Structural characterization of the Zalm district, West Saudi Arabia, using aeromagnetic data: An approach for gold mineral exploration by Alzahrani Hassan, Ibrahim Elkhedr

“…In the present study, the structural framework and major structural trends that most likely control the distribution of the gold mineral deposits in the Zalm district are interpreted using aeromagnetic data. For this purpose, the aeromagnetic data were subjected to enhancement filters to make the structural interpretation of the data easier. …”
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Non-Linear Synthetic Time Series Generation for Electroencephalogram Data Using Long Short-Term Memory Models by Bakr Rashid Alqaysi, Manuel Rosa-Zurera, Ali Abdulameer Aldujaili

“…<b>Background/Objectives:</b> The implementation of artificial intelligence-based systems for disease detection using biomedical signals is challenging due to the limited availability of training data. …”
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Early prediction of CKD from time series data using adaptive PSO optimized echo state networks by Thangadurai Anbazhagan, Balamurugan Rangaswamy

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Assessing the Impact of Conservation Practices on Post-Wildfire Recovery of Evergreen and Conifer Forests Using Remote Sensing Data by Shima Bahramvash Shams, Jennifer Boehnert, Olga Wilhelmi

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SDN-Based Multipath Data Offloading Scheme Using Link Quality Prediction for LTE and WiFi Networks by Santhosha Kamath, J. Aravinda Raman, Pankaj Kumar, Sanjay Singh, M. Sathish Kumar

“…Simultaneous data transfer on Long Term Evolution (LTE) and WiFi has gained attention for data offloading in 5G HetNet. …”
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Diagnosing epileptic seizures using combined features from independent components and prediction probability from EEG data by Madiha Khalid, Ali Raza, Adnan Akhtar, Furqan Rustam, Julien Brito Ballester, Carmen Lili Rodriguez, Isabel de la Torre Díez, Imran Ashraf

“…A novel ensemble approach consisting of a fast, independent component analysis random forest (FIR) and prediction probability is proposed, which uses electroencephalography (EEG) data to investigate the efficacy of the proposed approach for early detection of epileptic seizures. …”
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Annotation of genomics data using bidirectional hidden Markov models unveils variations in Pol II transcription cycle by Benedikt Zacher, Michael Lidschreiber, Patrick Cramer, Julien Gagneur, Achim Tresch

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Estimating Flood-Affected Houses as an SDG Indicator to Enhance the Flood Resilience of Sahel Communities Using Geospatial Data by Miguel A. Belenguer-Plomer, Inês Mendes, Michele Lazzarini, Omar Barrilero, Paula Saameño, Sergio Albani

“…Thus, the present study aims to enhance the capacity to monitor Sustainable Development Goals (SDGs) using the abovementioned technologies. In this context, a methodology that integrates ecoregion-specific model training and flood potential related geospatial datasets has been developed to estimate the number of houses affected by floods. …”
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Multimodal Classification of Alzheimer’s Disease Using Longitudinal Data Analysis and Hypergraph Regularized Multi-Task Feature Selection by Shuaiqun Wang, Huan Zhang, Wei Kong

“…While magnetic resonance imaging has become an indispensable neuroimaging modality for Alzheimer’s disease diagnosis and monitoring, current diagnostic paradigms predominantly rely on single-time-point data analysis, neglecting the inherent longitudinal nature of neuroimaging applications. …”
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Automated Risk Prediction of Post-Stroke Adverse Mental Outcomes Using Deep Learning Methods and Sequential Data by Chien Wei Oei, Eddie Yin Kwee Ng, Matthew Hok Shan Ng, Yam Meng Chan, Vinithasree Subbhuraam, Lai Gwen Chan, U. Rajendra Acharya

“…The combination of using DL algorithms, such as multi-layer perceptron (MLP) and long short-term memory (LSTM), which can process complex patterns in the data, and the inclusion of new data types, such as sequential data, helped to improve model performance. …”
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Constructing hidden differential equations using a data-driven approach with the alternating direction method of multipliers (ADMM) by Jye Ying Sia, Yong Kheng Goh, How Hui Liew, Yun Fah Chang

“…This paper adopted the alternating direction method of multipliers (ADMM) which aims to delve into data-driven differential equations. ADMM is an optimization method designed to solve convex optimization problems. …”
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Modelling fourth-order hyperelasticity in soft solids using physics informed neural networks without labelled data by Vikrant Pratap, Pratyush Kumar, Chethana Rao, Michael D. Gilchrist, Bharat B. Tripathi

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Exploring the use of new data assimilation technologies to map groundwater quality vulnerability in a large alluvial aquifer by Wes Kitlasten, Catherine Moore, John Doherty

“…These are demonstrated using a case study where groundwater head, streamflow and groundwater age data are assimilated in order to assess groundwater vulnerability to anthropomorphic deterioration of its quality. …”
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Hinge-FM2I: an approach using image inpainting for interpolating missing data in univariate time series by Saad Noufel, Nadir Maaroufi, Mehdi Najib, Mohamed Bakhouya

“…Inspired by door hinges, Hinge-FM2I drops a data point either before or after the gap (left/right-hinge), then uses FM2I for imputation. …”
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Test of the relationship between adolescents’ 24-h activity behavior and anxiety symptoms using compositional data analysis by Ning Wang, Ziyi Wang, Hui Liu, Yifeng Wang, Jinkun Li, Xiaobin Hong

“…Data were analyzed using CoDA and the isotemporal substitution model to statistically modify the intensity and duration of exercise in predicting anxiety. …”
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An explainable machine learning framework for railway predictive maintenance using data streams from the metro operator of Portugal by Silvia García-Méndez, Francisco de Arriba-Pérez, Fátima Leal, Bruno Veloso, Benedita Malheiro, Juan Carlos Burguillo-Rial

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A data ensemble-based approach for detecting vocal disorders using replicated acoustic biomarkers from electroglottography by Lizbeth Naranjo, Carlos J. Pérez, Daniel F. Merino

“…Electroglottography (EGG), a non-invasive technique measuring vocal fold contact area, has proven valuable in identifying and diagnosing vocal disorders. …”
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Mapping winter rapeseed in South China using Sentinel-2 data based on a novel separability index by Jian-bin TAO, Xin-yue ZHANG, Qi-fan WU, Yun WANG

“…Large-scale crop mapping using remote sensing data is of great significance for agricultural production, food security and the sustainable development of human societies. …”
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Estimating Aboveground Biomass and Carbon Sequestration in Afforestation Areas Using Optical/SAR Data Fusion and Machine Learning by Kashif Khan, Shahid Nawaz Khan, Anwar Ali, Muhammad Fahim Khokhar, Junaid Aziz Khan

“…This study aims to quantify aboveground biomass (AGB) and carbon sequestration potential (CSP) in the BTAP plantation regions using remote sensing and field data. Random sampling of 310 circular plots (17.84 m radius) provided measurements for tree height and diameter, from which AGB was calculated using allometric equations. …”
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Visualization of four-dimensional X-ray absorption fine structure data using a virtual reality system by Haruo Igarashi, Daiki Kido, Yutaka Ishii, Yasuhiro Niwa, Atsushi Okamoto, Masao Kimura

“…Our methodology establishes a new platform for analyzing 4D or 5D XAFS data that has applicability potential in various other multidimensional datasets, including microstructures coupled with spectroscopy and diffraction data.…”
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