From Ontology Design to User Experience. A Methodology to Design Interfaces for Information Seeking Purposes by Marco Grasso, Marilena Daquino, Giulia Renda

“…When designing data-driven web applications, users’ informative needs are aligned to knowledge organization (KO) requirements, which are secondly mapped to user interfaces (UI) components, and finally to user experience (UX) journeys. …”
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IoT and BDA in the Brazilian future logistics 4.0 scenario by Jobel Santos Correa, Mauro Sampaio, Rodrigo de Casto Barros, Wilson de Castro Hilsdorf

“…Abstract Paper aims This paper aims to identify the degree of interest and expected return time on investment in Internet of Things (IoT) and Big Data Analytics (BDA) technologies by Brazilian logistics companies. …”
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ARTIFICIAL INTELLIGENCE IN LANGUAGE EDUCATION IN TÜRKİYE: POTENTIAL CHALLENGES by S. Doğruer, Y. Tuğlu

“…RESULTS: Technological infrastructure limitations, high costs, reduced human interaction, and data security concerns could hinder the effective and secure use of AI-supported language learning applications. …”
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Constrained adversarial learning for automated software testing: a literature review by João Vitorino, Tiago Dias, Tiago Fonseca, Eva Maia, Isabel Praça

“…The found constrained data generation applications were systematized, and the advantages and limitations of approaches specific for white-box, grey-box, and black-box testing were analyzed, identifying research gaps and opportunities to improve automated testing tools with data generated by adversarial attacks.…”
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A Comprehensive Review of Multimodal Analysis in Education by Jared D. T. Guerrero-Sosa, Francisco P. Romero, Víctor H. Menéndez-Domínguez, Jesus Serrano-Guerrero, Andres Montoro-Montarroso, Jose A. Olivas

“…This comprehensive review synthesises findings from 177 peer-reviewed studies to examine the foundations, methodologies, tools, and applications of MMLA in education. It provides a detailed analysis of data collection modalities, feature extraction pipelines, modelling techniques—including machine learning, deep learning, and fusion strategies—and software frameworks used across various educational settings. …”
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Damage Detection and Identification on Elevator Systems Using Deep Learning Algorithms and Multibody Dynamics Models by Josef Koutsoupakis, Dimitrios Giagopoulos, Panagiotis Seventekidis, Georgios Karyofyllas, Amalia Giannakoula

“…For this purpose, multiple signal analysis methods have been developed to help identify anomalies in a system, through quantities such as vibrations or deformations in its critical components. In most applications, however, these data may be scarce or inexistent, hindering the overall process. …”
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Obtaining personalized predictions from a randomized controlled trial on Alzheimer’s disease by Dennis Shen, Anish Agarwal, Vishal Misra, Bjoern Schelter, Devavrat Shah, Helen Shiells, Claude Wischik

“…The SNN estimator is interpretable, transparent, and causally justified under a broad class of missing data scenarios. Relative to several standard methods, we empirically find that SNN performs well for the above two applications using Phase 3 clinical trial data on patients with Alzheimer’s Disease. …”
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DLProv: a suite of provenance services for deep learning workflow analyses by Débora Pina, Liliane Kunstmann, Adriane Chapman, Daniel de Oliveira, Marta Mattoso

“…Each step involves decisions impacting the final model’s performance, interpretability, and applicability. These models rely on data, preprocessing operations, and configuration, underscoring the need for mechanisms to ease the analysis throughout the entire life cycle—from model generation and selection to deployment. …”
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Motif clustering and digital biomarker extraction for free-living physical activity analysis by Ya-Ting Liang, Charlotte Wang

“…Abstract Background Analyzing free-living physical activity (PA) data presents challenges due to variability in daily routines and the lack of activity labels. …”
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Comparison of Manhattan and Chebyshev Distance Metrics in Quantum-Based K-Medoids Clustering by Solikhun Solikhun, Muhammad Rahmansyah Siregar, Lise Pujiastuti, Mochamad Wahyudi, Deny Kurniawan

“…Clustering is a technique in data mining used to identify patterns that can support decision-making processes. …”
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A Drone-Deployable Remote Current Sensor for Non-Invasive Overhead Transmission Lines Monitoring by Khaled Osmani, Detlef Schulz

“…This topology offers a promising solution for remote current monitoring in TLs, contributing to smart grid applications. The paper also outlines potential future work to enhance the system’s performance and applicability.…”
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MACHINE LEARNING AS A CORPORATION'S TOOL FOR SELECTION OF SUPPLIERS by V. V. Baklushinskii, E. V. Pustynnikova

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USER ACCEPTANCE OF TERMS & CONDITIONS AND PRIVACY POLICY: A LEGAL ANALYSIS OF THE POSITION OF FOOD DELIVERY MOBILE APPS IN THE MALAYSIAN CONTEXT by Mohammed Ibrahim Al Rezan, Md. Mostafa Hosain, Mohammad Ershadul Karim

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Dataset for Optical Processes in Dense Astrophysical and Laboratory Plasmas by Nenad M. Sakan, Vladimir A. Srećković, Zoran J. Simić, Momchil Dechev

“…The methodologies of our research, as well as the current and future elements of their applications, are explained. In addition to being helpful to other researchers for achieving a variety of goals, the data from this study could be useful the interdisciplinary fields of machine learning, astrochemistry and fusion physics. …”
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Elph: An open-source program for acquisition control and analysis of electrophysiological signals by A.V. Zakharov

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A Novel Deep Learning Architecture for Agriculture Land Cover and Land Use Classification from Remote Sensing Images Based on Network-Level Fusion of Self-Attention Architecture by Hussain Mobarak Albarakati, Muhammad Attique Khan, Ameer Hamza, Faheem Khan, Naoufel Kraiem, Leila Jamel, Latifah Almuqren, Roobaea Alroobaea

“…AI-driven precision agriculture applications can benefit from the large data source that remote sensing (RS) provides, as it can gather agricultural monitoring data at various scales throughout the year. …”
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GRAPEVNE - Graphical Analytical Pipeline Development Environment for Infectious Diseases [version 1; peer review: 2 approved] by Samir Bhatt, John-Stuart Brittain, Houriiyah Tegally, Rhys Inward, Joseph Tsui, Gaspary Mwanyika, Bernardo Gutierrez, Sofonias Kifle Tessema, Tuyen Huynh, Abhishek Dasgupta, John T. McCrone, George Githinji, Moritz U.G. Kraemer, Stephen Ratcliffe

“…Its modular approach already supports a diverse range of scientific applications, including genomic analysis, epidemiological modeling, and large-scale data processing. …”
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The AI revolution in micro-credentialing: personalized learning paths by Pooja Shanmughan, Jeena Joseph, Brinda Nair S., Anitha S. M., Anuja C. S., Jobin Jose

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Domain adaptation of deep neural networks for tree part segmentation using synthetic forest trees by Mitch Bryson, Ahalya Ravendran, Celine Mercier, Tancred Frickey, Sadeepa Jayathunga, Grant Pearse, Robin J.L. Hartley

“…Supervised deep learning algorithms have recently achieved state-of-the-art performance in the classification, segmentation and analysis of 3D LiDAR point cloud data in a wide-range of applications and environments. …”
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A Logarithmic Transfer Function for Binary Swarm Intelligence Algorithms: Enhanced Feature Selection with White Shark Optimizer by Seyma Gules, Alper Kılıç, Mustafa Servet Kiran, Mesut Gunduz

“…With the increasing size of datasets in data mining applications, feature selection has become critical for enhancing classification accuracy and reducing computational complexity. …”
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