Machine Education: Designing semantically ordered and ontologically guided modular neural networks

The literature on machine teaching, machine education, and curriculum design for machines is in its infancy with sparse papers on the topic primarily focusing on data and model engineering factors to improve machine learning. In this paper, we first discuss selected attempts to date on machine teaching and education. We then bring theories and methodologies together from human education to structure and mathematically define the core problems in lesson design for machine education and the modelling approaches required to support the steps for machine education. Last, but not least, we offer an ontology-based methodology to guide the development of lesson plans to produce transparent and explainable modular learning machines, including neural networks.Comment: IEEE Symposium Series on Computational Intelligence, 201

Informal Color Communication on Newly Decorated Interiors of the University North

The fact is that the energy of each tone of colors has emotional and psychological features, which is used as a tool in informal communication with the aim of long-term memory. Despite the importance of color experience in spaces, only a few studies were conducted on the topic. The aim of this paper was to explore the influence of color experience on the premises of the University North, University Center Varaždin. This paper explores and analyzes experience and satisfaction with warm and cold colors, measures the students’ degree of noticing certain colors in space, i.e. associating certain colors on the University’s ground floor or the first floor to a product or company. Furthermore, this paper examines the evironmental color impact of lecture halls that are painted white, blue, brown or a reddish color. In the design of the University North premises, the emphasis was put on the act of entering into main lecture halls, where wall colors had to match the colors of the University logo. Since the University logo has only two color tones; it is predominantly red, and therefore, when painting the entrance spaces, the emphasis was put on the color white, which, psychologically, makes a space seem bigger and brighter. The last question in the questionnaire was on the color that remained in the long-term memory, and the largest number of respondents opted for the color red. The survey was conducted on 315 students from the University North. Statistical data processing was performed using descriptive statistics. The study has proved that the red tone, although present in a small amount, confirms an affiliation to the University when it comes to informal communication

Path Planning for Shepherding a Swarm in a Cluttered Environment using Differential Evolution

Shepherding involves herding a swarm of agents (\emph{sheep}) by another a control agent (\emph{sheepdog}) towards a goal. Multiple approaches have been documented in the literature to model this behaviour. In this paper, we present a modification to a well-known shepherding approach, and show, via simulation, that this modification improves shepherding efficacy. We then argue that given complexity arising from obstacles laden environments, path planning approaches could further enhance this model. To validate this hypothesis, we present a 2-stage evolutionary-based path planning algorithm for shepherding a swarm of agents in 2D environments. In the first stage, the algorithm attempts to find the best path for the sheepdog to move from its initial location to a strategic driving location behind the sheep. In the second stage, it calculates and optimises a path for the sheep. It does so by using \emph{way points} on that path as the sequential sub-goals for the sheepdog to aim towards. The proposed algorithm is evaluated in obstacle laden environments via simulation with further improvements achieved

Adaptive topologies: improving wireless networks through the use of additional nodes and power control.

The work presented in this thesis shows that shared spectrum wireless networks can be enhanced through the use of additional nodes and power control. Network improvement is demonstrated in three key areas: connectivity, capacity and power efficiency. It is also shown that the techniques developed to increase network capacity and power efficiency have a positive effect on the security of the network. Mobile ad hoc networks are the specific focus of the work, but the results are applicable to both wireless sensor networks and shared spectrum wireless infrastructure based networks. This thesis demonstrates how additional nodes may be used in mobile wireless networks to maintain connectivity by specifically targeting bridges and articulation points. It then takes a graph theoretical approach to networking, with the assumption that lowering interference increases network capacity, to show that additional nodes combined with power control can be used to simultaneously increase the capacity and power efficiency of wireless networks. An implementation of a novel method to generate all possible transmission states under a Request To Send (RTS) / Clear To Send (CTS) scheme is used in the creation of a repeatable metric, Uniform Average Network Capacity (UANC). This metric describes the capacity that can be held within a network, and is suitable for comparing one network to another, enabling its use in optimisations. UANC is used in a multi objective cross entropy optimisation of capacity and power efficiency to create Pareto optimal sets of viable network topologies which exhibit high capacity and low power use. The work presented then derives the conditions under which n simultaneous transmissions are beneficial to capacity. This leads to the definition of a separation multiplier, i.e., the ratio of distances between receivers and between senders and their receivers, which is used to create wireless networks which exhibit high UANC. The separation multiplier is then utilised in existing networks, where topologies are altered through the modification of transmission powers and the use of additional nodes, to create higher capacity networks, showing that additional nodes can benefit network capacity. This technique has the added benefit of increasing network power efficiency. A modification to the RTS/CTS protocol which uses the separation multiplier is then presented. The new scheme has the effect of allowing only beneficial simultaneous transmissions to occur. It is shown through simulation that this approach increases network capacity. Networks which implement the capacity and power efficiency enhancing measures presented are shown to exhibit increased security, in that the lowering of transmission power and allowance of multiple transmissions within the network reduces the distance at which trans- missions can be detected and decoded. Finally, an implementation of the overall knowledge gained through the thesis is presented, augmenting existing networks with additional nodes and power control to create bi-connected, power efficient and high capacity networks.Thesis (Ph.D.) -- University of Adelaide, School of Electrical and Electronic Engineering, 201

A swarm intelligent approach to data ferrying in sparse disconnected networks

<p>Swarming and emergent behaviour techniques can offer simple control schemes for the organisation of many nodes, with little communications overhead and processing time. These mechanisms are robust against node losses, and are able to run on cheap, disposable platforms. This article examines the usefulness of a swarming technique to address data ferrying in disconnected networks to provide delay-tolerant type communications. Mathematical analysis of a pheromone-based ferrying approach reveals a robust solution to the round-robin ferrying problem. Simulation results from static and dynamic network topologies agree with the mathematical model and show encouraging results in coordinating data ferries in a disconnected environment.</p> <p>A simulated scenario of UAVs intelligently ferrying data between deployed tactical nodes in a RF contested environment.</p