Covers advanced features of Perl, how the Perl interpreter works, and presents areas of modern computing technology such as networking, user interfaces, persistence, and code generation.
Build end-to-end AI solutions with IBM Cloud Pak for Data to operationalize AI on a secure platform based on cloud-native reliability, cost-effective multitenancy, and efficient resource management Key FeaturesExplore data virtualization by accessing data in real time without moving itUnify the data and AI experience with the integrated end-to-end platformExplore the AI life cycle and learn to build, experiment, and operationalize trusted AI at scaleBook Description Cloud Pak for Data is IBM's modern data and AI platform that includes strategic offerings from its data and AI portfolio delivered in a cloud-native fashion with the flexibility of deployment on any cloud. The platform offers a unique approach to addressing modern challenges with an integrated mix of proprietary, open-source, and third-party services. You'll begin by getting to grips with key concepts in modern data management and artificial intelligence (AI), reviewing real-life use cases, and developing an appreciation of the AI Ladder principle. Once you've gotten to grips with the basics, you will explore how Cloud Pak for Data helps in the elegant implementation of the AI Ladder practice to collect, organize, analyze, and infuse data and trustworthy AI across your business. As you advance, you'll discover the capabilities of the platform and extension services, including how they are packaged and priced. With the help of examples present throughout the book, you will gain a deep understanding of the platform, from its rich capabilities and technical architecture to its ecosystem and key go-to-market aspects. By the end of this IBM book, you'll be able to apply IBM Cloud Pak for Data's prescriptive practices and leverage its capabilities to build a trusted data foundation and accelerate AI adoption in your enterprise. What you will learnUnderstand the importance of digital transformations and the role of data and AI platformsGet to grips with data architecture and its relevance in driving AI adoption using IBM's AI LadderUnderstand Cloud Pak for Data, its value proposition, capabilities, and unique differentiatorsDelve into the pricing, packaging, key use cases, and competitors of Cloud Pak for DataUse the Cloud Pak for Data ecosystem with premium IBM and third-party servicesDiscover IBM's vibrant ecosystem of proprietary, open-source, and third-party offerings from over 35 ISVsWho this book is for This book is for data scientists, data stewards, developers, and data-focused business executives interested in learning about IBM's Cloud Pak for Data. Knowledge of technical concepts related to data science and familiarity with data analytics and AI initiatives at various levels of maturity are required to make the most of this book.
The growth of social media and data in various domains increased the interest in analyzing network algorithms. The networks are highly unstructured and exhibit poor locality, which has been a challenge for developing scalable parallel algorithms. The state-of-the-art network algorithms such as Prim's algorithm for Minimum Spanning Tree, Dijkstra's algorithm for Single Source Shortest Path, Google's Page Rank algorithm, and iSpan algorithm for detecting strongly connected components are designed and optimized for static networks. For the networks that change with time, i.e. the dynamic networks (such as social networks, biological networks, or temporal networks) the above-mentioned approaches can only be utilized if they are computed from scratch each time. Performing a computation from scratch for a significant amount of changes is not only computationally expensive, however, increases the memory footprint and the execution time. In the case of dynamic networks, developing scalable parallel algorithms is very challenging and there has been a very limited amount of research work that has been performed when compared to developing parallel scalable algorithms for static networks. To address the above challenges, this Ph. D. dissertation proposes a new high performance, scalable, portable, open-source software package, and an efficient network data structure to update the dynamic networks on the fly. This approach is different from the naive approach which is the re-computation from scratch and is scalable for random, small-world, scale-free, real-world, and synthetic networks. The software package currently is implemented on a shared memory system and GPU which updates network properties such as Connected Components (CC), Minimum Spanning Tree (MST), Single Source Shortest Path (SSSP), Page Rank (PR), and Strongly Connected Components(SCC). The key attributes of the software are faster insertions and deletions. Additionally, the software takes less time and memory for updating the networks when compared to the state of the art Galois(CPU), and Gunrock (GPU). The GPU implementation processes over 50 million updates for updating SSSP on a real-world network in under 300 seconds. This dissertation also provides a novel shared memory implementation of detecting, overlapping, and non-overlapping communities on static networks using Permanence. Detecting communities on large scale networks is a fundamental operation in various domains. Detecting correct communities is a challenging problem due to the limitations of the metric such as the state-of-the-art metric modularity since it suffers from the resolution limit. This dissertation is the first attempt to implement shared memory overlapping and non-overlapping communities using permanence. The key attributes of this implementation are the accuracy of the communities when compared to the ground truth and achieve speed up to 10× when compared to its sequential implementation. The dissertation concludes with a summarization of the contributions and their improvement in large-scale network analytics and a discussion about future work in this field.
Covers advanced features of Perl, how the Perl interpreter works, and presents areas of modern computing technology such as networking, user interfaces, persistence, and code generation.
Build end-to-end AI solutions with IBM Cloud Pak for Data to operationalize AI on a secure platform based on cloud-native reliability, cost-effective multitenancy, and efficient resource management Key FeaturesExplore data virtualization by accessing data in real time without moving itUnify the data and AI experience with the integrated end-to-end platformExplore the AI life cycle and learn to build, experiment, and operationalize trusted AI at scaleBook Description Cloud Pak for Data is IBM's modern data and AI platform that includes strategic offerings from its data and AI portfolio delivered in a cloud-native fashion with the flexibility of deployment on any cloud. The platform offers a unique approach to addressing modern challenges with an integrated mix of proprietary, open-source, and third-party services. You'll begin by getting to grips with key concepts in modern data management and artificial intelligence (AI), reviewing real-life use cases, and developing an appreciation of the AI Ladder principle. Once you've gotten to grips with the basics, you will explore how Cloud Pak for Data helps in the elegant implementation of the AI Ladder practice to collect, organize, analyze, and infuse data and trustworthy AI across your business. As you advance, you'll discover the capabilities of the platform and extension services, including how they are packaged and priced. With the help of examples present throughout the book, you will gain a deep understanding of the platform, from its rich capabilities and technical architecture to its ecosystem and key go-to-market aspects. By the end of this IBM book, you'll be able to apply IBM Cloud Pak for Data's prescriptive practices and leverage its capabilities to build a trusted data foundation and accelerate AI adoption in your enterprise. What you will learnUnderstand the importance of digital transformations and the role of data and AI platformsGet to grips with data architecture and its relevance in driving AI adoption using IBM's AI LadderUnderstand Cloud Pak for Data, its value proposition, capabilities, and unique differentiatorsDelve into the pricing, packaging, key use cases, and competitors of Cloud Pak for DataUse the Cloud Pak for Data ecosystem with premium IBM and third-party servicesDiscover IBM's vibrant ecosystem of proprietary, open-source, and third-party offerings from over 35 ISVsWho this book is for This book is for data scientists, data stewards, developers, and data-focused business executives interested in learning about IBM's Cloud Pak for Data. Knowledge of technical concepts related to data science and familiarity with data analytics and AI initiatives at various levels of maturity are required to make the most of this book.
Fully revised, new edition providing complete overview of surgical procedures for undergraduate students. The comprehensive text of nearly 1300 pages is enhanced by more than 3000 clinical photographs. Previous edition published in 2012.
SRB’s Clinical Methods in Surgery is the second edition of this highly illustrated, extensive guide to a broad range of surgical methods. This is an ideal book for medical students, focussing on various types of clinical examinations and covering many aspects of basic clinical surgery. The book is comprised of 5 sections; examination in general surgery, abdominal and related conditions, specialised areas, trauma and clinical methods in orthopaedics. These sections are further divided into 40 chapters covering the examination of specific parts of the body, traumatic injuries, diseases and orthopaedic injuries. The importance of history taking is emphasised along with techniques for interpreting clinical signs and symptoms in preparation for clinical and differential diagnosis. This second edition discusses common practice as well as newer innovations in clinical methods. Each chapter ends with a case relevant to the topic, presented with discussion on probable diagnosis, examination and investigations, to encourage a better understanding of each examination. Enhanced by over 1600 full colour images and illustrations, this expanded second edition of SRB’s Clinical Methods in Surgery also includes an interactive DVD, forming a complete and indispensable guide for postgraduate medical students, residents and fellows in surgery. Key Points Covers a broad range of clinical examinations in surgery Each chapter features a clinical case with discussion on diagnosis, examination and investigation 1607 full colour images and illustrations Includes an interactive DVD Fully revised edition First edition published 2010
Tantrasangraha, composed by the renowned Kerala astronomer Nīlakantha Somayājī (c.1444-1545 AD) ranks along with Āryabhatīya of Āryabhata and Siddhāntaśiromani of Bhāskarācārya as one of the major works which significantly influenced further work on astronomy in India. One of the distinguishing features is the introduction of a major revision of the traditional Indian planetary model. Nīlakantha arrived at a unified theory of planetary latitudes and a better formulation of the equation of centre for the interior planets (Mercury and Venus) than was previously available. In preparing the translation and explanatory notes, K. Ramasubramanian and M. S. Sriram have used authentic Sanskrit editions of Tantrasangraha by Surand Kunjan Pillai and K V Sarma. All verses have been translated into English, which have been supplemented with detailed explanations including all necessary mathematical relations, illustrative examples, figures and tables using modern mathematical notation.
Physical Design for Multichip Modules collects together a large body of important research work that has been conducted in recent years in the area of Multichip Module (MCM) design. The material consists of a survey of published results as well as original work by the authors. All major aspects of MCM physical design are discussed, including interconnect analysis and modeling, system partitioning and placement, and multilayer routing. For readers unfamiliar with MCMs, this book presents an overview of the different MCM technologies available today. An in-depth discussion of various recent approaches to interconnect analysis are also presented. Remaining chapters discuss the problems of partitioning, placement, and multilayer routing, with an emphasis on timing performance. For the first time, data from a wide range of sources is integrated to present a clear picture of a new, challenging and very important research area. For students and researchers looking for interesting research topics, open problems and suggestions for further research are clearly stated. Points of interest include : Clear overview of MCM technology and its relationship to physical design; Emphasis on performance-driven design, with a chapter devoted to recent techniques for rapid performance analysis and modeling of MCM interconnects; Different approaches to multilayer MCM routing collected together and compared for the first time; Explanation of algorithms is not overly mathematical, yet is detailed enough to give readers a clear understanding of the approach; Quantitative data provided wherever possible for comparison of different approaches; A comprehensive list of references to recent literature on MCMs provided.
India was an economic power to reckon with until its economic decline in the 18th century. What explains this long period of prosperity? The answer might lie in a framework of social and economic thought that lies buried in our ancient heritage, says Sriram Balasubramanian, of which Kautilya's Arthashastra is a major example. Kautilyanomics for Modern Times seeks to do three things-first, to provide a structure and a context for Kautilya's economic thoughts; second, to examine his work's relevance today; and third, to do it in a way that a lay reader can follow and grasp easily. Kautilya's thought is mainly articulated through the prism of dharmic capitalism and its components-some examples include his views on global economic outlook, state-market dynamics, and sustainable growth through observance of environmental, societal and familial responsibilities. Fathoming India's rich economic and philosophical heritage and making use of it, Balasubramanian argues, would prove to be a great asset in India's/the country's/the nation's ascent again.
Against the backdrop of consistent and continuous failure of the formal rural financial system to fulfill the goals and aspirations of government policy and poor masses, on the one hand, and the resilience of the traditional rural informal credit system, on the other, this study has applied the tools of institutional economics—especially those pertaining to information asymmetry and transaction costs to develop a conceptual framework to capture the broad features of the current rural credit scenario in India. Using a fairly large size data from 700 borrower households and 94 lending organizations across the country and over a period of three years, supplemented by case studies of several new generation credit organizations, it has evolved both demand and supply side perspective and action points to resolve the observed problems of rural credit—especially those pertaining to small farmers and other vulnerable (mostly landless) groups.
When we say ‘blue’, we imagine sorrow and sadness. As though blue is all negative. A clear sky is a symbol of hope, but isn’t it all blue? Then why is it, that when we see a little blue in ourselves, we start to lose hope? Maybe that blue is a part of you. When you are your happiest, the blue shines. When you are low, the blue glows. And if you’re lost in the dark, maybe you could just follow the soft glow of your blue to find your way back.
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