The Ambiguous Identifier Clustering Technique

Investigations of online transaction data often face the problem that entries for identical products cannot be identified as such. There is, for example, typically no unique product identifier in online auctions; retailers make their offers at price comparison sites hardly comparable and online stores often use different identifiers for virtually equal products. Existing studies typically use data sets that are restricted to one or only a few products in order to avoid product heterogeneity if a unique product identifier is not available. We propose the Ambiguous Identifier Clustering Technique (AICT) that identifies online transaction data that refer to virtually the same product. Based on a data set of eBay auctions, we demonstrate that AICT clusters online transactions for identical products with high accuracy. We further show how researchers benefit from AICT and the reduced product heterogeneity when analyzing data with econometric models.     

Preference representation using Gaussian functions on a hyperplane in evolutionary multi-objective optimization

Many-objective optimization has attracted much attention in evolutionary multi-objective optimization (EMO). This is because EMO algorithms developed so far often degrade their search ability for optimization problems with four or more objectives, which are frequently referred to as many-objective problems. One of promising approaches to handle many objectives is to incorporate the preference of a decision maker (DM) into EMO algorithms. With the preference, EMO algorithms can focus the search on regions preferred by the DM, resulting in solutions close to the Pareto front around the preferred regions. Although a number of preference-based EMO algorithms have been proposed, it is not trivial for the DM to reflect his/her actual preference in the search. We previously proposed to represent the preference of the DM using Gaussian functions on a hyperplane. The DM specifies the center and spread vectors of the Gaussian functions so as to represent his/her preference. The preference handling is integrated into the framework of NSGA-II. This paper extends our previous work so that obtained solutions follow the distribution of Gaussian functions specified. The performance of our proposed method is demonstrated mainly for benchmark problems and real-world applications with a few objectives in this paper. We also show the applicability of our method to many-objective problems.     

Deep learning for content-based video retrieval in film and television production

While digitization has changed the workflow of professional media production, the content-based labeling of image sequences and video footage, necessary for all subsequent stages of film and television production, archival or marketing is typically still performed manually and thus quite time-consuming. In this paper, we present deep learning approaches to support professional media production. In particular, novel algorithms for visual concept detection, similarity search, face detection, face recognition and face clustering are combined in a multimedia tool for effective video inspection and retrieval. The analysis algorithms for concept detection and similarity search are combined in a multi-task learning approach to share network weights, saving almost half of the computation time. Furthermore, a new visual concept lexicon tailored to fast video retrieval for media production and novel visualization components are introduced. Experimental results show the quality of the proposed approaches. For example, concept detection achieves a mean average precision of approximately 90% on the top-100 video shots, and face recognition clearly outperforms the baseline on the public Movie Trailers Face Dataset.     

Direct computation of solution spaces

In engineering, it is often desirable to find a subset of the set of feasible designs, a solution space, rather than a single solution. A feasible design is defined as a design which does not violate any constraints and has a performance value below a desired threshold. Performance measure, threshold value and constraints depend on the specific problem. For evaluation of a design with respect to feasibility, a model is required which maps the design parameters from the input space onto the performance measures in the output space. In state-of-the-art methodology, iterative sampling is used to generate an estimate of the frontier between feasible and infeasible regions in the input space. By evaluating each sample point with respect to feasibility, areas which contain a large fraction of feasible designs are identified and subsequently resampled. The largest hypercube containing only feasible designs is sought, because this results in independent intervals for each design parameter. Estimating this hypercube with sufficient precision may require a large number of model evaluations, depending on the dimensionality of the input space. In this paper, a novel approach is proposed for modeling the inequality constraints and an objective function in a way for which a linear formulation can be used, independently of the dimensionality of the problem. Thereby the exact solution for the largest feasible hypercube can be calculated at much lower cost than with stochastic sampling as described above, as the problem is reduced to solving a linear system of equations. The method is applied to structural design with respect to the US-NCAP frontal impact. The obtained solution is compared to numerical solutions of an identical system, which are computed using reduced order models and stochastic methods. By this example, the high potential of the new direct method for solution space computation is shown.     

Photoinduced Tetrazole‐Based Functionalization of Off‐Stoichiometric Clickable Microparticles

We report the preparation of tetrazole‐containing step‐growth microparticles and the subsequent use of photoinduced nitrile imine‐mediated tetrazole‐ene cycloaddition (NITEC) reactions on the particles with spatiotemporal control. Microparticles with an average diameter of 4.1 µm and with inherent tetrazole‐ene dual functionality are prepared by a one‐pot off‐stoichiometric thiol‐Michael addition dispersion polymerization. The NITEC reaction is performed efficiently in the solid phase by UV irradiation, leading to the formation of fluorescent pyrozoline adducts, with an estimated quantum yield of 0.7. Particle concentration‐independent reaction kinetics are observed and full conversion is reached within 10 min of UV exposure at an intensity of 8 mW cm^?2. Temporal control is demonstrated with either UV or rooftop sunlight irradiation of variable duration. By using two‐photon writing with a laser centered around 700 nm wavelength, spatial control is demonstrated with micrometer‐scale resolution via surface patterning of the microparticles. Further, microparticles with exclusive tetrazole functionality are prepared by a one‐pot, two‐step thiol‐Michael addition dispersion polymerization. The NITEC reaction between tetrazole‐functional particles and acrylates in solution is examined at various tetrazole/alkene molar ratios, and a 10:1 excess of alkenes in solution is found necessary for efficient functionalization.     

Determinants of nitrogen surplus at farm level in Swiss agriculture

This paper investigated the determinants of nitrogen surplus, also denoted as nitrogen balance, at farm level in Swiss agriculture. Our analysis was based on a cross-section of 210 farms from the year 2010. The nitrogen surplus of each farm was estimated according to the OECD soil-surface approach and decomposed in two components—nitrogen intensity and nitrogen inefficiency. The average nitrogen surplus of the farms investigated amounted to 89 kg/ha, resulting from an average nitrogen intensity of 255 kg/ha and an average nitrogen inefficiency of 34%. The determinants of nitrogen surplus and its two components were analyzed by means of a three-equation regression model estimated using a robust seemingly unrelated regression approach. Farm size, part-time farming, organic farming, arable cropping and farmer’s age were found to decrease nitrogen surplus, whereas dairy, pig and poultry farming were associated with an increase in nitrogen surplus.     

Struktursynthese und Optimierung nichtidealer Rektifizierprozesse

Optimization processes with MINLP are inherently capable of dramatically reducing the effort and time required for synthesis and analysis of separation processes. This approach represents an extremely powerful tool whose use, however, requires an understanding of process engineering. The principal advantage of the method lies in the simultaneous optimization of both the structure and also the operating conditions of a process. Reliable convergence to the global optimum requires careful limitation, scaling, and prior assignment of all variables. Starting values can be obtained by thermodynamic analysis of the phase equilibrium and by an overall balancing of the individual separation steps. Heuristic reduction of the superstructure generated on the basis of the preferred separation, appears appropriate given the present status of available models and solution algorithms. Under these conditions, the outer approximation algorithm recommended for this model will find the optimum solution after just a few iteration steps.     

Elastic Moduli and Hardness of Cubic Silicon Nitride

The bulk modulus B ₀= 290(5) GPa and its first pressure derivative B '₀= 4.9(6) were obtained for c -Si₃N₄ from volume versus pressure dependence. Measurements were performed under quasi-hydrostatic conditions in a diamond anvil cell to 53 GPa using synchrotron radiation and energy dispersive X-ray powder diffraction. This combined with nanoindentation measurements determined the shear modulus G ₀ of c -Si₃N₄ to be 148(16) GPa. The Vickers microhardness H _V(0.5) for dense, oxygen-free c -Si₃N₄ was estimated to be between 30 and 43 GPa. Both the elastic moduli and microhardness of c -Si₃N₄ exceed those of the hexagonal counterparts, α- and β-phases.     

Photosensitizedcis-trans isomerization of jojoba wax

Jojoba wax solutions were irradiated at wavelengths longer than 366 nm, in the presence of sensitizers, at room temperature.Cis-trans isomerization took place only with sensitizers with triplet energy greater than 68 kcal/mol. Quantum yields were low and a conversion of up to 25% of thetrans isomer was achieved at the photostationary state.