Results 141 to 150 of about 188 (174)

STELLAR‐CB: Synthetic Temporal LSTM for Livestock Activity Recognition—Cow Behaviour

Veterinary Medicine and Science, Volume 12, Issue 4, July 2026.
This study introduces a novel framework combining LSTM networks with SMOTE to address class imbalance in precision livestock farming. It improves the detection of rare behaviours in livestock, achieving state‐of‐the‐art performance while reducing computational overhead, offering a practical, breed‐agnostic solution for enhancing automated behaviour ...
Ghufran Ahmed, Rauf Ahmed Shams Malick, Ahmad Sami Al‐Shamayleh, Muhammad Adnan Ayub, Usama Antuley, Twaha Ahmed Minai, Muhammad Faisal Khan, Muhammad Faraz Hyder, Muhammad Mubashir Khan, Adnan Akhunzada   +9 more
wiley   +1 more source

Quantum machine learning: a classical perspective. [PDF]

Proc Math Phys Eng Sci, 2018
Ciliberto C, Herbster M, Ialongo AD, Pontil M, Rocchetto A, Severini S, Wossnig L.   +6 more
europepmc   +1 more source

From Language Identification to Topic Modelling: A Fully Integrated Pipeline for Multilingual Aspect‐Based Sentiment Analysis and Component‐Level Insights

Expert Systems, Volume 43, Issue 7, July 2026.
ABSTRACT The rapid expansion of multilingual digital platforms has made the accurate analysis of user‐generated content across different languages and cultural contexts increasingly essential. However, existing methods struggle to maintain consistent performance due to linguistic diversity, morphological complexity, and structural variations in text ...
Abdulkadir Şeker
wiley   +1 more source

Reducing the worst case running times of a family of RNA and CFG problems, using Valiant's approach. [PDF]

Algorithms Mol Biol, 2011
Zakov S, Tsur D, Ziv-Ukelson M.
europepmc   +1 more source

Machine Learning‐Based Loan Approval Automation: Enhancing Efficiency, Accuracy and Fairness in Credit Decision‐Making

Expert Systems, Volume 43, Issue 7, July 2026.
ABSTRACT Traditional loan approval processes are manual, time‐consuming and susceptible to human bias. This research develops a machine learning‐based system to automate loan eligibility assessment while enhancing efficiency, accuracy and fairness in credit decision‐making. We developed and compared multiple supervised ML models—including Random Forest,
Mani Ghahremani, Hellen Amimo Otieno, Mishanil Kazreen, Stavros Shiaeles   +3 more
wiley   +1 more source

Finding a mix of renewable energy for different stakeholders by applying multi‐criteria decision‐making techniques

International Transactions in Operational Research, Volume 33, Issue 4, Page 2499-2534, July 2026.
Abstract This paper presents a two‐stage model for planning a renewable energy portfolio by balancing economic, social and environmental sustainability goals. The first stage addresses a multi‐objective problem where conflictive impacts generated by the energy portfolios should be optimised according to the corresponding economic, social or ...
Amelia Bilbao‐Terol, Verónica Cañal‐Fernández, Carmen González‐Pérez   +2 more
wiley   +1 more source

A Path to Improving Simulated Properties of Low Clouds Over the Beaufort Sea Using Airborne in Situ Observations of Subgrid‐Scale Variability

Journal of Geophysical Research: Atmospheres, Volume 131, Issue 11, 16 June 2026.
Abstract Arctic low clouds influence Arctic system evolution through their effects on the atmosphere and surface. Unfortunately, atmospheric models and retrospective analysis (reanalysis) struggle to simulate Arctic low cloud occurrence and properties.
J. B. Dodson, P. C. Taylor, D. O. Barahona   +2 more
wiley   +1 more source

Atomic‐Scale Understanding of Selectivity Control in Nitrate Reduction on Cu(100) Under Acidic and Alkaline Conditions

Angewandte Chemie, Volume 138, Issue 23, 1 June 2026.
A combination of ab initio molecular dynamics simulations and density functional theory calculations clarifies the pH‐dependent origin of the selectivity of nitrate reduction on Cu(100). ABSTRACT We investigate the nitrate reduction reaction (NO3 RR) on the Cu(100) surface using grand‐canonical density functional theory (GC‐DFT) under constant ...
Ebrahim Tayyebi, Kai S. Exner
wiley   +2 more sources

Graphene‐Based Wearable Textile Triboelectric Nanogenerators and Biomechanical Sensors

Advanced Materials Technologies, Volume 11, Issue 12, 18 June 2026.
This study presents a wearable textile‐based triboelectric nanogenerator (T‐TENG) using sprayed graphene enhanced with a PVA adhesion layer. The graphene‐based electrode demonstrates high electrical conductivity and robustness to multiple bends. The fabricated T‐TENG provides stable and efficient output, with strong responsiveness to biomotion.
Hongyang Dang, Benji Fenech‐Salerno, Antonio Alessio Leonardi, Federico La Barbera, Felice Torrisi   +4 more
wiley   +1 more source

Graph‐based imitation and reinforcement learning for efficient Benders decomposition

AIChE Journal, Volume 72, Issue 6, June 2026.
Abstract This work introduces an end‐to‐end graph‐based agent for accelerating the computational efficiency of Benders Decomposition. The agent's policy is parameterized by a graph neural network, which takes as input a bipartite graph representation of the master problem and proposes a candidate solution.
Bernard T. Agyeman, Zhe Li, Ilias Mitrai, Prodromos Daoutidis   +3 more
wiley   +1 more source