Results 51 to 60 of about 168,829 (242)

Security in Machine Learning (ML) Workflows

International Journal of Computing and Engineering
Purpose: This paper addresses the comprehensive security challenges inherent in the lifecycle of machine learning (ML) systems, including data collection, processing, model training, evaluation, and deployment. The imperative for robust security mechanisms within ML workflows has become increasingly paramount in the rapidly advancing field of ML, as ...
Dinesh Reddy Chittibala, Srujan Reddy Jabbireddy   +1 more
openaire   +1 more source

Machine Learning at Microsoft with ML.NET [PDF]

Proceedings of the 25th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining, 2019
Machine Learning is transitioning from an art and science into a technology available to every developer. In the near future, every application on every platform will incorporate trained models to encode data-based decisions that would be impossible for developers to author.
Ahmed, Zeeshan, Amizadeh, Saeed, Bilenko, Mikhail, Carr, Rogan, Chin, Wei-Sheng, Dekel, Yael, Dupre, Xavier, Eksarevskiy, Vadim, Erhardt, Eric, Eseanu, Costin, Filipi, Senja, Finley, Tom, Goswami, Abhishek, Hoover, Monte, Inglis, Scott, Interlandi, Matteo, Katzenberger, Shon, Kazmi, Najeeb, Krivosheev, Gleb, Luferenko, Pete, Matantsev, Ivan, Matusevych, Sergiy, Moradi, Shahab, Nazirov, Gani, Ormont, Justin, Oshri, Gal, Pagnoni, Artidoro, Parmar, Jignesh, Roy, Prabhat, Shah, Sarthak, Siddiqui, Mohammad Zeeshan, Weimer, Markus, Zahirazami, Shauheen, Zhu, Yiwen   +33 more
openaire   +2 more sources

A Topology Optimization Framework for the Inverse Design of Nonlinear Mechanical Metamaterials

Advanced Engineering Materials, EarlyView.
This work uses topology optimization to design unit cells for mechanical metamaterials with a prescribed nonlinear stress–strain response. The framework adds contact and postbuckling modeling to synthesize microstructures for three highly nonlinear responses, including pseudoductile behavior, monostable with snap‐through buckling, and bistable ...
Charlie Aveline, Matthew Santer, Robert Hewson   +2 more
wiley   +1 more source

Machine learning (ML) in science and STEM education: a systematic review

Frontiers in Education
Especially in Machine Learning (ML), the quick development of Artificial Intelligence (AI) has heightened interest in its ability to aid science and STEM education. Still, ML has frequently been used as a technical tool for assessment and analysis inside
Malek Jdaitawi, Malek Jdaitawi, Ashraf Fouad Kan'an, Reda Al-Mawadieh, Burhan Hamadneh, Hala Alsabatin, Seif Alkafaween, Omar Alomar   +7 more
doaj   +1 more source

Leveraging machine learning and blockchain in E-commerce and beyond: benefits, models, and application

Discover Artificial Intelligence, 2023
Blockchain technology (BT) allows market participants to keep track of digital transactions without central recordkeeping. The features of blockchain, including decentralization, persistency, and attack resistance, allow data security and privacy ...
Hrag Jebamikyous, Menglu Li, Yoga Suhas, Rasha Kashef   +3 more
doaj   +1 more source

Advancing Electronic Application of Coordination Solids: Enhancing Electron Transport and Device Integration via Surface‐Mounted MOFs (SURMOFs)

Advanced Functional Materials, EarlyView.
The layer‐by‐layer (LbL) assembly of coordination solids, enabled by the surface‐mounted metal‐organic framework (SURMOF) platform, is on the cusp of generating the organic counterpart of the epitaxy of inorganics. The programmable and sequential SURMOF protocol, optimized by machine learning (ML), is suited for accessing high‐quality thin films of ...
Zhengtao Xu, Christof Wöll, Stefan Bräse   +2 more
wiley   +1 more source

3D (Bio) Printing Combined Fiber Fabrication Methods for Tissue Engineering Applications: Possibilities and Limitations

Advanced Functional Materials, EarlyView.
Biofabrication aims at providing innovative technologies and tools for the fabrication of tissue‐like constructs for tissue engineering and regenerative medicine applications. By integrating multiple biofabrication technologies, such as 3D (bio) printing with fiber fabrication methods, it would be more realistic to reconstruct native tissue's ...
Waseem Kitana, Indra Apsite, Leonid Ionov   +2 more
wiley   +1 more source

Patterning the Void: Combining L‐Systems with Archimedean Tessellations as a Perspective for Tissue Engineering Scaffolds

Advanced Functional Materials, EarlyView.
This study introduces a novel multi‐scale scaffold design using L‐fractals arranged in Archimedean tessellations for tissue regeneration. Despite similar porosity, tiles display vastly different tensile responses (1–100 MPa) and deformation modes. In vitro experiments with hMSCs show geometry‐dependent growth and activity. Over 55 000 tile combinations
Maria Kalogeropoulou, Kenny A. van Kampen, Pierpaolo Fucile, Carlos Mota, Lorenzo Moroni   +4 more
wiley   +1 more source

Electroactive Metal–Organic Frameworks for Electrocatalysis

Advanced Functional Materials, EarlyView.
Electrocatalysis is crucial in sustainable energy conversion as it enables efficient chemical transformations. The review discusses how metal–organic frameworks can revolutionize this field by offering tailorable structures and active site tunability, enabling efficient and selective electrocatalytic processes.
Irena Senkovska, Yutong Luo, Ruyan Zhao, Jianjun Zhang, Mingchao Wang, Xinliang Feng, Eike Brunner, Stefan Kaskel   +7 more
wiley   +1 more source

EXPLORING THE ROLE OF MACHINE LEARNING IN ADVANCING THE SUSTAINABLE DEVELOPMENT AGENDA [PDF]

Proceedings on Engineering Sciences
A subset of artificial intelligence (AI), machine learning (ML) has the potential to transform several industries by increasing productivity and encouraging sustainability completely.
Diksha Dalal , Ankit Kumar , Sandeep Kumar   +2 more
doaj   +1 more source