Machine Learning Supports Robust Operation of Thermosiphon Reboilers

The analysis of process and equipment operational data in chemical engineering regularly requires a high level of expert knowledge. This work presents a Machine Learning-based approach to evaluate and interpret process data to support robust operation of a thermosiphon reboiler. By applying an outlier detection, potentially interesting and unstable operating conditions can be identified quickly. A multidimensional regression allows to forecast the circulating mass flow. The results obtained fit well into the current state of research and manual evaluation of thermosiphon reboilers.     

Inorganic Protection of Polymer Nanocapsules: A Strategy to Improve the Efficiency of Encapsulated Optically Active Molecules

We demonstrate that the efficiency under ambient conditions of optically active molecules encapsulated in polymer nanocapsules can be significantly improved by depositing an inorganic layer onto the polymeric shell. A triplet-triplet annihilation upconversion (TTA-UC) system consisting of a porphyrin derivative and perylene is used as a representative case. Different inorganic materials are deposited on the surface of functionalized polymer nanocapsules synthesized by free-radical polymerization in miniemulsion. First, a silicate clay with formula [Si₈(Mg_5.45Li_0.4)O₂₀(OH)₄]Na_0.7 is deposited on the surface of positively charged polystyrene nanocapsules via layer-by-layer deposition. Second, controlled in situ mineralization of hydroxyapatite and cerium(IV) oxide are carried out on the surface of negatively charged polystyrene nanocapsules. In both cases the inorganic materials on the nanocapsule surface act as a scavenger and avoid the entry of oxygen from the external environment. By avoiding the entry of oxygen, the photo-oxidation process of perylene molecules is avoided within the system, and an increase in the TTA-UC properties occurs.     

Gezielte Variation des Beanspruchungskollektivs zur Verbesserung des Einlaufverhaltens im Trockenlauf

Forschung im Ingenieurwesen - Präzise steuer- und regelbaren Kupplungen wird eine Schlüsselrolle in der Transformation der Automobilwirtschaft zugesprochen. Als Grundlage der...     

Effects of task experience and layout on learning from text and pictures with or without unnecessary picture descriptions

The presentation of extraneous (i.e., irrelevant or unnecessary) information may hamper learning with multimedia. The present study examined whether people can learn to ignore unnecessary information with increasing experience with the task and whether this depends on the layout of that information. In two experiments, participants learned about the process of mitosis from a multimedia slideshow, with each slide presenting a combination of expository text and a picture on one of the stages in the process. Slides either contained no unnecessary text (control condition) or unnecessary text (i.e., merely describing the picture) either integrated in the picture (integrated condition) or presented underneath the picture (separated condition). Knowledge about the studied mitosis phase was tested immediately after each slide using a cloze test. Across Experiments 1 and 2, we did not find a reliable negative effect of the unnecessary text on cloze test performance. As a result, the question of whether task experience would reduce or eliminate that negative effect could not be answered. The eye movement data did confirm, however, that participants attended less to the unnecessary information with increasing task experience, suggesting that students can adapt their study strategy and learn to ignore unnecessary information.     

Stereo‐Consistent Contours in Object Space

Notebook scribbles, art or technical illustrations—line drawings are a simplistic method to visually communicate information. Automated line drawings often originate from virtual 3D models, but one cannot trivially experience their three‐dimensionality. This paper introduces a novel concept to produce stereo‐consistent line drawings of virtual 3D objects. Some contour lines do not only depend on an objects geometry, but also on the position of the observer. To accomplish consistency between multiple view positions, our approach exploits geometrical characteristics of 3D surfaces in object space. Established techniques for stereo‐consistent line drawings operate on rendered pixel images. In contrast, our pipeline operates in object space using vector geometry, which yields many advantages: The position of the final viewpoint(s) is flexible within a certain window even after the contour generation, e.g. a stereoscopic image pair is only one possible application. Such windows can be concatenated to simulate contours observed from an arbitrary camera path. Various types of popular contour generators can be handled equivalently, occlusions are natively supported and stylization based on geometry characteristics is also easily possible.