528 research outputs found

    Multidisciplinary perspectives on Artificial Intelligence and the law

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    This open access book presents an interdisciplinary, multi-authored, edited collection of chapters on Artificial Intelligence (‘AI’) and the Law. AI technology has come to play a central role in the modern data economy. Through a combination of increased computing power, the growing availability of data and the advancement of algorithms, AI has now become an umbrella term for some of the most transformational technological breakthroughs of this age. The importance of AI stems from both the opportunities that it offers and the challenges that it entails. While AI applications hold the promise of economic growth and efficiency gains, they also create significant risks and uncertainty. The potential and perils of AI have thus come to dominate modern discussions of technology and ethics – and although AI was initially allowed to largely develop without guidelines or rules, few would deny that the law is set to play a fundamental role in shaping the future of AI. As the debate over AI is far from over, the need for rigorous analysis has never been greater. This book thus brings together contributors from different fields and backgrounds to explore how the law might provide answers to some of the most pressing questions raised by AI. An outcome of the Católica Research Centre for the Future of Law and its interdisciplinary working group on Law and Artificial Intelligence, it includes contributions by leading scholars in the fields of technology, ethics and the law.info:eu-repo/semantics/publishedVersio

    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

    Usable Security. A Systematic Literature Review

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    Usable security involves designing security measures that accommodate users’ needs and behaviors. Balancing usability and security poses challenges: the more secure the systems, the less usable they will be. On the contrary, more usable systems will be less secure. Numerous studies have addressed this balance. These studies, spanning psychology and computer science/engineering, contribute diverse perspectives, necessitating a systematic review to understand strategies and findings in this area. This systematic literature review examined articles on usable security from 2005 to 2022. A total of 55 research studies were selected after evaluation. The studies have been broadly categorized into four main clusters, each addressing different aspects: (1) usability of authentication methods, (2) helping security developers improve usability, (3) design strategies for influencing user security behavior, and (4) formal models for usable security evaluation. Based on this review, we report that the field’s current state reveals a certain immaturity, with studies tending toward system comparisons rather than establishing robust design guidelines based on a thorough analysis of user behavior. A common theoretical and methodological background is one of the main areas for improvement in this area of research. Moreover, the absence of requirements for Usable security in almost all development contexts greatly discourages implementing good practices since the earlier stages of development

    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

    Disaster decision-making with a mixing regret philosophy DDAS method in Fermatean fuzzy number

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    In this paper, the use of the Fermatean fuzzy number (FFN) in a significant research problem of disaster decision-making by defining operational laws and score function is demonstrated. Generally, decision control authorities need to brand suitable and sensible disaster decisions in the direct conceivable period as unfitting decisions may consequence in enormous financial dead and thoughtful communal costs. To certify that a disaster comeback can be made, professionally, we propose a new disaster decision-making (DDM) technique by the Fermatean fuzzy Schweizer-Sklar environment. First, the Fermatean fuzzy Schweizer-Sklar operators are employed by decision-makers to rapidly analyze their indefinite and vague assessment information on disaster choices. Then, the DDM technique based on the FFN is planned to identify highly devastating disaster choices and the best available choices. Finally, the proposed regret philosophy DDM technique is shown functional to choose the ideal retort explanation for a communal fitness disaster in Pakistan. The dominance and realism of the intended technique are further defensible through a relative study with additional DDM systems

    Circular Economy and Sustainable Development: A Systematic Literature Review

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    Circular Economy put forth as an alternative to traditional linear model of extract-use-dispose along with the concept of Sustainable Development encompassing economic, environmental, and social aspects have garnered tremendous impetus among academics, practitioners and policymakers alike. The UN Sustainable Development Goals embraced by the member nations in 2015 based on the preceding Millenium Development Goals have been placed as the targets to be achieved as a part of holistic human development. In this backdrop, this paper examines the intersection of sustainability and circular economy with a focus on the three aspects of sustainable development, first the economic aspect by examining the relationship between GDP and circular economy, second the social economic aspect within the interaction of Circular Economy with Sustainable development and third the environmental-economical aspect by examining circularity and sustainability in waste management and waste valorisation. This paper achieves its objective through a systematic literature review of 1748 journal articles collected from Web of Science and SCOPUS database following PRISMA standards, network analysis of keywords, and manual review of texts. Four Research Questions are formulated: RQ1: What are the major emergent topics in Circular Economy and Sustainable Development and how are they related? RQ2: What is the relationship among CE and GDP in the CE and Sustainability? RQ3: What are the relationships between CE and Sustainability? RQ4: What are different use cases of valorisation of waste as CE tool, and can valorisation be sustainable? RQ1 is answered by presenting hotspot of research on Circular Economy and Sustainable Development through keywords occurrence network analysis using VosViewer. This study identifies three clusters and seven thematic areas of research, along with 25 most used keywords. RQ2 is attended through review of the relationship between economic growth (Gross Domestic Product) and Circular Economy and proposes based on the review that CE is still at its infancy. The paper also discusses the appropriateness of using GDP as a measure of sustainable development. This paper addresses RQ3 by examining the relationship between Circular Economy and Sustainable Development through review of literatures. The indicators used to measure CE and SD are also discussed and summarised. This review finds that achieving SDGs require greater effort, and that the present status of achievement is a bleak picture. Further, the role of waste management and potentiality of waste valorisation to aid in circular economy and sustainable development is analysed to answer RQ4. Though there are ample potential, however the recycle rate is very minimal to quench the required level of circularity. While CE and SD are related, CE cannot be a universal panacea to global challenges like emissions reduction, energy consumption, climate change, gender equality, poverty, well-being, environmental protection etc. even though the impact of CE to achieve SD can be substantial. The paper recommends avenues for future research and presents the conclusion of the study

    Mathematical Methods and Operation Research in Logistics, Project Planning, and Scheduling

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    In the last decade, the Industrial Revolution 4.0 brought flexible supply chains and flexible design projects to the forefront. Nevertheless, the recent pandemic, the accompanying economic problems, and the resulting supply problems have further increased the role of logistics and supply chains. Therefore, planning and scheduling procedures that can respond flexibly to changed circumstances have become more valuable both in logistics and projects. There are already several competing criteria of project and logistic process planning and scheduling that need to be reconciled. At the same time, the COVID-19 pandemic has shown that even more emphasis needs to be placed on taking potential risks into account. Flexibility and resilience are emphasized in all decision-making processes, including the scheduling of logistic processes, activities, and projects

    Design of an artificial intelligence model that refines the results of analysis in economic decision making. The case of final energy consumption in the UE

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    [ES] El objetivo de este Trabajo de Fin de Grado, titulado ‘Diseño de un modelo de Inteligencia Artificial que afina los resultados del análisis en la toma de decisiones en economía: el caso del consumo final de energía en la UE’, es arrojar luz sobre el potencial de la Inteligencia Artificial (IA) para el proceso de toma de decisiones. El estudio comienza estableciendo las bases del enfoque tradicional para la toma de decisiones y analizando los procesos que existen. Además, se definen las limitaciones de estos enfoques tradicionales. La siguiente sección explora los nuevos enfoques basados en IA. En primer lugar, se establecen los conceptos fundamentales de la IA. Además, se aclaran las diferencias entre IA y ‘Machine Learning’. Luego, se profundiza en el proceso de toma de decisiones utilizando esta tecnología. Habiendo sentado las bases, la investigación se adentra en los efectos económicos que surgen de la integración de la IA en empresas y organizaciones internacionales, diferenciando entre el nivel de la empresa y las repercusiones micro y macroeconómicas. Por último, se presenta un estudio de un caso real en el sector energético europeo, para comparar el rendimiento predictivo de los métodos tradicionales con las técnicas novedosas de la IA.[EN] The objective of this Final Degree Dissertation, entitled ‘Design of an Artificial Intelligence model that refines the results of the analysis in economic decision making: the case of final energy consumption in the UE’ is to shed light on the potential of Artificial Intelligence (AI) from a decision-maker perspective. The study commences by establishing the bases of the traditional way of conducting data-driven decisions and discussing the various processes that exist. Additionally, it defines the limitations of these traditional approaches. The subsequent section explores the novel AI approaches for the decision making process, first, it establishes the fundamental concepts of AI. Additionally, it clarifies the distinctions between AI and Machine Learning. Then, it dives into the process of making decisions using AI, proposing examples of techniques employed in different areas. Having laid the groundwork, the research delves into the economic effects that arise from the integration of AI in businesses and international organizations, distinguishing between firm level, and microeconomic and macroeconomic level repercussions. Lastly, a real-world case study in the European energy sector is presented, to compare the predictive performance of traditional methods with AI techniques

    ADOPTION OF EMERGING TECHNOLOGY TOOLS IN LOGISTICS INDUSTRY: PRIORITIZATION USING ANP AND BOCR METHODS

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    This study aims to prioritize technology tools in the logistics industry. It focuses on four key technology trends: Augmented Reality (AR), the Internet of Things (IoT), Big Data, and Robotics and Automation (R&A). The objective is to determine the prioritization and ranking of these technologies in the logistics sector using the Analytic Network Process (ANP) model and analyzing using the Benefits, Opportunities, Costs, and Risks (BOCR) model. The study identified specific criteria and sub-criteria to evaluate the technologies, and experts from the fields provided judgments based on these criteria. Applying the ANP and BOCR models, the research presents the ranking of the technology trends, highlighting their importance and potential impact on the logistics industry. The findings of this research help to gain further knowledge of the technology adoption in the logistics sector and provide valuable insights for industry professionals and decision-makers
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