Prediction of the binding affinity of aptamers against the influenza virus

X Yu, Y Wang, H Yang, X Huang - SAR and QSAR in …, 2019 - Taylor & Francis
Thousands of investigations on quantitative structure–activity/property relationships
(QSARs/QSPRs) have been reported. However, few publications can be found that deal with …

Evaluation of digital transformation process through the Presidential Government System: Digital transformation office

S Şahnagil, H Salahaddin Gezici… - Journal of Information …, 2022 - Taylor & Francis
In today's world, where we are in the process of information society, especially the
development of internet technology and the use of the internet by large masses of people in …

Deep learning using multilayer perception improves the diagnostic acumen of spirometry: a single-centre Canadian study

A Mac, T Xu, JKY Wu, N Belousova… - BMJ Open …, 2022 - bmjopenrespres.bmj.com
Rationale Spirometry and plethysmography are the gold standard pulmonary function tests
(PFT) for diagnosis and management of lung disease. Due to the inaccessibility of …

Connectionist based models for solving Diophantine equation

SK Jeswal, S Chakraverty - Journal of Interdisciplinary Mathematics, 2020 - Taylor & Francis
Diophantine equation is an important concept while studying number theory. But there is as
such no standard method or procedure to find the solution of the Diophantine equation. In …

Intelligent malware detection using a neural network ensemble based on a hybrid search mechanism

SM Akandwanaho, M Kooblal - The African Journal of Information and …, 2019 - scielo.org.za
Malware threats have become increasingly dynamic and complex, and, accordingly, artificial
intelligence techniques have become the focal point for cybersecurity, as they are viewed as …

Enhancing Wind Energy Forecasting for Cost Efficiency in Hybrid Diesel and Solar Power Plants Using Artificial Neural Networks and Meteoblue Weather Data

TF Fadel, KM Banjarnahor, F Setiadi… - 2024 6th International …, 2024 - ieeexplore.ieee.org
This study integrates Artificial Neural Networks (ANN) with Meteoblue Weather data to
improve the performance of hybrid diesel and solar power plants by accurately predicting …

Can We Predict Tax Dispute Outcomes? The Case of Promotional Expenses in Indonesia

A Rosid, I Yulianto - 2023 - papers.ssrn.com
Tax disputes, along with their myriad variables and complexities, pose significant challenges
to economic and legal predictability. The importance of accurately predicting outcomes …

Exploring Machine Learning Models for Predicting Suicide Rates

P Dhaka, C Beukes - … on Information and Communication Technology for …, 2024 - Springer
Psychosocial factors influence suicide and are a major preventable cause of premature
death. Mental health disorders are the major cause of self-harm and suicides worldwide …

Sparse two level topic model for extraction of general summary words

N Akhtar, MM Sufyan Beg… - Journal of …, 2020 - Taylor & Francis
Extractive multi-document summarization methods based on topic models find relevant
general concepts or topics that are most representative of the documents. These topics are …

A comparison between classification statistical models and neural networks with application on Palestine data

AM Mohamed, MA Abdel-Fattah, ASM Aldirawi - J. Math. Comput. Sci., 2021 - scik.org
The paper has used labor force as dependent variable which contains two categories
(Employment and Unemployment) and 8 independent variables. The results regarding the …