Skip to content
Free planNo credit card requiredStart writing
AI for Research home
AI for Research home
Dashboard
Sign inGet started

Search 250 million research papers

Read the abstract, see who wrote it and who cites it, and get the citation in APA, MLA, Chicago or Harvard.

About 10,000 papers for “Natural computing”

Natural Computing

Bournez, Olivier, Dowek, Gilles · HAL (Le Centre pour la Communication Scientifique Directe) · 2012

Cited by 0

NATURAL COMPUTING

Matthew N. O. Sadiku, Mahamadou Tembely, Sarhan M. Musa · International Journal of Advanced Research in Computer Science and Software Engineering · 2018

Natural computing refers to the field that investigates both human-designed computing inspired by nature and computing taking place in nature. It is based on the premise that “nature computes.” Due of its interdisciplinary nature, natural computing covers a spectrum of research areas including biology, chemistry, physics, computer science, and engineering. This paper provides a brief introduction to natural computing.

Cited by 0

Natural Computing

R. Brijder, H. J. Hoogeboom, J. N. Kok et al. · 2008

A number of basic life processes can be considered as computations. Natural Computing studies these computations. We can distinguish two types of Natural Computing. One is devoted to understanding the computations in biology and the other is to develop human designed computing inspired by nature. A representative of the first type is Gene Assembly and a representative of the second type is Membrane Computing. Gene Assembly Gene Assembly is one of the most complex types of DNA transformation known in organisms. Gene assembly occurs in ciliates, a large group of one cellular organisms. Ciliates have two nuclei (instead of one in other organisms): the macronucleus and the micronucleus. The micronucleus contains chromosomes, but the genes on the chromosomes are silent: segments of the genes (called MDSs) are dispersed on the chromosomes. The macronucleus contains all genes with their segments properly aligned as separate DNA fragments. Gene Assembly is the process which transforms a micronucleus into a macronucleus. The process is nondeterministic and always halts.

Cited by 0

Natural Computing

Leandro Nunes de Castro · IGI Global eBooks · 2005

There are several artifacts developed by taking inspiration from natural organisms and phenomena. For instance, Velcro was inspired by a plant burr, bullet- proof vests were inspired by spider silk, sonars were inspired by bats, airplanes were motivated by the flying of birds, and the list goes on. The observation of nature has also allowed the development of several laws and theories that describe how parts of nature work; the laws of physics are a great example – laws of thermodynamics (conservation, entropy, and absolute zero); laws of movement (Newton’s laws); laws of electromagnetism (Maxwell’s laws); and others. They are used to explain the trajectories, attraction and other aspects of objects.

Cited by 1

Natural Computing

R. Brijder, H. J. Hoogeboom, J. N. Kok et al. · 2008

A number of basic life processes can be considered as computations. Natural Computing studies these computations. We can distinguish two types of Natural Computing. One is devoted to understanding the computations in biology and the other is to develop human designed computing inspired by nature. A representative of the first type is Gene Assembly and a representative of the second type is Membrane Computing. Gene Assembly Gene Assembly is one of the most complex types of DNA transformation known in organisms. Gene assembly occurs in ciliates, a large group of one cellular organisms. Ciliates have two nuclei (instead of one in other organisms): the macronucleus and the micronucleus. The micronucleus contains chromosomes, but the genes on the chromosomes are silent: segments of the genes (called MDSs) are dispersed on the chromosomes. The macronucleus contains all genes with their segments properly aligned as separate DNA fragments. Gene Assembly is the process which transforms a micronucleus into a macronucleus. The process is non-deterministic and always halts.

Cited by 0

Natural Computing Group

Rui Li, Jeroen Eggermont, Ernst G. P. Bovenkamp · 2009

In this paper we compare Mixed-Integer Evolution Strategies (MI-ES) and standard Evolution Strategies (ES) when applied to find optimal solutions for artificial test problems and medical image processing problems. MI-ES are special instantiations of standard ES that can solve optimization problems with different objective variable types (continuous, integer, and nominal discrete). Artificial test problems are generated with a mixed-integer test generator. The practical image processing problem iss the detection of the lumen boundary in IntraVascular UltraSound (IVUS) images. Based on the experimental results, it is shown that MI-ES generally perform better than standard ES on both artifical and practical image processing problems. Moreover it is shown that MI-ES can effectively improve the parameters settings for the IVUS lumen detection algorithm. Categories and Subject Descriptors

Cited by 0

Natural Language Computing

Ray C. Dougherty · Psychology Press eBooks · 2013

This book's main goal is to show readers how to use the linguistic theory of Noam Chomsky, called Universal Grammar, to represent English, French, and German on a computer using the Prolog computer language. In so doing, it presents a follow-the-dots approach to natural language processing, linguistic theory, artificial intelligence, and expert systems. The basic idea is to introduce meaningful answers to significant problems involved in representing human language data on a computer. The book offers a hands-on approach to anyone who wishes to gain a perspective on natural language processing -- the computational analysis of human language data. All of the examples are illustrated using computer programs. The optimal way for a person to get started is to run these existing programs to gain an understanding of how they work. After gaining familiarity, readers can begin to modify the programs, and eventually write their own.The first six chapters take a reader who has never heard of non-procedural, backtracking, declarative languages like Prolog and, using 29 full page diagrams and 75 programs, detail how to represent a lexicon of English on a computer. A bibliography is programmed into a Prolog database to show how linguists can manipulate the symbols used in formal representations, including braces and brackets. The next three chapters use 74 full page diagrams and 38 programs to show how data structures (subcategorization, selection, phrase marker) and processes (top-down, bottom-up, parsing, recursion) crucial in Chomsky's theory can be explicitly formulated into a constraint-based grammar and implemented in Prolog. The Prolog interpreters provided with the book are basically identical to the high priced Prologs, but they lack the speed and memory capacities. They are ideal since anything learned about these Prologs carries over unmodified to C-Prolog and Quintas on the mainframes. Anyone who studies the prolog implementations of the lexicons and syntactic principles of combination should be able to use Prolog to represent their own linguistic data on the most complex Prolog computer available, whether their data derive from syntactic theory, semantics, sociolinguistics, bilingualism, language acquisition, language learning, or some related area in which the grammatical patterns of words and phrases are more crucial than concepts of quantity. The printed examples illustrate C-Prolog on an Ultrix Vax, a standard university configuration. The disk included with the book contains shareware version of Prolog-2 (IBM PC) and MacProlog (Macintosh) plus versions of the programs that run on C-Prolog, Quintas, Prolog-2, and MacProlog. Appendix II contains information about how to use the Internet, Gopher, CompuServe, and the free More BBS to download the latest copies of Prolog, programs, lexicons, and parsers. All figures (100+) in the book are available scaled to make full size transparencies for class lectures. Valuable special features of this volume include: * more than 100 full page diagrams illustrating the basic concepts of natural language processing, Prolog, and Chomsky's linguistic theories; * more than 100 programs -- illustrated in at least one script file -- showing how to encode the representations and derivations of generative grammar into Prolog; * more than 100 session files guiding readers through their own hands-on sessions with the programs illustrating Chomsky's theory; * a 3.5" disk (IBM Format) containing: 1. all programs in versions to run in C-Prolog or Quintas Prolog on an Ultrix Vax, and on an IBM PC and a Macintosh, 2. a shareware version of Prolog-2 for IBM PC clones which runs all programs in the book, 3. a shareware version of MacProlog for Macintosh which runs all programs in the book; * instructions on using Internet, CompuServe, and the free More BBS to download the latest copies of Prolog, programs, lexicons, and parsers; and * numerous references enabling interested students to pursue questions at greater depth by consulting the items in the extensive bibliography.

Cited by 2

Natural Language Computing

2025

Advancements in emotion-aware language processing increasingly shape vital NLP applications ranging from conversational AI and affective computing to computational psychology and creative content genera-tion.Existing emotion datasets either lack emotional granularity or fail to capture necessary stylistic diver-sity, limiting the advancement of effective emotion-conditioned text generation systems.Seeking to bridge this crucial gap between granularity and style diversity, this paper introduces a novel systematically con-structed dataset named ELSA (Emotion and Language Style Alignment Dataset) 1 leveraging fine-grained emotion taxonomies adapted from existing sources (dairai/emotion dataset and GoEmotions taxonomy).This dataset comprises multiple emotionally nuanced variations of original sentences regenerated across distinct contextual styles (conversational, formal, poetic, and narrative) using advanced Large Language Models (LLMs).Rigorous computational evaluation using metrics such as perplexity, embedding variance, readability, lexical diversity, and semantic coherence measures validates the dataset's emotional authentic-ity, linguistic fluency, and textual diversity.Comprehensive metric analyses affirm its potential to support deeper explorations into emotion-conditioned style-adaptive text generation.By enabling precision-tuned emotionally nuanced language modeling, our dataset creates fertile ground for research on fine-grained emotional control, prompt-driven explanation, interpretability, and styleadaptive expressive language gen-eration with LLMs.

Cited by 0Open access

Natural Computing and Beyond

Toshiyuki Nakagaki, Yasuhiro Suzuki · Directory of Open access Books (OAPEN Foundation) · 2013

Cited by 0Open access