Results 111 to 120 of about 24,118,381 (294)

Normal Workflow and Key Strategies for Data Cleaning Toward Real-World Data: Viewpoint. [PDF]

Interact J Med Res, 2023
Guo M, Wang Y, Yang Q, Li R, Zhao Y, Li C, Zhu M, Cui Y, Jiang X, Sheng S, Li Q, Gao R.   +11 more
europepmc   +1 more source

A Knowledge‐Based Approach for Understanding and Managing Additive Manufacturing Data

Advanced Engineering Materials, EarlyView.
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, Prithwish Tarafder, Anton Wiberg, Huanyu Li, Johan Moverare, Patrick Lambrix   +5 more
wiley   +1 more source

Turkish Telephone Conversations in Credit Risk Management: Natural Language Processing and LSTM Approach

Applied Sciences
This study aims to analyze text data obtained from Turkish phone calls to manage credit risk in the banking sector and predict whether customers will fulfill their payment promises.
Emre Ridvan Muratlar, Dogan Yildiz, Erhan Ustaoglu   +2 more
doaj   +1 more source

Flexural Behavior of 3D‐Printed Porous Bouligand‐Structured Polymers: Influence of Pitch Angle and Porosity

Advanced Engineering Materials, EarlyView.
This study examines how helicoidal architectures with different porosities respond to bending. Adjusting layer angle and spacing in 3D‐printed polymers reveals clear tradeoffs between stiffness, strength, and energy absorption. Experiments and simulations highlight designs that distribute stress effectively, offering pathways for optimizing lightweight
Praveenkumar Subhash Patil, Edward D. McCarthy, Parvez Alam   +2 more
wiley   +1 more source

Towards an automated data cleaning with deep learning in CRESST. [PDF]

Eur Phys J Plus, 2023
Angloher G, Banik S, Bartolot D, Benato G, Bento A, Bertolini A, Breier R, Bucci C, Burkhart J, Canonica L, D'Addabbo A, Di Lorenzo S, Einfalt L, Erb A, Feilitzsch FV, Iachellini NF, Fichtinger S, Fuchs D, Fuss A, Garai A, Ghete VM, Gerster S, Gorla P, Guillaumon PV, Gupta S, Hauff D, Ješkovský M, Jochum J, Kaznacheeva M, Kinast A, Kluck H, Kraus H, Lackner M, Langenkämper A, Mancuso M, Marini L, Meyer L, Mokina V, Nilima A, Olmi M, Ortmann T, Pagliarone C, Pattavina L, Petricca F, Potzel W, Povinec P, Pröbst F, Pucci F, Reindl F, Rizvanovic D, Rothe J, Schäffner K, Schieck J, Schmiedmayer D, Schönert S, Schwertner C, Stahlberg M, Stodolsky L, Strandhagen C, Strauss R, Usherov I, Wagner F, Willers M, Zema V, Waltenberger W, CRESST Collaboration.   +65 more
europepmc   +1 more source

Is an Apple an Orange? A Large Language Model Benchmark for Candidate Term Extraction and Subclass Decisions Against Upper Ontologies in Engineering and Materials Science

Advanced Engineering Materials, EarlyView.
Building machine‐readable vocabularies for materials science is slow, expert‐driven work. This study benchmarks 13 large language models on two of its first steps: finding candidate terms in engineering articles and deciding where they belong in a class hierarchy.
Thomas Bjarsch, Maximilian Holland, Klaus Drechsler, Johannes Schilp   +3 more
wiley   +1 more source

Cleaning Collections Data Using OpenRefine

Issues in Science and Technology Librarianship, 2019
Elizabeth Sterner
doaj   +1 more source

Sensor data cleaning for applications in dairy herd management and breeding

Frontiers in Animal Science
Data cleaning is a core process when it comes to using data from dairy sensor technologies. This article presents guidelines for sensor data cleaning with a specific focus on dairy herd management and breeding applications.
Katharina Schodl, Anna Stygar, Franz Steininger, Christa Egger-Danner   +3 more
doaj   +1 more source

Eleven quick tips for data cleaning and feature engineering. [PDF]

PLoS Comput Biol, 2022
Chicco D, Oneto L, Tavazzi E.
europepmc   +1 more source

PASTA‐ELN: Simplifying Research Data Management for Experimental Materials Science

Advanced Engineering Materials, EarlyView.
Research data management faces ongoing hurdles as many ELNs remain complex and restrictive. PASTA‐ELN offers an open‐source, cross‐platform solution that prioritizes simplicity, offline access, and user control. Its in tuitive folder structure, modular Python add‐ons, and open formats enable seamless documentation, FAIR data practices, and easy ...
S. Brinckmann, G. Winkens, R. Schwaiger
wiley   +1 more source