Results 211 to 220 of about 97,336 (289)

A multi-criteria approach to ESG-based portfolio optimization incorporating historical performance, forward-looking insights, and credibilistic CVaR: a case study on the DJIA. [PDF]

Sci Rep
Taheripour E, Sadjadi SJ, Amiri B.
europepmc   +1 more source

What is “accuracy”? Rethinking machine learning classifier performance metrics for highly imbalanced, high variance, zero‐inflated species count data

Limnology and Oceanography: Methods, EarlyView.
Abstract Machine learning has opened the door for the automated sorting (classification) of images, holograms and acoustic backscatters of individual plankton, invertebrates, fish and marine mammals. However, this field is complicated by decades of paradoxically promising reports of classifier performance that do not correlate with real‐world uptake of
Bianca M. Owen, James R. Tweedley, Navid R. Moheimani, Chris S. Hallett, Jeffrey J. Cosgrove, Leopold P. O. Silberstein   +5 more
wiley   +1 more source

Robust securable economic operation of grid-connected renewable integrated energy system with hydrogen storage and electric and fuel cell vehicles. [PDF]

Sci Rep
Varei H, Zayandehroodi H, Shahbazzadeh MJ, Eslami M.   +3 more
europepmc   +1 more source

Ocean acidification at the crossroads I: Harmonizing unpurified and purified meta‐cresol purple spectrophotometric pHT measurements based on absorbance data

Limnology and Oceanography: Methods, EarlyView.
Abstract Consistent monitoring of seawater spectrophotometric pH on the total hydrogen ion scale (pHT) has been questioned by an evolving method, with changes in parameterization and the purity of the meta‐cresol purple (mCP). Using real seawater samples, we demonstrate that spectrophotometric pHT measurements obtained with unpurified (UNPUR) and ...
Marta Álvarez, Maribel I. García‐Ibáñez, Rubén Acerbi, Rocío Santiago‐Domenech, Elisa F. Guallart, Noelia M. Fajar, Lisandro Arbilla   +6 more
wiley   +1 more source

Einstein aggregation operators for multicriteria group decision making in uncertain environments using cubic picture fuzzy sets. [PDF]

Sci Rep
Tanoli MNK, Rafique K, Mahmood Z, Abdalla NSE, Popa IL, Kumar A.   +5 more
europepmc   +1 more source

Optical Coherence Tomography for High‐Precision Industrial Inspection in Industry 4.0: Advances, Challenges, and Future Trends

Laser &Photonics Reviews, EarlyView.
This review examines how optical coherence tomography transforms industrial inspection by delivering real‐time, micrometer‐resolution, depth‐resolved imaging. It surveys applications across display manufacturing, thin films, microelectronics, laser processing, and coatings, evaluates performance against conventional techniques, and highlights emerging ...
Nipun Shantha Kahatapitiya, Sm Abu Saleah, Daewoon Seong, Naresh Kumar Ravichandran, Sangyeob Han, Ruchire Eranga Wijesinghe, Mansik Jeon, Jeehyun Kim   +7 more
wiley   +1 more source

Use of Clinical Decision Support Systems for Diagnosis and Prognosis of Gastric Cancer: A Scoping Review. [PDF]

Health Sci Rep
Nopour R.
europepmc   +1 more source

Dynamic Evolution and Transformative Trends in the Consumer Market: A Technology Paradox Perspective

Psychology &Marketing, EarlyView.
ABSTRACT The consumer market is defined by tensions arising from the clash between technological advancement and consumer psychology. Current research lacks a unifying framework to explain these contradictions. Addressing this gap, we introduce a conceptual model based on technology paradox theory, which maps the dynamic process from antecedents ...
Chanaka Jayawardhena, Hongfei Liu, Chatura Ranaweera, P.K. Senyo   +3 more
wiley   +1 more source

Unveiling cost reduction potential of carbon capture and storage clusters in China under multiple uncertainties. [PDF]

iScience
Wang Y, Li J, Zhang X, Li K, Fan JL, Xiang X, Hou Y.   +6 more
europepmc   +1 more source

Machine Learning for Predictive Modeling in Nanomedicine‐Based Cancer Drug Delivery

Med Research, EarlyView.
The integration of AI/ML into nanomedicine offers a transformative approach to therapeutic design and optimization. Unlike conventional empirical methods, AI/ML models (such as classification, regression, and neural networks) enable the analysis of complex clinical and formulation datasets to predict optimal nanoparticle characteristics and therapeutic
Rohan Chand Sahu, Sanchit Arora, Dinesh Kumar, Ashish Kumar Agrawal   +3 more
wiley   +1 more source