Implementation of Machine Vision Methods for Cattle Detection and Activity Monitoring by Roman Bumbálek, Tomáš Zoubek, Jean de Dieu Marcel Ufitikirezi, Sandra Nicole Umurungi, Radim Stehlík, Zbyněk Havelka, Radim Kuneš, Petr Bartoš

“…The goal of this research was to implement machine vision algorithms in a cattle stable to detect cattle in stalls and determine their activities. …”
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Automated Text Structuring: Natural Language Processing and Regular Expressions in XML Tag Filling by Ivan P. Malashin, Vadim S. Tynchenko, Andrei P. Gantimurov, Vladimir A. Nelyub, Aleksei S. Borodulin

“…The conversion of documents into XML markup requires efficient algorithms and automated solutions. The focus is on tagging documents to meet NISO STS standards, ensuring compatibility across systems. …”
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Spatial and Temporal Variability of Rainfall Erosivity in the Niyang River Basin by Qingqin Bai, Lei Wang, Yangzong Cidan

“…This paper utilizes daily precipitation data from 123 grid points in the Niyang River Basin, spanning from 2008 to 2016, to calculate rainfall erosivity using a straightforward algorithmic model. Ordinary Kriging was used to examine the spatial and temporal variations in rainfall erosivity, while Spearman’s correlation analysis was employed to examine the relationships between annual rainfall erosivity and various factors, including multi-year average precipitation, erosive rainfall, dry-season rainfall, wet-season rainfall, temperature, and elevation. …”
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Global Sensitivity Analysis of CASC2D Hydrological Model Parameters by LI Xiao-ying, ZHANG Jin-hui, ZHAO Hong-jie

“…During the flow concentration process, channel routing played a controlling role, while overland flow routing played a supporting role. …”
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Combined Analysis of Transcriptome and Mendelian Randomization Reveals AKT1 and PPARG as Biomarkers Related to Glucose Metabolism in Sepsis by Ma J, Li W, Ma Q, Ding L, Wang Z, Wang R, Huang Y, Ma G, Gao J

“…AKT1 may inhibit sepsis development, while PPARG may promote it. These findings provide valuable insights for sepsis diagnosis and therapeutic drug development.Keywords: sepsis, glucose metabolism, transcriptomics, Mendelian randomization, biomarkers…”
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Linguistic Markers of Pain Communication on X (Formerly Twitter) in US States With High and Low Opioid Mortality: Machine Learning and Semantic Network Analysis by ShinYe Kim, Winson Fu Zun Yang, Zishan Jiwani, Emily Hamm, Shreya Singh

“…Chronic pain, affecting 1 in 5 US adults, is a key contributor to opioid use and misuse. While previous research has explored clinical and behavioral predictors of opioid risk, less attention has been given to large-scale linguistic patterns in public discussions of pain. …”
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TECHNOLOGY, AN ALLY TO THE 21ST CENTURY WOMEN by Vivian López Núñez

“…It also highlights the persistent gender inequalities in Paraguay and argues that, while technology is not a cure-all, it can significantly reduce barriers to real equality—if implemented thoughtfully. …”
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Dynamic Obstacle Avoidance for Robotic Arms Using Deep Reinforcement Learning with Adaptive Reward Mechanisms by Sen Yan, Yanping Zhu, Wenlong Chen, Jianqiang Zhang, Chenyang Zhu, Qi Chen

“…The experimental results demonstrate that the improved method significantly outperforms traditional algorithms in terms of convergence speed, reward value, and success rate.…”
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Quantum Machine Learning: Exploring the Role of Data Encoding Techniques, Challenges, and Future Directions by Deepak Ranga, Aryan Rana, Sunil Prajapat, Pankaj Kumar, Kranti Kumar, Athanasios V. Vasilakos

“…This paper aims at reviewing various data-encoding techniques in Quantum Machine Learning (QML) while highlighting their significance in transforming classical data into quantum systems. …”
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Automated Edge Detection for Cultural Heritage Conservation: Comparative Evaluation of Classical and Deep Learning Methods on Artworks Affected by Natural Disaster Damage by Laya Targa, Carmen Cano, Álvaro Solbes-García, Sergio Casas, Ester Alba, Cristina Portalés

“…The results show that while traditional methods often yield higher precision and recall scores, they are also sensitive to texture and contrast variations. …”
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Uncertainty analysis based on Bayesian inference for partial defect verification of PWR spent nuclear fuel by Hojik Kim, Hyung-Joo Choi, Woojin Kim, Seungmin Lee, Chul Hee Min, Sung-Woo Kwak

“…Ensuring the integrity of spent nuclear fuel (SNF) is essential for nuclear non-proliferation efforts. While detecting gross defects is relatively straightforward, identifying partial defects remain challenging. …”
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A multi-functional simulation platform for on-demand ride service operations by Siyuan Feng, Taijie Chen, Yuhao Zhang, Jintao Ke, Zhengfei Zheng, Hai Yang

“…Acting as a proper test bed, a simulation platform for ride-sourcing systems will thus be essential for both researchers and industrial practitioners. While previous studies have established simulators for their tasks, they lack a fair and public platform for comparing the models/algorithms proposed by different researchers. …”
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Clinical and Imaging Features of Sporadic and Genetic Frontotemporal Lobar Degeneration TDP‐43 A and B by Sean Coulborn, Rhiana Schafer, Ashlin R. K. Roy, Andrzej Sokolowski, Noah G. Cryns, Dana Leichter, Argentina Lario Lago, Eliana Marisa Ramos, Yann Cobigo, Salvatore Spina, Lea T. Grinberg, Daniel H. Geschwind, Maria L. Gorno‐Tempini, Joel H. Kramer, Howard J. Rosen, Bruce L. Miller, William W. Seeley, David C. Perry

“…TDP‐A was more dorsal in atrophy than TDP‐B, regardless of genetic status. Interpretation While some neuroimaging features are FTLD‐TDP subtype‐specific and do not significantly differ based on genotype, other features differ between sporadic and genetic forms within the same subtype and could decrease accuracy of classification algorithms that group genetic and sporadic cases.…”
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Hydrogen Enhancement in Syngas Through Biomass Steam Gasification: Assessment with Machine Learning Models by Yunye Shi, Diego Mauricio Yepes Maya, Electo Silva Lora, Albert Ratner

“…A detailed SHAP analysis identified the steam-to-biomass ratio (SBR) as the most critical factor in these predictions while also noting the significant impact of temperature conditions. …”
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RETRACTED ARTICLE: Intelligent dynamic spectrum access using fuzzy logic in cognitive radio networks by K. Krishna Kishore, Arun Sekar Rajasekaran, Ismail Keshta, Haewon Byeon, Mohammed Wasim Bhatt, Azeem Irshad, Isaac Ofori

“…By enabling secondary users to opportunistically access underutilized frequency bands while avoiding harmful interference to primary users, cognitive radio networks offer the potential for more efficient and dynamic spectrum allocation. …”
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Future horizons in diabetes: integrating AI and personalized care by Kaiqi Zhang, Yun Qi, Wenjun Wang, Xinyi Tian, Jiahui Wang, Lili Xu, Xu Zhai

“…Future horizons in diabetes care must focus on overcoming challenges in data privacy, algorithmic bias, device interoperability, and equity in AI-driven care while integrating these innovations into healthcare systems to improve patient outcomes and quality of life.…”
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Resource-Efficient Traffic Classification Using Feature Selection for Message Queuing Telemetry Transport-Internet of Things Network-Based Security Attacks by Emmanuel Tuyishime, Marco Martalò, Petru A. Cotfas, Vlad Popescu, Daniel T. Cotfas, Alexandre Rekeraho

“…The aim is to reduce feature dimensionality while maintaining high detection accuracy. Validated on the MQTTset dataset through binary and multiclass classification using seven ML algorithms, the results highlight its ability to enhance computational efficiency without compromising performance, showcasing its potential in real-world IoT security applications.…”
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Epigenetic modifications of cfDNA in liquid biopsy for the cancer care continuum by Jodie Wong, Rohit Muralidhar, Liang Wang, Chiang-Ching Huang

“…It advocates for the integration of multi-omic data through machine learning algorithms to refine predictive models and stresses the importance of collaboration among clinicians, researchers, and data scientists. …”
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Spectral-Spatial Ensemble Low-Rank Domain Adaptation for Hyperspectral Image Classification by Xue Zhang, Guoguo Yang, Hongjun Su, Yiping Chen, Zhaohui Xue, Qian Du

“…Current domain adaptation algorithms focus on finding domain-invariant subspaces to reduce domain shift, but there is still room to improve sample discriminability. …”
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Explainable Machine Learning for Mapping Minerals From CRISM Hyperspectral Data by Sandeepan Dhoundiyal, Moni Shankar Dey, Shashikant Singh, Pattathal V. Arun, Guneshwar Thangjam, Alok Porwal

“…Abstract This paper addresses some of the challenges in automating mineral mapping from CRISM hyperspectral data using two ML algorithms, namely, Random Forest (RF) and Gradient Boosted Trees (GBTree) algorithms. …”
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