Anomaly Detection Algorithms for Real-Time Log Data Analysis at Scale by Andras Horvath, Andras Olah, Attila Pinter, Balint Siklosi, Gergely Lukacs, Istvan Z. Reguly, Kalman Tornai, Tamas Zsedrovits, Zoltan Mathe

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Controlling Cable Driven Parallel Robots Operations—Deep Reinforcement Learning Approach by Muhammad Kamran Joyo, Abdulmajeed M. Alenezi, Wenfu Xu, Mohamad A. Alawad, Muhmmad Tayyab Yaqoob, Noor Maricar, Sheroz Khan

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Efficient Text Encoders for Labor Market Analysis by Jens-Joris Decorte, Jeroen van Hautte, Chris Develder, Thomas Demeester

“…Labor market analysis relies on extracting insights from job advertisements, which provide valuable yet unstructured information on job titles and corresponding skill requirements. …”
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Point-Cloud Instance Segmentation for Spinning Laser Sensors by Alvaro Casado-Coscolla, Carlos Sanchez-Belenguer, Erik Wolfart, Vitor Sequeira

“…Since the sensors natively provide their measurements in a 2D grid, we directly use state-of-the-art models designed for visual information for the segmentation task and then exploit the range information to ensure 3D accuracy. …”
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Remote Sensing Image Semantic Segmentation Sample Generation Using a Decoupled Latent Diffusion Framework by Yue Xu, Honghao Liu, Ruixia Yang, Zhengchao Chen

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xLSTMKT: xLSTM for Knowledge Tracing by Yasser Aderghal, Hakim Hafidi, Abdellatif El Ghazi

“…In recent years, KT models based on Long Short-Term Memory (LSTM) and Transformer architectures have achieved significant performance improvements, surpassing traditional Bayesian approaches. …”
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An inherently interpretable AI model improves screening speed and accuracy for early diabetic retinopathy. by Kerol Djoumessi, Ziwei Huang, Laura Kühlewein, Annekatrin Rickmann, Natalia Simon, Lisa M Koch, Philipp Berens

“…We developed and evaluated an inherently interpretable deep learning model, which explicitly models the local evidence of DR as part of its network architecture, for clinical decision support in early DR screening. …”
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A Two-Dimensional Cell Model of Phases Transport in a Fluidized Bed Column: Development and Validation by Andrey Mitrofanov

“…The numerical experiments performed in the study showed the qualitative consistency of the proposed model. …”
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Leveraging modality‐specific and shared features for RGB‐T salient object detection by Shuo Wang, Gang Yang, Qiqi Xu, Xun Dai

“…Extensive experiments on three public datasets show that the MSTNet outperforms 14 state‐of‐the‐art methods, demonstrating that this method can extract and utilise the multi‐modality information more adequately and extract more complete and rich features, thus improving the model's performance. …”
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Geometry‐Enhanced Implicit Function for Detailed Clothed Human Reconstruction With RGB‐D Input by Pengpeng Liu, Zhi Zeng, Qisheng Wang, Min Chen, Guixuan Zhang

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A Coherent Approach-Based Fine-Tuning of Segment Anything Model Plus Watershed Algorithm for Instance Segmentation of Mitochondria in Electron Microscopy Images by Zahra Faska, Lahbib Khrissi, Imadeddine Mountasser, Khalid Haddouch, Nabil El Akkad, Samah Alshathri, Walid El-Shafai

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ALGORITHMIC PROCEDURES OF IDENTIFYING ADVERTISEMENT TEXTS IN MASS MEDIA DISCOURSE by Mikhail V. Kamensky, Sergey N. Bredikhin

“…This proves the effectiveness of natural language processing systems in identifying messages with explicit and implicit advertisement content, determining the discursive type of media texts, and classifying them as either informative texts or advertisements.…”
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The missing link: Predicting connectomes from noisy and partially observed tract tracing data. by Max Hinne, Annet Meijers, Rembrandt Bakker, Paul H E Tiesinga, Morten Mørup, Marcel A J van Gerven

“…Finally, our probabilistic approach enables us to make explicit which connections are easy to predict and which prove difficult, allowing for informed follow-up studies.…”
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Hybrid A*-Guided Model Predictive Path Integral Control for Robust Navigation in Rough Terrains by Joonyeol Yang , Minhyeong Kang , Seulchan Lee, Sanghyun Kim

“…By integrating terrain-aware guidance through the Hybrid A* algorithm with the MPPI, the proposed methodology automates the selection of the appropriate mean control input and enhances control performance by explicitly incorporating terrain properties into the planning process. …”
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3D-SCUMamba: An Abdominal Tumor Segmentation Model by Juwita, Ghulam Mubashar Hassan, Amitava Datta

“…Existing deep learning models typically adopt encoder-decoder architectures integrating convolutional layers with global dependency modeling to capture broader contextual information around tumors. Capturing global dependencies is critical, as local information alone often inadequately distinguishes tumors, especially given their diverse sizes, complex shapes, and interference from imaging artifacts. …”
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An Association Rule Mining-Based Method for Revealing the Impact of Operational Sequence on Nuclear Power Plants Operating by Yuxuan He, Jian Song, Shaoke Shi, Haibo Lian, Jiangyang He, Ren Yu, Tete Liu, Bin Sun, Jiangtao Yuan, Yingbin Hu

“…The operations of the operators are important for nuclear safety, but conventional operating experience feedback and common data-driven methods make it difficult to explicitly find valuable information hidden in these operational sequences that can help the operator to provide advice at the operational level. …”
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Reinforcement-Learning-Based Trajectory Design and Phase-Shift Control in UAV-Mounted-RIS Communications by Tianjiao Sun, Sixing Yin, Li Deng, F. Richard Yu

“…Experimental results demonstrate that the proposed RL solutions are highly efficient in model training along with acceptable performance close to the benchmark, which relies on conventional optimization algorithms with the UT’s locations and channel parameters explicitly known beforehand.…”
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Multiscale Edge Enhancement and Progressive Change-Aware Network for Remote Sensing Change Detection by Yan Xing, Jiali Hu, Yunan Jia, Rui Huang

“…Specifically, we introduce an edge enhancement module (EEM) to capture the long-range dependency, explicitly emphasizing high-frequency feature, and strengthening edge information to improve the accuracy of change regions. …”
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The Scenarios for Sustainability of Vannamei (Litopenaeus vannamei) Aquaculture Through Environmental Management Accounting by Tiwi Nurjannati Utami, Mulyanto, Niken Hendrakusma Wardhani, Dwi Setijawati, Feny Iranawati, Tri Djoko Lelono, Ledhyane Ika Harlyan, Rizky Fadilla Agustin

“…There is increasing awareness of the importance of sustainability in aquaculture, however, research that explicitly integrates accounting with environmental information in decision-making remains relatively unexplored. …”
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Developing artificial intelligence tools for institutional review board pre-review: A pilot study on ChatGPT's accuracy and reproducibility. by Yasuko Fukataki, Wakako Hayashi, Naoki Nishimoto, Yoichi M Ito

“…We assessed the baseline performance of generative AI-Generative Pre-trained Transformer (GPT)-4 and GPT-4o-in analyzing clinical research protocols and informed consent forms (ICFs). …”
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