Second version on a centralized approach to reducing burnouts in the IT industry using work pattern monitoring using artificial intelligence using MongoDB atlas and …

SR Chanthati - 2021 - digitalcommons.harrisburgu.edu
Industry burnout is interlinked with cultural, individual, physical, or emotional exhaustion,
and social factors, the resolution of which requires the technology-driven trends in the …

[HTML][HTML] Exploring predictors of AI chatbot usage intensity among students: Within-and between-person relationships based on the technology acceptance model

AK Kleine, I Schaffernak, E Lermer - Computers in Human Behavior …, 2025 - Elsevier
The current research investigated the factors associated with the intensity of AI chatbot
usage among university students, applying the Technology Acceptance Model (TAM) and its …

[HTML][HTML] The synergy of immersion and basic psychological needs satisfaction: Exploring gamification's impact on student engagement and learning outcomes

B Nguyen-Viet, B Nguyen-Viet - Acta Psychologica, 2025 - Elsevier
The integration of gamification into educational institutions has recently attracted
considerable interest, owing to the digital era and emerging learning contexts. This study …

Classifying Different Types of Smokers and Drinkers by Analyzing Body Signals using Machine Learning

R Hasan, F Hasan, M Hasan, M Islam… - … on Computing for …, 2024 - ieeexplore.ieee.org
Alcohol consumption and smoking are one of the most leading preventable causes of
mortality worldwide. Timely detection can play a vital role to prevent these kinds of …

Innovating workplace mental health strategies with advanced machine learning: application of a superior ensemble classifier for accurate stress detection in business …

MU Bokhari, G Yadav, M Zeyauddin - International Journal of Information …, 2024 - Springer
This study introduces a novel approach leveraging cutting-edge ensemble classification
algorithms to tackle the persistent issue of job stress among corporate professionals …

Predicting Diabetes in Women through Machine Learning

R Hasan, M Islam, MM Hosen… - … on Computing for …, 2024 - ieeexplore.ieee.org
Diabetes, a predominant non-communicable illness, presents a significant worldwide open
well-being concern with rising incidence rates and noteworthy mortality around the world …

Traffic Congestion Prediction using Machine Learning

MA Kafy, SI Faisal, ML Rahman, R Moni… - … on Computing for …, 2024 - ieeexplore.ieee.org
Due to the world population growing rapidly over time, the number of personal and local
vehicles are increasing which is one of the main causes of high traffic on the roads. For high …

Exploring Video Event Classification: Leveraging Two-Stage Neural Networks and Customized CNN Models with UCF-101 and CCV Datasets

K Sachdeva, JK Sandhu, R Sahu - 2024 11th International …, 2024 - ieeexplore.ieee.org
Rapid technological advances have significantly improved our ability to analyse video data.
This comprehensive review examines machine learning (ML) models applied to video event …

Anemia Disease Prediction using Machine Learning Techniques and Performance Analysis

MM Rahman, MU Mojumdar, HA Shifa… - … on Computing for …, 2024 - ieeexplore.ieee.org
The most frequent hematological disorder is anemia, which can affect anyone. This illness
develops when the blood lacks enough red blood cells or hemoglobin. However, if a person …

Improving Predictive Analytics for Student Dropout: A Comprehensive Analysis and Model Evaluation

W Sabbir, M Abdullah-Al-Kafi, AS Afridi… - … on Computing for …, 2024 - ieeexplore.ieee.org
This research project uses careful data preparation and machine learning model
assessment to provide an in-depth analysis of a dataset of students in college or university …