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833 tulosta hakusanalla Ajith Fernando

Zamki samoligaturujące

Zamki samoligaturujące

Abhijith Ajith; Anshu Sahu; Raghu Ranjan Mds

Wydawnictwo Nasza Wiedza
2025
nidottu
"Zamki samoligaturujące" to termin używany w odniesieniu do zamk w wyposażonych w mechanizm blokujący, kt ry utrzymuje drut luku w szczelinie zamka. Zamki samoligaturujące zostaly wprowadzone do ortodoncji okolo 7 dekad temu jako zamki Russel lock edgewise firmy Stolzenberg. W ciągu ostatnich dw ch dekad nastąpil wzrost produkcji i wypuszczania aparat w samoligaturujących z aktywnymi lub pasywnymi trybami samoligaturowania, a stosowanie zamk w samoligaturujących zczasem wzros lo. W związku z tym książka zawiera pelny przegląd potrzeby opracowania zamk w samoligaturujących, ich perspektywy historycznej i ewolucji, klasyfikacji i rodzaj w zamk w oraz ich cech i wlaściwości.
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Vishnu kanda Pralayam

Vishnu kanda Pralayam

Sudha Ajith

Vayanappura Publications
2021
pokkari
Vishnu Kanda Pralayam by Sudha Ajith, published by Vayanappura Publications, stands as a beacon of knowledge and inspiration. With its insightful content and engaging narrative style, this book transcends genres, offering something valuable for every reader.
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Oru pravasiyude ormakal

Oru pravasiyude ormakal

V B Ajith Raj

Green Books Pvt Ltd
2020
pokkari
ഓര്]മ്മകളിലൂടെ ജീവിതത്തിന്]റെ കഥ പറയുകയാണ് ഗ്രന്ഥകാരന്]. എത്ര എഴുതിയാലും തീരാത്ത പുസ്തകത്താളുകളാണ് ജീവിതമെന്ന മഹാഗ്രന്ഥത്തിലുള്ളത് എന്ന വാക്യത്തെ ഓര്]മ്മിപ്പിക്കുന്ന എഴുത്ത്. സ്വന്തം തട്ടകത്തിന്]റെ കഥയില്]നിന്നും തുടങ്ങി അറ്യേന്] ജീവിതനാള്]വഴികളിലൂടെയുള്ള അനുസ്യൂതമായ യാത്ര. മനുഷ്യജീവിതത്തെ സംബന്ധിച്ച തത്ത്വചിന്തകളും ജീവിതസത്യങ്ങളും ഒരു പരിവ്രാജകന്]റെ മനസ്സോടെയാണ് ഓര്]മ്മക്കാലങ്ങളെ എഴുത്തുകാരന്] കണ്ടെടുക്കുന്നത്. നിസ്സംഗമമായ, നിര്]മ്മമമായ സ്മരണകളുടെ തുടര്]ച്ചകള്].
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Total Information Risk Management

Total Information Risk Management

Alexander Borek; Ajith Kumar Parlikad; Jela Webb; Philip Woodall

Morgan Kaufmann Publishers In
2013
nidottu
How well does your organization manage the risks associated with information quality? Managing information risk is becoming a top priority on the organizational agenda. The increasing sophistication of IT capabilities along with the constantly changing dynamics of global competition are forcing businesses to make use of their information more effectively. Information is becoming a core resource and asset for all organizations; however, it also brings many potential risks to an organization, from strategic, operational, financial, compliance, and environmental to societal. If you continue to struggle to understand and measure how information and its quality affects your business, this book is for you. This reference is in direct response to the new challenges that all managers have to face. Our process helps your organization to understand the "pain points" regarding poor data and information quality so you can concentrate on problems that have a high impact on core business objectives. This book provides you with all the fundamental concepts, guidelines and tools to ensure core business information is identified, protected and used effectively, and written in a language that is clear and easy to understand for non-technical managers.
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Introduction to Graphene

Introduction to Graphene

Challa Vijaya Kumar; Ajith Pattammattel

Elsevier Science Publishing Co Inc
2017
nidottu
Introduction to Graphene: Chemical and Biochemical Applications addresses a broad range of graphene research, including the prehistory and background of graphene, synthetic approaches, characterization techniques, composites/derivatives, inorganic graphene analogues, and applications of graphene. The book’s special emphasis on solution chemistry and graphene sets it apart from less practical titles in that its concepts are immediately implementable in the laboratories of chemists and biochemists. The book presents a variety of experimental approaches from the authors’ research laboratories and others around the world for graphene preparation in the solution phase, especially under aqueous conditions or in animal serum—the most practical kind of graphene for chemists and biochemists. The book is ideally suited for a broad range of readers, including advanced undergraduates, graduate research students and professionals in state-of-the-art research labs who want to use graphene to develop novel applications.
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Generative Artificial Intelligence and Ethics for Healthcare

Generative Artificial Intelligence and Ethics for Healthcare

Loveleen Gaur; Ajith Abraham

ELSEVIER SCIENCE PUBLISHING CO INC
2025
nidottu
Generative Artificial Intelligence and Ethics for Healthcare conducts a deep dive into the potential issues and challenges associated with Generative AI applications. The book begins with foundational concepts of generative AI and then explores ethical theories, including specific case studies in healthcare, and concludes with discussions on policy and future implications. Written for healthcare professionals, policymakers, academics and AI developers, by authors who have a thorough understanding of AI and machine learning in the healthcare.
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ESD in Silicon Integrated Circuits

ESD in Silicon Integrated Circuits

E. Ajith Amerasekera; Charvaka Duvvury

John Wiley Sons Inc
2002
sidottu
As high density circuits move deeper into submicron dimensions Electrostatic Discharge (ESD) effects become an increasing concern. This new edition of a classic reference presents a practical and systematic approach to ESD device physics, modelling and design techniques. The authors draw upon their wealth of industrial experience to provide a complete overview of ESD and its implications in the development of advanced integrated circuits. Fully revised to incorporate the latest industry achievements and featuring: *Design methods for a variety of technologies from 1 micron to the current sub-micron regimes, along with complete design approaches for MOS, BiCMOS and Power MOSFETs. *New sections on ESD design rules, process technology effects, layout approaches, package effects and circuit simulations. *Guidance on the implementation of circuit protection measures for a range of I/O configurations. *Detailed coverage of ESD simulation stress models. This unique reference provides the means to design protection circuits for a variety of applications and to diagnose and solve ESD problems in IC products. The coverage of state-of-the-art circuit design for ESD prevention will appeal to engineers and scientists working in the fields of IC and transistor design. Graduate students and researchers in device/circuit modeling and semiconductor reliability will appreciate this comprehensive coverage of ESD fundamentals.
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Failure Mechanisms in Semiconductor Devices

Failure Mechanisms in Semiconductor Devices

E. Ajith Amerasekera; Farid N. Najm

JOHN WILEY SONS INC
1997
sidottu
Failure Mechanisms in Semiconductor Devices Second Edition E. Ajith Amerasekera Texas Instruments Inc., Dallas, USA Farid N. Najm University of Illinois at Urbana-Champaign, USA Since the successful first edition of Failure Mechanisms in Semiconductor Devices, semiconductor technology has become increasingly important. The high complexity of today's integrated circuits has engendered a demand for greater component reliability. Reflecting the need for guaranteed performance in consumer applications, this thoroughly updated edition includes more detailed material on reliability modelling and prediction. The book analyses the main failure mechanisms in terms of cause, effects and prevention and explains the mathematics behind reliability analysis. The authors detail methodologies for the identification of failures and describe the approaches for building reliability into semiconductor devices. Their thorough yet accessible text covers the physics of failure mechanisms from the semiconductor die itself to the packaging and interconnections. Incorporating recent advances, this comprehensive survey of semiconductor reliability will be an asset to both engineers and graduate students in the field.
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Whole-Life Value-Based Decision-Making in Asset Management

Whole-Life Value-Based Decision-Making in Asset Management

Rengarajan Srinivasan; Ajith Kumar Parlikad

ICE Publishing
2016
sidottu
Whole-Life Value-Based Decision-Making in Asset Management is a comprehensive guide to improving the effectiveness of infrastructure asset management by determining the level of expenditure on infrastructure assets in order to maximise life-cycle value. Using clear and concise examples, this book provides detailed guidance for making whole-life asset management decisions based on value rather than cost. This best practice guide aims to aid asset management decision-makers to understand better the value generated by assets and the risks associated with this in order to make better informed decisions, and to also have a deeper understanding of the impact of their decision. Whole-Life Value-Based Decision-Making in Asset Management: delivers a systematic method to map the value generation processsupports stakeholders in making asset management decisionsprovides guidance to make a decision framework based on valueillustrates its applicability through industrial case studies such as seepage in London Underground tunnels. Part of a series of best practice guides written by experts at the Cambridge Centre for Smart Infrastructure and Construction (CSIC), this value-based tool addresses the challenges of managing current ageing infrastructure by determining the type, level and timing of investment required so that assets can meet current and future demand.
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Deep Learning

Deep Learning

Manel Martinez-Ramon; Meenu Ajith; Aswathy Rajendra Kurup

JOHN WILEY SONS INC
2024
sidottu
An engaging and accessible introduction to deep learning perfect for students and professionals In Deep Learning: A Practical Introduction, a team of distinguished researchers delivers a book complete with coverage of the theoretical and practical elements of deep learning. The book includes extensive examples, end-of-chapter exercises, homework, exam material, and a GitHub repository containing code and data for all provided examples. Combining contemporary deep learning theory with state-of-the-art tools, the chapters are structured to maximize accessibility for both beginning and intermediate students. The authors have included coverage of TensorFlow, Keras, and Pytorch. Readers will also find: Thorough introductions to deep learning and deep learning toolsComprehensive explorations of convolutional neural networks, including discussions of their elements, operation, training, and architecturesPractical discussions of recurrent neural networks and non-supervised approaches to deep learningFulsome treatments of generative adversarial networks as well as deep Bayesian neural networks Perfect for undergraduate and graduate students studying computer vision, computer science, artificial intelligence, and neural networks, Deep Learning: A Practical Introduction will also benefit practitioners and researchers in the fields of deep learning and machine learning in general.
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Metaheuristics for Data Clustering and Image Segmentation

Metaheuristics for Data Clustering and Image Segmentation

Meera Ramadas; Ajith Abraham

Springer Nature Switzerland AG
2019
sidottu
In this book, differential evolution and its modified variants are applied to the clustering of data and images. Metaheuristics have emerged as potential algorithms for dealing with complex optimization problems, which are otherwise difficult to solve using traditional methods. In this regard, differential evolution is considered to be a highly promising technique for optimization and is being used to solve various real-time problems. The book studies the algorithms in detail, tests them on a range of test images, and carefully analyzes their performance. Accordingly, it offers a valuable reference guide for all researchers, students and practitioners working in the fields of artificial intelligence, optimization and data analytics.
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Intelligent Web Data Management: Software Architectures and Emerging Technologies

Intelligent Web Data Management: Software Architectures and Emerging Technologies

Kun Ma; Ajith Abraham; Bo Yang; Runyuan Sun

Springer International Publishing AG
2016
sidottu
This book presents some of the emerging techniques and technologies used to handle Web data management. Authors present novel software architectures and emerging technologies and then validate using experimental data and real world applications. The contents of this book are focused on four popular thematic categories of intelligent Web data management: cloud computing, social networking, monitoring and literature management. The Volume will be a valuable reference to researchers, students and practitioners in the field of Web data management, cloud computing, social networks using advanced intelligence tools.
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Intelligent Web Data Management: Software Architectures and Emerging Technologies

Intelligent Web Data Management: Software Architectures and Emerging Technologies

Kun Ma; Ajith Abraham; Bo Yang; Runyuan Sun

Springer International Publishing AG
2018
nidottu
This book presents some of the emerging techniques and technologies used to handle Web data management. Authors present novel software architectures and emerging technologies and then validate using experimental data and real world applications. The contents of this book are focused on four popular thematic categories of intelligent Web data management: cloud computing, social networking, monitoring and literature management. The Volume will be a valuable reference to researchers, students and practitioners in the field of Web data management, cloud computing, social networks using advanced intelligence tools.
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Metaheuristic Clustering

Metaheuristic Clustering

Swagatam Das; Ajith Abraham; Amit Konar

Springer-Verlag Berlin and Heidelberg GmbH Co. K
2009
sidottu
Cluster analysis means the organization of an unlabeled collection of objects or patterns into separate groups based on their similarity. The task of computerized data clustering has been approached from diverse domains of knowledge like graph theory, multivariate analysis, neural networks, fuzzy set theory, and so on. Clustering is often described as an unsupervised learning method but most of the traditional algorithms require a prior specification of the number of clusters in the data for guiding the partitioning process, thus making it not completely unsupervised. Modern data mining tools that predict future trends and behaviors for allowing businesses to make proactive and knowledge-driven decisions, demand fast and fully automatic clustering of very large datasets with minimal or no user intervention. In this volume, we formulate clustering as an optimization problem, where the best partitioning of a given dataset is achieved by minimizing/maximizing one (single-objective clustering) or more (multi-objective clustering) objective functions. Using several real world applications, we illustrate the performance of several metaheuristics, particularly the Differential Evolution algorithm when applied to both single and multi-objective clustering problems, where the number of clusters is not known beforehand and must be determined on the run. This volume comprises of 7 chapters including an introductory chapter giving the fundamental definitions and the last Chapter provides some important research challenges. Academics, scientists as well as engineers engaged in research, development and application of optimization techniques and data mining will find the comprehensive coverage of this book invaluable.
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