Partitioning variability in animal behavioral videos using semi-supervised variational autoencoders. by Matthew R Whiteway, Dan Biderman, Yoni Friedman, Mario Dipoppa, E Kelly Buchanan, Anqi Wu, John Zhou, Niccolò Bonacchi, Nathaniel J Miska, Jean-Paul Noel, Erica Rodriguez, Michael Schartner, Karolina Socha, Anne E Urai, C Daniel Salzman, International Brain Laboratory, John P Cunningham, Liam Paninski

“…Here we introduce a new video analysis tool that combines the output of supervised pose estimation algorithms (e.g. DeepLabCut) with unsupervised dimensionality reduction methods to produce interpretable, low-dimensional representations of behavioral videos that extract more information than pose estimates alone. …”
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Accuracy measurement of automatic remeshing tools by Mattia Sullini

“…While in the applications for which remeshing algorithms have historically been developed, the problem can be addressed without affecting the mesh polycount, for the authoring of 3D assets intended for Real-Time Rendering applications, maintaining a low polycount is mandatory. …”
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Performance Evaluation of Uplink Cell-Free Massive MIMO Network Under Weichselberger Rician Fading Channel by Birhanu Dessie, Javed Shaikh, Georgi Iliev, Maria Nenova, Umar Syed, K. Kiran Kumar

“…However, estimating the channel with high-performance, low-cost computational methods is still a problem. Different algorithms have been developed to address these challenges in channel estimation. …”
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Artificial neural networks-based multi-objective optimization of immersion cooling battery thermal management system using Hammersley sampling method by Muhammed Donmez, Mehmet Ihsan Karamangil

“…Multi-objective optimization, using ANN-based multi objective genetic algorithms, is conducted on a 16S1P configuration at 4C discharge and 0.008 kg/s. …”
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Low-complexity detection for MIMO visible light communication system using generalized spatial modulation by Wei-Chiang Wu, Gan-Lin Chen

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Grey wolf optimization for enhanced performance in wind power system with dual-star induction generators by Katia Benamara, Hocine Amimeur, Yanis Hamoudi, Maher G. M. Abdolrasol, Umit Cali, Umit Cali, Taha Selim Ustun

“…A comparative analysis of the optimization results has been conducted, focusing on the outcomes obtained with the GWO algorithm. The findings reveal a notable reduction in steady-state error, signifying improved stability, and an overall enhancement in the wind power system’s performance. …”
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Ad-BBR: Enhancing Round-Trip Time Fairness and Transmission Stability in TCP-BBR by Mingjun Wang, Xuezhi Zhang, Feng Jing, Mei Gao

“…Compared to the BBRv1 algorithm, Ad-BBR achieved a 17% increase in throughput and a 30% improvement in RTT fairness, along with a 13% reduction in the retransmission rate and an approximate 20% decrease in latency.…”
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A simplification method for large-scale urban point clouds considering diversity of terrain object features by Shen Shen, Yonghong Wu, Hongwei Zhang, Jiankai Lu, Hong Fan

“…Comparative experimental results indicate that compared to baseline algorithms that consider geometric features on the test dataset, the proposed method achieves about 16.5-min processing time for 13-million-point dataset, significantly faster than other algorithms. …”
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Explainable light-weight deep learning pipeline for improved drought stress identification by Aswini Kumar Patra, Aswini Kumar Patra, Lingaraj Sahoo

“…Sensor-based imaging data serves as a rich source of information for machine learning and deep learning algorithms, facilitating further analysis that aims to identify drought stress. …”
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A Framework of Recommendation System for Unmanned Aerial Vehicle Autonomous Maneuver Decision by Qinzhi Hao, Tengyu Jing, Yao Sun, Zhuolin Yang, Jiali Zhang, Jiapeng Wang, Wei Wang

“…Through rigorous computer-based testing, we validated the effectiveness of established recommendation algorithms within our framework. Notably, the prioritized experience replay deep deterministic policy gradient (PER-DDPG) algorithm, employing dense rewards and continuous actions, demonstrated superior performance, achieving a 69% success rate in confrontational scenarios against a versatile expert algorithm after 1000 training iterations, marking an 80% reduction in training time compared to conventional reinforcement learning methods. …”
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Lossless Hyperspectral Image Compression in Comet Interceptor and Hera Missions with Restricted Bandwith by Kasper Skog, Tomáš Kohout, Tomáš Kašpárek, Antti Penttilä, Monika Wolfmayr, Jaan Praks

“…These results contribute valuable knowledge to the behavioral characteristics of both algorithms and provide insight for entities planning on using either algorithm on board planetary missions.…”
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Integrated Time Series Analysis, Clustering, and Forecasting for Energy Efficiency Optimization and Tariff Management by Anderson Jhones Passos Nascimento, Menaouar Berrehil El Kattel, Jose Antonio Fernandes de Macedo, Fernando Luiz Marcelo Antunes

“…Additionally, the BIRCH algorithm was evaluated in combination with dimensionality reduction methods, such as Principal Component Analysis (PCA) and Autoencoders, to enhance clustering performance. …”
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Machine Learning Using Approximate Computing by Padmanabhan Balasubramanian, Syed Mohammed Mosayeeb Al Hady Zaheen, Douglas L. Maskell

“…The design metrics estimated show that NAA achieves a 37% reduction in delay, a 22% reduction in area, and a 31% reduction in power compared to the accurate adder. …”
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Standardized conversion model for retinal thickness measurements between spectral-domain and swept-source optical coherence tomography based on machine learning by Zhongping Tian, Yinning Guo, Xi Chen, Qifeng Zhou, Yuan Liu, Zhizhu Yi, Li Zhang, Li Zhang

“…Machine learning models exhibited superior performance in central subfield thickness (CST) prediction, achieving test set R2 values of 0.930 (LR), 0.926 (LASSO), 0.936 (SVR), and 0.892 (RF). …”
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Vital Sign and Biochemical Data Collection Using Non-contact Photoplethysmography and the Comestai Mobile Health App: Protocol for an Observational Study by Gianvincenzo Zuccotti, Paolo Osvaldo Agnelli, Lucia Labati, Erika Cordaro, Davide Braghieri, Simone Balconi, Marco Xodo, Fabrizio Losurdo, Cesare Celeste Federico Berra, Roberto Franco Enrico Pedretti, Paolo Fiorina, Sergio Maria De Pasquale, Valeria Calcaterra

“…Sensitivity, specificity, positive predictive value, negative predictive value, accuracy, and likelihood ratios will be calculated to determine the ability of the new app to accurately measure vital signs. …”
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Solutions to face and combat disinformation: proposals in scientific literature from the web of science by Jônatas Edison da Silva, Enrique Muriel-Torrado

“…(a) Science and scientific community; (b) States and governments; (c) Media and communications; (d) Platforms and algorithms; (e) Users and education; and (f) Others. …”
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A Hubness Information-Based k-Nearest Neighbor Approach for Multi-Label Learning by Zeyu Teng, Shanshan Tang, Min Huang, Xingwei Wang

“…Experimental results on 28 benchmark datasets demonstrate that MLHiKNN is competitive among the compared methods, including nine well-established MLC algorithms and three commonly used hubness reduction techniques, in dealing with MLC problems.…”
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Basics of the semantic portal of nuclear knowledge BelNET functioning by S. N. Sytovа, V. V. Haurylavets, A. P. Dunets, A. N. Kavalenka, S. V. Charapitsa

“…The described basic principles of organization and algorithms based on semantic technologies, which underlie the functioning of the content management system of the scientific and educational portal eLab-Science and the Belarusian nuclear knowledge portal BelNET, created on its basis, make it possible to effectively implement the placement of content records in the portal taxonomy, as well as automatically generate a set of keywords for the resource being created…”
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3D-CNN with Multi-Scale Fusion for Tree Crown Segmentation and Species Classification by Jiayao Wang, Zhen Zhen, Yuting Zhao, Ye Ma, Yinghui Zhao

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Giant pseudoangiomatous stromal hyperplasia of breast: Management challenge of gigantomastia with ptosis by Uma Krishnaswamy, K Balachandar, Thulasilingam Kathirazhagan

“…A pragmatic and individualized approach is the solution in the absence of reliable algorithms for management. This instance of a giant PASH tumor producing gigantomastia with severe ptosis is a case to point. …”
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