Performance of biologically inspired algorithms tuned on TiO2 nanoparticle benchmark system

A novel approach of integrating two swarm intelligence algorithms is considered, one simulating the behaviour of birds flocking (Particle Swarm Optimisation) and the other one (Stochastic Diffusion Search) mimics the recruitment behaviour of one species of ants – Leptothorax acervorum. This hybrid algorithm is assisted by a biological mechanism inspired by the behaviour of blood flow and cells in blood vessels, where the concept of high and low blood pressure is utilised. The performance of the nature-inspired algorithms and the biologically inspired mechanisms in the hybrid algorithm is reflected through a cooperative attempt to make a drawing on the canvas. The scientific value of the marriage between the two swarm intelligence algorithms is currently being investigated thoroughly on many benchmarks, and the results reported suggest a promising prospect (al-Rifaie, Bishop & Blackwell, 2011). It may also be discussed whether or not the artworks generated by nature and biologically inspired algorithms can possibly be considered as computationally creative.

Download Full-text

Biologically Inspired and Agent-Based Algorithms for Music

10.1093/oxfordhb/9780190226992.013.18 ◽

2018 ◽

Author(s):

Alice Eldridge ◽

Oliver Bown

Keyword(s):

Contemporary Music ◽

Adaptive Behaviour ◽

Biologically Inspired ◽

Agent Based ◽

Agent Based Modelling ◽

Music Making ◽

Algorithmic Music ◽

Biologically Inspired Algorithms ◽

Systems Art ◽

Future Work

This chapter examines a range of approaches to algorithmic music making inspired by biological systems, and considers topics at the intersection of contemporary music, computer science, and computational creativity. A summary of core precursor movements both within and beyond musical practice (A Life, cybernetics, systems art, etc.) sets the scene, before core models and algorithms are introduced and illustrated. These include evolutionary algorithms, agent-based modelling and self-organizing systems, adaptive behaviour and interactive performance systems, and ecosystemic approaches to composition and computational creative discovery. The chapter closes by reviewing themes for future work in this area: autonomy and agency, and the poetics of biologically inspired algorithms.

Download Full-text

Chaotic-Based and Biologically Inspired Cryptosystems for Secure Image Communication and Storage

Improving Information Security Practices through Computational Intelligence - Advances in Information Security, Privacy, and Ethics ◽

10.4018/978-1-4666-9426-2.ch004 ◽

2016 ◽

pp. 74-98

Author(s):

El-Sayed M. El-Alfy

Keyword(s):

Chaos Theory ◽

Data Encryption ◽

Sensitive Data ◽

Biologically Inspired ◽

Image Communication ◽

Work Related ◽

Biologically Inspired Algorithms ◽

And Storage ◽

Crossover And Mutation

Protecting confidentiality of sensitive data is growing in importance in many personal, commercial, governmental, medical and military applications. Data encryption remains the most prevalent mechanism for this goal in cybersecurity to store and communicate data in unintelligible form. However, images are known to have intrinsic characteristics different from text, which limit the applicability of conventional cryptographic algorithms. This chapter provides a review of the work related to image cryptosystems based on chaos theory and biologically-inspired algorithms. Then, a case study is presented using ideas from genetic crossover and mutation to confuse and diffuse images to generate secure cipher images with very low correlation between pixels.

Download Full-text