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Overuse of natural resources results in environmental deterioration, lowering the effectiveness of important ecosystem services, such as the mitigation of floods and landslides. This leads to a greater risk of disaster and, in turn, natural hazards that can further deteriorate the environment. The deterioration of the capacity of the environment to meet social and ecological aims and demands is described as environmental degradation. This degradation and the concomitant reduction of ecosystems and their irreplaceable services (the benefits humans gain) are driving disaster risk. Changes to the environment can alter the frequency and intensity of risks, as well as our exposure and sensitivity to these hazards. Addressing these issues requires improvement of the capacity to perform short and medium-term operations in disaster management based on long-term environmental considerations. At the local level, minimizing environmental degradation and ecosystem loss involves awareness of the links between unsustainable development and poverty. Communities are often driven to ruin their natural environment as a short-term coping mechanism for dealing with immediate issues; for instance, surviving a bad harvest by selling wood. Strategies for decreasing poverty by investing in environment-sensitive development should therefore support initiatives to minimize disaster risk and build resilience. There are common aspects in successful policies throughout various regions at the policy level, which extends to controlling climate change. Tools such as integrated water resources and coastal zone management, the removal of environmentally harmful subsidies, especially on fossil fuels and/or carbon taxes, renewable energy, marine protected areas, and cross-boundary biodiversity conservation, are all examples of policies used in more than one region but customized to each context. This scoping study finds and assesses available materials that relate environmental challenges and management with catastrophes and risk reduction activities in the Asia-Pacific area. This volume's analysis relies on case studies, examples, and the results of questionnaires and interviews of practitioners and organizations operating in the environment, disaster, and development domains.
AUTOMATIC SPEECH RECOGNITION and TRANSLATION for LOW-RESOURCE LANGUAGES This book is a comprehensive exploration into the cutting-edge research, methodologies, and advancements in addressing the unique challenges associated with ASR and translation for low-resource languages. Automatic Speech Recognition and Translation for Low Resource Languages contains groundbreaking research from experts and researchers sharing innovative solutions that address language challenges in low-resource environments. The book begins by delving into the fundamental concepts of ASR and translation, providing readers with a solid foundation for understanding the subsequent chapters. It then explores the intricacies of low-resource languages, analyzing the factors that contribute to their challenges and the significance of developing tailored solutions to overcome them. The chapters encompass a wide range of topics, ranging from both the theoretical and practical aspects of ASR and translation for low-resource languages. The book discusses data augmentation techniques, transfer learning, and multilingual training approaches that leverage the power of existing linguistic resources to improve accuracy and performance. Additionally, it investigates the possibilities offered by unsupervised and semi-supervised learning, as well as the benefits of active learning and crowdsourcing in enriching the training data. Throughout the book, emphasis is placed on the importance of considering the cultural and linguistic context of low-resource languages, recognizing the unique nuances and intricacies that influence accurate ASR and translation. Furthermore, the book explores the potential impact of these technologies in various domains, such as healthcare, education, and commerce, empowering individuals and communities by breaking down language barriers. Audience The book targets researchers and professionals in the fields of natural language processing, computational linguistics, and speech technology. It will also be of interest to engineers, linguists, and individuals in industries and organizations working on cross-lingual communication, accessibility, and global connectivity.
Computational Intelligent Techniques welcomes a diverse audience to learn about technological innovation in the mechatronics system. This comprehensive resource is designed to empower readers with the knowledge and skills in the rapidly evolving world of mechatronics. Equipped with knowledge about mechatronic systems, and discussions on cutting-edge technologies in the latest innovations, this book is a learning gateway with tools to design, analyze, and implement mechatronic systems across various industries. Dive into 15 chapters covering the basics of mechatronics, computational intelligence approaches, simulation, and modeling concepts. This book will help research and development departments understand various branches of the engineering design process. Learn about challenges and opportunities in employing these techniques and how mechatronics proposes future research direction to optimize the system. Explore the components, challenges, and benefits of integrating AI in self-driving transportation systems. Lastly, read up on the latest mechatronics in altering current agriculture practices including productivity and sustainability.
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