Data Mining for Vehicle Telemetry

This article presents a data mining methodology for driving-condition monitoring via CAN-bus data that is based on the general data mining process. The approach is applicable to many driving condition problems, and the example of road type classification without the use of location information is investigated. Location information from Global Positioning Satellites and related map data are often not available (for business reasons), or cannot represent the full dynamics of road conditions. In this work, Controller Area Network (CAN)-bus signals are used instead as inputs to models produced by machine learning algorithms. Road type classification is formulated as two related labeling problems: Road Type (A, B, C, and Motorway) and Carriageway Type (Single or Dual). An investigation is presented into preprocessing steps required prior to applying machine learning algorithms, that is, signal selection, feature extraction, and feature selection. The selection methods used include principal components analysis (PCA) and mutual information (MI), which are used to determine the relevance and redundancy of extracted features and are performed in various combinations. Finally, because there is an inherent bias toward certain road and carriageway labelings, the issue of class imbalance in classification is explained and investigated. A system is produced, which is demonstrated to successfully ascertain road type from CAN-bus data, and it is shown that the classification correlates well with input signals such as vehicle speed, steering wheel angle, and suspension height.     

Computer vision for improved estimates of SO2 emission rates and plume dynamics

Imaging cameras operating at ultraviolet (UV) and infrared (IR) wavelengths can measure sulphur dioxide (SO₂) gas path concentrations or slant column densities. These measurements are useful in a variety of applications including the monitoring of emissions from volcanoes and also emissions from stacks at industrial plants and on ships. The usefulness of these data is increased if the emission rates (or fluxes) of the gases can also be estimated. Here we present an optical flow algorithm that allows rapid and accurate estimates of emission rates using both UV and IR camera imagery sampling at around 1 Hz or higher. Examples are provided from measurements made at Turrialba volcano, Costa Rica, and also at a ship in Hong Kong harbour. Other aspects of the properties of the fluid flow are also introduced, notably the divergence and the vorticity of the two-dimensional wind field. We demonstrate how the divergence can be used in a new method to calculate the emission rate and show how rotational effects observed in volcanic plumes and the resulting entrainment of ambient air affects plume rise and can be observed using vorticity. This is an important aspect for understanding the emplacement of gases and particles into the atmosphere that are subsequently transported by atmospheric winds, sometimes causing pollution episodes at long distances from the source.     

Scheduling reclaimers serving a stock pad at a coal terminal

We study a variant of an abstract scheduling problem inspired by the management of reclaimers in the stockyard of a coal export terminal. We prove NP-completeness of the problem and formulate it as a mixed-integer program. We show that for a given reclaiming sequence, the problem can be solved in pseudo-polynomial time. In addition, we provide simple, constant-factor approximation algorithms as well as exact branch-and-bound algorithms. An extensive computational study analyzes the performance of the algorithms.     

Observation of Sublattice Disordering of the Catalytic Sites in a Complex Mo–V–Nb–Te–O Oxidation Catalyst Using High Temperature STEM Imaging

A Mo–V–Nb–Te–O oxidation catalyst has been imaged using scanning transmission electron microscopy at 780 K, which is slightly above its operating temperature. We observe a sublattice disordering of the corner-sharing octahedra forming the catalytic sites containing V⁵⁺ while the edge-sharing pentagonal bipyramidal {Nb(Mo₅)} sublattice remains structurally more rigid and thereby maintains the overall structural integrity of the catalyst. Imaging the termination of the edges of the [001] basal zones at room temperature reveal a preference for presence of a closed network of secondary structural {Nb(Mo)₅} units providing further evidence of the stability of this sublattice structure. We propose that sublattice disordering of catalytic sites enables structural flexibility to accommodate different oxidation states during multistep chemical reactions within a more rigid superstructure and presents a new paradigm for compositionally and structurally complex catalysts.     

Structural Properties of Boron-Doped Germanium-Tin Alloys Grown by Molecular Beam Epitaxy

Boron-doped Ge_1?x Sn _x alloys with atomic fractions of tin up to x = 0.08 were grown on n-Ge(001) substrates using solid-source molecular beam epitaxy, in order to study their structural properties. The total boron concentration in the alloys was ~ 10¹⁸ cm^?3 as measured by secondary-ion mass spectroscopy, which also indicated low amounts of impurities such as carbon and oxygen. More than 90% of the Sn atoms occupied substitutional lattice sites in the alloy as determined by Rutherford backscattering spectrometry. High-resolution x-ray diffraction showed that the boron-doped Ge_1?x Sn _x alloys were single crystals that were completely strained with low defect densities and coherent interfaces for thickness up to 90 nm, and for Sn composition of 8%. The boron-doped Ge_1?x Sn _x /n-Ge formed p–n junctions with conventional rectifying characteristics, indicating that the boron produced electrically active acceptor states.     

Ultrasound‐based,in‐line monitoring of anaerobe yeast fermentation: model,sensor design and process application

In order to implement process analytical technology in beer manufacturing, an ultrasound‐based in‐line sensor was developed which is capable to determine sound velocity and density via the multiple reflection method. Based on a systematic study of the ternary system water–maltose–ethanol, two models were established to estimate the critical process parameters: sugar and ethanol mass fraction. The sound velocity‐based model showed unreasonable high errors although temperature variations and deviations due to dissolved CO₂ were corrected. In contrast, the sound velocity–density–temperature model provided an average root mean square error of 0.53%g/g sugar and 0.26%g/g ethanol content for the main fermentation. Method, sensor and model showed the capability to capture the process signature which may be related to product and process quality.     

用于连铸漏钢坯壳的三维厚度检测技术

利用激光扫描仪精确检测漏钢发生后坯壳的厚度。坯壳厚度的变化与结晶器热监测数据有关。详细的三维厚度扫描证实结晶器里可能发生坯壳厚度局部变化。结合结晶器热监测数据,厚度变化的根本原因被确认。以DSP高速薄板连铸机的两个漏钢实例为例,讨论了漏钢坯壳。第一次漏钢与宽边的大型夹杂物有关。第二次漏钢发生在窄边,与局部坯壳变薄和错误的锥度设定有关。这两种情况中,漏钢都与坯壳厚度的局部减少有关。结晶器相应位置的坯壳温度降低,说明钢水和结晶器铜板之间产生气隙或绝缘层。用CON1D计算,证实了绝缘层的存在。应用CON1D有助于更好地理解导致这类漏钢产生的原因或行为。     

Discrediting in a Message Board Forum: The Effects of Social Support and Attacks on Expertise and Trustworthiness

Given the prevalence of online media today, credibility continues to be a popular subject of empirical research. However, studies examining the effects of discrediting strategies are rare. This issue is significant given the popularity of online media and the ease of such sources to spread misinformation. Therefore, the present study examines the effects of attacking the expertise and trustworthiness of a proponent of a major social issue. Results showed that support as well specific combinations of discrediting attack strategies significantly reduced message board readers' perceptions of the proponent's credibility. In addition, attacks on either the proponent's expertise or trustworthiness resulted in a reduced likelihood of readers taking action with respect to the issue.