Vienna University of Technology

About: Vienna University of Technology is a education organization based out in Vienna, Austria. It is known for research contribution in the topics: Laser & Cloud computing. The organization has 16723 authors who have published 49341 publications receiving 1302168 citations.

Parity-time symmetry and exceptional points in photonics.

Abstract: Exploiting the interplay between gain, loss and the coupling strength between different optical components creates a variety of new opportunities in photonics to generate, control and transmit light. Inspired by the discovery of real eigenfrequencies for non-Hermitian Hamiltonians obeying parity–time (PT) symmetry, many counterintuitive aspects are being explored, particularly close to the associated degeneracies also known as ‘exceptional points’. This Review explains the underlying physical principles and discusses the progress in the experimental investigation of PT-symmetric photonic systems. We highlight the role of PT symmetry and non-Hermitian dynamics for synthesizing and controlling the flow of light in optical structures and provide a roadmap for future studies and potential applications. This Review discusses recent developments in the area of non-Hermitian physics, and more specifically the special case of non-Hermitian optical systems with parity–time symmetry.

Introduction to Multivariate Statistical Analysis in Chemometrics

Abstract: Introduction Chemoinformatics-Chemometrics-Statistics This Book Historical Remarks about Chemometrics Bibliography Starting Examples Univariate Statistics-A Reminder Multivariate Data Definitions Basic Preprocessing Covariance and Correlation Distances and Similarities Multivariate Outlier Identification Linear Latent Variables Summary Principal Component Analysis (PCA) Concepts Number of PCA Components Centering and Scaling Outliers and Data Distribution Robust PCA Algorithms for PCA Evaluation and Diagnostics Complementary Methods for Exploratory Data Analysis Examples Summary Calibration Concepts Performance of Regression Models Ordinary Least Squares Regression Robust Regression Variable Selection Principal Component Regression Partial Least Squares Regression Related Methods Examples Summary Classification Concepts Linear Classification Methods Kernel and Prototype Methods Classification Trees Artificial Neural Networks Support Vector Machine Evaluation Examples Summary Cluster Analysis Concepts Distance and Similarity Measures Partitioning Methods Hierarchical Clustering Methods Fuzzy Clustering Model-Based Clustering Cluster Validity and Clustering Tendency Measures Examples Summary Preprocessing Concepts Smoothing and Differentiation Multiplicative Signal Correction Mass Spectral Features Appendix 1: Symbols and Abbreviations Appendix 2: Matrix Algebra Appendix 3: Introduction to R Index References appear at the end of each chapter

The Promise of Edge Computing

Abstract: The success of the Internet of Things and rich cloud services have helped create the need for edge computing, in which data processing occurs in part at the network edge, rather than completely in the cloud. Edge computing could address concerns such as latency, mobile devices' limited battery life, bandwidth costs, security, and privacy.