Transfer learning nonlinear plasma dynamic transitions in low dimensional embeddings via deep neural networks by Zhe Bai, Xishuo Wei, William Tang, Leonid Oliker, Zhihong Lin, Samuel Williams

“…Deep learning algorithms provide a new paradigm to study high-dimensional dynamical behaviors, such as those in fusion plasma systems. …”
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Deep Learning Approaches for Automated Prediction of Treatment Response in Non-Small-Cell Lung Cancer Patients Based on CT and PET Imaging by Randy Guzmán Gómez, Guadalupe Lopez Lopez, Victor M. Alvarado, Froylan Lopez Lopez, Eréndira Esqueda Cisneros, Hazel López Moreno

“…The rapid growth of artificial intelligence, particularly in the field of deep learning, has opened up new advances in analyzing and processing large and complex datasets. …”
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Quantifying Topographic Ruggedness Using Principal Component Analysis by Maan Habib

“…The development of geospatial technologies has opened a new era in terms of data collection techniques and analysis procedures. …”
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Single image super-resolution via Image Quality Assessment-Guided Deep Learning Network. by Zhengqiang Xiong, Manhui Lin, Zhen Lin, Tao Sun, Guangyi Yang, Zhengxing Wang

“…Extensive benchmark experiments and analyses also prove that our method provides a promising and opening architecture for SISR, which is not confined to a specific network model.…”
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Multisensory Museums, Hybrid Realities, Narration, and Technological Innovation: A Discussion Around New Perspectives in Experience Design and Sense of Authenticity by Eva Pietroni

“…A short overview about how these algorithms evolve and work is presented, considering the challenges, threats, expectations, and ethical implications they pose. …”
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Convergence of nanotechnology and artificial intelligence in the fight against liver cancer: a comprehensive review by Manjusha Bhange, Darshan Telange

“…Recent advancements in nanotechnology and artificial intelligence (AI) have opened new frontiers in the fight against this disease. …”
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Fault detection in electrical power systems using attention-GRU-based fault classifier (AGFC-Net) by Deepen Khandelwal, Prateek Anand, Mayukh Ray, Sangeetha R. G.

“…Experimental results show that AGFC-Net attains a fault detection accuracy of 99.52%, better than conventional machine learning and deep learning algorithms. The suggested method presents a stronger, adaptive, and scalable solution for autonomous fault diagnosis, opening the door to intelligent and trustworthy fault detection systems in future power grids and industrial applications.…”
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DMSA-Net: a deformable multiscale adaptive classroom behavior recognition network by Chunyu Dong, Jing Liu, Shenglong Xie

“…Moreover, there are occlusions and scale differences in the front and back rankings, which can easily cause confusion and interference with target features in the detection process, greatly limiting the accurate recognition ability of existing visual algorithms for classroom behavior. This article proposes a deformable multiscale adaptive classroom behavior recognition network. …”
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Remote Sensing Perspective on Monitoring and Predicting Underground Energy Sources Storage Environmental Impacts: Literature Review by Aleksandra Kaczmarek, Jan Blachowski

“…The review covers modelling and prediction methods used to analyze the environmental impacts of UGS, with data-driven models employing geostatistical tools and machine learning algorithms. The limited number of contributions treating geological storage sites holistically opens perspectives for the development of complex approaches capable of monitoring and modelling its environmental impacts.…”
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Autonomous Driving Road Environment Recognition with Multiscale Object Detection by Jeny J.R.V., Divya Phulari, Varsha Kolanu, Mrunalini Anantha, Irfan S.K.M.

“…The system delivers significant gains in efficiency and accuracy of detection by incorporating the deep learning models, providing a solid basis for the creation of safer and more reliable autonomous cars. This study opens the door to a future in which self-driving cars navigate roadways with increased safety and efficiency by demonstrating the critical role that cutting-edge deep learning algorithms play in enabling precise perception and decision-making capabilities within autonomous driving systems.…”
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A novel hybrid fuzzy logic and federated learning framework for enhancing cybersecurity and fraud detection in IoT-enabled metaverse transactions by Amjad Rehman, Kamran Ahmad Awan, Amal Al-Rasheed, Anees Ara, Fahad F. Alruwaili, Shaha Al-Otaibi, Tanzila Saba

“…Increasing integration of the Internet of Things (IoT) with virtual environments like the Metaverse has opened up new avenues in the applicability of technologies but faces severe challenges to security and fraud detection. …”
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Application of Phi (<italic>&#x03A6;</italic>), the Golden Ratio, in Computing: A Systematic Review by M. Akhtaruzzaman, Jamal Uddin Tanvin, Amir Akramin Shafie, Fahim Shahryer, Sachitra Halder

“…This study opens promising avenues for future research on the applications of <inline-formula> <tex-math notation="LaTeX">$\phi $ </tex-math></inline-formula> in diverse fields of science, engineering, and computing.…”
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A Review of Artificial Intelligence Applications in Predicting Faults in Electrical Machines by Mathew Habyarimana, Abayomi A. Adebiyi

“…Traditional human-dependent diagnostic techniques are changing as a result of advances in artificial intelligence (AI), opening the door to automated and predictive maintenance plans. …”
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Combination of Music, Artificial Intelligence, and Brainwaves for the Promotion of Mental Well-Being by Georgios Karachalios, Evina Makaroni

“…On a theoretical level, adapting music through machine learning opens new avenues for understanding the connection between human perception and psychological states. …”
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Fused Space in Architecture via Multi-Material 3D Printing Using Recycled Plastic: Design, Fabrication, and Application by Jiangjing Mao, Lawrence Hsu, Mai Altheeb

“…Furthermore, to generate diverse properties for the fused space, several nature-inspired forming algorithms are employed, including Swarm Behavior, Voronoi, Game of Life, and Shortest Path, to shape the building enclosure. …”
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A New Approach for Quantification of Finger Angles with Applications in Rehabilitation and Medical Assessment by Marius Turnea, Andrei Gheorghita, Irina Duduca, Mariana Rotariu

“…These findings demonstrate the feasibility of integrating the proposed method into a broader clinical framework for objective monitoring of patient progress in functional rehabilitation programs. The study opens new perspectives for the development of advanced data processing algorithms, including the integration of deep learning neural networks for modelling and optimizing joint movements…”
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Mammography In Breast Cancer Screening – Current Knowledge, Challenges, The Impact of Artificial Intelligence, And Effectiveness With A Focus On Poland by Maciej Pachana, Marcin Piersiak, Hubert Sawczuk, Anna Tomasiewicz, Jan Zabierowski, Piotr Kukuła, Julia Marschollek, Maciej Ziomek

“…The integration of artificial intelligence (AI) in mammographic image analysis opens new opportunities, supporting radiologists by automating the detection and classification of potential lesions, thereby increasing screening efficiency and reducing false-positive rates. …”
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Robust Corner Detection Using Local Extrema Differences by Reza Yazdi, Hassan Khotanlou, Hosna Khademfar

“…We conduct a comprehensive evaluation comparing our detector to seven established algorithms using five benchmark images with ground truth corner locations. …”
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Insights and caveats from mining local and global temporal motifs in cryptocurrency transaction networks by Naomi A. Arnold, Peijie Zhong, Cheick Tidiane Ba, Ben Steer, Raul Mondragon, Felix Cuadrado, Renaud Lambiotte, Richard G. Clegg

“…Abstract Distributed ledger technologies have opened up a wealth of fine-grained transaction data from cryptocurrencies like Bitcoin and Ethereum. …”
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Closing the multichannel gap through computational reconstruction of interaction in super-resolution microscopy by Ben Cardoen, Hanene Ben Yedder, Ivan Robert Nabi, Ghassan Hamarneh

“…We review novel interaction-analysis algorithms, and we identify specific SRM factors that can compromise the accuracy of interaction analysis. …”
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