An Evidential Solar Irradiance Forecasting Method Using Multiple Sources of Information by Mohamed Mroueh, Moustapha Doumiati, Clovis Francis, Mohamed Machmoum

“…The proposed machine learning model is designed to effectively handle missing data and make optimal use of available information. …”
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Image Inpainting Algorithm Based on Structure-Guided Generative Adversarial Network by Li Zhao, Tongyang Zhu, Chuang Wang, Feng Tian, Hongge Yao

“…To address the challenges of image inpainting in scenarios with extensive or irregular missing regions—particularly detail oversmoothing, structural ambiguity, and textural incoherence—this paper proposes an Image Structure-Guided (ISG) framework that hierarchically integrates structural priors with semantic-aware texture synthesis. …”
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Effective Marine Monitoring with Multimodal Sensing and Improved Underwater Robotic Perception towards Environmental Protection and Smart Energy Transition by Hamidreza FARHADI TOLIE, REN Jinchang, Md Junayed HASAN, MA Ping, Somasundar KANNAN, LI Yinhe

“…Depth images from the stereo camera are enhanced using a Depth-Anything model, addressing underwater-specific issues like noise, missing regions, and light attenuation, achieving accurate depth maps for distances up to 1.2 meters underwater. …”
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An improved synergistic dual-layer feature selection algorithm with two type classifier for efficient intrusion detection in IoT environment by G Logeswari, K Thangaramya, M Selvi, J. Deepika Roselind

“…To tackle these challenges, an Intrusion Detection System (IDS) is specifically designed for IoT environments. This system integrates a multi-faceted approach to enhance security against emerging threats. …”
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Short-Term Telephone-Traffic Prediction of Power Grid Customer Service Based on Adaboost-CNN by QIN Hao, SU Liwei, WU Guangbin, JIANG Chongying, XU Zhipeng, KANG Feng, TAN Huochao, ZHANG Yongjun

“…An Adaboost algorithm is applied to integrate multiple CNN models, resulting in an Adaboost-CNN traffic prediction model. …”
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An Improved Hierarchical Optimization Framework for Walking Control of Underactuated Humanoid Robots Using Model Predictive Control and Whole Body Planner and Controller by Yuanji Liu, Haiming Mou, Hao Jiang, Qingdu Li, Jianwei Zhang

“…Finally, a position–velocity–torque (PVT) controller integrates feedforward torque commands with the desired trajectories for robust execution. …”
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BERT-Residual Quantum Language Model Inspired by ODE Multi-Step Method by Shaohui Liang, Yingkui Wang, Shuxin Chen

“…Therefore, how to effectively integrate the quantum-inspired language model and the pre-trained model, and make them function under the fine-tuning paradigm of the pre-trained model has become a key issue for the further development of the quantum-inspired language model. …”
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A Thorough Comparative Analysis of PI and Sliding Mode Controllers in Permanent Magnet Synchronous Motor Drive Based on Optimization Algorithms by Fatemeh Khorsand, Reza Shahnazi, Esmael Fallah

“…In this paper, the speed tracking for permanent magnet synchronous motor (PMSM) in field oriented control (FOC) method is investigated using linear proportional-integral (PI) controller, sliding mode controller (SMC) and its advanced counterparts. …”
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An innovative hybrid model combining informer and K‐Means clustering methods for invisible multisite solar power estimation by Quoc‐Thang Phan, Yuan‐Kang Wu, Quoc‐Dung Phan

“…The proposed framework integrates Missforest, that is, a robust tool for missing data imputation, with a hybrid application of K‐Means, Pearson Correlation Coefficient, and Principal Component Analysis, for the precise selection of representative PV sites. …”
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A systematic review of mediation analysis frameworks in studies examining the determinants of cardiometabolic outcomes in people living with HIV by Peter Vanes Ebasone, Nasheeta Peer, Anastase Dzudie, Merveille Foaleng, Johney Melpsa, Andre Pascal Kengne

“…However, inconsistencies and gaps in reporting were noted, particularly in handling missing data, detailing identifiability assumptions, and the use of sensitivity analyses. …”
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Deep consensus semantic aware network for partial multi-view incomplete multi-label classification by Bo Shao, Yang Xu

“…However, due to overlooking incomplete views and missing labels caused by data collection limitations and unreliable annotations, many existing methods have difficulty in extracting consensus semantic information from diverse data sources. …”
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Air quality prediction using stacked bi- long short-term memory and convolutional neural network in India by S Karkuzhali, Thendral Puyalnithi, R Nirmalan

“…Through meticulous preprocessing - encompassing missing value handling, normalization, and temporal sequencing - the dataset is prepared for the Stacked Bi-LSTM and CNN hybrid model. …”
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Fostering college students’ mental well-being: the impact of social networking site utilization on emotion management and regulation by Yuehua Han, Zhifen Xu

“…Abstract With the widespread proliferation of the Internet, social networking sites have increasingly become integrated into the daily lives of university students, leading to a growing reliance on these platforms. …”
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Machine learning prediction of cancer cell sensitivity to drugs based on genomic and chemical properties. by Michael P Menden, Francesco Iorio, Mathew Garnett, Ultan McDermott, Cyril H Benes, Pedro J Ballester, Julio Saez-Rodriguez

“…Our in silico models can be used to optimise the experimental design of drug-cell screenings by estimating a large proportion of missing IC₅₀ values rather than experimentally measuring them. …”
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Spatiotemporal analysis of mangroves using median composites and convolutional neural network by Kathiroli R, Madhumitha P S, Achyut Prasad D C, Sandhiya S

“…The median composite technique reconstructs missing or obscured information by aggregating temporal pixel statistics. …”
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Improving Survey Data Interpretation: A Novel Approach to Analyze Single-Item Ordinal Responses with Non-Response Categories by Ewa Roszkowska

“…This study introduces BS-TOSIE (Belief Structure-Based TOPSIS for Survey Item Evaluation), a novel method that preserves and integrates all response types, including ambiguous ones. …”
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BlindFG: Learning Contextual Fishing Trajectories for Unreported Fishing Gear Classification by Changha Lee, Chan-Hyun Youn

“…In this paper, we propose BlindFG, a novel framework for unreported fishing gear classification that leverages a fishing-conditioned latent space to overcome the limitations imposed by AIS-off periods. BlindFG integrates a Fishing-Conditioned Generative Model (FCGen) with a Fishing Context Sommelier (FCSom) to both reconstruct missing trajectory data and classify vessel fishing types under partial AIS availability. …”
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Deep learning time-series modeling for assessing land subsidence under reduced groundwater use by Chih-Yu Liu, Cheng-Yu Ku, Chuen‑Fa Ni

“…A long short-term memory (LSTM) neural network is trained to reconstruct missing subsidence records and forecast subsidence trends, while an artificial neural network links well electricity usage to groundwater level fluctuations. …”
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Superselective embolic particle guidance in vessel networks via shape-adaptive acoustic manipulation by Yucheng Luo, Qiu Yin, Keke Chen, Zhaoyu Deng, Xiaozhou Liu, Yinning Zhou, Benpeng Zhu, Wenming Zhang, Zhichao Ma

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Terror films: The socio-cultural reconstruction of trauma in contemporary Israeli cinema by Yael Ben-Moshe, Tobias Ebbrecht-Hartmann

“…The public discourse in Israel regarding events such as the Holocaust, war, or terror attacks mostly failed to embrace the trauma caused by such events, and to integrate their effects in the collective memory. According to trauma theoreticians, the location of trauma in the discourse is related to the character of trauma as a non-narratable memory, since personal trauma exist in the void, thus marking a missing memory. …”
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