Measurement of Principal Modes in Few-Mode Fibers by S² Method by Zixiang Di, Zhiqun Yang, Yaping Liu, Guanju Peng, Lin Zhang, Guifang Li

“…Using principal modes (PMs) can avoid the inter-mode crosstalk in fiber-optic communication and reduce the complexity of digital signal processing. In this paper, a new detection method for PMs based on spatially and spectrally resolved imaging (S²) is used to recover their intensity distributions and inter-mode dispersion parameters. …”
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Potential use of saliva infrared spectra and machine learning for a minimally invasive screening test for congenital syphilis in infants by Deise Cristina Dal’Ongaro, Cicero Cena, Bruno Spolon Marangoni, Daniele A. Soares-Marangoni

“…Abstract Congenital syphilis is a global public health issue, and its diagnostic complexity poses a challenge to early treatment. Fourier Transform Infrared Spectroscopy (FTIR) is a promising technological tool that facilitates the detection and diagnosis of various diseases by providing information on the biochemical composition of biofluids, including saliva. …”
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Large Language Models Meet Graph Neural Networks: A Perspective of Graph Mining by Yuxin You, Zhen Liu, Xiangchao Wen, Yongtao Zhang, Wei Ai

“…Within this framework, we reveal the capabilities of LLMs in enhancing graph feature extraction as well as improving the effectiveness of downstream tasks such as node classification, link prediction, and community detection. Although LLMs have demonstrated their great potential in handling graph-structured data, their high computational requirements and complexity remain challenges. …”
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A simple validation and screening method for CRISPR/Cas9-mediated gene editing in mouse embryos to facilitate genetically modified mice production. by Dawid Winiarczyk, Hossein Khodadadi, Paweł Leszczyński, Hiroaki Taniguchi

“…We propose herein an evaluation method (cleavage assay - CA) for CRISPR/Cas9-mediated gene editing in preimplantation mouse embryos that allows us to detect mutants efficiently and later on initiate in vivo production without the extensive number of samples needing to be sent for Sanger sequencing and animal usage. …”
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An Effective Algorithm for Collision Resolution in Security Policy Rules by Sergey V. Morzhov, Valeriy A. Sokolov

“…In addition, the authors present a new efficient algorithm for detecting and resolving collisions in firewall rules by the example of the Floodlight SDN controller.…”
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A Resilient Deep Learning Approach for State Estimation in Distribution Grids With Distributed Generation by Ronald Kfouri, Harag Margossian

“…Results demonstrate that our method efficiently solves the DSSE problem—which cannot be solved using conventional methods—and detects and mitigates bad data, further enhancing the reliability of the state estimation results.…”
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Performance Comparison of Data Reduction Techniques for Wireless Multimedia Sensor Network Applications by Pinar Sarisaray-Boluk, Kemal Akkaya

“…The experiment results indicated that the most energy-efficient BS algorithm could also provide the best quality in terms of the foreground detected. …”
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Red-KPLS Feature Reduction with 1D-ResNet50: Deep Learning Approach for Multiclass Alzheimer’s Staging by Syrine Neffati, Ameni Filali, Kawther Mekki, Kais Bouzrara

“…However, the complexity of neuroimaging data presents significant obstacles to accurate classification. …”
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An Optimization Algorithm for Forward-Scatter Radar Network Node Deployment Based on BFGS and Improved NSGA-II by Yuqing Zheng, Xiaofeng Ai, Zhiming Xu, Jing Wu, Feng Zhao

“…A multi-objective optimization model was subsequently established with the objective functions of minimizing node cost and maximizing spatial detection area. Second, a method based on the Broyden–Fletcher–Goldfarb–Shanno (BFGS) algorithm was introduced to obtain the sub-optimal solution of node cost, thereby reducing the computational complexity of the optimization process. …”
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KEDM: Knowledge-Embedded Diffusion Model for Infrared Image Destriping by Lingxiao Li, Xin Wang, Dan Huang, Yunan He, Zhuqiang Zhong, Qingling Xia

“…Specifically, LDM leverages a pretrained variational autoencoder (VAE) to transform the input image into latent feature space for efficient diffusion propagation, reducing computational complexity while preserving image restoration quality. …”
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An energy-balanced multi-sensor scheduling scheme for collaborative target tracking in wireless sensor networks by Pengcheng Fu, Hongying Tang, Yongbo Cheng, Baoqing Li, Hanwang Qian, Xiaobing Yuan

“…From simulation results, it is demonstrated that the proposed node scheduling scheme can not only maintain the preset tracking accuracy but also extend network lifespan with a low computation complexity.…”
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A comparison of statistical methods for deriving occupancy estimates from machine learning outputs by Lydia K. D. Katsis, Tessa A. Rhinehart, Elizabeth Dorgay, Emma E. Sanchez, Jake L. Snaddon, C. Patrick Doncaster, Justin Kitzes

“…The inability to determine stable parameter choices a priori, coupled with the increased computational complexity of several models (i.e. the detection-count and continuous-score models), limits the practical application of false-positive models. …”
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Quantifying variability associated with high-resolution respirometry in human permeabilized skeletal muscle fibers by Emily J. Ferguson, Justin Bureau, Tanner Stokes, Danielle Nyman, Joel Seigel, Shivam Gandhi, Luca J. Delfinis, Brendon J. Gurd, Christopher G.R. Perry, Chris McGlory

“…Mean average intra- and inter-biopsy CVs for maximal complex I+II-supported, ADP-stimulated mitochondrial respiration were 11.5 % and 9.7 %, respectively. …”
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Exploring sustainable strategies for mitigating microplastic contamination in soil, water, and the food chain: A comprehensive analysis by Udaratta Bhattacharjee, Kamal Narayan Baruah, Maulin P. Shah

“…Further, the article suggests a cost effective, efficient, and sustainable strategy to intercept MPs infiltration in the food chain and establish practical data applicability in real-life scenarios.…”
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Comparative analysis of innovative cooling systems for Li-ion cells using carbon-graphene coatings, metal foams, and 3D printing by Luigi Sequino, Bianca Maria Vaglieco

“…However, electric vehicles operate at high working temperatures, so designers must devote considerable effort to developing efficient cooling systems. The complexity of battery-cooling solutions varies with the application: city cars, trucks, and hyper-cars require increasingly sophisticated systems. …”
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Multi-modal action recognition via advanced image fusion techniques for cyber-physical systems by Zaiyong Shou, Daoyu Zhu

“…IntroductionThe increasing complexity of cyber-physical systems (CPS) demands robust and efficient action recognition frameworks capable of seamlessly integrating multi-modal data. …”
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Implementation of MF block in CNN for advanced REB fault diagnosis by M. Pandiyan, Narendiranath Babu T.

“…Furthermore, computational complexity analysis, including FLOPs estimation, was performed to assess real-time applicability. …”
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Empowering sentiment analysis in social media: a comprehensive approach to enhance the classification of abusive Tamil comments using transformer models by Malliga Subramanian, Sathishkumar Veerappampalayam Easwaramoorthy, Nandhini Subbarayan, Usha Moorthy

“…Of the models explored, the adapter-based mDeBERTa achieved the highest accuracy of 75.393%, validating the effectiveness of parameter-efficient transfer learning for abusive language detection in low-resource, code-mixed contexts.…”
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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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Ruminococcus flavefaciens 007C cellulosomes and cellulase consortium by Maša VODOVNIK

“…Ruminococcus flavefaciens is among the most important cellulolytic bacterial species in rumen and gastrointestinal tract of monogastric herbivorous animals. Its efficiency in degradation of (hemi)cellulosic substrates is associated with the production of remarkably intricate extracellular multienzyme complexes, named cellulosomes. …”
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