404 research outputs found

    Advances and Applications of DSmT for Information Fusion. Collected Works, Volume 5

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    This fifth volume on Advances and Applications of DSmT for Information Fusion collects theoretical and applied contributions of researchers working in different fields of applications and in mathematics, and is available in open-access. The collected contributions of this volume have either been published or presented after disseminating the fourth volume in 2015 in international conferences, seminars, workshops and journals, or they are new. The contributions of each part of this volume are chronologically ordered. First Part of this book presents some theoretical advances on DSmT, dealing mainly with modified Proportional Conflict Redistribution Rules (PCR) of combination with degree of intersection, coarsening techniques, interval calculus for PCR thanks to set inversion via interval analysis (SIVIA), rough set classifiers, canonical decomposition of dichotomous belief functions, fast PCR fusion, fast inter-criteria analysis with PCR, and improved PCR5 and PCR6 rules preserving the (quasi-)neutrality of (quasi-)vacuous belief assignment in the fusion of sources of evidence with their Matlab codes. Because more applications of DSmT have emerged in the past years since the apparition of the fourth book of DSmT in 2015, the second part of this volume is about selected applications of DSmT mainly in building change detection, object recognition, quality of data association in tracking, perception in robotics, risk assessment for torrent protection and multi-criteria decision-making, multi-modal image fusion, coarsening techniques, recommender system, levee characterization and assessment, human heading perception, trust assessment, robotics, biometrics, failure detection, GPS systems, inter-criteria analysis, group decision, human activity recognition, storm prediction, data association for autonomous vehicles, identification of maritime vessels, fusion of support vector machines (SVM), Silx-Furtif RUST code library for information fusion including PCR rules, and network for ship classification. Finally, the third part presents interesting contributions related to belief functions in general published or presented along the years since 2015. These contributions are related with decision-making under uncertainty, belief approximations, probability transformations, new distances between belief functions, non-classical multi-criteria decision-making problems with belief functions, generalization of Bayes theorem, image processing, data association, entropy and cross-entropy measures, fuzzy evidence numbers, negator of belief mass, human activity recognition, information fusion for breast cancer therapy, imbalanced data classification, and hybrid techniques mixing deep learning with belief functions as well

    Tradition and Innovation in Construction Project Management

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    This book is a reprint of the Special Issue 'Tradition and Innovation in Construction Project Management' that was published in the journal Buildings

    Managing distributed situation awareness in a team of agents

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    The research presented in this thesis investigates the best ways to manage Distributed Situation Awareness (DSA) for a team of agents tasked to conduct search activity with limited resources (battery life, memory use, computational power, etc.). In the first part of the thesis, an algorithm to coordinate agents (e.g., UAVs) is developed. This is based on Delaunay triangulation with the aim of supporting efficient, adaptable, scalable, and predictable search. Results from simulation and physical experiments with UAVs show good performance in terms of resources utilisation, adaptability, scalability, and predictability of the developed method in comparison with the existing fixed-pattern, pseudorandom, and hybrid methods. The second aspect of the thesis employs Bayesian Belief Networks (BBNs) to define and manage DSA based on the information obtained from the agents' search activity. Algorithms and methods were developed to describe how agents update the BBN to model the system’s DSA, predict plausible future states of the agents’ search area, handle uncertainties, manage agents’ beliefs (based on sensor differences), monitor agents’ interactions, and maintains adaptable BBN for DSA management using structural learning. The evaluation uses environment situation information obtained from agents’ sensors during search activity, and the results proved superior performance over well-known alternative methods in terms of situation prediction accuracy, uncertainty handling, and adaptability. Therefore, the thesis’s main contributions are (i) the development of a simple search planning algorithm that combines the strength of fixed-pattern and pseudorandom methods with resources utilisation, scalability, adaptability, and predictability features; (ii) a formal model of DSA using BBN that can be updated and learnt during the mission; (iii) investigation of the relationship between agents search coordination and DSA management

    A Bayesian Network Approach for Product Safety Risk Management

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    A new method for safety risk management and assessment using Bayesian networks is proposed to resolve limitations of existing methods and to ensure that products and systems available on the market are acceptably safe for use. The method is applicable to a wide range of products and systems, ranging from consumer goods through to medical devices, and even complex systems such as aircraft. While methods such as Fault Tree Analysis (FTA) and Failure Mode and Effects Analysis (FMEA) have been used quite effectively in safety assessment for certain classes of critical systems, they have several limitations which are addressed by the proposed Bayesian network (BN) method. In particular, the BN approach enables us to combine multiple sources of knowledge and data to provide quantified, auditable risk estimates at all stages of a product’s life cycle, including especially when there are limited or no testing or operational safety data available. The BN approach also enables us to incorporate different perceptions of risk, including taking account of personal differences in the perceived benefits of the product under assessment. The proposed BN approach provides a means for safety regulators, manufacturers, risk professionals, and even individuals to better assess safety and risk. It is powerful and flexible, can complement traditional safety and risk assessment methods, and is applicable to a far greater range of products and systems. The method can also be used to validate the results of traditional safety and risk assessment methods when relevant data become available. It is demonstrated and validated using case studies from consumer product safety risk assessment and medical device risk management

    A systematic risk management model for construction project management: a case study of the new infrastructure project in the University of Mpumalanga

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    The construction industry has become the significant player in the economy of many developed and developing countries in the world. The industry contributes to the Gross Domestic Product (GDP) and employment rate of many nations. As such, the industry is the engine for the economic development and growth across the world. Recently, African countries have received global attention due to its calls for massive infrastructure development and maintenance thereof. Accordingly, the South African government has adopted a National Infrastructure Development Plan (NIDP), which seeks not only to transform the economic landscape of the country, but also to support the integration of the African economies through infrastructure development. To ensure that the execution of these infrastructure projects is successfully delivered in terms of time, cost, and scope; project risk management in the construction industry has become an important area of interest in the execution and delivery of the infrastructure projects. However, the constantly increasing complexity and dynamics in the delivery of construction projects have serious effects on the risk management processes during the execution of the project. In practice, risk methods and techniques have proven to be unrealistic when using the traditional risk management approach in the context of the complexity and dynamic environments wherein construction projects are delivered. Worryingly, project management practitioners in engineering and construction projects still lack the holistic and systematic insight and understanding of construction projects when applying the risk management procedures in the complex and dynamic projects environments. As a result, there are growing reports of unsatisfactory delivery of construction projects in terms of time, cost, quality, and environmental objectives. In this regard, the call for embracing the systems thinking paradigm as the alternative approach that will provide more clarity in dealing with the complex management challenges and which will gradually substitute the traditional theoretical approach of dealing with construction project management, is becoming prominent. Against this background, this study uses a multiple case study approach to explore how a systematic risk management approach could be developed and applied towards successful delivery of construction projects, and subsequently to propose a systematic risk management model that is designed to depict and grasp the underlying complexities and dynamics embedded ix | P a g e in construction projects. The choice of the case study design is founded on its utility and appropriateness for in-depth investigations into phenomena in its context as well as its usefulness for exploratory studies. Therefore, to explore the risk management phenomenon in real-life settings, the unit of analysis in this study was based on three construction projects built in one of the new Institutions of Higher Learning in South Africa during the period between 2017 and 2019. Notwithstanding the unique characteristics of these projects, the complexity and dynamic environments of these projects also emanated from the facts that i) the successful delivery of the projects was a predecessor activity to the academic schedule and activities; ii) this was one of the first universities to be built by the democratic Republic of South Africa; and, iii) the construction contract used for the delivery of the construction projects is relatively new to the professionals in the country’s construction industry. This qualitative case study design has its backbone in the constructivism philosophical paradigm which is underpinned by the ontology that there are multiple realities as conceptualized, experienced, and perceived by the people in their real-life situations or natural settings. Accordingly, the construction professionals, projects’ documents as well as field work observations were purposively chosen as the essential and reliable methods of data collection for this case study. For analysis, a conventional content data analysis methodology was applied on the empirical data that was obtained from the multiple data sources to provide a clearer understanding of the contexts in which the risk management for construction projects is performed. Accordingly, a qualitative data analysis software system called MAXQDA was used to enable the performance of data coding, managing coding, and eventually the retrieving of the coded segments in a form of visual models and summary tables. Ultimately, the qualitative content analysis approach in this thesis was performed in terms of a ‘critical filter of thick description’ which involved a balanced approach between the deductive analysis and the inductive analysis processes. With the assistance of the MAXQDA, performing the multiple levels coding and analysis processes in this thesis has not only been efficient, but also more reliable. To shed insight into the empirical findings of the study, a hybrid theoretical framework has been applied in the discussion and interpretation of the findings. The theoretical framework of this study is underpinned by the complexity theory and the theory of systems engineering. The applicability of these theories in this study is essential in providing a x | P a g e systematic and logical explanation of the practices of risk management in construction projects and further helps to explain why particular events occurred in the processes of risk management. Eventually, the theoretical framework has enabled the designing and developing of a systematic risk management model that will assist in depicting and grasping the underlying complexities while supporting proactive decision making in the delivery of construction projects. To this end, this study has made several major contributions in three multiple folds in the body of knowledge. Firstly, this study makes theoretical contributions by developing an empirically underpinned systematic risk management model which provide more clarity on comprehending the multifaceted and complex risk factors embedded in construction projects. Secondly, the qualitative case study approach and the associated analysis methods thereof in this thesis provides novelty and lays the groundwork for future research and methodological replicability in another similar phenomenon elsewhere in the world. Thirdly, this study has gone some way towards expanding the understanding and the basis for managerial decision making in relation to front-end planning and proactive approach for risk management, and eventually to improve projects’ performances on cost, time, scope, and environmental sustainability. In this regard, the key practical implication for project management practitioners is that the adoption and embracing of the systematic and holistic thinking approach in the risk management processes could enhance the successful delivery of construction projects. In the literature, there is paucity and need for more research into the exploration and analysis of the integration and interplay between the systems engineering and complexity perspectives and the other knowledge areas in the PMBOK. In conclusion, this thesis therefore argues that to address the deficiencies in risk management practices during construction projects’ delivery, the solution requires a paradigm shift from the traditional linear approach which, by design, overlooks the complexities, non-linearity and interdependences of the elements that are underpinning and characterizing the nature of the contemporary construction projects. Therefore, this thesis supports the increasingly emerging debate on the discourse that the superior traditional and linear approaches do not solve the current problems, and as such they should be replaced with the systems and holistic thinking approach that will provide more clarity in dealing with the complex management challenges in contemporary construction projects.Thesis (PhD) -- Faculty of Engineering, Built environment and Information Technology, School of the built Environment 202

    Operational Research: methods and applications

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    This is the final version. Available on open access from Taylor & Francis via the DOI in this recordThroughout its history, Operational Research has evolved to include methods, models and algorithms that have been applied to a wide range of contexts. This encyclopedic article consists of two main sections: methods and applications. The first summarises the up-to-date knowledge and provides an overview of the state-of-the-art methods and key developments in the various subdomains of the field. The second offers a wide-ranging list of areas where Operational Research has been applied. The article is meant to be read in a nonlinear fashion and used as a point of reference by a diverse pool of readers: academics, researchers, students, and practitioners. The entries within the methods and applications sections are presented in alphabetical order. The authors dedicate this paper to the 2023 Turkey/Syria earthquake victims. We sincerely hope that advances in OR will play a role towards minimising the pain and suffering caused by this and future catastrophes

    Measurable Safety of Automated Driving Functions in Commercial Motor Vehicles

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    With the further development of automated driving, the functional performance increases resulting in the need for new and comprehensive testing concepts. This doctoral work aims to enable the transition from quantitative mileage to qualitative test coverage by aggregating the results of both knowledge-based and data-driven test platforms. The validity of the test domain can be extended cost-effectively throughout the software development process to achieve meaningful test termination criteria

    Sensing the Cultural Significance with AI for Social Inclusion

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    Social Inclusion has been growing as a goal in heritage management. Whereas the 2011 UNESCO Recommendation on the Historic Urban Landscape (HUL) called for tools of knowledge documentation, social media already functions as a platform for online communities to actively involve themselves in heritage-related discussions. Such discussions happen both in “baseline scenarios” when people calmly share their experiences about the cities they live in or travel to, and in “activated scenarios” when radical events trigger their emotions. To organize, process, and analyse the massive unstructured multi-modal (mainly images and texts) user-generated data from social media efficiently and systematically, Artificial Intelligence (AI) is shown to be indispensable. This thesis explores the use of AI in a methodological framework to include the contribution of a larger and more diverse group of participants with user-generated data. It is an interdisciplinary study integrating methods and knowledge from heritage studies, computer science, social sciences, network science, and spatial analysis. AI models were applied, nurtured, and tested, helping to analyse the massive information content to derive the knowledge of cultural significance perceived by online communities. The framework was tested in case study cities including Venice, Paris, Suzhou, Amsterdam, and Rome for the baseline and/or activated scenarios. The AI-based methodological framework proposed in this thesis is shown to be able to collect information in cities and map the knowledge of the communities about cultural significance, fulfilling the expectation and requirement of HUL, useful and informative for future socially inclusive heritage management processes

    Jornadas Nacionales de Investigación en Ciberseguridad: actas de las VIII Jornadas Nacionales de Investigación en ciberseguridad: Vigo, 21 a 23 de junio de 2023

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    Jornadas Nacionales de Investigación en Ciberseguridad (8ª. 2023. Vigo)atlanTTicAMTEGA: Axencia para a modernización tecnolóxica de GaliciaINCIBE: Instituto Nacional de Cibersegurida

    Operational research:methods and applications

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    Throughout its history, Operational Research has evolved to include a variety of methods, models and algorithms that have been applied to a diverse and wide range of contexts. This encyclopedic article consists of two main sections: methods and applications. The first aims to summarise the up-to-date knowledge and provide an overview of the state-of-the-art methods and key developments in the various subdomains of the field. The second offers a wide-ranging list of areas where Operational Research has been applied. The article is meant to be read in a nonlinear fashion. It should be used as a point of reference or first-port-of-call for a diverse pool of readers: academics, researchers, students, and practitioners. The entries within the methods and applications sections are presented in alphabetical order
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