Geschichtlich-wissenschaftliche Darstellung Der St繹chiometrie Und Electrometrie
Geschichtlich-wissenschaftliche Darstellung Der St繹chiometrie Und Electrometrie
Artificial Intelligence-Driven Models for Environmental Management
Step-by-step guidelines for the development of artificial neural network-based environmental pollution models Artificial Intelligence-Driven Models for Environmental Management delves into the application of AI across a plethora of areas in environmental management, including climate forecasting, natural resource optimization, waste management, and biodiversity conservation. This book shows how AI can help in monitoring, predicting, and mitigating environmental impacts with tremendous accuracy and speed by leveraging machine learning, deep learning, and other data-driven models. The methodologies explored in this volume reflect a synthesis of computational intelligence, data science, and ecological expertise, underscoring how AI-driven systems have been making strides in managing and preserving our planet's natural resources. The text is structured to guide readers through numerous AI models and their practical environmental management applications, showcasing theoretical foundations as well as case studies. This book also addresses the challenges and ethical considerations related to deploying AI in ecological contexts, underscoring the importance of transparency, inclusivity, and alignment with sustainability goals. Sample topics discussed in Artificial Intelligence-Driven Models for Environmental Management include: Tools and methods for monitoring and predicting environmental pollutants faster and more accurately AI technology for the protection of water supplies from contamination to produce healthier foods Use of AI for the evaluation of the impacts of environmental pollution on human health AI and waste management technologies for sustainable agriculture and soil management The role of AI in environmental research and sustainability and key social and economic aspects of natural resource management through AI Artificial Intelligence-Driven Models for Environmental Management is a timely, forward-thinking resource for a diverse readership, including researchers, policymakers, environmental scientists, and AI practitioners.
Streamlining Your Research Laboratory with Python
Enables scientists and researchers to efficiently use one of the most popular programming languages in their day-to-day work Streamlining Your Research Laboratory with Python covers the Python programming language and its ecosystem of tools applied to tasks encountered by laboratory scientists and technicians working in the life sciences. After opening with the basics of Python, the chapters move through working with and analyzing data, generating reports, and automating the lab environment. The book includes example processes within chapters and code listings on nearly every page along with schematics and plots that can clearly illustrate Python at work in the lab. The book also explores some real-world examples of Python's application in research settings, demonstrating its potential to streamline processes, improve productivity, and foster innovation. Streamlining Your Research Laboratory with Python includes information on: Language basics including the interactive console, data types, variables and literals, strings, and expressions using operators Custom functions and exceptions such as arguments and parameters, names and scope, and decorators Conditional and repeated execution as methods to control the flow of a program Tools such as JupyterLab, Matplotlib, NumPy, pandas DataFrame, and SciPy Report generation in Microsoft Word and PowerPoint, PDF report generation, and serving results through HTTP and email automatically Whether you are a biologist analyzing genetic data, a chemist scouting synthesis routes, an engineer optimizing machine parameters, or a social scientist studying human behavior, Streamlining Your Research Laboratory with Python serves as a logical and practical guide to add Python to your research toolkit.
Advances in Solar Thermal Energy Harvesting, Storage and Conversion
On the Chemical Constitution of the Proteins of Wheat Flour and its Relation to Baking Strength ..
On the Chemical Constitution of the Proteins of Wheat Flour and its Relation to Baking Strength ..
Essentials of Physics and Chemistry Written Especially for the Use of Students in Medicine
