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\"The increasing interest in Artificial Intelligence (AI), Digital Twin (DT) and Internet of Things (IoT) is progressively playing a wider impact on many different sectors, and and this book offers several applications and challenges in various vital roles such as Product design and lifecycle, Smart Cities, Agriculture, Environment automation, Healthcare, Farming, Wearable, Climate, Sensors, Transportation, Electrical generation, E-governance renewable energy, and eco-system for sustainable growth\"-- Provided by publisher.

A broad and growing literature describes the deep and multidisciplinary nature of the sustainability challenges faced by the United States and the world. Despite the profound technical challenges involved, sustainability is not, at its root, a technical problem, nor will merely technical solutions be sufficient. Instead, deep economic, political, and cultural adjustments will ultimately be required, along with a major, long-term commitment in each sphere to deploy the requisite technical solutions at scale. Nevertheless, technological advances and enablers have a clear role in supporting such change, and information technology (IT) is a natural bridge between technical and social solutions because it can offer improved communication and transparency for fostering the necessary economic, political, and cultural adjustments. Moreover, IT is at the heart of nearly every large-scale socioeconomic system-including systems for finance, manufacturing, and the generation and distribution of energy-and so sustainability-focused changes in those systems are inextricably linked with advances in IT. The focus of Computing Research for Sustainability is \"greening through IT,\" the application of computing to promote sustainability broadly. The aim of this report is twofold: to shine a spotlight on areas where IT innovation and computer science (CS) research can help, and to urge the computing research community to bring its approaches and methodologies to bear on these pressing global challenges. Computing Research for Sustainability focuses on addressing medium- and long-term challenges in a way that would have significant, measurable impact. The findings and recommended principles of the Committee on Computing Research for Environmental and Societal Sustainability concern four areas: (1) the relevance of IT and CS to sustainability; (2) the value of the CS approach to problem solving, particularly as it pertains to sustainability challenges; (3) key CS research areas; and (4) strategy and pragmatic approaches for CS research on sustainability.

\"On January 30-31, 2019 the Board on Mathematical Sciences and Analytics, in collaboration with the Board on Energy and Environmental Systems and the Computer Science and Telecommunications Board, convened a workshop in Washington, D.C. to explore the frontiers of mathematics and data science needs for sustainable urban communities. The workshop strengthened the emerging interdisciplinary network of practitioners, business leaders, government officials, nonprofit stakeholders, academics, and policy makers using data, modeling, and simulation for urban and community sustainability, and addressed common challenges that the community faces. Presentations highlighted urban sustainability research efforts and programs under way, including research into air quality, water management, waste disposal, and social equity and discussed promising urban sustainability research questions that improved use of big data, modeling, and simulation can help address. This publication summarizes the presentation and discussion of the workshop\"--Publisher's description.

Going beyond performing simple analyses, researchers involved in the highly dynamic field of computational intelligent data analysis design algorithms that solve increasingly complex data problems in changing environments, including economic, environmental, and social data. This volume presents novel methodologies for automatically processing these types of data to support rational decision making for sustainable development. Through numerous case studies and applications, it illustrates important data analysis methods, including mathematical optimization, machine learning, signal processing, and temporal and spatial analysis, for quantifying and describing sustainable development problems.

El liderazgo educacional como proceso de influencia en las personas busca el respaldo en las actividades que se convocan al interior y exterior de las instituciones desde objetivos y metas comunes, este proceso cobra relevancia en la planificación y organización de la socialización de los resultados científicos derivado de organizaciones como es el caso de la Red Iberoamericana de Investigación en Liderazgo y Prácticas Educativas (RIILPE). La consolidación del trabajo en red ha provocado el desarrollo y realización del Primer Congreso Internacional de RIILPE, organizado por la Universidad de San Carlos de Guatemala https://humanides.usac.edu.gt/rilpe.El congreso tuvo lugar en la Ciudad Antigua de Guatemala los días 21, 22 y 23 de noviembre de 2023, participaron más de cien investigadores iberoamericanos de siente países (Argentina, Chile, Cuba, España, Guatemala, México y Nicaragua), se impartieron conferencias magistrales, se presentaron ponencias y libros, propiciando el debate científico entre los participantes del cónclave.La Red se fortalece a través de la ejecución de 18 proyectos de investigación financiados por instituciones socias con participación extranjera, permitiendo a los miembros (103) académicos de once países: Argentina (1); Brasil (2); Chile (12); Colombia (4); Cuba (30); España (11); Guatemala (14); Honduras (1); México (19); Nicaragua (7) y Portugal (2) tener una vida académica que favorece su actividad y desempeño profesional desde sus instituciones con vínculos internacionales.El trabajo en red cobra fuerza cada día, los avances tecnológicos y el uso de plataformas: Google Meet, Zoom, Teams y otras permiten la transferencia de conocimiento a través de reuniones, seminarios, cursos, clases espejos desde procesos virtuales, permite la movilidad de académicos sin traslados geográficos, la inversión económica es en menor cuantía, por tanto, todo ello constituye un método de trabajo para el logro de la formación continua de los profesionales que forman parte de RILPE.Las investigaciones que se describen en el libro forman parte del trabajo investigativo desde las ciencias de la educación en el contexto iberoamericano, se realza la educación e investigación comparada, el liderazgo, la administración científica y sus insuficiencias observadas en la práctica educativa, la educación a distancia, la formación de profesionales a través de pasantías como método de formación, el arte como proceso favorecedor del patrimonio cultural, la promoción del comportamiento computacional, la innovación educativa, los procesos de ética como crítica a la disciplina, la tutoría académica, el podcast, el derecho de aprender y las actitudes y tipologías son líneas de investigación que forman parte del interés de cada uno de los investigadores con vista a elevar la calidad de la clase y los procesos de influencias desde aprendizajes significativos tanto en la Educación General como en la Superior.Convencidos de que la investigación es el secreto de la victoria en el campo educacional para elevar los aprendizajes, desde el trabajo en redes se introduce un proceso transversal para lograr articular junto a la docencia y la extensión los procesos sustantivos universitarios, la denominada internacionalización de las universidades ocupa un lugar especial en el logro de la eficiencia y eficacia del trabajo colaborativo en red, desde la creación de perfiles en Google Académico, ORCID, Researchgate, Scopus, Web of Science se logra que las organizaciones se favorezcan en los rankings de universidades del mundo a través de indicadores como: visibilidad, transparencia y presencia, ello conlleva al impacto y excelencia de las instituciones de educación Superior que participan en redes de investigación.

This book is bridging the gap for organisations and individuals, in an English as a second language setting, who need to learn and use R in a part-time professional context. It gives people with a non-technical background a set of skills to understand the usefulness of graphing, mapping, and modelling in R, using relatable examples throughout. It also provides background on inference and data integration in project management to assist the reader in understanding the logic and utility behind evidence-based decision making. The book explains the major functions in R in clear terms, making it accessible to everyone, with the aim to demystify R and give people the confidence to use it. Key Features: Foundation sections on inference and evidence, and data integration in project management Exploration of R usage through a narrative examining a generic integrated conservation and development project A final section on R for reproducible workflow Accompanied by an R package

Intelligent data analysis techniques offer powerful solutions to collecting and analyzing vast quantities of environmental and economic data, which lead to better decision making for sustainable development. This volume is the first to discuss the treatment of intelligent data analysis techniques in sustainable development applications. The book describes the emerging use of data mining, machine learning, artificial neural networks, data visualization, knowledge discovery, GIS, and other technologies to tackle environmental, economic, and social issues, including climate change, risk management, and population growth.

This book provides the necessary elements to determine exactly what information should be collected to make the collected information relevant for policy makers. It highlights the dissatisfaction of information users about the information they get and the reasons for this dissatisfaction. It also discusses general issues around the role and use of information in policy making. The text then describes the how to develop a full understanding of the policy makers' information needs and will describe how policy makers can be included in the process. Finally, the book describes how the results from this process are input for the information production process.

Sensors are everywhere. Small, flexible, economical, and computationally powerful, they operate ubiquitously in environments. They compile massive amounts of data, including information about air, water, and climate. Never before has such a volume of environmental data been so broadly collected or so widely available. Grappling with the consequences of wiring our world,Program Earthexamines how sensor technologies are programming our environments. As Jennifer Gabrys points out, sensors do not merely record information about an environment. Rather, they generate new environments and environmental relations. At the same time, they give a voice to the entities they monitor: to animals, plants, people, and inanimate objects. This book looks at the ways in which sensors converge with environments to map ecological processes, to track the migration of animals, to check pollutants, to facilitate citizen participation, and to program infrastructure. Through discussing particular instances where sensors are deployed for environmental study and citizen engagement across three areas of environmental sensing, from wild sensing to pollution sensing and urban sensing,Program Earthasks how sensor technologies specifically contribute to new environmental conditions. What are the implications for wiring up environments? How do sensor applications not only program environments, but also program the sorts of citizens and collectives we might become? Program Earthsuggests that the sensor-based monitoring of Earth offers the prospect of making new environments not simply as an extension of the human but rather as new \"technogeographies\" that connect technology, nature, and people.

Sustainability analysis practice has so far proved that measurement of the level of sustainable development (SD) is associated with a large number of methodological difficulties and limitations, related mainly to the selection of indicators, data processing and interpretation of the results. This study is based on an assumption that SD should be measured in ways that depend on the level of development of the country, i.e., it is highly recommended to develop separate sets of indicators to be used for highly developed, medium-developed and poor countries. To that end, we carried out the study on a sample of 13 Southeast European (SEE) countries, and Germany and the Russian Federation for comparison—which are at different levels of development and overall political and socio-economic ambients. The research includes analysis by three different approaches to SD, each based on different sets of indicators: a “GDP approach” which is traditional, and in which economic and GDP-based indicators hold the dominant role; a “Beyond-GDP approach” that reduces the use of economic indicators while increasing the share of social indicators and those based on natural resources; and an “SDG-based approach” that is mainly using indicators of quality of life as defined by the United Nations (UN) SDG. The analysis was performed using the method of composite indicators. Groups of 20 indicators were selected according to their suitability to each of the 3 above-described approaches. The study objective leads to examining ways for measuring development, to suggest new ones, recommend approaches to sustainability planning for the considered SEE countries and beyond, to contribute to the analysis methodology (by assessing usability and reliability of certain indicators and of linkages between them), as well as to rank the countries’ levels of SD under these approaches. Some of the main conclusions are: (a) the indicators having the highest potential impact on the level of SD were foreign direct investments, public debt, energy imports, total natural resources rents, terrestrial and marine protected areas, vulnerable employment, and the Corruption Index; (b) use of the Inclusive Wealth Index is encouraged, so it is important to advance proper methodologies for its measurement; (c) Slovenia and Hungary were the highest-ranked SEE countries under all three approaches, just under Germany; and (d) the ranking order under the SDG-based approach could be used to identify the prioritization of development effort and funding that countries should apply and receive for meeting the SDG. Recommendations for further sustainability measurement were made based on the study’s findings.