Results 61 to 70 of about 76,023 (254)
In this experimental study, the mechanical properties of additively manufactured Ti‐6Al‐4V lattice structures of different geometries are characterized using compression, four point bending and fatigue testing. While TPMS designs show superior fatigue resistance, SplitP and Honeycomb lattice structures combine high stiffness and strength. The resulting
Klaus Burkart +3 more
wiley +1 more source
Climate change-induced drought threatens global food security, with reports indicating that maize yield losses can exceed 30% in vulnerable regions, such as sub-Saharan Africa and South Asia.
Bushra Quyoom +5 more
doaj +1 more source
This article presents the NFDI‐MatWerk Ontology (MWO), a Basic Formal Ontology‐based framework for interoperable research data management in materials science and engineering (MSE). Covering consortium structures, research data management resources, services, and instruments, MWO enables semantic integration, Findable, Accessible, Interoperable, and ...
Hossein Beygi Nasrabadi +4 more
wiley +1 more source
Currently, advances in healthcare technologies are transforming medical diagnostics, particularly for data-driven disease detection. Acute lymphoblastic leukemia is a common and life-threatening blood cancer, especially prevalent in children.
Khadija Parwez +5 more
doaj +1 more source
Explainable Artificial Intelligence for Diabetes Diagnosis [PDF]
Whether young, old, type 1, type 2, gestational, newly diagnosed, long-time sufferer, caretaker or loved one, millions of people are afflicted and affected by diabetes.
Lamri Mohamed +3 more
doaj +1 more source
A Knowledge‐Based Approach for Understanding and Managing Additive Manufacturing Data
Additive manufacturing processes generate a large amount of data. Effectively managing, understanding, and retrieving information from this data remains a major challenge. Therefore, we propose an ontology‐based approach to integrate heterogeneous data, enable semantic queries, and support decision‐making.
Mina Abd Nikooie Pour +5 more
wiley +1 more source
Causal inference is a powerful modeling tool for explanatory analysis, which might enable current machine learning to become explainable. How to marry causal inference with machine learning to develop explainable artificial intelligence (XAI) algorithms ...
Kun Kuang +9 more
doaj +1 more source
This study presents novel anti‐counterfeiting tags with multilevel security features that utilize additional disguise features. They combine luminescent nanosized Ln‐MOFs with conductive polymers to multifunctional mixed‐matrix membranes and powder composites. The materials exhibit visible/NIR emission and matrix‐based conductivity even as black bodies.
Moritz Maxeiner +9 more
wiley +1 more source
An all‐in‐one analog AI accelerator is presented, enabling on‐chip training, weight retention, and long‐term inference acceleration. It leverages a BEOL‐integrated CMO/HfOx ReRAM array with low‐voltage operation (<1.5 V), multi‐bit capability over 32 states, low programming noise (10 nS), and near‐ideal weight transfer.
Donato Francesco Falcone +11 more
wiley +1 more source
Introducing Geo-Glocal Explainable Artificial Intelligence
Geospatial use cases involve data with a geospatial and a temporal dimension. Machine learning is applied to such use cases for tasks such as prediction and classification.
Cedric Roussel, Klaus Bohm
doaj +1 more source

