Ethics dumping in artificial intelligence by Jean-Christophe Bélisle-Pipon, Gavin Victor

“…Artificial Intelligence (AI) systems encode not just statistical models and complex algorithms designed to process and analyze data, but also significant normative baggage. …”
Get full text

Lightweight Football Motion Recognition and Intensity Analysis Using Low-Cost Wearable Sensors by Qian Xie, Ning Jin, Shanshan Lu

“…A feature extraction scheme is designed in the initial data processing, and feature data augmentation is performed to solve the small sample data problem. To evaluate the performance of the designed football motion recognition algorithm, this paper proposes a data extraction experimental scheme to complete the data collection of different motions. …”
Get full text

Land use and land cover classification and change analysis in the area surrounding the Manglares Churute Ecological Reserve (Ecuador) using Sentinel-1 time series by D.A. Vélez-Alvarado, J. Álvarez-Mozos

“…Then, a Random Forests (RF) classification algorithm was built and optimized, following a five-fold cross validation scheme using the training dataset (70% of the ground truth). …”
Get full text

Explainable AI and optimized solar power generation forecasting model based on environmental conditions. by Rizk M Rizk-Allah, Lobna M Abouelmagd, Ashraf Darwish, Vaclav Snasel, Aboul Ella Hassanien

“…The performance of LSTM is compared with other machine learning algorithm such as Decision tree (DT), Linear regression (LR) and Gradient Boosting. …”
Get full text

Deep Learning Techniques in the Cancer-Related Medical Domain: A Transfer Deep Learning Ensemble Model for Lung Cancer Prediction by Omar Abdullatif Jassim, Mohammed Jawad Abed, Zenah Hadi Saied Saied

“…All models were evaluated using accuracy, precision, recall, and the F1-score. …”
Get full text

Joint User Association and Resource Allocation for Hierarchical Federated Learning Based on Games in Satisfaction Form by Panagiotis Charatsaris, Maria Diamanti, Symeon Papavassiliou

“…The latter includes the global model’s training accuracy and the users’ consumed energy and time during transmission. …”
Get full text

A Federated Learning-Based Framework for Accurately Identifying Human Activity in the Environment by Nwadher Suliman Al-Blihed, Dina M. Ibrahim

“…Analysis of the data generated by HAR devices may involve deep learning models and algorithms of different kinds. These data are personal and may include some sensitive data. …”
Get full text

Establishment of an MRI-based radiomics model for distinguishing between intramedullary spinal cord tumor and tumefactive demyelinating lesion by Zifeng Zhang, Ning Li, Yuhang Qian, Huilin Cheng

“…This study aims to develop and evaluate the effectiveness of a magnetic resonance imaging (MRI)-based radiomics model for distinguishing scTDL from IMSCT before treatment initiation. …”
Get full text

Hip arthroscopy for Legg-Calvè-Perthes disease in paediatric population by Ulunay Kanatli, Tacettin Ayanoglu, Mustafa Ozer, Muhammet Baybars Ataoglu, Mehmet Cetinkaya

Get full text

An Efficient Radio Map Construction Method Using Region-Aware Adaptive Ensemble Regression for Indoor Localization by Farid Yuli Martin Adiyatma, Panarat Cherntanomwong

“…RAER adapts to the statistical characteristics of the training data to efficiently produce high-quality virtual RSSI maps with low computational cost. …”
Get full text

Hindcasting Maximum Water Depths in Coastal Watersheds: The Importance of Incorporating Off‐Channel Data and Their Uncertainties in Machine Learning Models by Maryam Pakdehi, Ebrahim Ahmadisharaf

“…Abstract In the absence of adequate observations on the off‐channel areas, flood models are typically trained and validated against stream water depths. …”
Get full text

Development of a neural network-based risk prediction model for mild cognitive impairment in older adults with functional disability by Deyan Liu, Yuge Tian, Min Liu, Shangjian Yang

“…Model performance was evaluated using accuracy, precision, recall, F1 score, and the area under the receiver operating characteristic curve (ROC AUC). …”
Get full text

Predictive Archaeological Modeling with MaxEnt (Late Roman Settlements in The Upper Don Basin Case) by D. V. Sarychev, G. L. Zemtsov

“…The coordinates of these sites split into training and testing subsets served for developing a predictive model with MaxEnt. …”
Get full text

Prediction of Solar Radiation Data for Garlic Production in Magelang Regency Using Long Short-Term Memory by Muhammad Safrul Safrudin, Imas Sukaesih Sitanggang, Hari Agung Adrianto, Syarifah Aini

“…This study aims to determine the optimal solar radiation for garlic growth using the Long Short-Term Memory (LSTM) algorithm. This algorithm was selected due to its ability to analyze time-series data and predict long-term patterns. …”
Get full text

Enhanced Moisture Retrieval Near Boundary Layer From Satellite Sounder Data Through Atmospheric‐Surface Radiance Separation by Ronglian Zhou, Di Di, Jun Li, Zhenglong Li

Get full text

Efficient and accurate determination of the degree of substitution of cellulose acetate using ATR-FTIR spectroscopy and machine learning by Frank Rhein, Timo Sehn, Michael A. R. Meier

“…Predicting the DS of other cellulose acetate data sets yielded similar accuracy, demonstrating that the developed models are robust and suitable for efficient and accurate routine evaluations. The model solely trained on cellulose acetate was further able to predict the DS of other cellulose esters with an accuracy of $$\approx 0.1-0.2$$ in DS and model architectures for a more general analysis of cellulose esters were proposed.…”
Get full text

A Novel Approach to Autonomous Driving Using Double Deep Q-Network-Bsed Deep Reinforcement Learning by Ahmed Khlifi, Mohamed Othmani, Monji Kherallah

“…Deep reinforcement learning (DRL) trains agents to make decisions by learning from rewards and penalties, using trial and error. …”
Get full text

Hybrid RGSA and Support Vector Machine Framework for Three-Dimensional Magnetic Resonance Brain Tumor Classification by R. Rajesh Sharma, P. Marikkannu

“…The optimal features are selected using the proposed refined gravitational search algorithm (RGSA). Support vector machines, over backpropagation network, and k-nearest neighbor are used to evaluate the goodness of classifier approach. …”
Get full text

Enhancing Kidney Disease Diagnosis Using ACO-Based Feature Selection and Explainable AI Techniques by Abbas Jafar, Myungho Lee

“…The ant colony optimization method identified the most relevant feature subsets using a clinical dataset, reducing model complexity while preserving predictive accuracy. Performance evaluation shows that the extra trees classifier, when using optimized selected features, achieved the highest performance with an accuracy of 97.70% and an area under the curve of 99.55%, outperforming previous models trained on raw and complete processed feature sets. …”
Get full text

Prediction and Stage Classification of Pressure Ulcers in Intensive Care Patients by Machine Learning by Mürsel Kahveci, Levent Uğur

Get full text