225 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

    Precision mass measurements for the astrophysical rp-process and electron cooling of trapped ions

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    Precision mass measurements of rare isotopes with decay half-lives far below one second are of importance to a variety of applications including studies of nuclear structure and nuclear astrophysics as well as tests of fundamental symmetries. The first part of this thesis discusses mass measurements of neutron-deficient gallium isotopes in direct vicinity of the proton drip line. The reported measurements of 60-63Ga were performed with the MR-TOF-MS of TRIUMF's Ion Trap for Atomic and Nuclear Science (TITAN) in Vancouver, Canada. The measurements mark the first direct mass determination of 60Ga and yield a 61Ga mass value three times more precise than the literature value from AME2020. Our 60Ga mass value constrains the location of the proton dripline in the gallium isotope chain and extends the experimentally evaluated IMME for isospin triplets up to A=60. The improved precision of the 61Ga mass has important implications for the astrophysical rapid proton capture process (rp-process). Calculations in a single-zone model demonstrate that the improved mass data substantially reduces uncertainties in the predicted light curves of Type I X-ray bursts. TITAN has demonstrated that charge breeding provides a powerful means to increase the precision and resolving power of Penning trap mass measurements of radioactive ions. However, the charge breeding process deteriorates the ion beam quality, thus mitigating the benefits associated with Penning trap mass spectrometry of highly charged ions (HCI). As a potential remedy for the beam quality loss, a cooler Penning trap has been developed in order to investigate the prospects of electron cooling the HCI prior to the mass measurement. The second part of this thesis reports exploratory studies of electron cooling of singly charged ions in this cooler Penning trap. Comparison of measured ion energy evolutions to a cooling model provides a detailed understanding of the underlying cooling dynamics. Extrapolation of the model enables the deduction of tentative estimates of the expected cooling times for radioactive HCI

    A Survey of GPT-3 Family Large Language Models Including ChatGPT and GPT-4

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    Large language models (LLMs) are a special class of pretrained language models obtained by scaling model size, pretraining corpus and computation. LLMs, because of their large size and pretraining on large volumes of text data, exhibit special abilities which allow them to achieve remarkable performances without any task-specific training in many of the natural language processing tasks. The era of LLMs started with OpenAI GPT-3 model, and the popularity of LLMs is increasing exponentially after the introduction of models like ChatGPT and GPT4. We refer to GPT-3 and its successor OpenAI models, including ChatGPT and GPT4, as GPT-3 family large language models (GLLMs). With the ever-rising popularity of GLLMs, especially in the research community, there is a strong need for a comprehensive survey which summarizes the recent research progress in multiple dimensions and can guide the research community with insightful future research directions. We start the survey paper with foundation concepts like transformers, transfer learning, self-supervised learning, pretrained language models and large language models. We then present a brief overview of GLLMs and discuss the performances of GLLMs in various downstream tasks, specific domains and multiple languages. We also discuss the data labelling and data augmentation abilities of GLLMs, the robustness of GLLMs, the effectiveness of GLLMs as evaluators, and finally, conclude with multiple insightful future research directions. To summarize, this comprehensive survey paper will serve as a good resource for both academic and industry people to stay updated with the latest research related to GPT-3 family large language models.Comment: Preprint under review, 58 page

    IEOM Society International

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    IEOM Society Internationa

    Machine Learning-Driven Decision Making based on Financial Time Series

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    L'abstract è presente nell'allegato / the abstract is in the attachmen

    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

    Investor risk profiling: an enhanced behavioral finance perspective and technique for identifying client risk profiles

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    The ramifications of financial crises and the complex structures of financial products have enabled the hand of regulation to extend beyond the security of investors and into the suitability of the investments proposed by financial institutions and advisors. This process, assessed through a risk profiling questionnaire, carries an opportunity to choose the optimal financial product based on the risk tolerance of the investor and thereafter retain the clients and help their investments grow. In this paper, we argue that the traditional risk profiling questionnaire requires an overhaul through the lens of behavioral finance which offers a more rigorous understanding of the risk appetite of the investor. Through independent samples t test, we measure the performance of two groups of investors over time; one with behavioral finance questions and one offered the traditional risk profiling questionnaire. A Pearson Chi Square test is also conducted to assess the relationship between the risk profile rating and the financial return of the investor groups. The methodology is supported with a review of the yield performance and client retention of the group of investors who had answered behavioral finance questions. Moreover, a qualitative approach was also adopted whereby interviews with financial advisors were conducted to determine their perspectives. Our findings indicate a better performance through financial returns for investors who answered behavioral finance questions and a higher retention for that group of investors with their financial advisor(s). These findings reinforce our hypothesis on the inclusion of behavioral finance questions into risk profiling and its impact on the suitability of investments. The study proposes recommendations to improve the suitability of investments process through risk profiling. The study also proposes further research to be conducted in the field of behavioral finance and risk, as a solution to the limitations offered by traditional financial behavior theorie

    Multi Indicator based Hierarchical Strategies for Technical Analysis of Crypto market Paradigm

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    The usage of technical analysis in the crypto market is very popular among algorithmic traders. This involves the application of strategies based on technical indicators, which shoot BUY and SELL signals to help the investors to take trading decisions. However, instead of depending on the popular myths of the market, a proper empirical analysis can be helpful in lucrative endeavors in trading cryptocurrencies. In this work, four technical indicators namely Exponential Moving Averages (EMA), Bollinger Bands (BB), Relative Strength Index (RSI), and Parabolic Stop And Reverse (PSAR) are used individually to devise strategies that are implemented, and their performance is validated using the price data of Bitcoin from yahoo finance for 2018-22, individually for each year and all the five years consolidated to compute the performance metrics including Profit percentage, Net profitability percentage, and Number of total transactions. The results show that the performance of strategies based on trend indicators is better than that of momentum indicators where the EMA strategy provided the best result with a profit percentage of 394.13%. Further, the performance of these strategies is analyzed in three different market scenarios namely Uptrend/Bullish trend, Downtrend/Bearish trend, and Fluctuating/oscillating markets to analyze the applicability of each of these smart strategies in the three scenarios. Based on the insights obtained from the analysis, Hybrid strategies using multiple indicators with a hierarchical approach are developed whose performance is further improved by imposing constraints in a Downtrend market scenario. The novelty of these algorithms is that they identify the scenario in the market using multiple indicators in a hierarchal approach, and utilize appropriate indicators as per the market scenario. Four strategies namely, Multi indicator based Hierarchical Strategy (MIHS) with EMA9, Multi indicator based Hierarchical Strategy (MIHS) with EMA7, Multi-Indicator based Hierarchical Constrained Strategy (MIHCS) with EMA9, and Multi-Indicator based Hierarchical Constrained Strategy (MIHCS) with EMA7 are developed which give profit percentage of 154.45%, 437.48%, 256.31%, and 701.77% respectively when applied on the Bitcoin price data during 2018-22

    Statistical Modeling and Analysis

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    Die Blockchain-Technologie revolutioniert die Interaktion zwischen Menschen durch Peer-to-Peer-Netzwerke, Kryptografie und Konsensalgorithmen. Trustless Trust ermöglicht sichere und transparente Transaktionen ohne Zwischenhändler. Trotz der zunehmenden Beliebtheit von Krypto-Assets und den damit verbundenen „Tokenomics“ hat die Öffentlichkeit immer noch kein umfangreiches Wissen über die Funktionsweisen dieser Technologie, und ein Großteil des Diskurses bleibt spekulativ. Das Hauptziel dieser Arbeit ist, die grundlegenden Prinzipien von Krytowährungen (Cryptos) und Non-Fungible Tokens (NFTs) zu untersuchen sowie eine Korrelation zwischen der Technologie und ihren Auswirkungen auf die Wirtschaft aus statistischer und wirtschaftlicher Sicht herzustellen. Um dieses Ziel zu erreichen, wird in den Kapiteln 2 und 3 der Einfluss der Blockchain-Technologie auf Ökonomie und Funktionsweise von Kryptowährungen anhand ökonometrischer Modelle und Clustering-Techniken untersucht. Kapitel 3 untersucht Kryptowirschaft und Blockchain-Funktionalität anhand empirischer Methoden, insbesondere für Coincreatoren und Investoren. Wir zeigen am Beispiel von Ethereum, dass die wirtschaftliche Leistung von Kryptowährungen durch die Gestaltung der ihnen zugrunde liegenden Blockchain-Technologie beeinflusst werden kann. Kapitel 4 untersucht die partiellen Korrelationen von Bitcoin-Renditen über neun verschiedene Zentralbörsen aus der Perspektive eines hochfrequenten, dynamischen Netzwerks. Die vorgeschlagene MHAR-CM liefert Kovarianzschätzungen, die die Besonderheiten der Kryptomärkte berücksichtigen. Das Kapitel zeigt Spillover- und Third-Party-Risiken zwischen diesen Börsen. Kapitel 5 verwendet eine Hedonische Bewertungsmethode, um den DAI Digital Art Index basierend auf dem NFT-Kunstmarkt zu konstruieren. Ein besonderer Fokus liegt auf der Nivellierung der Auswirkungen von Ausreißern mit einer einstufigen robusten Regressions-Huberisierung und einem dynamic conditional score model. Diese Arbeit verknüpft neue Technologien und Wirtschaft durch statistische Modellierung und Analyse. Durch die Bereitstellung empirischer Belege beobachten wir, wie die Blockchain-Technologie unsere Wahrnehmung von Geld, Kunst und anderen Branchen verändert.The emergence of distributed ledger technologies, such as blockchain, has revolutionized how individuals interact by enabling "trust-less trust" through peer-to-peer networks, cryptography, and consensus algorithms. This technology eliminates intermediaries and provides secure, transparent transaction methods. However, public understanding of this technology, along with "Tokenomics", remains limited, resulting in speculative discourse. The main objective of this thesis is to investigate the fundamental principles of cryptocurrencies (cryptos) and non-fungible tokens (NFTs) and establish a correlation between the technology and its economic impact from statistical and economic perspectives. To achieve this, Chapters 2 and 3 explore the influence of blockchain technology on the economic and functional performance of cryptos using econometric models and clustering techniques. Chapter 3 presents an empirical framework that offers insights to coin creators and investors regarding the interplay between cryptonomics, blockchain functionality, and market dynamics. The economic performance of cryptocurrencies, illustrated with Ethereum as an example, is shown to be affected by the design of their underlying blockchain technology. Chapter 4 examines partial correlations of Bitcoin returns across nine centralized exchanges from a high-frequency dynamic network perspective. The proposed MHAR-CM provides reasonable covariance estimates that account for the unique characteristics of crypto markets. This chapter uncovers spillover risk and counterparty risk among these exchanges. In Chapter 5, a hedonic regression approach is employed to construct the DAI digital art index for the NFT art market. Special emphasis is given to mitigating the impact of outliers using one-step robust regression Huberization and a dynamic conditional score model. The DAI index enhances our understanding of this emerging art market and facilitates observation of its macroeconomic trends. This thesis establishes a connection between emerging technologies and the economy through statistical modeling and analysis. By providing empirical evidence, we gain insights into how blockchain technology is transforming our perceptions of money, art, and various industries

    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
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