Comparative Analysis of Automated Machine Learning for Hyperparameter Optimization and Explainable Artificial Intelligence Models by Muhammad Salman Khan, Tianbo Peng, Hanzlah Akhlaq, Muhammad Adeel Khan

“…Artificial intelligence (AI) has been increasingly applied to solve complex real-world problems. One of the most significant challenges in AI lies in selecting and fine-tuning the optimal algorithm for a given task. …”
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Comparative Study on Dynamic Mechanical Properties and Energy Dissipation of Rocks under Impact Loads by Renshu Yang, Weiyu Li, Zhongwen Yue

“…Geological conditions are often complex during rock engineering construction (such as blasting and drilling) and usually involve rocks of several or multiple lithologies. …”
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ASSESSMENT OF AVIATION SECURITY SCREENERS PROFFICIENCY BY MEANS OF APPLYING THE A. BIRNBAUM TWO-PARAMETER MODEL by B. V. Zubkov, A. K. Volkov

“…The main advantage of similar systems application is the possibility of adaptation to the individual screeners’ requirements by changing the level of training task complexity. The efficiency of applying these systems is proved by foreign researches. …”
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Spatial and Spectral Structure-Aware Mamba Network for Hyperspectral Image Classification by Jie Zhang, Ming Sun, Sheng Chang

“…Recently, a network based on selective state space models (SSMs), Mamba, has emerged as a research focus in hyperspectral image (HSI) classification due to its linear computational complexity and strong long-range dependency modeling capability. …”
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A Comprehensive Review of Explainable Artificial Intelligence (XAI) in Computer Vision by Zhihan Cheng, Yue Wu, Yule Li, Lingfeng Cai, Baha Ihnaini

“…Explainable Artificial Intelligence (XAI) is increasingly important in computer vision, aiming to connect complex model outputs with human understanding. This review provides a focused comparative analysis of representative XAI methods in four main categories, attribution-based, activation-based, perturbation-based, and transformer-based approaches, selected from a broader literature landscape. …”
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Intensification of the process of extraction of sucrose from sugar beet of different technological advantage by Kulneva Nadezhda, Korobova Lyudmila, Matytsina Irina, Matvienko Natalia, Chernyaeva Svetlana

“…Experimental data on determining the molecular diffusion coefficient after processing sugar beet tissue using salt solutions confirmed the efficiency of the proposed method. A design of an apparatus for the complex thermochemical processing of sugar beet chips before extraction using rational technical solutions has been developed. …”
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Evaluating Predictive Accuracy of Regression Models with First-Order Autoregressive Disturbances: A Comparative Approach Using Artificial Neural Networks and Classical Estimators by Rauf I. Rauf, Masad A. Alrasheedi, Rasheedah Sadiq, Abdulrahman M. A. Aldawsari

“…These findings underscore the advantages of the ANN for predictive tasks involving autocorrelated data, highlighting its robustness and suitability for complex, large-scale datasets. This study provides practical guidance for selecting optimal prediction techniques in the presence of autocorrelation, recommending the ANN as the preferred method due to its superior performance.…”
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Investigation on Imbibition Recovery Characteristics in Jimusar Shale Oil and White Mineral Oil by NMR by Dunqing Liu, Chengzhi Jia, Keji Chen

“…Specifically, when the oil phase contains complex hydrocarbon components, lighter fractions in larger pores are preferentially mobilized; when the oil composition is homogeneous, oil in smaller pores is mobilized first.…”
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Construction and scheduling optimization of renewable energy consumption forecasting system for twisted tire porcelain manufacturing industry based on deep learning by Fangrong Liao, Runlin Ran, Jiayi Zhang

“…Abstract As a traditional handicraft with a long history and exquisite skills, the manufacturing process of twisted tire porcelain involves complex steps and high energy consumption. Because twisted tire porcelain has many unique patterns, it is necessary to classify porcelain according to the patterns in the production process. …”
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Development of a model system for in vitro simulated application testing of neurovascular stent systems by Siewert Stefan, Brandt-Wunderlich Christoph, Streckenbach Felix, Paetow Hagen, Schmidt Wolfram, Stiehm Michael, Langner Sönke, Cantré Daniel, Weber Marc-André, Schmitz Klaus-Peter

“…Trackability in the distal catheter area, which was positioned inside a complex 3D vascular model was analyzed for two neurovascular stent systems (Neuroform EZ 4.0x20 mm and Enterprise VRD 4.5x14 mm) combined with different microcatheters (Excelsior XT-27 Flex, PX Slim Delivery Microcatheter and Prowler Select Plus Infusion Catheter). …”
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Molecular Modification Strategies for Enhancing CO₂ Electroreduction by Yali Wang, Leibing Chen, Guoying Li, Jing Mei, Feng Zhang, Jiaxing Lu, Huan Wang

“…Electrocatalytic CO₂ reduction reaction (CO₂RR) is a crucial technology for achieving carbon cycling and renewable energy conversion, yet it faces challenges such as complex reaction pathways, competition for intermediate adsorption, and low product selectivity. …”
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Machine Learning with Evolutionary Parameter Tuning for Singing Registers Classification by Tales Boratto, Gabriel de Oliveira Costa, Alexsandro Meireles, Anna Klara Sá Teles Rocha Alves, Camila M. Saporetti, Matteo Bodini, Alexandre Cury, Leonardo Goliatt

“…Behind human voice production, a complex biological mechanism generates and modulates sound. …”
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Phase-dependent photo-assisted electrocatalytic conversion of nitrate to ammonia using TiO2: Insights into amorphous and rutile activity by Vitor R. Silveira, Daniel F. Fernandes, Robert Bericat-Vadell, Tomas Edvinsson, Tomas Kubart, Jacinto Sá

“…TiO2 was found to be the active catalyst, but the precise active structure responsible for each catalytic step remains unclear, as the reaction involves a complex, multistep process. By analyzing the catalytic activity of different TiO2 phases, we found that amorphous TiO2 significantly enhances the nitrate-to-nitrite reduction step, increasing nitrite concentration in solution by nearly 50 % and resulting in a 10 % increase in Faradaic efficiency for this product. …”
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An Adaptive Variance Adjustment Strategy for a Static Background Error Covariance Matrix—Part I: Verification in the Lorenz-96 Model by Lilan Huang, Hongze Leng, Junqiang Song, Dongzi Wang, Wuxin Wang, Ruisheng Hu, Hang Cao

“…Given its adaptability and efficiency, DRL-AST holds great potential for application in high-dimensional NWP models, where deep learning-based dimensionality reduction and reinforcement learning techniques could further enhance its feasibility and effectiveness in complex assimilation frameworks.…”
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Application of bifidobacterium in tumor therapy by Yinwu Kong, Han Bai, Feifei Deng, Yaomin Zhao, Qianyan Li, Li Chang

“…Nevertheless, their clinical application remains limited by challenges such as complex synthesis, high costs, low delivery efficiency, and poor biodegradability. …”
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Allosteric modulation of Grb2 drives ligand-dependent signal responses by Mariana Di Felice, Lucrezia Romana Rolfi, Julian Toso, Valeria Pennacchietti, Eduarda S. Ventura, Angelo Toto, Antonella Tramutola, Stefano Gianni

“…Abstract Adaptor proteins play a crucial role in signal transduction by facilitating the assembly of protein complexes at specific subcellular domains. These multifunctional molecules contain multiple binding modules that enhance the efficiency and flexibility of cellular signaling pathways, thereby orchestrating complex responses. …”
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SambaMixer: State of Health Prediction of Li-Ion Batteries Using Mamba State Space Models by Jose Ignacio Olalde-Verano, Sascha Kirch, Clara Perez-Molina, Sergio Martin

“…Approaches leveraging deep learning architectures have been proposed to predict the SOH using convolutional networks, recurrent networks, and transformers. Recently, Mamba selective state space models have emerged as a new sequence model that combines fast parallel training with data efficiency and fast sampling. …”
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Information requirement analysis for establishing intelligent natural language query interfaces in BIM-based construction projects by Mengtian Yin, Zhuoqian Wu, Haotian Li, Mun On Wong, Llewellyn Tang, Shu Tang, Junxiang Zhu

“…Emerging artificial intelligence (AI)-based natural language interface (NLI) systems show significant potential for enabling stakeholders to efficiently retrieve complicated building information models (BIM). …”
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Generating a Set of Reference Images for Reliable Condition Monitoring of Critical Infrastructure using Mobile Robots by Sotnikov O., Tymochko O., Bondarchuk S., Dzhuma L., Rudenko V., Mandryk Ya., Surkov K., Palonyi A., Olizarenko S.

“…The significance of the obtained results consists in the possibility of solving a complex task of forming a set of reference images, depending on the information content and stochastic conditions of sighting of critical infrastructure objects. …”
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Study on Connectivity of Fractured-Vuggy Marine Carbonate Reservoirs Based on Dynamic and Static Methods by Yintao Zhang, Chengyan Lin, Lihua Ren, Chong Sun, Jing Li, Zhicheng Wang, Guojin Xu

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