Unraveling relevant cross-waves pattern drifts in patient-hospital risk factors among hospitalized COVID-19 patients using explainable machine learning methods by Fernanda Cristina Barbosa Lana, Carolina Coimbra Marinho, Bruno Barbosa Miranda de Paiva, Lucas Rocha Valle, Guilherme Fonseca do Nascimento, Leonardo Chaves Dutra da Rocha, Marcelo Carneiro, Joanna d‘Arc Lyra Batista, Fernando Anschau, Pedro Gibson Paraiso, Frederico Bartolazzi, Christiane Corrêa Rodrigues Cimini, Alexandre Vargas Schwarzbold, Danyelle Romana Alves Rios, Marcos André Gonçalves, Milena Soriano Marcolino

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ADPO: Adaptive DRAM Controller for Performance Optimization by Zhuorui Liu, Yan Li, Xiaoyang Zeng

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A Temporal Attention-Based SARIMA-BiLSTM Residual Learning Model Tuned by Grey Wolf Optimizer for Parallel Urban Traffic Forecasting by Manas Kamal Das, Christopher Columbus Chinnappan, E. Elakiya

“…Furthermore, the entire pipeline is adapted for parallel execution to improve scalability and reduce computational latency, enabling faster processing of large-scale traffic data. …”
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Early crowd forecasting away from stations by geographically complemented regression using transit search and mobility logs by Soto Anno, Kota Tsubouchi, Masamichi Shimosaka

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Lightweight Deep Learning Model for Fire Classification in Tunnels by Shakhnoza Muksimova, Sabina Umirzakova, Jushkin Baltayev, Young-Im Cho

“…Deployment optimizations, such as quantization and layer fusion, ensure computational efficiency, achieving an average inference time of 12ms/frame, making it suitable for resource-constrained environments like IoT and edge devices. …”
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Metering Automation System 3.0 Base Version Based on Machine Learning by Sheng Li, Leping Zhang, Hang Dai, Lukun Zeng, Yuan Ai, Shuang Qi, Yuanzhai Cui

“…However, traditional machine learning methods and standalone deep learning architectures struggle to balance spatiotemporal feature extraction, computational efficiency, and deployment constraints for high-frequency multivariate metering data. …”
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Mixed photonic/electronic neural network based on microLED arrays by M Müller, R Kraneis, N Kälin, N von Malm, A Waag, C Werner

“…Activations are represented by patterns of incoherent light generated by microLED arrays. …”
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Medical Diagnostic Systems Using Artificial Intelligence (AI) Algorithms: Principles and Perspectives by Simarjeet Kaur, Jimmy Singla, Lewis Nkenyereye, Sudan Jha, Deepak Prashar, Gyanendra Prasad Joshi, Shaker El-Sappagh, Md. Saiful Islam, S. M. Riazul Islam

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Efficient Computation of the <italic>K</italic> Nearest Neighbors Query Using Incremental Radius on a <italic>k</italic>&#x00B2;-tree by Rodrigo Torres-Aviles, Monica Caniupan

“…Proximity searches within metric spaces are critical for numerous real world applications, including pattern recognition, multimedia information retrieval, and spatial data analysis, among others. …”
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Two-Dimensional X-Ray Diffraction (2D-XRD) and Micro-Computed Tomography (Micro-CT) Characterization of Additively Manufactured 316L Stainless Steel by Puskar Pathak, Goran Majkic, Timmons Erickson, Tian Chen, Venkat Selvamanickam

“…This study focuses on the use of 2D X-Ray diffraction (2D-XRD) and X-Ray micro-computed tomography (micro-CT) techniques to evaluate the crystallography and internal defects of 316L SS parts fabricated by the powder-based direct energy deposition (DED) technique. …”
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Spark: The First Choice for Novices by Judith Gal-Ezer, Smadar Szekely

“…Spark, one of the products offered by MyQ (formerly Plethora), is a game-based platform meticulously designed to introduce students to the foundational concepts of computer science. By navigating through logical challenges, users delve into topics like abstraction, loops, and graph patterns. …”
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Evaluation of a content-based image retrieval system for radiologists in high-resolution CT of interstitial lung diseases by Benjamin Böttcher, Marly van Assen, Roberto Fari, Philipp L. von Knebel Doeberitz, Eun Young Kim, Eugene A. Berkowitz, Felix G. Meinel, Carlo N. De Cecco

“…Abstract Background This retrospective study aims to evaluate the impact of a content-based image retrieval (CBIR) application on diagnostic accuracy and confidence in interstitial lung disease (ILD) assessment using high-resolution computed tomography CT (HRCT). Methods Twenty-eight patients with verified pattern-based ILD diagnoses were split into two equal datasets (1 and 2). …”
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Device Specifications for Neural Network Training with Analog Resistive Cross‐Point Arrays Using Tiki‐Taka Algorithms by Jinho Byun, Seungkun Kim, Doyoon Kim, Jimin Lee, Wonjae Ji, Seyoung Kim

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Theoretical approaches to detecting anomalies in meter readings in scientific literature by D.V. Furikhata, T.A. Vakalyuk

“…The study demonstrates the advantages of decentralised approaches to data processing, particularly the use of edge computing and fog computing technologies, which allow information to be analysed directly on metering devices or in their immediate vicinity. …”
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Gait Perception via Actual and Estimated Pneumatic Physical Reservoir Output by Junyi Shen, Tetsuro Miyazaki, Swaninda Ghosh, Toshihiro Kawase, Kenji Kawashima

“…Traditional approaches to gait perception—such as estimating joint angles and walking conditions—often rely on electronic sensors and neural networks, which can compromise wearability and impose high computational demands. Physical reservoir computing (PRC), which utilizes the inherent nonlinearity of physical systems for data processing, offers a promising alternative. …”
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Stereotactic body radiotherapy-induced arterial hypervascularity of non-tumorous hepatic parenchyma in patients with hepatocellular carcinoma: potential pitfalls in tumor response... by Mee Jin Park, So Yeon Kim, Sang Min Yoon, Jong Hoon Kim, Seong Ho Park, Seung Soo Lee, Yedaun Lee, Moon-Gyu Lee

“…<h4>Purpose</h4>To evaluate temporal changes in contrast enhancement patterns of non-tumorous hepatic parenchyma with a focus on arterial hypervascularity on multiphase computed tomography (CT) in patients with hepatocellular carcinoma (HCC) treated with stereotactic body radiotherapy (SBRT).…”
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The role of nuclear medicine in the diagnosis of Erdheim–chester disease. A series of clinical observations by A. S. Krylov, A. D. Ryzhkov, A. A. Odzharova, Ya. A. Shchipakhina, E. E. Stanyakina, A. A. Martinovich, K. D. Ilkaev, A. M. Stroganova, S. L. Dranko, O. P. Bliznyukovv, A. V. Kuzin, P. A. Zeynalova, A. A. Semenova, M. B. Dolgushin

“…This is a specific, almost pathognomonic scintigraphic picture of the skeleton, “coated” aorta, “hairy” kidney patterns on computer tomography. There is a Erdheim–Chester Disease Global Alliance (ECDGA), which try to unite and provide with information about diagnostics and treatment of this rare disease both patients and doctors. …”
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Doodle.AI: Redefining creative play with human-AI competition in real-time doodle recognition by Ishan Panta, Biplov Paneru, Bishwash Paneru, Bipul Thapa

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Impact of hypertension on coronary artery plaques and FFR-CT in type 2 diabetes mellitus patients: evaluation utilizing artificial intelligence processed coronary computed tomograp... by Yan Xi, Yi Xu, Zheng Shu

“…HRPs were associated with HbA1c levels (OR = 1.631, 95% CI = 1.387–1.918).ConclusionAI analysis of CCTA identifies patterns in quantitative plaque characteristics and FFR-CT values. …”
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Effectiveness of Partition and Graph Theoretic Clustering Algorithms for Multiple Source Partial Discharge Pattern Classification Using Probabilistic Neural Network and Its Adaptiv... by S. Venkatesh, S. Gopal, K. Kannan

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