Space-Based FPGA Radio Receiver Design, Debug, and Development of a Radiation-Tolerant Computing System by Zachary K. Baker, Mark E. Dunham, Keith Morgan, Michael Pigue, Matthew Stettler, Paul Graham, Eric N. Schmierer, John Power

“…This processing capability enables very advanced algorithms such as our wideband RF compression scheme to operate at the source, allowing bandwidth-constrained applications to deliver previously unattainable performance. …”
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Hierarchical Classification of Variable Stars Using Deep Convolutional Neural Networks by Mahdi Abdollahi, Nooshin Torabi, Sadegh Raeisi, Sohrab Rahvar

“…There have been many attempts to classify variable stars by traditional algorithms like Random Forest. In recent years, neural networks as classifiers have come to notice because of their lower computational cost compared to traditional algorithms. …”
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Real-Time Audio-Visual Analysis for Multiperson Videoconferencing by Petr Motlicek, Stefan Duffner, Danil Korchagin, Hervé Bourlard, Carl Scheffler, Jean-Marc Odobez, Giovanni Del Galdo, Markus Kallinger, Oliver Thiergart

“…The obtained results demonstrate the effectiveness of the proposed design, the various algorithms, and the benefit of fusing different modalities in this scenario.…”
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Bulk Low-Inertia Power Systems Adaptive Fault Type Classification Method Based on Machine Learning and Phasor Measurement Units Data by Mihail Senyuk, Svetlana Beryozkina, Inga Zicmane, Murodbek Safaraliev, Viktor Klassen, Firuz Kamalov

“…This research focuses on developing and testing a method for classifying disturbances in power systems using machine learning algorithms and phasor measurement unit (PMU) data. To enhance the speed and accuracy of disturbance classification, we employ a range of ensemble machine learning techniques, including Random forest, AdaBoost, Extreme gradient boosting (XGBoost), and LightGBM. …”
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AI‐Powered Multimodal Modeling of Personalized Hemodynamics in Aortic Stenosis by Caglar Ozturk, Daniel H. Pak, Luca Rosalia, Debkalpa Goswami, Mary E. Robakowski, Raymond McKay, Christopher T. Nguyen, James S. Duncan, Ellen T. Roche

“…The efficiency and reliability of these algorithms make them an ideal complementary tool for personalized high‐fidelity modeling of AS biomechanics, hemodynamics, and treatment planning.…”
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High School Scores to College Performance: Exploring the Predictive Validity of Grade 12 Standardized Test Scores for University GPA by Abdurrahman Wahab, Hemin Ibrahim

“…The study employs traditional statistical methods and advanced AI-based algorithms to categorize and analyze a dataset comprising 225 students admitted between 2014 through 2019. …”
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Three-Dimensional Near-Field Microwave Holography for Tissue Imaging by Reza K. Amineh, Ali Khalatpour, Haohan Xu, Yona Baskharoun, Natalia K. Nikolova

“…Then, novel holographic imaging algorithms are implemented to provide three-dimensional images of the inspected domain. …”
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The Advances in Neuromorphic Computing and Brain-Inspired Systems (ANCBIS). by DanielRaj K, Ponseka G, Bharath Sanjai Lordwin D J3

“…This paper examines recent advancements in neuromorphic computing, with an emphasis on innovative hardware and algorithms that boost computational power while reducing energy consumption. …”
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Collaborative Penalized Least Squares for Background Correction of Multiple Raman Spectra by Long Chen, Yingwen Wu, Tianjun Li, Zhuo Chen

“…Although Raman spectroscopy has been widely used as a noninvasive analytical tool in various applications, backgrounds in Raman spectra impair its performance in quantitative analysis. Many algorithms have been proposed to separately correct the background spectrum by spectrum. …”
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Classification and risk assessment of ovarian-adnexal lesions using parametric and radiomic analysis of co-registered ultrasound-photoacoustic tomographic images by Yixiao Lin, Quing Zhu

“…Additionally, statistics-based radiomic algorithms were applied to quantify differences in the lesion texture on US-PAT images. …”
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Representing groups of students as personas: A systematic review of persona creation, application, and trends in the educational domain by Ali Farooq, Amani Alabed, Pilira Stella Msefula, Reham AL Tamime, Joni Salminen, Soon-gyo Jung, Bernard J. Jansen

“…The findings suggest significant opportunities for the educational sector to leverage algorithmic methods to advance persona creation and broaden their application scope.…”
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Translation of Value-Semantic Narratives in Public Digital Communication: Opportunities and Limitations by Albina B. Romashkina, Daria A. Kirichuk

“…Traditional agents of socialization cannot fully shape a person’s worldview, and therefore citizens may be more susceptible to manipulative algorithmic tools of digital platforms on which destructive narratives are broadcast that contribute to the destruction of the worldview and values of society. …”
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Real time synthesis of digital automatic control systems for training by Dalia Baziukaitė, Artūras Bielskis

“…Such links are useful optimizing system dynamics in real time, creating leaning programs and applying adaptation algorithms of the automatic control systems. …”
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Ancient Tamil inscription recognition using detect, recognize and labelling, interpreter framework of text method by Balasubramanian Murugan, P. Visalakshi

“…The dataset used consists of third-century Tamil inscriptions. The algorithms within the DR-LIFT method specifically designed to detect text with intricate features such as curves, loops, and lines, significantly enhancing detection accuracy. …”
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Random Frequency Division Multiplexing by Chanzi Liu, Jianjian Wu, Qingfeng Zhou

“…However, the signal is not sparse which makes the reconstruction algorithms ineffective. We take full account of the great power of deep neural networks (DNN) to detect the signal as it is an underdetermined equation. …”
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EMG Dataset for Gesture Recognition with Arm Translation by Iris Kyranou, Katarzyna Szymaniak, Kianoush Nazarpour

“…This dataset, comprising EMG and hand kinematics data from 8 participants performing 6 different hand gestures, provides a comprehensive resource for investigating position-invariant myoelectric control decoding algorithms. We envision this dataset to serve as a valuable resource for both training and benchmark arm position-invariant myoelectric control algorithms. …”
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Drug discovery and mechanism prediction with explainable graph neural networks by Conghao Wang, Gaurav Asok Kumar, Jagath C. Rajapakse

“…The unprecedented development of machine learning and deep learning algorithms has expedited the drug response prediction research. …”
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Convolutional neural network model over encrypted data based on functional encryption by Chen WANG, Jiarun LI, Jian XU

“…Currently, homomorphic encryption, secure multi-party computation, and other encryption schemes are used to protect the privacy of sensitive data in outsourced convolutional neural network (CNN) models.However, the computational and communication overhead caused by the above schemes would reduce system efficiency.Based on the low cost of functional encryption, a new convolutional neural network model over encrypted data was constructed using functional encryption.Firstly, two algorithms based on functional encryption were designed, including inner product functional encryption and basic operation functional encryption algorithms to implement basic operations such as inner product, multiplication, and subtraction over encrypted data, reducing computational and communication costs.Secondly, a secure convolutional computation protocol and a secure loss optimization protocol were designed for each of these basic operations, which achieved ciphertext forward propagation in the convolutional layer and ciphertext backward propagation in the output layer.Finally, a secure training and classification method for the model was provided by the above secure protocols in a module-composable way, which could simultaneously protect the confidentiality of user data as well as data labels.Theoretical analysis and experimental results indicate that the proposed model can achieve CNN training and classification over encrypted data while ensuring accuracy and security.…”
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Inverse problems with the digital image correlation: approach and applications by Emanuele Sgambitterra, Fabrizio Niccoli

“…It is based on regression algorithms to estimate materials and/or loading parameters by fitting the experimentally-evaluated displacement field to representative analytical solutions. …”
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Machine learning in the prediction of human wellbeing by Ekaterina Oparina, Caspar Kaiser, Niccolò Gentile, Alexandre Tkatchenko, Andrew E. Clark, Jan-Emmanuel De Neve, Conchita D’Ambrosio

“…In response, we here use tree-based Machine Learning (ML) algorithms to provide a better understanding of respondents’ self-reported wellbeing. …”
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