Improving Quality of the Solution for the Team Formation Problem in Social Networks Using SCAN Variant and Evolutionary Computation

Social Network Analysis helps to visualize and understand the roles and relationships that ease or impede the collaboration and sharing of the information and knowledge in an organization. In this research work, we will focus on the Team Formation Problem (TFP) which is an open problem where we need to identify an ideal team, with members of complementary talent or skills, to solve any given task. Current research suggests that TFP solutions have been attempted with evolutionary computation approach using Cultural Algorithms (CA) and Genetic Algorithms (GA). However, SCAN (Structural Clustering Algorithm for Networks) variants such as WSCAN (Weighted Structural Clustering Algorithm for Networks) demonstrate a high capability to find solutions for another type of network problems. In this thesis, we first propose to use WSCAN-TFP algorithm to deal with the problem of team formation in social networks, and we our findings indicate that WSCAN-TFP algorithm worked faster than the evolutionary algorithms counterparts but was of lower performance compared to CAs and GAs. Next, we propose two hybrid solutions by combining GA and CA with a modified WSCAN-TFP algorithm. To test the performance of our proposed approaches, we define multiple quality criteria based on communication cost (CC), average fitness score (AFS) and average processing time. We used big datasets from DBLP nodes network with sizes 50K and 100K. The results show that our proposed methods HGA and HCA can find the near-optimal solutions faster with minimum communication cost with the improvement of $\approx 66\%$ and $\approx 57\%$ in average fitness in comparison to existing GA and CA methods respectively

Activities of the Space Advanced Research Team at the University of Glasgow

A wide range of technologies and methodologies for space systems engineering are currently being developed at the University of Glasgow. Much of the work is centred on mission analysis and trajectory optimisation, complemented by research activities in autonomous and multi-agent systems. This paper will summarise these activities to provide a broad overview of the current research interests of the Space Advanced Research Team (SpaceART). It will be seen that although much of the work is mission driven and focussed on possible future applications, some activities represent basic research in space systems engineering

An Experimental Platform for Multi-spacecraft Phase-Array Communications

The emergence of small satellites and CubeSats for interplanetary exploration will mean hundreds if not thousands of spacecraft exploring every corner of the solar-system. Current methods for communication and tracking of deep space probes use ground based systems such as the Deep Space Network (DSN). However, the increased communication demand will require radically new methods to ease communication congestion. Networks of communication relay satellites located at strategic locations such as geostationary orbit and Lagrange points are potential solutions. Instead of one large communication relay satellite, we could have scores of small satellites that utilize phase arrays to effectively operate as one large satellite. Excess payload capacity on rockets can be used to warehouse more small satellites in the communication network. The advantage of this network is that even if one or a few of the satellites are damaged or destroyed, the network still operates but with degraded performance. The satellite network would operate in a distributed architecture and some satellites maybe dynamically repurposed to split and communicate with multiple targets at once. The potential for this alternate communication architecture is significant, but this requires development of satellite formation flying and networking technologies. Our research has found neural-network control approaches such as the Artificial Neural Tissue can be effectively used to control multirobot/multi-spacecraft systems and can produce human competitive controllers. We have been developing a laboratory experiment platform called Athena to develop critical spacecraft control algorithms and cognitive communication methods. We briefly report on the development of the platform and our plans to gain insight into communication phase arrays for space.Comment: 4 pages, 10 figures, IEEE Cognitive Communications for Aerospace Applications Worksho

Space activities in Glasgow; advanced microspacecraft from Scotland

The City of Glasgow is renowned for its engineering and technological innovation; famous Glaswegian inventors and academics include James Watt (Steam Engine) and John Logie Baird (television), amongst many others. Contemporary Glasgow continues to pioneer and invent in a multitude of areas of science and technology and has become a centre of excellence in many fields of engineering; including spacecraft engineering. This paper will discuss how Clyde Space Ltd and the space groups at both Glasgow and Strathclyde Universities are combining their knowledge and expertise to develop an advanced microspacecraft platform that will enable a step change in the utility value of miniature spacecraft. The paper will also explore how the relationship between the academic and industrial partners works in practice and the steps that have been taken to harness resulting innovation to create space industry jobs within a city that was, until recently, void of any commercial space activity

New evolutionary models for pre-main sequence and main sequence low-mass stars down to the hydrogen-burning limit

We present new models for low-mass stars down to the hydrogen-burning limit that consistently couple atmosphere and interior structures, thereby superseding the widely used BCAH98 models. The new models include updated molecular linelists and solar abundances, as well as atmospheric convection parameters calibrated on 2D/3D radiative hydrodynamics simulations. Comparison of these models with observations in various colour-magnitude diagrams for various ages shows significant improvement over previous generations of models. The new models can solve flaws that are present in the previous ones, such as the prediction of optical colours that are too blue compared to M dwarf observations. They can also reproduce the four components of the young quadruple system LkCa 3 in a colour-magnitude diagram with one single isochrone, in contrast to any presently existing model. In this paper we also highlight the need for consistency when comparing models and observations, with the necessity of using evolutionary models and colours based on the same atmospheric structures.Comment: 7 pages, 8 figures, Astronomy & Astrophysics in pres

Co-evolutionary dynamics in strategic alliances : the influence of the industry lifecycle

This study examines the application of the co-evolution literature to strategic alliance formation in SME’s in the UK and Australia in two differing industries at different stages of the industry life-cycle. Extending the framework developed by Das and Teng (2002) and that of Wilson and Hynes (2009), it engages with wider industry and environmental characteristics present in these two countries, specifically examining whether different theories of alliance formation are better suited to different stages of an industry life cycle. The issues discussed above are explored and developed through the use of a qualitative case study approach. Findings indicate strong resource-based drivers for alliance formation in both industries, with firms dependent on the co-evolution of their alliances and indeed selected by the results of their alliance participation. However, differences emerged in the strategic use of alliances in these two industries. The influence of the stage of the industry life cycle on this is discussed