Reliability analysis of non‐repairable systems modeled by dynamic fault trees with priority AND gates

Many real‐life systems are typically involved in sequence‐dependent failure behaviors. Such systems can be modeled by dynamic fault trees (DFTs) with priority AND gates, in which the occurrence of the top events depends on not only combinations of basic events but also their failure sequences. To the author's knowledge, the existing methods for reliability assessment of DFTs with priority AND gates are mainly Markov‐state‐space‐based, inclusion–exclusion‐based, Monte Carlo simulation‐based, or sequential binary decision diagram‐based approaches. Unfortunately, all these methods have their shortcomings. They either suffer the problem of state space explosion or are restricted to exponential components time‐to‐failure distributions or need a long computation time to obtain a solution with a high accuracy. In this article, a novel method based on dynamic binary decision tree (DBDT) is first proposed. To build the DBDT model of a given DFT, we present an adapted format of the traditional Shannon's decomposition theorem. Considering that the chosen variable index has a great effect on the final scale of disjoint calculable cut sequences generated from a built DBDT, which to some extent determines the computational efficiency of the proposed method, some heuristic branching rules are presented. To validate our proposed method, a case study is analyzed. The results indicate that the proposed method is reasonable and efficient. Copyright © 2015 John Wiley & Sons, Ltd.     

预警探测中的多传感器多目标分配

针对多传感器多目标分配中传感器对目标的配对函数难以确定的问题,结合预警探测作战场景,提出传感器对目标的配对能力由传感器间的协同系数、“信息价值”函数和“信息代价”函数3部分共同决定,通过对传感器探测能力及现有目标信息的分析比较,计算出了传感器对目标的配对能力值,并以传感器对目标分配的综合效能最大为目标函数,构建了适用于预警探测的分配模型。仿真结果表明,所提方法合理、有效,分配方案简单、可行。     

改进的K-Means算法在特征关联中的应用

特征关联是无源多传感器辐射源融合识别的一个关键步骤。特征关联是根据来源于同一辐射源的量测数据所具有的相似性,采用一定的算法和分配策略将多传感器获取的对多辐射源的量测值进行分类划分和关联判定,利用辐射源的特征信息来消除关联模糊。特征关联过程中一个重要环节就是分类算法的选取。K-Means算法是基于划分的聚类算法,已经广泛应用于诸多领域。改进了 K-Means算法,用灰关联度代替传统的距离度量定义了样本点间的距离,并对模拟产生的雷达辐射源特征参数样本集 Radar-da-tabase进行了分类。仿真结果表明,改进的K-Means算法提高了关联正确率,但消耗了更多时间。     

Spider Silk Coatings as a Bioshield to Reduce Periprosthetic Fibrous Capsule Formation

Medical grade silicones have been employed for decades in medical applications. The associated long‐term complications, such as capsule formation and contraction have, however, not been fully addressed yet. The aim of this study is to elucidate if capsule formation and/or contraction can be mitigated by veiling the surface of the silicone during the critical phase after implantation. Medical grade silicone implants are homogeneously coated with a micrometer thin layer of recombinant spider silk proteins. Biocompatibility analysis in vitro and in vivo focuses on specific physiological reactions. Applying quantitative methods for the determination of marker‐specific gene expression and protein concentration, it is detected that the silk coating inhibits fibroblast proliferation, collagen I synthesis, and differentiation of monocytes into CD68‐positive histiocytes. It significantly reduces capsule thickness, post‐operative inflammation, synthesis and re‐modeling of extracellular matrix, and expression of contracture‐mediating factors. Therefore, coatings made of recombinant spider silk proteins considerably reduce major post‐operative complications associated with implantation of silicone‐based alloprosthetics, such as capsular fibrosis and contraction, rendering spider silk coatings a bioshield for such implants.     

模糊数学在评判大学生的心理素质中的应用

阐述了模糊数学的模糊综合评判模型,并且给出了相应的计算步骤.通过实例分析表明,利用模糊综合评判评价心理素质是一种客观、有效的方法,该评判方法计算方便、易于操作和推广.     

基于小波变换与小域特征模糊融合的人脸识别

小波变换是一种很好的图像压缩方法,利用小波变换对人脸图像进行三次小波分解,并将低频分量分割成为7个子图像。鉴于人脸上的各小域子图像信息的相互独立性。先利用小域子图像实现软分类,然后使用传统奇异值分解(SVD)法提取出各小域子图像的奇异值(SV),构造出小域奇异值特征向量,给出待识别图像对训练样本图像的隶属度,并采用模糊融合的方法对小域特征进行数据融合,获得识别结果。实验结果表明,该方法实现起来简单、识别速度快,具有很高的识别率。     

Evaluation of Polycyclic Aromatic Hydrocarbons in Smoked Cheeses Made in Poland by HPLC Method

Smoked cheeses are particularly popular among consumers for their flavor and aroma. Of interest, therefore, is the health aspect related to the likelihood of polycyclic aromatic hydrocarbons (PAHs), which are known carcinogens found in smoked products. Thus, the purpose of this study was to evaluate the occurrence of 15 polycyclic aromatic hydrocarbons (PAHs) in smoked and non-smoked cheeses purchased in Poland to monitor their safety. The level of selected PAHs in cheese samples was determined using the HPLC-DAD-FLD method. Most of the cheeses tested met the maximum level of benzo[a]pyrene (2 μg/kg) and the sum of benz[a]anthracene, chrysene, benzo[b]fluoranthene and benzo[a]pyrene (12 μg/kg) established for these products. However, all the cheeses studied in this work had relatively low amounts of the sum of these compounds compared to the information available in the cheese literature, ranging from <LOD to 24.5 μg/kg. This amount does not pose a health risk to consumers. The predominant PAHs found were naphthalene, phenanthrene, fluorene and acenaphthene. Benzo[a]pyrene, the marker compound representing carcinogenic PAHs, was found in 100% and 0% of Polish smoked and non-smoked cheeses, respectively. Although there are currently no regulations for smoked cheeses and maximum concentrations of PAHs in this type of food product, control of PAHs content in cheeses is important due to the mutagenic and carcinogenic potential of these chemicals.     

辉光放电质谱法测定核级石墨粉中痕量杂质

建立了直流辉光放电质谱法(DC-GDMS)测定核级石墨粉中痕量杂质元素的方法。用一定的压力将石墨粉镶嵌在高纯铟片上,形成一个直径约为5 mm的圆形石墨薄层,用铟片辅助石墨粉放电,实现了粉状样品直接检测。优化的实验条件为放电电流0.8 mA,放电电压1.2 kV,放电气体流速0.437 mL/min。用石墨粉标准样品(19J T61029)单点校准了仪器相对灵敏度因子,消除基体效应,实现15个关键杂质元素定量分析。方法检出限为5.0 ng/g,在单侧0.05显著性水平下,利用Student’s t检验,方法测定结果 t值均小于临界值,与标准值无显著性差异。相对标准偏差(RSD)均小于10%。本方法与电感耦合等离子体光谱法测定结果比较,相对误差在2.4%～17.4%之间。     

车联网中基于移动边缘计算的内容感知分类卸载算法研究

随着智能交通的快速发展,车辆终端产生大量需要实时处理的数据消息,而在有限资源上的竞争将会增加消息处理的时延,且对终端设备造成很大的能量消耗。针对时延和能量损耗的均衡关系,该文提出一种基于移动边缘计算(MEC)的内容感知分类卸载算法。首先根据层次分析法对安全消息进行优先级划分,然后建立时延和能量损耗的最优任务卸载模型,通过给时延和能量损耗赋予不同的权重系数构造关系模型,并利用拉格朗日松弛法将非凸问题转化为凸问题,从而结合次梯度投影法和贪婪算法得到问题的可行解。性能评估结果表明,该算法在一定程度上改善了消息处理时延和能量损耗。     

VoiceXML语音平台中预取方案的研究

该文在分析目前主要预取算法优劣的基础上,根据VoiceXML语音平台与基于HTML的WWW之间的区别,认为在VoiceXML语音平台中应该预取其引用的语音资源,提出一种自适应的多用户共享的Markov预测模型,统一预测所有在线用户下一步所需的资源及其访问概率,有助于提高预测的准确率。最后,该文还提出抢占式优先级模型来调度预取任务,将资源的访问概率映射为优先级。仿真研究表明,与单用户预测算法和循环调度模型比较,该预取算法和调度模型都能很好地减少用户请求的访问延迟,提高响应速度。