Autoencoder-Augmented Graph Neural Networks for Accurate and Scalable Structure Recognition in Analog/Mixed-Signal Schematics by Mohamed Salem, Witesyavwirwa Vianney Kambale, Ali Deeb, Sergii Tkachov, Anjeza Karaj, Joachim Pichler, Manuel Ludwig Lexer, Kyandoghere Kyamakya

“…The increasing complexity of Analog/Mixed-Signal (AMS) schematics has been posing significant challenges in structure recognition, particularly in the intellectual property (IP) industry, where data scarcity and confidentiality constraints limit model training. …”
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An Enhanced Model Free Adaptive Control Approach for Functional Electrical Stimulation Assisted Knee Joint Regulation and Control by T Alif, Shubhendu Bhasin, Kanwaljeet Garg, Deepak Joshi

“…The model free adaptive control with a data-driven approach is provided with recursive feasibility, compliance with input constraints, and exponential stability. …”
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Multimodal deep learning for enhanced temperature prediction with uncertainty quantification in directed energy deposition (DED) process by Adrian Matias Chung Baek, Taehwan Kim, Minkyu Seong, Seungjae Lee, Hogyeong Kang, Eunju Park, Im Doo Jung, Namhun Kim

“…The proposed methodology implements multimodal data fusion, combining reproduced grayscale images of deposition strategy with numerical process variables, including process parameters, geometrical features, and printing process status. …”
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Impact of Normalization Techniques on Synthetic Load Profile Generation Using Deep Generative Models by Luis H. T. Bandoria, Walquiria N. Silva, Madson C. De Almeida

“…These findings highlight the critical role of normalization in developing effective synthetic data generation pipelines for power system applications.…”
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Profiling chronic migraine patients according to clinical characteristics: a cluster analysis approach by Masahito Katsuki, Masahito Katsuki, Masahito Katsuki, Masahito Katsuki, Yasuhiko Matsumori, Shin Kawamura, Kenta Kashiwagi, Akihito Koh, Tetsuya Goto, Kazuma Kaneko, Kazuma Kaneko, Naomichi Wada, Naomichi Wada, Fuminori Yamagishi

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Singular Value Decomposition (SVD) Method for LiDAR and Camera Sensor Fusion and Pattern Matching Algorithm by Kaiqiao Tian, Meiqi Song, Ka C. Cheok, Micho Radovnikovich, Kazuyuki Kobayashi, Changqing Cai

“…This method provides a practical solution for maintaining reliable sensor fusion in autonomous driving applications subject to long-term calibration drift.…”
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Multi-Information-Assisted Bistatic Active Sonar Target Tracking for Autonomous Underwater Vehicles in Shallow Water by Zhanpeng Bao, Yonglin Zhang, Yupeng Tai, Jun Wang, Haibin Wang, Chao Li, Chenghao Hu, Peng Zhang

“…By utilizing this amplitude information, the algorithm proposed in this paper demonstrates a 23.95% performance improvement over the traditional probabilistic data association algorithm. The proposed algorithm provides AUVs with enhanced tracking autonomy, significantly advancing their capability in ocean engineering applications.…”
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Ensuring Energy Efficiency of Air Quality Monitoring Systems Based on Internet of Things Technology by Krzysztof Przystupa, Nataliya Bernatska, Elvira Dzhumelia, Tomasz Drzymała, Orest Kochan

“…A comprehensive analysis of sensor types, data transmission protocols, and system architectures was conducted, focusing on their energy consumption. …”
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Advanced intrusion detection technique (AIDT) for secure communication among devices in internet of medical things (IoMT) by M. Ramya, Pradeep Sudhakaran, Yuvaraj Sivagnanam, C. Santhana Krishnan

“…Considering the aforementioned, this study suggests an advanced intrusion detection technology (AIDT) to guarantee safe data exchange amongst IoMT devices. The model uses a probabilistic neural network (PNN) to classify whether intrusions are present or not, and particle swarm optimization (PSO) for feature extraction. …”
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Operational Energy Consumption Map for Urban Electric Buses: Case Study for Warsaw by Maciej Kozłowski, Andrzej Czerepicki

“…We aim to present a comprehensive data-driven methodology for analysing energy consumption within a large urban agglomeration. …”
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Generalized cross-entropy for learning from crowds based on correlated chained Gaussian processes by J. Gil-González, G. Daza-Santacoloma, D. Cárdenas-Peña, A. Orozco-Gutiérrez, A. Álvarez-Meza

“…Machine learning applications heavily depend on labeled data provided by domain experts to train accurate models. …”
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Univariate deep learning framework for short-term SST forecasting at high spatio-temporal scales by Jagdish Prajapati, Balaji Baduru, Athul C R, Biswamoy Paul, Vinod Daiya, Arya Paul

“…These capabilities hold significant applications for Potential Fishing Zone identification and coral bleaching alerts. …”
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A Formal Fuzzy Concept-Based Approach for Association Rule Discovery with Optimized Time and Storage by Gamal F. Elhady, Haitham Elwahsh, Maazen Alsabaan, Mohamed I. Ibrahem, Ebtesam Shemis

“…The necessity of this research stems from the high computational cost and redundancy associated with traditional fuzzy approaches, which, while capable of managing quantitative and imprecise data, are often impractical for large-scale applications in real scenarios. …”
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Using fuzzy decision support to create a positive mental health environment for preschoolers by Xinyue Li

“…Future work should explore integrating real-time data collection methods like wearable devices or mobile applications to gather more comprehensive and dynamic behavioural data.…”
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MKD-Net: A Novel Neuro Evolutionary Approach for Blockchain-Based Secure Medical Image Classification Using Multi-Kernel DLM by Virendra P. Vishwakarma, Abhay Kumar Yadav

“…Multiple kernels are employed in the proposed MKD-Net for different data representations in the classification of heterogeneous data. …”
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Reducing Label Dependency in Human Activity Recognition with Wearables: From Supervised Learning to Novel Weakly Self-Supervised Approaches by Taoran Sheng, Manfred Huber

“…These results not only highlight the complementary strengths of different learning paradigms, offering insights into tailoring HAR solutions based on the availability of labeled data, but also establish that our novel weakly self-supervised framework offers a promising solution for practical HAR applications where labeled data are limited.…”
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MPLS Network Actions: Technological Overview and P4-Based Implementation on a High-Speed Switching ASIC by Fabian Ihle, Michael Menth

“…We explain that for MNA with in-stack data (ISD), some header bits must remain unchanged during forwarding, and give an outlook on post-stack data (PSD).…”
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An Institutional Theory Framework for Leveraging Large Language Models for Policy Analysis and Intervention Design by J. de Curtò, I. de Zarzà, Leandro Sebastián Fervier, Victoria Sanagustín-Fons, Carlos T. Calafate

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An Energy-Efficient Battery Monitoring and Logging System for Agricultural Robotics with CAN Bus Integration by Soosaar Guido, Lillerand Tormi

“…Beyond real-time monitoring, the system’s primary value lies in the structured dataset it generates. This long-term data enables future applications such as AI-based diagnostics, predictive maintenance, and adaptive control strategies. …”
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Exploring Deep Clustering Methods in Vibro-Acoustic Sensing for Enhancing Biological Tissue Characterization by Robin Urrutia, Diego Espejo, Montserrat Guerra, Karin Vio, Thomas Suhn, Nazila Esmaeili, Axel Boese, Patricio Fuentealba, Alfredo Illanes, Christian Hansen, Victor Poblete

“…Nonlinear dimensionality reduction techniques, often referred to as manifold learning, are increasingly valuable for data visualization and unsupervised clustering. In the context of surgery and medicine, these methods facilitate the analysis of complex datasets, enabling pattern recognition in surgical data. …”
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