A framework for extracting and representing project knowledge contexts using topic models and dynamic knowledge maps

There is still a lack of effective paradigms and tools for analysing and discovering the contents and relationships of project knowledge contexts in the field of project management. In this paper, a new framework for extracting and representing project knowledge contexts using topic models and dynamic knowledge maps under big data environments is proposed and developed. The conceptual paradigm, theoretical underpinning, extended topic model, and illustration examples of the ontology model for project knowledge maps are presented, with further research work envisaged.

Territories of scarcity and creativity: a critical view of informal settlements and emerging tactics under conditions of scarcity in Nairobi, Kenya and Quito, Ecuador

This thesis explores the processes through which scarcity is constructed in informal settlements and how conditions emerging within its limits gives way to particular socio-spatial phenomena and influence the emergence of self-organisation and creative strategies from a non-expert perspective. At the same time, this thesis deconstructs these emerging tactics (reactive and transformative) in a diagrammatic way to generate a critical study of their potential for socio-spatial change that goes beyond the everyday survival. Most people associate scarcity with “not having enough” of something, most usually of a material nature. In contrast, this paper is based on the premise that scarcity is a constructed condition, therefore exploring it beyond its immediate manifestation and illustrating its discursive, distributive and socio-material components. In this line, the research uses Assemblage Theory as both an approach and a tool for analysis. This approach allows the research to depart from everyday narratives of the residents, and gradually evolve into a multi-scalar, non-linear reading of scarcity, by following leads into different realms and unpacking a series of routine events to uncover their connections to wider processes and particular elements affecting the settlement and the city as a whole. For this purpose, the research is based on a qualitative, flexible and multi-sited methodology, using different case studies as testing grounds. Collected data stems from a 11-months ethnographic fieldwork in informal settlements in Ecuador and Kenya, analysing the socio-spatial practices and strategies deployed by the different actors producing the built environment and arising from everyday and latent experiences of scarcity. The thesis examines the multi-scalar nature of these strategies, including self-building and management tactics, the mobilisation of grassroots organisations, the innovative ways of collaborating deployed by different coalitions and the reformulation of urban development policies. As outcomes of the research, the thesis will show illustrative diagrams that allow a better understanding of, firstly, the construction of scarcity in the built environment beyond its immediate manifestation and secondly, the way that emerging tactics a) improve existing conditions of scarcity, b) reinforce the status quo or c) contribute to the worsening of the original condition. Therefore, this thesis aims to offer lessons with both practical and theoretical considerations, by firstly, giving an insight into the complexity and transcalar nature of the construction of scarcity in informal settlements; secondly, by illustrating how acute conditions related to scarcity gives birth to a plethora of particular phenomena shaping the territory, social relationships and processes; and thirdly, by identifying specific characteristics within the informal that might allow for new readings of the city and possibilities for socio-spatial change under conditions of scarcity.

LUTI models, freight transport and freight facility location

The subject of this book is the new scientific research in the field of modelling the interaction between land use and transport (LUTI modelling). Transport and the location of activities in space have been important themes of study in engineering, social sciences and urban and regional planning

The Data of Things: Strategies, Patterns and Practice of Cloud-based Participatory Sensing

The broad capabilities of current mobile devices have paved the way for Mobile Crowd Sensing (MCS) applications. The success of this emerging paradigm strongly depends on the quality of received data which, in turn, is contingent to mass user participation; the broader the participation, the more useful these systems become. However, there is an ongoing trend that tries to integrate MCS applications with emerging computing paradigms such as cloud computing. The intuition is that such a transition can significantly improve the overall efficiency while at the same time it offers stronger security and privacy-preserving mechanisms for the end-user. In this position paper, we dwell on the underpinnings of incorporating cloud computing techniques to facilitate the vast amount of data collected in MCS applications. That is, we present a list of core system, security and privacy requirements that must be met if such a transition is to be successful. To this end, we first address several competing challenges not previously considered in the literature such as the scarce energy resources of battery-powered mobile devices as well as their limited computational resources that they often prevent the use of computationally heavy cryptographic operations and thus offering limited security services to the end-user. Finally, we present a use case scenario as a comprehensive example. Based on our findings, we posit open issues and challenges, and discuss possible ways to address them, so that security and privacy do not hinder the migration of MCS systems to the cloud.

Risk Modelling Framework for Emergency Hospital Readmission, Using Hospital Episode Statistics Inpatient Data

The objective of this study was to develop, test and benchmark a framework and a predictive risk model for hospital emergency readmission within 12 months. We performed the development using routinely collected Hospital Episode Statistics data covering inpatient hospital admissions in England. Three different timeframes were used for training, testing and benchmarking: 1999 to 2004, 2000 to 2005 and 2004 to 2009 financial years. Each timeframe includes 20% of all inpatients admitted within the trigger year. The comparisons were made using positive predictive value, sensitivity and specificity for different risk cut-offs, risk bands and top risk segments, together with the receiver operating characteristic curve. The constructed Bayes Point Machine using this feature selection framework produces a risk probability for each admitted patient, and it was validated for different timeframes, sub-populations and cut-off points. At risk cut-off of 50%, the positive predictive value was 69.3% to 73.7%, the specificity was 88.0% to 88.9% and sensitivity was 44.5% to 46.3% across different timeframes. Also, the area under the receiver operating characteristic curve was 73.0% to 74.3%. The developed framework and model performed considerably better than existing modelling approaches with high precision and moderate sensitivity.

Business Process Modelling based on formal temporal theory with an application to hospital patient flows

Existing Workflow Management Systems (WFMSs) follow a pragmatic approach. They often use a proprietary modelling language with an intuitive graphical layout. However the underlying semantics lack a formal foundation. As a consequence, analysis issues, such as proving correctness i.e. soundness and completeness, and reliable execution are not supported at design level. This project will be using an applied ontology approach by formally defining key terms such as process, sub-process, action/task based on formal temporal theory. Current business process modelling (BPM) standards such as Business Process Modelling Notation (BPMN) and Unified Modelling Language (UML) Activity Diagram (AD) model their constructs with no logical basis. This investigation will contribute to the research and industry by providing a framework that will provide grounding for BPM to reason and represent a correct business process (BP). This is missing in the current BPM domain, and may result in reduction of the design costs and avert the burden of redundant terms used by the current standards. A graphical tool will be introduced which will implement the formal ontology defined in the framework. This new tool can be used both as a modelling tool and at the same time will serve the purpose of validating the model. This research will also fill the existing gap by providing a unified graphical representation to represent a BP in a logically consistent manner for the mainstream modelling standards in the fields of business and IT. A case study will be conducted to analyse a catalogue of existing ‘patient pathways’ i.e. processes, of King’s College Hospital NHS Trust including current performance statistics. Following the application of the framework, a mapping will be conducted, and new performance statistics will be collected. A cost/benefits analysis report will be produced comparing the results of the two approaches.

A general framework for Business Process Modelling (BPM) based on Formal Temporal Theory with an application to Hospital Patient flows

Existing Workflow Management Systems (WFMSs) follow a pragmatic approach. They often use a proprietary modelling language with an intuitive graphical layout. However the underlying semantics lack a formal foundation. As a consequence, analysis issues, such as proving correctness i.e. soundness and completeness, and reliable execution are not supported at design level. This project will be using an applied ontology approach by formally defining key terms such as process, sub-process, action/task based on formal temporal theory. Current business process modelling (BPM) standards such as Business Process Modelling Notation (BPMN) and Unified Modelling Language (UML) Activity Diagram (AD) model their constructs with no logical basis. This investigation will contribute to the research and industry by providing a framework that will provide grounding for BPM to reason and represent a correct business process (BP). This is missing in the current BPM domain, and may result in reduction of the design costs and avert the burden of redundant terms used by the current standards. A graphical tool will be introduced which will implement the formal ontology defined in the framework. This new tool can be used both as a modelling tool and at the same time will serve the purpose of validating the model. This research will also fill the existing gap by providing a unified graphical representation to represent a BP in a logically consistent manner for the mainstream modelling standards in the fields of business and IT. A case study will be conducted to analyse a catalogue of existing ‘patient pathways’ i.e. processes, of King’s College Hospital NHS Trust including current performance statistics. Following the application of the framework, a mapping will be conducted, and new performance statistics will be collected. A cost/benefits analysis report will be produced comparing the results of the two approaches.

Methods, Models & Systems for Dealing with Some Business, Management & Engineering Problems

This keynote presentation will report some of our research work and experience on the development and applications of relevant methods, models, systems and simulation techniques in support of different types and various levels of decision making for business, management and engineering. In particular, the following topics will be covered. Modelling, multi-agent-based simulation and analysis of the allocation management of carbon dioxide emission permits in China (Nanfeng Liu & Shuliang Li Agent-based simulation of the dynamic evolution of enterprise carbon assets (Yin Zeng & Shuliang Li) A framework & system for extracting and representing project knowledge contexts using topic models and dynamic knowledge maps: a big data perspective (Jin Xu, Zheng Li, Shuliang Li & Yanyan Zhang) Open innovation: intelligent model, social media & complex adaptive system simulation (Shuliang Li & Jim Zheng Li) A framework, model and software prototype for modelling and simulation for deshopping behaviour and how companies respond (Shawkat Rahman & Shuliang Li) Integrating multiple agents, simulation, knowledge bases and fuzzy logic for international marketing decision making (Shuliang Li & Jim Zheng Li) A Web-based hybrid intelligent system for combined conventional, digital, mobile, social media and mobile marketing strategy formulation (Shuliang Li & Jim Zheng Li) A hybrid intelligent model for Web & social media dynamics, and evolutionary and adaptive branding (Shuliang Li) A hybrid paradigm for modelling, simulation and analysis of brand virality in social media (Shuliang Li & Jim Zheng Li) Network configuration management: attack paradigms and architectures for computer network survivability (Tero Karvinen & Shuliang Li)