许卖空的情况下, 建立了带单期最低期望收益约束、破产控制约束和投资比例边界约束的多期可信性均值−下半方差−偏度投资组合优化模型。设计了一个改进的多种群粒子群算法对模型进行求解。最后, 采用真实股票数据进行数值算例分析, 说明了所提出的优化模型和算法的有效性。     

高温高湿盐环境下SBS改性沥青胶浆的高温性能

基于自行设计的室内盐蚀干湿循环试验,采用动态剪切流变仪,对SBS改性沥青胶浆进行温度扫描试验和多重应力重复蠕变恢复(MSCR)试验. 以3.2 kPa应力下的不可恢复蠕变柔量J_nr,3.2为胶浆高温流变性能评价指标,分析试验环境和干湿循环耦合作用对胶浆流变性能的影响. 采用灰色关联理论,探究J_nr,3.2与常规流变参数、干湿循环次数及试验环境之间的关联性. 结果表明,随着盐蚀干湿循环次数的增加,胶浆的复数切变模量、车辙因子及J_nr,3.2均呈增大趋势,相位角和蠕变恢复率呈减小趋势. 在同种试验条件下,硫酸盐环境对胶浆高温性能的影响最大. J_nr,3.2与改进型车辙因子、试验环境的灰色关联度最大,关联度系数均大于0.93. 建议采用日常清扫、定期洒水冲洗的方式来减小路面盐分的积累,提高高温高湿环境中沥青路面的抵抗变形的能力.     

一种引入通信的多移动机器人编队方法*

提出以视觉跟踪为基础并引入通信进行多机器人的编队控制方法,根据需要编写了一种新的通信协议,采用闭环l-Φ实现编队算法.这种多机器人编队控制避免了视觉系统的局限,能够更好地在复杂未知环境中协作完成任务,解决了编队控制的无反馈和实时性不高的问题,使得机器人能够准确迅速地进行跟踪和通信编队,一起顺利达到目标点.试验结果证明了该方法的有效性.     

The Contribution of Small Vessel Disease to Neurodegeneration: Focus on Alzheimer’s Disease,Parkinson’s Disease and Multiple Sclerosis

Brain small vessel disease (SVD) refers to a variety of structural and functional changes affecting small arteries and micro vessels, and manifesting as white matter changes, microbleeds and lacunar infarcts. Growing evidence indicates that SVD might play a significant role in the neurobiology of central nervous system (CNS) neurodegenerative disorders, namely Alzheimer’s disease (AD) and Parkinson’s disease (PD), and neuroinflammatory diseases, such as multiple sclerosis (MS). These disorders share different pathophysiological pathways and molecular mechanisms (i.e., protein misfolding, derangement of cellular clearance systems, mitochondrial impairment and immune system activation) having neurodegeneration as biological outcome. In these diseases, the actual contribution of SVD to the clinical picture, and its impact on response to pharmacological treatments, is not known yet. Due to the high frequency of SVD in adult-aged patients, it is important to address this issue. In this review, we report preclinical and clinical data on the impact of SVD in AD, PD and MS, with the main aim of clarifying the predictability of SVD on clinical manifestations and treatment response.