11 papers · ranked by Valyu relevance
Hui Liu, Tao Cui, Wei Leng, Linbo Zhang
Hilbert order is widely applied in many areas. However, most of the algorithms are confined to low dimensional cases. In this paper, algorithms for encoding and decoding arbitrary dimensional Hilbert order are presented. Eight algorithms are proposed. Four algorithms are based on arithmetic operations and the other…
Amir Said
Entropy coding, compression, complexity This introduction to arithmetic coding is divided in two parts. The first explains how and why arithmetic coding works. We start presenting it in very general terms, so that its simplicity is not lost under layers of implementation details. Next, we show some of its basic…
Jarek Duda
The modern data compression is mainly based on two approaches to entropy coding: Huffman (HC) and arithmetic/range coding (AC). The former is much faster, but approximates probabilities with powers of 2, usually leading to relatively low compression rates. The latter uses nearly exact probabilities - easily approaching…
Melih Şahin, Beyza E. Ortlek, Özgür B. Akan
(IoBNT) Authors: ['Melih Şahin' 'Beyza E. Ortlek' 'Özgür B. Akan'] Abstract—Molecular Communication (MC) has emerged as a promising paradigm employing molecules to transfer information at the nano-scale. Unlike MC channel coding, MC source coding has remained mostly an unexplored area of research. In a recent paper…
Somdip Dey, Asoke Nath, Shalabh Agarwal
—Now, security and authenticity of data is a big challenge. To solve this problem, we propose an innovative method to authenticate the digital documents. In this paper, we propose a new method, where the marks obtained by a candidate will also be encoded in QR CodeTM in encrypted form, so that if an intruder tries to…
Somayeh Kafaie, Yuanzhu Peter Chen, Octavia A. Dobre, Mohamed H. Ahmed
'Mohamed H. Ahmed'] Abstract- In recent years, network coding has become one of the most interesting fields and has attracted considerable attention from both industry and academia. The idea of network coding is based on the concept of allowing intermediate nodes to encode and combine incoming packets instead of only…
Rıza Özçelik, Laura van Weesep, Sarah de Ruiter, Francesca Grisoni
In this work, we introduce peptidy -- a lightweight Python library that facilitates converting peptides (expressed as aminoacid sequences) to numerical representations suited to machine learning. peptidy is free from external dependencies, integrates seamlessly into modern Python environments, and supports a range of…
Authors not listed
Experimental design plays an important role in efficiently acquiring informative data for system characterization and deriving robust conclusions under resource limitations. Recent advancements in high-throughput experimentation coupled with machine learning have notably improved experimental procedures. While Bayesian…
Jürgen Köfinger, Gerhard Hummer
The proper balancing of information from experiment and theory is a long-standing problem in the analysis of noisy and incomplete data. Viewed as a Pareto optimization problem, improved agreement with the experimental data comes at the expense of growing inconsistencies with the theoretical reference model. Here, we…
Jürgen Köfinger, Gerhard Hummer
The proper balancing of information from experiment and theory is a long-standing problem in the analysis of noisy and incomplete data. Viewed as a Pareto optimization problem, improved agreement with the experimental data comes at the expense of growing inconsistencies with the theoretical reference model. Here, we…
Sanjar Adilov
Generative neural networks have shown promising results in de novo drug design. Recent studies suggest that one of the efficient ways to produce novel molecules matching target properties is to model SMILES sequences using deep learning in a way similar to language modeling in natural language processing. In this…