High-Confidence Data-Driven Ambiguity Sets for Time-Varying Linear Systems

This paper builds Wasserstein ambiguity sets for the unknown probability distribution of dynamic random variables leveraging noisy partial-state observations. The constructed ambiguity sets contain the true distribution of the data with quantifiable probability and can be exploited to formulate robust stochastic optimization problems with out...

Application of the electrical resistivity method and the estimation of limestone volume: a case study

The present work used the electrical resistivity approach to conduct a three-dimensional modeling and initial volume estimation of the limestone layer in the Mintom region located in southern Cameroon. In order to achieve the objectives of the study, a total of 21 electrical soundings spaced 250 m were first collected in the field using the...

Scenario Parameter Generation Method and Scenario Representativeness Metric for Scenario-Based Assessment of Automated Vehicles

The development of assessment methods for the performance of Automated Vehicles (AVs) is essential to enable the deployment of automated driving technologies, due to the complex operational domain of AVs. One candidate is scenario-based assessment, in which test cases are derived from real-world road traffic scenarios obtained from driving...

A Digital Twin Approach for Improving Estimation Accuracy in Dynamic Thermal Rating of Transmission Lines

The limitation of transmission lines thermal capacity plays a crucial role in the safety and reliability of power systems. Dynamic thermal line rating approaches aim to estimate the transmission line’s temperature and assess its compliance with the limitations above. Existing physics-based standards estimate the temperature based on environment...

A comprehensive toolbox for the gamma distribution: The gammadist package

The gamma distribution is one of the most important parametric models in probability theory and statistics. Although a multitude of studies have theoretically investigated the properties of the gamma distribution in the literature, there is still a serious lack of tailored statistical tools to facilitate its practical applications. To fill...

Gas Turbines Power Regulation Subject to Actuator Constraints, Disturbances and Measurement Noises

An accurate understanding of the output power functionality in gas turbines concerning the fuel, inlet valve status and other parameters can provide a general overview of the turbine's performance. In this study, the problem of practical power regulation in gas turbines is investigated in the simultaneous presence of actuator constraints,...

On the Coupling of Orbit and Attitude Determination of Satellite Formations from Atmospheric Drag: Observability and Estimation Performance

Spacecraft orbit and attitude dynamics have been classically seen as two separated<br/>subjects, since the effect of attitude in orbit dynamics was deemed too small to be<br/>considered, or simply, modeled as noise in the estimation process for most satellites.<br/>In the eighties, a study by [1] showed that for a very large spacecraft,...

Certification of a functionality in a quantum network stage

We consider testing the ability of quantum network nodes to execute multi-round quantum protocols. Specifically, we examine protocols in which the nodes are capable of performing quantum gates, storing qubits and exchanging said qubits over the network a certain number of times. We propose a simple ping-pong test, which provides a certificate...

Performances of the HL (Hyperloop) transport system

This paper deals with an analysis of performances of the HL (Hyperloop) transport system considered as an advanced transport alternative to the existing APT (Air Passenger Transport) and HSR (High Speed Rail) systems. The considered performances are operational, financial, social and environmental. The operational performance include capacity...

Sparse Sensing for Statistical Inference: Theory, Algorithms, and Applications

In today's society, we are flooded with massive volumes of data in the order of a billion gigabytes on a daily basis from pervasive sensors. It is becoming increasingly challenging to locally store and transport the acquired data to a central location for signal/data processing (i.e., for inference). To alleviate these problems, it is evident...

A method to suppress spurious multiples in virtual-source gathers retrieved using seismic interferometry with reflection data

Seismic interferometry applied to surface reflection data (with source and receivers at the surface) allows to retrieve virtual-source gathers at the position of receivers, where no source was shot. As a result of the crosscorrelation of all primary and multiple reflections, the virtual-source gathers contain retrieved physical reflections as...

High-Level Power Estimation and Optimization of DRAMs

Embedded systems have become an integral part of our life in the last few years in multifarious ways, be it in mobile phones, portable audio players, smart watches or even cars. Most embedded systems fall under the category of consumer electronics, such as televisions, mobile devices, and wearable electronics. With several players competing in...

The road ahead in seismic processing

The next generation seismic processing system will comprise a chain of unified algorithms, from preprocessing to reservoir characterization. All these algorithms are formulated in terms of a closed-loop estimation problem, showing a great similarity with each other. A critical module in each algorithm is forward modeling, allowing feedback...

Real time data management for estimating probabilities of incidents and near misses

Advances in real-time data collection, data storage and computational systems have led to development of algorithms for transport administrators and engineers that improve traffic safety and reduce cost of road operations. Despite these advances, problems in effectively integrating real-time data acquisition, processing, modelling and road-use...

Model-based Process Monitoring and Control of Micro-milling using Active Magnetic Bearings

The process of micro-milling is a promising technology for the fabrication of micro-parts with arbitrary 3D features in a wide range of materials. However, as a result of the reduced dimensions, the susceptibility of the process for machine tool errors and vibrations is higher, having adverse effects on accuracy and surface quality of the...

Relative state estimation and observability for formation flying satellites in the presence of sensor noise

This paper presents an investigation into the relative state estimation and observability for two formation flying satellites using two different relative navigation sensor sets. The first set consists out of a transmitter antenna on one satellite and a single receiver antenna on the other satellite to measure the inter-satellite range using a...

Sampling of particulate materials: New theoretical approach

A canonical process for estimation of convex functions: The "invelope" of integrated Brownian motion +t4

A process associated with integrated Brownian motion is introduced that characterizes the limit behavior of nonparametric least squares and maximum likelihood estimators of convex functions and convex densities, respectively. We call this process “the invelope” and show that it is an almost surely uniquely defined function of integrated Brownian...