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Integrated Weed Management for Reduced Weed Infestations in Sustainable Cropping Systems
Weeds pose a major challenge to the sustainability of agricultural production systems, causing significant crop yield, economic and environmental losses. Chemical weed control tactics play a major role in modern weed management, maintaining the productivity of diverse cropping systems, reducing yield losses and facilitating conservation agriculture. However, the over-reliance on chemical weed control has led to shifts in weed communities in agroecosystems which are now becoming dominated by high competitors and herbicide resistance. Thus, weed scientists and practitioners are urged to develop and incorporate innovative and feasible integrated weed management (IWM) systems that can reduce weed infestations and environmental impacts.
Advances in Data Science and Information Engineering
The book presents the proceedings of two conferences: the 16th International Conference on Data Science (ICDATA 2020) and the 19th International Conference on Information & Knowledge Engineering (IKE 2020), which took place in Las Vegas, NV, USA, July 27-30, 2020. The conferences are part of the larger 2020 World Congress in Computer Science, Computer Engineering, & Applied Computing (CSCE'20), which features 20 major tracks. Papers cover all aspects of Data Science, Data Mining, Machine Learning, Artificial and Computational Intelligence (ICDATA) and Information Retrieval Systems, Information & Knowledge Engineering, Management and Cyber-Learning (IKE). Authors include academics, researchers, professionals, and students. Presents the proceedings of the 16th International Conference on Data Science (ICDATA 2020) and the 19th International Conference on Information & Knowledge Engineering (IKE 2020); Includes papers on topics from data mining to machine learning to informational retrieval systems; Authors include academics, researchers, professionals and students.
Proceedings of International Joint Conference on Computational Intelligence
This book gathers outstanding research papers presented at the International Joint Conference on Computational Intelligence (IJCCI 2018), which was held at Daffodil International University on 14–15 December 2018. The topics covered include: collective intelligence, soft computing, optimization, cloud computing, machine learning, intelligent software, robotics, data science, data security, big data analytics, and signal and natural language processing.
Machine Vision in Plant Leaf Disease Detection for Sustainable Agriculture
This book offers a comprehensive exploration of the intersection between advanced technology and agricultural sustainability. With a focus on leveraging machine vision techniques for the early detection and management of plant diseases, this book serves as a vital resource for researchers, practitioners, and stakeholders in the agricultural sector. The book begins by providing an overview of the challenges posed by plant diseases to global food security and agricultural sustainability. It highlights the limitations of traditional disease detection methods and underscores the need for innovative approaches that can offer timely and accurate diagnosis. Through a systematic examination of machine vision principles and methodologies, the book delves into the various stages of disease detection, from image acquisition to feature extraction and classification. Key concepts such as image preprocessing, feature selection, and machine learning algorithms are discussed in detail, with emphasis on their practical implementation in real-world scenarios. Moreover, the book explores the potential of machine vision to contribute to sustainable agriculture practices.
Arsenic Toxicity Remediation
Arsenic contamination in drinking water and crops is a major health issue in many countries worldwide, threatening the health of millions of people due to arsenic’s toxicity and carcinogenicity. This edited volume brings together a diverse group of environmental science, sustainability and health researchers to address the challenges posed by arsenic contamination. The book sheds light on this global environmental issue and proposes solutions to aquatic contamination through multi-disciplinary sustainable approaches and case studies from different parts of the world. The chapters contained here present the status quo in different parts of the world and provide essential information on arse...
Federated Learning in Health Care Technology
This book offers an in-depth exploration of federated learning (FL), a groundbreaking approach that facilitates collaborative data analysis while ensuring patient privacy and data security. As healthcare systems worldwide generate vast amounts of data, the challenge lies in harnessing this information without compromising confidentiality. Federated learning addresses this by allowing multiple institutions to collaborate on machine learning models without sharing sensitive data. In this context, the authors delve into the foundational principles of FL, illustrating how it enables the aggregation of decentralized data to improve diagnostic accuracy, develop personalized treatment plans, and en...
Hydroponics
Hydroponics-A standard methodology for plant biological researches provides useful information on the requirements and techniques needs to be considered in order to grow crops successfully in hydroponics. The main focuses of this book are preparation of hydroponic nutrient solution, use of this technique for studying biological aspects and environmental controls, and production of vegetables and ornamentals hydroponically. The first chapter of this book takes a general description of nutrient solution used for hydroponics followed by an outline of in vitro hydroponic culture system for vegetables. Detailed descriptions on use of hydroponics in the context of scientific research into plants r...
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