Results 91 to 100 of about 1,373,815 (267)
Heat generation in lithium‐ion batteries affects performance, aging, and safety, requiring accurate thermal modeling. Traditional methods face efficiency and adaptability challenges. This article reviews machine learning‐based and hybrid modeling approaches, integrating data and physics to improve parameter estimation and temperature prediction ...
Qi Lin +4 more
wiley +1 more source
Exceeding Customer Expectations [PDF]
openaire +3 more sources
This study uses the Importance-Performance Analysis (IPA) method to evaluate the service quality at the House of Tjihapit, a restaurant in Bandung that faces challenges due to the COVID-19 pandemic.
Kayla Vania Ayu Tjandra +1 more
doaj +1 more source
This article implements a unified human digital twin framework that integrates cutting edge actuation, sensing, simulation, and bidirectional feedback capability. The approach includes integrating multimodal sensing, AI, and biomechanical simulation into one compact system.
Tajbeed Ahmed Chowdhury +4 more
wiley +1 more source
The Interoperability Challenge in DFT Workflows Across Implementations
Interoperability and cross‐validation remain major challenges in the computational materials science. In this work, we introduce a common input/output standard that enables internal translation across multiple workflow managers—AiiDA, PerQueue, Pipeline Pilot, and SimStack—while producing results in a unified schema.
Simon K. Steensen +13 more
wiley +1 more source
This study aimed to examine the effect of brand awareness, perceived quality, customer expectations and product innovation on buying decisions and on increasing customer loyalty.
Tamamudin *
doaj
THE ROLE OF CUSTOMER EXPERIENCE IN RETAIL BANKING AND THE RISE OF FINTECHS [PDF]
We are part of historic changes in terms of profoundness and velocity in all industries and in customers’ expectations. The aim of this paper is to create an overview of a new age in customer experience generated by a banking environment disturbed by ...
PAUL HANDRO
doaj
Data‐Efficient Cycle‐Level Capacity Prediction Using 1D Deep Convolutional Network
We introduce DeepBat, a deep learning framework featuring a 1D convolutional backbone designed to extract latent degradation patterns from a microstructurally diverse electrode dataset. By learning complex formulation–performance relationships, the model accurately predicts long‐term specific discharge capacity using limited early‐cycle data, providing
Tao Huang +16 more
wiley +1 more source
Exceeding Customer Expectations [PDF]
openaire +3 more sources
A Multidimensional Perspective on Network Conditions in Telesurgery
A multidimensional framework systematically evaluates how combined network impairments influence telesurgical performance. By jointly analyzing latency, jitter, bandwidth, and packet loss, the proposed methodology identifies relevant network condition parameters and their interactions, supporting the design of reliable and safe telesurgical systems ...
Florian Heemeyer +4 more
wiley +1 more source

