Deep-EFNet: An Optimized EfficientNetB0 Architecture With Dual Regularization for Scalable Multi-Class Brain Tumor Classification in MRI by Hussein Alshaari, Saeed Alqahtani

“…These enhancements include batch normalization layers for stable training, dropout and L2 regularization mechanisms for preventing overfitting, and a hierarchical dense layer structure for improved feature representation. …”
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An Evolutionary Deep Reinforcement Learning-Based Framework for Efficient Anomaly Detection in Smart Power Distribution Grids by Mohammad Mehdi Sharifi Nevisi, Mehrdad Shoeibi, Francisco Hernando-Gallego, Diego Martín, Sarvenaz Sadat Khatami

“…The increasing complexity of modern smart power distribution systems (SPDSs) has made anomaly detection a significant challenge, as these systems generate vast amounts of heterogeneous and time-dependent data. …”
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Deep Reinforcement Learning With Dueling DQN for Partial Computation Offloading and Resource Allocation in Mobile Edge Computing by Ehzaz Mustafa, Junaid Shuja, Faisal Rehman, Abdallah Namoun, Mazhar Ali, Abdullah Alourani

“…The Dueling DQN alleviates the complexity of simultaneous offloading and resource allocation decisions, with each branch independently controlling a subset of the decision variables to scale efficiently with an increasing number of IoT devices, thereby avoiding the combinatorial explosion of potential actions. …”
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Feasibility of continuous action unit parameters for road underlay formation by V. A. Nikolaev

“…Continuous action units, moving one after another, will consistently perform a set of works, carrying out the full construction of the road by flow method. The complex should have a continuous action unit to form a underlying layer. …”
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MORPHOLOGICAL FEATURES OF MUCOUS MEMBRANE OVER IMPACTED TEETH DEPENDENING ON CONDITIONS OF THEIR POSITION by P.I. Tkachenko, I.I. Starchenko, M.I. Dmytrenko, M.O. Cholovskyi

“… Impacted teeth are rather common and complex dentofacial anomaly, which requires a balanced approach not only in differential diagnosis of its specific nosological form, but also in a choice of rational treatment methods. …”
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GS-DTA: integrating graph and sequence models for predicting drug-target binding affinity by Junwei Luo, Ziguang Zhu, Zhenhan Xu, Chuanle Xiao, Jingjing Wei, Jiquan Shen

“…However, some current methods have certain shortcomings in focusing on important nodes in drug molecular graphs and dealing with complex structural molecules. In particular, when considering important nodes and complex substructures in molecules, they may not be able to fully explore the potential relationships between different parts. …”
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A hierarchical simulation framework incorporating full-link physical response for short-range infrared detection by Mingze Gao, Lixin Xu, Shiyuan Hu, Xiaolong Shi, Jiaming Gao, Yanjiang Wu, Huimin Chen

“…To this end, this study proposes a SIRD simulation framework incorporating full-link physical response, which is integrated through the radiative transfer layer, the sensor response layer, and the model-driven layer. …”
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A hybrid deep learning framework for global irradiance prediction using fuzzy C-Means, CNN-WNN, and Informer models by Walid Mchara, Lazhar Manai, Mohamed Abdellatif Khalfa, Monia Raissi, Wissem Dimassi, Salah Hannachi

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La Zone critique by Jérôme Gaillardet, Soraya Boudia

“…The interview reviews efforts to develop an infrastructure for overcoming points of ignorance and incomplete knowledge about complex interactions between gas and the atmosphere, stone, water, and the living.…”
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An Algorithm for Designing Circles in a Bubble Chart by Ching-Shoei Chiang, Hung-Chieh Li

“…The bubble chart that we designed has a unit circle at the center and is surrounded by a series of layered circle rings. In order to add the next layer of circles, there is always a silhouette circle that is tangential to all circles in the newest layer. …”
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A Multi-Scale Deep Learning Framework Combining MobileViT-ECA and LSTM for Accurate ECG Analysis by Abduljabbar S. Ba Mahel, Mehdhar S. A. M. Al-Gaashani, Reem Ibrahim Alkanhel, Dina S. M. Hassan, Mohammed Saleh Ali Muthanna, Ammar Muthanna, Ahmed Aziz

“…However, the variability and complexity of ECG signals make AF classification challenging, highlighting the need for more accurate and reliable methods. …”
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Fast real-time detection and counting of thrips in greenhouses with multi-level feature attention and fusion by Zhangzhang He, Xinyue Chen, Ying Gao, Yu Zhang, Yuheng Guo, Tong Zhai, Xiaochen Wei, Huan Li, Haipeng Zhu, Yongkun Fu, Zhiliang Zhang, Zhiliang Zhang

“…First, we propose a lightweight backbone network, PartialNeXt, which optimizes convolution layers through Partial Convolution (PConv), ensuring both network performance and reduced complexity. …”
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Coupling HEC-RAS and AI for River Morphodynamics Assessment Under Changing Flow Regimes: Enhancing Disaster Preparedness for the Ottawa River by Mohammad Uzair Anwar Qureshi, Afshin Amiri, Isa Ebtehaj, Silvio José Guimere, Juraj Cunderlik, Hossein Bonakdari

“…The Next-Gen GMDH addresses the complexity and limitations of standard GMDH by incorporating non-adjacent connections and optimizing intermediate layers, significantly reducing computational overhead while enhancing performance. …”
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Oral Lipid Nanoparticles for Improving the Efficiency of Drug Delivery Systems in Ulcerative Colitis: Recent Advances and Future Prospects by Siyu Zhu, Zhenlin Yang, Yulong Liu, Lan Cheng, Dingpei Long, Fangyin Dai

“…Ulcerative colitis (UC) is a chronic inflammatory bowel disease characterized by persistent, recurrent, and relapsing inflammation of the mucosal layer. Its pathogenesis is complex and not yet fully understood, with current treatments mainly focused on alleviating symptoms through pharmacological methods. …”
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Multi-mechanism synergistic adsorption of lead and cadmium in water by structure-functionally adapted modified biochar: A review by Di Zhang, Bo Wu, Tongtong Wang, Murat Yılmaz, Gaurav Sharma, Amit Kumar, Hui Shi

“…Where Pb2+ adsorption predominantly relies on inner layer complexation and precipitation, while Cd2+ is mainly removed through outer layer complexation and electrostatic attraction. …”
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The Role of Overflow on the Mechanical Propert ies of 3D Printed PLA by M. Axinte, D.L. Chicet, R. Chelariu, R.I. Comăneci

“…3D printing is a technology used on an ever-increasing scale, which makes it easier to obtain parts with complex geometry. The printing process is very complex because, in addition to the variables introduced by the various materials that are used, there is a multitude of process parameters: printing direction, layer thickness, infill level, filament feed rate, printing temperature, printing bed temperature, etc. …”
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Architected Design and Fabrication of Soft Mechanical Metamaterials by Thileepan Stalin, Aby Raj Plamootil Mathai, Naresh Kumar Thanigaivel, Elgar Kanhere, Saikrishna Dontu, Gumawang Hiramandala, Aaron Chooi, Arturo Castillo Ugalde, Pablo Valdivia Y Alvarado

“…Planar printing tool paths, utilized in layer‐by‐layer printing such as fused deposition modeling (FDM) and prevalently used in most slicing algorithms, severely limit the realization of complex topologies required in metamaterials. …”
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Morphological and chemical features of submarine groundwater discharge zones in the south-eastern part of the Baltic Sea by Krek Alexander V, Danchenkov Alexander, Mikhnevich Galina Sergeevna

“…The complex study of the bottom sediments and near-bottom water layer of the Gdansk Deep revealed the Ca maximum anomaly, marking the discharge of the Oxford-Titonian aquifer. …”
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Superstrate structured Sb2S3 thin-film solar cells by magnetron sputtering of Sb and post-sulfurization by Evgeniia Gilshtein, Harshvardhan Maheshkant Gupta, Andrea Maria Pierri Enevoldsen, Cristina Besleaga, Aurelian Catalin Galca, Stela Canulescu

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Convolution Self-Guided Transformer for Diagnosis and Recognition of Crop Disease in Different Environments by Huinian Li, Nannan Li, Wenmin Wang, Chengcheng Yang, Ningxia Chen, Fuqin Deng

“…The CSGT model demonstrates exceptional performance in diagnosing crop diseases across diverse backgrounds, overcoming the limitations of current models, especially in complex settings. The CSGT model’s CNN layer, hybrid-scale, and self-guided attention mechanisms ensure accurate diagnoses, even in the presence of background clutter. …”
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