Image-tag-based indoor localization using end-to-end learning by Mohammed Alarfaj, Zhenqiang Su, Raymond Liu, Abdulaziz Al-Humam, Huaping Liu

“…The performance of the proposed scheme is evaluated via a set of experiments in a real setting and has achieved less than 20 cm of positioning errors.…”
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Interpretable Deep Learning Models for Arrhythmia Classification Based on ECG Signals Using PTB-X Dataset by Ahmed E. Mansour Atwa, El-Sayed Atlam, Ali Ahmed, Mohamed Ahmed Atwa, Elsaid Md. Abdelrahim, Ali I. Siam

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SB-Tree: A B+-Tree for In-Memory Time Series Databases With Segmented Block by Christine Euna Jung, Jaesang Hwang, Yedam Na, Haena Lee, Wook-Hee Kim

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FASTSeg3D: A Fast, Efficient, and Adaptive Ground Filtering Algorithm for 3D Point Clouds in Mobile Sensing Applications by Daniel Ayo Oladele, Elisha Didam Markus, Adnan M. Abu-Mahfouz

“…However, existing methods struggle with over-segmentation, under-segmentation, and computational inefficiency, particularly in dynamic or complex environments. …”
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Blockchain-Assisted Secure and Lightweight Authentication Scheme for Multi-Server Internet of Drones Environments by Sieun Ju, Hyewon Park, Seunghwan Son, Hyungpyo Kim, Youngho Park, Yohan Park

“…These issues are further compounded by the limited computational capabilities of IoT devices and the inherent vulnerabilities of wireless communication channels. …”
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Predicting drug protein interactions based on improved support vector data description in unbalanced data by Alireza Khorramfard, Jamshid Pirgazi, Ali Ghanbari Sorkhi

“…Introduction: Predicting drug-protein interactions is critical in drug discovery, but traditional laboratory methods are expensive and time-consuming. Computational approaches, especially those leveraging machine learning, are increasingly popular. …”
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Hybrid transfer learning and self-attention framework for robust MRI-based brain tumor classification by Soumyarashmi Panigrahi, Dibya Ranjan Das Adhikary, Binod Kumar Pattanayak

“…Leveraging features from the pre-trained DenseNet201 Convolutional Neural Networks (CNN) model and integrating a Transformer-based architecture, our approach overcomes challenges like computational intensity, detail detection, and noise sensitivity. …”
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Fraud Detection in Privacy Preserving Health Insurance System Using Blockchain Technology by Md. Mazharul Islam, Mubasshir Ahmed, Rajesh Palit, Mohammad Shahriar Rahman, Salekul Islam

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Enhanced Retrieval-Augmented Generation Using Low-Rank Adaptation by Yein Choi, Sungwoo Kim, Yipene Cedric Francois Bassole, Yunsick Sung

“…Specifically, our model reduced the number of trainable parameters by 13.6% and lowered computational costs by 18.7%. Performance evaluations using BLEU, CIDEr, and SPICE scores revealed a 4.36% increase in BLEU-4, a 6.83% improvement in CIDEr, and a 5.46% improved in SPICE, confirming greater structural accuracy in regulatory text generation. …”
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SpaCCC: Large Language Model-Based Cell-Cell Communication Inference for Spatially Resolved Transcriptomic Data by Boya Ji, Xiaoqi Wang, Debin Qiao, Liwen Xu, Shaoliang Peng

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Centralized Measurement Level Fusion of GNSS and Inertial Sensors for Robust Positioning and Navigation by Mohamed F. Elkhalea, Hossam Hendy, Ahmed Kamel, Ashraf Abosekeen, Aboelmagd Noureldin

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A statistical approach to the use of control entropy identifies differences in constraints of gait in highly trained versus untrained runners by Rana D. Parshad, Stephen J. McGregor, Michael A. Busa, Joseph D. Skufca, Erik Bollt

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HYBRID WLS-KF APPROACH FOR REAL-TIME STATE ESTIMATION IN AUTOMATED DISTRIBUTION GRIDS by Abdulrafiu Yusuf, Olalekan Ogunbiyi, Lambe Mutalub Adesina, Bashiru Olalekan Ariyo

“…The performance of each method was evaluated in terms of estimation accuracy, computational efficiency, and robustness against bad data. …”
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Deep-m6Am: a deep learning model for identifying N6, 2′-O-Dimethyladenosine (m6Am) sites using hybrid features by Islam Uddin, Salman A. AlQahtani, Sumaiya Noor, Salman Khan

“…The performance of the proposed model was evaluated in comparison with traditional machine learning (ML) algorithms and existing models. …”
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ACU-Net: Attention-based convolutional U-Net model for segmenting brain tumors in fMRI images by Md Alamin Talukder, Md Abu Layek, Md Aslam Hossain, Md Aminul Islam, Mohammad Nur-e-Alam, Mohsin Kazi

“…Current techniques often struggle with capturing complex tumor features and are computationally demanding, limiting their clinical application. …”
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Innovative framework for fault detection and system resilience in hydropower operations using digital twins and deep learning by Jun Tan, Raoof Mohammed Radhi, Kimia Shirini, Sina Samadi Gharehveran, Zamen Parisooz, Mohsen Khosravi, Hossein Azarinfar

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Deep learning-based automatic diagnosis of rice leaf diseases using ensemble CNN models by Prameetha Pai, S. Amutha, Seema Patil, T. Shobha, Mustafa Basthikodi, B. M. Ahamed Shafeeq, Ananth Prabhu Gurpur

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Predicting Nottingham grade in breast cancer digital pathology using a foundation model by Jun Seo Kim, Jeong Hoon Lee, Yousung Yeon, Doyeon An, Seok Jun Kim, Myung-Giun Noh, Suehyun Lee

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Adaptive Transmission Rate Control for Decentralized Sensing Applications by Stefan Schuhback, Lars Wischhof, Jorg Ott

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Reinforcement Learning-Driven Hunter-Prey Algorithm Applied to 3D Underwater Sensor Network Coverage Optimization by Zibo Huang, Fangxiu Wang, Chen Su, Yi Wang, Hui Liu

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