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Concept

Cost curve

Related publications (30)

Geometric Algebra for Optimal Control With Applications in Manipulation Tasks

Sylvain Calinon, Tobias Löw

Many problems in robotics are fundamentally problems of geometry, which have led to an increased research effort in geometric methods for robotics in recent years. The results were algorithms using the various frameworks of screw theory, Lie algebra, and d ...

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC2023

A 3D-Printed Functional Mems Accelerometer

Luis Guillermo Villanueva Torrijo, Damien Maillard

3D printing of MEMS devices could enable the cost-efficient production of custom-designed and complex 3D MEMS for prototyping and for low-volume applications. In this work, we present the first micro 3D-printed functional MEMS accelerometers using two-phot ...

IEEE2023

New Developments in Amorphous Silicon Based Microchannel Plates

Christophe Ballif, Nicolas Würsch, Luca Massimiliano Antognini, Samira Alexandra Frey, Mohammad Beygi

Microchannel plates fabricated from hydrogenated amorphous silicon (AMCPs) are a promising alternative to conventional glass microchannel plates. Their main advantages lie in their flexible fabrication processes, allowing for adaptable channel shapes and t ...

2023

Impact of Redundancy on Resilience in Distributed Optimization and Learning

Nirupam Gupta, Shuo Liu

This paper considers the problem of resilient distributed optimization and stochastic learning in a server-based architecture. The system comprises a server and multiple agents, where each agent has its own local cost function. The agents collaborate with ...

Assoc Computing Machinery2023

A Framework for Autonomic Computing for In Situ Imageomics

Nina Marion Aurélia Van Tiel

In situ imageomics is a new approach to study ecological, biological and evolutionary systems wherein large image and video data sets are captured in the wild and machine learning methods are used to infer biological traits of individual organisms, animal ...

The Institute of Electrical and Electronics Engineers, Inc2023

Deep learning-based solid component measuring enabled interpretable prediction of tumor invasiveness for lung adenocarcinoma

Li Zhang, Jiancheng Yang, Xinchao Wang

Background: The nature of the solid component of subsolid nodules (SSNs) can indicate tumor pathological invasiveness. However, preoperative solid component assessment still lacks a reference standard.Methods: In this retrospective study, an AI algorithm w ...

Elsevier Ireland Ltd2023

Lead immobilization for environmentally sustainable perovskite solar cells

Michael Graetzel, Antonio Abate, Hui Zhang

Lead halide perovskites are promising semiconducting materials for solar energy harvesting. However, the presence of heavy-metal lead ions is problematic when considering potential harmful leakage into the environment from broken cells and also from a publ ...

NATURE PORTFOLIO2023

Modeling and mitigating supply chain disruptions as a bilevel network flow problem

Ralf Seifert, Anna Timonina-Farkas, René Yves Glogg

Years of globalization, outsourcing and cost cutting have increased supply chain vulnerability calling for more effective risk mitigation strategies. In our research, we analyze supply chain disruptions in a production setting. Using a bilevel optimization ...

2022

Optimal Matching of Random Parts

Thomas Alois Weber

This paper examines the minimization of the cost for an expected random production output, given an assembly of finished goods from two random inputs, matched in two categories. We describe the optimal input portfolio, first using the standard normal appro ...

2022

Memory of Motion for Initializing Optimization in Robotics

Teguh Santoso Lembono

Many robotics problems are formulated as optimization problems. However, most optimization solvers in robotics are locally optimal and the performance depends a lot on the initial guess. For challenging problems, the solver will often get stuck at poor loc ...

EPFL2022