1 Graphical modeling using L-systems.- 1.1 Rewriting systems.- 1.2 DOL-systems.- 1.3 Turtle interpretation of strings.- 1.4 Synthesis of DOL-systems.- 1.4.1 Edge rewriting.- 1.4.2 Node rewriting.- 1.4.3 Relationship between edge and node rewriting.- 1.5 Modeling in three dimensions.- 1.6 Branching structures.- 1.6.1 Axial trees.- 1.6.2 Tree OL-systems.- 1.6.3 Bracketed OL-systems.- 1.7 Stochastic L-systems.- 1.8 Context-sensitive L-systems.- 1.9 Growth functions.- 1.10 Parametric L-systems.- 1.10.1 Parametric OL-systems.- 1.10.2 Parametric 2L-systems.- 1.10.3 Turtle interpretation of parametric words.- 2 Modeling of trees.- 3 Developmental models of herbaceous plants.- 3.1 Levels of model specification.- 3.1.1 Partial L-systems.- 3.1.2 Control mechanisms in plants.- 3.1.3 Complete models.- 3.2 Branching patterns.- 3.3 Models of inflorescences.- 3.3.1 Monopodial inflorescences.- 3.3.2 Sympodial inflorescences.- 3.3.3 Polypodial inflorescences.- 3.3.4 Modified racemes.- 4 Phyllotaxis.- 4.1 The planar model.- 4.2 The cylindrical model.- 5 Models of plant organs.- 5.1 Predefined surfaces.- 5.2 Developmental surface models.- 5.3 Models of compound leaves.- 6 Animation of plant development.- 6.1 Timed DOL-systems.- 6.2 Selection of growth functions.- 6.2.1 Development of nonbranching filaments.- 6.2.2 Development of branching structures.- 7 Modeling of cellular layers.- 7.1 Map L-systems.- 7.2 Graphical interpretation of maps.- 7.3 Microsorium linguaeforme.- 7.4 Dryopteris thelypteris.- 7.5 Modeling spherical cell layers.- 7.6 Modeling 3D cellular structures.- 8 Fractal properties of plants.- 8.1 Symmetry and self-similarity.- 8.2 Plant models and iterated function systems.- Epilogue.- Appendix A Software environment for plant modeling.- A.1 A virtual laboratory in botany.- A.2 List of laboratory programs.- Appendix B About the figures.- Turtle interpretation of symbols.

/pdf/the-algorithmic-beauty-of-plants-4f9yunhil9.pdf

The Algorithmic Beauty of Plants

コンピュータ・サイエンス : ACM computing surveys

The aim of this chapter is to generalize concepts and techniques of formal language theory to two dimensions. Informally, a two-dimensional string is called a picture and is defined as a rectangular array of symbols taken from a finite alphabet. A two-dimensional language (or picture language) is a set of pictures.

Two-dimensional languages

With the widespread adoption of the Internet of Things (IoT), the number of connected devices is growing at an exponential rate, which is contributing to ever-increasing, massive data volumes. Real-time analytics on the massive IoT data, referred to as the “real-time IoT analytics” in this paper, is becoming the mainstream with an aim to provide an immediate or non-immediate actionable insights and business intelligence. However, the analytics network of the existing IoT systems does not adequately consider the requirements of the real-time IoT analytics. In fact, most researchers overlooked an appropriate design of the IoT analytics network while focusing much on the sensing and delivery networks of the IoT system. Since much of the IoT analytics network has often been taken as granted, the survey, in this paper, we aim to review the state-of-the-art of the analytics network methodologies, which are suitable for real-time IoT analytics. In this vein, we first describe the basics of the real-time IoT analytics, use cases, and software platforms, and then explain the shortcomings of the network methodologies to support them. To address those shortcomings, we then discuss the relevant network methodologies which may support the real-time IoT analytics. Also, we present a number of prospective research problems and future research directions focusing on the network methodologies for the real-time IoT analytics.

A Survey on Network Methodologies for Real-Time Analytics of Massive IoT Data and Open Research Issues

A new method for generating pictures is presented and illustrated with examples. The idea is to generate a string of symbols using an L−system, and to interpret this string as a sequence of commands which control a "turtle". Suitable generalizations of the notions of the L−system and of a turtle are introduced. The resulting mathematical model can be used to create a variety of (finite approximations of) fractal curves, ranging from Koch curves, to classic space−filling curves, to relatively realistic−looking pictures of plants and trees. All these pictures are defined in a uniform and compact way.

http://algorithmicbotany.org/papers/graphical.gi86.pdf

Graphical applications of L-systems

Let qt q2 be univalent in t:= {z : Iz I < I} We give some applications of first order differential superordinations to obtain sufficient conditions for normalized analytic functions {(z) to satisfy

/pdf/differential-sandwich-theorems-for-certain-analytic-48xazyajae.pdf

Differential sandwich theorems for certain analytic functions

We consider array languages (sets of pictures consisting of symbols placed in the lattice points of the 2D grid) and the possibility to handle them with P systems. After proving binary normal forms for array matrix grammars (which, even in the case when no appearance checking is used, are known to generate the array languages of arbitrary array grammars), we prove that the P systems with context-free rules (with three membranes and no control on the communication or the use of rules) are computationally universal, able to generate all computable array languages. Some open problems are also formulated.

Array-rewriting P systems

Spiking neural P systems with anti-spikes (ASN P systems, for short) are a variant of spiking neural P systems, which were inspired by inhibitory impulses/spikes or inhibitory synapses. In this work, we consider normal forms of ASN P systems. Specifically, we prove that ASN P systems with pure spiking rules of categories (a, a) and (a, a) without forgetting rules are universal as number generating devices. In an ASN P system with spiking rules of categories (a, a) and (a, a) without forgetting rules, the neurons change spikes to anti-spikes or change anti-spikes to spikes; such systems are proved to be universal. We also prove that ASN P systems with inhibitory synapses using pure spiking rules of category (a, a) and forgetting rules are universal. These results answer an open problem and improve a corresponding result from [IJCCC, IV(3), 2009, 273-282].

Normal Forms of Spiking Neural P Systems With Anti-Spikes

Subclasses of uniformly convex and uniformly starlike functions

Circular strings representing DNA molecules and certain recombinant behaviour are formalized. Various actions of splicing schemes on linear and circular DNA molecules are examined. It is shown that there is a difference in the regularity result of Culik and Harju [1] between the linear and circular strings. A consequence of this result is that a conjecture of Head [4] that the circular string language of a splicing system under an action on circular strings is regular, when the set of initial circular strings is regular, is disproved.

K. G. Subramanian

Papers

Differential sandwich theorems for certain analytic functions

Array-rewriting P systems

Normal Forms of Spiking Neural P Systems With Anti-Spikes

Subclasses of uniformly convex and uniformly starlike functions

Circular DNA and Splicing Systems