This paper presents a brief review of some existing correlation models which attempt to map Quality of Service (QoS)

This paper explores the idea that it may be possible to combine two ideas -UAV flocking, and wireless cluster computing -in a single system, the UltraSwarm. The possible advantages of such a system are considered, and solutions to some of the technical problems are identified. Initial work on constructing such a system based around miniature electric helicopters is described. INTRODUCTIONAt one time or another we have all been impressed by the sheer agility of a flock of starlings flying in a city square at dusk -wheeling and manoeuvring so swiftly and precisely as to create the illusion of a single and very superior controlling intelligence. Artificial flock and swarm systems exploiting these abilities, which thanks to the seminal work of Craig Reynolds [1] are now well understood, have been the focus of active research for almost twenty years. But there is another way of looking at a flock of starlings: a typical flock will contain upwards of a thousand birds, and each bird will contain a gram or so of brain tissue, so in the aggregate the flock will contain about the same amount as a single human brain. If there were some way in which the starlings' brains could be linked together to form one human-sized nervous system, could the flock collectively achieve something approaching a human level of intelligence?Of course, the knowledge that no such linkage is possible instantly takes the steam out of such a speculation (although some biologists have proposed analogies between ants and neurons, suggesting for example that the chemically-mediated interactions between individual ants in a colony and the chemically mediated interactions between individual neurons in a brain may support intelligent behavior in ways that are somehow similar). However, the constraints on the effective linkage of computational components clearly do not apply to artificial systems: the recent convergence between computation and communication means that distributed processing, in the form of cluster computing, is becoming the norm for highperformance computing. (In the latest top 500 supercomputer rankings, 58% are cluster machines.) In these clusters, large numbers of relatively low-powered computers are linked into a single architecture using highbandwidth (1 or 2 Gigabits/sec) wired network connections. Might it be possible to construct a flock of individually simple artificial agents that flew like a flock of starlings, but was also able to process information like a cluster-based supercomputer by using high-bandwidth wireless links between the agents' computational elements?We have named the general concept of combining swarm intelligence and wireless cluster computing the UltraSwarm. Although the genesis of the idea occurred in the context of flocking systems, the basic philosophy could also apply to swarm intelligence systems based on social insect behaviour. In both flock-based and social-insectbased UltraSwarms, the attraction lies in the potential for combining the two technologies of swarm intelligence and conventional c...

Abstract-Human-Computer Speech is gaining momentum as a technique of computer interaction. There has been a recent upsurge in speech based search engines and assistants such as Siri, Google Chrome and Cortana. Natural Language Processing (NLP) techniques such as NLTK for Python can be applied to analyse speech, and intelligent responses can be found by designing an engine to provide appropriate human like responses. This type of programme is called a Chatbot, which is the focus of this study. This paper presents a survey on the techniques used to design Chatbots and a comparison is made between different design techniques from nine carefully selected papers according to the main methods adopted. These papers are representative of the significant improvements in Chatbots in the last decade. The paper discusses the similarities and differences in the techniques and examines in particular the Loebner prizewinning Chatbots.

Abstract-Traditional marine monitoring systems such as oceanographic and hydrographic research vessels use either wireless sensor networks with a limited coverage, or expensive satellite communication that is not suitable for small and midsized vessels. This paper proposes a novel Internet of Marine Things (IoMaT) data acquisition and cartography system in the marine environment using Very High Frequency (VHF) available on the majority of ships. The proposed system is equipped with many sensors such as sea depth, temperature, wind speed and direction, and the collected data is sent to 5G edge cloudlets connected to sink/base station nodes on shore. The sensory data is ultimately aggregated at a central cloud on the internet to produce up to date cartography systems. Several observations and obstacles unique to the marine environment have been discussed and feed into the solutions presented. The impact of marine sparsity on the network is examined and a novel hybrid Mobile Ad-hoc/Delay Tolerant routing protocol (MADNET) is proposed to switch automatically between Mobile Ad-hoc Network (MANET) and Delay Tolerant Network (DTN) routing according to the network connectivity. The low rate data transmission offered by VHF radio has been investigated in terms of the network bottlenecks and the data collection rate achievable near the sinks. A data synchronization and transmission approach has also been proposed at the 5G network core using Information Centric Networks (ICN).

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