CBR and MBR techniques: review for an application in the emergencies domain

The purpose of this document is to provide an in-depth analysis of current reasoning engine practice and the integration strategies of Case Based Reasoning and Model Based Reasoning that will be used in the design and development of the RIMSAT system. RIMSAT (Remote Intelligent Management Support and Training) is a European Commission funded project designed to: a.. Provide an innovative, 'intelligent', knowledge based solution aimed at improving the quality of critical decisions b.. Enhance the competencies and responsiveness of individuals and organisations involved in highly complex, safety critical incidents - irrespective of their location. In other words, RIMSAT aims to design and implement a decision support system that using Case Base Reasoning as well as Model Base Reasoning technology is applied in the management of emergency situations. This document is part of a deliverable for RIMSAT project, and although it has been done in close contact with the requirements of the project, it provides an overview wide enough for providing a state of the art in integration strategies between CBR and MBR technologies.Postprint (published version

An Overview of Semi-Quantitative, Qualitative and Knowledge-Based System Methodologies Relevant to Solid Waste Disposal Site Design in Arid and Semiarid Environments

This paper provides an overview of the methodologies and techniques currently being employed in geotechnical engineering and engineering geology fields and examines their relevance to waste disposal site design in arid and semi-arid environments. The methodologies covered are: semi-quantitative, qualitative and knowledge-based systems. Various fundamentals and limitations associated with each of the techniques are discussed. The combination of semi-quantitative and qualitative techniques in developing Knowledge-Based System Model Methodologies for evaluating the performance and design of waste disposal sites in arid and semiarid environments can provide relevant and sufficient data, and reduce uncertainty in the final results. However, such systems should be aimed at giving advice rather than attempting to replace human expertise

Enhancing sustainability and resilience through multi-level infrastructure planning

[EN] Resilient planning demands not only resilient actions, but also resilient implementation, which promotes adaptive capacity for the attainment of the planned objectives. This requires, in the case of multi-level infrastructure systems, the simultaneous pursuit of bottom-up infrastructure planning for the promotion of adaptive capacity, and of top-down approaches for the achievement of global objectives and the reduction of structural vulnerabilities and imbalances. Though several authors have pointed out the need to balance bottom-up flexibility with top-down hierarchical control for better plan implementation, very few methods have yet been developed with this aim, least of all with a multi-objective perspective. This work addressed this lack by including, for the first time, the mitigation of urban vulnerability, the improvement of road network condition, and the minimization of the economic cost as objectives in a resilient planning process in which both actions and their implementation are planned for a controlled, sustainable development. Building on Urban planning support system (UPSS), a previously developed planning tool, the improved planning support system affords a planning alternative over the Spanish road network, with the best multi-objective balance between optimization, risk, and opportunity. The planning process then formalizes local adaptive capacity as the capacity to vary the selected planning alternative within certain limits, and global risk control as the duties that should be achieved in exchange. Finally, by means of multi-objective optimization, the method reveals the multi-objective trade-offs between local opportunity, global risk, and rights and duties at local scale, thus providing deeper understanding for better informed decision-making.This research was funded by the Spanish Ministry of Economy and Competitiveness, along with FEDER, grant number Project: BIA2017-85098-R.Salas, J.; Yepes, V. (2020). Enhancing sustainability and resilience through multi-level infrastructure planning. International Journal of Environmental research and Public Health. 17(3):1-22. https://doi.org/10.3390/ijerph17030962S122173Holling, C. S. (2004). From Complex Regions to Complex Worlds. Ecology and Society, 9(1). doi:10.5751/es-00612-090111Sharifi, A., & Yamagata, Y. (2014). Resilient Urban Planning: Major Principles and Criteria. Energy Procedia, 61, 1491-1495. doi:10.1016/j.egypro.2014.12.154Chen, Z., & Qiu, B. (2015). Resilient Planning Frame for Building Resilient Cities. 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Technology and Management Applied in Construction Engineering Projects

This book focuses on fundamental and applied research on construction project management. It presents research papers and practice-oriented papers. The execution of construction projects is specific and particularly difficult because each implementation is a unique, complex, and dynamic process that consists of several or more subprocesses that are related to each other, in which various aspects of the investment process participate. Therefore, there is still a vital need to study, research, and conclude the engineering technology and management applied in construction projects. This book present unanimous research approach is a result of many years of studies, conducted by 35 well experienced authors. The common subject of research concerns the development of methods and tools for modeling multi-criteria processes in construction engineering

Software tools for the cognitive development of autonomous robots

Robotic systems are evolving towards higher degrees of autonomy. This paper reviews the cognitive tools available nowadays for the fulfilment of abstract or long-term goals as well as for learning and modifying their behaviour.Peer ReviewedPostprint (author's final draft

Mining Aircraft Telemetry Data With Evolutionary Algorithms

The Ganged Phased Array Radar - Risk Mitigation System (GPAR-RMS) was a mobile ground-based sense-and-avoid system for Unmanned Aircraft System (UAS) operations developed by the University of North Dakota. GPAR-RMS detected proximate aircraft with various sensor systems, including a 2D radar and an Automatic Dependent Surveillance - Broadcast (ADS-B) receiver. Information about those aircraft was then displayed to UAS operators via visualization software developed by the University of North Dakota. The Risk Mitigation (RM) subsystem for GPAR-RMS was designed to estimate the current risk of midair collision, between the Unmanned Aircraft (UA) and a General Aviation (GA) aircraft flying under Visual Flight Rules (VFR) in the surrounding airspace, for UAS operations in Class E airspace (i.e. below 18,000 feet MSL). However, accurate probabilistic models for the behavior of pilots of GA aircraft flying under VFR in Class E airspace were needed before the RM subsystem could be implemented. In this dissertation the author presents the results of data mining an aircraft telemetry data set from a consecutive nine month period in 2011. This aircraft telemetry data set consisted of Flight Data Monitoring (FDM) data obtained from Garmin G1000 devices onboard every Cessna 172 in the University of North Dakota\u27s training fleet. Data from aircraft which were potentially within the controlled airspace surrounding controlled airports were excluded. Also, GA aircraft in the FDM data flying in Class E airspace were assumed to be flying under VFR, which is usually a valid assumption. Complex subpaths were discovered from the aircraft telemetry data set using a novel application of an ant colony algorithm. Then, probabilistic models were data mined from those subpaths using extensions of the Genetic K-Means (GKA) and Expectation- Maximization (EM) algorithms. The results obtained from the subpath discovery and data mining suggest a pilot flying a GA aircraft near to an uncontrolled airport will perform different maneuvers than a pilot flying a GA aircraft far from an uncontrolled airport, irrespective of the altitude of the GA aircraft. However, since only aircraft telemetry data from the University of North Dakota\u27s training fleet were data mined, these results are not likely to be applicable to GA aircraft operating in a non-training environment