Assessing Functional Connectivity Dynamics During Cognitive Tasks Involving the Dorsal Stream by Huifang E. Wang, Jorge Gonzalez-Martinez, Viktor Jirsa, Patrick Chauvel, F.-Xavier Alario, Catherine Liegeois-Chauvel

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TSTBench: A Comprehensive Benchmark for Text Style Transfer by Yifei Xie, Jiaping Gui, Zhengping Che, Leqian Zhu, Yahao Hu, Zhisong Pan

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A Communication-Efficient Distributed Matrix Multiplication Scheme with Privacy, Security, and Resiliency by Tao Wang, Zhiping Shi, Juan Yang, Sha Liu

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On the Effects of Viscosity on the Shock Waves for a Hydrodynamical Case—Part I: Basic Mechanism by Huseyin Cavus

“…The algorithm concentrated on the compression rate, the entropy change, pressures, and Mach number ratios across the shock wave. …”
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A Fast and Efficient Adaptive Threshold Rate Control Scheme for Remote Sensing Images by Xiao Chen, Xiaoqing Xu

“…In the present study, an improved rate control algorithm for remote sensing images is proposed. The required coded blocks are sorted downward according to their numbers of bit planes prior to entropy coding. …”
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Efficient Chlorophyll Prediction and Sampling in the Sea: A Real-Time Approach With UCB-Based Path Planning by Perihan Karakose, Cafer Bal

“…In the second phase of the study, an exhaustive search algorithm is combined with reward functions like Upper Confidence Bound (UCB), entropy, and variance reduction. …”
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Rotor Location During Atrial Fibrillation: A Framework Based on Data Fusion and Information Quality by Miguel A. Becerra, Diego H. Peluffo-Ordoñez, Johana Vela, Cristian Mejía, Juan P. Ugarte, Catalina Tobón

“…The signals were then preprocessed, and five statistical features (sample entropy, approximate entropy, Shannon entropy, mean amplitude, and standard deviation) were extracted to generate rotor location maps using a wavelet fusion technique. …”
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Combined CNN-BiLSTM-Att tourism flow prediction based on VMD-MWPE decomposition reconstruction by Maomao Luo, Danhong Chen, Xinxing Hou, Kang Luo, Tao Wang

“…Finally, the CNN-BiLSTM prediction model, incorporating an attention mechanism and optimized using a genetic algorithm, was applied to generate the final prediction results. …”
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Tree networks of real-world data: Analysis of efficiency and spatiotemporal scales by Davide Cipollini, Lambert Schomaker

“…We resolve the network properties over multiple phase transitions and across a continuity of scales, using the von Neumann entropy, its generalized susceptibility, and the recent definition of thermodynamic-like quantities, such as work, heat, and efficiency. …”
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Detecting Anomalies in Sequences of Short Text Using Iterative Language Models by Cynthia Freeman, Ian Beaver, Abdullah Mueen

“…We introduce a technique for detecting anomalies in sequences of short textual data by adaptively and iteratively learning low perplexity language models. Our algorithm defines a short textual item as anomalous when its cross-entropy exceeds the upper confidence interval of a trained additive regression model. …”
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Optimized exposer region-based modified adaptive histogram equalization method for contrast enhancement in CXR imaging by Shivam Gangwar, Reeta Devi, Nor Ashidi Mat Isa

“…Each region undergoes adaptive contrast enhancement via a novel weighted probability density function (PDF) and power-law transformation to ensure balanced enhancement across different exposure levels. The PSO algorithm is then employed to optimize power-law parameters, further refining contrast enhancement and illumination uniformity while maintaining the natural appearance of medical images. …”
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Dynamic Placement of Pinching Antennas for Multicast MU-MISO Downlinks by Jung-Chieh Chen, Po-Ching Wu, Kai-Kit Wong

“…For each problem, we develop a probability-learning algorithm within a cross-entropy optimization (CEO) framework, iteratively refining a parameterized sampling distribution via closed-form updates. …”
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A novel network with enhanced edge information for left atrium segmentation from LGE-MRI by Ze Zhang, Zhen Wang, Xiqian Wang, Kuanquan Wang, Yongfeng Yuan, Qince Li

“…Compared with other state-of-the-art algorithms, the proposed algorithm demonstrated a significant improvement with an average symmetric surface distance of 0.684 mm and achieved a commendable Dice coefficient of 0.924, implicating the effectiveness of enhancing edge information.DiscussionThe method offers a practical framework for precise LA localization and segmentation, particularly strengthening the algorithm’s effectiveness in improving segmentation outcomes for irregular protrusions and discrete multiple targets. …”
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ecochange: An R‐package to derive ecosystem change indicators from freely available earth observation products by Wilson Lara, Maria C. Londoño, Ivan Gonzalez, Victor H. Gutierrez‐Velez

“…Its functionality is described with an example workflow to calculate ecosystem‐class areas and conditional entropy across an area of interest contained in the package documentation. …”
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Multi-objective optimization of residential energy-saving design based on fuzzy multi-criteria decision-making behavior model by Suzhen Pei, Gaoxiang Chen, Jian Yao, Yichen Dang

“…This study introduces a multi-objective optimization framework based on a Fuzzy Multi-Criteria Decision-Making (FMCDM) behavioral model. The NSGA-II algorithm is applied to optimize building envelope configurations, targeting three objectives: minimizing per-unit-area energy consumption, reducing energy disparities across residential units, and lowering annual discomfort hours. …”
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Optimizing Intermodal Port–Inland Hub Systems in Spain: A Capacitated Multiple-Allocation Model for Strategic and Sustainable Freight Planning by José Moyano Retamero, Alberto Camarero Orive

“…The most efficient configuration involved 300 generations, 150 individuals, a crossover rate of 0.85, and a mutation rate of 0.40. The algorithm integrates guided mutation, elitist reinsertion, and local search on the top 15% of individuals. …”
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Integrated pixel-level crack detection and quantification using an ensemble of advanced U-Net architectures by Rakshitha R, Srinath S, N Vinay Kumar, Rashmi S, Poornima B V

“…Transformer-based models like TransUNet and Swin-Unet use self-attention mechanisms to capture both local and global spatial relationships, enhancing robustness across diverse crack patterns. A key contribution of this study is the evaluation of loss functions, including Binary Cross-Entropy (BCE) Loss, Dice Loss, and Binary Focal Loss. …”
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AIpollen: An Analytic Website for Pollen Identification Through Convolutional Neural Networks by Xingchen Yu, Jiawen Zhao, Zhenxiu Xu, Junrong Wei, Qi Wang, Feng Shen, Xiaozeng Yang, Zhonglong Guo

“…For the optimization algorithm, we opted for the Adam optimizer and utilized the cross-entropy loss function. …”
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Comparative Analysis of Deep Learning Models for Intrusion Detection in IoT Networks by Abdullah Waqas, Sultan Daud Khan, Zaib Ullah, Mohib Ullah, Habib Ullah

“…This study addresses the problem of detecting intrusions in IoT environments by evaluating the performance of deep learning (DL) models under different data and algorithmic conditions. We conducted a comparative analysis of three widely used DL models—Convolutional Neural Networks (CNNs), Long Short-Term Memory (LSTM), and Bidirectional LSTM (biLSTM)—across four benchmark IoT intrusion detection datasets: BoTIoT, CiCIoT, ToNIoT, and WUSTL-IIoT-2021. …”
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A robust method to simultaneously place sensors and calibrate parameters for urban drainage pipe system models using Bayesian decision theory by Yuan Huang, Junyi Xiong, Jiangjiang Zhang, Feifei Zheng, Yiran Ji, Hoshin Gupta

“…The UDM is sequentially calibrated using an ensemble smoother algorithm with observation data collected from these strategically placed sensors. …”
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