LapEx: A new multimodal dataset for context recognition and practice assessment in laparoscopic surgery by Arthur Derathé, Fabian Reche, Sylvain Guy, Katia Charrière, Bertrand Trilling, Pierre Jannin, Alexandre Moreau-Gaudry, Bernard Gibaud, Sandrine Voros

“…Abstract In Surgical Data Science (SDS), there is an increasing demand for large, realistic annotated datasets to facilitate the development of machine learning techniques. However, in laparoscopic surgery, most publicly available datasets focus on low-granularity procedural annotations (such as phases or steps) and image segmentation of instruments or specific organs, often using animal models that lack clinical realism. …”
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A CNN-LSTM model for road surface recognition of electric balance vehicles by Feifei Yu, Yongxian Huang, Canyi Du, Feng Li, Yongkang Gong, Guoyan Chen

“…Through analysis, the classification accuracy of using continuous time series data as learning samples is higher than that of using a single time step signal. …”
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SLICES-PLUS: A crystal representation leveraging spatial symmetry by Baoning Wang, Zhiyuan Xu, Zhiyu Han, Qiwen Nie, Xi Chen, Hang Xiao, Gang Yan

“…Finally, we explore autoregressive generation towards multiple elastic properties in few-shot learning. Our research represents a significant step forward in the realm of computational materials discovery.…”
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Turkish Chest X-Ray Report Generation Model Using the Swin Enhanced Yield Transformer (Model-SEY) Framework by Murat Ucan, Buket Kaya, Mehmet Kaya

“…The proposed model is one of the first studies in the field of autonomous reporting using deep learning architectures specific to the Turkish language, representing an important step forward in this field. …”
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Defining students’ socioscientific issues classroom decision-making components and practice proficiencies by Jenny M. Dauer, Caitlin K. Kirby, Amanda E. Sorensen

“…This work represents a useful first step for defining decision making for science education research, and for learning designs in science classrooms.…”
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Developing a culture-based Indonesian language textbook for non-native speakers for academic purposes by Kastam Syamsi, Darmiyati Zuchdi, Ari Kusmiatun, Widyastuti Purbani, Aleeyah Masae

“…Language and culture could not be learned and taught separately. Therefore, a learning material based on culture should be considered for a meaningful instructional process. …”
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Clustering-based interactive image segmentation by B. A. Zalesky

“…In such cases, powerful neural network and other segmentation tools that require deep learning can not be used.Methods. An algorithm for interactive image segmentation is proposed, based on the analysis of the colors of areas selected interactively. …”
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Adaptive strategies of a medical school during Sudan’s armed conflict by Mohamed Hassan Taha, Nazik Elmalaika Obaid Seid Ahmed Husain, Wail Nuri Osman Mukhtar, Mohamed Elhassan Abdalla

“…FMUG’s integration of flexible learning, technology, and strategic partnerships enabled both immediate crisis response and long-term resilience. …”
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Improving the quality and reliability of clinical reviews of psychotropic PRN medicines in a large English mental health Trust by James Innes, Uju Ugochukwu, Julie Trenholm, Leo Boswell

“…Exploring the variation between wards in fully engaged and partially engaged groups of wards could be a next step for the Trust.…”
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Preceptors inspire students to be competent in nursing practice in a psychiatric public unit by Bhekithemba Vellem, Karien Jooste

“…Professionalism, respect and inclusivity were the defining characteristics of the welcoming learning atmosphere that preceptors provided. Student nurses praised the preceptors’ willingness to respond to questions, treat them like professionals and support their required learning opportunities. …”
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Fair ultrasound diagnosis via adversarial protected attribute aware perturbations on latent embeddings by Zikang Xu, Fenghe Tang, Quan Quan, Qingsong Yao, Qingpeng Kong, Jianrui Ding, Chunping Ning, S. Kevin Zhou

“…Abstract Deep learning techniques have significantly enhanced the convenience and precision of ultrasound image diagnosis, particularly in the crucial step of lesion segmentation. …”
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Unlocking Wheat Drought Tolerance: The Synergy of Omics Data and Computational Intelligence by Marlon‐Schylor Le Roux, Karl J. Kunert, Christopher A. Cullis, Anna‐Maria Botha

“…This understanding can be significantly advanced with the aid of computational intelligence, more often referred to as artificial intelligence (AI) models, especially those leveraging machine learning and deep learning tools. However, there is an imminent and continuous need for omics and AI integration. …”
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Adaptive Reuse Suggestions in Interior Architecture Education: A Registered Workshop in Ankara by Mine Sungur

“…The second stage, analysis, entails taking measurements of the building's interior and exterior as well as photographing and collecting written and visual records of it. The third step, the design phase, begins with the choice of a new function appropriate for the building's location and style in light of all available data and documentation. …”
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Robust Extrinsic Calibration for LiDAR-Camera Systems via Depth and Height Complementary Supervision Network by Chen Yaqing, Wang Huaming

“…Extrinsic calibration between cameras and LiDAR (Light Detection and Ranging) is a fundamental step for numerous autonomous driving applications, such as 3D object detection, lane detection, and trajectory planning. …”
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Enhancing prostate cancer segmentation in bpMRI: Integrating zonal awareness into attention-guided U-Net by Chao Wei, Zheng Liu, Yibo Zhang, Lianhui Fan

“…This research not only enhances the field of medical imaging for oncology but also underscores the potential of deep learning models to progress PCa diagnosis and personalized patient care.…”
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PerGOLD: Identification of offensive language in Persian tweets: leveraging crowdsourcing by Fatemeh Jafarinejad, Marziea Rahimi, Maryam Khodabakhsh, Seyedehfatemeh Karimi

“…Moreover, dataset labeling emerges as a crucial and fundamental step for training high-quality models, considering the increasing use of artificial intelligence and machine learning tools. …”
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Collaborative multiview time series modeling for vehicle maintenance demand prediction by Fanghua Chen, Deguang Shang, Gang Zhou, Ke Ye, Fujie Ren, Guofang Wu

“…To enhance the interaction between distinct time points and temporal dependencies, we developed a dependency-aware learning algorithm that effectively integrates and weighs the information and dependencies at each time step, thereby improving the model’s ability to capture the complex relationships among maintenance projects over time. …”
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A Continuous Space Path Planning Method for Unmanned Aerial Vehicle Based on Particle Swarm Optimization-Enhanced Deep Q-Network by Le Han, Hui Zhang, Nan An

“…Furthermore, we incorporate a mechanism into the base prioritized experience replay (PER) and N-step updates, which combines the current temporal difference error (TD-error) with historical priorities and includes a policy entropy penalty term, thereby enhancing DQN’s ability to learn long-term dependencies. …”
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On the Prediction and Forecasting of PMs and Air Pollution: An Application of Deep Hybrid AI-Based Models by Youness El Mghouchi, Mihaela Tinca Udristioiu

“…The methodology consists of three main phases: (i) data preprocessing, including anomaly detection and missing value handling; (ii) exploratory analysis to identify trends and correlations between PM concentrations (PMs) and predictor variables; and (iii) model development using 23 machine learning and deep learning algorithms, enhanced by 50 feature selection techniques. …”
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Evaluating statistical consistency for the ocean component of earth system models using physics informed convolutional autoencoder by Yangyang Yu, Shaoqing Zhang, Haohuan Fu, Dexun Chen, Yishuai Jin, Yang Gao, Xiaopei Lin, Zhao Liu, Xiaojing Lv, Yunlong Fei, Kaidi Wang

“…Abstract Model verification is a crucial step in the development and optimization of Earth system models (ESMs). …”
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