3,998 research outputs found

    Undergraduate Catalog of Studies, 2023-2024

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    Systematic mapping of software engineering management with an agile approach

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    El enfoque ágil ha generado una amplia variedad de estrategias para administrar con éxito diversos proyectos de software en todo el mundo. Además, podemos asegurar que los proyectos de software se han beneficiado de los métodos ágiles ya conocidos. En este sentido, este artículo busca demostrar cómo se aplica el enfoque ágil en las áreas de la gestión en la ingeniería del Software. Para ello, este estudio realiza un mapeo sistemático para identificar las principales tendencias en la gestión de la ingeniería de software con un enfoque ágil. Se han identificado un total de 1137 artículos, de los cuales 165 son relevantes para los fines de este estudio, estos indican que la entrega temprana de valor, un principio clave de la agilidad, sigue siendo la principal tendencia para el uso de métodos ágiles. Sin embargo, también existen fuertes tendencias enfocadas en puntos clave de la gestión en ingeniería de software, como optimizar la gestión de calidad, optimizar la especificación de requisitos, optimizar la gestión de riesgos y mejorar la comunicación y coordinación del equipo, estos resultados permitirán generar nuevas líneas de investigación para cada punto clave de la gestión en la ingeniería del software impactado por el enfoque ágil.The agile approach has generated a wide variety of strategies to successfully manage various software projects worldwide. In addition, we can ensure that software projects have benefited from the already known agile methods. In this sense, this article seeks to demonstrate how the agile approach is applied in Software engineering management areas. To do this, this study performs a systematic mapping to identify the main trends in software engineering management with an agile approach. A total of 1137 articles have identified, of which 165 are relevant for the purposes of this study, these indicate that early value delivery, a key principle of agility, continues to be the main trend for the use of agile methods. However, there are also strong trends focused on key points of management in software engineering, such as optimize quality management, optimize requirements specification, optimize risk management, and improve team communication and coordination, these results will allow generating new lines of research for each key point of management in software engineering impacted by the agile approach

    The Impact of Artificial Intelligence on Organizational Justice and Project Performance: A Systematic Literature and Science Mapping Review

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    By adopting a systematic literature and science mapping review, this paper aims to explore the impact of artificial intelligence (AI) on organizational justice and project performance. A total of 47 bibliographic records from the Scopus database were analyzed. The results revealed the annual publication trends of research articles and relevant peer-reviewed journals in the studied domain. It was found that while AI technology has made significant progress in several fields, its application areas in project management and organizational justice are still relatively low. Moreover, it objectively discussed the co-occurrence analysis of keywords, co-authors, countries/regions, and documents in the fields, revealing the current research topics. The main research topics include the (1) AI’s influence on organizational justice, decision analysis, and digital transformation, (2) fostering organizational justice and AI’s role in enhancing project performance, and (3) improving organizational performance approaches. Furthermore, this paper proposed research gaps and future research directions, including (1) advancing business intelligence strategies, (2) unlocking AI technology potential on organizational justice and project performance, (3) the adaption of cultural, diversity, environmental, and social factors, (4) the impact of AI on complex and challenging leadership styles, and (5) developing a comprehensive understanding of the agile framework. The findings of this paper could contribute to a better understanding of how AI shapes project/construction management and organizational justice, providing practical solutions for innovative development for researchers and policymakers

    Unleashing the power of artificial intelligence for climate action in industrial markets

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    Artificial Intelligence (AI) is a game-changing capability in industrial markets that can accelerate humanity's race against climate change. Positioned in a resource-hungry and pollution-intensive industry, this study explores AI-powered climate service innovation capabilities and their overall effects. The study develops and validates an AI model, identifying three primary dimensions and nine subdimensions. Based on a dataset in the fast fashion industry, the findings show that the AI-powered climate service innovation capabilities significantly influence both environmental and market performance, in which environmental performance acts as a partial mediator. Specifically, the results identify the key elements of an AI-informed framework for climate action and show how this can be used to develop a range of mitigation, adaptation and resilience initiatives in response to climate change

    Digitalization and Development

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    This book examines the diffusion of digitalization and Industry 4.0 technologies in Malaysia by focusing on the ecosystem critical for its expansion. The chapters examine the digital proliferation in major sectors of agriculture, manufacturing, e-commerce and services, as well as the intermediary organizations essential for the orderly performance of socioeconomic agents. The book incisively reviews policy instruments critical for the effective and orderly development of the embedding organizations, and the regulatory framework needed to quicken the appropriation of socioeconomic synergies from digitalization and Industry 4.0 technologies. It highlights the importance of collaboration between government, academic and industry partners, as well as makes key recommendations on how to encourage adoption of IR4.0 technologies in the short- and long-term. This book bridges the concepts and applications of digitalization and Industry 4.0 and will be a must-read for policy makers seeking to quicken the adoption of its technologies

    Smart Gas Sensors: Materials, Technologies, Practical ‎Applications, and Use of Machine Learning – A Review

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    The electronic nose, popularly known as the E-nose, that combines gas sensor arrays (GSAs) with machine learning has gained a strong foothold in gas sensing technology. The E-nose designed to mimic the human olfactory system, is used for the detection and identification of various volatile compounds. The GSAs develop a unique signal fingerprint for each volatile compound to enable pattern recognition using machine learning algorithms. The inexpensive, portable and non-invasive characteristics of the E-nose system have rendered it indispensable within the gas-sensing arena. As a result, E-noses have been widely employed in several applications in the areas of the food industry, health management, disease diagnosis, water and air quality control, and toxic gas leakage detection. This paper reviews the various sensor fabrication technologies of GSAs and highlights the main operational framework of the E-nose system. The paper details vital signal pre-processing techniques of feature extraction, feature selection, in addition to machine learning algorithms such as SVM, kNN, ANN, and Random Forests for determining the type of gas and estimating its concentration in a competitive environment. The paper further explores the potential applications of E-noses for diagnosing diseases, monitoring air quality, assessing the quality of food samples and estimating concentrations of volatile organic compounds (VOCs) in air and in food samples. The review concludes with some challenges faced by E-nose, alternative ways to tackle them and proposes some recommendations as potential future work for further development and design enhancement of E-noses

    Impacto de las características personales de los programadores en la efectividad de Test-Driven-Development (TDD)

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    Contexto: El desarrollo dirigido por pruebas (Test Driven Development - TDD), es una estrategia de programación propuesta por Kent Beck (Beck,2002) como alternativa al desarrollo de software tradicional, ha sido una técnica ampliamente estudiada en la ingeniería de software experimental, especialmente con la realización de estudios que intentan demostrar su efectividad en términos de calidad del código y productividad de los programadores. Objetivos: En este trabajo de tesis doctoral, se propone la realización de una familia de experimentos (Basili,1999), para determinar la influencia de factores personales en la Calidad externa y en la Productividad al aplicar TDD en comparación con el desarrollo iterativo con pruebas al final (ITLD). Metodología: Se realizó una serie de 7 estudios experimentales en el ámbito académico e industrial, partiendo de un experimento tomado como base. Posteriormente los resultados fueron sintetizados mediante un meta- análisis tipo Individual Patient Data (IPD) con descomposición en subgrupos. Resultados: Se obtuvieron diferentes resultados en cuanto a la influencia de los factores humanos sobre la Calidad externa y Productividad, dependiendo del tipo de reclutamiento de los participantes que fueron agrupados como voluntarios (volunteer), no voluntarios (conscripted) y aquellos que participaron de los experimentos como un curso de entrenamiento (Training course), o también agrupados como profesionales y estudiantes. la Calidad externa no produjo diferencias significativas al aplicar TDD, aunque en ciertos casos hubo mejoras al aplicar TDD con estudiantes que participaron como conscripted, pero en otros casos la calidad externa decreció cuando fueron estudiantes que participaron como voluntarios. Por otra parte, los desarrolladores que usaron TDD fueron más productivos que aquellos que usaron ITLD. La experiencia en el uso de herramientas de prueba produjo resultados significativos para la Calidad externa y Productividad, aunque esto depende del tipo de reclutamiento y del carácter profesional o estudiante. Así mismo, la experiencia en Java incidió significativamente en la Calidad externa y el conocimiento del entorno Eclipse en la Productividad. La edad y el grado de completitud o cantidad de código entregado por los participantes al realizar las tareas experimentales fue un factor que influyó significativamente en la Productividad, independientemente de la técnica utilizada. Otro resultado obtenido es que conforme los participantes profesionales tienen mayor edad, su grado de completitud fue disminuyendo, aunque existió cierto interés por realizar un mejor trabajo al aplicar TDD. Conclusiones: Creemos que uno de los principales aportes de nuestro estudio, que lo consideramos de carácter exploratorio, es haber comprobado cómo la motivación, en este caso determinada por el tipo de reclutamiento, incide en el interés de los sujetos sean profesionales o estudiantes al realizar las tareas experimentales y por tanto influye en su productividad. También observamos que la edad es otro factor humano que debe ser objeto de una mayor investigación en trabajos futuros.Facultad de Informátic

    Digital Innovations for a Circular Plastic Economy in Africa

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    Plastic pollution is one of the biggest challenges of the twenty-first century that requires innovative and varied solutions. Focusing on sub-Saharan Africa, this book brings together interdisciplinary, multi-sectoral and multi-stakeholder perspectives exploring challenges and opportunities for utilising digital innovations to manage and accelerate the transition to a circular plastic economy (CPE). This book is organised into three sections bringing together discussion of environmental conditions, operational dimensions and country case studies of digital transformation towards the circular plastic economy. It explores the environment for digitisation in the circular economy, bringing together perspectives from practitioners in academia, innovation, policy, civil society and government agencies. The book also highlights specific country case studies in relation to the development and implementation of different innovative ideas to drive the circular plastic economy across the three sub-Saharan African regions. Finally, the book interrogates the policy dimensions and practitioner perspectives towards a digitally enabled circular plastic economy. Written for a wide range of readers across academia, policy and practice, including researchers, students, small and medium enterprises (SMEs), digital entrepreneurs, non-governmental organisations (NGOs) and multilateral agencies, policymakers and public officials, this book offers unique insights into complex, multilayered issues relating to the production and management of plastic waste and highlights how digital innovations can drive the transition to the circular plastic economy in Africa. The Open Access version of this book, available at https://www.taylorfrancis.com, has been made available under a Creative Commons Attribution-Non Commercial-No Derivatives (CC-BY-NC-ND) 4.0 license

    Software Design Change Artifacts Generation through Software Architectural Change Detection and Categorisation

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    Software is solely designed, implemented, tested, and inspected by expert people, unlike other engineering projects where they are mostly implemented by workers (non-experts) after designing by engineers. Researchers and practitioners have linked software bugs, security holes, problematic integration of changes, complex-to-understand codebase, unwarranted mental pressure, and so on in software development and maintenance to inconsistent and complex design and a lack of ways to easily understand what is going on and what to plan in a software system. The unavailability of proper information and insights needed by the development teams to make good decisions makes these challenges worse. Therefore, software design documents and other insightful information extraction are essential to reduce the above mentioned anomalies. Moreover, architectural design artifacts extraction is required to create the developer’s profile to be available to the market for many crucial scenarios. To that end, architectural change detection, categorization, and change description generation are crucial because they are the primary artifacts to trace other software artifacts. However, it is not feasible for humans to analyze all the changes for a single release for detecting change and impact because it is time-consuming, laborious, costly, and inconsistent. In this thesis, we conduct six studies considering the mentioned challenges to automate the architectural change information extraction and document generation that could potentially assist the development and maintenance teams. In particular, (1) we detect architectural changes using lightweight techniques leveraging textual and codebase properties, (2) categorize them considering intelligent perspectives, and (3) generate design change documents by exploiting precise contexts of components’ relations and change purposes which were previously unexplored. Our experiment using 4000+ architectural change samples and 200+ design change documents suggests that our proposed approaches are promising in accuracy and scalability to deploy frequently. Our proposed change detection approach can detect up to 100% of the architectural change instances (and is very scalable). On the other hand, our proposed change classifier’s F1 score is 70%, which is promising given the challenges. Finally, our proposed system can produce descriptive design change artifacts with 75% significance. Since most of our studies are foundational, our approaches and prepared datasets can be used as baselines for advancing research in design change information extraction and documentation
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