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2nd IEEE International Conference on Wireless Communications, Signal Processing and Networking (WiSPNET)

作者： Sofi, Shabir Ahmad Mir, Roohie Naaz Natl Inst Technol Srinagar Hazratbal 190006 J&K India

ISBN: (纸本)9781509044429

In Underwater Wireless Sensor Network (UWSN) there are many challenges and one of the major challenge is limited battery power. In UWSN it is not possible to recharge or replace the batteries. Also signal attenuation under water is more as compared to the terrestrial WSN. Therefore for the same distance and amount of data we need to use more power to push the signal on the surface of the water as compared to the terrestrial Wireless Sensor Network (WSN). The scenario is further worsen by the fact that in some cases due to water current etc. there is frequent change in the position and location of the nodes with respect to the cluster head or other nodes. Due to the above reasons the routing in UWSN should be energy efficient and adaptive to the changes in the network. This paper proposes an adaptive architecture which is based on the natural algorithms to keep the nodes connected even if they get away from their cluster and a dedicated cluster head named as advanced node is used to overcome the additional power requirements due to the signal attenuation.

关键词： Underwater Wireless Sensor Networks Cluster Adaptive Protocol natural algorithm Cuckoo algorithm Energy Efficient WSN

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The Genetic Language: natural algorithms, Developmental Patterns, and Instinctive Behavior 2nd

The Genetic Language: Natural Algorithms, Developmental Patt...

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2nd International Conference of Artificial Intelligence, Medical Engineering, Education (AIMEE)

作者： Shklovskiy-Kordi, Nikita E. Finn, Victor K. Ehrlich, Lev I. Igamberdiev, Abir U. Natl Res Ctr Hematol Moscow Russia RAS Fed Res Ctr Comp Sci Management Moscow Russia Moscow MV Lomonosov State Univ Ctr Res Comp Moscow Russia Mem Univ Newfoundland Dept Biol St John NF Canada

ISBN: (纸本)9783030120825;9783030120818

The genetic system of biological organisms possesses a structure which corresponds to the general principles of linguistics and can be defined as the genetic language. In this study, we suggest to analyze the mechanisms for interpretation of genetic texts based on the universal model of operation of the programs in electronic computers as initially suggested by Efim Liberman. Ontogenetic development is realized at the level of reading of genetic texts by the structure named by Liberman as a molecular computer of the cell (MCC), which includes DNA, RNA, and the corresponding enzymes that work with molecular addresses. The main feature of the biological computer is the search for addresses using the thermal Brownian motion and the complex formation of weak bonds without the cost of free energy. The implementation of genetic programs takes place not only in the course of individual development, characterized by the encoding of the sequences of reading proteins, but also in the execution of instinctive behavior. The description of external reality occurs in terms of the genetic language in all living beings. In addition, the reality is universally described in the natural (human) language. In both cases, the description is implemented in the form of using models, the calculation of which allows prediction of the future of the simulated reality and its management. The success of such control depends on the choice of model and the correct scale, which determines the energy and time spent on the calculation. This quantity, equal to the production of energy and time, is quantized and is related to Planck's constant. An attempt has been made to construct a semantic system of the genetic language, for which a deliberately narrowed but instrumental definition of "text" and "meaning" is given.

关键词： Biological computer Encoding Genetic language natural algorithm Noosphere

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Analytical Methods on Computational Capabilities of Multi-Parameter natural algorithm 7

Analytical Methods on Computational Capabilities of Multi-Pa...

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7th International Symposium on Computational Intelligence and Design (ISCID)

作者： Li Jianhua Wei Xing Lanzhou Univ Technol Sch Mech & Elect Engn Lanzhou Peoples R China Lanzhou Univ Technol Sch Comp & Commun Lanzhou Peoples R China

ISBN: (纸本)9781479970056

Concerning the Computational capabilities of Multi-parameter natural algorithm, the Mathematical statistical analysis method using multi-indicators has been proposed. These indicators include the calculation central tendency, the dispersion trends and data distribution, which can clearly reflect the natural algorithm computational capabilities for specific problems, and reveal the influence of different parameters on the process of algorithms calculation. Finally, the immune clone operator is taken as an Analysis case. the experimental data has given the rule of the influence of computing power in different parameters.

关键词： natural algorithm Immune clone operator Computational capabilities

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On the Convergence Time of a natural Dynamics for Linear Programming

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algorithmICA 2020年第2期82卷 300-315页

作者： Bonifaci, Vincenzo CNR IASI Natl Res Council Italy Rome Italy

We consider a system of nonlinear ordinary differential equations for the solution of linear programming (LP) problems that was first proposed in the mathematical biology literature as a model for the foraging behavior of acellular slime mold Physarum polycephalum, and more recently considered as a method to solve LP instances. We study the convergence time of the continuous Physarum dynamics in the context of the linear programming problem, and derive a new time bound to approximate optimality that depends on the relative entropy between projected versions of the optimal point and of the initial point. The bound scales logarithmically with the LP cost coefficients and linearly with the inverse of the relative accuracy, establishing the efficiency of the dynamics for arbitrary LP instances with positive costs.

关键词： Linear programming natural algorithm Physarum dynamics Relative entropy Mirror Descent

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natural computation and its limits: Efim Liberman at the dawn of a new science

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BIOSYSTEMS 2022年 215卷 104653-104653页

作者： Shklovskiy-Kordi, Nikita E. Igamberdiev, Abir U. Natl Res Ctr Hematol Moscow Russia Mem Univ Newfoundland Dept Biol St John NF Canada

Efim A. Liberman (1925-2011) can be considered as a founder of the new field of science that explores natural computation and its limits. He named it Chaimatics and suggested its generalization to the ultimate all-encompassing theory that unites biology, physics and mathematics. He made a number of experimental discoveries, including color coding in the retina, the participation mechanisms of Ca2+ ions in synaptic transmission, and the measurement of potential in the coupling membranes of mitochondria and chloroplasts. He also made a decisive contribution to the proof of the chemiosmotic hypothesis of oxidative phosphorylation. In a series of works started in 1972, Liberman developed the concept of the molecular computer of the cell, which includes the programs written on DNA and RNA nucleotide sequences and executed by enzymes playing the role of processing units whereas nucleotide sequences are interpreted as commands and addresses. In this framework, Liberman predicted RNA splicing before its discovery and suggested the role of processing of small informational molecules (later defined as small RNAs) in controlling biological processes. Efim Liberman defined the fundamental property of life as a molecular and quantum computational system and introduced the idea of quantum computing inside a cell for making decisions on complex control tasks described by equations of mathematical physics. He approached the brain as a net of molecular computers and created a model of neuron operation based on the transmission of hypersound signals via cytoskeleton where the molecular computational system encodes the digital output. In 1979 Liberman published a hypothesis of human self-consciousness associated with not a chemical, but with a physical quantum coherent system and named it "extremal quantum regulator ". We review here the contributions of Liberman in understanding the mechanisms of intracellular processing of information and his efforts to create an integrative theory

关键词： Efim Liberman Quantum computation Biological computation Unity of science Encoding Genetic language natural algorithm Molecular computer of the cell Quantum regulator

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On the Convergence Time of a natural Dynamics for Linear Programming 28

On the Convergence Time of a Natural Dynamics for Linear Pro...

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28th International Symposium on algorithms and Computation (ISAAC)

作者： Bonifaci, Vincenzo CNR IASI Natl Res Council Italy Rome Italy

ISBN: (纸本)9783959770545

关键词： Linear programming natural algorithm Physarum dynamics Relative entropy Mirror Descent

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Physarum can compute shortest paths: A short proof

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INFORMATION PROCESSING LETTERS 2013年第1-2期113卷 4-7页

作者： Bonifaci, Vincenzo CNR Ist Anal Sistemi & Informat Antonio Ruberti Rome Italy

The purpose of this note is to give a short proof that a standard model for the Physarum polycephalum slime mold correctly computes the shortest path in an undirected weighted graph [V. Bonifaci, K. Mehlhorn, G. Varma, Physarum can compute shortest paths, in: Proc. of the 23rd ACM-SIAM Symposium on Discrete algorithms, SIAM, 2012, pp. 233-240]. (c) 2012 Elsevier B.V. All rights reserved.

关键词： Combinatorial problems natural algorithm Shortest path Thomson's principle

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Physarum can compute shortest paths

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JOURNAL OF THEORETICAL BIOLOGY 2012年 309卷 121-133页

作者： Bonifaci, Vincenzo Mehlhorn, Kurt Varma, Girish CNR Ist Anal Sistemi & Informat Antonio Ruberti Rome Italy MPI Informat Saarbrucken Germany Tata Inst Fundamental Res Mumbai 400005 Maharashtra India

Physarum polycephalum is a slime mold that is apparently able to solve shortest path problems. A mathematical model has been proposed by Tero et al. (Journal of Theoretical Biology, 244, 2007, pp. 553-564) to describe the feedback mechanism used by the slime mold to adapt its tubular channels while foraging two food sources so and s(1). We prove that, under this model, the mass of the mold will eventually converge to the shortest s(0)-s(1) path of the network that the mold lies on, independently of the structure of the network or of the initial mass distribution. This matches the experimental observations by Tero et al. and can be seen as an example of a "natural algorithm", that is, an algorithm developed by evolution over millions of years. (C) 2012 Elsevier Ltd. All rights reserved.

关键词： Slime mold natural algorithm natural adaptive networks

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