Albert Camus

Partnership for Sustainable Development

The book explores issues impacting Africa’s development, approaches across sectors. It is focused on interdisciplinary and multi-sector collaboration to address Africa’s development challenges. The book explores how partnerships across academia, government, industry, and communities can contribute to sustainable development.

1. Soraia Raupp Musse
2. Julia Melgaré
3. Greice Pinho

From Pixels to Perception: The Interplay Between Real and Virtual Human Experiences

The book delves into two key aspects of the interaction between real and virtual humans. First, it examines the intricate dynamics of human perception in relation to virtual human representation, beginning with an exploration of the Uncanny Valley (UV) theory to understand why certain virtual humans evoke discomfort or a sense of strangeness in users. It also addresses how human biases influence these perceptions, offering a deeper understanding of the subjective factors at play. The book introduces innovative methods to investigate this phenomenon, correlating objective image characteristics, such as Hu Moments and Histogram Oriented Gradient (HOG), with subjective feelings of discomfort. The second aspect of the book shifts focus to the perspective of virtual humans, discussing how they perceive the virtual world and the importance of gaze behavior in creating believable characters. By integrating insights from neuroscience with data-driven models, the book illustrates how animated gaze and virtual human perception can enhance user interaction with virtual environments. Bringing together both sides of perception, this comprehensive analysis reveals how these dynamics impact the user experience with technology.

Intelligent Urban Systems: IoT-Driven Energy Management and Smart City Optimization

This comprehensive volume delivers cutting-edge solutions for integrating artificial intelligence into renewable energy systems, addressing critical challenges in sustainable energy transition. Readers will discover innovative approaches to optimizing photovoltaic systems, wind energy conversion, smart grids, and hybrid energy storage through advanced machine learning algorithms and intelligent control strategies. The book presents practical applications spanning MPPT optimization techniques, predictive maintenance using SCADA data, IoT-based monitoring systems, and AI-driven fault detection in power electronics. Contributors explore emerging topics including green hydrogen production, electric vehicle control systems, energy forecasting with deep learning, and autonomous microgrid management. Special emphasis is placed on real-world implementations tested in diverse environmental conditions. Featuring contributions from leading international researchers and practitioners, this work bridges the gap between academic research and industrial application. Engineers, researchers, and graduate students working in renewable energy, power systems, and artificial intelligence will find invaluable insights for developing efficient, resilient, and sustainable energy solutions that meet urgent climate and energy security challenges.

Machine Learning Strategies and Security Enhancement in Agricultural Sustainability

The book offers a unique perspective on the investigation of machine learning's incorporation into agriculture. It discusses the important components of agricultural sustainability and security enhancement. It provides a deeper exploration of the optimization component using machine learning approaches.

Artificial Intelligence-Driven Triple Helix Innovation

Digital technologies are reshaping economies, societies, and governance structures worldwide. The integration of Artificial Intelligence (AI) within the framework of the Triple Helix model; consisting of academia, industry, and government, has become essential for innovation. This book aims to explore the dynamic relationship between these three sectors. The Triple Helix framework outlines the interaction and cooperation among three key participants in the innovation process: academia, industry, and government. Originally proposed by Etzkowitz and Leydesdorff in the 1990s, this model serves as a tool for comprehending the dynamics of innovation in modern societies that rely on knowledge (Schebesch et al, 2024). With increasing global challenges such as climate change, healthcare, and economic inequality, the need for innovative solutions that utilize the strengths of academia, industry, and government is vital.  This book is designed for a diverse audience, including scholars and researchers in fields such as innovation studies, technology management, and public policy. Moreover, it targets industry leaders and decision-makers looking to understand the power of AI in driving innovation. It is also intended for government officials interested in using AI for public benefit and enhancing economic competitiveness. Finally, it targets students and academics in education who aim to gain insight into contemporary innovation practices.

Nigerian Media's Artificial Intelligence Revolution

Artificial Intelligence (AI) is rapidly transforming communication and media sectors around the world, but much of the global academic literature on this remains Western-centric. This book will be an important read for researchers working on media, communication, and education both in Nigeria, and in Africa more broadly.