On problems of multicomponent system maintenance modelling

We present an overview of some recent developments in the area of mathematical modeling of maintenance decisions for multi-unit systems. The emphasis is on three main groups of multicomponent maintenance optimization models： the block replacement models, group maintenance models, and opportunistic maintenance models. Moreover, an example of a two-unit system maintenance process is provided in order to compare various maintenance policies.     

A Y-channel design for improving zeta potential and surface conductivity measurements using the current monitoring method

This study presents a new Y-channel design for measuring the zeta potential and surface conductance of a solid-liquid pairing using the current monitoring technique. The new design improves the throughput and reliability of the testing apparatus since the displacement between two solutions can be repeated many times without interfering with the experiments. It also increases the accuracy of the measurement by producing sharper start and end transitions for the current–time plot of the solution displacement process. In this design, efforts have been made to minimize the effects of electrolysis, Joule heating and undesired pressure driven flow on the measurements. An improvement on the current–time slope analysis is also presented. The Y-channel design was validated by comparing zeta potential measurements to published results. The zeta potential of several biological buffers relevant to the microfluidic community in plasma treated PDMS/PDMS and PDMS/Glass microchannels are presented. Preliminary studies of surface conductivity measurements using the Y-channel design were also conducted and are briefly discussed.     

Biofunctionalized upconverting CaF<Subscript>2</Subscript>:Yb,Tm nanoparticles for <Emphasis Type="Italic">Candida albicans</Emphasis> detection and imaging

Versatile optimization of the synthesis method and composition of Yb3+ and Tm3+ co-doped CaF2 nanoparticles as well as a novel biofunctionalization method were developed and evaluated.Through multistep synthesis,the luminescence intensity of the Tm3+ activator was enhanced by more than 10-fold compared to standard one-step synthesis.The proposed methods were used to homogenously distribute the doping ions within the nanoparticle's volume and thus reduce luminescence quenching.Optimization of dopant ions concentration led to the selection of the most efficient visible and near-infrared up-converting nanoparticles,which were CaF2 doped with 10％ Yb3+ 0.05％ Tm3+ and 20％ Yb3+ 0.5％ Tm3+,respectively.To illustrate the suitability of the synthesized nanoparticles as bio-labels,a dedicated biofunctionalization method was used,and the nanoparticles were applied for labeling and imaging of Candida albicans cells.This method shows great promise because of extremely low background and high specificity because of the presence of the attached molecules.     

Controlling patterns of geospatial phenomena

Modeling spatially distributed phenomena in terms of its controlling factors is a recurring problem in geoscience. Most efforts concentrate on predicting the value of response variable in terms of controlling variables either through a physical model or a regression model. However, many geospatial systems comprises complex, nonlinear, and spatially non-uniform relationships, making it difficult to even formulate a viable model. This paper focuses on spatial partitioning of controlling variables that are attributed to a particular range of a response variable. Thus, the presented method surveys spatially distributed relationships between predictors and response. The method is based on association analysis technique of identifying emerging patterns, which are extended in order to be applied more effectively to geospatial data sets. The outcome of the method is a list of spatial footprints, each characterized by a unique “controlling pattern”—a list of specific values of predictors that locally correlate with a specified value of response variable. Mapping the controlling footprints reveals geographic regionalization of relationship between predictors and response. The data mining underpinnings of the method are given and its application to a real world problem is demonstrated using an expository example focusing on determining variety of environmental associations of high vegetation density across the continental United States.     

Michell cantilevers constructed within a half strip. Tabulation of selected benchmark results

The paper delivers the benchmark results for the Michell cantilevers constructed within a half strip, for selected values of the σ _T /σ _C ratio, σ _T , σ _C being the admissible stresses in tension and compression, respectively.     

TSV constraints related to temperature excursion, pressure during molding, materials used and handling loads

The current paper focuses on several mechanical aspects of a waferlevel packaging approach using a direct face-to-face Chip-to-Wafer (C2W) bonding of a MEMS device on an ASIC substrate wafer. Requirements of minimized inherent stress from packaging and good decoupling from forces applied in manufacturing and application are discussed with particular attention to the presence of through-silicon vias (TSV) in the substrate wafer. The paper deals with FEM analysis of temperature excursion, pressure during molding, materials used and handling load influence on mechanical stress within the TSV system and on wafer level, which can be large enough to disintegrate the system.     

Vocal-based emotion recognition using random forests and decision tree

This paper proposes a new vocal-based emotion recognition method using random forests, where pairs of the features on the whole speech signal, namely, pitch, intensity, the first four formants, the first four formants bandwidths, mean autocorrelation, mean noise-to-harmonics ratio and standard deviation, are used in order to recognize the emotional state of a speaker. The proposed technique adopts random forests to represent the speech signals, along with the decision-trees approach, in order to classify them into different categories. The emotions are broadly categorised into the six groups, which are happiness, fear, sadness, neutral, surprise, and disgust. The Surrey Audio-Visual Expressed Emotion database is used. According to the experimental results using leave-one-out cross-validation, by means of combining the most significant prosodic features, the proposed method has an average recognition rate of \(66.28\%\), and at the highest level, the recognition rate of \(78\%\) has been obtained, which belongs to the happiness voice signals. The proposed method has \(13.78\%\) higher average recognition rate and \(28.1\%\) higher best recognition rate compared to the linear discriminant analysis as well as \(6.58\%\) higher average recognition rate than the deep neural networks results, both of which have been implemented on the same database.     

Reducing Protocol Analysis with XOR to the XOR-Free Case in the Horn Theory Based Approach

In the Horn theory based approach for cryptographic protocol analysis, cryptographic protocols and (Dolev?CYao) intruders are modeled by Horn theories and security analysis boils down to solving the derivation problem for Horn theories. This approach and the tools based on this approach, including ProVerif, have been very successful in the automatic analysis of cryptographic protocols. However, dealing with the algebraic properties of operators, such as the exclusive OR (XOR), which are frequently used in cryptographic protocols has been problematic. In particular, ProVerif cannot deal with XOR. In this paper, we show how to reduce the derivation problem for Horn theories with XOR to the XOR-free case. Our reduction works for an expressive class of Horn theories. A large class of intruder capabilities and protocols that employ the XOR operator can be modeled by these theories. Our reduction allows us to carry out protocol analysis using tools, such as ProVerif, that cannot deal with XOR, but are very efficient in the XOR-free case. We implemented our reduction and, in combination with ProVerif, used it for the fully automatic analysis of several protocols that employ the XOR operator. Among others, our analysis revealed a new attack on an IBM security module.