PAPR Reduction in DCO-OFDM Visible Light Communication Systems Using Optimized Odd and Even Sequences Combination by Wei-Wen Hu

“…Simulation results show that the proposed scheme can achieve comparable PAPR reduction performance with the conventional selected mapping (CSLM) scheme with random and chaotic sequences, but at a considerably low computational complexity. Moreover, the proposed blind SI detection scheme provides almost the same bit error rate (BER) performance as that of the CSLM scheme with a perfect SI detection and symmetric selected mapping for a DCO-OFDM VLC system with 1024 subcarriers and 16-QAM. …”
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A fair dividend approach for aggregating wearable sensor data to improve electronic health records. by Turki M Alanazi, Noha Alduaiji, Chahira Lhioui, Rim Hamdaoui, Somia Asklany, Monia Hamdi, Ali Elrashidi, Ghulam Abbas

“…The sequence determination uses balanced linear scheduling, optimizing the structure of sensing operations and increasing WS input availability when interruptions from multiple sensors, thereby boosting operating efficiency. The proposed approach outperforms baseline methods in access time, computational complexity, data utilization, processing time, aggregation ratio, and error rate by 10.18%, 5.19%, 10.57%, 8.48%, and 10.42%, respectively. …”
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Transfer-Learning Approach for Enhanced Brain Tumor Classification in MRI Imaging by Amarnath Amarnath, Ali Al Bataineh, Jeremy A. Hansen

“…Results: Our findings indicate that these models can improve the accuracy of MRI analysis for brain tumor classification, with the Xception model achieving the highest performance with a test F1 score of 0.9817, followed by EfficientNetV2-S with a test F1 score of 0.9629. Conclusions: Implementing pre-trained deep learning models can enhance MRI accuracy for detecting brain tumors.…”
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ResTreeNet: A Height-Aware LiDAR Tree Classification Model With Explainable AI for Forestry Applications by Asrat Kaleab Taye, Jeong-Mook Park, Hyung-Ju Cho, Jin-Taek Kang, Yeon-Ok Seo

“…To address these critical limitations, we propose ResTreeNet, an efficient and lightweight deep learning model designed explicitly for tree classification using terrestrial LiDAR point clouds. …”
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Biotransformation of Acetaminophen by <i>Ganoderma parvulum</i> Ligninolytic Enzymes Immobilized on Chitosan Microspheres by María Alejandra Flórez-Restrepo, Xiomara López-Legarda, Magdalena de Jesús Rostro-Alanis, Roberto Parra-Saldívar, Freimar Segura-Sánchez

“…Among these, acetaminophen (paracetamol) is one of the most frequently detected pharmaceutical pollutants in aquatic environments. …”
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Rethinking feature representation and attention mechanisms in intelligent recognition of leaf pests and diseases in wheat by Yuhan Zhang, Dongsheng Liu

“…RReNet captures key information more efficiently by focusing on complex pest and disease characteristics and fusing multi-semantic feature information. …”
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Micro- and Nano-Plastics in Drinking Water: Threat or Hype? Critical State-of-the-Art Analysis of Risks and Approaches by Andrea G. Capodaglio

“…MP decomposition generates smaller nanoplastics (NPs) with different properties, closer to engineered nanoparticles than to MP. Their detection is more complex and laborious than MP’s, and, as such, their fate and effects are still poorly studied. …”
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GCF-DeepLabv3+: An Improved Segmentation Network for Maize Straw Plot Classification by Yuanyuan Liu, Jiaxin Zhang, Yueyong Wang, Yang Luo, Pengxiang Sui, Ying Ren, Xiaodan Liu, Jun Wang

“…An improved GCF-DeepLabv3+ model was utilized for detecting straw coverage types. The model incorporates StarNet as its backbone, reducing parameter count and computational complexity. …”
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Overall architecture design of row/column scanning silicon-based focal plane switch array LiDAR transmitter system by Yu Wang, Yue Wang, Zeyang Zhang, Hang Cheng, Yuanhui Li, Guohui Yang, Kuang Zhang, Chunhui Wang

“…This architecture allows each optical path to control multiple grating couplers for simultaneous transmission, integrating both time-domain and spatial detection to enhance system detection efficiency and accuracy. …”
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Mapping the Global Public Health Intelligence Landscape, 2023 by Mrs Alba Mendez Brito, Mrs Romy Kerber, Dr Angela Fehr, Mrs Sarah Esquevin, Dr Andreas Jansen, Dr Carlos L Correa-Martínez

“…Introduction: Public health intelligence (PHI) is becoming increasingly crucial for early threat detection, leveraging efficient identification and information exchange. …”
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Highly customizable, ultrawide-temperature free-form flexible sensing electronic systems based on medium-entropy alloy paintings by Weiwei Li, Yingzhe Li, Manzhang Xu, Yilin Zhou, Ruoyan Miao, Kexin Wang, Yunqiang Cao, Yizhong Song, Siying Dang, Lu Zheng, Xuewen Wang, Wei Huang

“…Abstract High-performance flexible sensing electronics on complex surfaces operating across broad temperatures are critical for aerospace and industrial applications. …”
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Defect intelligent recognition of membrane product based on deep learning by Maonian Wu, Ling Li, Wei Peng, Tao Wu, Jinwei Yu, Bo Zheng, Shaojun Zhu

“…This enhances the recognition accuracy of bounding boxes, ensuring that the model maintains high detection accuracy even after complex scenarios. Moreover, the proposed methodology exhibits broad applicability across a wide spectrum of prevalent defect detection paradigms. …”
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A Novel Framework for Whole-Slide Pathological Image Classification Based on the Cascaded Attention Mechanism by Dehua Liu, Bin Hu

“…Automated models can rapidly and accurately process large datasets, revolutionizing tumor detection and classification. However, existing methods often rely on single attention mechanisms, failing to fully exploit the complexity of pathological images, especially in extracting critical features from whole-slide images. …”
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JET: Fast Estimation of Hierarchical Time Series Clustering by Phillip Wenig, Mathias Höfgen, Thorsten Papenbrock

“…In this paper, we propose JET, an unsupervised, highly efficient clustering algorithm for large numbers of variable-lengths time series. …”
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Optimised Extension of an Ultra-Low-Power RISC-V Processor to Support Lightweight Neural Network Models by Qiankun Liu, Sam Amiri

“…With the increasing demand for efficient deep learning models in resource-constrained environments, Binary Neural Networks (BNNs) have emerged as a promising solution due to their ability to significantly reduce computational complexity while maintaining accuracy. …”
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Text Removal for Trademark Images Based on Self-Prompting Mechanisms and Multi-Scale Texture Aggregation by Wenchao Zhou, Xiuhui Wang, Boxiu Zhou, Longwen Li

“…These mechanisms are capable of efficiently extracting multilevel features and multiscale textual information, which enhances the model’s stability and adaptability in complex scenarios. …”
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Far-field ammonia gas sensing at room temperature with graphene nanoplatelets-infused PEDOT:PSS transparent thin film by Vinod K Ganesan, Chun Hui Tan, Pei Song Chee, Jen Hahn Low, Soon Poh Lee, Eng Hock Lim

“…Widely used in various industrial applications, ammonia poses significant environmental and health risks, emphasizing the need for efficient monitoring. Although traditional gas sensing methods effective, they often constrained by high operating temperatures and complex electronic components, limiting their practicality. …”
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Resolving Non-Proportional Frequency Components in Rotating Machinery Signals Using Local Entropy Selection Scaling–Reassigning Chirplet Transform by Dapeng Quan, Yuli Niu, Zeming Zhao, Caiting He, Xiaoze Yang, Mingyang Li, Tianyang Wang, Lili Zhang, Limei Ma, Yong Zhao, Hongtao Wu

“…Under complex operating conditions, vibration signals from rotating machinery often exhibit non-stationary characteristics with non-proportional and closely spaced instantaneous frequency (IF) components. …”
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LncRNA of peripheral blood mononuclear cells: HYMAI acts as a potential diagnostic and therapeutic biomarker for female major depressive disorder by Tianyi Bu, Jiarun Yang, Jiawei Zhou, Yeran Liu, Kexin Qiao, Yan Wang, Jili Zhang, Erying Zhao, Boakye Kwame Owura, Xiaohui Qiu, Zhengxue Qiao, Yanjie Yang

“…IntroductionAs a common and complex mental disorder, major depressive disorder (MDD) has brought a huge burden and challenges globally. …”
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ETAFHrNet: A Transformer-Based Multi-Scale Network for Asymmetric Pavement Crack Segmentation by Chao Tan, Jiaqi Liu, Zhedong Zhao, Rufei Liu, Peng Tan, Aishu Yao, Shoudao Pan, Jingyi Dong

“…These findings demonstrate the effectiveness of interpretable, multi-scale attention architectures in complex object detection and image classification tasks, making our approach relevant for broader applications, such as autonomous driving, remote sensing, and smart infrastructure systems.…”
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