Exploring Swarm-Based Visual Effects

In this paper, we explore the visual effects of animated 2D line strokes and 3D cubes. A given 2D image is segmented into either 2D line strokes or 3D cubes. Each segmented object (i.e., line stroke or each cube) is initialised with the position and the colour of the corresponding pixel in the image. The program animates these objects using the boid framework. This simulates a flocking behavior of line strokes in a 2D space and cubes in a 3D space. In this implementation the animation runs in a cycle from the disintegration of the original image to a swarm of line strokes or 3D cubes, then the swarm moves about and then integrates back into the original image (an example clip has been uploaded to YouTube and can be viewed at https://www.youtube.com/watch?v=aV6h0VzTZ8)

Composing first species counterpoint with a variable neighbourhood search algorithm

In this article, a variable neighbourhood search (VNS) algorithm is developed that can generate musical fragments consisting of a melody for the cantus firmus and the first species counterpoint. The objective function of the algorithm is based on a quantification of existing rules for counterpoint. The VNS algorithm developed in this article is a local search algorithm that starts from a randomly generated melody and improves it by changing one or two notes at a time. A thorough parametric analysis of the VNS reveals the significance of the algorithm's parameters on the quality of the composed fragment, as well as their optimal settings. A comparison of the VNS algorithm with a developed genetic algorithm shows that the VNS is more efficient. The VNS algorithm has been implemented in a user-friendly software environment for composition, called Optimuse. Optimuse allows a user to specify a number of characteristics such as length, key and mode. Based on this information, Optimuse 'composes' both cantus firmus and first species counterpoint. Alternatively, the user may specify a cantus firmus, and let Optimuse compose the accompanying first species counterpoint. © 2012 Taylor & Francis

Evaluation of Musical Creativity and Musical Metacreation Systems

The field of computational creativity, including musical metacreation, strives to develop artificial systems that are capable of demonstrating creative behavior or producing creative artefacts. But the claim of creativity is often assessed, subjectively only on the part of the researcher and not objectively at all. This article provides theoretical motivation for more systematic evaluation of musical metacreation and computationally creative systems and presents an overview of current methods used to assess human and machine creativity that may be adapted for this purpose. In order to highlight the need for a varied set of evaluation tools, a distinction is drawn among three types of creative systems: those that are purely generative, those that contain internal or external feedback, and those that are capable of reflection and self-reflection. To address the evaluation of each of these aspects, concrete examples of methods and techniques are suggested to help researchers (1) evaluate their systems' creative process and generated artefacts, and test their impact on the perceptual, cognitive, and affective states of the audience, and (2) build mechanisms for reflection into the creative system, including models of human perception and cognition, to endow creative systems with internal evaluative mechanisms to drive self-reflective processes. The first type of evaluation can be considered external to the creative system and may be employed by the researcher to both better understand the efficacy of their system and its impact and to incorporate feedback into the system. Here we take the stance that understanding human creativity can lend insight to computational approaches, and knowledge of how humans perceive creative systems and their output can be incorporated into artificial agents as feedback to provide a sense of how a creation will impact the audience. The second type centers around internal evaluation, in which the system is able to reason about its own behavior and generated output. We argue that creative behavior cannot occur without feedback and reflection by the creative/metacreative system itself. More rigorous empirical testing will allow computational and metacreative systems to become more creative by definition and can be used to demonstrate the impact and novelty of particular approaches

Particle swarm optimization with area extension (AEPSO)

Particle Swarm Optimization (PSO) is one of the evolutionary algorithms which proved to be useful in solving multi-robots tasks. PSO outperforms other evolutionary algorithms, such as GA, in this area. In this paper we introduce a new modified version of PSO called Area Extension PSO (AEPSO). Information about the environment in extended area together with various heuristics improves the performance of each robot and the group. We believe this AEPSO is suitable to solve problems in environments with large area which have more similarity to real world robotic problems. The result of this study shows a magnificent improvement and the potential of AEPSO, especially in dynamic environments

Intelligent learning environment: Building hybrid system from standard application and web application

In this paper, we explore the idea of Intelligent Learning Environment (ILE) by building a system for teaching and learning music in a web-based environment. Our system is a framework that utilises existing web architecture. Instead of using a standard web browser as our client tool, we are going to develop our own. By following this, some design issues regarding the shifting and their solutions will be addressed. In a nutshell, this environment allows us to gain more control in monitoring students' learning activities within a single environment while keeping instructors away from a bundle of computer codes

Interactivities in music intelligent tutoring system

We report our work in progress in the area of music intelligent tutoring systems (MITS). We discuss the motivation behind the design of GUI that aim to support an interactive learning in the MITS environment. These interactivities include onscreen score editing and capturing student behaviours during tutorial sessions (e.g. feedbacks, queries, stream of action-events). In this report, we discuss our representation, then our design and finally present some interaction examples from our system

New operators of GA for improving the performance of high-level synthesis

Evolutionary algorithms (EAs) have been largely applied to optimization and synthesis of VLSI design. In spite of several successful applications and competitive solutions, the stochastic nature of EAs and the uncertainty of the results have considerably hindered their use in industrial applications. This paper describes an investigation and its results on an evolutionary approach to solving a particular class of highly constrained VLSI problem, the high-level synthesis (HLS). HLS, also called architectural synthesis, is the process of automatically generating a Register Transfer Level (RTL) design from a behavioral specification. Two significant features were added to the standard genetic algorithm (SGA): guided genetic operators based on directional mutation and selection tournaments based on genome vicinity. The approach generates offspring by preserving the building blocks of the parents. The experiment results show that the proposed GA is able to guarantee high performance and low variance in the results from different runs. Computational experiments over real test problems showed promising results

Metaheuristic methods in hybrid flow shop scheduling problem

Memetic algorithms are hybrid evolutionary algorithms that combine global and local search by using an evolutionary algorithm to perform exploration while the local search method performs exploitation. This paper presents two hybrid heuristic algorithms that combine particle swarm optimization (PSO) with simulated annealing (SA) and tabu search (TS), respectively. The hybrid algorithms were applied on the hybrid flow shop scheduling problem. Experimental results reveal that these memetic techniques can effectively produce improved solutions over conventional methods with faster convergence

Data encryption using event-related brain signals

A method based on event-related brain signal is used for data encryption. The idea is to shuffle the Huffman tree using an encryption key generated by electroencephalogram (EEG) signals recorded when the user perceives a common black and white line picture. As different persons have different thought processes, the generated key is unique to each individual and hence the encryption is robust to fraudulent attacks as compared to other encryption systems. Further, as Huffman tree is used to encode the data during encryption, the method achieves both compression and encryption. This pilot study has shown the huge potential of the method as it is impossible to be compromised