Combining first principles and machine learning for rapid assessment response of WO3 based gas sensors by Ran Zhang, Guo Chen, Shasha Gao, Lu Chen, Yongchao Cheng, Xiuquan Gu, Yue Wang

“…The collected data was subsequently utilized to develop a correlation model linking the multi-physical parameters to gas sensitive performance using intelligent algorithms. The model’s performance was assessed through receiver operating characteristic (ROC) curves, confusion matrices, and other evaluation metrics, ultimately achieving a prediction accuracy of 90% for identifying key features influencing gas adsorption performance. …”
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Local Diversity-Guided Weakly Supervised Fine-Grained Image Classification Method by Yuebo Meng, Xianglong Luo, Hua Zhan, Bo Wang, Shilong Su, Guanghui Liu

“…Extensive experiments conducted on four fine-grained datasets and explainable visualization demonstrate that the LDGNet can effectively enhance discriminative region localization and detailed feature acquisition for fine-grained objects, achieving competitive performance over other state-of-the-art algorithms.…”
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Scalable Semantic Adaptive Communication for Task Requirements in WSNs by Hong Yang, Xiaoqing Zhu, Jia Yang, Ji Li, Linbo Qing, Xiaohai He, Pingyu Wang

“…The experimental results show that the proposed SSAC is more robust than traditional and other semantic communication algorithms in image classification tasks, and achieves scalable compression rates without sacrificing classification performance, while improving the bandwidth utilization of the communication system.…”
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The Impact of Integrating Variable Renewable Energy Sources into Grid-Connected Power Systems: Challenges, Mitigation Strategies, and Prospects by Emmanuel Ejuh Che, Kang Roland Abeng, Chu Donatus Iweh, George J. Tsekouras, Armand Fopah-Lele

“…Many research efforts in using prediction models have developed real-time monitoring of variability and machine learning predictive algorithms in contrast to the conventional methods of studying variability. …”
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Artificial Intelligence in Breast Reconstruction: A Narrative Review by Andrei Iulian Rugină, Andreea Ungureanu, Carmen Giuglea, Silviu Adrian Marinescu

“…AI shows promise in enhancing imaging for tumor detection and surgical planning, improving microsurgical precision, predicting complications such as flap failure, and optimizing postoperative monitoring. …”
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Overview and Prospects of Visibility Analysis Approaches by Jianghong Zhao, Ailin Xu, Xueqing Zhang, Yunhui Zhang, Yihong Zhang, Mengtian Cao, Ming Huang

“…Chronologically, this paper reviews various algorithms, comparing their advantages and limitations in terms of processing speed, accuracy, and applicability. …”
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Comparative effects of metformin and varying intensities of exercise on miR-133a expression in diabetic rats: Insights from machine learning analysis by Elahe Alivaisi, Sabrieh Amini, Karimeh Haghani, Hori Ghaneialvar, Fatemeh Keshavarzi

“…We used the CatBoost algorithm to develop a predictive model for miR-133a expression based on metabolic parameters. …”
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Enhanced Vector Quantization for Embedded Machine Learning: A Post-Training Approach With Incremental Clustering by Thommas K. S. Flores, Morsinaldo Medeiros, Marianne Silva, Daniel G. Costa, Ivanovitch Silva

“…While VQ is a technique that reduces model size by grouping similar parameters, incremental clustering, implemented via the AutoCloud K-Fixed algorithm, preserves accuracy during compression. This combined approach was validated on an automotive dataset predicting CO2 emissions from vehicle sensor measurements such as mass air flow, intake pressure, temperature, and speed. …”
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AgriChainSync: A Scalable and Secure Blockchain-Enabled Framework for IoT-Driven Precision Agriculture by Hassam Ahmed Tahir, Walaa Alayed, Waqar Ul Hassan, Fahad Nabi, Truong X. Tran

“…The proposed framework shows a dynamic data storage algorithm that optimizes storage decisions based on data characteristics and features. …”
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Forecasting Model for Danube River Water Temperature Using Artificial Neural Networks by Cristina-Sorana Ionescu, Ioana Opriș, Daniela-Elena Gogoașe Nistoran, Constantin-Alexandru Baciu

“…The ANN uses the Levenberg–Marquardt feedforward backpropagation algorithm. This feature is useful for the irrigation systems and for the power plants in the area that use river water for different purposes. …”
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Advanced modeling of salt-inducible kinase (SIK) inhibitors incorporating protein flexibility through molecular dynamics and cross-docking by Jorge Luis Valdés-Albuernes, Erbio Díaz-Pico, Sergio Alfaro, Julio Caballero

“…Our results highlight the importance of protein flexibility in achieving accurate correlations between docking energies and experimental pIC50 values, enhancing inhibitor selectivity predictions.…”
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SHapley Additive exPlanations (SHAP) for Landslide Susceptibility Models: Shedding Light on Explainable AI by H. Al-Najjar, B. Kalantar, B. Pradhan, G. Beydoun, N. Ueda

“…The first approach incorporates geoenvironmental factors, while the second integrates both geoenvironmental factors and an additional physically based model. Random Forest (RF) algorithm is used to develop and compare these landslide susceptibility models. …”
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Shape optimization of bellmouth to improve flow uniformity under non-aligned inflow condition in gas turbine casing by Myoung Hun Han, Jin Hyeong Park, Jae Sung Yang, Sang Youl Yoon, June Kee Min

“…The optimized shape of the bellmouth was obtained by using the two correlations and the genetic algorithm. In addition, the optimized bellmouth was found using conditional U-Net, which predicted the flow uniformity image according to the given shape conditions. …”
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3D Volumetric Strain Distribution of the Cerro Prieto Geothermal Field Inferred From Inverse Modeling of InSAR and Leveling Data by Luis A. Gallardo, Olga Sarychikhina, Ewa Glowacka, Braulio Robles

“…Whereas the combined use of high‐resolution InSAR, leveling and GPS data may enable highly detailed three‐dimensional deformation models, publicly available modeling and inversion algorithms either seek a single homogeneously deformed source or involve a few thousand modeling elements. …”
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Investigating employment patterns and determinants in the European Union through panel data insights by Vasilescu Maria Denisa, Stănilă Larisa, Crivoi Silvana, Belu Maria Berta

“…The selected indicators covered the economic, educational, and social dimensions, providing a complex vision of employment and how it can be improved. …”
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An automated network-based tool to search for metabolic vulnerabilities in cancer by Luis V. Valcárcel, Edurne San José-Enériz, Raquel Ordoñez, Iñigo Apaolaza, Danel Olaverri-Mendizabal, Naroa Barrena, Ana Valcárcel, Leire Garate, Jesús San Miguel, Antonio Pineda-Lucena, Xabier Agirre, Felipe Prósper, Francisco J. Planes

“…Here, we present gmctool, a freely accessible online tool that allows us to accomplish this task in a simple, efficient and intuitive environment. gmctool exploits the concept of genetic Minimal Cut Sets (gMCSs), a theoretical approach to synthetic lethality based on genome-scale metabolic networks, including a unique database of synthetic lethals computed from Human1, the most recent metabolic reconstruction of human cells. gmctool introduces qualitative and quantitative improvements over our previously developed algorithms to predict, visualize and analyze metabolic vulnerabilities in cancer, demonstrating a superior performance than competing algorithms. …”
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Integrative analysis of crotonylation-associated genes reveals prognostic and therapeutic targets in gliomas by Bowen Yin, Bowen Yin, Zhuoyang Fan, Panpan Yu, Panpan Yu, Jin Li, Jin Li, Yilin Wang, Yilin Wang, Minfeng Shu, Minfeng Shu

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A Multi-Modal Attentive Framework That Can Interpret Text (MMAT) by Vijay Kumari, Sarthak Gupta, Yashvardhan Sharma, Lavika Goel

“…Deep learning algorithms have demonstrated exceptional performance on various computer vision and natural language processing tasks. …”
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Accurate Virtual Trial Assembly Method of Prefabricated Steel Components Using Terrestrial Laser Scanning by Yin Zhou, Daguang Han, Kaixin Hu, Guocheng Qin, Zhongfu Xiang, Chunli Ying, Lidu Zhao, Xingyi Hu

“…Experimental results show that the geometric prediction deviation of VTA is less than 1/1800 of the experimental bridge span, and the mean stress predicted via VTA is 90% of the measured mean stress. …”
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Fractional Optimizers for LSTM Networks in Financial Time Series Forecasting by Mustapha Ez-zaiym, Yassine Senhaji, Meriem Rachid, Karim El Moutaouakil, Vasile Palade

“…We extend several widely used optimization algorithms—including Adam, RMSprop, SGD, Adadelta, FTRL, Adamax, and Adagrad—by incorporating fractional derivatives into their update rules. …”
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