Spatial Aspects of Demographic Processes in Serbia by Nikola Krunić, Aleksandra Gajić, Danijela Srnić, Dragutin Tošić

“…A model of population distribution was created by using selected census statistical data and correlating them with phenomena in actual geospace. …”
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Integrating Artificial Intelligence into an Automated Irrigation System by Nicoleta Cristina Gaitan, Bianca Ioana Batinas, Calin Ursu, Filaret Niculai Crainiciuc

“…This system uses data from all devices connected to the application to assess current climate conditions at a national level, identifying trends and generating reports that aid in adapting to extreme events. …”
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Independent validation and outlier analysis of EuroPOND Alzheimer’s disease staging model using ADNI and real-world clinical data by Mandy M. J. Wittens, Diana M. Sima, Arne Brys, Hanne Struyfs, Ellis Niemantsverdriet, Ellen De Roeck, Christine Bastin, Florence Benoit, Bruno Bergmans, Jean-Christophe Bier, Peter Paul de Deyn, Olivier Deryck, Bernard Hanseeuw, Adrian Ivanoiu, Gaëtane Picard, Eric Salmon, Kurt Segers, Anne Sieben, Evert Thiery, Jos Tournoy, Anne-Marie van Binst, Jan Versijpt, Dirk Smeets, Maria Bjerke, Maura Bellio, Neil P. Oxtoby, Daniel C. Alexander, Annemie Ribbens, Sebastiaan Engelborghs

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Uncovering the potential of smartphones for behavior monitoring during migraine follow-up by Marija Stojchevska, Jonas Van Der Donckt, Nicolas Vandenbussche, Mathias De Brouwer, Koen Paemeleire, Femke Ongenae, Sofie Van Hoecke

“…By utilizing built-in sensors and monitoring phone interactions, we gather data from which we derive metrics such as keyboard usage, application interaction, physical activity levels, ambient light conditions, and sleep patterns. …”
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Predictive Equations for Estimation of the Slump of Concrete Using GEP and MARS Methods by Ismail Husein, Ramaswamy Sivaraman, Sarwar Hasan Mohmmad, Forqan Ali Hussein Al-Khafaji, Sokaina Issa Kadhim, Yousof Rezakhani

“…This paper developed two robust data-driven models, namely gene expression programming (GEP) and multivariate adaptive regression splines (MARS), for the estimation of the slump of concrete (SL). …”
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The Alignment of High-resolution Solar Prominence Images Observed by the New Vacuum Solar Telescope by Yunfang Cai, Yongyuan Xiang, Kaifan Ji

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Beyond the numbers: App-enabled stroke prediction system for high-risk individuals in imbalanced datasets by Abrar Faiaz Eram, Aliva Sadnim Mahmud, Marwan Mostafa Khadem, Md Amimul Ihsan

“…While machine learning approaches show promise in stroke prediction, current research often relies on synthetic data to address dataset imbalance, potentially compromising real-world model performance in clinical settings. …”
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On the Theoretical Link between Optimized Geospatial Conflation Models for Linear Features by Zhen Lei, Zhangshun Yuan, Ting L. Lei

“…It has received increased research attention in recent years due to its wide range of applications in GIS (Geographic Information System) data production and analysis. …”
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Using Large Language Models for Microbiome Findings Reports in Laboratory Diagnostics by Thomas Krause, Laura Glau, Patrick Newels, Thoralf Reis, Marco X. Bornschlegl, Michael Kramer, Matthias L. Hemmje

“…Background: Advancements in genomic technologies are rapidly evolving, with the potential to transform laboratory diagnostics by enabling high-throughput analysis of complex biological data, such as microbiome data. Large Language Models (LLMs) have shown significant promise in extracting actionable insights from vast datasets, but their application in generating microbiome findings reports with clinical interpretations and lifestyle recommendations has not been explored yet. …”
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Spiking neural network tactile classification method with faster and more accurate membrane potential representation by Jing Yang, Zukun Yu, Xiaoyang Ji, Zhidong Su, Shaobo Li, Yang Cao

“…Efficiently classifying data obtained by touch sensors has long been an issue. …”
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The NANOGrav 12.5 yr Data Set: Probing Interstellar Turbulence and Precision Pulsar Timing with PSR J1903+0327 by Abra Geiger, James M. Cordes, Michael T. Lam, Stella Koch Ocker, Shami Chatterjee, Zaven Arzoumanian, Ava L. Battaglia, Harsha Blumer, Paul R. Brook, Olivia A. Combs, H. Thankful Cromartie, Megan E. DeCesar, Paul B. Demorest, Timothy Dolch, Justin A. Ellis, Robert D. Ferdman, Elizabeth C. Ferrara, Emmanuel Fonseca, Nate Garver-Daniels, Peter A. Gentile, Deborah C. Good, Megan L. Jones, Duncan R. Lorimer, Jing Luo, Ryan S. Lynch, Maura A. McLaughlin, Cherry Ng, David J. Nice, Timothy T. Pennucci, Nihan S. Pol, Scott M. Ransom, Renée Spiewak, Ingrid H. Stairs, Kevin Stovall, Joseph K. Swiggum, Sarah J. Vigeland

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Using machine learning to reveal seasonal nutrient dynamics and their impact on chlorophyll-a levels in lake ecosystems: A focus on nitrogen and phosphorus by Yong Fang, Ruting Huang, Xianyang Shi

“…Studies examining nutrients limiting lake eutrophication at large scales have traditionally focused on summer and autumn, potentially limiting the applicability of their findings. This study encompasses 86 state-controlled points in the Eastern China Basin, spanning data collected from January 2020 to July 2023. …”
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Securing smart cities through machine learning: A honeypot‐driven approach to attack detection in Internet of Things ecosystems by Yussuf Ahmed, Kehinde Beyioku, Mehdi Yousefi

“…Results demonstrate significant improvement in cyber‐attack detection and mitigation when integrating honeypot data into IoT security frameworks. The authors advance knowledge and provides practical insights for implementing robust security measures in diverse IoT applications, filling a crucial research gap.…”
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Theoretical and experimental results on time-series representations of polynomials by Asoke K. Nandi

“…This study considers time-series representations of polynomials. Often in data modelling and many other applications, accurate estimations of the degree of a polynomial, of the noise standard deviation, and of the coefficient of the highest degree of a polynomial are useful in detection, estimation, and prediction. …”
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Landslide Susceptibility Assessment in Hong Kong with Consideration of Spatio-Temporal Consistency by Agen Qiu, Qinglian Wang, Yajun Chen, Kunwang Tao, Xiangyu Peng, Wangjun He, Lifeng Gao, OU’er Geli, Fuhao Zhang

“…Previous studies have focused on static landslide susceptibility, using landslide assessment factor data from varying years, making it difficult to estimate spatio-temporal consistency and resulting in low prediction accuracy. …”
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Robust Low-Overlap Point Cloud Registration via Displacement-Corrected Geometric Consistency for Enhanced 3D Sensing by Xin Wang, Qingguang Li

“…These advances establish a new paradigm for robust 3D sensing in real-world applications where partial sensor data is prevalent.…”
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Metropolitan Area Network Model Design Algorithm Using Regional Railways Information and Daily Movement Data for Beyond 5G Research by Koga Nakamura, Shotaro Kitano, Yusuke Hirota, Takehiro Tsuritani, Hiroshi Hasegawa, Takuji Tachibana

“…Next, links are added in the topology according to the daily movement data such as person trip (PT) data. By using the proposed algorithm with daily movement data, the MAN model can be designed in metropolitan areas that are not completely covered by railways. …”
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Intellectual code analysis in automation grading by Denys Seliutin, Elena Yashyna

“…An astute examination of the gathered data will enable the formulation of precise suggestions for students to enhance their coding skills. …”
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Cyber-Biosecurity Challenges in Next-Generation Sequencing: A Comprehensive Analysis of Emerging Threat Vectors by Nasreen Anjum, Hani Alshahrani, Asadullah Shaikh, Mahreen-Ul-Hassan, Mehreen Kiran, Shah Raz, Abu Alam

“…It calls for focused efforts to mitigate risks associated with unauthorised access, data misuse, and exploitation. Failure to address these vulnerabilities could result in severe consequences, such as breaches of medical confidentiality, ethical concerns, and the potential for misuse in malicious applications like genetic warfare or bioterrorism. …”
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Sentiment Analysis Using Stacking Ensemble After the 2024 Indonesian Election Results by Andy Victor Pakpahan, Fahmi Reza Ferdiansyah, Robby Gustian, Muhammad Nur Faiz, Sukma Aji

“…By leveraging the complementary strengths of each base model, stacking not only boosts accuracy but also increases model robustness, making it highly suitable for real-world sentiment analysis applications that involve noisy and informal textual data from social media.…”
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