A General Framework for Sensor Placement in Source Localization

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IntroductionThe current assessment and standardization of microsurgical skills are subjective, posing challenges in reliable skill evaluation. We aim to address these limitations by developing a quantitative and objective framework for accurately assessing ...

Modern power distribution systems are experiencing a large-scale integration of Converter-Interfaced Distributed Energy Resources (CIDERs). Their presence complicates the analysis and mitigation of harmonics, whose creation and propagation may be amplified ...

This study presents a novel framework for evaluating the luminance measurement capabilities of High Dynamic Range (HDR) sensor cameras in indoor glare conditions. Results indicate that the practical usage range of the CSEM VIP camera is significantly lower ...

Single-photon avalanche diodes (SPADs) are novel image sensors that record the arrival of individual photons at extremely high temporal resolution. In the past, they were only available as single pixels or small-format arrays, for various active imaging ap ...

Car sharing systems (CSSs) are one of the environmentally beneficial solutions in urban transportation. However, the operators still struggle to make these systems profitable. One of the main contributors in operational cost is rebalancing operations. Ther ...

Loop closure detection helps simultaneous localization and mapping systems reduce map and state uncertainty via recognizing previously visited places along the path of a mobile robot. However, visual loop closure detection is susceptible to scenes with dyn ...

Fluoxetine (FL) is one of the selective serotonin reuptake inhibitors, which is used as an anti-depressant, as well as anti-panic drug. In this work, a sensor for label-free recognition of trace amounts of FL is introduced, which is based on an extended ga ...

Unstructured neural network pruning algorithms have achieved impressive compression ratios. However, the resulting-typically irregular-sparse matrices hamper efficient hardware implementations, leading to additional memory usage and complex control logic t ...

We propose a new modelling approach for daily activity scheduling which integrates the different daily scheduling choice dimensions (activity participation, location, schedule, duration and transportation mode) into a single optimisation problem. The funda ...

In this thesis, we reveal that supervised learning and inverse problems share similar mathematical foundations. Consequently, we are able to present a unified variational view of these tasks that we formulate as optimization problems posed over infinite-di ...

Quantification of chemical toxicity in small-scale bioassays is challenging owing to small volumes used and extensive analytical resource needs. Yet, relying on nominal concentrations for effect determination maybe erroneous because loss processes can sign ...

Although different vehicle sharing systems (VSSs) use different vehicle types, the management challenges and optimization problems to be solved are similar or even the same. This observation led us to create a generalized and holistic VSS management framew ...

Time series with missing data are signals encountered in important settings for machine learning. Some of the most successful prior approaches for modeling such time series are based on recurrent neural networks that transform the input and previous state ...

In this paper, we propose a novel framework capable of generating various walking and running gaits for bipedal robots. The main goal is to relax the fixed center of mass (CoM) height assumption of the linear inverted pendulum model (LIPM) and generate a w ...

The ab initio determination of electronic excited state (ES) properties is the cornerstone of theoretical photochemistry. Yet, traditional ES methods become impractical when applied to fairly large molecules, or when used on thousands of systems. Machine l ...

Dynamic environments such as urban areas are still challenging for popular visual-inertial odometry (VIO) algorithms. Existing datasets typically fail to capture the dynamic nature of these environments, therefore making it difficult to quantitatively eval ...

Dedicated bus lanes provide a low cost and easily implementable strategy to improve transit service by minimizing congestion-related delays. Identifying the best spatial distribution of bus-only lanes in order to maximize traffic performance of an urban ne ...

In this paper, we propose and experimentally validate a scheduling and control framework for distributed energy resources (DERs) that achieves to track a day-ahead dispatch plan of a distribution network hosting controllable and stochastic heterogeneous re ...

A central task in high-level synthesis is scheduling: the allocation of operations to clock cycles. The classic approach to scheduling is static, in which each operation is mapped to a clock cycle at compile-time, but recent years have seen the emergence o ...

The majority of currently available webpages are dynamic in nature and are changing frequently. New content gets added to webpages, and existing content gets updated or deleted. Hence, people find it useful to be alert for changes in webpages that contain ...

A General Framework for Sensor Placement in Source Localization

Chattez avec Graph Search

An objective skill assessment framework for microsurgical anastomosis based on ALI scores

Unified Harmonic Power-Flow and Stability Analysis of Power Grids with Converter-Interfaced Distributed Energy Resources

Performance investigation of cameras using HDR sensors for daylight glare evaluations

Burst Vision Using Single-Photon Cameras

A general framework to evaluate different rebalancing operations strategies in one-way car sharing systems

PlaceNet: A multi-scale semantic-aware model for visual loop closure detection

Highly Sensitive Detection of the Antidepressant Fluoxetine With an Extended Gate Field Effect Transistor

Dynamic Probabilistic Pruning: A General Framework for Hardware-Constrained Pruning at Different Granularities

Capturing trade-offs between daily scheduling choices

Optimization Over Banach Spaces: A Unified View on Supervised Learning and Inverse Problems

Predicting exposure concentrations of chemicals with a wide range of volatility and hydrophobicity in different multi-well plate set-ups

Vehicle sharing systems: A review and a holistic management framework

Recursive Input And State Estimation: A General Framework For Learning From Time Series With Missing Data

A unified framework for walking and running of bipedal robots

Learning the Exciton Properties of Azo-dyes

VIODE: A Simulated Dataset to Address the Challenges of Visual-Inertial Odometry in Dynamic Environments

Modeling and optimization of dedicated bus lanes space allocation in large networks with dynamic congestion

Grid-aware Distributed Model Predictive Control of Heterogeneous Resources in a Distribution Network: Theory and Experimental Validation

Combining Dynamic & Static Scheduling in High-level Synthesis

Change Detection and Notification of Web Pages: A Survey