A Hybrid Large Language Model for Context-Aware Document Ranking in Telecommunication Data by Abhay Bindle, Preeti Singla, Sachin Sharma, Abdukodir Khakimov, Reem Ibrahim Alkanhel, Ammar Muthanna

“…This research enhances information retrieval by combining machine learning-based ranking with traditional methods, improving knowledge discovery and decision-making in telecommunications and technical document processing.…”
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Detection of Tomato Leaf Pesticide Residues Based on Fluorescence Spectrum and Hyper-Spectrum by Jiayu Gao, Xuhui Yang, Simo Liu, Yufeng Liu, Xiaofeng Ning

“…In this study, fluorescence spectrum acquisition and hyperspectral imaging processing of tomato leaf samples with and without pesticides were conducted, and spectral data from regions of interest of hyperspectral images were extracted. …”
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An Edge Computing-Based and Threat Behavior-Aware Smart Prioritization Framework for Cybersecurity Intrusion Detection and Prevention of IEDs in Smart Grids With Integration of Mod... by Abdulmohsen Algarni, Zulfiqar Ahmad, Mohammed Alaa Ala'Anzy

“…It implements edge-computing technology for data storage and processing in smart grids. It applies machine-learning models for cybersecurity intrusion detection in IEDs and provides prevention by assigning priorities to the threats based on their behavior. …”
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Inherent Trade-Offs Between the Conflicting Aspects of Designing the Compact Global Navigation Satellite System (GNSS) Anti-Interference Array by Xiangjun Li, Xiaoyu Zhao, Xiaozhou Ye, Zukun Lu, Feixue Wang, Peiguo Liu

“…Building on these insights, we innovatively propose a multi-objective optimization framework based on the non-dominated sorting genetic algorithm-II (NSGA-II) model, integrating antenna electromagnetic characteristics and signal processing constraints. Through iterative generation of the Pareto front, this framework achieves a globally optimal solution that balances spatial efficiency and anti-interference performance. …”
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Timeseries Fault Classification in Power Transmission Lines by Non-Intrusive Feature Extraction and Selection Using Supervised Machine Learning by Rab Nawaz, Hani A. Albalawi, Syed Basit Ali Bukhari, Khawaja Khalid Mehmood, Muhammad Sajid

“…Performing specific operations on data in sequence of steps provided flexibility and adaptability in processing the data, making it easy to train, evaluate, and validate the learning algorithms. …”
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Handwritten Urdu Characters and Digits Recognition Using Transfer Learning and Augmentation With AlexNet by Aqsa Rasheed, Nouman Ali, Bushra Zafar, Amsa Shabbir, Muhammad Sajid, Muhammad Tariq Mahmood

“…The presented methods can be applied for research on Urdu characters and in diverse domains such as handwritten text image retrieval, reading postal addresses, bank’s cheque processing, preserving and digitization of manuscripts from old ages.…”
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Genetic algorithm optimization of ensemble learning approach for improved land cover and land use mapping: Application to Talassemtane National Park by Ali Azedou, Aouatif Amine, Isaya Kisekka, Said Lahssini

“…Using Sentinel-2 satellite imagery processed in Google Earth Engine (GEE), six spectral features and six vegetation indices were extracted. …”
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Improving the accuracy of remotely sensed TSS and turbidity using quality enhanced water reflectance by a statistical resampling technique by Kunwar Abhishek Singh, Dongryeol Ryu, Meenakshi Arora, Manoj Kumar Tiwari, Bhabagrahi Sahoo

“…The resampled spectral data and in-situ TSS and turbidity measurements were used to train four ML models: Partial Least Squares Regression (PLSR), Random Forest Regression (RFR), Extreme Gradient Boosting (XGBoost), and Support Vector Regression (SVR). Our approach improved the estimation accuracy of the TSS by 33% and turbidity by 28% compared to the input processed using the built-in Sentinel-2 cloud and cloud shadow masks. …”
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Designing a Four-Group Permutational Hybrid Feature Selection Scheme for Transient Stability Prediction Based on Multivariate Trajectory Data by Seyed Alireza Bashiri Mosavi, Omid Khalaf Beigi

“…The results show that FGPHFSS has a prediction accuracy of 99 % and a processing time of 101.819 milliseconds for TSP.…”
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Daily Crude Oil Prices Forecasting Using a Novel Hybrid Time Series Technique by Hasnain Iftikhar, Moiz Qureshi, Paulo Canas Rodrigues, Muhammad Usman Iftikhar, Javier Linkolk Lopez-Gonzales, Hasnain Iftikhar

“…First, it involved processing the original crude oil prices time series to address missing values, variance stabilization, and normalization. …”
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Identification of Exosome-Associated Biomarkers in Diabetic Foot Ulcers: A Bioinformatics Analysis and Experimental Validation by Tianbo Li, Lei Gao, Jiangning Wang

“…A GeneMANIA network highlighted RNA processing and vesicle trafficking. Transcription factor and miRNA predictions uncovered regulatory circuits, and DGIdb-driven drug repurposing followed by molecular docking identified Indatuximab ravtansine and heparin as high-affinity SDC1 binders. …”
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Reproducibility of evoked and induced MEG responses to proprioceptive stimulation of the ankle joint by Toni Mujunen, Santtu Seipäjärvi, Mila Nurminen, Tiina Parviainen, Harri Piitulainen

“…Cortical processing of proprioceptive afference can be investigated by examining phase locked evoked and induced responses in cortical signals to passive movement stimuli. …”
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Machine learning for classification of pediatric bipolar disorder with and without psychotic symptoms based on thalamic subregional structural volume by Weijia Gao, Kejing Zhang, Qing Jiao, Linyan Su, Dong Cui, Shaojia Lu, Rongwang Yang

“…Abstract Background The thalamus plays a crucial role in sensory processing, emotional regulation, and cognitive functions, and its dysregulation may be implicated in psychosis. …”
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Development of the Russian Space: Barriers and Opportunities for Regional Policy by N. V. Zubarevich

“…It, in principle, cannot be uniform, which is confirmed by the central-peripheral theory and studies of processes of spatial concentration of the economy, including within the framework of the “new economic geography” of the middle and the end of the 20th century. …”
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Formation of a policy of technological sovereignty in the territories of advanced socio-economic development by attracting private and public capital by N. S. Stepanov

“…The following methods were used: comparative and logical analysis in studying of trends in the digital economy, synthesis and generalisation in determining the essence of technological sovereignty and formulating directions to improve these processes. The article gives reasons for the phenomenon being in fact an object of industrial policy, competition,innovative development, and geopolitical studies, which actualises the issue of its formation. …”
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Semasiological Relationships of Lexical Parallels in English and French Color Nomenclature by A. V. Ageeva, L. R. Abdullina

“…This study allows for the identification and comparison of ascending and descending trends in color naming across both languages, taking into account the influence of extralinguistic reality on linguistic processes.…”
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Challenges and Prospects of Rite Tourism in Russian Regions by Yu. Yu. Pavlova

“…The article analyzes processes influencing current trends of tourism development. …”
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Val d’Hérens (Switzerland): A history of Missed (tourist) Transitions by Marjolaine Gros-Balthazard, Caterina Franco, Anouk Bonnemains

“…While tourism, as a development model, has been one of the vectors of these transformations, it is now adapting to address socio-environmental and climate issues. …”
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Regulation of microtubule nucleation in glioblastoma cells by ARF GTPase-activating proteins GIT1 and GIT2 and protein kinase C by Vadym Sulimenko, Eduarda Dráberová, Vladimíra Sládková, Tetyana Sulimenko, Věra Vosecká, Omar Skalli, Pavel Dráber

“…To further investigate their role in microtubule modulation, we examined the function of GITs in microtubule nucleation and the involvement of protein kinase C (PKC) in this process. Methods Glioblastoma cell lines with depleted GIT protein levels were generated using shRNA lentiviral vectors. …”
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Sentence Embedding Generation Framework Based on Kullback–Leibler Divergence Optimization and RoBERTa Knowledge Distillation by Jin Han, Liang Yang

“…Traditional word vector methods, such as Word2Vec and GloVe, as well as deep learning models like BERT, face limitations in handling context dependency and polysemy and present challenges in computational resources and real-time processing. …”
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