Results 31 to 40 of about 77,058 (245)

A Hybrid Approach to Credit Risk Assessment Using Bill Payment Habits Data and Explainable Artificial Intelligence

Applied Sciences
Credit risk is one of the most important issues in the rapidly growing and developing finance sector. This study utilized a dataset containing real information about the bill payments of individuals who made transactions with a payment institution ...
Cem Bulut, Emel Arslan
doaj   +1 more source

Credit risk prediction in an imbalanced social lending environment

International Journal of Computational Intelligence Systems, 2018
Credit risk prediction is an effective way of evaluating whether a potential borrower will repay a loan, particularly in peer-to-peer lending where class imbalance problems are prevalent.
Anahita Namvar, Mohammad Siami, Fethi Rabhi, Mohsen Naderpour   +3 more
doaj   +1 more source

Spatial distribution and fixed-precision sequential sampling plans for Popillia japonica (Coleoptera: Scarabaeidae) adults in primocane raspberry: influence of foliar insecticides

Frontiers in Insect Science
The Japanese beetle, Popillia japonica Newman (Coleoptera: Scarabaeidae), an invasive species from northern Japan, was first detected in Minnesota in 1968.
Adam G. Toninato, Eric C. Burkness, William D. Hutchison   +2 more
doaj   +1 more source

Analysing the significance of small conformational changes and low occupancy states in serial crystallographic data

FEBS Open Bio, EarlyView.
This protocol paper outlines methods to establish the success of a time‐resolved serial crystallographic experiment, by means of statistical analysis of timepoint data in reciprocal space and models in real space. We show how to amplify the signal from excited states to visualise structural changes in successful experiments.
Jake Hill, Yelyzaveta Pulnova, Elke De Zitter, Helen M. Ginn, Briony A. Yorke   +4 more
wiley   +1 more source

Reduced Muscular Carnosine in Proximal Myotonic Myopathy—A Pilot 1H‐MRS Study

Annals of Clinical and Translational Neurology, EarlyView.
ABSTRACT Objective Myotonic dystrophy type 2 (proximal myotonic myopathy, PROMM) is a progressive multisystem disorder with muscular symptoms (proximal weakness, pain, myotonia) and systemic manifestations such as diabetes mellitus, cataracts, and cardiac arrhythmias.
Alexander Gussew, Maryam Kargaran, Maik Rothe, Andreas Deistung, Dietrich Stoevesandt, Walter A. Wohlgemuth, David Strube, Thomas Kendzierski, Anna Katharina Kölsch, Maurits Gerhard Abraham Heuschen, Markus Otto, Alexander Mensch   +11 more
wiley   +1 more source

Development of a Prediction Model for Progression Risk in High‐Grade Gliomas Based on Habitat Radiomics and Pathomics

Annals of Clinical and Translational Neurology, EarlyView.
ABSTRACT Objective To investigate the value of constructing models based on habitat radiomics and pathomics for predicting the risk of progression in high‐grade gliomas. Methods This study conducted a retrospective analysis of preoperative magnetic resonance (MR) images and pathological sections from 72 patients diagnosed with high‐grade gliomas (52 ...
Yuchen Zhu, Yuxi Gong, Weilin Xu, Xingjian Sun, Gefei Jiang, Lei Qiu, Kexin Shi, Mengxing Wu, Yinjiao Fei, Jinling Yuan, Jinyan Luo, Yurong Li, Yuandong Cao, Minhong Pan, Shu Zhou   +14 more
wiley   +1 more source

On the Convergence, Bias and Degeneracy Properties of Iterative Multiple Disturbance Particle Filtering

IEEE Access
The interest of this paper is the design of Bayesian particle filters for nonlinear state estimation (target tracking) applications. Particle filters employ a point mass representation of the probability densities using a set of weighted particles, in ...
Deepthi Kattula, Rajesh K. Pullagura, Praveen B. Choppala   +2 more
doaj   +1 more source

Entropy-Based Bagging for Fault Prediction of Transformers Using Oil-Dissolved Gas Data

Energies, 2011
The development of the smart grid has resulted in new requirements for fault prediction of power transformers. This paper presents an entropy-based Bagging (E-Bagging) method for prediction of characteristic parameters related to power transformers ...
Weigen Chen, Jian Li, Qing Yang, Yuanbing Zheng, Caixin Sun   +4 more
doaj   +1 more source

Multidimensional Profiling of MRI‐Negative Temporal Lobe Epilepsy Uncovers Distinct Phenotypes

Annals of Clinical and Translational Neurology, EarlyView.
ABSTRACT Objective Although hippocampal sclerosis (TLE‐HS) represents the most frequent cause of temporal lobe epilepsy (TLE), up to 30% of patients show no lesion on visual MRI inspection (TLE‐MRIneg). These cases pose diagnostic and therapeutic challenges and are underrepresented in surgical series.
Alice Ballerini, Alessia Casarini, Niccolò Biagioli, Laura Mirandola, Daniela Ballotta, Paul Summers, Simona Scolastico, Laura Madrassi, Maurilio Genovese, Marcella Malagoli, Gaetano Cantalupo, Giada Giovannini, Matteo Pugnaghi, Niccolò Orlandi, Laura Tassi, Valeria Cuccarini, Domenico Aquino, Elena Tartara, Fulvia Palesi, Giuseppe Didato, Paolo Vitali, the 3TLE Study Group, Roberta Di Giacomo, Fabio Doniselli, Federica Mazzi, Carlo Andrea Galimberti, Claudia A. M. Gandini Wheeler‐Kingshott, Stefano Meletti, Anna Elisabetta Vaudano   +28 more
wiley   +1 more source

Determining Resampling Ratios Using BSMOTE and SVM-SMOTE for Identifying Rare Attacks in Imbalanced Cybersecurity Data

Computers, 2023
Machine Learning is widely used in cybersecurity for detecting network intrusions. Though network attacks are increasing steadily, the percentage of such attacks to actual network traffic is significantly less.
Sikha S. Bagui, Dustin Mink, Subhash C. Bagui, Sakthivel Subramaniam   +3 more
doaj   +1 more source