No More Privacy Any More?

The embodiment of the potential loss of privacy through a combination of artificial intelligence algorithms, big data analytics and Internet of Things technology might be something as simple, yet potentially terrifying, as an integrated app capable of recognising anyone, anytime, anywhere: effectively a global ‘Shazam for People’; but one additionally capable of returning extremely personal material about the individual. How credible is such a system? How many years away? And what might stop it

Principles of Cost Minimisation in Wireless Networks

This paper considers variations of the minimum connected vertex cover problem to be found in the study of wireless network design. A simple, theoretic formulation is followed by a discussion of practical constraints. Two algorithms are given and results compared

Artificial intelligence and machine learning for efficient minefield clearance

Landmines, particularly anti-personnel mines, are dreadful instruments of war. Mines can remain in the ground for decades and injure or kill long after the original conflict. Clearing mines is a dangerous, time consuming and expensive task. Fortunately, mine clearing already has well established and documented processes. To further support these efforts a new research project has started at Wrexham Glyndŵr University to explore the use of machine learning to create a prediction model able to better suggest the positions of hidden landmines based on locations of those already found. Research in psychology and computer science demonstrates the difficulty for humans and machines to create true randomness in their actions. The project will investigate whether it is possible to discover hidden patterns or sequences in mine deployment that could give hints where to look for more. The advantage of the envisioned technique is a lightweight data set only comprising numerical values and their simple acquisition in the field. The proposed system will support – not replace – conventional technology. Although machine learning and A.I. can discover structures, patterns and sequences in a huge data set, that humans cannot, it remains a form of prediction. The aim is therefore not to declare the ground safe (‘cleared’) but to give suggestions where additional explosives are likely to be found and thus, it is proposed, help to direct mine clearing resources better

Performance Evaluation of The Split Transmission in Multihop Wireless Networks

Multimedia applications in multihop wireless networks have great market potential. Multiple channels and multiple radios are commonly used for exploring multimedia transmissions in multihop wireless networks. Split transmission allows multiple channels attached to different radios simultaneously to be used, and so to achieve a fundamentally improved transmission capacity. The goal of this paper is to present a theoretical background to justify the improved performance of split transmission. We believe that this is the first attempt to consider split transmission in theory

Some Notes and Results on Bandwidth-based Routing and Implicit Load Balancing

The Maximum Bandwidth Path Algorithm (MBPA) is introduced as an alternative to Dijkstra’s Shortest Path Algorithm (DSPA) for Internet routing. The two are compared and differences noted. Of particular interest is the extent to which each algorithm achieves Implicit Load Balancing (ILB) – the principle of effective link usage for traffic across the network as a whole for non-equal paths and without the use of explicit routing variance. Although MBPA may prove to be more efficient than DSPA generally (further work is required), it is shown, through extensive simulation, that it produces better levels of ILB for real, as opposed to artificial, network scenarios

Complexity Issues in Control Software Design: A practical perspective

There is a tendency to overlook or play down software issues in industrial systems design. However the very best hardware will only be as effective as the programs that control it. The search for a software solution to a problem should not stop with the discovery of the first approach that works, or appears to work. Many problems support good and bad methods of solution and determining the best often requires deeper consideration. In this paper we present some rudimentary introductions and examples of common computational challenges. We aim to highlight key issues for consideration when implementing control systems which otherwise might be unintentionally overlooked

Audio Compression Exploiting Repetition (ACER): Challenges and Solutions

This paper presents issues relating to information and musical content dealt with as part of the development of an innovative audio compression system, designed to exploit repetition sequences in audio, and particularly, music. The paper briefly introduces and describes how musical content and structure within audio can be exploited to achieve compression. A new system to take advantage of these hypotheses is described. The paper introduces a new file format to deal with high-level data chunks and repetitive structuring. The practicalities of searching for large blocks of audio data are discussed and evidence provided of the high amounts of complexity involved in performing brute-force searches for self-similar matching. This high complexity is the subject of current work by the authors and research to date so far reveals that search time can be reduced by considering content analysis, this time to reduce complexity rather than data volume

Realistic Large-Scale Network Optimisation

This paper considers communication network design problems that arise in the real world, with large numbers of nodes - and link and switch costs dependent upon their traffic capacity. Such costs, in turn, depend upon network topology so are not fixed at the start of, or through, any optimisation process. Realistic topological restrictions are also discussed. The limitations of conventional approaches – both constructive and search based – are noted and the requirements of practical optimisation methods explored. Two workable approaches to network design - one an established local search variant, another a more novel geometric approach – are introduced and combined. Various simple and compound algorithms, ranging from exhaustive search to fast heuristic are compared with experimental results given in conclusion

Advances in Similarity-Based Audio Compression

Existing lossy audio compression techniques such as MP3, WMA and Ogg Vorbis, for example, demonstrate great success in providing compression ratios which successfully reduce the data size from the original sampled audio. These techniques employ psychoacoustic models and traditional statistical coding techniques to achieve data reduction. However, these methods do not take into account the perceived content of the audio, which is often particularly relevant in musical audio. In this paper, we present our research and development work completed to date, in producing a system for audio analysis, which will consider and exploit the repetitive nature of audio and the similarities which frequently occur in audio recordings. We demonstrate the feasibility and scope of the analysis system and consider the techniques and challenges that are employed to achieve data reduction

Virtual Backbone Configuration in Wireless Mesh Networks

This paper introduces methods for the minimisation of virtual backbone size in wireless mesh networks, subject to practical constraints. The methods are centralised, which limits their usage to static applications. Four algorithms are presented, one exact and three heuristic. The exact method guarantees to find an optimal solution but runs in exponential time. Of the three heuristics, one is shown to match the performance of the optimal algorithm for all problem instances tested. The problem is constrained to introduce potentially massive levels of redundancy into the network topology, making the designs survivable