This book presents focussed information related to dynamic cropland transformation, agriculture development, climate change and environment with the application of advance geospatial technology. It describes research using geospatial tools and techniques to develop the models, design, and planning for agricultural land use optimization especially in south Asian countries. It covers agriculture production, water scarcity, industrial development, natural resources, environmental degradation, and sustainable development. Features: • Provides the adaptation strategy from a multidisciplinary resilience perspective • Addresses contemporary agricultural resilience to various climate change issues • Develops novel approaches for sustainability with environmentally sound practices • Discusses methodological and innovative approaches at local to global perspective • Reports research using geospatial tools and techniques to develop the models, design and planning for agricultural land use optimization The book is aimed at researchers, professionals and graduate students in GIS, Environmental Engineering, Geography, Agriculture, and Climate studies.

This book covers computational statistics-based approaches for Artificial Intelligence. The aim of this book is to provide comprehensive coverage of the fundamentals through the applications of the different kinds of mathematical modelling and statistical techniques and describing their applications in different Artificial Intelligence systems. The primary users of this book will include researchers, academicians, postgraduate students, and specialists in the areas of data science, mathematical modelling, and Artificial Intelligence. It will also serve as a valuable resource for many others in the fields of electrical, computer, and optical engineering. The key features of this book are: Presents development of several real-world problem applications and experimental research in the field of computational statistics and mathematical modelling for Artificial Intelligence Examines the evolution of fundamental research into industrialized research and the transformation of applied investigation into real-time applications Examines the applications involving analytical and statistical solutions, and provides foundational and advanced concepts for beginners and industry professionals Provides a dynamic perspective to the concept of computational statistics for analysis of data and applications in intelligent systems with an objective of ensuring sustainability issues for ease of different stakeholders in various fields Integrates recent methodologies and challenges by employing mathematical modeling and statistical techniques for Artificial Intelligence

Small Area Estimation and Microsimulation Modeling is the first practical handbook that comprehensively presents modern statistical SAE methods in the framework of ultramodern spatial microsimulation modeling while providing the novel approach of creating synthetic spatial microdata. Along with describing the necessary theories and their advantages and limitations, the authors illustrate the practical application of the techniques to a large number of substantive problems, including how to build up models, organize and link data, create synthetic microdata, conduct analyses, yield informative tables and graphs, and evaluate how the findings effectively support the decision making processes in government and non-government organizations. Features Covers both theoretical and applied aspects for real-world comparative research and regional statistics production Thoroughly explains how microsimulation modeling technology can be constructed using available datasets for reliable small area statistics Provides SAS codes that allow readers to utilize these latest technologies in their own work. This book is designed for advanced graduate students, academics, professionals and applied practitioners who are generally interested in small area estimation and/or microsimulation modeling and dealing with vital issues in social and behavioural sciences, applied economics and policy analysis, government and/or social statistics, health sciences, business, psychology, environmental and agriculture modeling, computational statistics and data simulation, spatial statistics, transport and urban planning, and geospatial modeling.

This book presents a comprehensive and detailed description of remediation techniques for metal-contaminated soils derived from both natural processes and anthropogenic activities. Using a methodical, step-by-step presentation, the book starts by overviewing the origin of toxicants and the correlated comparative extent of contamination to the environment. The legal provisions as proposed or applied in different countries are then discussed to explain the global regulatory situation regarding soil contamination and the extent of consequent concern. The core part of this publication describes the major techniques for in situ or ex situ treatment of the contaminated soil to meet the regulatory limits. Finally, risk evaluation is incorporated, giving special attention to possible impacts during or after implementation of the remediation strategies. The intrusion of metals in soils mostly occurs from various anthropogenic activities, e.g., agricultural practices, industrial activities, and municipal waste disposal. The volumes of metal-contaminated soil are becoming greater than before and are ever-increasing due to rapid urbanization, intensified industrialization, and/or population booms in certain parts of the world. Hence, the options previously proposed, such as isolation of the contaminated site or movement of the contaminated mass to a secure disposal site after excavation, are becoming unsuitable from the economic point of view, and instead, decontamination alternatives are preferred. This book will help readers such as scientists and regulators to understand the details of the remediation techniques available to deal with the soils contaminated by toxic metals.

In the quarter century since its emergence from military rule and integration into the global economy, Bangladesh's economy has achieved high growth, reduced aid dependence and made remarkable improvement in social indicators while at the same time it continues to suffer from increasing inequality. This book analyses these successes and failures.

A volume of essays by a number of economists to honour Nurul Islam, an Asian economist who made important contributions as an academic economist and political planner. The essays fall under three subject headings - international trade and aid, planning and rural development.

The introductory chapter briefly presents the fundamental topologies and operation of power inverters. The second chapter contains a description of wavelet basis functions and sampling theory with particular reference to the switching model of inverters. Chapter three outlines the connection between the non-uniform sampling theorem and wavelet functions to develop an ideal sampling-reconstruction process to operate an inverter for obtaining its optimal performances. The scale based linearly combined basis functions are developed in chapter four in order to successfully operate single phase wavelet modulated inverters. Chapter four also contains the development of the non-dyadic type multiresolution analysis, that are responsible for sampling and recontruction of three continuous time reference modulating signals for three phase inverters. The performances of single phase wavelet modulated inverters for static, dynamic and non-linear loads are presented in chapter five, while chapter six contains the simulation and experimental performances of three phase wavelet modulated voltage source inverters for different loads at various operating conditions. This book presents the latest technology in the advancing power electronics field.

This book presents innovative work by leading academics, researchers, and experts from industry which is useful for young researchers and students. This book includes selected papers from International Conference on Intelligent Cyber-Physical Systems (ICPS 2021), held at Indian Institute of Information Technology Kota (IIIT Kota), MNIT Jaipur Campus, Jaipur, India, during 16-18 April 2021. The book is a collection of the state-of-the art research work in the cutting-edge technologies related to the artificial intelligence and cyber physical systems.

This book presents innovative work by leading academics, researchers, and experts from industry which is useful for young researchers and students. This book includes selected papers from International Conference on Intelligent Cyber-Physical Systems (ICPS 2021), held at Indian Institute of Information Technology Kota (IIIT Kota), MNIT Jaipur Campus, Jaipur, India, during 16-18 April 2021. The book is a collection of the state-of-the art research work in the cutting-edge technologies related to the artificial intelligence and cyber physical systems.

The present investigation was undertaken to study the bioecology and development of preventive and self sustaining methods of pest control by various cultural manipulations against two major insect pests of mango, mango leaf hopper Amritodus atkinsoni (Homoptera: Cicadellidae) and shoot gall psylla Apsylla cistellata (Buckton) (Homoptera: Psyllidae). Experiments were conducted at the Horticultural Research Centre, Patharchatta with a view to find out the effect of orientation and light intensity on floral biology, pollinators and hoppers, population dynamics of hoppers in relation to weather parameters, loss assessment by hoppers, effect of plant density and impact of different agronomic practices on hoppers, role of pest, diseases and flower hormones on fruit harvest, and lastly, effect of insecticides and biopesticides on shoot gall psylla.

Arsenic, a deadly toxic element, is widely distributed in freshwater systems with an average concentration of approximately 1.7 g/L, predominantly as inorganic forms, from natural and anthropogenic sources. Phytoremediation, a plant-based eco-friendly technology, is receiving increasing attention, and aquatic plants can be used for the remediation of arsenic-contaminated water. Water hyacinth (Eichhornia crassipes), duckweeds (Lemna spp., Spirodela polyrhiza), water fern (Azolla spp.), hydrilla (Hydrilla verticillata) and watercress (Lepidium sativum) have been studied to assess their potential for arsenic phytoremediation. Arsenic is mainly taken up by aquatic plants through the phosphate uptake pathway, however, physico-chemical adsorption of arsenate on aquatic plant surfaces also contributes significantly in arsenic accumulation in the plants. Phosphate and iron influence arsenate uptake, while these chemicals do not influence arsenite, MMAA and DMAA uptake in aquatic plants. From my studies, I proposed that aquatic floating macrophytes such as duckweed (Spirodella polyrhiza) and water fern (Azolla pinnata) can be used for the remediation of arsenic from freshwater."

Micro - Finance (MF) has proved to be an effective tool towards poverty alleviation and economic empowerment of women in a number of Third World countries, Bangladesh Brazil are the best examples of this claim. India with more or less the same realties as many other countries, also recognized the potential of MF for poverty alleviation and adopted Micro - finance to achieve the similar results of reducing poverty and inequality in early 80's. Though MF in India achieved substantial growth, however, this industry is facing a number of challenges today and calls for some good and context specific wise policies and rigorous implementation. This can be effective in making MF work towards fulfilling its promises of making contribution to alleviating poverty and empowering women by ensuring outreach of MF services the poorest of the poor. The monograph is an endeavour to analyze multiple challenges prevailing in the industry and draw up on policy prescriptions to cope these challenges.

In real life often we need to make inferences about the behaviour of the unobserved responses for a model based on the observed responses from the model. Regression models with normal errors are commonly considered in prediction problems. However, when the underlying distributions have heavier tails, the normal errors assumption fails to allow sufficient probability in the tail areas to make allowance for any extreme value or outliers. As well, it cannot deal with the uncorrelated but not independent observations which are common in time series and econometric studies. In such situations, the Student-t errors assumption is appropriate. Traditionally, a number of statistical methods such as the classical, structural distribution and structural relations approaches can lead to prediction distributions, the Bayesian approach is more sound in statistical theory. This book, therefore, deals with the derivation problems of prediction distributions for some widely used linear models having Student-t errors under the Bayesian approach. Results reveal that our models are robust and the Bayesian approach is competitive with traditional methods. In perturbation analysis, process control, optimization, classification, discordancy testing, interim analysis, speech recognition, online environmental learning and sampling curtailment studies predictive inferences are successfully used.