Mobile phone data for anticipating displacements: practices, opportunities, and challenges by Bilgeçağ Aydoğdu, Özge Bilgili, Subhi Güneş, Albert Ali Salah

“…The paper concludes by evaluating the potential benefits of MPD analysis for targeted and effective policy interventions and discusses future research avenues, drawing on recent studies and ongoing collaborations with mobile network operators.…”
Get full text

Video-Based Plastic Bag Grabbing Action Recognition: A New Video Dataset and a Comparative Study of Baseline Models by Pei Jing Low, Bo Yan Ng, Nur Insyirah Mahzan, Jing Tian, Cheung-Chi Leung

“…The second approach leverages a multiple-frame <i>convolutional neural network</i> (CNN) to exploit temporal and spatial patterns in the video data. …”
Get full text

Zero-shot intelligent fault diagnosis via semantic fusion embedding by Honghua Xu, Zijian Hu, Ziqiang Xu, Qilong Qian

“…On the other hand, a neural network-based metric module is designed to replace traditional distance measurements, enhancing the transferring capability between domains. …”
Get full text

Strengthening the public health system of Sierra Leone through scientific research and community engagement by Gebrekrstos Negash Gebru, Adel Hussein Elduma, James Sylvester Squire, Mohamed Alex Vandi, Soter Ameh, Hawawu Hussein, Kassim Kamara, Eric Ikoona, Ikechukwu Ogbuanu

“…The topics covered include investigations and responses to outbreaks and pandemics of both national and international significance, evaluations of electronic surveillance systems, assessments of the impact of COVID-19 on routine immunization, factors associated with COVID-19 fatalities, predictors of mental health disorders, and analyses of trends and patterns related to various priority diseases. …”
Get full text

Well Testing of Fracture Corridors in Naturally Fractured Reservoirs for an Improved Recovery Strategy by Yingying Guo, Andrew Wojtanowicz

“…This study introduces a well-testing technique designed to identify fracture corridors and to evaluate well placement for improved recovery prediction. …”
Get full text

Real-Time Traffic Data Analysis and Deep Learning-based Traffic Volume Classification for Congestion Mitigation at Urban Intersections by Omar Abdullah Hasan, Duraid Y. Mohammed

“…The collected data underwent analysis through signal processing techniques, followed by detection using machine learning models: Support Vector Machine (SVM), Random Forest (RF), Artificial Neural Network (ANN), Long Short-Term Memory (LSTM). Evaluating tow datasets, RTD and IDMT-Traffic, across four frame sizes, the results demonstrate the effectiveness of the proposed method. …”
Get full text

Robust Synthetic Data Generation for Sequential Financial Models Using Hybrid Variational Autoencoder–Markov Chain Monte Carlo Architectures by Francesco Bruni Prenestino, Enrico Barbierato, Alice Gatti

“…The model leverages Gated Recurrent Unit (GRU) layers for capturing long-term temporal dependencies and MCMC sampling for effective latent space exploration, ensuring high variability and accuracy. Experimental evaluations on datasets of Google, Tesla, and Nestlé stock prices demonstrate the model’s superior performance in preserving statistical and temporal patterns, as validated by quantitative metrics (discriminative and predictive scores), statistical tests (Kolmogorov–Smirnov), and t-Distributed Stochastic Neighbour Embedding (t-SNE) visualisations. …”
Get full text

Intercomparison of Antarctic Sea-Ice Thickness Estimates from Satellite Altimetry and Assessment over the 2019 Data-Rich Year by Magata Jesaya Mangatane, Marcello Vichi

“…Based on the limited set of available data, we did not find any single best performing method, and we recommend using the methods in a complementary way and to establish a network of concerted and continued field measurements for method assessments.…”
Get full text

Differential neural decoding of alarm and avoidance information from vocal alarm calls in humans by Gard K. Beinnes, Christine Skjegstad, Sascha Frühholz

“…This points to a critical involvement of the amygdala at neural levels of choice arbitrations rather than in threat evaluations signaled by screams.…”
Get full text

AI-Driven Drought Monitoring: Advanced Machine Learning Techniques for Early Prediction by Vij Priya, Tiwari Ankita

“…The study employs Convolutional Neural Networks (CNNs) and Recurrent Neural Networks (RNNs) to capture complex spatial and temporal patterns, enabling more accurate and timely drought forecasting compared to traditional approaches. …”
Get full text

Intra-seasonal Variability of Ball Speed and Coordination of Two Team-Handball Throwing Techniques in Elite Male Adolescent Players. by Serrien B., Clijsen R., Anders S., Goossens M., Baeyens J-P.

“…For coordination variability, a qualitative description based on the output of neural networks was used. All participants presented multiple coordination patterns, representing multi-stability on a month-to-month timescale and switched between stable states without the manipulation of any control variable. …”
Get full text

Ensemble of features for efficient classification of high-resolution remote sensing image by Gladima Nisia T, Rajesh S

“…The proposed system introduces two novel ideas, in its feature extraction implementation, namely (1) initialisation of filter values for the CNN and (2) change in local binary pattern feature extraction process. The experimental results are carried out with LISS IV Madurai image, and evaluation is done for the verification of the results. …”
Get full text

Enhanced MRI brain tumor detection using deep learning in conjunction with explainable AI SHAP based diverse and multi feature analysis by Asif Rahman, Maqsood Hayat, Nadeem Iqbal, Fawaz Khaled Alarfaj, Salem Alkhalaf, Fahad Alturise

“…This study investigates the synergy among multiple feature representation schemes such as local Binary Patterns (LBP), Gabor filters, Discrete Wavelet Transform, Fast Fourier Transform, Convolutional Neural Networks (CNN), and Gray-Level Run Length Matrix alongside five learning algorithms namely: k-nearest Neighbor, Random Forest, Support Vector Classifier (SVC), and probabilistic neural network (PNN), and CNN. …”
Get full text

Identification of therapeutic targets in lung adenocarcinoma using Mendelian randomization and multi-omics by Yue Li, Keru Ma, Hao Wang, Zongying Liu, Zhuying Li

“…Functional interactions were explored via protein–protein interaction network analysis, while single-cell analyses were employed to determine cell-specific expression patterns and differentiation trajectories. …”
Get full text

A Hybrid ANN–GWR Model for High-Accuracy Precipitation Estimation by Ye Zhang, Leizhi Wang, Lingjie Li, Yilan Li, Yintang Wang, Xin Su, Xiting Li, Lulu Wang, Fei Yao

“…This study advances precipitation estimation by introducing an artificial neural network into the event recognition period.…”
Get full text

Explainable AI for Spectral Analysis of Electromagnetic Fields by Dimitris Kalatzis, Agapi Ploussi, Ellas Spyratou, Theodor Panagiotakopoulos, Efstathios P. Efstathopoulos, Yiannis Kiouvrekis

“…The frequency bands analyzed include FM radio (87.5-108 MHz), VHF, UHF television, and various mobile telephony zones (700 MHz, 800 MHz, 900 MHz, 1800 MHz, 2100 MHz, 2600 MHz, and 3600 MHz), representing both traditional and emerging wireless technologies. A comparative evaluation of six machine learning algorithms was conducted: XGBoost, LightGBM, Random Forests, k-Nearest Neighbors, Neural Networks and Decision Trees to assess prediction performance across each frequency band. …”
Get full text

UNION: A Trust Model Distinguishing Intentional and Unintentional Misbehavior in Inter-UAV Communication by Ezedin Barka, Chaker Abdelaziz Kerrache, Nasreddine Lagraa, Abderrahmane Lakas, Carlos T. Calafate, Juan-Carlos Cano

“…Our proposal simultaneously establishes the inter-UAV trust and estimates the current context in terms of UAV energy, mobility pattern, and enqueued packets, in order to ensure full context awareness in the overall honesty evaluation. …”
Get full text

Bidirectional Transcriptome Analysis of Rat Bone Marrow-Derived Mesenchymal Stem Cells and Activated Microglia in an In Vitro Coculture System by Da Yeon Lee, Moon Suk Jin, Balachandran Manavalan, Hak Kyun Kim, Jun Hyeok Song, Tae Hwan Shin, Gwang Lee

“…The prediction of the gene network using IPA and experimental validation showed that LPS-stimulated primary rat microglia increase the migration of rBM-MSCs. …”
Get full text

GaitTriViT and GaitVViT: Transformer-based methods emphasizing spatial or temporal aspects in gait recognition by Hongyun Sheng

“…Previous gait recognition methods mostly focused on constructing a sophisticated model structure for better model performance during evaluation. Moreover, these methods are primarily based on traditional convolutional neural networks (CNNs) due to the dominance of CNNs in computer vision. …”
Get full text

Assessing the prognostic and therapeutic value of cuproptosis-related genes in colon adenocarcinoma patients by Zhanhui Ye, Yixian Song, Mengqing Zhu, Fuying Zheng, Wenjie Qin, Wenjie Qin, Xue Li, Pei Wang, Zihua Li, Kequan Chen, Aimin Li

“…Using the Weighted Gene Co-expression Network Analysis (WGCNA) method, we identified the gene module most strongly linked to cuproptosis and conducted functional enrichment analysis to explore the roles of genes within this module in COAD tumorigenesis. …”
Get full text