SWARMs Ontology: A Common Information Model for the Cooperation of Underwater Robots

In order to facilitate cooperation between underwater robots, it is a must for robots to exchange information with unambiguous meaning. However, heterogeneity, existing in information pertaining to different robots, is a major obstruction. Therefore, this paper presents a networked ontology, named the Smart and Networking Underwater Robots in Cooperation Meshes (SWARMs) ontology, to address information heterogeneity and enable robots to have the same understanding of exchanged information. The SWARMs ontology uses a core ontology to interrelate a set of domain-specific ontologies, including the mission and planning, the robotic vehicle, the communication and networking, and the environment recognition and sensing ontology. In addition, the SWARMs ontology utilizes ontology constructs defined in the PR-OWL ontology to annotate context uncertainty based on the Multi-Entity Bayesian Network (MEBN) theory. Thus, the SWARMs ontology can provide both a formal specification for information that is necessarily exchanged between robots and a command and control entity, and also support for uncertainty reasoning. A scenario on chemical pollution monitoring is described and used to showcase how the SWARMs ontology can be instantiated, be extended, represent context uncertainty, and support uncertainty reasoning.Eurpean Commission, H2020, 66210

Geração automática de ontologias probabilísticas a partir de um modelo UMP-ST

Trabalho de Conclusão de Curso (graduação)—Universidade de Brasília, Instituto de Ciências Exatas, Departamento de Ciência da Computação, 2017.O URP-ST é uma metodologia baseada no processo unificado que orienta o engenheiro de ontologias durante a construção de ontologias probabilísticas por meio de uma série de etapas que englobam desde a modelagem até a realização de inferências. A etapa de modelagem é definida pelo UMP-ST, uma metodologia iterativa e incremental voltada para a maioria das tecnologias semânticas. Uma delas é o PR-OWL, uma linguagem para a representação do MEBN. A modelagem de ontologias probabilísticas a partir do UMP-ST utilizando MEBN/PR-OWL pode ser realizada no UnBBayes, um framework para a construção gráfica de modelos probabilísticos e a realização de raciocínio plausível. Apesar da orientação dada pelo UMP-ST, a modelagem de ontologias probabilísticas é uma tarefa penosa e repetitiva. Durante a implementação do modelo, é necessário a construção da ontologia a partir do zero utilizando um determinada tecnologia semântica, além da modelagem feita no UMP-ST. Uma integração apropriada que ajude o usuário a implementar a ontologia, tal como um estrutura intermediária, agilizaria e facilitaria a sua implementação. Esse trabalho propõe um plug-in Java para o UnBBayes com o objetivo de automatizar o mapeamento de uma ontologia modelada via UMP ST em um modelo MEBN, permitindo ao usuário realizar inferências probabilísticas em ontologias com representação de conhecimento com ou sem incerteza probabilística.The URP-ST is a methodology based on the unified process that guides the ontology engineer in how to design Probabilistic Onologies. The UMP-ST is an incremental and iterative approach that covers the modeling step related to the URP-ST. It is a general methodology for the majority of the existing semantic technologies which support uncertainty. One of them is the PR-OWL, a language for MEBN representation. The modeling of probabilistic ontologies from the UMP-ST using MEBN / PR-OWL can be performed in UnBBayes, a framework for building probabilistic graphical models and performing plausible reasoning. Despite the guidance given by the UMP-ST, the implementation of a PO is a painful and repetitive task. During the implementation of the model, it is necessary to build the ontology from the zero using a specific semantic technology, even if the user models the PO in UMP-ST. A proper integration that helps the user to implement the PO, such as an intermediate structure, would expedite and facilitate its implementation. This work presents an automatic way to generate POs using MEBN representation from the UMP-ST model by mapping the elements of both sides. This is an extension of the UMP-ST to generate POs to an specific formalism and it is developed as a Java plug-in for UnBBayes

Inferring Complex Activities for Context-aware Systems within Smart Environments

The rising ageing population worldwide and the prevalence of age-related conditions such as physical fragility, mental impairments and chronic diseases have significantly impacted the quality of life and caused a shortage of health and care services. Over-stretched healthcare providers are leading to a paradigm shift in public healthcare provisioning. Thus, Ambient Assisted Living (AAL) using Smart Homes (SH) technologies has been rigorously investigated to help address the aforementioned problems. Human Activity Recognition (HAR) is a critical component in AAL systems which enables applications such as just-in-time assistance, behaviour analysis, anomalies detection and emergency notifications. This thesis is aimed at investigating challenges faced in accurately recognising Activities of Daily Living (ADLs) performed by single or multiple inhabitants within smart environments. Specifically, this thesis explores five complementary research challenges in HAR. The first study contributes to knowledge by developing a semantic-enabled data segmentation approach with user-preferences. The second study takes the segmented set of sensor data to investigate and recognise human ADLs at multi-granular action level; coarse- and fine-grained action level. At the coarse-grained actions level, semantic relationships between the sensor, object and ADLs are deduced, whereas, at fine-grained action level, object usage at the satisfactory threshold with the evidence fused from multimodal sensor data is leveraged to verify the intended actions. Moreover, due to imprecise/vague interpretations of multimodal sensors and data fusion challenges, fuzzy set theory and fuzzy web ontology language (fuzzy-OWL) are leveraged. The third study focuses on incorporating uncertainties caused in HAR due to factors such as technological failure, object malfunction, and human errors. Hence, existing studies uncertainty theories and approaches are analysed and based on the findings, probabilistic ontology (PR-OWL) based HAR approach is proposed. The fourth study extends the first three studies to distinguish activities conducted by more than one inhabitant in a shared smart environment with the use of discriminative sensor-based techniques and time-series pattern analysis. The final study investigates in a suitable system architecture with a real-time smart environment tailored to AAL system and proposes microservices architecture with sensor-based off-the-shelf and bespoke sensing methods. The initial semantic-enabled data segmentation study was evaluated with 100% and 97.8% accuracy to segment sensor events under single and mixed activities scenarios. However, the average classification time taken to segment each sensor events have suffered from 3971ms and 62183ms for single and mixed activities scenarios, respectively. The second study to detect fine-grained-level user actions was evaluated with 30 and 153 fuzzy rules to detect two fine-grained movements with a pre-collected dataset from the real-time smart environment. The result of the second study indicate good average accuracy of 83.33% and 100% but with the high average duration of 24648ms and 105318ms, and posing further challenges for the scalability of fusion rule creations. The third study was evaluated by incorporating PR-OWL ontology with ADL ontologies and Semantic-Sensor-Network (SSN) ontology to define four types of uncertainties presented in the kitchen-based activity. The fourth study illustrated a case study to extended single-user AR to multi-user AR by combining RFID tags and fingerprint sensors discriminative sensors to identify and associate user actions with the aid of time-series analysis. The last study responds to the computations and performance requirements for the four studies by analysing and proposing microservices-based system architecture for AAL system. A future research investigation towards adopting fog/edge computing paradigms from cloud computing is discussed for higher availability, reduced network traffic/energy, cost, and creating a decentralised system. As a result of the five studies, this thesis develops a knowledge-driven framework to estimate and recognise multi-user activities at fine-grained level user actions. This framework integrates three complementary ontologies to conceptualise factual, fuzzy and uncertainties in the environment/ADLs, time-series analysis and discriminative sensing environment. Moreover, a distributed software architecture, multimodal sensor-based hardware prototypes, and other supportive utility tools such as simulator and synthetic ADL data generator for the experimentation were developed to support the evaluation of the proposed approaches. The distributed system is platform-independent and currently supported by an Android mobile application and web-browser based client interfaces for retrieving information such as live sensor events and HAR results

Solving Multi-objective Integer Programs using Convex Preference Cones

Esta encuesta tiene dos objetivos: en primer lugar, identificar a los individuos que fueron víctimas de algún tipo de delito y la manera en que ocurrió el mismo. En segundo lugar, medir la eficacia de las distintas autoridades competentes una vez que los individuos denunciaron el delito que sufrieron. Adicionalmente la ENVEI busca indagar las percepciones que los ciudadanos tienen sobre las instituciones de justicia y el estado de derecho en Méxic

A framework for ethical sourcing of construction materials

Climate change and a speedily depreciating ecosystem are global challenges. These challenges are, in the main, attributed to activities in the construction industry, which relies heavily on the environment to provide materials. Studies show that the impact in developing countries is worse, due to the low level of awareness. Consequently, there is a dearth of research-based evidence on the ethics of sourcing of materials. This research aimed at changing that by investigating the ethics of materials sourcing in Nigeria. Epistemologically, the research is subjective and paradigmatically phenomenological. The methods used for data collection include a comprehensive literature review, collection of archival records, empirical studies of sixteen organisations that are involved in materials sourcing, transportation and production of eight construction materials across the six geo-political zones in Nigeria, that were purposefully selected. The findings reveal that the majority of the processes employed to source, transport and produce materials for the construction industry are not ethical environmentally due to their contribution to air pollution, water pollution, noise pollution and vibration, landscape damage, harm to flora and fauna and waste production. Furthermore, the study found that the majority of the organisations studied, do not produce sustainability reports for their operations. The study developed a framework for ethical sourcing of construction materials. The study recommends that organisations should utilise the framework developed in this study to enhance their sustainability practices

The 45th Australasian Universities Building Education Association Conference: Global Challenges in a Disrupted World: Smart, Sustainable and Resilient Approaches in the Built Environment, Conference Proceedings, 23 - 25 November 2022, Western Sydney University, Kingswood Campus, Sydney, Australia

This is the proceedings of the 45th Australasian Universities Building Education Association (AUBEA) conference which will be hosted by Western Sydney University in November 2022. The conference is organised by the School of Engineering, Design, and Built Environment in collaboration with the Centre for Smart Modern Construction, Western Sydney University. This year’s conference theme is “Global Challenges in a Disrupted World: Smart, Sustainable and Resilient Approaches in the Built Environment”, and expects to publish over a hundred double-blind peer review papers under the proceedings