Results 131 to 140 of about 66,599 (306)
Emerging Memory and Device Technologies for Hardware‐Accelerated Model Training and Inference
Advanced Electronic Materials, EarlyView.This review investigates the suitability of various emerging memory technologies as compute‐in‐memory hardware for artificial intelligence (AI) applications. Distinct requirements for training‐ and inference‐centric computing are discussed, spanning device physics, materials, and system integration.
Yoonho Cho +6 more
wiley +1 more source
Product to process lifecycle management in assembly automation systems [PDF]
Presently, the automotive industry is facing enormous pressure due to global competition and ever changing legislative, economic and customer demands. Product and process development in the automotive manufacturing industry is a challenging task for ...
Haq, Izhar Ul +5 more
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Detecting anomalies in multivariate time series from automotive systems [PDF]
, 2013 This thesis was submitted for the degree of Doctor of Philosophy and awarded by Brunel University.In the automotive industry test drives are conducted during the development of new vehicle models or as a part of quality assurance for series vehicles ...
Theissler, Andreas
core
Advanced Electronic Materials, EarlyView.In dynamic driving scenarios, the proposed approach ensures only temporally aligned sensor inputs to make driving decisions, preventing false activations. By enabling selective hardware‐level learning, it achieves fast, reliable responses under noisy conditions.
Kapil Bhardwaj +4 more
wiley +1 more source
COMET : A Component-Based Real-Time Database for Automotive Systems
, 2004 With the increase of complexity in automotive control systems, the amount of data that needs to be managed is also increasing. Using a real-time database management system (RTDBMS) as a tightly integrated part of the software development process can give
Nyström, Dag, +4 more
core
Comparative Analysis of Machine Learning Models for CO Emission Prediction in Engine Performance
Sakarya University Journal of Computer and Information SciencesThis study presents a comparative analysis of machine learning models for predicting carbon monoxide (CO) emissions in automotive engines. Four models—Linear Regression, Decision Tree, Random Forest, and Support Vector Regression—were evaluated using a ...
Beytullah Eren, İdris Cesur
doaj +1 more source
Advanced Electronic Materials, EarlyView.Compact circuits based on contact‐controlled transistors are well‐suited to unsupervised thermal management, sensitive temperature measurement, or temperature‐stable current references. Demonstrated on flexible microcrystalline silicon and supported by simulation, the approach does not require supply voltage regulation, remains manufacturable across ...
Eva Bestelink +6 more
wiley +1 more source
Advanced Energy Materials, EarlyView.This review provides a bottom‐up evaluation of sodium‐ion battery safety, linking material degradation mechanisms, cell engineering parameters, and module/pack assembly. It emphasizes that understanding intrinsic material stability and establishing coordinated engineering control across hierarchical levels are vital for preventing degradation coupling ...
Won‐Gwang Lim +5 more
wiley +1 more source
Rare‐Earth Yttrium Doping Advances High‐Performance AgSbTe2 Thermoelectrics
Advanced Energy Materials, EarlyView.Y‐doped AgSbTe2 achieves band and microstructure co‐optimization, with coherent Y‐Ag2Te interfaces enhancing phonon scattering and reducing lattice thermal conductivity to 0.26 W m−1 K−1. Combined with valence‐band broadening and increased carrier concentration, this yields ZT ≈ 2 at 623 K, average ZT = 1.5, and 7.3 % conversion efficiency of a single ...
Lan Li +11 more
wiley +1 more source
Automotive Cybersecurity Engineering with Modeling Support [PDF]
Annals of computer science and information systemsAlexander Fischer +2 more
doaj +1 more source