Entity matching with transformer architectures - a step forward in data integration

Transformer architectures have proven to be very effective and provide state-of-the-art results in many natural language tasks. The attention-based architecture in combination with pre-training on large amounts of text lead to the recent breakthrough and a variety of slightly different implementations. In this paper we analyze how well four of the most recent attention-based transformer architectures (BERT, XLNet, RoBERTa and DistilBERT) perform on the task of entity matching - a crucial part of data integration. Entity matching (EM) is the task of finding data instances that refer to the same real-world entity. It is a challenging task if the data instances consist of long textual data or if the data instances are "dirty" due to misplaced values. To evaluate the capability of transformer architectures and transfer-learning on the task of EM, we empirically compare the four approaches on inherently difficult data sets. We show that transformer architectures outperform classical deep learning methods in EM by an average margin of 27.5%

Model based analysis of forced and natural convection effects in an electrochemical cell

High purity copper, suitable for electrical applications, can only be obtained by electro-winning. The hallmark of this process is its self-induced natural convection through density variations of the electrolyte at both anode and cathode. In order to accelerate the process, first its full dynamic complexity needs to be understood. Thus, an OpenFoam®-based 2D model has been created. This finite-volume multiphysics approach solves the laminar momentum and copper-ion species conservation equations, as well as local copper-ion conversion kinetics. It uses a Boussinesq approximation to simulate the species-momentum coupling, namely natural draft forces induced by variations of the spatial copper concentration within the fluid. The model shows good agreement with benchmark-cases of real-life electrochemical cells found in literature. An additional flow was imposed at the bottom of a small-scale electrochemical cell in order to increase the ionic transport and thereby increase the overall performance of the cell. In a small-scale electrochemical cell in strictly laminar flow, the overall performance could be increased and stratification decreased

CONTRIBUTION TO THE BIOMECHANICAL ANALYSIS OF THE LONG JUMP

The Austrian national outdoor-record for men’s long jump is 8.30 m. This record was set in 1988. Since then the national record has not been broken. Therefore the purpose of this study was to examine the various parameters affecting performance during the last support phase of the long jump. The current work is an attempt to help both the coaches and the athletes to improve performance

CFD modelling of pressure and shear rate in torsionally vibrating structures using ANSYS CFX and COMSOL multiphysics

This paper discusses numerical methodologies to simulate micro vibrations on a nontrivial torsionally oscillating structure. The torsional structure is the tip of a viscosity-density sensor using micro vibrations to measure the fluid properties. A 2D transient simulation of the fluid domain surrounding the tip of the sensor has been conducted in ANSYS CFX and COMSOL Multiphysics software. ANSYS CFX uses a frame of reference to induce the micro vibration whereas a moving wall approach is used in COMSOL Multiphysics for the full Navier-Stokes equation as well as their linearized form. The shear rate and pressure amplitude have been compared between the different numerical approaches. The obtained results show good agreement for both pressure and shear rate amplitudes in all models

Aeroponic test bed for hypergravity research

Taking one pound of food to space costs over $10,000. A plant growth chamber in space would help reduce the cost of transporting food by creating a healthy, long-term source of food that can be used for extended space missions. Currently, there is a lack of knowledge in gravity response mechanisms of plants to facilitate employing such a system. The overarching goal of this project is to add to the current body of knowledge related to growing plants in space by conducting research regarding the effect of hypergravity on cherry belle radish growth. To successfully accomplish this goal, an aeroponic test bed that induces hypergravitational fields ranging from 3gs to 5gs while also providing the nutrients and lighting necessary for growing cherry belle radishes was constructed

ValueNet : a natural language-to-SQL system that learns from database information

In this paper we propose ValueNet light and ValueNet - two end-to-end Natural Language-to-SQL systems that incorporate values using the challenging Spider dataset.The main idea of our approach is to use not only metadata information from the underlying database but also information on the base data as input for our neural network architecture. In particular, we propose a novel architecture sketch to extract values from a user question and come up with possible value candidates which are not explicitly mentioned in the question. We then use a neural model based on an encoder-decoder architecture to synthesize the SQL query. Finally, we evaluate our model on the Spider challenge using the Execution Accuracy metric, a more difficult metric than used by most participants of the challenge. Our experimental evaluation demonstrates that ValueNet light and ValueNet reach state-of-the-art results of 67% and 62% accuracy, respectively, for translating from NL to SQL whilst incorporating values