AI-driven point cloud framework for predicting solder joint reliability using 3D FEA data by Mohd Zubair Akhtar, Maximilian Schmid, Gordon Elger

“…Traditional Finite Element Analysis (FEA) techniques for predicting solder joint lifespan often rely on manual post-processing to identify high-risk regions for plastic strain accumulation. …”
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Added wave resistance prediction and comparative study based on point cloud feature extraction by Mingfeng WU, Renchuan ZHU, Dekang XU

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Treegraph: tree architecture from terrestrial laser scanning point clouds by Wanxin Yang, Phil Wilkes, Matheus B. Vicari, Kate Hand, Kim Calders, Mathias Disney

“…Terrestrial laser scanning (TLS) offers millimetre‐level point cloud data, but current approaches to 3D tree reconstruction from TLS point clouds primarily focus on retrieving total volume at tree scale for aboveground biomass (AGB) estimation. …”
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Event camera-based human pose estimation via hybrid spiking-point cloud neural architecture by Sichao Tang, Hengyi Lv, Xiangzhi Li, Yuchen Zhao, Yisa Zhang, Yang Feng

“…The system also incorporates a cross-modal adaptive fusion mechanism that dynamically adjusts weights across different modalities, and an asynchronous skeleton constraint module that leverages human anatomical prior knowledge to constrain prediction results. Compared to existing methods, our network architecture more effectively processes the sparse asynchronous characteristics of event data, achieving a better balance between accuracy and efficiency, particularly excelling in complex scenes and rapid motion scenarios. …”
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Experimental test on 3D-printing components for Architectural Restoration by Valentina Tomei, Ernest Grande, Maura Imbimbo

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Development and Evaluation of Neural Network Architectures for Model Predictive Control of Building Thermal Systems by Jevgenijs Telicko, Andris Krumins, Agris Nikitenko

“…In this study, we adapt neural network architectures such as GRU and TCN for use in the context of building model predictive control. …”
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A multimodal deep learning architecture for predicting interstitial glucose for effective type 2 diabetes management by Muhammad Salman Haleem, Daphne Katsarou, Eleni I. Georga, George E. Dafoulas, Alexandra Bargiota, Laura Lopez-Perez, Miguel Rujas, Giuseppe Fico, Leandro Pecchia, Dimitrios Fotiadis, Gatekeeper Consortium

“…We achieved the multimodal architecture prediction results with Mean Absolute Point Error (MAPE) between 14 and 24 mg/dL, 19–22 mg/dL, 25–26 mg/dL in case of Menarini sensor and 6–11 mg/dL, 9–14 mg/dL, 12–18 mg/dL in case of Abbot sensor for 15, 30 and 60 min prediction horizon respectively. …”
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Developing and presenting a mathematical model for the purpose of organizational culture architecture based on creating alignment between the strategic reference points of organiza... by Elyas hasanzadeh Shweili, Mir Mehrdad peidaie, Ali reza Rezghi Rostami

“…Abstract The purpose of this research is to formulate and present a mathematical model for the purpose of organizational culture architecture based on creating alignment between the strategic reference points of organizational elements. …”
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Wavelets Application in Prediction of Friction Stir Welding Parameters of Alloy Joints from Vibroacoustic ANN-Based Model by Emilio Jiménez-Macías, Angel Sánchez-Roca, Hipólito Carvajal-Fals, Julio Blanco-Fernández, Eduardo Martínez-Cámara

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Continuous Joint Kinematics Prediction Using GAT-LSTM Framework Based on Muscle Synergy and Sparse sEMG by Meiju Li, Zijun Wei, Zhi-Qiang Zhang, Shuhao Ma, Sheng Quan Xie

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Beyond the Backbone: A Quantitative Review of Deep-Learning Architectures for Tropical Cyclone Track Forecasting by He Huang, Difei Deng, Liang Hu, Yawen Chen, Nan Sun

“…Building on this framework, we conduct a critical cross-model analysis that reveals key trends, performance disparities, and architectural tradeoffs. Our analysis also highlights several persistent challenges, such as long-term forecast degradation, limited physical integration, and generalization to extreme events, pointing toward future directions for developing more robust and operationally viable DL models for TC track forecasting. …”
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Hydrogen Safety in Solid Oxide Fuel Cells: an LSTM-Based Model for Predicting Temperature Anomalies and Change Points by Tomaso Vairo, Davide Clematis, Maria Paola Carpanese, Bruno Fabiano

“…The model efficacy in predicting temperature-related issues and detecting change points with high accuracy is verified by extensive runs in a laboratory scale plant. …”
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Multiscale Modeling of Meandering Fluvial Reservoir Architecture Based on Multiple-Point Geostatistics: A Case Study of the Minghuazhen Formation, Yangerzhuang Oilfield, Bohai Bay... by Jia Li, Chengyan Lin, Xianguo Zhang, Chunmei Dong, Yannan Wei, Wenyan Ning, Changcheng Han, Wei Guo

“…Model verification suggests this workflow can accurately realize the multiscale stochastic simulation of channels, point bars, and lateral accretion layers of meandering fluvial reservoirs. …”
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Presentation of a Novel Method for Prediction of Traffic with Climate Condition Based on Ensemble Learning of Neural Architecture Search (NAS) and Linear Regression by Javad Artin, Amin Valizadeh, Mohsen Ahmadi, Sathish A. P. Kumar, Abbas Sharifi

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A Study on Predicting Key Times in the Takeout System’s Order Fulfillment Process by Dongyi Hu, Wei Deng, Zilong Jiang, Yong Shi

“…Their behaviors involve multiple key time points, and accurately predicting these critical moments in advance is essential for enhancing both user retention and operational efficiency on such platforms. …”
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Kinematic Integration Network With Enhanced Temporal Intelligence and Quality-Driven Attention for Precise Joint Angle Prediction in Exoskeleton-Based Gait Analysis by Lyes Saad Saoud, Irfan Hussain

“…Exoskeleton robots offer transformative potential in aiding the rehabilitation of patients with lower limb motor dysfunction, where precise and real-time prediction of knee joint angles is critical. Despite advances in deep learning for motion prediction, existing models struggle with balancing accuracy and real-time performance, particularly in wearable applications. …”
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Explosion resistance evaluation and damage prediction of middle partition walls in prefabricated frame tunnels by Zhen Huang, Yuzhu Zhou, Ziming Xiong, Hao Lu, Minqian Sun, Maojiang Qin

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The Fatigue Life Prediction of Welded Joints in Orthotropic Steel Bridge Decks Considering Weld-Induced Residual Stress and Its Relaxation Under Vehicle Loads by Wen Zhong, Youliang Ding, Yongsheng Song, Sumei Liu, Mengyao Xu, Xin Wang

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Advancing Neurodegenerative Disease Management: Technical, Ethical, and Regulatory Insights from the NeuroPredict Platform by Marilena Ianculescu, Lidia Băjenaru, Ana-Mihaela Vasilevschi, Maria Gheorghe-Moisii, Cristina-Gabriela Gheorghe

“…Machine learning algorithms process these data flows to find patterns that point out disease evolution. This paper covers the design and architecture of the NeuroPredict platform, stressing the ethical and regulatory requirements that guide its development. …”
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Algorithm profiling for architectures with dataflow accelerators by Nenad Korolija, Veljko Milutinović, Borko Furht

“…However, dataflow hardware runs typically at an order of magnitude lower frequencies compared to the control-flow processor. From a programmer’s point of view, programming dataflow architectures is considerably harder than programming control-flow architectures. …”
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