Experimental 5G Network Performance Analysis in a Semi-Anechoic and Semi-Reverberation Chamber by Felix Delgado-Ferro, Alejandro Ramirez-Arroyo, Jorge Navarro-Ortiz, Juan F. Valenzuela-Valdes

“…This dataset has been analyzed using statistical algorithms such as Principal Component Analysis and SHapley Additive ExPlanations. …”
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The Role of BCL-2 Expression in Patients with Myelodysplastic Neoplasms by Bartłomiej Kuszczak, Krzysztof Zduniak, Angela Jendzierowska, Tomasz Wróbel, Piotr Ziółkowski, Justyna Rybka

“…BCL-2 immunohistochemistry should be viewed as a complementary biomarker that, when integrated with IPSS-R and mutational data, could refine therapeutic algorithms.…”
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Seronegative Sicca Syndrome: Diagnostic Considerations and Management Strategies by Yordanka M. Basheva-Kraeva, Krasimir I. Kraev, Petar A. Uchikov, Maria I. Kraeva, Bozhidar K. Hristov, Nina St. Stoyanova, Vesela T. Mitkova-Hristova, Borislav Ivanov, Stanislav S. Karamitev, Nina Koleva, Aleksandar Marinkov, Veselin A. Vassilev

“…To address these gaps, a paradigm shift is needed—one that embraces the spectrum of sicca syndromes, incorporates advanced immunophenotyping, and allows inclusion of seronegative patients in research and care algorithms.…”
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Human-based metaheuristics and non-parametric learning for groundwater-prone area mapping by Seyed Vahid Razavi-Termeh, Abolghasem Sadeghi-Niaraki, Seyedeh Zeinab Shogrkhodaei, Biswajeet Pradhan, Soo-Mi Choi

“…This research introduces a novel approach combining human-based metaheuristics—Teaching Learning Based Optimization (TLBO) and Cultural Algorithms (CA)—with non-parametric Decision Tree (DT) models. …”
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Enhancing Vehicle Location Prediction Accuracy with Road-Aware Rectification for Multi-Access Edge Computing Applications by Asif Mehmood, Afaq Muhammad, Faisal Mehmood, Wang-Cheol Song

“…Existing estimation techniques to forecast vehicle position aim to meet the real-time data needs but compromise accuracy due to a lack of context awareness. While algorithms such as the Kalman filter improve estimation accuracy by considering certainty-grading and current-state estimate of measurements, they do not include the road context, which is vital for more accurate predictions. …”
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LLM in the Loop: A Framework for Contextualizing Counterfactual Segment Perturbations in Point Clouds by Veljka Kocic, Niko Lukac, Dzemail Rozajac, Stefan Schweng, Christoph Gollob, Arne Nothdurft, Karl Stampfer, Javier del Ser, Andreas Holzinger

“…Point Cloud Data analysis has seen a major leap forward with the introduction of PointNet algorithms, revolutionizing how we process 3D environments. …”
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Integrating transcriptomic data with a novel drug efficacy prediction model for TCM active compound discovery by Yingcan Li, Yu Shen, Yezi Cai, Yulin zhang, Jiahui Gao, Lei Huang, Weinuo Si, Kai Zhou, Shan Gao, Qichao Luo

“…Abstract Identifying the active natural compounds remains a challenge for drug discovery, and new algorithms need to be developed to predict active ingredients from complex natural products. …”
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Texas rural land market integration: A causal analysis using machine learning applications by Tian Su, Senarath Dharmasena, David Leatham, Charles Gilliland

“…Using quarterly transactional land value data from 1966 to 2017, this study uses cutting-edge machine learning algorithms and probabilistic graphical models to uncover causal interaction patterns of different land markets in Texas. …”
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Harnessing Artificial Intelligence for the Diagnosis, Treatment and Research of Multiple Sclerosis by Manisha S. Patil, Linda Y. Lin, Rachel K. Ford, Elizaveta J. James, Stella Morton, Felix Marsh-Wakefield, Simon Hawke, Georges E. Grau

“…AI is revolutionising the diagnosis and treatment of MS by enhancing the accuracy and efficiency of both processes. AI algorithms, particularly those based on machine learning, are being used to analyse medical imaging data, such as MRI scans, to detect early signs of MS, monitor disease progression and assess patient treatment response with greater precision. …”
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A Comprehensive Review of the Main Heavyweight and Lightweight SDLC for Big Data Analytics Systems (BDAS) by David Alejandro Montoya-Murillo, Sergio Galvan-Cruz, Manuel Mora, Estela Lizbeth Munoz Andrade

“…However, despite the advanced technological progress – i.e. on BDAS algorithms, languages and platforms-, their development has been mainly through uncomplete ad-hoc or old rigorous heavyweight System Development Life Cycles (SDLC). …”
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Deep Learning-Enabled Dynamic Model for Nutrient Status Detection of Aquaponically Grown Plants by Mohamed Farag Taha, Hanping Mao, Samar Mousa, Lei Zhou, Yafei Wang, Gamal Elmasry, Salim Al-Rejaie, Abdallah Elshawadfy Elwakeel, Yazhou Wei, Zhengjun Qiu

“…Also, features selected by the DAE showed better performance compared to features extracted using both genetic algorithms (GAs) and sequential forward selection (SFS). …”
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Real-time Data Sharing Platform Technology for Rail Transit Management Systems by LIU Chao, LI Shen, SU Cheng, WANG Wei, HUANG Qing

“…Efficient real-time data processing capabilities can provide actionable insights for decision-making systems and support various artificial intelligence algorithms used in rail transit sector. Addressing this issue, the real-time data sharing platform technology for rail transit management systems is investigated. …”
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Reinforcement learning for an efficient and effective malware investigation during cyber incident response by Dipo Dunsin, Mohamed Chahine Ghanem, Karim Ouazzane, Vassil Vassilev

“…Future work will incorporate more advanced RL algorithms and large language models (LLMs) to further enhance the effectiveness of malware forensic analysis.…”
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A Spatiotemporal Fusion Network for Remote Sensing Based on Global Context Attention Mechanism by Weisheng Li, Yusha Liu, Yidong Peng, Fengyan Wu

“…Spatial-temporal fusion algorithms commonly encounter difficulties in effectively striking a balance between the extraction of intricate spatial details and changes over time. …”
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Low-Cost, LiDAR-Based, Dynamic, Flood Risk Communication Viewer by Debra F. Laefer, Evan O’Keeffe, Kshitij Chandna, Kim Hertz, Jing Zhu, Raul Lejano, Anh Vu Vo, Michela Bertolotto, Ulrich Ofterdinger

“…The method couples a laser scanning point cloud with algorithms that produce textured floodwaters, achieved through compounding multiple sine functions in a graphics shader. …”
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Automatic Real-Time Mining Software Process Activities From SVN Logs Using a Naive Bayes Classifier by Rui Zhu, Yichao Dai, Tong Li, Zifei Ma, Ming Zheng, Yahui Tang, Jiayi Yuan, Yue Huang

“…However, traditional process mining algorithms cannot be applied to event logs recorded in software configuration management (SCM) systems, such as SVN, because of missing activity attributes. …”
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Leveraging Large Language Models for Integrated Satellite-Aerial-Terrestrial Networks: Recent Advances and Future Directions by Shumaila Javaid, Ruhul Amin Khalil, Nasir Saeed, Bin He, Mohamed-Slim Alouini

“…We outline the current architecture of ISATNs and highlight the significant role LLMs can play in optimizing data flow, signal processing, and network management to advance 5G/6G communication technologies through advanced predictive algorithms and real-time decision-making. A comprehensive analysis of ISATN components is conducted, assessing how LLMs can effectively address traditional data transmission and processing bottlenecks. …”
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A two-stage voltage control method for distribution network integrated with complex electric vehicle clusters by Xin FANG, Juan LI, Yubo YUAN, Xiaodong YUAN

“…The day-ahead control stage provides a day-ahead operational scheduling of on-load tap changers and capacitor banks through global optimization algorithms to avoid potential voltage violation issues. …”
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Radiomics Analysis of Whole-Kidney Non-Contrast CT for Early Identification of Chronic Kidney Disease Stages 1–3 by Guirong Zhang, Pan Zhang, Yuwei Xia, Feng Shi, Yuelang Zhang, Dun Ding

“…Key features were selected through Relief, MRMR, and LASSO regression algorithms. A machine learning classifier was trained to differentiate CKD from healthy kidneys and compared with the radiologist assessments. …”
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Traceability Method for the Causes of Abnormal Electricity Prices Based on Comparative Analysis of Key Features by Weijia ZHAO, Yunxiao BAI, Yunyong ZHANG, Zhirun ZHU, Mingxu XIANG

“…Finally, using the alternative algorithms, the influencing degree of each element within the collection of key features on the electricity price are calculated respectively, and ranked based on their importance, thereby achieving filtering and tracing of the causes for abnormal electricity prices. …”
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