Results 81 to 90 of about 192,753 (304)

Komadu: A Capture and Visualization System for Scientific Data Provenance

Journal of Open Research Software, 2015
Data provenance captured from scientific applications is a critical precursor to data sharing and reuse. For researchers wanting to repurpose data, it is a source of information about the lineage and attribution of the data and this is needed in order to
Isuru Suriarachchi, Quan Zhou, Beth Plale   +2 more
doaj   +1 more source

Sustainable Materials Design With Multi‐Modal Artificial Intelligence

Advanced Science, EarlyView.
Critical mineral scarcity, high embodied carbon, and persistent pollution from materials processing intensify the need for sustainable materials design. This review frames the problem as multi‐objective optimization under heterogeneous, high‐dimensional evidence and highlights multi‐modal AI as an enabling pathway.
Tianyi Xu, Tianshuo Wei, Yan Ge, Bo Peng, Yue Li, Maolin Wang, Peng Wen, Chao Yang, Ye Wei   +8 more
wiley   +1 more source

Tamper-Evident Data and Model Provenance for IoT-Based Machine Learning Using Blockchain and Off-Chain Storage

Information
Machine learning models increasingly rely on continuously generated sensor data for automated decision-making in Internet of Things (IoT) environments.
Sangheethaa Sukumaran, Arun Korath, Gowri Arun Menon   +2 more
doaj   +1 more source

CF-PROV: A Content-Rich and Fine-Grained Scientific Workflow Provenance Model

IEEE Access, 2019
Due to the complexity of scientific experiments, existing methods for capturing the provenance information from the scientific workflows (SWFs) face high programming overhead and code errors.
Qi Sun, Yue Liu, Wenjie Tian, Yike Guo
doaj   +1 more source

Data Isotopes for Data Provenance in DNNs

Proceedings on Privacy Enhancing Technologies
Today, creators of data-hungry deep neural networks (DNNs) scour the Internet for training fodder, leaving users with little control over or knowledge of when their data, and in particular their images, are used to train models. To empower users to counteract unwanted use of their images, we design, implement and evaluate a practical system that ...
Emily Wenger, Xiuyu Li, Ben Y. Zhao, Vitaly Shmatikov   +3 more
openaire   +3 more sources

DEEP: a provenance-aware executable document system [PDF]

, 2012
The concept of executable documents is attracting growing interest from both academics and publishers since it is a promising technology for the dissemination of scientific results. Provenance is a kind of metadata that provides a rich description of the
Charlton, Chris, William J. Browne, Charlton, Christopher M J, Luc Moreau, Huanjia Yang (7122116), Moreau, L, William J. Browne (7167704), Moreau, Luc, Huanjia Yang, Chris Charlton (7167701), Browne, William, Browne, William J, michaelides, dt, Michaelides, Danius T., Chris Charlton, Yang, Huanjia, Danius T. Michaelides, Luc Moreau (3689335), Yang, H, Danius T. Michaelides (3612746)   +19 more
core   +1 more source

Environmental Insights and Sustainability Opportunities for Scaled‐Up MXene Production Without Etching

Advanced Science, EarlyView.
Through a systematic and comprehensive analysis of the environmental impacts for the emerging MXene synthesis pathways, this study presents process transformation and optimization opportunities for low‐carbon MXene production from laboratory to industrial scales.
Yushuai Huang, Peng Peng, Maoqiao Xiang, Fen Yue, Jiangyan Wang, Wenwei Liu, Qingshan Zhu   +6 more
wiley   +1 more source

Scalable Engineering of Bio‐Manufactured Extracellular Vesicles for Selective Delivery in Ovarian Cancer Patient‐Derived Models

Advanced Science, EarlyView.
Engineered extracellular vesicles displaying Ephrin‐B2 selectively target Ephrin‐B4–expressing ovarian cancer cells, enabling precise delivery in patient‐derived models. This scalable bio‐manufacturing platform reveals a versatile strategy to exploit Ephrin signaling for highly specific therapeutic payload delivery and motivates exploration of tailored
Nihar Godbole, Andrew Lai, Alexander Quinn, Marianne Gillard, Dominic Guanzon, Katherin Scholz‐Romero, Alexis Salas‐Burgos, Bastián Lillo Dapremont, Rohan Lourie, Naven Chetty, Richard Lobb, Kate Beecher, Amy E. McCart Reed, Kaltin Ferguson, Biao Sun, Yaowu He, John D. Hooper, Carlos Salomon   +17 more
wiley   +1 more source

Bionic Solar‐Powered Heavy Metal Trap for Eco‐Friendly Sludge Drying and Simultaneous Electricity Generation

Advanced Science, EarlyView.
Herein, we propose a solar‐powered heavy metal trap (SPHT) for sludge disposal. The indoor experiments demonstrated that the sludge water content decreased from 90 % to 31 %, coupled with a decrease in heavy metal content to 6 % at most. Furthermore, the designed SPHT generated an initial potential of 0.10 V, and monitoring this hydrovoltaic potential ...
Yanlin Li, Jinglan Wang, Hailin Gu, Zhen Yu, Fawei Lin, Cunku Dong, Ningning Cao, Miao Yu   +7 more
wiley   +1 more source

Securing Data Provenance in the Cloud [PDF]

, 2012
Cloud storage offers the flexibility of accessing data from anywhere at any time while providing economical benefits and scalability. However, cloud stores lack the ability to manage data provenance. Data provenance describes how a particular piece of data has been produced.
Muhammad Rizwan Asghar, Mihaela Ion, Giovanni Russello, Bruno Crispo   +3 more
openaire   +2 more sources