Targeted K‐Edge Nanoprobes From Praseodymium and Hafnium for Ratiometric Tracking of Dual Biomarkers using Spectral Photon Counting CT by Nivetha Gunaseelan, Parikshit Moitra, Pranay Saha, Teresa Aditya, Mahdieh Moghiseh, Kevin Jonker, Steven Gieseg, Anthony Butler, Fadia Kamal, Dipanjan Pan

“…Abstract Utilizing metal nanoprobes with unique K‐edge identities to visualize complementary biological activities simultaneously can provide valuable information about complex biological processes. This study describes the design and preparation of an innovative pair of K‐edge metal nanoprobes and demonstrates the feasibility of their simultaneous quantitative detection using spectral photon‐counting computed tomography (SPCCT). …”
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Classifying breast cancer and fibroadenoma tissue biopsies from paraffined stain-free slides by fractal biomarkers in Fourier Ptychographic Microscopy by Vittorio Bianco, Marika Valentino, Daniele Pirone, Lisa Miccio, Pasquale Memmolo, Valentina Brancato, Luigi Coppola, Giovanni Smaldone, Massimiliano D’Aiuto, Gennaro Mossetti, Marco Salvatore, Pietro Ferraro

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MediScan: A Framework of U-Health and Prognostic AI Assessment on Medical Imaging by Sibtain Syed, Rehan Ahmed, Arshad Iqbal, Naveed Ahmad, Mohammed Ali Alshara

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Improving brain tumor classification: An approach integrating pre-trained CNN models and machine learning algorithms by Mohamed R. Shoaib, Jun Zhao, Heba M. Emara, Ahmed S. Mubarak, Osama A. Omer, Fathi E. Abd El-Samie, Hamada Esmaiel

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Explainable Deep Learning for COVID-19 Vaccine Sentiment in Arabic Tweets Using Multi-Self-Attention BiLSTM with XLNet by Asmaa Hashem Sweidan, Nashwa El-Bendary, Shereen A. Taie, Amira M. Idrees, Esraa Elhariri

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DeB3RTa: A Transformer-Based Model for the Portuguese Financial Domain by Higo Pires, Leonardo Paucar, Joao Paulo Carvalho

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A simplified approach for efficiency analysis of machine learning algorithms by Muthuramalingam Sivakumar, Sudhaman Parthasarathy, Thiyagarajan Padmapriya

“…This article presents a comprehensive framework for evaluating ML algorithm efficiency by incorporating metrics, such as training time, prediction time, memory usage, and computational resource utilization. The proposed methodology involves a multistep process: collecting raw metrics, normalizing them, applying the Analytic Hierarchy Process (AHP) to determine weights, and computing a composite efficiency score. …”
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PSOOptimizedFast Segmentation Algorithm for 3D Otsu Forest Canopy Image by ZHU Liang-kuan, SHAO Si-xie, JING Wei-peng, LIU Liang

“…Forest canopy image segmentation is a key step to forest canopy parameters using digital image processing methods According to the characteristics of forest canopy fisheye images with complex background and high resolution, this paper proposed a PSOoptimized forest canopy image decomposition Otsu method 3D segmentation algorithm In this method, the 3D OTSU was decomposed, which reduced the computing time and storage space, and the PSO algorithm was adopted to optimize the twodimensional Otsu to obtain the threshold process Experimental results showed that the algorithm proposed in this paper can quickly and accurately segment the fisheye images of forest canopy, especially in the details of treetops The proposed method can provide a technical support for forest canopy parameters measurement…”
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CQL-GNN: Coupled question-label graph neural networks for multi-label educational question classification by Liwei Gao, Luojia Wang

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Decision-Making Model for Reliable Electronic Component Manufacturing in a Blockchain Environment by Sung Yong An, Guy Ngayo, Seng-Phil Hong

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Beyond Classical AI: Detecting Fake News with Hybrid Quantum Neural Networks by Volkan Altıntaş

“…The model integrates classical fully connected neural layers with a parameterized quantum circuit, enabling the processing of textual data within both classical and quantum computational domains. …”
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Preprocessing of Aspect-based English Telugu Code Mixed Sentiment Analysis by Arun Kodirekka, Ayyagari Srinagesh

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EVALUATION OF SUBSOIL MASSIF STABILITY TAKING INTO ACCOUNT THE IRREGULARITY OF CONSTITUENT ROCKS ON THE BASIS OF A RANDOM SIZE AND FUNCTION MODEL by M. O. Allaev

“…This article considers issues involved in the development and continued improvement of computing methods for the study of the causes of landslides. …”
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Security, QoS and energy aware optimization of cloud-edge data centers using game theory and homomorphic encryption: Modeling and formal verification by Mbarek Marwan, Abdelkarim Ait Temghart, Said Ouhmi, Mohamed Lazaar

“…Privacy and efficient data processing are crucial research areas in the field of outsourcing computing. …”
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Group feature calibration for sound event detection by Yanzhen Ren, Wuyang Liu, Chenyu Liu, Tingting Zhu

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Encryption of sensor data using the Lorentz attractor in embedded systems by Akbota Kulzhanova, Sholpan Jomartova, Talgat Mazakov

“…The algorithm has demonstrated efficiency in processing text arrays and sensory data, making it suitable for use in smart cities, medical devices, and industrial networks. …”
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MSRP-TODNet: a multi-scale reinforced region wise analyser for tiny object detection by Thulasi Bikku, K. P. N. V. Satya Sree, Srinivasarao Thota, Malligunta Kiran Kumar, P. Shanmugasundaram

“…These are processed by the Enhanced Feature Pyramid Network (EFPN), which merges them into a single feature map. …”
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Minimizing Delay in UAV-Aided Federated Learning for IoT Applications With Straggling Devices by Mudassar Liaq, Waleed Ejaz

“…In this paper, we propose a UAV-aided FL framework that utilizes the computation capacity of UAV-MEC to process some portion of the datasets from the straggling devices (devices which are unable to process their dataset in reasonable time and are lagging, increasing delay in the whole system). …”
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THE FEATURES OF TRAINING OF TEACHERS AND STUDENTS TO THE USE OF INFORMATION TECHNOLOGIES TRAINING OF MATHEMATICS IN HIGHER EDUCATIONAL ESTABLISHMENTS by Y. I. Sinko

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Natural Language Understanding: Methodological Conceptualization by Vitalii Shymko

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