Education in Process Systems Engineering: Why it matters more than ever and how it can be structured

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Artificial Intelligence has revolutionized numerous fields, driving advancements in healthcare, finance, and autonomous systems. At the core of this revolution lies Deep Learning---algorithms that learn representations from data through computational layer ...

Toward bridging classical optimal control and online learning, regret minimization has recently been proposed as a control design criterion. This competitive paradigm penalizes the loss relative to the optimal control actions chosen by a clairvoyant policy ...

Despite the growing interest in emotions in engineering education, empirical research on incorporating them into engineering ethics education is limited. Therefore, we designed this experimental study to assess how different methods for integrating compass ...

The paper details the process of developing the ITER Plasma Control System (PCS), that is, how to design and deploy it systematically, in the most efficient and effective manner. The integrated nature of the ITER PCS, with its multitude of coupled control ...

Federated learning (FL) is a privacy-preserving collaboratively machine learning paradigm. Traditional FL requires all data owners (a.k.a. FL clients) to train the same local model. This design is not well-suited for scenarios involving data and/or system ...

Industrial information integration engineering (IIIE) is an interdisciplinary field to facilitate the industrial information integration process. In the age of complex and large-scale systems, model-based systems engineering (MBSE) is widely adopted in ind ...

Conversational tutoring systems (CTSs) offer a promising avenue for individualized learning support, especially in domains like persuasive writing. Although these systems have the potential to enhance the learning process, the specific role of learner cont ...

Buildings play a pivotal role in the ongoing worldwide energy transition, accounting for 30% of the global energy consumption. With traditional engineering solutions reaching their limits to tackle such large-scale problems, data-driven methods and Machine ...

Soil contamination by petroleum hydrocarbons (PHCs) causes various acute problems such as crop growth, yield, and grain quality. Many Physico-chemical and biological approaches are employed to remove the PHCs from polluted soil. However, some of these appr ...

Perovskite solar cells are among the most dominant emerging PV technologies which have shown unparallel improvement in power conversion efficiency in just over a decade. Long charge carrier diffusion lengths and lifetimes, high absorption coefficients, ban ...

Exploiting the recent advancements in artificial intelligence, showcased by ChatGPT and DALL-E, in real-world applications necessitates vast, domain-specific, and publicly accessible datasets. Unfortunately, the scarcity of such datasets poses a significan ...

Lack of incentives mainly explains why the implementation of novel methods and technologies in bridge engineering practice is generally postponed by the engineering community despite the urgent need to advance also bridge engineering to meet the objectives ...

The real-time, and accurate inference of model parameters is of great importance in many scientific and engineering disciplines that use computational models (such as a digital twin) for the analysis and prediction of complex physical processes. However, f ...

Meta-Learning aims to speed up the learning process on new tasks by acquiring useful inductive biases from datasets of related learning tasks. While, in practice, the number of related tasks available is often small, most of the existing approaches assume ...

Team projects are an integral part of the student learning experience. However, emotions can significantly affect student performance during team projects. Students use different emotion regulation strategies, such as surface-acting (emotive dissonance) an ...

The concept of creating all-mechanical soft microrobotic systems has great potential to address outstanding challenges in biomedical applications, and introduce more sustainable and multifunctional products. To this end, magnetic fields and light have been ...

A multi-agent system consists of a collection of decision-making or learning agents subjected to streaming observations from some real-world phenomenon. The goal of the system is to solve some global learning or optimization problem in a distributed or dec ...

Cell-free biology is increasingly utilized for engineering biological systems, incorporating novel functionality, and circumventing many of the complications associated with cells. The central dogma describes the information flow in biology consisting of t ...

Semiconductor materials have given rise to today's digital technology and consumer electronics. Widespread adoption is closely linked to the ability to process and integrate them in devices at scale. Where flexibility and large surfaces are required, such ...

Although engineering education is often characterized as a rational activity, research suggests that emotions are vital for learning at all levels of education. In ethics education, there is evidence that including mild emotional information in case studie ...

Education in Process Systems Engineering: Why it matters more than ever and how it can be structured

Chattez avec Graph Search

How data structures affect generalization in Kernel Methods and Deep Learning

On the Guarantees of Minimizing Regret in Receding Horizon

The impact of different methods of increasing the intensity of compassion in engineering ethics cases

Strategy to systematically design and deploy the ITER plasma control system: A system engineering and model-based design approach

FedSSA: Semantic Similarity-based Aggregation for Efficient Model-Heterogeneous Personalized Federated Learning

Design ontology for cognitive thread supporting traceability management in model-based systems engineering

Evaluating the Impact of Learner Control and Interactivity in Conversational Tutoring Systems for Persuasive Writing

Fusing Pre-existing Knowledge and Machine Learning for Enhanced Building Thermal Modeling and Control

Microbial electrochemical bioremediation of petroleum hydrocarbons (PHCs) pollution: Recent advances and outlook

Critical analysis of decision variables for high-throughput experimentation (HTE) with perovskite solar cells

Dated: Guidelines for Creating Synthetic Datasets for Engineering Design Applications

Making Bridges Sustainable

Real-time model calibration with deep reinforcement learning

Scalable PAC-Bayesian Meta-Learning via the PAC-Optimal Hyper-Posterior: From Theory to Practice

Emotional labor experienced in team-projects: A comparison of engineering and hospitality students

3D Printed Acoustically Programmable Soft Microactuators

Multi-agent Learning with Privacy Guarantees

Biochemistry of Aminoacyl tRNA Synthetase and tRNAs and Their Engineering for Cell-Free and Synthetic Cell Applications

Semiconductor-based device architectures in multimaterial fibers

Emotional empathy and engineering students’moral reasoning