Results 41 to 50 of about 637,518 (299)
DNABIT Compress-Genome Compression Algorithm [PDF]
Bioinformation, 2011 Data compression is concerned with how information is organized in data. Efficient storage means removal of redundancy from the data being stored in the DNA molecule. Data compression algorithms remove redundancy and are used to understand biologically important molecules. We present a compression algorithm, "DNABIT Compress" for DNA sequences based on
Allam Apparao, Pothuraju Rajarajeswari
openaire +2 more sources
RAZOR: A Compression and Classification Solution for the Internet of Things
Sensors, 2013 The Internet of Things is expected to increase the amount of data produced and exchanged in the network, due to the huge number of smart objects that will interact with one another. The related information management and transmission costs are increasing
Matteo Danieletto +2 more
doaj +1 more source
Strengthening of Masonry Columns with BFRCM or with Steel Wires: An Experimental Study
Fibers, 2016 Nowadays, innovative materials are more frequently adopted for strengthening historical constructions and masonry structures. The target of these techniques is to improve the structural efficiency with retrofitting methods while having a reduced ...
Marinella Fossetti, Giovanni Minafò
doaj +1 more source
Anisotropic Deformation in the Compressions of Single Crystalline Copper Nanoparticles
Crystals, 2018 Atomistic simulations are performed to probe the anisotropic deformation in the compressions of face-centred-cubic metallic nanoparticles. In the elastic regime, the compressive load-depth behaviors can be characterized by the classical Hertzian model or
Jianjun Bian +3 more
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FEBS Letters, EarlyView.Metabolic dysfunction‐associated steatotic liver disease (MASLD) affects nearly one‐third of the global population and poses a significant risk of progression to cirrhosis or liver cancer. Here, we discuss the roles of hepatic dendritic cell subtypes in MASLD, highlighting their distinct contributions to disease initiation and progression, and their ...
Camilla Klaimi +3 more
wiley +1 more source
International Journal of Adaptive Control and Signal Processing, EarlyView., 2023 Summary In this contribution, we propose a detailed study of interpolation‐based data‐driven methods that are of relevance in the model reduction and also in the systems and control communities. The data are given by samples of the transfer function of the underlying (unknown) model, that is, we analyze frequency‐response data.
Quirin Aumann, Ion Victor Gosea
wiley +1 more source
The First Draco 3D Object Crypto-Compression Scheme
IEEE Access, 2022 3D objects have come to play an essential role in industry. They can also be very large, sometimes containing millions of vertices, and therefore it is vital that they are compressed, particularly when it comes to uploading them to the web and during ...
Bianca Jansen Van Rensburg +2 more
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Making tau amyloid models in vitro: a crucial and underestimated challenge
FEBS Letters, EarlyView.This review highlights the challenges of producing in vitro amyloid assemblies of the tau protein. We review how accurately the existing protocols mimic tau deposits found in the brain of patients affected with tauopathies. We discuss the important properties that should be considered when forming amyloids and the benchmarks that should be used to ...
Julien Broc, Clara Piersson, Yann Fichou
wiley +1 more source
Data‐driven performance metrics for neural network learning
International Journal of Adaptive Control and Signal Processing, EarlyView., 2023 Summary Effectiveness of data‐driven neural learning in terms of both local mimima trapping and convergence rate is addressed. Such issues are investigated in a case study involving the training of one‐hidden‐layer feedforward neural networks with the extended Kalman filter, which reduces the search for the optimal network parameters to a state ...
Angelo Alessandri +2 more
wiley +1 more source
Compressed kNN: K-Nearest Neighbors with Data Compression
Entropy, 2019 The kNN (k-nearest neighbors) classification algorithm is one of the most widely used non-parametric classification methods, however it is limited due to memory consumption related to the size of the dataset, which makes them impractical to apply to ...
Jaime Salvador–Meneses +2 more
doaj +1 more source