Subrata Das – författare

Metal Oxides for Next Generation Optoelectronic, Photonic and Photovoltaic Applications focuses on the optoelectronic, photonic and photovoltaic behaviors of metallic oxides and closely related phenomena, from elementary principles to the latest findings. Each chapter includes a comprehensive evaluation of the synthesis and characterization of the most relevant metal oxides nanostructures for each application. In addition, there is a focus on methods to tune the materials' properties in order to improve devices performance.� This book is suitable for researchers and practitioners in academia and industry working in the disciplines of materials science and engineering, chemistry and physics.

Metal oxides are widely used in various optoelectronic devices, photonics, display devices, smart windows, sensors, optical components, energy-saving, and harvesting devices. Each application requires materials with their own specific properties. By controlling the particle size, shape, crystal structure, one can tune various properties of metal oxides viz. bandgap, absorption properties, conductivity, which alter the material for the specific application.

Includes discussions of synthesis and characterization of metal oxides materials for applications in next-generation optoelectronic, photonic and photovoltaic devices Emphasizes material design strategies of metal oxide nanostructures Focuses on the optoelectronic, photonic and photovoltaic behaviors of metallic oxides and closely related phenomena, from elementary principles to the latest findings

This book provides an overview of the types of fibres used in home textiles and the key issues relating to product development, industry standards, regulatory aspects, and evaluation systems. An understanding of these topics can assist the designer or manufacturer in developing product performance and quality in line with the value addition and to maintain the basic concept underlying in green consumerism. The books emphasis is on how to achieve the commercial success of the desired end product through knowledge of the key markets producing various home textiles, scope of development through sustainable and eco-friendly fibres, evaluation systems and above all safety aspects and environmental regulations.

Consumer awareness of the purchasing of safe and eco-friendly apparel products is on the rise. Knowledge of the restricted substances helps the industry navigate often complex product safety and chemical management requirements in order to address consumer preferences in the apparel supply chain. There is no doubt that risk analysis of the product at appropriate stage eliminates the possibilities of existence of restricted substances by adopting a right safety compliance policy. Thus, different safety aspects of apparel and its related requirements shall be covered in Product safety and restricted substances in apparel. Potential sources of restricted substances, chemicals of concern, and the scope of implementation for a proper testing program will also be discussed. Different standards to comply with legal regulations associated with the chemical management of restricted substances will be included in this book.

Learn How to Properly Use the Latest Analytics Approaches in Your OrganizationComputational Business Analytics presents tools and techniques for descriptive, predictive, and prescriptive analytics applicable across multiple domains. Through many examples and challenging case studies from a variety of fields, practitioners easily see the connections to their own problems and can then formulate their own solution strategies.The book first covers core descriptive and inferential statistics for analytics. The author then enhances numerical statistical techniques with symbolic artificial intelligence (AI) and machine learning (ML) techniques for richer predictive and prescriptive analytics. With a special emphasis on methods that handle time and textual data, the text: Enriches principal component and factor analyses with subspace methods, such as latent semantic analyses Combines regression analyses with probabilistic graphical modeling, such as Bayesian networks Extends autoregression and survival analysis techniques with the Kalman filter, hidden Markov models, and dynamic Bayesian networks Embeds decision trees within influence diagramsAugments nearest-neighbor and k-means clustering techniques with support vector machines and neural networks These approaches are not replacements of traditional statistics-based analytics; rather, in most cases, a generalized technique can be reduced to the underlying traditional base technique under very restrictive conditions. The book shows how these enriched techniques offer efficient solutions in areas, including customer segmentation, churn prediction, credit risk assessment, fraud detection, and advertising campaigns.